Sample records for extreme daily precipitation
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Combining Radar and Daily Precipitation Data to Estimate Meaningful Sub-daily Precipitation Extremes
Pegram, G. G. S.; Bardossy, A.
2016-12-01
Short duration extreme rainfalls are important for design. The purpose of this presentation is not to improve the day by day estimation of precipitation, but to obtain reasonable statistics for the subdaily extremes at gauge locations. We are interested specifically in daily and sub-daily extreme values of precipitation at gauge locations. We do not employ the common procedure of using time series of control station to determine the missing data values in a target. We are interested in individual rare events, not sequences. The idea is to use radar to disaggregate daily totals to sub-daily amounts. In South Arica, an S-band radar operated relatively continuously at Bethlehem from 1998 to 2003, whose scan at 1.5 km above ground [CAPPI] overlapped a dense (10 km spacing) set of 45 pluviometers recording in the same 6-year period. Using this valuable set of data, we are only interested in rare extremes, therefore small to medium values of rainfall depth were neglected, leaving 12 days of ranked daily maxima in each set per year, whose sum typically comprised about 50% of each annual rainfall total. The method presented here uses radar for disaggregating daily gauge totals in subdaily intervals down to 15 minutes in order to extract the maxima of sub-hourly through to daily rainfall at each of 37 selected radar pixels [1 km square in plan] which contained one of the 45 pluviometers not masked out by the radar foot-print. The pluviometer data were aggregated to daily totals, to act as if they were daily read gauges; their only other task was to help in the cross-validation exercise. The extrema were obtained as quantiles by ordering the 12 daily maxima of each interval per year. The unusual and novel goal was not to obtain the reproduction of the precipitation matching in space and time, but to obtain frequency distributions of the gauge and radar extremes, by matching their ranks, which we found to be stable and meaningful in cross-validation tests. We provide and
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Stochastic generation of multi-site daily precipitation focusing on extreme events
Directory of Open Access Journals (Sweden)
G. Evin
2018-01-01
Full Text Available Many multi-site stochastic models have been proposed for the generation of daily precipitation, but they generally focus on the reproduction of low to high precipitation amounts at the stations concerned. This paper proposes significant extensions to the multi-site daily precipitation model introduced by Wilks, with the aim of reproducing the statistical features of extremely rare events (in terms of frequency and magnitude at different temporal and spatial scales. In particular, the first extended version integrates heavy-tailed distributions, spatial tail dependence, and temporal dependence in order to obtain a robust and appropriate representation of the most extreme precipitation fields. A second version enhances the first version using a disaggregation method. The performance of these models is compared at different temporal and spatial scales on a large region covering approximately half of Switzerland. While daily extremes are adequately reproduced at the stations by all models, including the benchmark Wilks version, extreme precipitation amounts at larger temporal scales (e.g., 3-day amounts are clearly underestimated when temporal dependence is ignored.
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Decadal changes in extreme daily precipitation in Greece
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P. T. Nastos
2008-04-01
Full Text Available The changes in daily precipitation totals in Greece, during the 45-year period (1957–2001 are examined. The precipitation datasets concern daily totals recorded at 21 surface meteorological stations of the Hellenic National Meteorological Service, which are uniformly distributed over the Greek region. First and foremost, the application of Factor Analysis resulted in grouping the meteorological stations with similar variation in time. The main sub groups represent the northern, southern, western, eastern and central regions of Greece with common precipitation characteristics. For representative stations of the extracted sub groups we estimated the trends and the time variability for the number of days (% exceeding 30 mm (equal to the 95% percentile of daily precipitation for eastern and western regions and equal to the 97.5% percentile for the rest of the country and 50 mm which is the threshold for very extreme and rare events. Furthermore, the scale and shape parameters of the well fitted gamma distribution to the daily precipitation data with respect to the whole examined period and to the 10-year sub periods reveal the changes in the intensity of the precipitation.
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Changes and Attribution of Extreme Precipitation in Climate Models: Subdaily and Daily Scales
Zhang, W.; Villarini, G.; Scoccimarro, E.; Vecchi, G. A.
2017-12-01
Extreme precipitation events are responsible for numerous hazards, including flooding, soil erosion, and landslides. Because of their significant socio-economic impacts, the attribution and projection of these events is of crucial importance to improve our response, mitigation and adaptation strategies. Here we present results from our ongoing work.In terms of attribution, we use idealized experiments [pre-industrial control experiment (PI) and 1% per year increase (1%CO2) in atmospheric CO2] from ten general circulation models produced under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the fraction of attributable risk to examine the CO2 effects on extreme precipitation at the sub-daily and daily scales. We find that the increased CO2 concentration substantially increases the odds of the occurrence of sub-daily precipitation extremes compared to the daily scale in most areas of the world, with the exception of some regions in the sub-tropics, likely in relation to the subsidence of the Hadley Cell. These results point to the large role that atmospheric CO2 plays in extreme precipitation under an idealized framework. Furthermore, we investigate the changes in extreme precipitation events with the Community Earth System Model (CESM) climate experiments using the scenarios consistent with the 1.5°C and 2°C temperature targets. We find that the frequency of annual extreme precipitation at a global scale increases in both 1.5°C and 2°C scenarios until around 2070, after which the magnitudes of the trend become much weaker or even negative. Overall, the frequency of global annual extreme precipitation is similar between 1.5°C and 2°C for the period 2006-2035, and the changes in extreme precipitation in individual seasons are consistent with those for the entire year. The frequency of extreme precipitation in the 2°C experiments is higher than for the 1.5°C experiment after the late 2030s, particularly for the period 2071-2100.
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Seasonal Cycle in German Daily Precipitation Extremes
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Madlen Fischer
2018-01-01
Full Text Available The seasonal cycle of extreme precipitation in Germany is investigated by fitting statistical models to monthly maxima of daily precipitation sums for 2,865 rain gauges. The basis is a non-stationary generalized extreme value (GEV distribution variation of location and scale parameters. The negative log-likelihood serves as the forecast error for a cross validation to select adequate orders of the harmonic functions for each station. For nearly all gauges considered, the seasonal model is more appropriate to estimate return levels on a monthly scale than a stationary GEV used for individual months. The 100-year return-levels show the influence of cyclones in the western, and convective events in the eastern part of Germany. In addition to resolving the seasonality, we use a simulation study to show that annual return levels can be estimated more precisely from a monthly-resolved seasonal model than from a stationary model based on annual maxima.
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Contractor, S.; Donat, M.; Alexander, L. V.
2017-12-01
Reliable observations of precipitation are necessary to determine past changes in precipitation and validate models, allowing for reliable future projections. Existing gauge based gridded datasets of daily precipitation and satellite based observations contain artefacts and have a short length of record, making them unsuitable to analyse precipitation extremes. The largest limiting factor for the gauge based datasets is a dense and reliable station network. Currently, there are two major data archives of global in situ daily rainfall data, first is Global Historical Station Network (GHCN-Daily) hosted by National Oceanic and Atmospheric Administration (NOAA) and the other by Global Precipitation Climatology Centre (GPCC) part of the Deutsche Wetterdienst (DWD). We combine the two data archives and use automated quality control techniques to create a reliable long term network of raw station data, which we then interpolate using block kriging to create a global gridded dataset of daily precipitation going back to 1950. We compare our interpolated dataset with existing global gridded data of daily precipitation: NOAA Climate Prediction Centre (CPC) Global V1.0 and GPCC Full Data Daily Version 1.0, as well as various regional datasets. We find that our raw station density is much higher than other datasets. To avoid artefacts due to station network variability, we provide multiple versions of our dataset based on various completeness criteria, as well as provide the standard deviation, kriging error and number of stations for each grid cell and timestep to encourage responsible use of our dataset. Despite our efforts to increase the raw data density, the in situ station network remains sparse in India after the 1960s and in Africa throughout the timespan of the dataset. Our dataset would allow for more reliable global analyses of rainfall including its extremes and pave the way for better global precipitation observations with lower and more transparent uncertainties.
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Extreme daily precipitation in Western Europe with climate change at appropriate spatial scales
Booij, Martijn J.
2002-01-01
Extreme daily precipitation for the current and changed climate at appropriate spatial scales is assessed. This is done in the context of the impact of climate change on flooding in the river Meuse in Western Europe. The objective is achieved by determining and comparing extreme precipitation from
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Mahoney, Kelly M.; Ralph, F. Martin; Walter, Klaus; Doesken, Nolan; Dettinger, Michael; Gottas, Daniel; Coleman, Timothy; White, Allen
2015-01-01
The climatology of Colorado’s historical extreme precipitation events shows a remarkable degree of seasonal and regional variability. Analysis of the largest historical daily precipitation totals at COOP stations across Colorado by season indicates that the largest recorded daily precipitation totals have ranged from less than 60 mm day−1 in some areas to more than 250 mm day−1 in others. East of the Continental Divide, winter events are rarely among the top 10 events at a given site, but spring events dominate in and near the foothills; summer events are most common across the lower-elevation eastern plains, while fall events are most typical for the lower elevations west of the Divide. The seasonal signal in Colorado’s central mountains is complex; high-elevation intense precipitation events have occurred in all months of the year, including summer, when precipitation is more likely to be liquid (as opposed to snow), which poses more of an instantaneous flood risk. Notably, the historic Colorado Front Range daily rainfall totals that contributed to the damaging floods in September 2013 occurred outside of that region’s typical season for most extreme precipitation (spring–summer). That event and many others highlight the fact that extreme precipitation in Colorado has occurred historically during all seasons and at all elevations, emphasizing a year-round statewide risk.
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Beranová, Romana; Kyselý, Jan; Hanel, Martin
2018-04-01
The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model version 3 (HadRM3) and Rossby Centre Regional Atmospheric Model version 4 (RCA4) regional climate models (RCMs) driven by reanalyses and examines diurnal cycles of hourly precipitation and their dependence on intensity and surface temperature. The observed warm-season (May-September) maxima of short-duration (1, 2 and 3 h) amounts show one diurnal peak in the afternoon, which is simulated reasonably well by RCA4, although the peak occurs too early in the model. HadRM3 provides an unrealistic diurnal cycle with a nighttime peak and an afternoon minimum coinciding with the observed maximum for all three ensemble members, which suggests that convection is not captured realistically. Distorted relationships of the diurnal cycles of hourly precipitation to daily maximum temperature in HadRM3 further evidence that underlying physical mechanisms are misrepresented in this RCM. Goodness-of-fit tests indicate that generalised extreme value distribution is an applicable model for both observed and RCM-simulated precipitation maxima. However, the RCMs are not able to capture the range of the shape parameter estimates of distributions of short-duration precipitation maxima realistically, leading to either too many (nearly all for HadRM3) or too few (RCA4) grid boxes in which the shape parameter corresponds to a heavy tail. This means that the distributions of maxima of sub-daily amounts are distorted in the RCM-simulated data and do not match reality well. Therefore, projected changes of sub-daily precipitation extremes in climate change scenarios based on RCMs not resolving convection need to be interpreted with caution.
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Investigating NARCCAP Precipitation Extremes via Bivariate Extreme Value Theory (Invited)
Weller, G. B.; Cooley, D. S.; Sain, S. R.; Bukovsky, M. S.; Mearns, L. O.
2013-12-01
We introduce methodology from statistical extreme value theory to examine the ability of reanalysis-drive regional climate models to simulate past daily precipitation extremes. Going beyond a comparison of summary statistics such as 20-year return values, we study whether the most extreme precipitation events produced by climate model simulations exhibit correspondence to the most extreme events seen in observational records. The extent of this correspondence is formulated via the statistical concept of tail dependence. We examine several case studies of extreme precipitation events simulated by the six models of the North American Regional Climate Change Assessment Program (NARCCAP) driven by NCEP reanalysis. It is found that the NARCCAP models generally reproduce daily winter precipitation extremes along the Pacific coast quite well; in contrast, simulation of past daily summer precipitation extremes in a central US region is poor. Some differences in the strength of extremal correspondence are seen in the central region between models which employ spectral nudging and those which do not. We demonstrate how these techniques may be used to draw a link between extreme precipitation events and large-scale atmospheric drivers, as well as to downscale extreme precipitation simulated by a future run of a regional climate model. Specifically, we examine potential future changes in the nature of extreme precipitation along the Pacific coast produced by the pineapple express (PE) phenomenon. A link between extreme precipitation events and a "PE Index" derived from North Pacific sea-surface pressure fields is found. This link is used to study PE-influenced extreme precipitation produced by a future-scenario climate model run.
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Directory of Open Access Journals (Sweden)
R. Serrano-Notivoli
2017-09-01
Full Text Available A high-resolution daily gridded precipitation dataset was built from raw data of 12 858 observatories covering a period from 1950 to 2012 in peninsular Spain and 1971 to 2012 in Balearic and Canary islands. The original data were quality-controlled and gaps were filled on each day and location independently. Using the serially complete dataset, a grid with a 5 × 5 km spatial resolution was constructed by estimating daily precipitation amounts and their corresponding uncertainty at each grid node. Daily precipitation estimations were compared to original observations to assess the quality of the gridded dataset. Four daily precipitation indices were computed to characterise the spatial distribution of daily precipitation and nine extreme precipitation indices were used to describe the frequency and intensity of extreme precipitation events. The Mediterranean coast and the Central Range showed the highest frequency and intensity of extreme events, while the number of wet days and dry and wet spells followed a north-west to south-east gradient in peninsular Spain, from high to low values in the number of wet days and wet spells and reverse in dry spells. The use of the total available data in Spain, the independent estimation of precipitation for each day and the high spatial resolution of the grid allowed for a precise spatial and temporal assessment of daily precipitation that is difficult to achieve when using other methods, pre-selected long-term stations or global gridded datasets. SPREAD dataset is publicly available at https://doi.org/10.20350/digitalCSIC/7393.
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Trends and variability of extreme precipitation events are important for water-related disaster prevention and mitigation as well as water resource management. Based on daily precipitation dataset from 143 meteorological stations in the Yangtze River Basin (YRB), a suite of precipitation indices rec...
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Two case studies on NARCCAP precipitation extremes
Weller, Grant B.; Cooley, Daniel; Sain, Stephan R.; Bukovsky, Melissa S.; Mearns, Linda O.
2013-09-01
We introduce novel methodology to examine the ability of six regional climate models (RCMs) in the North American Regional Climate Change Assessment Program (NARCCAP) ensemble to simulate past extreme precipitation events seen in the observational record over two different regions and seasons. Our primary objective is to examine the strength of daily correspondence of extreme precipitation events between observations and the output of both the RCMs and the driving reanalysis product. To explore this correspondence, we employ methods from multivariate extreme value theory. These methods require that we account for marginal behavior, and we first model and compare climatological quantities which describe tail behavior of daily precipitation for both the observations and model output before turning attention to quantifying the correspondence of the extreme events. Daily precipitation in a West Coast region of North America is analyzed in two seasons, and it is found that the simulated extreme events from the reanalysis-driven NARCCAP models exhibit strong daily correspondence to extreme events in the observational record. Precipitation over a central region of the United States is examined, and we find some daily correspondence between winter extremes simulated by reanalysis-driven NARCCAP models and those seen in observations, but no such correspondence is found for summer extremes. Furthermore, we find greater discrepancies among the NARCCAP models in the tail characteristics of the distribution of daily summer precipitation over this region than seen in precipitation over the West Coast region. We find that the models which employ spectral nudging exhibit stronger tail dependence to observations in the central region.
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Arctic daily temperature and precipitation extremes: Observed and simulated physical behavior
Glisan, Justin Michael
Simulations using a six-member ensemble of Pan-Arctic WRF (PAW) were produced on two Arctic domains with 50-km resolution to analyze precipitation and temperature extremes for various periods. The first study used a domain developed for the Regional Arctic Climate Model (RACM). Initial simulations revealed deep atmospheric circulation biases over the northern Pacific Ocean, manifested in pressure, geopotential height, and temperature fields. Possible remedies to correct these large biases, such as modifying the physical domain or using different initial/boundary conditions, were unsuccessful. Spectral (interior) nudging was introduced as a way of constraining the model to be more consistent with observed behavior. However, such control over numerical model behavior raises concerns over how much nudging may affect unforced variability and extremes. Strong nudging may reduce or filter out extreme events, since the nudging pushes the model toward a relatively smooth, large-scale state. The question then becomes---what is the minimum spectral nudging needed to correct biases while not limiting the simulation of extreme events? To determine this, we use varying degrees of spectral nudging, using WRF's standard nudging as a reference point during January and July 2007. Results suggest that there is a marked lack of sensitivity to varying degrees of nudging. Moreover, given that nudging is an artificial forcing applied in the model, an important outcome of this work is that nudging strength apparently can be considerably smaller than WRF's standard strength and still produce reliable simulations. In the remaining studies, we used the same PAW setup to analyze daily precipitation extremes simulated over a 19-year period on the CORDEX Arctic domain for winter and summer. We defined these seasons as the three-month period leading up to and including the climatological sea ice maximum and minimum, respectively. Analysis focused on four North American regions defined using
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Risk assessment of precipitation extremes in northern Xinjiang, China
Yang, Jun; Pei, Ying; Zhang, Yanwei; Ge, Quansheng
2018-05-01
This study was conducted using daily precipitation records gathered at 37 meteorological stations in northern Xinjiang, China, from 1961 to 2010. We used the extreme value theory model, generalized extreme value (GEV) and generalized Pareto distribution (GPD), statistical distribution function to fit outputs of precipitation extremes with different return periods to estimate risks of precipitation extremes and diagnose aridity-humidity environmental variation and corresponding spatial patterns in northern Xinjiang. Spatiotemporal patterns of daily maximum precipitation showed that aridity-humidity conditions of northern Xinjiang could be well represented by the return periods of the precipitation data. Indices of daily maximum precipitation were effective in the prediction of floods in the study area. By analyzing future projections of daily maximum precipitation (2, 5, 10, 30, 50, and 100 years), we conclude that the flood risk will gradually increase in northern Xinjiang. GEV extreme value modeling yielded the best results, proving to be extremely valuable. Through example analysis for extreme precipitation models, the GEV statistical model was superior in terms of favorable analog extreme precipitation. The GPD model calculation results reflect annual precipitation. For most of the estimated sites' 2 and 5-year T for precipitation levels, GPD results were slightly greater than GEV results. The study found that extreme precipitation reaching a certain limit value level will cause a flood disaster. Therefore, predicting future extreme precipitation may aid warnings of flood disaster. A suitable policy concerning effective water resource management is thus urgently required.
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The Contribution of Extreme Precipitation to the Total Precipitation in China
Institute of Scientific and Technical Information of China (English)
SUN Jian-Qi
2012-01-01
Using daily precipitation data from weather stations in China, the variations in the contribution of extreme precipitation to the total precipitation are analyzed. It is found that extreme precipitation accounts for approximately one third of the total precipitation based on the overall mean for China. Over the past half century, extreme precipitation has played a dominant role in the year-to-year variability of the total precipitation. On the decadal time scale, the extreme precipitation makes different contributions to the wetting and drying regions of China. The wetting trends of particular regions are mainly attributed to increases in extreme precipitation; in contrast, the drying trends of other regions are mainly due to decreases in non-extreme precipitation.
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Toll, Velle; Post, Piia
2018-04-01
Daily 2-m temperature and precipitation extremes in the Baltic Sea region for the time period of 1965-2005 is studied based on data from the BaltAn65 + high resolution atmospheric reanalysis. Moreover, the ability of regional reanalysis to capture extremes is analysed by comparing the reanalysis data to gridded observations. The shortcomings in the simulation of the minimum temperatures over the northern part of the region and in the simulation of the extreme precipitation over the Scandinavian mountains in the BaltAn65+ reanalysis data are detected and analysed. Temporal trends in the temperature and precipitation extremes in the Baltic Sea region, with the largest increases in temperature and precipitation in winter, are detected based on both gridded observations and the BaltAn65+ reanalysis data. However, the reanalysis is not able to capture all of the regional trends in the extremes in the observations due to the shortcomings in the simulation of the extremes.
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Probability Distribution and Projected Trends of Daily Precipitation in China
Institute of Scientific and Technical Information of China (English)
CAO; Li-Ge; ZHONG; Jun; SU; Bu-Da; ZHAI; Jian-Qing; Macro; GEMMER
2013-01-01
Based on observed daily precipitation data of 540 stations and 3,839 gridded data from the high-resolution regional climate model COSMO-Climate Limited-area Modeling(CCLM)for 1961–2000,the simulation ability of CCLM on daily precipitation in China is examined,and the variation of daily precipitation distribution pattern is revealed.By applying the probability distribution and extreme value theory to the projected daily precipitation(2011–2050)under SRES A1B scenario with CCLM,trends of daily precipitation series and daily precipitation extremes are analyzed.Results show that except for the western Qinghai-Tibetan Plateau and South China,distribution patterns of the kurtosis and skewness calculated from the simulated and observed series are consistent with each other;their spatial correlation coefcients are above 0.75.The CCLM can well capture the distribution characteristics of daily precipitation over China.It is projected that in some parts of the Jianghuai region,central-eastern Northeast China and Inner Mongolia,the kurtosis and skewness will increase significantly,and precipitation extremes will increase during 2011–2050.The projected increase of maximum daily rainfall and longest non-precipitation period during flood season in the aforementioned regions,also show increasing trends of droughts and floods in the next 40 years.
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Ramos, Alexandre M.; Trigo, Ricardo M.; Liberato, Margarida LR
2014-05-01
Extreme precipitation events in the Iberian Peninsula during the extended winter months have major socio-economic impacts such as floods, landslides, extensive property damage and life losses. These events are usually associated with low pressure systems with Atlantic origin, although some extreme events in summer/autumn months can be linked to Mediterranean low pressure systems. Quite often these events are evaluated on a casuistic base and making use of data from relatively few stations. An objective method for ranking daily precipitation events is presented here based on the extensive use of the most comprehensive database of daily gridded precipitation available for the Iberian Peninsula (IB02) and spanning from 1950 to 2008, with a resolution of 0.2° (approximately 16 x 22 km at latitude 40°N), for a total of 1673 pixels. This database is based on a dense network of rain gauges, combining two national data sets, 'Spain02' for peninsular Spain and Balearic islands, and 'PT02' for mainland Portugal, with a total of more than two thousand stations over Spain and four hundred stations over Portugal, all quality-controlled and homogenized. Through this objective method for ranking daily precipitation events the magnitude of an event is obtained after considering the area affected as well as its intensity in every grid point and taking into account the daily precipitation normalised departure from climatology. Different precipitation rankings are presented considering the entire Iberian Peninsula, Portugal and also the six largest river basins in the Iberian Peninsula. Atmospheric Rivers (AR) are the water vapour (WV) core section of the broader warm conveyor belt occurring over the oceans along the warm sector of extra-tropical cyclones. They are usually W-E oriented steered by pre-frontal low level jets along the trailing cold front and subsequently feed the precipitation in the extra-tropical cyclones. They are relatively narrow regions of concentrated WV
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Chen, Ajiao; He, Xinguang; Guan, Huade; Cai, Yi
2018-04-01
In this study, the trends and periodicity in climate extremes are examined in Hunan Province over the period 1960-2013 on the basis of 27 extreme climate indices calculated from daily temperature and precipitation records at 89 meteorological stations. The results show that in the whole province, temperature extremes exhibit a warming trend with more than 50% stations being statistically significant for 7 out of 16 temperature indices, and the nighttime temperature increases faster than the daytime temperature at the annual scale. The changes in most extreme temperature indices show strongly coherent spatial patterns. Moreover, the change rates of almost all temperature indices in north Hunan are greater than those of other regions. However, the statistically significant changes in indices of extreme precipitation are observed at fewer stations than in extreme temperature indices, forming less spatially coherent patterns. Positive trends in indices of extreme precipitation show that the amount and intensity of extreme precipitation events are generally increasing in both annual and seasonal scales, whereas the significant downward trend in consecutive wet days indicates that the precipitation becomes more even over the study period. Analysis of changes in probability distributions of extreme indices for 1960-1986 and 1987-2013 also demonstrates a remarkable shift toward warmer condition and increasing tendency in the amount and intensity of extreme precipitation during the past decades. The variations in extreme climate indices exhibit inconstant frequencies in the wavelet power spectrum. Among the 16 temperature indices, 2 of them show significant 1-year periodic oscillation and 7 of them exhibit significant 4-year cycle during some certain periods. However, significant periodic oscillations can be found in all of the precipitation indices. Wet-day precipitation and three absolute precipitation indices show significant 1-year cycle and other seven provide
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How extreme is extreme hourly precipitation?
Papalexiou, Simon Michael; Dialynas, Yannis G.; Pappas, Christoforos
2016-04-01
The importance of accurate representation of precipitation at fine time scales (e.g., hourly), directly associated with flash flood events, is crucial in hydrological design and prediction. The upper part of a probability distribution, known as the distribution tail, determines the behavior of extreme events. In general, and loosely speaking, tails can be categorized in two families: the subexponential and the hyperexponential family, with the first generating more intense and more frequent extremes compared to the latter. In past studies, the focus has been mainly on daily precipitation, with the Gamma distribution being the most popular model. Here, we investigate the behaviour of tails of hourly precipitation by comparing the upper part of empirical distributions of thousands of records with three general types of tails corresponding to the Pareto, Lognormal, and Weibull distributions. Specifically, we use thousands of hourly rainfall records from all over the USA. The analysis indicates that heavier-tailed distributions describe better the observed hourly rainfall extremes in comparison to lighter tails. Traditional representations of the marginal distribution of hourly rainfall may significantly deviate from observed behaviours of extremes, with direct implications on hydroclimatic variables modelling and engineering design.
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Thiombiano, Alida N.; El Adlouni, Salaheddine; St-Hilaire, André; Ouarda, Taha B. M. J.; El-Jabi, Nassir
2017-07-01
In this paper, a statistical inference of Southeastern Canada extreme daily precipitation amounts is proposed using a classical nonstationary peaks-over-threshold model. Indeed, the generalized Pareto distribution (GPD) is fitted to excess time series derived from annual averages of independent precipitation amount events above a fixed threshold, the 99th percentile. Only the scale parameter of the fitted distribution is allowed to vary as a function of a covariate. This variability is modeled using B-spline function. Nonlinear correlation and cross-wavelet analysis allowed identifying two dominant climate indices as covariates in the study area, Arctic Oscillation (AO) and Pacific North American (PNA). The nonstationary frequency analysis showed that there is an east-west behavior of the AO index effects on extreme daily precipitation amounts in the study area. Indeed, the higher quantiles of these events are conditional to the AO positive phase in Atlantic Canada, while those in the more southeastern part of Canada, especially in Southern Quebec and Ontario, are negatively related to AO. The negative phase of PNA also gives the best significant correlation in these regions. Moreover, a regression analysis between AO (PNA) index and conditional quantiles provided slope values for the positive phase of the index on the one hand and the negative phase and on the other hand. This statistic allows computing a slope ratio which permits to sustain the nonlinear relation assumption between climate indices and precipitation and the development of the nonstationary GPD model for Southeastern Canada extremes precipitation modeling.
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Czech Academy of Sciences Publication Activity Database
Beranová, Romana; Kyselý, Jan; Hanel, M.
2018-01-01
Roč. 132, 1-2 (2018), s. 515-527 ISSN 0177-798X R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : sub-daily precipitation * regional climate models * extremes * Czech Republic Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 2.640, year: 2016 https://link.springer.com/article/10.1007/s00704-017-2102-0
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Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel
2014-05-01
We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present
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Trends in extreme temperature and precipitation in Muscat, Oman
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L. N. Gunawardhana
2014-09-01
Full Text Available Changes in frequency and intensity of weather events often result in more frequent and intensive disasters such as flash floods and persistent droughts. In Oman, changes in precipitation and temperature have already been detected, although a comprehensive analysis to determine long-term trends is yet to be conducted. We analysed daily precipitation and temperature records in Muscat, the capital city of Oman, mainly focusing on extremes. A set of climate indices, defined in the RClimDex software package, were derived from the longest available daily series (precipitation over the period 1977–2011 and temperature over the period 1986–2011. Results showed significant changes in temperature extremes associated with cooling. Annual maximum value of daily maximum temperature (TX, on average, decreased by 1°C (0.42°C/10 year. Similarly, the annual minimum value of daily minimum temperature (TN decreased by 1.5°C (0.61°C/10 year, which, on average, cooled at a faster rate than the maximum temperature. Consequently, the annual count of days when TX > 45°C (98th percentile decreased from 8 to 3, by 5 days. Similarly, the annual count of days when TN < 15°C (2nd percentile increased from 5 to 15, by 10 days. Annual total precipitation averaged over the period 1977–2011 is 81 mm, which shows a tendency toward wetter conditions with a 6 mm/10 year rate. There is also a significant tendency for stronger precipitation extremes according to many indices. The contribution from very wet days to the annual precipitation totals steadily increases with significance at 75% level. When The General Extreme Value (GEV probability distribution is fitted to annual maximum 1-day precipitation, the return level of a 10-year return period in 1995–2011 was estimated to be 95 mm. This return level in the recent decade is about 70% higher than the return level for the period of 1977–1994. These results indicate that the long-term wetting signal apparent in total
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Detection of the relationship between peak temperature and extreme precipitation
Yu, Y.; Liu, J.; Zhiyong, Y.
2017-12-01
Under the background of climate change and human activities, the characteristics and pattern of precipitation have changed significantly in many regions. As the political and cultural center of China, the structure and character of precipitation in Jingjinji District has varied dramatically in recent years. In this paper, the daily precipitation data throughout the period 1960-2013 are selected for analyzing the spatial-temporal variability of precipitation. The results indicate that the frequency and intensity of precipitation presents an increasing trend. Based on the precipitation data, the maximum, minimum and mean precipitation in different temporal and spatial scales is calculated respectively. The temporal and spatial variation of temperature is obtained by using statistical methods. The relationship between temperature and precipitation in different range is analyzed. The curve relates daily precipitation extremes with local temperatures has a peak structure, increasing at the low-medium range of temperature variations but decreasing at high temperatures. The relationship between extreme precipitation is stronger in downtown than that in suburbs.
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Institute of Scientific and Technical Information of China (English)
SUN; Wei; LI; Jian; YU; Ru-Cong
2013-01-01
Hourly data of 42 rain gauges over South China during 1966–2005 were used to analyze the corresponding relation between precipitation extremes and surface air temperature in the warm season(May to October).The results show that below 25℃,both daily and hourly precipitation extremes in South China increase with rising temperature.More extreme events transit to the two-time Clausius-Clapeyron(CC)relationship at lower temperatures.Daily as well as hourly precipitation extremes have a decreasing tendency nearly above 25℃,among which the decrease of hourly extremes is much more significant.In order to investigate the efects of rainfall durations,hourly precipitation extremes are presented by short duration and long duration precipitation,respectively.Results show that the dramatic decrease of hourly rainfall intensities above 25℃ is mainly caused by short duration precipitation,and long duration precipitation extremes rarely occur in South China when surface air temperature surpasses 28℃.
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Extreme Precipitation in Poland in the Years 1951-2010
Malinowska, Miroslawa
2017-12-01
The characteristics of extreme precipitation, including the dominant trends, were analysed for eight stations located in different parts of Poland for the period 1951-2010. Five indices enabling the assessment of the intensity and frequency of both extremely dry and wet conditions were applied. The indices included the number of days with precipitation ≥10mm·d-1 (R10), maximum number of consecutive dry days (CDD), maximum 5-day precipitation total (R5d), simple daily intensity index (SDII), and the fraction of annual total precipitation due to events exceeding the 95th percentile calculated for the period 1961-1990. Annual trends were calculated using standard linear regression method, while the fit of the model was assessed with the F-test at the 95% confidence level. The analysed changes in extreme precipitation showed mixed patterns. A significant positive trend in the number of days with precipitation ≥10mm·d-1 (R10) was observed in central Poland, while a significant negative one, in south-eastern Poland. Based on the analysis of maximum 5-day precipitation totals (R5d), statistically significant positive trends in north-western, western and eastern parts of the country were detected, while the negative trends were found in the central and northeastern parts. Daily precipitation, expressed as single daily intensity index (SDII), increased over time in northern and central Poland. In southern Poland, the variation of SDII index showed non-significant negative tendencies. Finally, the fraction of annual total precipitation due to the events exceeding the 1961-1990 95th percentile increased at one station only, namely, in Warsaw. The indicator which refers to dry conditions, i.e. maximum number of consecutive dry days (CDD) displayed negative trends throughout the surveyed area, with the exception of Szczecin that is a representative of north-western Poland.
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Does extreme precipitation intensity depend on the emissions scenario?
Pendergrass, Angeline; Lehner, Flavio; Sanderson, Benjamin; Xu, Yangyang
2016-04-01
The rate of increase of global-mean precipitation per degree surface temperature increase differs for greenhouse gas and aerosol forcings, and therefore depends on the change in composition of the emissions scenario used to drive climate model simulations for the remainder of the century. We investigate whether or not this is also the case for extreme precipitation simulated by a multi-model ensemble driven by four realistic emissions scenarios. In most models, the rate of increase of maximum annual daily rainfall per degree global warming in the multi-model ensemble is statistically indistinguishable across the four scenarios, whether this extreme precipitation is calculated globally, over all land, or over extra-tropical land. These results indicate that, in most models, extreme precipitation depends on the total amount of warming and does not depend on emissions scenario, in contrast to mean precipitation.
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Agel, Laurie; Barlow, Mathew; Feldstein, Steven B.; Gutowski, William J.
2018-03-01
Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. The tropopause height provides a compact representation of the upper-tropospheric potential vorticity, which is closely related to the overall evolution and intensity of weather systems. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into the overall context of patterns for all days. Six tropopause patterns are identified through KMC for extreme day precipitation: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong moisture transport preceding, and upward motion during, extreme precipitation events.
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Energy Technology Data Exchange (ETDEWEB)
Hertig, Elke; Seubert, Stefanie; Jacobeit, Jucundus [Augsburg Univ. (Germany). Inst. of Geography; Paxian, Andreas; Vogt, Gernot; Paeth, Heiko [Wuerzburg Univ. (Germany). Inst. of Geography and Geology
2012-02-15
Extreme precipitation events in the Mediterranean area have been defined by different percentile-based indices of extreme precipitation for autumn and winter: the number of events exceeding the 95{sup th} percentile of daily precipitation, percentage, total amount, and mean daily intensity of precipitation from these events. Results from statistical downscaling applying canonical correlation analysis as well as from dynamical downscaling using the regional climate model REMO are mapped for the 1961-1990 baseline period as well as for the magnitude of change for the future time slice 2021-2050 in relation to the former period. Direct output of the coupled global circulation model ECHAM5 is used as an additional source of information. A qualitative comparison of the two different downscaling techniques indicates that under the present climate both the dynamical and the statistical techniques have skill to reproduce extreme precipitation in the Mediterranean area. A good representation of the frequency of extreme precipitation events arises from the statistical downscaling approach, whereas the intensity of such events is adequately modelled by the dynamical downscaling. Concerning the change of extreme precipitation in the Mediterranean area until the mid-21{sup st} century, it is projected that the frequency of extreme precipitation events will decrease in most parts of the Mediterranean area in autumn and winter. The change of the mean intensity of such events shows a rather heterogeneous pattern with intensity increases in winter most likely at topographical elevations exposed to the West, where the uplift of humid air profits by the increase of atmospheric moisture under climate change conditions. For the precipitation total from events exceeding the 95{sup th} percentile of daily precipitation, widespread decreases are indicated in autumn, whereas in winter increases occur over the western part of the Iberian Peninsula and southern France, and reductions over
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Precipitation extremes in the Iberian Peninsula: an overview of the CLIPE project
Santos, João A.; Gonçalves, Paulo M.; Rodrigues, Tiago; Carvalho, Maria J.; Rocha, Alfredo
2014-05-01
The main aims of the project "Climate change of precipitation extreme episodes in the Iberian Peninsula and its forcing mechanisms - CLIPE" are 1) to diagnose the climate change signal in the precipitation extremes over the Iberian Peninsula (IP) and 2) to identify the underlying physical mechanisms. For the first purpose, a multi-model ensemble of 25 Regional Climate Model (RCM) simulations, from the ENSEMBLES project, is used. These experiments were generated by 15 RCMs, driven by five General Circulation Models (GCMs) under both historic conditions (1951-2000) and SRES A1B scenario (2001-2100). In this project, daily precipitation and mean sea level pressure, for the periods 1961-1990 (recent past) and 2021-2100 (future), are used. Using the Standardised Precipitation Index (SPI) on a daily basis, a precipitation extreme is defined by the pair of threshold values (Dmin, Imin), where Dmin is the minimum number of consecutive days with daily SPI above the Imin value. For both past and future climates, a precipitation extreme of a specific type is then characterised by two variables: the number of episodes with a specific duration in days and the number of episodes with a specific mean intensity (SPI/duration). Climate change is also assessed by changes in their Probability Density Functions (PDFs), estimated at sectors representative of different precipitation regimes. Lastly, for the second objective of this project, links between precipitation and Circulation Weather Regimes (CWRs) are explored for both past and future climates. Acknowledgments: this work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project CLIPE (PTDC/AAC-CLI/111733/2009).
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DEFF Research Database (Denmark)
Sørup, Hjalte Jomo Danielsen
-correlation lengths for sub-daily extreme precipitation besides having too low intensities. Especially the wrong spatial correlation structure is disturbing from an urban hydrological point of view as short-term extremes will cover too much ground if derived directly from bias corrected regional climate model output...... of precipitation are compared and used to rank climate models with respect to performance metrics. The four different observational data sets themselves are compared at daily temporal scale with respect to climate indices for mean and extreme precipitation. Data density seems to be a crucial parameter for good...... happening in summer and most of the daily extremes in fall. This behaviour is in good accordance with reality where short term extremes originate in convective precipitation cells that occur when it is very warm and longer term extremes originate in frontal systems that dominate the fall and winter seasons...
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Interdecadal Change in Extreme Precipitation over South China and Its Mechanism
Institute of Scientific and Technical Information of China (English)
NING Liang; QIAN Yongfu
2009-01-01
Based on the daily precipitation data taken from 17 stations over South China during the period of 1961 2003, a sudden change in summer extreme precipitation events over South China in the early 1990s along with the possible mechanism connected with the anomalies of the latent heat flux over the South China Sea and the sensible heat flux over the Indochina peninsula are examined. The results show that both the annual and summer extreme precipitation events have obvious interdecadal variations and have increased significantly since the early 1990s. Moreover, the latent heat flux over the South China Sea and the sensible heat flux over the Indochina peninsula also have obvious interdecadal variations consistent with that of the extreme precipitation, and influence different months' extreme precipitation, respectively. Their effects are achieved by the interdecadal increases of the strengthening convection over South China through the South China Sea Summer Monsoon.
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Development of a daily gridded precipitation data set for the Middle East
Directory of Open Access Journals (Sweden)
A. Yatagai
2008-03-01
Full Text Available We show an algorithm to construct a rain-gauge-based analysis of daily precipitation for the Middle East. One of the key points of our algorithm is to construct an accurate distribution of climatology. One possible advantage of this product is to validate high-resolution climate models and/or to diagnose the impact of climate changes on local hydrological resources. Many users are familiar with a monthly precipitation dataset (New et al., 1999 and a satellite-based daily precipitation dataset (Huffman et al., 2001, yet our data set, unlike theirs, clearly shows the effect of orography on daily precipitation and other extreme events, especially over the Fertile Crescent region. Currently the Middle-East precipitation analysis product is consisting of a 25-year data set for 1979–2003 based on more than 1300 stations.
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Hydrological impacts of precipitation extremes in the Huaihe River Basin, China.
Yang, Mangen; Chen, Xing; Cheng, Chad Shouquan
2016-01-01
Precipitation extremes play a key role in flooding risks over the Huaihe River Basin, which is important to understand their hydrological impacts. Based on observed daily precipitation and streamflow data from 1958 to 2009, eight precipitation indices and three streamflow indices were calculated for the study of hydrological impacts of precipitation extremes. The results indicate that the wet condition intensified in the summer wet season and the drought condition was getting worse in the autumn dry season in the later years of the past 50 years. The river basin had experienced higher heavy rainfall-related flooding risks in summer and more severe drought in autumn in the later of the period. The extreme precipitation events or consecutive heavy rain day events led to the substantial increases in streamflow extremes, which are the main causes of frequent floods in the Huaihe River Basin. The large inter-annual variation of precipitation anomalies in the upper and central Huaihe River Basin are the major contributor for the regional frequent floods and droughts.
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Fragoso, M.; Trigo, R. M.; Zêzere, J. L.; Valente, M. A.
2009-04-01
On 18 February 2008 the city of Lisbon had its rainiest day on record, i.e. since the establishment of the D. Luís Observatory in 1853 (continuous observations of meteorological variables are only available since 1864). Fortunately a Portuguese funded project (SIGN) allowed to digitize all the data between 1864 and 1941, allowing a proper comparison with previous extreme events and also to compute more significant return periods. We can now state that a new absolute maximum of daily precipitation at this station occurred last 18 February, when 118.4 mm were registered, surpassing the previous maximum of 110.7 mm (observed on 5 December 1876). Interestingly, these record breaking characteristics were confined to the city of Lisbon, not being observed in rural and suburban neighborhoods, where the anterior maxima recorded in 26 November 1967 or 18 November 1983 were not achieved. In fact, this extreme event was relatively uncharacteristic when compared with typical extreme precipitation events in southern Portugal (Fragoso and Tildes Gomes, 2008). These extreme episodes tend to occur preferably in fall (late September until early December) and covering a wider area. In this work we present an extensive analysis of the large-scale and synoptic atmospheric circulation environment leading to this extreme rainstorm as well as the consequences, namely floods and landslides that produced relevant socio-economic impacts (including 4 casualties). This will be achieved through the characterization of the extreme precipitation episode, describing its temporal structure and the geographic incidence of the event and also assessing statistically the exceptionality of the daily rainfall. The study of the atmospheric context of the episode will be performed with Satellite and radar data, complemented by several large-scale fields obtained from the NCAR/NCEP Reanalyses dataset, including sea level pressure, 500 hPa Geopotential height, precipitation rate, CAPE index. FRAGOSO, M
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Trend of extreme precipitation events over China in last 40 years
International Nuclear Information System (INIS)
Zhang Daquan; Hu Jingguo; Feng Guolin
2008-01-01
Using the daily precipitation data of 740 stations in China from 1960 to 2000, the analysis on the variations and distributions of the frequency and the percentage of extreme precipitation to the annual rainfall have been performed in this paper. Results indicate that the percentage of heavy rains (above 25mm/day) in the annual rainfall has increased, while on average the day number of heavy rains has slightly reduced during the past 40 years. In the end of 1970s and the beginning of 1980s, both the number of days with extreme precipitation and the percentage of extreme precipitation abruptly changed over China, especially in the northern China. By moving t test, the abrupt change year of extreme precipitation for each station and its spatial distribution over the whole country are also obtained. The abrupt change years concentrated in 1978–1982 for most regions of northern China while occurred at various stations in southern China in greatly different/diverse years. Besides the abrupt change years of extreme precipitation at part stations of Northwest China happened about 5 years later in comparison with that of the country's average
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Assessing changes in extreme convective precipitation from a damage perspective
Schroeer, K.; Tye, M. R.
2016-12-01
Projected increases in high-intensity short-duration convective precipitation are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to which, not only are extreme events rare, but such small scale events are likely to be underreported where they don't coincide with the observation network. Rather than focus solely on the convective precipitation, understanding the characteristics of these extremes which drive damage may be more effective to assess future risks. Two sources of data are used in this study. First, sub-daily precipitation observations over the Southern Alps enable an examination of seasonal and regional patterns in high-intensity convective precipitation and their relationship with weather types. Secondly, reports of private loss and damage on a household scale are used to identify which events are most damaging, or what conditions potentially enhance the vulnerability to these extremes.This study explores the potential added value from including recorded loss and damage data to understand the risks from summertime convective precipitation events. By relating precipitation generating weather types to the severity of damage we hope to develop a mechanism to assess future risks. A further benefit would be to identify from damage reports the likely occurrence of precipitation extremes where no direct observations are available and use this information to validate remotely sensed observations.
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Detection of non-stationarity in precipitation extremes using a max-stable process model
Westra, S.; Sisson, S.
2011-12-01
The question of how extreme precipitation will change under a future climate represents an urgent research problem, not least because of the significant societal impacts that would result from an increase in precipitation-induced flooding. To better constrain future projections, an important line of evidence comes from statistical assessments of change to extreme precipitation in the observational record, as a significant amount of warming since pre-industrial times has already taken place. In this study we address this problem by applying a max-stable process model to evaluate whether extreme precipitation at sub-daily and daily timescales has changed at various locations around Australia. This max-stable process approach, which was developed to simulate spatial fields comprising observations from multiple point locations, significantly increases the precision of a statistical inference compared to standard univariate methods. Applying the technique to a field of annual maxima derived from 30 sub-daily gauges in east Australia from 1965 to 2005, we find a statistically significant increase of 18% for 6-minute rainfall over this period, with smaller increases for longer duration events. We also find an increase of 5.6% and 22.5% per degree of Australian land surface temperature and global sea surface temperature at 6-minute durations, respectively, again with smaller scaling relationships for longer durations. In contrast, limited change could be observed in daily rainfall at most locations, with the exception of a statistically significant decline of 7.4% per degree land surface temperature in southwest Western Australia. These results suggest both the importance of better understanding changes to precipitation at the sub-daily timescale, as well as the need to more precisely simulate temporal variability by accounting for the spatial nature of precipitation in any statistical model.
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Observed changes in extreme precipitation in Poland: 1991-2015 versus 1961-1990
Pińskwar, Iwona; Choryński, Adam; Graczyk, Dariusz; Kundzewicz, Zbigniew W.
2018-01-01
Several episodes of extreme precipitation excess and extreme precipitation deficit, with considerable economic and social impacts, have occurred in Europe and in Poland in the last decades. However, the changes of related indices exhibit complex variability. This paper analyses changes in indices related to observed abundance and deficit of precipitated water in Poland. Among studied indices are maximum seasonal 24-h precipitation for the winter half-year (Oct.-March) and the summer half-year (Apr.-Sept.), maximum 5-day precipitation, maximum monthly precipitation and number of days with intense or very intense precipitation (respectively, in excess of 10 mm or 20 mm per day). Also, the warm-seasonal maximum number of consecutive dry days (longest period with daily precipitation below 1 mm) was examined. Analysis of precipitation extremes showed that daily maximum precipitation for the summer half-year increased for many stations, and increases during the summer half-year are more numerous than those in the winter half-year. Also, analysis of 5-day and monthly precipitation sums show increases for many stations. Number of days with intense precipitation increases especially in the north-western part of Poland. The number of consecutive dry days is getting higher for many stations in the summer half-year. Comparison of these two periods: colder 1961-1990 and warmer 1991-2015, revealed that during last 25 years most of statistical indices, such as 25th and 75th percentiles, median, mean and maximum are higher. However, many changes discussed in this paper are weak and statistically insignificant. The findings reported in this paper challenge results based on earlier data that do not include 2007-2015.
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Extreme Precipitation and Runoff under Changing Climate in Southern Maine
Energy Technology Data Exchange (ETDEWEB)
Yan, Eugene [Argonne National Lab. (ANL), Argonne, IL (United States); Jared, Alissa [Argonne National Lab. (ANL), Argonne, IL (United States); Mahat, Vinod [Argonne National Lab. (ANL), Argonne, IL (United States); Picel, Mark [Argonne National Lab. (ANL), Argonne, IL (United States); Verner, Duane [Argonne National Lab. (ANL), Argonne, IL (United States); Wall, Thomas [Argonne National Lab. (ANL), Argonne, IL (United States); Moges, Edom M. [Washington State Univ., Pullman, WA (United States); Demissie, Yonas K. [Washington State Univ., Pullman, WA (United States); Pierce, Julia [Argonne National Lab. (ANL), Argonne, IL (United States)
2016-12-01
The quantification of extreme precipitation events is vitally important for designing and engineering water and flood sensitive infrastructure. Since this kind of infrastructure is usually built to last much longer than 10, 50, or even 100 years, there is great need for statistically sound estimates of the intensity of 10-, 50-, 100-, and 500-year rainstorms and associated floods. The recent assessment indicated that the intensity of the most extreme precipitation events (or the heaviest 1% of all daily events) have increased in every region of the contiguous states since the 1950s (Melillo et al. 2014). The maximum change in precipitation intensity of extreme events occurred in the northeast region reaching 71%. The precipitation extremes can be characterized using intensity-duration-frequency analysis (IDF). However, the current IDFs in this region were developed around the assumption that climate condition remains stationary over the next 50 or 100 years. To better characterize the potential flood risk, this project will (1) develop precipitation IDFs on the basis of both historical observations and future climate projections from dynamic downscaling with Argonne National Laboratory’s (Argonne’s) regional climate model and (2) develop runoff IDFs using precipitation IDFs for the Casco Bay Watershed. IDF development also considers non-stationary distribution models and snowmelt effects that are not incorporated in the current IDFs.
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Effects of extreme precipitation to the distribution of infectious diseases in Taiwan, 1994-2008.
Directory of Open Access Journals (Sweden)
Mu-Jean Chen
Full Text Available The incidence of extreme precipitation has increased with the exacerbation of worldwide climate disruption. We hypothesize an association between precipitation and the distribution patterns that would affect the endemic burden of 8 infectious diseases in Taiwan, including water- and vector-borne infectious diseases. A database integrating daily precipitation and temperature, along with the infectious disease case registry for all 352 townships in the main island of Taiwan was analysed for the period from 1994 to 2008. Four precipitation levels, 350 mm, were categorized to represent quantitative differences, and their associations with each specific disease was investigated using the Generalized Additive Mixed Model and afterwards mapped on to the Geographical Information System. Daily precipitation levels were significantly correlated with all 8 mandatory-notified infectious diseases in Taiwan. For water-borne infections, extreme torrential precipitation (>350 mm/day was found to result in the highest relative risk for bacillary dysentery and enterovirus infections when compared to ordinary rain (<130 mm/day. Yet, for vector-borne diseases, the relative risk of dengue fever and Japanese encephalitis increased with greater precipitation only up to 350 mm. Differential lag effects following precipitation were statistically associated with increased risk for contracting individual infectious diseases. This study's findings can help health resource sector management better allocate medical resources and be better prepared to deal with infectious disease outbreaks following future extreme precipitation events.
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Energy Technology Data Exchange (ETDEWEB)
Wang, Lei [School of Atmospheric Sciences, Nanjing University, China; Pacific Northwest National Laboratory, Richland WA USA; Qian, Yun [Pacific Northwest National Laboratory, Richland WA USA; Zhang, Yaocun [School of Atmospheric Sciences, Nanjing University, China; Zhao, Chun [Pacific Northwest National Laboratory, Richland WA USA; Leung, L. Ruby [Pacific Northwest National Laboratory, Richland WA USA; Huang, Anning [School of Atmospheric Sciences, Nanjing University, China; Xiao, Chuliang [Cooperative Institute for Limnology and Ecosystems Research, School of Natural Resources and Environment, University of Michigan, Ann Arbor MI USA
2015-11-09
This paper presents a comprehensive analysis of interannual and interdecadal variations of summer precipitation and precipitation-related extreme events in China associated with variations of the East Asian summer monsoon (EASM) from 1979-2012. A high-quality daily precipitation dataset covering 2287 weather stations in China is analyzed. Based on the precipitation pattern analysis using empirical orthogonal functions, three sub-periods of 1979-1992 (period I), 1993-1999 (period II) and 2000-2012 (period III) are identified to be representative of the precipitation variability. Similar significant variability of the extreme precipitation indices is found across four sub-regions in eastern China. The spatial patterns of summer mean precipitation, the number of days with daily rainfall exceeding 95th percentile precipitation (R95p) and the maximum number of consecutive wet days (CWD) anomalies are consistent, but opposite to that of maximum consecutive dry days (CDD) anomalies during the three sub-periods. However, the spatial patterns of hydroclimatic intensity (HY-INT) are notably different from that of the other three extreme indices, but highly correlated to the dry events. The changes of precipitation anomaly patterns are accompanied by the change of the EASM regime and the abrupt shift of the position of the west Pacific subtropical high around 1992/1993 and 1999/2000, respectively, which influence the moisture transport that contributes most to the precipitation anomalies. Lastly, the EASM intensity is linked to sea surface temperature anomaly over the tropical Indian and Pacific Ocean that influences deep convection over the oceans.
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DEFF Research Database (Denmark)
Madsen, H.; Gregersen, Ida Bülow; Rosbjerg, Dan
2017-01-01
with daily measurements. The Poisson rate is positively correlated to the mean annual precipitation for all durations considered (1 min to 48 hours). The mean intensity can be assumed constant over Denmark for durations up to 1 hour. For durations larger than 1 hour the mean intensity is significantly...... correlated to the mean extreme daily precipitation. A Generalised Pareto distribution with a regional constant shape parameter is adopted. Compared to previous regional studies in Denmark a general increase in extreme rainfall intensity for durations up to 1 hour is found, whereas for larger durations both...
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High-resolution projections of mean and extreme precipitations over China through PRECIS under RCPs
Zhu, Jinxin; Huang, Gordon; Wang, Xiuquan; Cheng, Guanhui; Wu, Yinghui
2018-06-01
The impact of global warming on the characteristics of mean and extreme precipitations over China is investigated by using the Providing REgional Climate Impacts for Studies (PRECIS) model. The PRECIS model was driven by the Hadley Centre Global Environment Model version 2 with Earth System components and coupling (HadGEM2-ES). The results of both models are analyzed in terms of mean precipitation and indices of precipitation extremes (R95p, R99p, SDII, WDF, and CWD) over China at the resolution of 25 km under the Representative Concentration Pathways 4.5 and 8.5 (RCP4.5 and RCP8.5) scenarios for the baseline period (1976-2005) and two future periods (2036-2065 and 2070-2099). With improved resolution, the PRECIS model is able to better represent the fine-scale physical process than HadGEM2-ES. It can provide reliable spatial patterns of precipitation and its related extremes with high correlations to observations. Moreover, there is a notable improvement in temporal patterns simulation through the PRECIS model. The PRECIS model better reproduces the regional annual cycle and frequencies of daily precipitation intensity than its driving GCM. Under RCP4.5 and RCP8.5, both the HadGEM2-ES and the precis project increasing annual precipitation over the entire country for two future periods. Precipitation increase in winter is greater than the increase in summer. The results suggest that increased radiative forcing from RCP4.5 to RCP8.5 would further intensify the magnitude of projected precipitation changes by both PRECIS and HadGEM2-ES. For example, some parts of south China with decreased precipitation under RCP4.5 would expect even less precipitation under RCP8.5; regions (northwest, northcentral and northeast China) with increased precipitation under RCP4.5 would expect more precipitation under RCP8.5. Apart from the projected increase in annual total precipitation, the results also suggest that there will be an increase in the days with precipitation higher than
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Examine Precipitation Extremes in Terms of Storm Properties
Jiang, P.; Yu, Z.; Chen, L.; Gautam, M. R.; Acharya, K.
2017-12-01
The increasing potential of the extreme precipitation is of significant societal concern. Changes in precipitation extremes have been mostly examined using extreme precipitation indices or Intensity-Duration-Frequency (IDF) analyses, which often fail to reveal the characteristics of an integrated precipitation event. In this study, we will examine the precipitation extremes in terms of storm properties including storm duration, storm intensity, total storm precipitation, and within storm pattern. Single storm event will be identified and storm properties will be determined based on the hourly precipitation time series in the selected locations in southwest United States. Three types of extreme precipitation event will be recognized using the criteria as (1) longest storm duration; (2) Highest storm intensity; and (3) largest total precipitation over a storm. The trend and variation of extreme precipitation events will be discussed for each criterion. Based on the comparisons of the characteristics of extreme precipitation events identified using different criteria, we will provide guidelines for choosing proper criteria for extreme precipitation analysis in specific location.
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Li, Mao-Fen; Luo, Wei; Li, Hailiang; Liu, Enping; Li, Yuping
2018-04-01
Frequent occurrences of extreme precipitation events have significant impacts on agricultural production. Tropical agriculture has been playing an important role in national economy in China. A precise understanding of variability in extreme precipitation indices and their impacts on crop yields are of great value for farmers and policy makers at county level, particularly in tropical China where almost all agriculture is rainfed. This research has studied observed trends in extreme precipitation indices (a total of 10) during 1988-2013 over Hainan island, tropical China. Mann-Kendall nonparametric test was adopted for trend detection and the results showed that most of precipitation indices showed increasing trend. Since rice is the most important staple food in Hainan island, the impacts of extreme precipitation indices on rice yields were also analyzed through simple correlations. In general, the rainy days and rain intensity in late rice growing season showed increasing trend over Hainan island. The rice yield presented ninth-degree polynomial technological trend at all stations and increasing trend for early rice yield. Late rice yield showed a decreasing trend in some parts of Hainan island. Spearman rank correlation coefficient indicated that the correlation was more pronounced between extreme precipitation indices and yields at Haikou site for early rice, and Haikou, Sanya, and Qionghai stations for late rice, respectively. Further results also indicated that there were statistically significant positive trends of R10 and R20 (number of days with precipitation ≥10 mm and precipitation ≥20 mm, respectively) from July to November at Haikou (located in north of Hainan island), and this positive trend may be a disadvantage for late rice yield. The cut-off value of extreme precipitation indices and its correlation with rice yield anomaly indices for Hainan island provided a foundation for vulnerability assessment as well as a contribution to set up
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Lui, Yuk Sing; Tam, Chi-Yung; Lau, Ngar-Cheung
2018-04-01
This study examines the impacts of climate change on precipitation extremes in the Asian monsoon region during boreal summer, based on simulations from the 20-km Meteorological Research Institute atmospheric general circulation model. The model can capture the summertime monsoon rainfall, with characteristics similar to those from Tropical Rainfall Measuring Mission and Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation. By comparing the 2075-2099 with the present-day climate simulations, there is a robust increase of the mean rainfall in many locations due to a warmer climate. Over southeastern China, the Baiu rainband, Bay of Bengal and central India, extreme precipitation rates are also enhanced in the future, which can be inferred from increases of the 95th percentile of daily precipitation, the maximum accumulated precipitation in 5 consecutive days, the simple daily precipitation intensity index, and the scale parameter of the fitted gamma distribution. In these regions, with the exception of the Baiu rainband, most of these metrics give a fractional change of extreme rainfall per degree increase of the lower-tropospheric temperature of 5 to 8.5% K-1, roughly consistent with the Clausius-Clapeyron relation. However, over the Baiu area extreme precipitation change scales as 3.5% K-1 only. We have also stratified the rainfall data into those associated with tropical cyclones (TC) and those with other weather systems. The AGCM gives an increase of the accumulated TC rainfall over southeastern China, and a decrease in southern Japan in the future climate. The latter can be attributed to suppressed TC occurrence in southern Japan, whereas increased accumulated rainfall over southeastern China is due to more intense TC rain rate under global warming. Overall, non-TC weather systems are the main contributor to enhanced precipitation extremes in various locations. In the future, TC activities over southeastern China tend to further
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Scaling and clustering effects of extreme precipitation distributions
Zhang, Qiang; Zhou, Yu; Singh, Vijay P.; Li, Jianfeng
2012-08-01
SummaryOne of the impacts of climate change and human activities on the hydrological cycle is the change in the precipitation structure. Closely related to the precipitation structure are two characteristics: the volume (m) of wet periods (WPs) and the time interval between WPs or waiting time (t). Using daily precipitation data for a period of 1960-2005 from 590 rain gauge stations in China, these two characteristics are analyzed, involving scaling and clustering of precipitation episodes. Our findings indicate that m and t follow similar probability distribution curves, implying that precipitation processes are controlled by similar underlying thermo-dynamics. Analysis of conditional probability distributions shows a significant dependence of m and t on their previous values of similar volumes, and the dependence tends to be stronger when m is larger or t is longer. It indicates that a higher probability can be expected when high-intensity precipitation is followed by precipitation episodes with similar precipitation intensity and longer waiting time between WPs is followed by the waiting time of similar duration. This result indicates the clustering of extreme precipitation episodes and severe droughts or floods are apt to occur in groups.
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Climatic changes of extreme precipitation in Denmark from 1872 to 2100
DEFF Research Database (Denmark)
Arnbjerg-Nielsen, Karsten; Gregersen, Ida Bülow; Sunyer Pinya, Maria Antonia
of climate change impacts from anthropogenic effects can be established based on projections of daily precipitation. These estimates have then been further downscaled to enable urban pluvial inundation calculations using different statistical downscaling and extreme value analysis techniques. . From...... of precipitation extremes. The objective is to establish cities that are resilient to pluvial floods by means of a gradual upgrading of the drainage capacity in combination with a structured risk management approach. Using the regional climate model (RCM) data repositories from PRUDENCE and ENSEMBLES, estimates....... These results are important for the extrapolation to future events. Currently efforts are dedicated to constructing similar models based on outputs from climate models, but the models are complicated due to the fact that the correlation structure of high-resolution precipitation in the climate models deviates...
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United States Historical Climatology Network Daily Temperature and Precipitation Data (1871-1997)
Energy Technology Data Exchange (ETDEWEB)
Easterling, D.R.
2002-10-28
This document describes a database containing daily observations of maximum and minimum temperature, precipitation amount, snowfall amount, and snow depth from 1062 observing stations across the contiguous US. This database is an expansion and update of the original 138-station database previously released by the Carbon Dioxide Information Analysis Center (CDIAC) as CDIAC numeric data package NDP-042. These 1062 stations are a subset of the 1221-station US Historical Climatology Network (HCN), a monthly database compiled by the National Climatic Data Center (Asheville, North Carolina) that has been widely used in analyzing US climate. Data from 1050 of these daily records extend into the 1990s, while 990 of these extend through 1997. Most station records are essentially complete for at least 40 years; the latest beginning year of record is 1948. Records from 158 stations begin prior to 1900, with that of Charleston, South Carolina beginning the earliest (1871). The daily resolution of these data makes them extremely valuable for studies attempting to detect and monitor long-term climatic changes on a regional scale. Studies using daily data may be able to detect changes in regional climate that would not be apparent from analysis of monthly temperature and precipitation data. Such studies may include analyses of trends in maximum and minimum temperatures, temperature extremes, daily temperature range, precipitation ''event size'' frequency, and the magnitude and duration of wet and dry periods. The data are also valuable in areas such as regional climate model validation and climate change impact assessment. This database is available free of charge from CDIAC as a numeric data package (NDP).
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Modelling the potential impacts of afforestation on extreme precipitation over West Africa
Odoulami, Romaric C.; Abiodun, Babatunde J.; Ajayi, Ayodele E.
2018-05-01
This study examines how afforestation in West Africa could influence extreme precipitation over the region, with a focus on widespread extreme rainfall events (WEREs) over the afforestation area. Two regional climate models (RegCM and WRF) were applied to simulate the present-day climate (1971-2000) and future climate (2031-2060, under IPCC RCP 4.5 emission scenario) with and without afforestation of the Savannah zone in West Africa. The models give a realistic simulation of precipitation indices and WEREs over the subcontinent. On average, the regional models projected future decreases in total annual wet day precipitation (PRCPTOT) and total annual daily precipitation greater than or equal to the 95th percentile of daily precipitation threshold (R95pTOT) and increases in maximum number of consecutive dry days (CDD) over Sahel. Over Savannah, the models projected decreases in PRCPTOT but increases in R95pTOT and CDD. Also, an increase in WEREs frequency is projected over west, central and east Savannah, except that RegCM simulated a decrease in WEREs over east Savannah. In general, afforestation increases PRCPTOT and R95pTOT but decreases CDD over the afforestation area. The forest-induced increases in PRCPTOT and decreases in CDD affect all ecological zones in West Africa. However, the simulations show that afforestation of Savannah also decreases R95pTOT over the Guinea Coast. It further increases WEREs over west and central Savannah and decreases them over east Savannah because of the local decrease in R95pTOT. Results of this study suggest that the future changes in characteristics of extreme precipitation events over West Africa are sensitive to the ongoing land modification.
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Huang, Jin; Islam, A. R. M. Towfiqul; Zhang, Fangmin; Hu, Zhenghua
2017-10-01
With the increasing risk of meteorological disasters, it is of great importance to analyze the spatiotemporal changes of precipitation extremes and its possible impact on rice productivity, especially in Jiangsu province, southeast China. In this study, we explored the relationships between rice yield and extreme precipitation indices using Mann-Kendall trend test, Pettitt's test, and K-means clustering methods. This study used 10 extreme precipitation indices of the rice growing season (May to October) based on the daily precipitation records and rice yield data at 52 meteorological stations during 1961-2012 in Jiangsu province. The main findings were as follows: (1) correlation results indicated that precipitation extremes occurred in the months of July, August, and October, which had noticeable adverse effects on rice yield; (2) the maximum 7-day precipitation of July and the number of rainy days of August and October should be considered as three key indicators for the precipitation-induced rice meteorological disasters; and (3) most of the stations showed an increasing trends for the maximum 7-day precipitation of July and the number of rainy days of August, while the number of rainy days of October in all the stations demonstrated a decreasing trend. Moreover, Jiangsu province could be divided into two major sub-regions such as north and south areas with different temporal variations in the three key indicators.
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Huang, Jin; Islam, A R M Towfiqul; Zhang, Fangmin; Hu, Zhenghua
2017-10-01
With the increasing risk of meteorological disasters, it is of great importance to analyze the spatiotemporal changes of precipitation extremes and its possible impact on rice productivity, especially in Jiangsu province, southeast China. In this study, we explored the relationships between rice yield and extreme precipitation indices using Mann-Kendall trend test, Pettitt's test, and K-means clustering methods. This study used 10 extreme precipitation indices of the rice growing season (May to October) based on the daily precipitation records and rice yield data at 52 meteorological stations during 1961-2012 in Jiangsu province. The main findings were as follows: (1) correlation results indicated that precipitation extremes occurred in the months of July, August, and October, which had noticeable adverse effects on rice yield; (2) the maximum 7-day precipitation of July and the number of rainy days of August and October should be considered as three key indicators for the precipitation-induced rice meteorological disasters; and (3) most of the stations showed an increasing trends for the maximum 7-day precipitation of July and the number of rainy days of August, while the number of rainy days of October in all the stations demonstrated a decreasing trend. Moreover, Jiangsu province could be divided into two major sub-regions such as north and south areas with different temporal variations in the three key indicators.
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Linking increases in hourly precipitation extremes to atmospheric temperature and moisture changes
International Nuclear Information System (INIS)
Lenderink, Geert; Van Meijgaard, Erik
2010-01-01
Relations between hourly precipitation extremes and atmospheric temperature and moisture derived for the present-day climate are studied with the aim of understanding the behavior (and the uncertainty in predictions) of hourly precipitation extremes in a changing climate. A dependency of hourly precipitation extremes on the daily mean 2 m temperature of approximately two times the Clausius-Clapeyron (CC) relation is found for temperatures above 10 deg. C. This is a robust relation obtained in four observational records across western Europe. A dependency following the CC relation can be explained by the observed increase in atmospheric (absolute) humidity with temperature, whereas the enhanced dependency (compared to the CC relation) appears to be caused by dynamical feedbacks owing to excess latent heat release in extreme showers. Integrations with the KNMI regional climate model RACMO2 at 25 km grid spacing show that changes in hourly precipitation extremes may indeed considerably exceed the prediction from the CC relation. The results suggests that increases of + 70% or even more are possible by the end of this century. However, a different regional model (CLM operated at ETHZ) predicts much smaller increases; this is probably caused by a too strong sensitivity of this model to a decrease in relative humidity.
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Regional Frequency and Uncertainty Analysis of Extreme Precipitation in Bangladesh
Mortuza, M. R.; Demissie, Y.; Li, H. Y.
2014-12-01
Increased frequency of extreme precipitations, especially those with multiday durations, are responsible for recent urban floods and associated significant losses of lives and infrastructures in Bangladesh. Reliable and routinely updated estimation of the frequency of occurrence of such extreme precipitation events are thus important for developing up-to-date hydraulic structures and stormwater drainage system that can effectively minimize future risk from similar events. In this study, we have updated the intensity-duration-frequency (IDF) curves for Bangladesh using daily precipitation data from 1961 to 2010 and quantified associated uncertainties. Regional frequency analysis based on L-moments is applied on 1-day, 2-day and 5-day annual maximum precipitation series due to its advantages over at-site estimation. The regional frequency approach pools the information from climatologically similar sites to make reliable estimates of quantiles given that the pooling group is homogeneous and of reasonable size. We have used Region of influence (ROI) approach along with homogeneity measure based on L-moments to identify the homogenous pooling groups for each site. Five 3-parameter distributions (i.e., Generalized Logistic, Generalized Extreme value, Generalized Normal, Pearson Type Three, and Generalized Pareto) are used for a thorough selection of appropriate models that fit the sample data. Uncertainties related to the selection of the distributions and historical data are quantified using the Bayesian Model Averaging and Balanced Bootstrap approaches respectively. The results from this study can be used to update the current design and management of hydraulic structures as well as in exploring spatio-temporal variations of extreme precipitation and associated risk.
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Directory of Open Access Journals (Sweden)
Mingquan Lü
2018-01-01
Full Text Available The Three Gorges Dam (TGD is one of the largest hydroelectric projects in the world. Monitoring the spatiotemporal distribution of extreme precipitation offers valuable information for adaptation and mitigation strategies and reservoir management schemes. This study examined variations in extreme precipitation over the Three Gorges Reservoir area (TGRA in China to investigate the potential role of climate warming and Three Gorges Reservoir (TGR. The trends in extreme precipitation over the TGRA were investigated using the iterative-based Mann–Kendall (MK test and Sen’s slope estimator, based on weather station daily data series and TRMM (Tropical Rainfall Measuring Mission data series. The mean and density distribution of extreme precipitation indices between pre-dam and post-dam, pre-1985 and post-1985, and near and distant reservoir area were assessed by the Mann–Whitney test and the Kolmogorov–Smirnov test. The ratio of extreme precipitation to non-extreme precipitation became larger. The precipitation was characterized by increases in heavy precipitation as well as decreases in light and moderate rain. Comparing extreme precipitation indices between pre-1985 (cooling and post-1985 (warming indicated extreme precipitation has changed to become heavier. Under climate warming, the precipitation amount corresponding to more than the 95th percentile increased at the rate of 6.48%/°C. Results from comparing extreme precipitation for the pre- and post-dam, near reservoir area (NRA and away from the reservoir area (ARA imply an insignificant role of the TGR on rainfall extremes over the TGRA. Moreover, the impoundment of TGR did not exert detectable impacts on the surface relative humidity (RH and water vapor pressure (WP.
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Identifying Patterns in Extreme Precipitation Risk and the Related Impacts
Schroeer, K.; Tye, M. R.
2017-12-01
Extreme precipitation can harm human life and assets through flooding, hail, landslides, or debris flows. Flood risk assessments typically concentrate on river or mountain torrent channels, using water depth, flow velocity, and/or sediment deposition to quantify the risk. In addition, extreme events with high recurrence intervals are often the main focus. However, damages from short-term and localized convective showers often occur away from watercourses. Also, damages from more frequent small scale extremes, although usually less disastrous, can accumulate to considerable financial burdens. Extreme convective precipitation is expected to intensify in a warmer climate, and vulnerability patterns might change in tandem with changes in the character of precipitation and flood types. This has consequences for adaptation planners who want to establish effective protection measures and reduce the cost from natural hazards. Here we merge hydrological and exposure data to identify patterns of risk under varying synoptic conditions. Exposure is calculated from a database of 76k damage claims reported to the national disaster fund in 480 municipalities in south eastern Austria from 1990-2015. Hydrological data comprise sub-daily precipitation (59 gauges) and streamflow (62 gauges) observations. We use synoptic circulation types to identify typical precipitation patterns. They indicate the character of precipitation even if a gauge is not in close proximity, facilitating potential future research with regional climate model data. Results show that more claims are reported under synoptic conditions favouring convective precipitation (on average 1.5-3 times more than on other days). For agrarian municipalities, convective precipitation damages are among the costliest after long low-intensity precipitation events. In contrast, Alpine communities are particularly vulnerable to convective high-intensity rainfall. In addition to possible observational error, uncertainty is present
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Properties of Extreme Precipitation and Their Uncertainties in 3-year GPM Precipitation Radar Data
Liu, N.; Liu, C.
2017-12-01
Extreme high precipitation rates are often related to flash floods and have devastating impacts on human society and the environments. To better understand these rare events, 3-year Precipitation Features (PFs) are defined by grouping the contiguous areas with nonzero near-surface precipitation derived using Global Precipitation Measurement (GPM) Ku band Precipitation Radar (KuPR). The properties of PFs with extreme precipitation rates greater than 20, 50, 100 mm/hr, such as the geographical distribution, volumetric precipitation contribution, seasonal and diurnal variations, are examined. In addition to the large seasonal and regional variations, the rare extreme precipitation rates often have a larger contribution to the local total precipitation. Extreme precipitation rates occur more often over land than over ocean. The challenges in the retrieval of extreme precipitation might be from the attenuation correction and large uncertainties in the Z-R relationships from near-surface radar reflectivity to precipitation rates. These potential uncertainties are examined by using collocated ground based radar reflectivity and precipitation retrievals.
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Recent and future extreme precipitation over Ukraine
Vyshkvarkova, Olena; Voskresenskaya, Elena
2014-05-01
The aim of study is to analyze the parameters of precipitation extremes and inequality over Ukraine in recent climate epoch and their possible changes in the future. Data of observations from 28 hydrometeorological stations over Ukraine and output of GFDL-CM3 model (CMIP5) for XXI century were used in the study. The methods of concentration index (J. Martin-Vide, 2004) for the study of precipitation inequality while the extreme precipitation indices recommended by the ETCCDI - for the frequency of events. Results. Precipitation inequality on the annual and seasonal scales was studied using estimated CI series for 1951-2005. It was found that annual CI ranges vary from 0.58 to 0.64. They increase southward from the north-west (forest zone) and the north-east (forest steppe zone) of Ukraine. CI maxima are located in the coastal regions of the Black Sea and the Sea of Azov. Annual CI spatial distribution indicates that the contribution of extreme precipitation into annual totals is most significant at the boundary zone between steppe and marine regions. At the same time precipitation pattern at the foothill of Carpathian Mountains is more homogenous. The CI minima (0.54) are typical for the winter season in foothill of Ukrainian Carpathians. The CI maxima reach 0.71 in spring at the steppe zone closed to the Black Sea coast. It should be noted that the greatest ranges of CI maximum and CI minimum deviation are typical for spring. It is associated with patterns of cyclone trajectories in that season. The most territory is characterized by tendency to decrease the contribution of extreme precipitation into the total amount (CI linear trends are predominantly negative in all seasons). Decadal and interdecadal variability of precipitation inequality associated with global processes in ocean-atmosphere system are also studied. It was shown that precipitation inequality over Ukraine on 10 - 15 % stronger in negative phase of Pacific Decadal Oscillation and in positive phase
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Silva, W. L.; Dereczynski, C. P.; Cavalcanti, I. F.
2013-05-01
One of the main concerns of contemporary society regarding prevailing climate change is related to possible changes in the frequency and intensity of extreme events. Strong heat and cold waves, droughts, severe floods, and other climatic extremes have been of great interest to researchers because of its huge impact on the environment and population, causing high monetary damages and, in some cases, loss of life. The frequency and intensity of extreme events associated with precipitation and air temperature have been increased in several regions of the planet in recent years. These changes produce serious impacts on human activities such as agriculture, health, urban planning and development and management of water resources. In this paper, we analyze the trends in indices of climatic extremes related to daily precipitation and maximum and minimum temperatures at 22 meteorological stations of the National Institute of Meteorology (INMET) in Rio de Janeiro State (Brazil) in the last 50 years. The present trends are evaluated using the software RClimdex (Canadian Meteorological Service) and are also subjected to statistical tests. Preliminary results indicate that periods of drought are getting longer in Rio de Janeiro State, except in the North/Northwest area. In "Vale do Paraíba", "Região Serrana" and "Região dos Lagos" the increase of consecutive dry days is statistically significant. However, we also detected an increase in the total annual rainfall all over the State (taxes varying from +2 to +8 mm/year), which are statistically significant at "Região Serrana". Moreover, the intensity of heavy rainfall is also growing in most of Rio de Janeiro, except in "Costa Verde". The trends of heavy rainfall indices show significant increase in the "Metropolitan Region" and in "Região Serrana", factor that increases the vulnerability to natural disasters in these areas. With respect to temperature, it is found that the frequency of hot (cold) days and nights is
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The waviness of the extratropical jet and daily weather extremes
Röthlisberger, Matthias; Martius, Olivia; Pfahl, Stephan
2016-04-01
In recent years the Northern Hemisphere mid-latitudes have experienced a large number of weather extremes with substantial socio-economic impact, such as the European and Russian heat waves in 2003 and 2010, severe winter floods in the United Kingdom in 2013/2014 and devastating winter storms such as Lothar (1999) and Xynthia (2010) in Central Europe. These have triggered an engaged debate within the scientific community on the role of human induced climate change in the occurrence of such extremes. A key element of this debate is the hypothesis that the waviness of the extratropical jet is linked to the occurrence of weather extremes, with a wavier jet stream favouring more extremes. Previous work on this topic is expanded in this study by analyzing the linkage between a regional measure of jet waviness and daily temperature, precipitation and wind gust extremes. We show that indeed such a linkage exists in many regions of the world, however this waviness-extremes linkage varies spatially in strength and sign. Locally, it is strong only where the relevant weather systems, in which the extremes occur, are affected by the jet waviness. Its sign depends on how the frequency of occurrence of the relevant weather systems is correlated with the occurrence of high and low jet waviness. These results go beyond previous studies by noting that also a decrease in waviness could be associated with an enhanced number of some weather extremes, especially wind gust and precipitation extremes over western Europe.
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Dumitrescu, Alexandru; Busuioc, Aristita
2016-04-01
EURO-CORDEX is the European branch of the international CORDEX initiative that aims to provide improved regional climate change projections for Europe. The main objective of this paper is to document the performance of the individual models in reproducing the variability of precipitation extremes in Romania. Here three EURO-CORDEX regional climate models (RCMs) ensemble (scenario RCP4.5) are analysed and inter-compared: DMI-HIRHAM5, KNMI-RACMO2.2 and MPI-REMO. Compared to previous studies, when the RCM validation regarding the Romanian climate has mainly been made on mean state and at station scale, a more quantitative approach of precipitation extremes is proposed. In this respect, to have a more reliable comparison with observation, a high resolution daily precipitation gridded data set was used as observational reference (CLIMHYDEX project). The comparison between the RCM outputs and observed grid point values has been made by calculating three extremes precipitation indices, recommended by the Expert Team on Climate Change Detection Indices (ETCCDI), for the 1976-2005 period: R10MM, annual count of days when precipitation ≥10mm; RX5DAY, annual maximum 5-day precipitation and R95P%, precipitation fraction of annual total precipitation due to daily precipitation > 95th percentile. The RCMs capability to reproduce the mean state for these variables, as well as the main modes of their spatial variability (given by the first three EOF patterns), are analysed. The investigation confirms the ability of RCMs to simulate the main features of the precipitation extreme variability over Romania, but some deficiencies in reproducing of their regional characteristics were found (for example, overestimation of the mea state, especially over the extra Carpathian regions). This work has been realised within the research project "Changes in climate extremes and associated impact in hydrological events in Romania" (CLIMHYDEX), code PN II-ID-2011-2-0073, financed by the Romanian
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Addressing extreme precipitation change under future climates in the Upper Yangtze River Basin
Yang, Z.; Yuan, Z.; Gao, X.
2017-12-01
Investigating the impact of climate change on extreme precipitation accurately is of importance for application purposes such as flooding mitigation and urban drainage system design. In this paper, a systematical analysis framework to assess the impact of climate change on extreme precipitation events is developed and practiced in the Upper Yangtze River Basin (UYRB) in China. Firstly, the UYRB is gridded and five extreme precipitation indices (annual maximum 3- 5- 7- 15- and 30-day precipitation) are selected. Secondly, with observed precipitation from China's Ground Precipitation 0.5°×0.5° Gridded Dataset (V2.0) and simulated daily precipitation from ten general circulation models (GCMs) of CMIP5, A regionally efficient GCM is selected for each grid by the skill score (SS) method which maximizes the overlapped area of probability density functions of extreme precipitation indices between observations and simulations during the historical period. Then, simulations of assembled efficient GCMs are bias corrected by Equidistant Cumulative Distribution Function method. Finally, the impact of climate change on extreme precipitation is analyzed. The results show that: (1) the MRI-CGCM3 and MIROC-ESM perform better in the UYRB. There are 19.8 to 20.9% and 14.2 to 18.7% of all grids regard this two GCMs as regionally efficient GCM for the five indices, respectively. Moreover, the regionally efficient GCMs are spatially distributed. (2) The assembled GCM performs much better than any single GCM, with the SS>0.8 and SS>0.6 in more than 65 and 85 percent grids. (3) Under the RCP4.5 scenario, the extreme precipitation of 50-year and 100-year return period is projected to increase in most areas of the UYRB in the future period, with 55.0 to 61.3% of the UYRB increasing larger than 10 percent for the five indices. The changes are spatially and temporal distributed. The upstream region of the UYRB has a relatively significant increase compared to the downstream basin, while
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Characterizing the Spatial Contiguity of Extreme Precipitation over the US in the Recent Past
Touma, D. E.; Swain, D. L.; Diffenbaugh, N. S.
2016-12-01
The spatial characteristics of extreme precipitation over an area can define the hydrologic response in a basin, subsequently affecting the flood risk in the region. Here, we examine the spatial extent of extreme precipitation in the US by defining its "footprint": a contiguous area of rainfall exceeding a certain threshold (e.g., 90th percentile) on a given day. We first characterize the climatology of extreme rainfall footprint sizes across the US from 1980-2015 using Daymet, a high-resolution observational gridded rainfall dataset. We find that there are distinct regional and seasonal differences in average footprint sizes of extreme daily rainfall. In the winter, the Midwest shows footprints exceeding 500,000 sq. km while the Front Range exhibits footprints of 10,000 sq. km. Alternatively, the summer average footprint size is generally smaller and more uniform across the US, ranging from 10,000 sq. km in the Southwest to 100,000 sq. km in Montana and North Dakota. Moreover, we find that there are some significant increasing trends of average footprint size between 1980-2015, specifically in the Southwest in the winter and the Northeast in the spring. While gridded daily rainfall datasets allow for a practical framework in calculating footprint size, this calculation heavily depends on the interpolation methods that have been used in creating the dataset. Therefore, we assess footprint size using the GHCN-Daily station network and use geostatistical methods to define footprints of extreme rainfall directly from station data. Compared to the findings from Daymet, preliminary results using this method show fewer small daily footprint sizes over the US while large footprints are of similar number and magnitude to Daymet. Overall, defining the spatial characteristics of extreme rainfall as well as observed and expected changes in these characteristics allows us to better understand the hydrologic response to extreme rainfall and how to better characterize flood
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Sun, Qiaohong; Miao, Chiyuan; Qiao, Yuanyuan; Duan, Qingyun
2017-12-01
The El Niño-Southern Oscillation (ENSO) and local temperature are important drivers of extreme precipitation. Understanding the impact of ENSO and temperature on the risk of extreme precipitation over global land will provide a foundation for risk assessment and climate-adaptive design of infrastructure in a changing climate. In this study, nonstationary generalized extreme value distributions were used to model extreme precipitation over global land for the period 1979-2015, with ENSO indicator and temperature as covariates. Risk factors were estimated to quantify the contrast between the influence of different ENSO phases and temperature. The results show that extreme precipitation is dominated by ENSO over 22% of global land and by temperature over 26% of global land. With a warming climate, the risk of high-intensity daily extreme precipitation increases at high latitudes but decreases in tropical regions. For ENSO, large parts of North America, southern South America, and southeastern and northeastern China are shown to suffer greater risk in El Niño years, with more than double the chance of intense extreme precipitation in El Niño years compared with La Niña years. Moreover, regions with more intense precipitation are more sensitive to ENSO. Global climate models were used to investigate the changing relationship between extreme precipitation and the covariates. The risk of extreme, high-intensity precipitation increases across high latitudes of the Northern Hemisphere but decreases in middle and lower latitudes under a warming climate scenario, and will likely trigger increases in severe flooding and droughts across the globe. However, there is some uncertainties associated with the influence of ENSO on predictions of future extreme precipitation, with the spatial extent and risk varying among the different models.
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Toreti, A.; Xoplaki, E.; Maraun, D.; Kuglitsch, F. G.; Wanner, H.; Luterbacher, J.
2010-05-01
We present an analysis of daily extreme precipitation events for the extended winter season (October-March) at 20 Mediterranean coastal sites covering the period 1950-2006. The heavy tailed behaviour of precipitation extremes and estimated return levels, including associated uncertainties, are derived applying a procedure based on the Generalized Pareto Distribution, in combination with recently developed methods. Precipitation extremes have an important contribution to make seasonal totals (approximately 60% for all series). Three stations (one in the western Mediterranean and the others in the eastern basin) have a 5-year return level above 100 mm, while the lowest value (estimated for two Italian series) is equal to 58 mm. As for the 50-year return level, an Italian station (Genoa) has the highest value of 264 mm, while the other values range from 82 to 200 mm. Furthermore, six series (from stations located in France, Italy, Greece, and Cyprus) show a significant negative tendency in the probability of observing an extreme event. The relationship between extreme precipitation events and the large scale atmospheric circulation at the upper, mid and low troposphere is investigated by using NCEP/NCAR reanalysis data. A 2-step classification procedure identifies three significant anomaly patterns both for the western-central and eastern part of the Mediterranean basin. In the western Mediterranean, the anomalous southwesterly surface to mid-tropospheric flow is connected with enhanced moisture transport from the Atlantic. During ≥5-year return level events, the subtropical jet stream axis is aligned with the African coastline and interacts with the eddy-driven jet stream. This is connected with enhanced large scale ascending motions, instability and leads to the development of severe precipitation events. For the eastern Mediterranean extreme precipitation events, the identified anomaly patterns suggest warm air advection connected with anomalous ascent motions
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Directory of Open Access Journals (Sweden)
A. Toreti
2010-05-01
Full Text Available We present an analysis of daily extreme precipitation events for the extended winter season (October–March at 20 Mediterranean coastal sites covering the period 1950–2006. The heavy tailed behaviour of precipitation extremes and estimated return levels, including associated uncertainties, are derived applying a procedure based on the Generalized Pareto Distribution, in combination with recently developed methods. Precipitation extremes have an important contribution to make seasonal totals (approximately 60% for all series. Three stations (one in the western Mediterranean and the others in the eastern basin have a 5-year return level above 100 mm, while the lowest value (estimated for two Italian series is equal to 58 mm. As for the 50-year return level, an Italian station (Genoa has the highest value of 264 mm, while the other values range from 82 to 200 mm. Furthermore, six series (from stations located in France, Italy, Greece, and Cyprus show a significant negative tendency in the probability of observing an extreme event. The relationship between extreme precipitation events and the large scale atmospheric circulation at the upper, mid and low troposphere is investigated by using NCEP/NCAR reanalysis data. A 2-step classification procedure identifies three significant anomaly patterns both for the western-central and eastern part of the Mediterranean basin. In the western Mediterranean, the anomalous southwesterly surface to mid-tropospheric flow is connected with enhanced moisture transport from the Atlantic. During ≥5-year return level events, the subtropical jet stream axis is aligned with the African coastline and interacts with the eddy-driven jet stream. This is connected with enhanced large scale ascending motions, instability and leads to the development of severe precipitation events. For the eastern Mediterranean extreme precipitation events, the identified anomaly patterns suggest warm air advection connected with anomalous
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Future Projection of Summer Extreme Precipitation from High Resolution Multi-RCMs over East Asia
Kim, Gayoung; Park, Changyong; Cha, Dong-Hyun; Lee, Dong-Kyou; Suh, Myoung-Seok; Ahn, Joong-Bae; Min, Seung-Ki; Hong, Song-You; Kang, Hyun-Suk
2017-04-01
Recently, the frequency and intensity of natural hazards have been increasing due to human-induced climate change. Because most damages of natural hazards over East Asia have been related to extreme precipitation events, it is important to estimate future change in extreme precipitation characteristics caused by climate change. We investigate future changes in extremal values of summer precipitation simulated by five regional climate models participating in the CORDEX-East Asia project (i.e., HadGEM3-RA, RegCM4, MM5, WRF, and GRIMs) over East Asia. 100-year return value calculated from the generalized extreme value (GEV) parameters is analysed as an indicator of extreme intensity. In the future climate, the mean values as well as the extreme values of daily precipitation tend to increase over land region. The increase of 100-year return value can be significantly associated with the changes in the location (intensity) and scale (variability) GEV parameters for extreme precipitation. It is expected that the results of this study can be used as fruitful references when making the policy of disaster management. Acknowledgements The research was supported by the Ministry of Public Safety and Security of Korean government and Development program under grant MPSS-NH-2013-63 and the National Research Foundation of Korea Grant funded by the Ministry of Science, ICT and Future Planning of Korea (NRF-2016M3C4A7952637) for its support and assistant in completion of the study.
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Li, Zhen; Yan, Zhongwei; Tu, Kai; Wu, Hongyi
2015-09-01
Daily precipitation series at 15 stations in the Beijing metropolitan region (BMR) during 1960-2012 were homogenized using the multiple analysis of series for homogenization method, with additional adjustments based on analysis of empirical cumulative density function (ECDF) regarding climate extremes. The cumulative density functions of daily precipitation series, the trends of annual and seasonal precipitation, and summer extreme events during 1960-2012 in the original and final adjusted series at Beijing station were comparatively analyzed to show the necessity and efficiency of the new method. Results indicate that the ECDF adjustments can improve the homogeneity of high-order moments of daily series and the estimation of climate trends in extremes. The linear trends of the regional-mean annual and seasonal (spring, summer, autumn, and winter) precipitation series are -10.16, 4.97, -20.04, 5.02, and -0.11 mm (10 yr)-1, respectively. The trends over the BMR increase consistently for spring/autumn and decrease for the whole year/summer; however, the trends for winter decrease in southern parts and increase in northern parts. Urbanization affects local trends of precipitation amount, frequency, and intensity and their geographical patterns. For the urban-influenced sites, urbanization tends to slow down the magnitude of decrease in the precipitation and extreme amount series by approximately -10.4% and -6.0%, respectively; enhance the magnitude of decrease in precipitation frequency series by approximately 5.7%; reduce that of extremes by approximately -8.9%; and promote the decreasing trends in the summer intensity series of both precipitation and extremes by approximately 6.8% and 51.5%, respectively.
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Czech Academy of Sciences Publication Activity Database
Hanel, M.; Pavlásková, A.; Kyselý, Jan
2016-01-01
Roč. 36, č. 4 (2016), s. 1833-1845 ISSN 0899-8418 Institutional support: RVO:67179843 Keywords : sub-daily precipitation * fainfall events * erosivity * extremes * climate variability * Central Europe Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 3.760, year: 2016
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Floridian heatwaves and extreme precipitation: future climate projections
Raghavendra, Ajay; Dai, Aiguo; Milrad, Shawn M.; Cloutier-Bisbee, Shealynn R.
2018-02-01
Observational analysis and climate modeling efforts concur that the frequency, intensity, and duration of heatwaves will increase as the Earth's mean climate shifts towards warmer temperatures. While the impacts and mechanisms of heatwaves have been well explored, extreme temperatures over Florida are generally understudied. This paper sheds light on Floridian heatwaves by exploring 13 years of daily data from surface observations and high-resolution WRF climate simulations for the same timeframe. The characteristics of the current and future heatwaves under the RCP8.5 high emissions scenario for 2070-2099 were then investigated. Results show a tripling in the frequency, and greater than a sixfold increase in the mean duration of heatwaves over Florida when the current standard of heatwaves was used. The intensity of heatwaves also increased by 4-6 °C due to the combined effects of rising mean temperatures and a 1-2 °C increase attributed to the flattening of the temperature distribution. Since Florida's atmospheric boundary layer is rich in moisture and heatwaves could further increase the moisture content in the lower troposphere, the relationship between heatwaves and extreme precipitation was also explored in both the current and future climate. As expected, rainfall during a heatwave event was anomalously low, but it quickly recovered to normal within 3 days after the passage of a heatwave. Finally, the late 21st-century climate could witness a slight decrease in the mean precipitation over Florida, accompanied by heavier heatwave-associated extreme precipitation events over central and southern Florida.
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Large Scale Influences on Summertime Extreme Precipitation in the Northeastern United States
Collow, Allison B. Marquardt; Bosilovich, Michael G.; Koster, Randal Dean
2016-01-01
Observations indicate that over the last few decades there has been a statistically significant increase in precipitation in the northeastern United States and that this can be attributed to an increase in precipitation associated with extreme precipitation events. Here a state-of-the-art atmospheric reanalysis is used to examine such events in detail. Daily extreme precipitation events defined at the 75th and 95th percentile from gridded gauge observations are identified for a selected region within the Northeast. Atmospheric variables from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), are then composited during these events to illustrate the time evolution of associated synoptic structures, with a focus on vertically integrated water vapor fluxes, sea level pressure, and 500-hectopascal heights. Anomalies of these fields move into the region from the northwest, with stronger anomalies present in the 95th percentile case. Although previous studies show tropical cyclones are responsible for the most intense extreme precipitation events, only 10 percent of the events in this study are caused by tropical cyclones. On the other hand, extreme events resulting from cutoff low pressure systems have increased. The time period of the study was divided in half to determine how the mean composite has changed over time. An arc of lower sea level pressure along the East Coast and a change in the vertical profile of equivalent potential temperature suggest a possible increase in the frequency or intensity of synoptic-scale baroclinic disturbances.
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Severson, R. L.; Peng, R. D.; Anderson, G. B.
2017-12-01
There is substantial evidence that extreme precipitation and flooding are serious threats to public health and safety. These threats are predicted to increase with climate change. Epidemiological studies investigating the health effects of these events vary in the methods used to characterize exposure. Here, we compare two sources of precipitation data (National Oceanic and Atmospheric Administration (NOAA) station-based and North American Land Data Assimilation Systems (NLDAS-2) Reanalysis data-based) for estimating exposure to extreme precipitation and two sources of flooding data, based on United States Geological Survey (USGS) streamflow gages and the NOAA Storm Events database. We investigate associations between each of the four exposure metrics and short-term risk of four causes of mortality (accidental, respiratory-related, cardiovascular-related, and all-cause) in the United States from 1987 through 2005. Average daily precipitation values from the two precipitation data sources were moderately correlated (Spearman's rho = 0.74); however, values from the two data sources were less correlated when comparing binary metrics of exposure to extreme precipitation days (Jaccard index (J) = 0.35). Binary metrics of daily flood exposure were poorly correlated between the two flood data sources (Spearman's rho = 0.07; J = 0.05). There was little correlation between extreme precipitation exposure and flood exposure in study communities. We did not observe evidence of a positive association between any of the four exposure metrics and risk of any of the four mortality outcomes considered. Our results suggest, due to the observed lack of agreement between different extreme precipitation and flood metrics, that exposure to extreme precipitation may not serve as an effective surrogate for exposures related to flooding. Furthermore, It is possible that extreme precipitation and flood exposures may often be too localized to allow accurate exposure assessment at the
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Relating precipitation to fronts at a sub-daily basis
Hénin, Riccardo; Ramos, Alexandre M.; Liberato, Margarida L. R.; Gouveia, Célia
2017-04-01
.M. Trigo and M.L.R. Liberato (2014) A ranking of high-resolution daily precipitation extreme events for the Iberian Peninsula, Atmospheric Science Letters 15, 328 - 334. doi: 10.1002/asl2.507. Shemm S., I. Rudeva and I. Simmonds (2014) Extratropical fronts in the lower troposphere - global perspectives obtained from two automated methods. Quarterly Journal of the Royal Meteorological Society, 141: 1686-1698, doi: 10.1002/qj.2471. ACKNOWLEDGEMENTS This work is supported by FCT - project UID/GEO/50019/2013 - Instituto Dom Luiz. Fundação para a Ciência e a Tecnologia, Portugal (FCT) is also providing for R. Hénin doctoral grant (PD/BD/114479/2016) and A.M. Ramos postdoctoral grant (FCT/DFRH/SFRH/BPD/84328/2012).
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Is southwestern China experiencing more frequent precipitation extremes?
International Nuclear Information System (INIS)
Liu, Meixian; Xu, Xianli; Wang, Kelin; Sun, Alexander Y; Liu, Wen; Zhang, Xiaoyan
2014-01-01
Climate extremes have and will continue to cause severe damages to buildings and natural environments around the world. A full knowledge of the probability of the climate extremes is important for the management and mitigation of natural hazards. Based on Mann–Kendall trend test and copulas, this study investigated the characteristics of precipitation extremes as well as their implications in southwestern China (Yunnan, Guangxi and Guizhou Province), through analyzing the changing trends and probabilistic characteristics of six indices, including the consecutive dry days, consecutive wet days, annual total wet day precipitation, heavy precipitation days (R25), max 5 day precipitation amount (Rx5) and the rainy days (RDs). Results showed that the study area had generally become drier (regional mean annual precipitation decreased by 11.4 mm per decade) and experienced enhanced precipitation extremes in the past 60 years. Relatively higher risk of drought in Yuanan and flood in Guangxi was observed, respectively. However, the changing trends of the precipitation extremes were not spatially uniform: increasing risk of extreme wet events for Guangxi and Guizhou, and increasing probability of concurrent extreme wet and dry events for Yunnan. Meanwhile, trend analyses of the 10 year return levels of the selected indices implied that the severity of droughts decreased in Yunnan but increased significantly in Guangxi and Guizhou, and the severity of floods increased in Yunnan and Guangxi in the past decades. Hence, the policy-makers need to be aware of the different characterizations and the spatial heterogeneity of the precipitation extremes. (letters)
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Estimation of the impact of climate change-induced extreme precipitation events on floods
Hlavčová, Kamila; Lapin, Milan; Valent, Peter; Szolgay, Ján; Kohnová, Silvia; Rončák, Peter
2015-09-01
In order to estimate possible changes in the flood regime in the mountainous regions of Slovakia, a simple physically-based concept for climate change-induced changes in extreme 5-day precipitation totals is proposed in the paper. It utilizes regionally downscaled scenarios of the long-term monthly means of the air temperature, specific air humidity and precipitation projected for Central Slovakia by two regional (RCM) and two global circulation models (GCM). A simplified physically-based model for the calculation of short-term precipitation totals over the course of changing air temperatures, which is used to drive a conceptual rainfall-runoff model, was proposed. In the paper a case study of this approach in the upper Hron river basin in Central Slovakia is presented. From the 1981-2010 period, 20 events of the basin's most extreme average of 5-day precipitation totals were selected. Only events with continual precipitation during 5 days were considered. These 5-day precipitation totals were modified according to the RCM and GCM-based scenarios for the future time horizons of 2025, 2050 and 2075. For modelling runoff under changed 5-day precipitation totals, a conceptual rainfall-runoff model developed at the Slovak University of Technology was used. Changes in extreme mean daily discharges due to climate change were compared with the original flood events and discussed.
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Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.
2017-12-01
Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic
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Wilcox, Kevin R; Shi, Zheng; Gherardi, Laureano A; Lemoine, Nathan P; Koerner, Sally E; Hoover, David L; Bork, Edward; Byrne, Kerry M; Cahill, James; Collins, Scott L; Evans, Sarah; Gilgen, Anna K; Holub, Petr; Jiang, Lifen; Knapp, Alan K; LeCain, Daniel; Liang, Junyi; Garcia-Palacios, Pablo; Peñuelas, Josep; Pockman, William T; Smith, Melinda D; Sun, Shanghua; White, Shannon R; Yahdjian, Laura; Zhu, Kai; Luo, Yiqi
2017-10-01
Climatic changes are altering Earth's hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitation changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. We used meta-analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. This highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into future climate change
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Contributions of natural climate changes and human activities to the trend of extreme precipitation
Gao, Lu; Huang, Jie; Chen, Xingwei; Chen, Ying; Liu, Meibing
2018-06-01
This study focuses on the analysis of the nonstationarity characteristics of extreme precipitation and their attributions in the southeastern coastal region of China. The maximum daily precipitation (MDP) series is extracted from observations at 79 meteorological stations in the study area during the first flood season (April-June) from 1960 to 2012. The trends of the mean (Mn) and variance (Var) of MDP are detected using the Generalized Additive Models for Location, Scale, and Shape parameters (GAMLSS) and Mann-Kendall test. The contributions of natural climate change and human activities to the Mn and Var changes of MDP are investigated using six large-scale circulation variables and emissions of four greenhouse gases based on GAMLSS and a contribution analysis method. The results demonstrate that the nonstationarity of extreme precipitation on local scales is significant. The Mn and Var of extreme precipitation increase in the north of Zhejiang, the middle of Fujian, and the south of Guangdong. In general, natural climate change contributes more to Mn from 1960 to 2012 than to Var. However, human activities cause a greater Var in the rapid socioeconomic development period (1986-2012) than in the slow socioeconomic development period (1960-1985), especially in Zhejiang and Guangdong. The community should pay more attention to the possibility of extreme precipitation events and associated disasters triggered by human activities.
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Improving the Statistical Modeling of the TRMM Extreme Precipitation Monitoring System
Demirdjian, L.; Zhou, Y.; Huffman, G. J.
2016-12-01
This project improves upon an existing extreme precipitation monitoring system based on the Tropical Rainfall Measuring Mission (TRMM) daily product (3B42) using new statistical models. The proposed system utilizes a regional modeling approach, where data from similar grid locations are pooled to increase the quality and stability of the resulting model parameter estimates to compensate for the short data record. The regional frequency analysis is divided into two stages. In the first stage, the region defined by the TRMM measurements is partitioned into approximately 27,000 non-overlapping clusters using a recursive k-means clustering scheme. In the second stage, a statistical model is used to characterize the extreme precipitation events occurring in each cluster. Instead of utilizing the block-maxima approach used in the existing system, where annual maxima are fit to the Generalized Extreme Value (GEV) probability distribution at each cluster separately, the present work adopts the peak-over-threshold (POT) method of classifying points as extreme if they exceed a pre-specified threshold. Theoretical considerations motivate the use of the Generalized-Pareto (GP) distribution for fitting threshold exceedances. The fitted parameters can be used to construct simple and intuitive average recurrence interval (ARI) maps which reveal how rare a particular precipitation event is given its spatial location. The new methodology eliminates much of the random noise that was produced by the existing models due to a short data record, producing more reasonable ARI maps when compared with NOAA's long-term Climate Prediction Center (CPC) ground based observations. The resulting ARI maps can be useful for disaster preparation, warning, and management, as well as increased public awareness of the severity of precipitation events. Furthermore, the proposed methodology can be applied to various other extreme climate records.
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Extreme precipitation events in the Iberian Peninsula and its association with Atmospheric Rivers
Ramos, Alexandre M.; Liberato, Margarida L. R.; Trigo, Ricardo M.
2015-04-01
, Minho, Tagus and Duero) is noteworthy, while for the eastern and southern basins (Ebro, Guadiana and Guadalquivir) the impact of ARs is reduced. In addition, meteorological large scale influence associated with ARs was also analyzed. The anomalies between the extended winter (ONDJFM) long term mean and the composite for the persistent ARs time steps were computed for the IVT and SLP fields. Negative SLP anomalies are found centered in Ireland with slight positive anomalies of SLP located over northern Africa. It was found that the ARs hitting the IP are strongly correlated with the EA pattern, while the influence of other patterns such as the NAO or SCAND is weak. Main results presented are currently in print (Ramos et al., 2015) Ramos et al (2014), A ranking of high-resolution daily precipitation extreme events for the Iberian Peninsula. Atmospheric Science Letters, doi: 10.1002/asl2.507. Ramos et al. (2015), Daily precipitation extreme events in the Iberian Peninsula and its association with Atmospheric Rivers. Journal Hydrometeorology, in press. This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa Operacional Factores de Competitividade) and by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project STORMEx FCOMP-01-0124-FEDER-019524 (PTDC/AAC-CLI/121339/2010). A. M. Ramos was also supported by a FCT postdoctoral grant (FCT/DFRH/SFRH/BPD/84328/2012).
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Barbero, Renaud; Abatzoglou, John T.; Fowler, Hayley J.
2018-02-01
Midlatitude synoptic weather regimes account for a substantial portion of annual precipitation accumulation as well as multi-day precipitation extremes across parts of the United States (US). However, little attention has been devoted to understanding how synoptic-scale patterns contribute to hourly precipitation extremes. A majority of 1-h annual maximum precipitation (AMP) across the western US were found to be linked to two coherent midlatitude synoptic patterns: disturbances propagating along the jet stream, and cutoff upper-level lows. The influence of these two patterns on 1-h AMP varies geographically. Over 95% of 1-h AMP along the western coastal US were coincident with progressive midlatitude waves embedded within the jet stream, while over 30% of 1-h AMP across the interior western US were coincident with cutoff lows. Between 30-60% of 1-h AMP were coincident with the jet stream across the Ohio River Valley and southeastern US, whereas a a majority of 1-h AMP over the rest of central and eastern US were not found to be associated with either midlatitude synoptic features. Composite analyses for 1-h AMP days coincident to cutoff lows and jet stream show that an anomalous moisture flux and upper-level dynamics are responsible for initiating instability and setting up an environment conducive to 1-h AMP events. While hourly precipitation extremes are generally thought to be purely convective in nature, this study shows that large-scale dynamics and baroclinic disturbances may also contribute to precipitation extremes on sub-daily timescales.
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International Nuclear Information System (INIS)
Yu, Lejiang; Zhong, Shiyuan; Pei, Lisi; Bian, Xindi; Heilman, Warren E
2016-01-01
The mean global climate has warmed as a result of the increasing emission of greenhouse gases induced by human activities. This warming is considered the main reason for the increasing number of extreme precipitation events in the US. While much attention has been given to extreme precipitation events occurring over several days, which are usually responsible for severe flooding over a large region, little is known about how extreme precipitation events that cause flash flooding and occur at sub-daily time scales have changed over time. Here we use the observed hourly precipitation from the North American Land Data Assimilation System Phase 2 forcing datasets to determine trends in the frequency of extreme precipitation events of short (1 h, 3 h, 6 h, 12 h and 24 h) duration for the period 1979–2013. The results indicate an increasing trend in the central and eastern US. Over most of the western US, especially the Southwest and the Intermountain West, the trends are generally negative. These trends can be largely explained by the interdecadal variability of the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation (AMO), with the AMO making a greater contribution to the trends in both warm and cold seasons. (letter)
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Directory of Open Access Journals (Sweden)
Susanne Pfeifer
2015-05-01
Full Text Available Climate signal maps can be used to identify regions where robust climate changes can be derived from an ensemble of climate change simulations. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Climate signal maps do not show all information available from the model ensemble, but give a condensed view in order to be useful for non-climate scientists who have to assess climate change impact during the course of their work. Three different ensembles of regional climate projections have been analyzed regarding changes of seasonal mean and extreme precipitation (defined as the number of days exceeding the 95th percentile threshold of daily precipitation for Germany, using climate signal maps. Although the models used and the scenario assumptions differ for the three ensembles (representative concentration pathway (RCP 4.5 vs. RCP8.5 vs. A1B, some similarities in the projections of future seasonal and extreme precipitation can be seen. For the winter season, both mean and extreme precipitation are projected to increase. The strength, robustness and regional pattern of this increase, however, depends on the ensemble. For summer, a robust decrease of mean precipitation can be detected only for small regions in southwestern Germany and only from two of the three ensembles, whereas none of them projects a robust increase of summer extreme precipitation.
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Characteristics of storms that contribute to extreme precipitation events over the Iberian Peninsula
Trigo, Ricardo; Ramos, Alexandre M.; Ordoñez, Paulina; Liberato, Margarida L. R.; Trigo, Isabel F.
2014-05-01
Floods correspond to one of the most deadly natural disasters in the Iberian Peninsula during the last century. Quite often these floods are associated to intense low pressure systems with an Atlantic origin. In recent years a number of episodes have been evaluated on a case-by-case approach, with a clear focus on extreme events, thus lacking a systematic assessment. In this study we focus on the characteristics of storms for the extended winter season (October to March) that are responsible for the most extreme rainfall events over large areas of the Iberian Peninsula. An objective method for ranking daily precipitation events during the extended winter is used based on the most comprehensive database of high resolution (0.2º latitude by 0.2º longitude) gridded daily precipitation dataset available for the Iberian Peninsula. The magnitude of an event is obtained after considering the total area affected as well as its intensity in every grid point (taking into account the daily normalised departure from climatology). Different precipitation rankings are studied considering the entire Iberian Peninsula, Portugal and also the six largest river basins in the Iberian Peninsula (Duero, Ebro, Tagus, Minho, Guadiana and Guadalquivir). Using an objective cyclone detecting and tracking scheme [Trigo, 2006] the storm track and characteristics of the cyclones were obtained using the ERA-Interim reanalyses for the 1979-2008 period. The spatial distribution of extratropical cyclone positions when the precipitation extremes occur will be analysed over the considered sub-domains (Iberia, Portugal, major river basins). In addition, we distinguish the different cyclone characteristics (lifetime, direction, minimum pressure, position, velocity, vorticity and radius) with significant impacts in precipitation over the different domains in the Iberian Peninsula. This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa
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Evaluation of satellite-retrieved extreme precipitation using gauge observations
Lockhoff, M.; Zolina, O.; Simmer, C.; Schulz, J.
2012-04-01
Precipitation extremes have already been intensively studied employing rain gauge datasets. Their main advantage is that they represent a direct measurement with a relatively high temporal coverage. Their main limitation however is their poor spatial coverage and thus a low representativeness in many parts of the world. In contrast, satellites can provide global coverage and there are meanwhile data sets available that are on one hand long enough to be used for extreme value analysis and that have on the other hand the necessary spatial and temporal resolution to capture extremes. However, satellite observations provide only an indirect mean to determine precipitation and there are many potential observational and methodological weaknesses in particular over land surfaces that may constitute doubts concerning their usability for the analysis of precipitation extremes. By comparing basic climatological metrics of precipitation (totals, intensities, number of wet days) as well as respective characteristics of PDFs, absolute and relative extremes of satellite and observational data this paper aims at assessing to which extent satellite products are suitable for analysing extreme precipitation events. In a first step the assessment focuses on Europe taking into consideration various satellite products available, e.g. data sets provided by the Global Precipitation Climatology Project (GPCP). First results indicate that satellite-based estimates do not only represent the monthly averaged precipitation very similar to rain gauge estimates but they also capture the day-to-day occurrence fairly well. Larger differences can be found though when looking at the corresponding intensities.
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Santo, Fátima E.; Ramos, Alexandre M.; de Lima, M. Isabel P.; Trigo, Ricardo M.
2013-04-01
Changes in the precipitation regimes are expected to be accompanied by variations in the occurrence of extreme events, which in turn could be related to low frequency variability. The impact on the society and environment requires that the regional specificities are understood. For mainland Portugal, this work reports the results of the analysis of trends in selected precipitation indices calculated from daily precipitation data from 57 meteorological stations, recorded in the period 1941-2007; additionally we have also investigated the correlations between these indices and several modes of low frequency variability over the area. We focus on exploring regional differences and seasonal variations in the intensity, frequency and duration of extreme precipitation events. The precipitation indices were assessed at the seasonal scale and calculated at both the station and regional scales. Results sometimes highlight marked changes in seasonal precipitation and show that: i) trends in spring and autumn have opposite signals: statistically significant drying trends in the spring are accompanied by a reduction in precipitation extremes; in autumn, wetting trends are detected for all precipitation indices, although overall they are not significant at the 5% level; ii) there seems to be a tendency for a reduction in the duration of the rainy season; iii) the North Atlantic Oscillation (NAO) is the mode of variability that has the highest influence on precipitation extremes over mainland Portugal, particularly in the winter and autumn, and is one of the most important teleconnection patterns in all seasons. This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa Operacional Factores de Competitividade) and by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) through project STORMEx FCOMP-01-0124-FEDER-019524 (PTDC/AAC-CLI/121339/2010).
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Baisden, W Troy; Keller, Elizabeth D; Van Hale, Robert; Frew, Russell D; Wassenaar, Leonard I
2016-01-01
Predictive understanding of precipitation δ(2)H and δ(18)O in New Zealand faces unique challenges, including high spatial variability in precipitation amounts, alternation between subtropical and sub-Antarctic precipitation sources, and a compressed latitudinal range of 34 to 47 °S. To map the precipitation isotope ratios across New Zealand, three years of integrated monthly precipitation samples were acquired from >50 stations. Conventional mean-annual precipitation δ(2)H and δ(18)O maps were produced by regressions using geographic and annual climate variables. Incomplete data and short-term variation in climate and precipitation sources limited the utility of this approach. We overcome these difficulties by calculating precipitation-weighted monthly climate parameters using national 5-km-gridded daily climate data. This data plus geographic variables were regressed to predict δ(2)H, δ(18)O, and d-excess at all sites. The procedure yields statistically-valid predictions of the isotope composition of precipitation (long-term average root mean square error (RMSE) for δ(18)O = 0.6 ‰; δ(2)H = 5.5 ‰); and monthly RMSE δ(18)O = 1.9 ‰, δ(2)H = 16 ‰. This approach has substantial benefits for studies that require the isotope composition of precipitation during specific time intervals, and may be further improved by comparison to daily and event-based precipitation samples as well as the use of back-trajectory calculations.
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Czech Academy of Sciences Publication Activity Database
Hanel, M.; Pavlásková, A.; Kyselý, Jan
2016-01-01
Roč. 36, č. 4 (2016), s. 1833-1845 ISSN 0899-8418 R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : sub-daily precipitation * rainfall events * erosivity * extremes * climate variability * Central Europe Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 3.760, year: 2016 http://onlinelibrary.wiley.com/doi/10.1002/joc.4463/abstract
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Diaconescu, Emilia Paula; Mailhot, Alain; Brown, Ross; Chaumont, Diane
2018-03-01
This study focuses on the evaluation of daily precipitation and temperature climate indices and extremes simulated by an ensemble of 12 Regional Climate Model (RCM) simulations from the ARCTIC-CORDEX experiment with surface observations in the Canadian Arctic from the Adjusted Historical Canadian Climate Dataset. Five global reanalyses products (ERA-Interim, JRA55, MERRA, CFSR and GMFD) are also included in the evaluation to assess their potential for RCM evaluation in data sparse regions. The study evaluated the means and annual anomaly distributions of indices over the 1980-2004 dataset overlap period. The results showed that RCM and reanalysis performance varied with the climate variables being evaluated. Most RCMs and reanalyses were able to simulate well climate indices related to mean air temperature and hot extremes over most of the Canadian Arctic, with the exception of the Yukon region where models displayed the largest biases related to topographic effects. Overall performance was generally poor for indices related to cold extremes. Likewise, only a few RCM simulations and reanalyses were able to provide realistic simulations of precipitation extreme indicators. The multi-reanalysis ensemble provided superior results to individual datasets for climate indicators related to mean air temperature and hot extremes, but not for other indicators. These results support the use of reanalyses as reference datasets for the evaluation of RCM mean air temperature and hot extremes over northern Canada, but not for cold extremes and precipitation indices.
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Nissen, Katrin; Ulbrich, Uwe
2016-04-01
An event based detection algorithm for extreme precipitation is applied to a multi-model ensemble of regional climate model simulations. The algorithm determines extent, location, duration and severity of extreme precipitation events. We assume that precipitation in excess of the local present-day 10-year return value will potentially exceed the capacity of the drainage systems that protect critical infrastructure elements. This assumption is based on legislation for the design of drainage systems which is in place in many European countries. Thus, events exceeding the local 10-year return value are detected. In this study we distinguish between sub-daily events (3 hourly) with high precipitation intensities and long-duration events (1-3 days) with high precipitation amounts. The climate change simulations investigated here were conducted within the EURO-CORDEX framework and exhibit a horizontal resolution of approximately 12.5 km. The period between 1971-2100 forced with observed and scenario (RCP 8.5 and RCP 4.5) greenhouse gas concentrations was analysed. Examined are changes in event frequency, event duration and size. The simulations show an increase in the number of extreme precipitation events for the future climate period over most of the area, which is strongest in Northern Europe. Strength and statistical significance of the signal increase with increasing greenhouse gas concentrations. This work has been conducted within the EU project RAIN (Risk Analysis of Infrastructure Networks in response to extreme weather).
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Intensity changes in future extreme precipitation: A statistical event-based approach.
Manola, Iris; van den Hurk, Bart; de Moel, Hans; Aerts, Jeroen
2017-04-01
Short-lived precipitation extremes are often responsible for hazards in urban and rural environments with economic and environmental consequences. The precipitation intensity is expected to increase about 7% per degree of warming, according to the Clausius-Clapeyron (CC) relation. However, the observations often show a much stronger increase in the sub-daily values. In particular, the behavior of the hourly summer precipitation from radar observations with the dew point temperature (the Pi-Td relation) for the Netherlands suggests that for moderate to warm days the intensification of the precipitation can be even higher than 21% per degree of warming, that is 3 times higher than the expected CC relation. The rate of change depends on the initial precipitation intensity, as low percentiles increase with a rate below CC, the medium percentiles with 2CC and the moderate-high and high percentiles with 3CC. This non-linear statistical Pi-Td relation is suggested to be used as a delta-transformation to project how a historic extreme precipitation event would intensify under future, warmer conditions. Here, the Pi-Td relation is applied over a selected historic extreme precipitation event to 'up-scale' its intensity to warmer conditions. Additionally, the selected historic event is simulated in the high-resolution, convective-permitting weather model Harmonie. The initial and boundary conditions are alternated to represent future conditions. The comparison between the statistical and the numerical method of projecting the historic event to future conditions showed comparable intensity changes, which depending on the initial percentile intensity, range from below CC to a 3CC rate of change per degree of warming. The model tends to overestimate the future intensities for the low- and the very high percentiles and the clouds are somewhat displaced, due to small wind and convection changes. The total spatial cloud coverage in the model remains, as also in the statistical
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Prat, O. P.; Nelson, B. R.
2015-04-01
We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.
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Odenweller, Adrian; Donner, Reik V.
2017-04-01
Over the last decade, complex network methods have been frequently used for characterizing spatio-temporal patterns of climate variability from a complex systems perspective, yielding new insights into time-dependent teleconnectivity patterns and couplings between different components of the Earth climate. Among the foremost results reported, network analyses of the synchronicity of extreme events as captured by the so-called event synchronization have been proposed to be powerful tools for disentangling the spatio-temporal organization of particularly extreme rainfall events and anticipating the timing of monsoon onsets or extreme floodings. Rooted in the analysis of spike train synchrony analysis in the neurosciences, event synchronization has the great advantage of automatically classifying pairs of events arising at two distinct spatial locations as temporally close (and, thus, possibly statistically - or even dynamically - interrelated) or not without the necessity of selecting an additional parameter in terms of a maximally tolerable delay between these events. This consideration is conceptually justified in case of the original application to spike trains in electroencephalogram (EEG) recordings, where the inter-spike intervals show relatively narrow distributions at high temporal sampling rates. However, in case of climate studies, precipitation extremes defined by daily precipitation sums exceeding a certain empirical percentile of their local distribution exhibit a distinctively different type of distribution of waiting times between subsequent events. This raises conceptual concerns if event synchronization is still appropriate for detecting interlinkages between spatially distributed precipitation extremes. In order to study this problem in more detail, we employ event synchronization together with an alternative similarity measure for event sequences, event coincidence rates, which requires a manual setting of the tolerable maximum delay between two
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Predictability and possible earlier awareness of extreme precipitation across Europe
Lavers, David; Pappenberger, Florian; Richardson, David; Zsoter, Ervin
2017-04-01
Extreme hydrological events can cause large socioeconomic damages in Europe. In winter, a large proportion of these flood episodes are associated with atmospheric rivers, a region of intense water vapour transport within the warm sector of extratropical cyclones. When preparing for such extreme events, forecasts of precipitation from numerical weather prediction models or river discharge forecasts from hydrological models are generally used. Given the strong link between water vapour transport (integrated vapour transport IVT) and heavy precipitation, it is possible that IVT could be used to warn of extreme events. Furthermore, as IVT is located in extratropical cyclones, it is hypothesized to be a more predictable variable due to its link with synoptic-scale atmospheric dynamics. In this research, we firstly provide an overview of the predictability of IVT and precipitation forecasts, and secondly introduce and evaluate the ECMWF Extreme Forecast Index (EFI) for IVT. The EFI is a tool that has been developed to evaluate how ensemble forecasts differ from the model climate, thus revealing the extremeness of the forecast. The ability of the IVT EFI to capture extreme precipitation across Europe during winter 2013/14, 2014/15, and 2015/16 is presented. The results show that the IVT EFI is more capable than the precipitation EFI of identifying extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase. However, the precipitation EFI is superior during the negative NAO phase and at shorter lead times. An IVT EFI example is shown for storm Desmond in December 2015 highlighting its potential to identify upcoming hydrometeorological extremes.
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Changing precipitation extremes and flood risk over the conterminous U.S.
Lettenmaier, D. P.
2017-12-01
On the basis of first principles, precipitation extremes should increase in a warming climate. Effectively, the atmospheric "heat engine" is expected to turn over more rapidly as the climate warms, due to increased water holding capacity of the atmosphere. Most climate models reflect this behavior, and project that precipitation extremes should increase, at roughly the Clausius-Clapyron rate. From a societal standpoint though, changing precipitation extremes in and of themselves aren't necessarily a concern - rather, the question of societal interest is "are and/or will flood extremes change". Flood extremes of course respond to precipitation extremes, but they are affected by a number of other factors, among them being the duration of precipitation relative to catchment size and channel features, storm orientation relative to catchment orientation, soil characteristics, and antecedent hydrologic conditions. Various studies have shown that over both the conterminous U.S. and globally, there have been slight increases in precipitation extremes (i.e., more than would be expected due to chance. On the other hand, evidence for increases in flooding are less pervasive. I review past work in this area, and suggest the nature of studies that might be conducted going forward to better understand the likely signature of changing precipitation extremes on flooding.
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Wu, Huey-Tzu Jenny; Lau, William K.-M.
2016-01-01
We investigate changes in daily precipitation extremes using Tropical Rainfall Measuring Mission (TRMM) data (1998-2013), which coincides with the "global warming hiatus." Results show a change in probability distribution functions of local precipitation events (LPEs) during this period consistent with previous global warming studies, indicating increasing contrast between wet and dry extremes, with more intense LPE, less moderate LPE, and more dry (no rain) days globally. Analyses for land and ocean separately reveal more complex and nuanced changes over land, characterized by a strong positive trend (+12.0% per decade, 99% confidence level (c.l.)) in frequency of extreme LPEs over the Northern Hemisphere extratropics during the wet season but a negative global trend (-6.6% per decade, 95% c.l.) during the dry season. A significant global drying trend (3.2% per decade, 99% c.l.) over land is also found during the dry season. Regions of pronounced increased dry events include western and central U.S., northeastern Asia, and Southern Europe/Mediterranean.
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Computation of rainfall erosivity from daily precipitation amounts.
Beguería, Santiago; Serrano-Notivoli, Roberto; Tomas-Burguera, Miquel
2018-10-01
Rainfall erosivity is an important parameter in many erosion models, and the EI30 defined by the Universal Soil Loss Equation is one of the best known erosivity indices. One issue with this and other erosivity indices is that they require continuous breakpoint, or high frequency time interval, precipitation data. These data are rare, in comparison to more common medium-frequency data, such as daily precipitation data commonly recorded by many national and regional weather services. Devising methods for computing estimates of rainfall erosivity from daily precipitation data that are comparable to those obtained by using high-frequency data is, therefore, highly desired. Here we present a method for producing such estimates, based on optimal regression tools such as the Gamma Generalised Linear Model and universal kriging. Unlike other methods, this approach produces unbiased and very close to observed EI30, especially when these are aggregated at the annual level. We illustrate the method with a case study comprising more than 1500 high-frequency precipitation records across Spain. Although the original records have a short span (the mean length is around 10 years), computation of spatially-distributed upscaling parameters offers the possibility to compute high-resolution climatologies of the EI30 index based on currently available, long-span, daily precipitation databases. Copyright © 2018 Elsevier B.V. All rights reserved.
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Modeling the Pineapple Express phenomenon via Multivariate Extreme Value Theory
Weller, G.; Cooley, D. S.
2011-12-01
The pineapple express (PE) phenomenon is responsible for producing extreme winter precipitation events in the coastal and mountainous regions of the western United States. Because the PE phenomenon is also associated with warm temperatures, the heavy precipitation and associated snowmelt can cause destructive flooding. In order to study impacts, it is important that regional climate models from NARCCAP are able to reproduce extreme precipitation events produced by PE. We define a daily precipitation quantity which captures the spatial extent and intensity of precipitation events produced by the PE phenomenon. We then use statistical extreme value theory to model the tail dependence of this quantity as seen in an observational data set and each of the six NARCCAP regional models driven by NCEP reanalysis. We find that most NCEP-driven NARCCAP models do exhibit tail dependence between daily model output and observations. Furthermore, we find that not all extreme precipitation events are pineapple express events, as identified by Dettinger et al. (2011). The synoptic-scale atmospheric processes that drive extreme precipitation events produced by PE have only recently begun to be examined. Much of the current work has focused on pattern recognition, rather than quantitative analysis. We use daily mean sea-level pressure (MSLP) fields from NCEP to develop a "pineapple express index" for extreme precipitation, which exhibits tail dependence with our observed precipitation quantity for pineapple express events. We build a statistical model that connects daily precipitation output from the WRFG model, daily MSLP fields from NCEP, and daily observed precipitation in the western US. Finally, we use this model to simulate future observed precipitation based on WRFG output driven by the CCSM model, and our pineapple express index derived from future CCSM output. Our aim is to use this model to develop a better understanding of the frequency and intensity of extreme
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Spatial distribution of the daily precipitation concentration index in Southern Russia
Vyshkvarkova, Elena; Voskresenskaya, Elena; Martin-Vide, Javier
2018-05-01
The territory of Southern Russia presents a great diversity of climates and complex orography that lead to a very different precipitation distribution. Annual precipitation amounts differ between 222 mm in the coast of the Caspian Sea and > 2000 mm in the highest parts of the Caucasus Mountains. In order to investigate the statistical structure of daily precipitation across the study region the daily precipitation Concentration Index (CI) was used. In present paper, the CI was calculated for 42 meteorological stations during the 1970-2010 period. The analysis of precipitation concentration identified that the distribution of daily precipitation is more regular over the west, north and south regions compared to the east (the Caspian Sea coast and the Caspian Depression). The Crimean peninsula is characterized by low CI values in the north and high values in the eastern part.
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Changes in Indices of Daily Temperature and Precipitation Extremes ...
African Journals Online (AJOL)
It's a known fact that climate change will bring about increases in the occurrence of weather extreme events such as elevated temperature, drought, and floods; most especially in areas classified as hotspots to climate change – such as northwest Nigeria. This study investigates trends in extreme temperature and ...
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Evaluation of precipitation extremes over the Asian domain: observation and modelling studies
Kim, In-Won; Oh, Jaiho; Woo, Sumin; Kripalani, R. H.
2018-04-01
In this study, a comparison in the precipitation extremes as exhibited by the seven reference datasets is made to ascertain whether the inferences based on these datasets agree or they differ. These seven datasets, roughly grouped in three categories i.e. rain-gauge based (APHRODITE, CPC-UNI), satellite-based (TRMM, GPCP1DD) and reanalysis based (ERA-Interim, MERRA, and JRA55), having a common data period 1998-2007 are considered. Focus is to examine precipitation extremes in the summer monsoon rainfall over South Asia, East Asia and Southeast Asia. Measures of extreme precipitation include the percentile thresholds, frequency of extreme precipitation events and other quantities. Results reveal that the differences in displaying extremes among the datasets are small over South Asia and East Asia but large differences among the datasets are displayed over the Southeast Asian region including the maritime continent. Furthermore, precipitation data appear to be more consistent over East Asia among the seven datasets. Decadal trends in extreme precipitation are consistent with known results over South and East Asia. No trends in extreme precipitation events are exhibited over Southeast Asia. Outputs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulation data are categorized as high, medium and low-resolution models. The regions displaying maximum intensity of extreme precipitation appear to be dependent on model resolution. High-resolution models simulate maximum intensity of extreme precipitation over the Indian sub-continent, medium-resolution models over northeast India and South China and the low-resolution models over Bangladesh, Myanmar and Thailand. In summary, there are differences in displaying extreme precipitation statistics among the seven datasets considered here and among the 29 CMIP5 model data outputs.
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Scaling of Precipitation Extremes Modelled by Generalized Pareto Distribution
Rajulapati, C. R.; Mujumdar, P. P.
2017-12-01
Precipitation extremes are often modelled with data from annual maximum series or peaks over threshold series. The Generalized Pareto Distribution (GPD) is commonly used to fit the peaks over threshold series. Scaling of precipitation extremes from larger time scales to smaller time scales when the extremes are modelled with the GPD is burdened with difficulties arising from varying thresholds for different durations. In this study, the scale invariance theory is used to develop a disaggregation model for precipitation extremes exceeding specified thresholds. A scaling relationship is developed for a range of thresholds obtained from a set of quantiles of non-zero precipitation of different durations. The GPD parameters and exceedance rate parameters are modelled by the Bayesian approach and the uncertainty in scaling exponent is quantified. A quantile based modification in the scaling relationship is proposed for obtaining the varying thresholds and exceedance rate parameters for shorter durations. The disaggregation model is applied to precipitation datasets of Berlin City, Germany and Bangalore City, India. From both the applications, it is observed that the uncertainty in the scaling exponent has a considerable effect on uncertainty in scaled parameters and return levels of shorter durations.
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Using Extreme Tropical Precipitation Statistics to Constrain Future Climate States
Igel, M.; Biello, J. A.
2017-12-01
Tropical precipitation is characterized by a rapid growth in mean intensity as the column humidity increases. This behavior is examined in both a cloud resolving model and with high-resolution observations of precipitation and column humidity from CloudSat and AIRS, respectively. The model and the observations exhibit remarkable consistency and suggest a new paradigm for extreme precipitation. We show that the total precipitation can be decomposed into a product of contributions from a mean intensity, a probability of precipitation, and a global PDF of column humidity values. We use the modeling and observational results to suggest simple, analytic forms for each of these functions. The analytic representations are then used to construct a simple expression for the global accumulated precipitation as a function of the parameters of each of the component functions. As the climate warms, extreme precipitation intensity and global precipitation are expected to increase, though at different rates. When these predictions are incorporated into the new analytic expression for total precipitation, predictions for changes due to global warming to the probability of precipitation and the PDF of column humidity can be made. We show that strong constraints can be imposed on the future shape of the PDF of column humidity but that only weak constraints can be set on the probability of precipitation. These are largely imposed by the intensification of extreme precipitation. This result suggests that understanding precisely how extreme precipitation responds to climate warming is critical to predicting other impactful properties of global hydrology. The new framework can also be used to confirm and discount existing theories for shifting precipitation.
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Rosendahl, D. H.; Ćwik, P.; Martin, E. R.; Basara, J. B.; Brooks, H. E.; Furtado, J. C.; Homeyer, C. R.; Lazrus, H.; Mcpherson, R. A.; Mullens, E.; Richman, M. B.; Robinson-Cook, A.
2017-12-01
Extreme precipitation events cause significant damage to homes, businesses, infrastructure, and agriculture, as well as many injures and fatalities as a result of fast-moving water or waterborne diseases. In the USA, these natural hazard events claimed the lives of more than 300 people during 2015 - 2016 alone, with total damage reaching $24.4 billion. Prior studies of extreme precipitation events have focused on the sub-daily to sub-weekly timeframes. However, many decisions for planning, preparing and resilience-building require sub-seasonal to seasonal timeframes (S2S; 14 to 90 days), but adequate forecasting tools for prediction do not exist. Therefore, the goal of this newly funded project is an enhancement in understanding of the large-scale forcing and dynamics of S2S extreme precipitation events in the United States, and improved capability for modeling and predicting such events. Here, we describe the project goals, objectives, and research activities that will take place over the next 5 years. In this project, a unique team of scientists and stakeholders will identify and understand weather and climate processes connected with the prediction of S2S extreme precipitation events by answering these research questions: 1) What are the synoptic patterns associated with, and characteristic of, S2S extreme precipitation evens in the contiguous U.S.? 2) What role, if any, do large-scale modes of climate variability play in modulating these events? 3) How predictable are S2S extreme precipitation events across temporal scales? 4) How do we create an informative prediction of S2S extreme precipitation events for policymaking and planing? This project will use observational data, high-resolution radar composites, dynamical climate models and workshops that engage stakeholders (water resource managers, emergency managers and tribal environmental professionals) in co-production of knowledge. The overarching result of this project will be predictive models to reduce of
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Cui, Lifang; Wang, Lunche; Qu, Sai; Singh, Ramesh P.; Lai, Zhongping; Yao, Rui
2018-05-01
Recently, extreme climate variation has been studied in different parts of the world, and the present study aims to study the impacts of climate extremes on vegetation. In this study, we analyzed the spatiotemporal variations of temperature and precipitation extremes during 1960-2015 in the Yangtze River Basin (YRB) using the Mann-Kendall (MK) test with Sen's slope estimator and kriging interpolation method based on daily precipitation (P), maximum temperature (T max), and minimum temperature (T min). We also analyzed the vegetation dynamics in the YRB during 1982-2015 using Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) datasets and investigated the relationship between temperature and precipitation extremes and NDVI using Pearson correlation coefficients. The results showed a pronounced increase in the annual mean maximum temperature (T nav) and mean minimum temperature (T xav) at the rate of 0.23 °C/10 years and 0.15 °C/10 years, respectively, during 1960-2015. In addition, the occurrence of warm days and warm nights shows increasing trends at the rate of 1.36 days/10 years and 1.70 days/10 years, respectively, while cold days and cold nights decreased at the rate of 1.09 days/10 years and 2.69 days/10 years, respectively, during 1960-2015. The precipitation extremes, such as very wet days (R95, the 95th percentile of daily precipitation events), very wet day precipitation (R95p, the number of days with rainfall above R95), rainstorm (R50, the number of days with rainfall above 50 mm), and maximum 1-day precipitation (RX1day), all show pronounced increasing trends during 1960-2015. In general, annual mean NDVI over the whole YRB increased at the rate of 0.01/10 years during 1982-2015, with an increasing transition around 1994. Spatially, annual mean NDVI increased in the northern, eastern, and parts of southwestern YRB, while it decreased in the YRD and parts of southern YRB during 1982-2015. The correlation
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Spatial interpolation schemes of daily precipitation for hydrologic modeling
Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.
2012-01-01
Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.
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Trends in total and daily precipitation indices in japan from 1901 to 2000
Nagata, Rena; Zaiki, Masumi
2008-01-01
Long-term trends in seasonal precipitation amount and daily precipitation indices were investigated for spring, summer, autumn, and winter with a daily precipitation dataset for Japan from 1901 to 2000. Heavy precipitation in spring and summer has significantly increased along the west coast of Japan. Such changes in precipitation have resulted in the increased heavy precipitation intensity. For autumn and winter, total precipitation significantly decreased in the Kanto district and central J...
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Using damage data to estimate the risk from summer convective precipitation extremes
Schroeer, Katharina; Tye, Mari
2017-04-01
This study explores the potential added value from including loss and damage data to understand the risks from high-intensity short-duration convective precipitation events. Projected increases in these events are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows, and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to this, not only are extreme events rare, but such small-scale events are likely to be underreported where they do not coincide with the observation network. Reports of private loss and damage on a local administrative unit scale (LAU 2 level) are used to explore the relationship between observed rainfall events and damages reportedly related to hydro-meteorological processes. With 480 Austrian municipalities located within our south-eastern Alpine study region, the damage data are available on a much smaller scale than the available rainfall data. Precipitation is recorded daily at 185 gauges and 52% of these stations additionally deliver sub-hourly rainfall information. To obtain physically plausible information, damage and rainfall data are grouped and analyzed on a catchment scale. The data indicate that rainfall intensities are higher on days that coincide with a damage claim than on days for which no damage was reported. However, approximately one third of the damages related to hydro-meteorological hazards were claimed on days for which no rainfall was recorded at any gauge in the respective catchment. Our goal is to assess whether these events indicate potential extreme events missing in the observations. Damage always is a consequence of an asset being exposed and susceptible to a hazardous process, and naturally, many factors influence whether an extreme rainfall event causes damage. We set up a statistical
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Extreme climate, not extreme weather: the summer of 1816 in Geneva, Switzerland
Directory of Open Access Journals (Sweden)
R. Auchmann
2012-02-01
Full Text Available We analyze weather and climate during the "Year without Summer" 1816 using sub-daily data from Geneva, Switzerland, representing one of the climatically most severely affected regions. The record includes twice daily measurements and observations of air temperature, pressure, cloud cover, wind speed, and wind direction as well as daily measurements of precipitation. Comparing 1816 to a contemporary reference period (1799–1821 reveals that the coldness of the summer of 1816 was most prominent in the afternoon, with a shift of the entire distribution function of temperature anomalies by 3–4 °C. Early morning temperature anomalies show a smaller change for the mean, a significant decrease in the variability, and no changes in negative extremes. Analyzing cloudy and cloud-free conditions separately suggests that an increase in the number of cloudy days was to a significant extent responsible for these features. A daily weather type classification based on pressure, pressure tendency, and wind direction shows extremely anomalous frequencies in summer 1816, with only one day (compared to 20 in an average summer classified as high-pressure situation but a tripling of low-pressure situations. The afternoon temperature anomalies expected from only a change in weather types was much stronger negative in summer 1816 than in any other year. For precipitation, our analysis shows that the 80% increase in summer precipitation compared to the reference period can be explained by 80% increase in the frequency of precipitation, while no change could be found neither in the average intensity of precipitation nor in the frequency distribution of extreme precipitation. In all, the analysis shows that the regional circulation and local cloud cover played a dominant role. It also shows that the summer of 1816 was an example of extreme climate, not extreme weather.
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Rising Mediterranean Sea Surface Temperatures Amplify Extreme Summer Precipitation in Central Europe
Volosciuk, Claudia; Maraun, Douglas; Semenov, Vladimir A.; Tilinina, Natalia; Gulev, Sergey K.; Latif, Mojib
2016-08-01
The beginning of the 21st century was marked by a number of severe summer floods in Central Europe associated with extreme precipitation (e.g., Elbe 2002, Oder 2010 and Danube 2013). Extratropical storms, known as Vb-cyclones, cause summer extreme precipitation events over Central Europe and can thus lead to such floodings. Vb-cyclones develop over the Mediterranean Sea, which itself strongly warmed during recent decades. Here we investigate the influence of increased Mediterranean Sea surface temperature (SST) on extreme precipitation events in Central Europe. To this end, we carry out atmosphere model simulations forced by average Mediterranean SSTs during 1970-1999 and 2000-2012. Extreme precipitation events occurring on average every 20 summers in the warmer-SST-simulation (2000-2012) amplify along the Vb-cyclone track compared to those in the colder-SST-simulation (1970-1999), on average by 17% in Central Europe. The largest increase is located southeast of maximum precipitation for both simulated heavy events and historical Vb-events. The responsible physical mechanism is increased evaporation from and enhanced atmospheric moisture content over the Mediterranean Sea. The excess in precipitable water is transported from the Mediterranean Sea to Central Europe causing stronger precipitation extremes over that region. Our findings suggest that Mediterranean Sea surface warming amplifies Central European precipitation extremes.
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Directory of Open Access Journals (Sweden)
Danica Ciric
2018-04-01
Full Text Available Moisture transport from its sources to surrounding continents is one of the most relevant topics in hydrology, and its role in extreme events is crucial for understanding several processes such as intense precipitation and flooding. In this study, we considered the Mediterranean Sea as the main water source and estimated its contribution to the monthly climatological and extreme precipitation events over the surrounding continental areas. To assess the effect of the Mediterranean Sea on precipitation, we used the Multi-Source Weighted-Ensemble Precipitation (MSWEP database to characterize precipitation. The Lagrangian dispersion model known as FLEXPART was used to estimate the moisture contribution of this source. This contribution was estimated by tracking particles that leave the Mediterranean basin monthly and then calculating water loss (E − P < 0 over the continental region, which was modelled by FLEXPART. The analysis was conducted using data from 1980 to 2015 with a spatial resolution of 0.25°. The results showed that, in general, the spatial pattern of the Mediterranean source’s contribution to precipitation, unlike climatology, is similar during extreme precipitation years in the regions under study. However, while the Mediterranean Sea is usually not an important source of climatological precipitation for some European regions, it is a significant source during extreme precipitation years.
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Energy Technology Data Exchange (ETDEWEB)
You, Qinglong [Institute of Tibetan Plateau Research, Chinese Academy of Sciences (CAS), Laboratory of Tibetan Environment Changes and Land Surface Processes, Beijing (China); Friedrich-Schiller University Jena, Department of Geoinformatics, Jena (Germany); Graduate University of Chinese Academy of Sciences, Beijing (China); Kang, Shichang [Institute of Tibetan Plateau Research, Chinese Academy of Sciences (CAS), Laboratory of Tibetan Environment Changes and Land Surface Processes, Beijing (China); State Key Laboratory of Cryospheric Science, Chinese Academy of Sciences, Lanzhou (China); Aguilar, Enric [Universitat Rovirai Virgili de Tarragona, Climate Change Research Group, Geography Unit, Tarragona (Spain); Pepin, Nick [University of Portsmouth, Department of Geography, Portsmouth (United Kingdom); Fluegel, Wolfgang-Albert [Friedrich-Schiller University Jena, Department of Geoinformatics, Jena (Germany); Yan, Yuping [National Climate Center, Beijing (China); Xu, Yanwei; Huang, Jie [Institute of Tibetan Plateau Research, Chinese Academy of Sciences (CAS), Laboratory of Tibetan Environment Changes and Land Surface Processes, Beijing (China); Graduate University of Chinese Academy of Sciences, Beijing (China); Zhang, Yongjun [Institute of Tibetan Plateau Research, Chinese Academy of Sciences (CAS), Laboratory of Tibetan Environment Changes and Land Surface Processes, Beijing (China)
2011-06-15
Based on daily maximum and minimum surface air temperature and precipitation records at 303 meteorological stations in China, the spatial and temporal distributions of indices of climate extremes are analyzed during 1961-2003. Twelve indices of extreme temperature and six of extreme precipitation are studied. Temperature extremes have high correlations with the annual mean temperature, which shows a significant warming of 0.27 C/decade, indicating that changes in temperature extremes reflect the consistent warming. Stations in northeastern, northern, northwestern China have larger trend magnitudes, which are accordance with the more rapid mean warming in these regions. Countrywide, the mean trends for cold days and cold nights have decreased by -0.47 and -2.06 days/decade respectively, and warm days and warm nights have increased by 0.62 and 1.75 days/decade, respectively. Over the same period, the number of frost days shows a statistically significant decreasing trend of -3.37 days/decade. The length of the growing season and the number of summer days exhibit significant increasing trends at rates of 3.04 and 1.18 days/decade, respectively. The diurnal temperature range has decreased by -0.18 C/decade. Both the annual extreme lowest and highest temperatures exhibit significant warming trends, the former warming faster than the latter. For precipitation indices, regional annual total precipitation shows an increasing trend and most other precipitation indices are strongly correlated with annual total precipitation. Average wet day precipitation, maximum 1-day and 5-day precipitation, and heavy precipitation days show increasing trends, but only the last is statistically significant. A decreasing trend is found for consecutive dry days. For all precipitation indices, stations in the Yangtze River basin, southeastern and northwestern China have the largest positive trend magnitudes, while stations in the Yellow River basin and in northern China have the largest
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Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR
Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.
2017-12-01
Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.
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Patterns of precipitation and soil moisture extremes in Texas, US: A complex network analysis
Sun, Alexander Y.; Xia, Youlong; Caldwell, Todd G.; Hao, Zengchao
2018-02-01
Understanding of the spatial and temporal dynamics of extreme precipitation not only improves prediction skills, but also helps to prioritize hazard mitigation efforts. This study seeks to enhance the understanding of spatiotemporal covariation patterns embedded in precipitation (P) and soil moisture (SM) by using an event-based, complex-network-theoretic approach. Events concurrences are quantified using a nonparametric event synchronization measure, and spatial patterns of hydroclimate variables are analyzed by using several network measures and a community detection algorithm. SM-P coupling is examined using a directional event coincidence analysis measure that takes the order of event occurrences into account. The complex network approach is demonstrated for Texas, US, a region possessing a rich set of hydroclimate features and is frequented by catastrophic flooding. Gridded daily observed P data and simulated SM data are used to create complex networks of P and SM extremes. The uncovered high degree centrality regions and community structures are qualitatively in agreement with the overall existing knowledge of hydroclimate extremes in the study region. Our analyses provide new visual insights on the propagation, connectivity, and synchronicity of P extremes, as well as the SM-P coupling, in this flood-prone region, and can be readily used as a basis for event-driven predictive analytics for other regions.
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Katiraie-Boroujerdy, Pari-Sima; Akbari Asanjan, Ata; Hsu, Kuo-lin; Sorooshian, Soroosh
2017-09-01
In the first part of this paper, monthly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission 3B42 algorithm Version 7 (TRMM-3B42V7) are evaluated over Iran using the Generalized Three-Cornered Hat (GTCH) method which is self-sufficient of reference data as input. Climate Data Unit (CRU) is added to the GTCH evaluations as an independent gauge-based dataset thus, the minimum requirement of three datasets for the model is satisfied. To ensure consistency of all datasets, the two satellite products were aggregated to 0.5° spatial resolution, which is the minimum resolution of CRU. The results show that the PERSIANN-CDR has higher Signal to Noise Ratio (SNR) than TRMM-3B42V7 for the monthly rainfall estimation, especially in the northern half of the country. All datasets showed low SNR in the mountainous area of southwestern Iran, as well as the arid parts in the southeast region of the country. Additionally, in order to evaluate the efficacy of PERSIANN-CDR and TRMM-3B42V7 in capturing extreme daily-precipitation amounts, an in-situ rain-gauge dataset collected by the Islamic Republic of the Iran Meteorological Organization (IRIMO) was employed. Given the sparsity of the rain gauges, only 0.25° pixels containing three or more gauges were used for this evaluation. There were 228 such pixels where daily and extreme rainfall from PERSIANN-CDR and TRMM-3B42V7 could be compared. However, TRMM-3B42V7 overestimates most of the intensity indices (correlation coefficients; R between 0.7648-0.8311, Root Mean Square Error; RMSE between 3.29mm/day-21.2mm/5day); PERSIANN-CDR underestimates these extremes (R between 0.6349-0.7791 and RMSE between 3.59mm/day-30.56mm/5day). Both satellite products show higher correlation coefficients and lower RMSEs for the annual mean of consecutive dry spells than wet spells. The results show that TRMM-3B42V7
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Schroeer, K.; Kirchengast, G.
2018-06-01
Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale.
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Predictability of Extreme Precipitations Over the Conterminous us, 1949-2010
Jiang, M.; Felzer, B. S.
2015-12-01
Extreme precipitation plays an important role in regulating ecosystem services. Precipitation extremes vary in magnitude and duration both spatially and temporally, making it one of the most challenging climate variables to comprehend and predict. Using information theory, we provide an attempt to improve understanding of the predictability of extreme precipitation in the conterminous U.S. over the period of 1949-2010. We define predictability as the recurrent likelihood of patterns described by the measures of constancy and contingency, with the former describing the inter-annual variability and the latter describing the seasonality. This study shows that there are clear west-east contrasts of predictability over the U.S. landscape, with a generally decreasing gradient from the Northeast to the Southwest for intensity-based extremes and a generally increasing gradient from the West to the East for duration-based extremes. We further identify spatially heterogeneous patterns of temporal changes in predictability over the investigated timeframe. Finally, it is evident that constancy plays a heavier role in regulating predictability increases for both intensity and duration-based extremes and for predictability decreases for duration-based extremes, while contingency contributes equally with constancy to determining the decreases in predictability for intensity-based extremes.
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Energy Technology Data Exchange (ETDEWEB)
May, Wilhelm [Danish Meteorological Institute, Danish Climate Centre, Copenhagen (Denmark)
2008-05-15
In this study the potential future changes in various aspects of daily precipitation events over Europe as a consequence of the anticipated future increase in the atmospheric greenhouse gas concentrations are investigated. This is done by comparing two 3-member ensembles of simulations with the HIRHAM regional climate model for the period 1961-1990 and 2071-2100, respectively. Daily precipitation events are characterized by their frequency and intensity, and heavy precipitation events are described via 30-year return levels of daily precipitation. Further, extended periods with and without rainfall (wet and dry spells) are studied, considering their frequency and length as well as the average and extreme amounts of precipitation accumulated during wet spells, the latter again described via 30-year return levels. The simulations show marked changes in the characteristics of daily precipitation in Europe due to the anticipated greenhouse warming. In winter, for instance, the frequency of wet days is enhanced over most of the European continent except for the region on the Norwegian west coast and the Mediterranean region. The changes in the intensity and the 30-year return level of daily precipitation are characterized by a similar pattern except for central Europe with a tendency of decreased 30-year return levels and increased precipitation intensity. In summer, on the other hand, the frequency of wet days is decreased over most of Europe except for northern Scandinavia and the Baltic Sea region. In contrast, the precipitation intensity and the 30-year return level of daily precipitation are increased over entire Scandinavia, central and eastern Europe. The changes in the 30-year return level of daily precipitation are generally stronger than the corresponding changes in the precipitation intensity but can have opposite signs in some regions. Also the distribution of wet days is changed in the future. During summer, for instance, both the frequency and the length
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Daily extreme temperature multifractals in Catalonia (NE Spain)
International Nuclear Information System (INIS)
Burgueño, A.; Lana, X.; Serra, C.; Martínez, M.D.
2014-01-01
The multifractal character of the daily extreme temperatures in Catalonia (NE Spain) is analyzed by means of the multifractal detrended fluctuation analysis (MF-DFA) applied to 65 thermometric records covering years 1950–2004. Although no clear spatial patterns of the multifractal spectrum parameters appear, factor scores deduced from Principal Component analysis indicate some signs of spatial gradients. Additionally, the daily extreme temperature series are classified depending on their complex time behavior, through four multifractal parameters (Hurst exponent, Hölder exponent with maximum spectrum, spectrum asymmetry and spectrum width). As a synthesis of the three last parameters, a basic measure of complexity is proposed through a normalized Complexity Index. Its regional behavior is found to be free of geographical dependences. This index represents a new step towards the description of the daily extreme temperatures complexity.
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Daily extreme temperature multifractals in Catalonia (NE Spain)
Energy Technology Data Exchange (ETDEWEB)
Burgueño, A. [Departament d' Astronomia i Meteorologia, Universitat de Barcelona, Barcelona (Spain); Lana, X., E-mail: francisco.javier.lana@upc.edu [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Barcelona (Spain); Serra, C. [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Barcelona (Spain); Martínez, M.D. [Departament de Física Aplicada, Universitat Politècnica de Catalunya, Barcelona (Spain)
2014-02-01
The multifractal character of the daily extreme temperatures in Catalonia (NE Spain) is analyzed by means of the multifractal detrended fluctuation analysis (MF-DFA) applied to 65 thermometric records covering years 1950–2004. Although no clear spatial patterns of the multifractal spectrum parameters appear, factor scores deduced from Principal Component analysis indicate some signs of spatial gradients. Additionally, the daily extreme temperature series are classified depending on their complex time behavior, through four multifractal parameters (Hurst exponent, Hölder exponent with maximum spectrum, spectrum asymmetry and spectrum width). As a synthesis of the three last parameters, a basic measure of complexity is proposed through a normalized Complexity Index. Its regional behavior is found to be free of geographical dependences. This index represents a new step towards the description of the daily extreme temperatures complexity.
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Zhou, Yaping; Lau, William K M.; Liu, Chuntao
2013-01-01
This study adopts a "precipitation object" approach by using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Feature (PF) and National Centers for Environmental Prediction (NCEP) reanalysis data to study rainfall structure and environmental factors associated with extreme heavy rain events. Characteristics of instantaneous extreme volumetric PFs are examined and compared to those of intermediate and small systems. It is found that instantaneous PFs exhibit a much wider scale range compared to the daily gridded precipitation accumulation range. The top 1% of the rainiest PFs contribute over 55% of total rainfall and have 2 orders of rain volume magnitude greater than those of the median PFs. We find a threshold near the top 10% beyond which the PFs grow exponentially into larger, deeper, and colder rain systems. NCEP reanalyses show that midlevel relative humidity and total precipitable water increase steadily with increasingly larger PFs, along with a rapid increase of 500 hPa upward vertical velocity beyond the top 10%. This provides the necessary moisture convergence to amplify and sustain the extreme events. The rapid increase in vertical motion is associated with the release of convective available potential energy (CAPE) in mature systems, as is evident in the increase in CAPE of PFs up to 10% and the subsequent dropoff. The study illustrates distinct stages in the development of an extreme rainfall event including: (1) a systematic buildup in large-scale temperature and moisture, (2) a rapid change in rain structure, (3) explosive growth of the PF size, and (4) a release of CAPE before the demise of the event.
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Temperature sensitivity of extreme precipitation events in the south-eastern Alpine forelands
Schroeer, Katharina; Kirchengast, Gottfried
2016-04-01
How will convective precipitation intensities and patterns evolve in a warming climate on a regional to local scale? Studies on the scaling of precipitation intensities with temperature are used to test observational and climate model data against the hypothesis that the change of precipitation with temperature will essentially follow the Clausius-Clapeyron (CC) equation, which corresponds to a rate of increase of the water holding capacity of the atmosphere by 6-7 % per Kelvin (CC rate). A growing number of studies in various regions and with varying approaches suggests that the overall picture of the temperature-precipitation relationship is heterogeneous, with scaling rates shearing off the CC rate in both upward and downward directions. In this study we investigate the temperature scaling of extreme precipitation events in the south-eastern Alpine forelands of Austria (SEA) based on a dense rain gauge net of 188 stations, with sub-daily precipitation measurements since about 1990 used at 10-min resolution. Parts of the study region are European hot-spots for severe hailstorms and the region, which is in part densely populated and intensively cultivated, is generally vulnerable to climate extremes. Evidence on historical extremely heavy short-time and localized precipitation events of several hundred mm of rain in just a few hours, resulting in destructive flash flooding, underline these vulnerabilities. Heavy precipitation is driven by Mediterranean moisture advection, enhanced by the orographic lifting at the Alpine foothills, and hence trends in positive sea surface temperature anomalies might carry significant risk of amplifying future extreme precipitation events. In addition, observations from the highly instrumented subregion of south-eastern Styria indicate a strong and robust long-term warming trend in summer of about 0.7°C per decade over 1971-2015, concomitant with a significant increase in the annual number of heat days. The combination of these
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Wu, Y.; Wu, S.; Wen, J.; Xu, M.; Tan, J.
2013-12-01
The Yangtze River is the longest river in China, with its river basin covering an area of 1.8 million sq km, encompassing about one fifth of China's total territory, one third of the nation's total population, and one quarter of its total arable land. Flooding resulted from extreme precipitation has always been a major problem for the middle and lower part of the YRB, particularly during the monsoon season of eastern China from May to August. Meanwhile, the relatively dense population and large cities in this region make the floods more deadly and costly. In this study we aim to establish the temporal and spatial patterns of changes in extreme precipitation in the middle and lower YRB using daily precipitation data from 71 stations in the area from 1960 to 2012. It is hoped that this study will provide useful information for better flood control. In this study, we defined and examined three major indices. Extreme precipitation frequency is defined as number of days per year with precipitation exceeding the 95th percentile for the base period of 1961 - 1990. Extreme precipitation amount is defined as the total amount of precipitation from these days. Extreme precipitation intensity is defined as the amount divided by frequency. We used non-parametric Thiel-Sen method to estimate the rate of change at each station, and Mann-Kendall test for the significance of the trend. Using Thiessen polygons, we also calculated the area-weighted mean of station trends to get the total trend for the entire study area. Abrupt changes in the time series was detected by using Mann-Kendall test and the Moving-t test methods. Our results show that there is an increasing trend of for the frequency, amount, and intensity of extreme precipitation in the study region. Of the three indicators, the extreme precipitation amount increased most, and its abrupt change point happened in1987. Between the period before and after 1987, the mean annual amount, intensity and frequency of extreme
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Bador, M.; Donat, M.; Geoffroy, O.; Alexander, L. V.
2017-12-01
Precipitation intensity during extreme events is expected to increase with climate change. Throughout the 21st century, CMIP5 climate models project a general increase in annual extreme precipitation in most regions. We investigate how robust this future increase is across different models, regions and seasons. We find that there is strong similarity in extreme precipitation changes between models that share atmospheric physics, reducing the ensemble of 27 models to 14 independent projections. We find that future simulated extreme precipitation increases in most models in the majority of land grid cells located in the dry, intermediate and wet regions according to each model's precipitation climatology. These increases significantly exceed the range of natural variability estimated from long equilibrium control runs. The intensification of extreme precipitation across the entire spectrum of dry to wet regions is particularly robust in the extra-tropics in both wet and dry season, whereas uncertainties are larger in the tropics. The CMIP5 ensemble therefore indicates robust future intensification of annual extreme rainfall in particular in extra-tropical regions. Generally, the CMIP5 robustness is higher during the dry season compared to the wet season and the annual scale, but inter-model uncertainties in the tropics remain important.
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A two-component generalized extreme value distribution for precipitation frequency analysis
Czech Academy of Sciences Publication Activity Database
Rulfová, Zuzana; Buishand, A.; Roth, M.; Kyselý, Jan
2016-01-01
Roč. 534, March (2016), s. 659-668 ISSN 0022-1694 R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : precipitation extremes * two-component extreme value distribution * regional frequency analysis * convective precipitation * stratiform precipitation * Central Europe Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 3.483, year: 2016 http://www.sciencedirect.com/science/article/pii/S0022169416000500
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Daily precipitation statistics in regional climate models
DEFF Research Database (Denmark)
Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel
2003-01-01
An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...
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Lavers, David A.; Pappenberger, Florian; Richardson, David S.; Zsoter, Ervin
2016-11-01
In winter, heavy precipitation and floods along the west coasts of midlatitude continents are largely caused by intense water vapor transport (integrated vapor transport (IVT)) within the atmospheric river of extratropical cyclones. This study builds on previous findings that showed that forecasts of IVT have higher predictability than precipitation, by applying and evaluating the European Centre for Medium-Range Weather Forecasts Extreme Forecast Index (EFI) for IVT in ensemble forecasts during three winters across Europe. We show that the IVT EFI is more able (than the precipitation EFI) to capture extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase; conversely, the precipitation EFI is better during the negative NAO phase and at shorter leads. An IVT EFI example for storm Desmond in December 2015 highlights its potential to identify upcoming hydrometeorological extremes, which may prove useful to the user and forecasting communities.
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Knapp, Alan K.; Avolio, Meghan L.; Beier, Claus; Carroll, Charles J.W.; Collins, Scott L.; Dukes, Jeffrey S.; Fraser, Lauchlan H.; Griffin-Nolan, Robert J.; Hoover, David L.; Jentsch, Anke; Loik, Michael E.; Phillips, Richard P.; Post, Alison K.; Sala, Osvaldo E.; Slette, Ingrid J.; Yahdjian, Laura; Smith, Melinda D.
2017-01-01
Intensification of the global hydrological cycle, ranging from larger individual precipitation events to more extreme multiyear droughts, has the potential to cause widespread alterations in ecosystem structure and function. With evidence that the incidence of extreme precipitation years (defined statistically from historical precipitation records) is increasing, there is a clear need to identify ecosystems that are most vulnerable to these changes and understand why some ecosystems are more sensitive to extremes than others. To date, opportunistic studies of naturally occurring extreme precipitation years, combined with results from a relatively small number of experiments, have provided limited mechanistic understanding of differences in ecosystem sensitivity, suggesting that new approaches are needed. Coordinated distributed experiments (CDEs) arrayed across multiple ecosystem types and focused on water can enhance our understanding of differential ecosystem sensitivity to precipitation extremes, but there are many design challenges to overcome (e.g., cost, comparability, standardization). Here, we evaluate contemporary experimental approaches for manipulating precipitation under field conditions to inform the design of ‘Drought-Net’, a relatively low-cost CDE that simulates extreme precipitation years. A common method for imposing both dry and wet years is to alter each ambient precipitation event. We endorse this approach for imposing extreme precipitation years because it simultaneously alters other precipitation characteristics (i.e., event size) consistent with natural precipitation patterns. However, we do not advocate applying identical treatment levels at all sites – a common approach to standardization in CDEs. This is because precipitation variability varies >fivefold globally resulting in a wide range of ecosystem-specific thresholds for defining extreme precipitation years. For CDEs focused on precipitation extremes, treatments should be based
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Changes of the Temperature and Precipitation Extremes on Homogenized Data
Directory of Open Access Journals (Sweden)
LAKATOS, Mónika
2007-01-01
Full Text Available Climate indices to detect changes have been defined in several international projects onclimate change. Climate index calculations require at least daily resolution of time series withoutinhomogeneities, such as transfer of stations, changes in observation practice. In many cases thecharacteristics of the estimated linear trends, calculated from the original and from the homogenizedtime series are significantly different. The ECA&D (European Climate Assessment & Dataset indicesand some other special temperature and precipitation indices of own development were applied to theClimate Database of the Hungarian Meteorological Service. Long term daily maximum, minimum anddaily mean temperature data series and daily precipitation sums were examined. The climate indexcalculation processes were tested on original observations and on homogenized daily data fortemperature; in the case of precipitation a complementation process was performed to fill in the gapsof missing data. Experiences of comparing the climate index calculation results, based on original andcomplemented-homogenized data, are reported in this paper. We present the preliminary result ofclimate index calculations also on gridded (interpolated daily data.
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Wang, Yuan
2015-10-01
The recent study "Trends of Extreme Precipitation in Eastern China and Their Possible Causes" attributed the observed decrease/increase of light/heavy precipitation in eastern China to global warming rather than the regional aerosol effects. However, there exist compelling evidence from previous long-term observations and numerical modeling studies, suggesting that anthropogenic pollution is closely linked to the recent changes in precipitation intensity because of considerably modulated cloud physical properties by aerosols in eastern China. Clearly, a quantitative assessment of the aerosol and greenhouse effects on the regional scale is required to identify the primary cause for the extreme precipitation changes.
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Aguilar, E.; Aziz Barry, A.; Brunet, M.; Ekang, L.; Fernandes, A.; Massoukina, M.; Mbah, J.; Mhanda, A.; Do Nascimento, D. J.; Peterson, T. C.; Thamba Umba, O.; Tomou, M.; Zhang, X.
2009-01-01
Understanding how extremes are changing globally, regionally, and locally is an important first step for planning appropriate adaptation measures, as changes in extremes have major impacts. The Intergovernmental Panel on Climate Change's synthesis of global extremes was not able to say anything about western central Africa, as no analysis of the region was available nor was there an adequate internationally exchanged long-term daily data set available to use for analysis of extremes. This paper presents the first analysis of extremes in this climatically important region along with analysis of Guinea Conakry and Zimbabwe. As per many other parts of the world, the analysis shows a decrease in cold extremes and an increase in warm extremes. However, while the majority of the analyzed world has shown an increase in heavy precipitation over the last half century, central Africa showed a decrease. Furthermore, the companion analysis of Guinea Conakry and Zimbabwe showed no significant increases.
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Changes in temperature and precipitation extremes observed in Modena, Italy
Boccolari, M.; Malmusi, S.
2013-03-01
Climate changes has become one of the most analysed subjects from researchers community, mainly because of the numerous extreme events that hit the globe. To have a better view of climate changes and trends, long observations time series are needed. During last decade a lot of Italian time series, concerning several surface meteorological variables, have been analysed and published. No one of them includes one of the longest record in Italy, the time series of the Geophysical Observatory of the University of Modena and Reggio Emilia. Measurements, collected since early 19th century, always in the same position, except for some months during the second world war, embrace daily temperature, precipitation amount, relative humidity, pressure, cloudiness and other variables. In this work we concentrated on the analysis of yearly and seasonal trends and climate extremes of temperature, both minimum and maximum, and precipitation time series, for the periods 1861-2010 and 1831-2010 respectively, in which continuous measurements are available. In general, our results confirm quite well those reported by IPCC and in many other studies over Mediterranean area. In particular, we found that minimum temperature has a non significant positive trend of + 0.1 °C per decade considering all the period, the value increases to 0.9 °C per decade for 1981-2010. For maximum temperature we observed a non significant + 0.1 °C trend for all the period, while + 0.8 °C for the last thirty years. On the other hand precipitation is decreasing, -6.3 mm per decade, considering all the analysed period, while the last thirty years are characterised by a great increment of 74.8 mm per decade. For both variables several climate indices have been analysed and they confirm what has been found for minimum and maximum temperatures and precipitation. In particular, during last 30 years frost days and ice days are decreasing, whereas summer days are increasing. During the last 30-year tropical nights
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Temporal and spatial scaling impacts on extreme precipitation
Eggert, B.; Berg, P.; Haerter, J. O.; Jacob, D.; Moseley, C.
2015-01-01
Both in the current climate and in the light of climate change, understanding of the causes and risk of precipitation extremes is essential for protection of human life and adequate design of infrastructure. Precipitation extreme events depend qualitatively on the temporal and spatial scales at which they are measured, in part due to the distinct types of rain formation processes that dominate extremes at different scales. To capture these differences, we first filter large datasets of high-resolution radar measurements over Germany (5 min temporally and 1 km spatially) using synoptic cloud observations, to distinguish convective and stratiform rain events. In a second step, for each precipitation type, the observed data are aggregated over a sequence of time intervals and spatial areas. The resulting matrix allows a detailed investigation of the resolutions at which convective or stratiform events are expected to contribute most to the extremes. We analyze where the statistics of the two types differ and discuss at which resolutions transitions occur between dominance of either of the two precipitation types. We characterize the scales at which the convective or stratiform events will dominate the statistics. For both types, we further develop a mapping between pairs of spatially and temporally aggregated statistics. The resulting curve is relevant when deciding on data resolutions where statistical information in space and time is balanced. Our study may hence also serve as a practical guide for modelers, and for planning the space-time layout of measurement campaigns. We also describe a mapping between different pairs of resolutions, possibly relevant when working with mismatched model and observational resolutions, such as in statistical bias correction.
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DEFF Research Database (Denmark)
Sunyer Pinya, Maria Antonia; Luchner, J.; Onof, C.
2017-01-01
extreme precipitation over Denmark generated by the regional climate model (RCM) HIRHAM-ECEARTH at different spatial resolutions (8, 12, 25 and 50km), three RCM from the RiskChange project at 8km resolution and three RCMs from ENSEMBLES at 25km resolution at temporal aggregations from 1 to 48h...... are more skewed than the observational dataset, which leads to an overestimation by the higher spatial resolution simulations. Nevertheless, in general, under current conditions RCM simulations at high spatial resolution represent extreme events and high-order moments better. The changes projected...
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Ye, Hengchun; Fetzer, Eric J; Wong, Sun; Lambrigtsen, Bjorn H
2017-01-01
Convective precipitation-localized, short-lived, intense, and sometimes violent-is at the root of challenges associated with observation, simulation, and prediction of precipitation. The understanding of long-term changes in convective precipitation characteristics and their role in precipitation extremes and intensity over extratropical regions are imperative to future water resource management; however, they have been studied very little. We show that annual convective precipitation total has been increasing astonishingly fast, at a rate of 18.4%/°C, of which 16% is attributable to an increase in convective precipitation occurrence, and 2.4% is attributable to increased daily intensity based on the 35 years of two (combined) historical data sets of 3-hourly synoptic observations and daily precipitation. We also reveal that annual daily precipitation extreme has been increasing at a rate of about 7.4%/°C in convective events only. Concurrently, the overall increase in mean daily precipitation intensity is mostly due to increased convective precipitation, possibly at the expanse of nonconvective precipitation. As a result, transitional seasons are becoming more summer-like as convective becomes the dominant precipitation type that has accompanied higher daily extremes and intensity since the late 1980s. The data also demonstrate that increasing convective precipitation and daily extremes appear to be directly linearly associated with higher atmospheric water vapor accompanying a warming climate over northern Eurasia.
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Slinskey, E. A.; Loikith, P. C.; Waliser, D. E.; Goodman, A.
2017-12-01
Extreme precipitation events are associated with numerous societal and environmental impacts. Furthermore, anthropogenic climate change is projected to alter precipitation intensity across portions of the Continental United States (CONUS). Therefore, a spatial understanding and intuitive means of monitoring extreme precipitation over time is critical. Towards this end, we apply an event-based indicator, developed as a part of NASA's support of the ongoing efforts of the US National Climate Assessment, which assigns categories to extreme precipitation events based on 3-day storm totals as a basis for dataset intercomparison. To assess observational uncertainty across a wide range of historical precipitation measurement approaches, we intercompare in situ station data from the Global Historical Climatology Network (GHCN), satellite-derived precipitation data from NASA's Tropical Rainfall Measuring Mission (TRMM), gridded in situ station data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM), global reanalysis from NASA's Modern Era Retrospective-Analysis version 2 (MERRA 2), and regional reanalysis with gauge data assimilation from NCEP's North American Regional Reanalysis (NARR). Results suggest considerable variability across the five-dataset suite in the frequency, spatial extent, and magnitude of extreme precipitation events. Consistent with expectations, higher resolution datasets were found to resemble station data best and capture a greater frequency of high-end extreme events relative to lower spatial resolution datasets. The degree of dataset agreement varies regionally, however all datasets successfully capture the seasonal cycle of precipitation extremes across the CONUS. These intercomparison results provide additional insight about observational uncertainty and the ability of a range of precipitation measurement and analysis products to capture extreme precipitation event climatology. While the event category threshold is fixed
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Using stochastic space-time models to map extreme precipitation in southern Portugal
Directory of Open Access Journals (Sweden)
A. C. Costa
2008-07-01
Full Text Available The topographic characteristics and spatial climatic diversity are significant in the South of continental Portugal where the rainfall regime is typically Mediterranean. Direct sequential cosimulation is proposed for mapping an extreme precipitation index in southern Portugal using elevation as auxiliary information. The analysed index (R5D can be considered a flood indicator because it provides a measure of medium-term precipitation total. The methodology accounts for local data variability and incorporates space-time models that allow capturing long-term trends of extreme precipitation, and local changes in the relationship between elevation and extreme precipitation through time. Annual gridded datasets of the flood indicator are produced from 1940 to 1999 on 800 m×800 m grids by using the space-time relationship between elevation and the index. Uncertainty evaluations of the proposed scenarios are also produced for each year. The results indicate that the relationship between elevation and extreme precipitation varies locally and has decreased through time over the study region. In wetter years the flood indicator exhibits the highest values in mountainous regions of the South, while in drier years the spatial pattern of extreme precipitation has much less variability over the study region. The uncertainty of extreme precipitation estimates also varies in time and space, and in earlier decades is strongly dependent on the density of the monitoring stations network. The produced maps will be useful in regional and local studies related to climate change, desertification, land and water resources management, hydrological modelling, and flood mitigation planning.
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Spatiotemporal Analysis of Extreme Hourly Precipitation Patterns in Hainan Island, South China
Directory of Open Access Journals (Sweden)
Wenjie Chen
2015-05-01
Full Text Available To analyze extreme precipitation patterns in Hainan Island, hourly precipitation datasets from 18 stations, for the period from 1967 to 2012, were investigated. Two precipitation concentration indices (PCI and 11 extreme precipitation indices (EPI were chosen. PCI1 indicated a moderate seasonality in yearly precipitation and PCI2 showed that at least 80% of the total precipitation fell in 20% of the rainiest hours. Furthermore, the spatial variations of PCI1 and PCI2 differed. Linear regression indicated increasing trends in 11 of the calculated EPI. Principal component analysis found that the first recalculated principal component represented the 11 EPI. The recalculated principal component revealed an increasing trend in precipitation extremes for the whole island (except the interior section. Trend stability analysis of several of EPI suggested that the southern parts of Hainan Island, and especially the city of Sanya, should receive more attention to establish the drainage facilities necessary to prevent waterlogging.
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Li, Xin Xin; Sang, Yan Fang; Xie, Ping; Liu, Chang Ming
2018-04-01
Daily precipitation process in China showed obvious randomness and spatiotemporal variation. It is important to accurately understand the influence of precipitation changes on control of flood and waterlogging disaster. Using the daily precipitation data measured at 520 stations in China during 1961-2013, we quantified the stochastic characteristics of daily precipitation over China based on the index of information entropy. Results showed that the randomness of daily precipitation in the southeast region were larger than that in the northwest region. Moreover, the spatial distribution of stochastic characteristics of precipitation was different at various grades. Stochastic characteri-stics of P 0 (precipitation at 0.1-10 mm) was large, but the spatial variation was not obvious. The stochastic characteristics of P 10 (precipitation at 10-25 mm) and P 25 (precipitation at 25-50 mm) were the largest and their spatial difference was obvious. P 50 (precipitation ≥50 mm) had the smallest stochastic characteristics and the most obviously spatial difference. Generally, the entropy values of precipitation obviously increased over the last five decades, indicating more significantly stochastic characteristics of precipitation (especially the obvious increase of heavy precipitation events) in most region over China under the scenarios of global climate change. Given that the spatial distribution and long-term trend of entropy values of daily precipitation could reflect thespatial distribution of stochastic characteristics of precipitation, our results could provide scientific basis for the control of flood and waterlogging disaster, the layout of agricultural planning, and the planning of ecological environment.
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The effect of scale in daily precipitation hazard assessment
Directory of Open Access Journals (Sweden)
J. J. Egozcue
2006-01-01
Full Text Available Daily precipitation is recorded as the total amount of water collected by a rain-gauge in 24 h. Events are modelled as a Poisson process and the 24 h precipitation by a Generalised Pareto Distribution (GPD of excesses. Hazard assessment is complete when estimates of the Poisson rate and the distribution parameters, together with a measure of their uncertainty, are obtained. The shape parameter of the GPD determines the support of the variable: Weibull domain of attraction (DA corresponds to finite support variables as should be for natural phenomena. However, Fréchet DA has been reported for daily precipitation, which implies an infinite support and a heavy-tailed distribution. Bayesian techniques are used to estimate the parameters. The approach is illustrated with precipitation data from the Eastern coast of the Iberian Peninsula affected by severe convective precipitation. The estimated GPD is mainly in the Fréchet DA, something incompatible with the common sense assumption of that precipitation is a bounded phenomenon. The bounded character of precipitation is then taken as a priori hypothesis. Consistency of this hypothesis with the data is checked in two cases: using the raw-data (in mm and using log-transformed data. As expected, a Bayesian model checking clearly rejects the model in the raw-data case. However, log-transformed data seem to be consistent with the model. This fact may be due to the adequacy of the log-scale to represent positive measurements for which differences are better relative than absolute.
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Kürbis, K.; Mudelsee, M.; Tetzlaff, G.; Brázdil, R.
2009-09-01
For the analysis of trends in weather extremes, we introduce a diagnostic index variable, the exceedance product, which combines intensity and frequency of extremes. We separate trends in higher moments from trends in mean or standard deviation and use bootstrap resampling to evaluate statistical significances. The application of the concept of the exceedance product to daily meteorological time series from Potsdam (1893 to 2005) and Prague-Klementinum (1775 to 2004) reveals that extremely cold winters occurred only until the mid-20th century, whereas warm winters show upward trends. These changes were significant in higher moments of the temperature distribution. In contrast, trends in summer temperature extremes (e.g., the 2003 European heatwave) can be explained by linear changes in mean or standard deviation. While precipitation at Potsdam does not show pronounced trends, dew point does exhibit a change from maximum extremes during the 1960s to minimum extremes during the 1970s.
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Gibba, P.; Sylla, M. B.
2015-12-01
The ability of the state-of-the-art climate models to reproduce the mean spatial characteristics of extreme precipitation indices over Africa is evaluated. The ensembles of eight precipitation-based indices as defined by ETCCDI were extracted from seventeen CMIP5 GCMs and twelve CORDEX RCMs simulations based on absolute and percentile (95th) thresholds and computed from the 1975 to 2004 historical period. Daily precipitation indices calculated from GPCP and TRMM satellite-derived observation datasets during the period 1997 to 2012 and 1998 to 2011 respectively were also employed in this study for model validation. Results of spatial representation of the frequency of extreme precipitation events (R1mm, CDD, CWD and R95p) highlight a generally good consistency between the two observations. Equally, in the regional analysis some similarities exist in their median and interquartile (25th and 75th percentile) spread especially for CDD, CWD and R95p for most regions. In the associated intensities (SDII, RX5day, R95 and R95ptot), results indicate large spatial differences between the two observational datasets, with finer resolution TRMM generating higher rainfall intensities than the coarser resolution GPCP. TRMM has also demonstrated higher median and interquartile range as compared to GPCP. The CORDEX RCMs and CMIP5 GCMs simulations have estimated more number of extreme precipitation events, while underestimated the intensities. The differences between the models and observations can be as large as the typical model interquartile spread of the ensembles for some indices (R1mm, CWD, SDII and R95) in some regions. Meanwhile, CORDEX estimations are generally closer to the observations than CMIP5 in reproducing the frequency of extreme rainfall indices. For the estimation of rainfall intensities, CORDEX simulations are in most cases more consistence with TRMM observations whilst the CMIP5 GCMs simulations are closer to GPCP observations.
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How do the multiple large-scale climate oscillations trigger extreme precipitation?
Shi, Pengfei; Yang, Tao; Xu, Chong-Yu; Yong, Bin; Shao, Quanxi; Li, Zhenya; Wang, Xiaoyan; Zhou, Xudong; Li, Shu
2017-10-01
Identifying the links between variations in large-scale climate patterns and precipitation is of tremendous assistance in characterizing surplus or deficit of precipitation, which is especially important for evaluation of local water resources and ecosystems in semi-humid and semi-arid regions. Restricted by current limited knowledge on underlying mechanisms, statistical correlation methods are often used rather than physical based model to characterize the connections. Nevertheless, available correlation methods are generally unable to reveal the interactions among a wide range of climate oscillations and associated effects on precipitation, especially on extreme precipitation. In this work, a probabilistic analysis approach by means of a state-of-the-art Copula-based joint probability distribution is developed to characterize the aggregated behaviors for large-scale climate patterns and their connections to precipitation. This method is employed to identify the complex connections between climate patterns (Atlantic Multidecadal Oscillation (AMO), El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO)) and seasonal precipitation over a typical semi-humid and semi-arid region, the Haihe River Basin in China. Results show that the interactions among multiple climate oscillations are non-uniform in most seasons and phases. Certain joint extreme phases can significantly trigger extreme precipitation (flood and drought) owing to the amplification effect among climate oscillations.
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Directory of Open Access Journals (Sweden)
Alexander Gershunov, PhD
2018-05-01
Full Text Available Background: Pathogens and pollutants collect on the land surface or in infrastructure between strong rainfall episodes and are delivered via storm runoff to areas of human exposure, such as coastal recreational waters. In California, USA, precipitation events are projected to become more extreme and simultaneously decrease in frequency as storm tracks move poleward due to polar-amplified global warming. Precipitation extremes in California are dominated by atmospheric rivers, which carry more moisture in warmer climates. Thus, the physical driver of extreme precipitation events is expected to grow stronger with climate change, and pollutant accumulation and runoff-generated exposure to those pollutants are expected to increase, particularly after prolonged dry spells. Microbiological contamination of coastal waters during winter storms exposes human populations to elevated concentrations of microorganisms such as faecal bacteria, which could cause gastrointestinal and ear infections, and lead to exposure to pathogens causing life-threatening conditions, such as hepatitis A. The aim of this study was to quantitatively assess the effect of precipitation on coastal water quality in California. Methods: We used a recently published catalogue of atmospheric rivers, in combination with historical daily precipitation data and levels of three indicators of faecal bacteria (total and faecal coliforms, and Escherichia coli detected at roughly 500 monitoring locations in coastal waters along California's 840-mile coastline, to explore weekly associations between extreme precipitation events, particularly those related to atmospheric rivers, and the variability in water quality during 2003–09. We identified ten principal components (together explaining >90% of the variability in precipitation and faecal bacteria time-series to reduce the dimensionality of the datasets. We then performed canonical correlation analysis of the principal components to
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Directory of Open Access Journals (Sweden)
Saoussen Dhib
2017-06-01
Full Text Available Knowledge and evaluation of extreme precipitation is important for water resources and flood risk management, soil and land degradation, and other environmental issues. Due to the high potential threat to local infrastructure, such as buildings, roads and power supplies, heavy precipitation can have an important social and economic impact on society. At present, satellite derived precipitation estimates are becoming more readily available. This paper aims to investigate the potential use of the Meteosat Second Generation (MSG Multi-Sensor Precipitation Estimate (MPE for extreme rainfall assessment in Tunisia. The MSGMPE data combine microwave rain rate estimations with SEVIRI thermal infrared channel data, using an EUMETSAT production chain in near real time mode. The MPE data can therefore be used in a now-casting mode, and are potentially useful for extreme weather early warning and monitoring. Daily precipitation observed across an in situ gauge network in the north of Tunisia were used during the period 2007–2009 for validation of the MPE extreme event data. As a first test of the MSGMPE product's performance, very light to moderate rainfall classes, occurring between January and October 2007, were evaluated. Extreme rainfall events were then selected, using a threshold criterion for large rainfall depth (>50 mm/day occurring at least at one ground station. Spatial interpolation methods were applied to generate rainfall maps for the drier summer season (from May to October and the wet winter season (from November to April. Interpolated gauge rainfall maps were then compared to MSGMPE data available from the EUMETSAT UMARF archive or from the GEONETCast direct dissemination system. The summation of the MPE data at 5 and/or 15 min time intervals over a 24 h period, provided a basis for comparison. The MSGMPE product was not very effective in the detection of very light and light rain events. Better results were obtained for the slightly
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Qiu, Wenyu; Ren, Fumin; Wu, Liguang; Chen, Lianshou; Ding, Chenchen
2018-03-01
Extreme precipitation induced by a tropical cyclone (TC) is of great concern to Southeast China. Regional characteristics of daily TC-induced extreme precipitation (TCEP) between 1958 and 2016 and the associated preliminary causes over Southeast China (Zhejiang, Fujian, and Shanghai) were examined by applying the objective synoptic analysis technique, TC track similarity area index, daily precipitation observations, and reanalysis data. The intensity and frequency of high-intensity TCEP (≥ 100, ≥ 200, ≥ 300 mm) have had an increasing trend over recent decades. Most of TCEP occurs from July to September, with frequency peaks in August for TCEP at all intensity levels, apart from the frequency for TCEP ≥ 300 mm that peaks in September. Regions with high frequency and large TCEP (R-HFLTs) (relatively high frequency for TCEP ≥ 100 mm) were concentrated along the coastline of the southern coastal Fujian (Southern R-HFLT), the regions from northern coastal Fujian to southernmost coastal Zhejiang (Central R-HFLT), and central coastal Zhejiang (Northern R-HFLT), decreasing from the coastline to inland. The Central R-HFLT region had the highest TCEP intensity and frequency for TCEP ≥ 100 mm compared with the other R-HFLTs. Further analysis showed that the special terrain of Southeast China matched the spatial distribution of TCEP, which highlights the significance of the topography of Southeast China. To discover other factors responsible for the heavy TCEP, we compared two TC groups that influence Central R-HFLT. Under a more northerly direction and slow movement combined with the unique terrain, TCs with stronger vortex circulation generated heavier TCEP during landfall in Central R-HFLT. Heavy TCEP occurred with easterly and southeasterly winds interacting with terrain over the eastern coast for Central R-HFLT. Although large changes in the internal and external environment were sensitive to the observed TCEP intensity, the interaction between TC circulation
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Detection of trends in precipitation extremes in Zhejiang, east China
Tian, Ye; Xu, YuePing; Booij, Martijn J.; Lin, Shengji; Zhang, Qingqing; Lou, Zhanghua
2012-01-01
Extreme weather exerts a huge impact on human beings and it is of vital importance to study the regular pattern of meteorological and hydrological factors. In this paper, a selection of seven extreme indices is used to analyze the trend of precipitation extremes of 18 meteorological stations located
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Temporal variation of extreme precipitation events in Lithuania
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Egidijus Rimkus
2011-05-01
Full Text Available Heavy precipitation events in Lithuania for the period 1961-2008 were analysed. The spatial distribution and dynamics of precipitation extremes were investigated. Positive tendencies and in some cases statistically significant trends were determined for the whole of Lithuania. Atmospheric circulation processes were derived using Hess & Brezowski's classification of macrocirculation forms. More than one third of heavy precipitation events (37% were observed when the atmospheric circulation was zonal. The location of the central part of a cyclone (WZ weather condition subtype over Lithuania is the most common synoptic situation (27% during heavy precipitation events. Climatic projections according to outputs of the CCLM model are also presented in this research. The analysis shows that the recurrence of heavy precipitation events in the 21st century will increase significantly (by up to 22% in Lithuania.
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Climate Prediction Center (CPC) U.S. Daily Precipitation Observations
National Oceanic and Atmospheric Administration, Department of Commerce — Observational reports of daily precipitation (1200 UTC to 1200 UTC) are made by members of the NWS Automated Surface Observing Systems (ASOS) network; NWS...
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Dai, S.; Shulski, M.
2013-12-01
Climate warming and changes in rainfall patterns and increases in extreme events are resulting in higher risks of crop failures. A greater sense of urgency has been induced to understand the impacts of past climate on crop production in the U.S. As one of the most predominant sources of feed grains, corn is also the main source of U.S. ethanol. In the U.S. Corn Belt, region-scale evaluation on temperature and precipitation variability and extremes during the growing season is not well-documented yet. This study is part of the USDA-funded project 'Useful to Usable: Transforming climate variability and change information for cereal crop producers'. The overall goal of our work is to study the characteristics of average growing season conditions and changes in growing season temperature- and precipitation-based indices that are closely correlated with corn grain yield in the U.S. Corn Belt. The research area is the twelve major Corn Belt states, including IL, IN, IA, KS, MI, MN, MO, NE, OH, SD, ND, and WI. Climate data during 1981-2010 from 132 meteorological stations (elevation ranges from 122 m to 1,202 m) are used in this study, including daily minimum, maximum, and mean temperature, and daily precipitation. From 1981 to 2012, beginning date (BD), ending date (ED), and growing season length (GSL) in the climatological corn growing season are studied. Especially, during the agronomic corn growing season, from Apr to Oct, temperature- and precipitation-based indices are analyzed. The temperature-based indices include: number of days with daily mean temperature below 10°C, number of days with daily mean temperature above 30°C, the sum of growing degree days (GDD) between 10°C to 30°C (GDD10,30, growth range for corn), the sum of growing degree days above 30°C (GDD30+, exposure to harmful warming for corn), the sum of growing degree days between 0°C and 44°C (GDD0,44, survival range limits for corn), the sum of growing degree days between 5°C and 35°C (GDD5
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21st Century Changes in Precipitation Extremes Based on Resolved Atmospheric Patterns
Gao, X.; Schlosser, C. A.; O'Gorman, P. A.; Monier, E.
2014-12-01
Global warming is expected to alter the frequency and/or magnitude of extreme precipitation events. Such changes could have substantial ecological, economic, and sociological consequences. However, climate models in general do not correctly reproduce the frequency distribution of precipitation, especially at the regional scale. In this study, a validated analogue method is employed to diagnose the potential future shifts in the probability of extreme precipitation over the United States under global warming. The method is based on the use of the resolved large-scale meteorological conditions (i.e. flow features, moisture supply) to detect the occurrence of extreme precipitation. The CMIP5 multi-model projections have been compiled for two radiative forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). We further analyze the accompanying circulation features and their changes that may be responsible for shifts in extreme precipitation in response to changed climate. The application of such analogue method to detect other types of hazard events, i.e. landslides is also explored. The results from this study may guide hazardous weather watches and help society develop adaptive strategies for preventing catastrophic losses.
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Distributing urban resilience to extreme precipitation events with green infrastructure
Montalto, F. A.; Catalano De Sousa, M.; Yu, Z.
2013-12-01
New urban green spaces are being designed to manage stormwater, but their performance in a changing climate is untested. Key questions pertain to the ability of these systems to mitigate flood and sewer overflow concerns during impact of extreme events on, and to withstand (biologically and physically) increased frequency and intensity of drought and flood conditions. In this presentation, we present field data characterizing performance of a bioretention area, a stormwater treatment wetland, and a green roof under Hurricane Irene (2011), Superstorm Sandy (2012), and a variety of extreme precipitation events during the summer of 2013. Specifically, we characterize the fate and volume of incident runon and/or precipitation to the facilities during these extreme events, and compare them to long term monitored performance metrics. We also present laboratory test results documenting how vegetation in these facilities stands up to simulated flood and drought conditions. The results are discussed in the context of predicted climate change, specifically associated with the amount and timing of precipitation.
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Global Precipitation Climatology Project (GPCP) - Daily, Version 1.2
National Oceanic and Atmospheric Administration, Department of Commerce — The Global Precipitation Climatology Project (GPCP) comprises a total of 27 products. The Version 1.2 Daily product covers the period October 1998 to the present,...
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Changes in precipitation extremes projected by a 20-km mesh global atmospheric model
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Akio Kitoh
2016-03-01
Full Text Available High-resolution modeling is necessary to project weather and climate extremes and their future changes under global warming. A global high-resolution atmospheric general circulation model with grid size about 20 km is able to reproduce climate fields as well as regional-scale phenomena such as monsoonal rainfall, tropical and extratropical cyclones, and heavy precipitation. This 20-km mesh model is applied to project future changes in weather and climate extremes at the end of the 21st century with four different spatial patterns in sea surface temperature (SST changes: one with the mean SST changes by the 28 models of the Coupled Model Intercomparison Project Phase 5 (CMIP5 under the Representative Concentration Pathways (RCP-8.5 scenario, and the other three obtained from a cluster analysis, in which tropical SST anomalies derived from the 28 CMIP5 models were grouped. Here we focus on future changes in regional precipitation and its extremes. Various precipitation indices averaged over the Twenty-two regional land domains are calculated. Heavy precipitation indices (maximum 5-day precipitation total and maximum 1-day precipitation total increase in all regional domains, even where mean precipitation decrease (Southern Africa, South Europe/Mediterranean, Central America. South Asia is the domain of the largest extreme precipitation increase. In some domains, different SST patterns result in large precipitation changes, possibly related to changes in large-scale circulations in the tropical Pacific.
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Ritschel, Christoph; Ulbrich, Uwe; Névir, Peter; Rust, Henning W.
2017-12-01
For several hydrological modelling tasks, precipitation time series with a high (i.e. sub-daily) resolution are indispensable. The data are, however, not always available, and thus model simulations are used to compensate. A canonical class of stochastic models for sub-daily precipitation are Poisson cluster processes, with the original Bartlett-Lewis (OBL) model as a prominent representative. The OBL model has been shown to well reproduce certain characteristics found in observations. Our focus is on intensity-duration-frequency (IDF) relationships, which are of particular interest in risk assessment. Based on a high-resolution precipitation time series (5 min) from Berlin-Dahlem, OBL model parameters are estimated and IDF curves are obtained on the one hand directly from the observations and on the other hand from OBL model simulations. Comparing the resulting IDF curves suggests that the OBL model is able to reproduce the main features of IDF statistics across several durations but cannot capture rare events (here an event with a return period larger than 1000 years on the hourly timescale). In this paper, IDF curves are estimated based on a parametric model for the duration dependence of the scale parameter in the generalized extreme value distribution; this allows us to obtain a consistent set of curves over all durations. We use the OBL model to investigate the validity of this approach based on simulated long time series.
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Operational quality control of daily precipitation using spatio-climatological consistency testing
Scherrer, S. C.; Croci-Maspoli, M.; van Geijtenbeek, D.; Naguel, C.; Appenzeller, C.
2010-09-01
Quality control (QC) of meteorological data is of utmost importance for climate related decisions. The search for an effective automated QC of precipitation data has proven difficult and many weather services still use mainly manual inspection of daily precipitation including MeteoSwiss. However, man power limitations force many weather services to move towards less labour intensive and more automated QC with the challenge to keeping data quality high. In the last decade, several approaches have been presented to objectify daily precipitation QC. Here we present a spatio-climatological approach that will be implemented operationally at MeteoSwiss. It combines the information from the event based spatial distribution of everyday's precipitation field and the historical information of the interpolation error using different precipitation intensity intervals. Expert judgement shows that the system is able to detect potential outliers very well (hardly any missed errors) without creating too many false alarms that need human inspection. 50-80% of all flagged values have been classified as real errors by the data editor. This is much better than the roughly 15-20% using standard spatial regression tests. Very helpful in the QC process is the automatic redistribution of accumulated several day sums. Manual inspection in operations can be reduced and the QC of precipitation objectified substantially.
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Ashouri, Hamed; Sorooshian, Soroosh; Hsu, Kuo-Lin; Bosilovich, Michael G.; Lee, Jaechoul; Wehner, Michael F.; Collow, Allison
2016-01-01
This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC) U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that
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Directory of Open Access Journals (Sweden)
Mengqian Lu
2017-12-01
Full Text Available Three river basins, i.e., the Yangtze river, the Mississippi river and the Loire river, were presented as case studies to explore the association among atmospheric circulations, moisture exports and extreme precipitations in the mid-latitudes. The major moisture source regions in the tropics for the three river basins are first identified using the Tropical Moisture Exports (TMEs dataset. The space-time characteristics of their respective moisture sources are presented. Then, the trajectory curve clustering analysis is applied to the TMEs tracks originating from the identified source regions during each basin’s peak TMEs activity and flood seasons. Our results show that the moisture tracks for each basin can be categorized into 3 or 4 clusters with distinct spatial trajectory features. Our further analysis on these clustered trajectories reveals that the contributions of moisture release from different clusters are associated with their trajectory features and travel speeds. In order to understand the role of associated atmospheric steering, daily composites of the geopotential heights anomalies and the vertical integral of moisture flux anomalies from 7 days ahead to the extreme precipitation days (top 5% are examined. The evolutions of the atmospheric circulation patterns and the moisture fluxes are both consistent with the TMEs tracks that contribute more moisture releases to the study regions. The findings imply that atmospheric steering plays an important role in the moisture transport and release, especially for the extreme precipitations. We also find that the association between TMEs moisture release and precipitation is nonlinear. The extreme precipitation is associated with high TMEs moisture release for all of the three study regions.
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TAO/TRITON, RAMA, and PIRATA Buoys, Daily, 1997-present, Precipitation
National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Precipitation data from the TAO/TRITON (Pacific Ocean, https://www.pmel.noaa.gov/gtmba/ ), RAMA (Indian Ocean,...
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Piras, Monica; Mascaro, Giuseppe; Deidda, Roberto; Vivoni, Enrique R
2016-02-01
Mediterranean region is characterized by high precipitation variability often enhanced by orography, with strong seasonality and large inter-annual fluctuations, and by high heterogeneity of terrain and land surface properties. As a consequence, catchments in this area are often prone to the occurrence of hydrometeorological extremes, including storms, floods and flash-floods. A number of climate studies focused in the Mediterranean region predict that extreme events will occur with higher intensity and frequency, thus requiring further analyses to assess their effect at the land surface, particularly in small- and medium-sized watersheds. In this study, climate and hydrologic simulations produced within the Climate Induced Changes on the Hydrology of Mediterranean Basins (CLIMB) EU FP7 research project were used to analyze how precipitation extremes propagate into discharge extremes in the Rio Mannu basin (472.5km(2)), located in Sardinia, Italy. The basin hydrologic response to climate forcings in a reference (1971-2000) and a future (2041-2070) period was simulated through the combined use of a set of global and regional climate models, statistical downscaling techniques, and a process based distributed hydrologic model. We analyzed and compared the distribution of annual maxima extracted from hourly and daily precipitation and peak discharge time series, simulated by the hydrologic model under climate forcing. For this aim, yearly maxima were fit by the Generalized Extreme Value (GEV) distribution using a regional approach. Next, we discussed commonality and contrasting behaviors of precipitation and discharge maxima distributions to better understand how hydrological transformations impact propagation of extremes. Finally, we show how rainfall statistical downscaling algorithms produce more reliable forcings for hydrological models than coarse climate model outputs. Copyright © 2015 Elsevier B.V. All rights reserved.
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A global dataset of sub-daily rainfall indices
Fowler, H. J.; Lewis, E.; Blenkinsop, S.; Guerreiro, S.; Li, X.; Barbero, R.; Chan, S.; Lenderink, G.; Westra, S.
2017-12-01
It is still uncertain how hydrological extremes will change with global warming as we do not fully understand the processes that cause extreme precipitation under current climate variability. The INTENSE project is using a novel and fully-integrated data-modelling approach to provide a step-change in our understanding of the nature and drivers of global precipitation extremes and change on societally relevant timescales, leading to improved high-resolution climate model representation of extreme rainfall processes. The INTENSE project is in conjunction with the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges Project (GEWEX) Science questions. A new global sub-daily precipitation dataset has been constructed (data collection is ongoing). Metadata for each station has been calculated, detailing record lengths, missing data, station locations. A set of global hydroclimatic indices have been produced based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. This will provide a unique global data resource on sub-daily precipitation whose derived indices will be freely available to the wider scientific community.
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Gao, Tao; Wang, Huixia Judy; Zhou, Tianjun
2017-01-01
of precipitation extremes over monsoon regions in China (MRC). However, research on monsoon extremes in China and their associations with climate variables is limited. In this study, we examine the space-time variations of extreme precipitation across the MRC
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Ecosystem functional response across precipitation extremes in a sagebrush steppe.
Tredennick, Andrew T; Kleinhesselink, Andrew R; Taylor, J Bret; Adler, Peter B
2018-01-01
Precipitation is predicted to become more variable in the western United States, meaning years of above and below average precipitation will become more common. Periods of extreme precipitation are major drivers of interannual variability in ecosystem functioning in water limited communities, but how ecosystems respond to these extremes over the long-term may shift with precipitation means and variances. Long-term changes in ecosystem functional response could reflect compensatory changes in species composition or species reaching physiological thresholds at extreme precipitation levels. We conducted a five year precipitation manipulation experiment in a sagebrush steppe ecosystem in Idaho, United States. We used drought and irrigation treatments (approximately 50% decrease/increase) to investigate whether ecosystem functional response remains consistent under sustained high or low precipitation. We recorded data on aboveground net primary productivity (ANPP), species abundance, and soil moisture. We fit a generalized linear mixed effects model to determine if the relationship between ANPP and soil moisture differed among treatments. We used nonmetric multidimensional scaling to quantify community composition over the five years. Ecosystem functional response, defined as the relationship between soil moisture and ANPP, was similar among irrigation and control treatments, but the drought treatment had a greater slope than the control treatment. However, all estimates for the effect of soil moisture on ANPP overlapped zero, indicating the relationship is weak and uncertain regardless of treatment. There was also large spatial variation in ANPP within-years, which contributes to the uncertainty of the soil moisture effect. Plant community composition was remarkably stable over the course of the experiment and did not differ among treatments. Despite some evidence that ecosystem functional response became more sensitive under sustained drought conditions, the response
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Precipitation variability increases in a warmer climate.
Pendergrass, Angeline G; Knutti, Reto; Lehner, Flavio; Deser, Clara; Sanderson, Benjamin M
2017-12-21
Understanding changes in precipitation variability is essential for a complete explanation of the hydrologic cycle's response to warming and its impacts. While changes in mean and extreme precipitation have been studied intensively, precipitation variability has received less attention, despite its theoretical and practical importance. Here, we show that precipitation variability in most climate models increases over a majority of global land area in response to warming (66% of land has a robust increase in variability of seasonal-mean precipitation). Comparing recent decades to RCP8.5 projections for the end of the 21 st century, we find that in the global, multi-model mean, precipitation variability increases 3-4% K -1 globally, 4-5% K -1 over land and 2-4% K -1 over ocean, and is remarkably robust on a range of timescales from daily to decadal. Precipitation variability increases by at least as much as mean precipitation and less than moisture and extreme precipitation for most models, regions, and timescales. We interpret this as being related to an increase in moisture which is partially mitigated by weakening circulation. We show that changes in observed daily variability in station data are consistent with increased variability.
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Kim, Beomgeun; Seo, Dong-Jun; Noh, Seong Jin; Prat, Olivier P.; Nelson, Brian R.
2018-01-01
A new technique for merging radar precipitation estimates and rain gauge data is developed and evaluated to improve multisensor quantitative precipitation estimation (QPE), in particular, of heavy-to-extreme precipitation. Unlike the conventional cokriging methods which are susceptible to conditional bias (CB), the proposed technique, referred to herein as conditional bias-penalized cokriging (CBPCK), explicitly minimizes Type-II CB for improved quantitative estimation of heavy-to-extreme precipitation. CBPCK is a bivariate version of extended conditional bias-penalized kriging (ECBPK) developed for gauge-only analysis. To evaluate CBPCK, cross validation and visual examination are carried out using multi-year hourly radar and gauge data in the North Central Texas region in which CBPCK is compared with the variant of the ordinary cokriging (OCK) algorithm used operationally in the National Weather Service Multisensor Precipitation Estimator. The results show that CBPCK significantly reduces Type-II CB for estimation of heavy-to-extreme precipitation, and that the margin of improvement over OCK is larger in areas of higher fractional coverage (FC) of precipitation. When FC > 0.9 and hourly gauge precipitation is > 60 mm, the reduction in root mean squared error (RMSE) by CBPCK over radar-only (RO) is about 12 mm while the reduction in RMSE by OCK over RO is about 7 mm. CBPCK may be used in real-time analysis or in reanalysis of multisensor precipitation for which accurate estimation of heavy-to-extreme precipitation is of particular importance.
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Jha, Sanjeev Kumar
2015-07-21
A geostatistical framework is proposed to downscale daily precipitation and temperature. The methodology is based on multiple-point geostatistics (MPS), where a multivariate training image is used to represent the spatial relationship between daily precipitation and daily temperature over several years. Here, the training image consists of daily rainfall and temperature outputs from the Weather Research and Forecasting (WRF) model at 50 km and 10 km resolution for a twenty year period ranging from 1985 to 2004. The data are used to predict downscaled climate variables for the year 2005. The result, for each downscaled pixel, is daily time series of precipitation and temperature that are spatially dependent. Comparison of predicted precipitation and temperature against a reference dataset indicates that both the seasonal average climate response together with the temporal variability are well reproduced. The explicit inclusion of time dependence is explored by considering the climate properties of the previous day as an additional variable. Comparison of simulations with and without inclusion of time dependence shows that the temporal dependence only slightly improves the daily prediction because the temporal variability is already well represented in the conditioning data. Overall, the study shows that the multiple-point geostatistics approach is an efficient tool to be used for statistical downscaling to obtain local scale estimates of precipitation and temperature from General Circulation Models. This article is protected by copyright. All rights reserved.
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Gao, Tao
2017-07-19
The El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO) and Pacific decadal oscillation (PDO) are well understood to be major drivers for the variability of precipitation extremes over monsoon regions in China (MRC). However, research on monsoon extremes in China and their associations with climate variables is limited. In this study, we examine the space-time variations of extreme precipitation across the MRC, and assess the time-varying influences of the climate drivers using Bayesian dynamic linear regression and their combined nonlinear effects through fitting generalized additive models. Results suggest that the central-east and south China is dominated by less frequent but more intense precipitation. Extreme rainfalls show significant positive trends, coupled with a significant decline of dry spells, indicating an increasing chance of occurrence of flood-induced disasters in the MRC during 1960–2014. Majority of the regional indices display some abrupt shifts during the 1990s. The influences of climate variables on monsoon extremes exhibit distinct interannual or interdecadal variations. IOD, ENSO and AMO have strong impacts on monsoon and extreme precipitation, especially during the 1990s, which is generally consistent with the abrupt shifts in precipitation regimes around this period. Moreover, ENSO mainly affects moderate rainfalls and dry spells, while IOD has a more significant impact on precipitation extremes. These findings could be helpful for improving the forecasting of monsoon extremes in China and the evaluations of climate models.
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Comparing regional precipitation and temperature extremes in climate model and reanalysis products
Directory of Open Access Journals (Sweden)
Oliver Angélil
2016-09-01
Full Text Available A growing field of research aims to characterise the contribution of anthropogenic emissions to the likelihood of extreme weather and climate events. These analyses can be sensitive to the shapes of the tails of simulated distributions. If tails are found to be unrealistically short or long, the anthropogenic signal emerges more or less clearly, respectively, from the noise of possible weather. Here we compare the chance of daily land-surface precipitation and near-surface temperature extremes generated by three Atmospheric Global Climate Models typically used for event attribution, with distributions from six reanalysis products. The likelihoods of extremes are compared for area-averages over grid cell and regional sized spatial domains. Results suggest a bias favouring overly strong attribution estimates for hot and cold events over many regions of Africa and Australia, and a bias favouring overly weak attribution estimates over regions of North America and Asia. For rainfall, results are more sensitive to geographic location. Although the three models show similar results over many regions, they do disagree over others. Equally, results highlight the discrepancy amongst reanalyses products. This emphasises the importance of using multiple reanalysis and/or observation products, as well as multiple models in event attribution studies.
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DEFF Research Database (Denmark)
Sunyer Pinya, Maria Antonia; Hundecha, Y.; Lawrence, D.
2015-01-01
Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models......), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation...... that at least 30% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided...
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DEFF Research Database (Denmark)
Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten
2017-01-01
Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...... gauges in the model area. The spatiotemporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatiotemporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying on precipitation output...
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Cheng, L.; Du, J.
2015-12-01
The Xiang River, a main tributary of the Yangtze River, is subjected to high floods frequently in recent twenty years. Climate change, including abrupt shifts and fluctuations in precipitation is an important factor influencing hydrological extreme conditions. In addition, human activities are widely recognized as another reasons leading to high flood risk. With the effects of climate change and human interventions on hydrological cycle, there are several questions that need to be addressed. Are floods in the Xiang River basin getting worse? Whether the extreme streamflow shows an increasing tendency? If so, is it because the extreme rainfall events have predominant effect on floods? To answer these questions, the article detected existing trends in extreme precipitation and discharge using Mann-Kendall test. Continuous wavelet transform method was employed to identify the consistency of changes in extreme precipitation and discharge. The Pearson correlation analysis was applied to investigate how much degree of variations in extreme discharge can be explained by climate change. The results indicate that slightly upward trends can be detected in both extreme rainfalls and discharge in the upper region of Xiang River basin. For the most area of middle and lower river basin, the extreme rainfalls show significant positive trends, but the extreme discharge displays slightly upward trends with no significance at 90% confidence level. Wavelet transform analysis results illustrate that highly similar patterns of signal changes can be seen between extreme precipitation and discharge in upper section of the basin, while the changes in extreme precipitation for the middle and lower reaches do not always coincide with the extreme streamflow. The correlation coefficients of the wavelet transforms for the precipitation and discharge signals in most area of the basin pass the significance test. The conclusion may be drawn that floods in recent years are not getting worse in
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Are satellite products good proxies for gauge precipitation over Singapore?
Hur, Jina; Raghavan, Srivatsan V.; Nguyen, Ngoc Son; Liong, Shie-Yui
2018-05-01
The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000-2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate
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Directory of Open Access Journals (Sweden)
Xiaoxin Yang
2016-09-01
Full Text Available This study presents a stable oxygen isotope (δ18O record in daily precipitation from two sites located to the northeast of the Tibetan Plateau (TP: Yushu on the eastern TP and Xi'an on the eastern Chinese Loess Plateau. It attempts to reveal the unique features associated with variations in atmospheric circulation patterns over inland China. For δ18O in daily precipitation at both stations, temperature effect is significant (p < 0.01 only during non-monsoon, while amount effect is significant only during monsoon. This suggests the coexistence of local recycling with large-scale atmospheric circulation on regional precipitation, which is further verified by the significant correlation of relative humidity with δ18O at both stations during monsoon season. The similarity of δ18O in regions under the supposedly same atmospheric circulation streams is tested for Yushu with that at Lhasa, Lulang and Delingha, demonstrating the lag days of δ18O depletion at Yushu with that at Lulang as varying from 15 to 25 d. This confirms the Bay of Bengal monsoon dominance over Yushu. Daily δ18O at Xi'an is compared with contemporary data at Changsha and Guangzhou, featuring a close correlation with the East Asian summer monsoon evolution processes over eastern China, and reflecting the Meiyu-Baiu front influence during July. Back-trajectory analysis in October–November at Xi'an identified the combined effect of cooling of the atmospheric column by the colder air from the west and the lifting of the warmer air from the east, which coexists with local water vapour source. Interactions of the three result in condensation at lower temperatures that is coupled with the long-distance transport of 2/3 of the available water vapour, thus leading to extremely low δ18O values in the post-monsoon precipitation.
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Streamflow response to increasing precipitation extremes altered by forest management
Charlene N. Kelly; Kevin J. McGuire; Chelcy Ford Miniat; James M. Vose
2016-01-01
Increases in extreme precipitation events of floods and droughts are expected to occur worldwide. The increase in extreme events will result in changes in streamflow that are expected to affect water availability for human consumption and aquatic ecosystem function. We present an analysis that may greatly improve current streamflow models by quantifying the...
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The role of the subtropical North Atlantic water cycle in recent US extreme precipitation events
Li, Laifang; Schmitt, Raymond W.; Ummenhofer, Caroline C.
2018-02-01
The role of the oceanic water cycle in the record-breaking 2015 warm-season precipitation in the US is analyzed. The extreme precipitation started in the Southern US in the spring and propagated northward to the Midwest and the Great Lakes in the summer of 2015. This seasonal evolution of precipitation anomalies represents a typical mode of variability of US warm-season precipitation. Analysis of the atmospheric moisture flux suggests that such a rainfall mode is associated with moisture export from the subtropical North Atlantic. In the spring, excessive precipitation in the Southern US is attributable to increased moisture flux from the northwestern portion of the subtropical North Atlantic. The North Atlantic moisture flux interacts with local soil moisture which enables the US Midwest to draw more moisture from the Gulf of Mexico in the summer. Further analysis shows that the relationship between the rainfall mode and the North Atlantic water cycle has become more significant in recent decades, indicating an increased likelihood of extremes like the 2015 case. Indeed, two record-high warm-season precipitation events, the 1993 and 2008 cases, both occurred in the more recent decades of the 66 year analysis period. The export of water from the North Atlantic leaves a marked surface salinity signature. The salinity signature appeared in the spring preceding all three extreme precipitation events analyzed in this study, i.e. a saltier-than-normal subtropical North Atlantic in spring followed by extreme Midwest precipitation in summer. Compared to the various sea surface temperature anomaly patterns among the 1993, 2008, and 2015 cases, the spatial distribution of salinity anomalies was much more consistent during these extreme flood years. Thus, our study suggests that preseason salinity patterns can be used for improved seasonal prediction of extreme precipitation in the Midwest.
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Flood triggering in Switzerland: the role of daily to monthly preceding precipitation
Froidevaux, P.; Schwanbeck, J.; Weingartner, R.; Chevalier, C.; Martius, O.
2015-09-01
Determining the role of different precipitation periods for peak discharge generation is crucial for both projecting future changes in flood probability and for short- and medium-range flood forecasting. In this study, catchment-averaged daily precipitation time series are analyzed prior to annual peak discharge events (floods) in Switzerland. The high number of floods considered - more than 4000 events from 101 catchments have been analyzed - allows to derive significant information about the role of antecedent precipitation for peak discharge generation. Based on the analysis of precipitation times series, a new separation of flood-related precipitation periods is proposed: (i) the period 0 to 1 day before flood days, when the maximum flood-triggering precipitation rates are generally observed, (ii) the period 2 to 3 days before flood days, when longer-lasting synoptic situations generate "significantly higher than normal" precipitation amounts, and (iii) the period from 4 days to 1 month before flood days when previous wet episodes may have already preconditioned the catchment. The novelty of this study lies in the separation of antecedent precipitation into the precursor antecedent precipitation (4 days before floods or earlier, called PRE-AP) and the short range precipitation (0 to 3 days before floods, a period when precipitation is often driven by one persistent weather situation like e.g., a stationary low-pressure system). A precise separation of "antecedent" and "peak-triggering" precipitation is not attempted. Instead, the strict definition of antecedent precipitation periods permits a direct comparison of all catchments. The precipitation accumulating 0 to 3 days before an event is the most relevant for floods in Switzerland. PRE-AP precipitation has only a weak and region-specific influence on flood probability. Floods were significantly more frequent after wet PRE-AP periods only in the Jura Mountains, in the western and eastern Swiss plateau, and at
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Evaluation of TRMM 3B42V7 product on extreme precipitation measurements over peninsular Malaysia
Paska, Jacquoelyne; Lau, Alvin M. S.; Tan, Mou Leong; Tan, Kok Chooi
2017-10-01
Climate variability has become a matter worth our attention as this issue has unveiled to the extreme water-related disasters such as flood and drought. Increments in heavy precipitation have happened over the past century and future climate scenarios show that it may alter the recurrence, timing, force, and length of these occasions. Satellite precipitation products (SPPs) could be used as representation of precipitation over a large region. This could be useful for the monitoring of the precipitation pattern as well as extreme events. Nevertheless, application of these products in monitoring extreme precipitation is still limited because insufficiency of quality assessment. This study aims to evaluate the performance of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42V7 product in capturing the behavior of extreme precipitation events over Peninsular Malaysia from 2000 to 2015. Four extreme precipitation indices, in two general categories of absolute threshold (R10mm, R20mm and R50mm) and maximum (Rx1d) indices that recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) were used. General evaluation has shown that the TRMM 3B42V7 product performed good on the measurements of monthly and annual precipitation. In the respect of extreme precipitation measurements, weak to moderate positive correlations were found between the TRMM 3B42 product and rain gauges over Peninsular Malaysia. The TRMM 3B42V7 product overestimated the R10mm and R20mm indices, while an underestimation was found for the R50mm and Rx1d indices.
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Precipitation extremes and their relation to climatic indices in the Pacific Northwest USA
Zarekarizi, Mahkameh; Rana, Arun; Moradkhani, Hamid
2018-06-01
There has been focus on the influence of climate indices on precipitation extremes in the literature. Current study presents the evaluation of the precipitation-based extremes in Columbia River Basin (CRB) in the Pacific Northwest USA. We first analyzed the precipitation-based extremes using statistically (ten GCMs) and dynamically downscaled (three GCMs) past and future climate projections. Seven precipitation-based indices that help inform about the flood duration/intensity are used. These indices help in attaining first-hand information on spatial and temporal scales for different service sectors including energy, agriculture, forestry etc. Evaluation of these indices is first performed in historical period (1971-2000) followed by analysis of their relation to large scale tele-connections. Further we mapped these indices over the area to evaluate the spatial variation of past and future extremes in downscaled and observational data. The analysis shows that high values of extreme indices are clustered in either western or northern parts of the basin for historical period whereas the northern part is experiencing higher degree of change in the indices for future scenario. The focus is also on evaluating the relation of these extreme indices to climate tele-connections in historical period to understand their relationship with extremes over CRB. Various climate indices are evaluated for their relationship using Principal Component Analysis (PCA) and Singular Value Decomposition (SVD). Results indicated that, out of 13 climate tele-connections used in the study, CRB is being most affected inversely by East Pacific (EP), Western Pacific (WP), East Atlantic (EA) and North Atlaentic Oscillation (NAO).
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The probability distribution of extreme precipitation
Korolev, V. Yu.; Gorshenin, A. K.
2017-12-01
On the basis of the negative binomial distribution of the duration of wet periods calculated per day, an asymptotic model is proposed for distributing the maximum daily rainfall volume during the wet period, having the form of a mixture of Frechet distributions and coinciding with the distribution of the positive degree of a random variable having the Fisher-Snedecor distribution. The method of proving the corresponding result is based on limit theorems for extreme order statistics in samples of a random volume with a mixed Poisson distribution. The adequacy of the models proposed and methods of their statistical analysis is demonstrated by the example of estimating the extreme distribution parameters based on real data.
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Demaria, E. M.; Goodrich, D. C.; Keefer, T.
2017-12-01
Observed sub-daily precipitation intensities from contrasting hydroclimatic environments in the USA are used to evaluate temporal trends and to develop Intensity-Duration Frequency (IDF) curves under stationary and nonstationary climatic conditions. Analyses are based on observations from two United States Department of Agriculture (USDA)-Agricultural Research Service (ARS) experimental watersheds located in a semi-arid and a temperate environment. We use an Annual Maximum Series (AMS) and a Partial Duration Series (PDS) approach to identify temporal trends in maximum intensities for durations ranging from 5- to 1440-minutes. A Bayesian approach with Monte Carlo techniques is used to incorporate the effect of non-stationary climatic assumptions in the IDF curves. The results show increasing trends in observed AMS sub-daily intensities in both watersheds whereas trends in the PDS observations are mostly positive in the semi-arid site and a mix of positive and negative in the temperate site. Stationary climate assumptions lead to much lower estimated sub-daily intensities than those under non-stationary assumptions with larger absolute differences found for shorter durations and smaller return periods. The risk of failure (R) of a hydraulic structure is increased for non-stationary effects over those of stationary effects, with absolute differences of 25% for a 100-year return period (T) and a project life (n) of 100 years. The study highlights the importance of considering non-stationarity, due to natural variability or to climate change, in storm design.
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Energy Technology Data Exchange (ETDEWEB)
Heikkilae, U. [Bjerknes Centre for Climate Research, Uni Bjerknes Centre, Bergen (Norway); Australian Nuclear Science and Technology Organisation (ANSTO), Lucas Heights, NSW (Australia); Sorteberg, A. [University of Bergen, Geophysical Institute, Bergen (Norway); University of Bergen, Bjerknes Centre for Climate Research, Bergen (Norway)
2012-08-15
Extremely high autumn and winter precipitation events on the European west coast are often driven by low-pressure systems in the North Atlantic. Climate projections suggest the number and intensity of these events is likely to increase far more than the mean precipitation. In this study we investigate the autumn-winter extreme precipitation on the Norwegian west coast and the connection between its spatial distribution and sea level pressure (SLP) patterns using the k-means cluster analysis. We use three relatively high resolved downscalings of one global coupled model: the Arpege global atmospheric model (stretched grid with 35-km horizontal resolution over Norway) and the WRF-downscaled Arpege model (30 and 10-km) for the 30-year periods of 1961-1990 and 2021-2050. The cluster analysis finds three main SLP patterns responsible for extreme precipitation in different parts of the country. The SLP patterns found are similar to the NAO positive pattern known to strengthen the westerly flow towards European coast. We then apply the method to investigate future change in extreme precipitation. We find an increase in the number of days with extreme precipitation of 15, 39 and 35% in the two simulations (Arpege 35-km and WRF 30 and 10-km, respectively). We do not find evidence of a significant change in the frequency of weather patterns between the present and the future periods. Rather, it is the probability of a given weather pattern to cause extreme precipitation which is increased in the future, probably due to higher temperatures and an increased moisture content of the air. The WRF model predicts the increase in this probability caused by the most important SLP patterns to be >50%. The Arpege model does not predict such a significant change because the general increase in extreme precipitation predicted is smaller, probably due to its coarser resolution over ocean which leads to smoother representation of the low pressure systems. (orig.)
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Drobinski, P.; Alonzo, B.; Bastin, S.; Silva, N. Da; Muller, C.
2016-04-01
Expected changes to future extreme precipitation remain a key uncertainty associated with anthropogenic climate change. Extreme precipitation has been proposed to scale with the precipitable water content in the atmosphere. Assuming constant relative humidity, this implies an increase of precipitation extremes at a rate of about 7% °C-1 globally as indicated by the Clausius-Clapeyron relationship. Increases faster and slower than Clausius-Clapeyron have also been reported. In this work, we examine the scaling between precipitation extremes and temperature in the present climate using simulations and measurements from surface weather stations collected in the frame of the HyMeX and MED-CORDEX programs in Southern France. Of particular interest are departures from the Clausius-Clapeyron thermodynamic expectation, their spatial and temporal distribution, and their origin. Looking at the scaling of precipitation extreme with temperature, two regimes emerge which form a hook shape: one at low temperatures (cooler than around 15°C) with rates of increase close to the Clausius-Clapeyron rate and one at high temperatures (warmer than about 15°C) with sub-Clausius-Clapeyron rates and most often negative rates. On average, the region of focus does not seem to exhibit super Clausius-Clapeyron behavior except at some stations, in contrast to earlier studies. Many factors can contribute to departure from Clausius-Clapeyron scaling: time and spatial averaging, choice of scaling temperature (surface versus condensation level), and precipitation efficiency and vertical velocity in updrafts that are not necessarily constant with temperature. But most importantly, the dynamical contribution of orography to precipitation in the fall over this area during the so-called "Cevenoles" events, explains the hook shape of the scaling of precipitation extremes.
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Rajczak, Jan; Schär, Christoph
2017-10-01
Projections of precipitation and its extremes over the European continent are analyzed in an extensive multimodel ensemble of 12 and 50 km resolution EURO-CORDEX Regional Climate Models (RCMs) forced by RCP2.6, RCP4.5, and RCP8.5 (Representative Concentration Pathway) aerosol and greenhouse gas emission scenarios. A systematic intercomparison with ENSEMBLES RCMs is carried out, such that in total information is provided for an unprecedentedly large data set of 100 RCM simulations. An evaluation finds very reasonable skill for the EURO-CORDEX models in simulating temporal and geographical variations of (mean and heavy) precipitation at both horizontal resolutions. Heavy and extreme precipitation events are projected to intensify across most of Europe throughout the whole year. All considered models agree on a distinct intensification of extremes by often more than +20% in winter and fall and over central and northern Europe. A reduction of rainy days and mean precipitation in summer is simulated by a large majority of models in the Mediterranean area, but intermodel spread between the simulations is large. In central Europe and France during summer, models project decreases in precipitation but more intense heavy and extreme rainfalls. Comparison to previous RCM projections from ENSEMBLES reveals consistency but slight differences in summer, where reductions in southern European precipitation are not as pronounced as previously projected. The projected changes of the European hydrological cycle may have substantial impact on environmental and anthropogenic systems. In particular, the simulations indicate a rising probability of summertime drought in southern Europe and more frequent and intense heavy rainfall across all of Europe.
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Syafrina, A. H.; Zalina, M. D.; Juneng, L.
2014-09-01
A stochastic downscaling methodology known as the Advanced Weather Generator, AWE-GEN, has been tested at four stations in Peninsular Malaysia using observations available from 1975 to 2005. The methodology involves a stochastic downscaling procedure based on a Bayesian approach. Climate statistics from a multi-model ensemble of General Circulation Model (GCM) outputs were calculated and factors of change were derived to produce the probability distribution functions (PDF). New parameters were obtained to project future climate time series. A multi-model ensemble was used in this study. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081-2100). The model was able to simulate both hourly and 24-h extreme precipitation, as well as wet spell durations quite well for almost all regions. However, the performance of GCM models varies significantly in all regions showing high variability of monthly precipitation for both observed and future periods. The extreme precipitation for both hourly and 24-h seems to increase in future, while extreme of wet spells remain unchanged, up to the return periods of 10-40 years.
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Francia B. Avila; Siyan Dong; Kaah P. Menang; Jan Rajczak; Madeleine Renom; Markus G. Donat; Lisa V. Alexander
2015-01-01
Using daily station observations over the period 1951–2013 in a region of south-east Australia, we systematically compare how the horizontal resolution, interpolation method and order of operation in generating gridded data sets affect estimates of annual extreme indices of temperature and precipitation maxima (hottest and wettest days). Three interpolation methods (natural neighbors, cubic spline and angular distance weighting) are used to calculate grids at five different horizontal gridded...
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Predictability of summer extreme precipitation days over eastern China
Li, Juan; Wang, Bin
2017-08-01
Extreme precipitation events have severe impacts on human activity and natural environment, but prediction of extreme precipitation events remains a considerable challenge. The present study aims to explore the sources of predictability and to estimate the predictability of the summer extreme precipitation days (EPDs) over eastern China. Based on the region- and season-dependent variability of EPDs, all stations over eastern China are divided into two domains: South China (SC) and northern China (NC). Two domain-averaged EPDs indices during their local high EPDs seasons (May-June for SC and July-August for NC) are therefore defined. The simultaneous lower boundary anomalies associated with each EPDs index are examined, and we find: (a) the increased EPDs over SC are related to a rapid decaying El Nino and controlled by Philippine Sea anticyclone anomalies in May-June; (b) the increased EPDs over NC are accompanied by a developing La Nina and anomalous zonal sea level pressure contrast between the western North Pacific subtropical high and East Asian low in July-August. Tracking back the origins of these boundary anomalies, one or two physically meaningful predictors are detected for each regional EPDs index. The causative relationships between the predictors and the corresponding EPDs over each region are discussed using lead-lag correlation analyses. Using these selected predictors, a set of Physics-based Empirical models is derived. The 13-year (2001-2013) independent forecast shows significant temporal correlation skills of 0.60 and 0.74 for the EPDs index of SC and NC, respectively, providing an estimation of the predictability for summer EPDs over eastern China.
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Pelle, A.; Allen, M.; Fu, J. S.
2013-12-01
With rising population and increasing urban density, it is of pivotal importance for urban planners to plan for increasing extreme precipitation events. Climate models indicate that an increase in global mean temperature will lead to increased frequency and intensity of storms of a variety of types. Analysis of results from the Coupled Model Intercomparison Project, Phase 5 (CMIP5) has demonstrated that global climate models severely underestimate precipitation, however. Preliminary results from dynamical downscaling indicate that Philadelphia, Pennsylvania is expected to experience the greatest increase of precipitation due to an increase in annual extreme events in the US. New York City, New York and Chicago, Illinois are anticipated to have similarly large increases in annual extreme precipitation events. In order to produce more accurate results, we downscale Philadelphia, Chicago, and New York City using the Weather Research and Forecasting model (WRF). We analyze historical precipitation data and WRF output utilizing a Log Pearson Type III (LP3) distribution for frequency of extreme precipitation events. This study aims to determine the likelihood of extreme precipitation in future years and its effect on the of cost of stormwater management for these three cities.
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Gridded 5km GHCN-Daily Temperature and Precipitation Dataset, Version 1
National Oceanic and Atmospheric Administration, Department of Commerce — The Gridded 5km GHCN-Daily Temperature and Precipitation Dataset (nClimGrid) consists of four climate variables derived from the GHCN-D dataset: maximum temperature,...
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Climate Prediction Center(CPC)Daily U.S. Precipitation and Temperature Summary
National Oceanic and Atmospheric Administration, Department of Commerce — Daily U.S. minimum and maximum temperatures in whole degrees Fahrenheit and reported and estimated precipitation amounts in hundredths of inches(ex 100 is 1.00...
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DEFF Research Database (Denmark)
Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten
gauges in the model area. The spatio-temporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatio-temporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying onprecipitation output......Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...
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Observed increase in extreme daily rainfall in the French Mediterranean
Ribes, Aurélien; Thao, Soulivanh; Vautard, Robert; Dubuisson, Brigitte; Somot, Samuel; Colin, Jeanne; Planton, Serge; Soubeyroux, Jean-Michel
2018-04-01
We examine long-term trends in the historical record of extreme precipitation events occurring over the French Mediterranean area. Extreme events are considered in terms of their intensity, frequency, extent and precipitated volume. Changes in intensity are analysed via an original statistical approach where the annual maximum rainfall amounts observed at each measurement station are aggregated into a univariate time-series according to their dependence. The mean intensity increase is significant and estimated at + 22% (+ 7 to + 39% at the 90% confidence level) over the 1961-2015 period. Given the observed warming over the considered area, this increase is consistent with a rate of about one to three times that implied by the Clausius-Clapeyron relationship. Changes in frequency and other spatial features are investigated through a Generalised Linear Model. Changes in frequency for events exceeding high thresholds (about 200 mm in 1 day) are found to be significant, typically near a doubling of the frequency, but with large uncertainties in this change ratio. The area affected by severe events and the water volume precipitated during those events also exhibit significant trends, with an increase by a factor of about 4 for a 200 mm threshold, again with large uncertainties. All diagnoses consistently point toward an intensification of the most extreme events over the last decades. We argue that it is difficult to explain the diagnosed trends without invoking the human influence on climate.
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International Nuclear Information System (INIS)
Grimm, J.W.; Lynch, J.A.
2005-01-01
Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8 km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8 km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate. - A linear least-squares regression approach was used to develop daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed
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Sensitivity of Rainfall Extremes Under Warming Climate in Urban India
Ali, H.; Mishra, V.
2017-12-01
Extreme rainfall events in urban India halted transportation, damaged infrastructure, and affected human lives. Rainfall extremes are projected to increase under the future climate. We evaluated the relationship (scaling) between rainfall extremes at different temporal resolutions (daily, 3-hourly, and 30 minutes), daily dewpoint temperature (DPT) and daily air temperature at 850 hPa (T850) for 23 urban areas in India. Daily rainfall extremes obtained from Global Surface Summary of Day Data (GSOD) showed positive regression slopes for most of the cities with median of 14%/K for the period of 1979-2013 for DPT and T850, which is higher than Clausius-Clapeyron (C-C) rate ( 7%). Moreover, sub-daily rainfall extremes are more sensitive to both DPT and T850. For instance, 3-hourly rainfall extremes obtained from Tropical Rainfall Measurement Mission (TRMM 3B42 V7) showed regression slopes more than 16%/K aginst DPT and T850 for the period of 1998-2015. Half-hourly rainfall extremes from the Integrated Multi-satellitE Retrievals (IMERGE) of Global precipitation mission (GPM) also showed higher sensitivity against changes in DPT and T850. The super scaling of rainfall extremes against changes in DPT and T850 can be attributed to convective nature of precipitation in India. Our results show that urban India may witness non-stationary rainfall extremes, which, in turn will affect stromwater designs and frequency and magniture of urban flooding.
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Directory of Open Access Journals (Sweden)
A. H. Syafrina
2014-09-01
Full Text Available A stochastic downscaling methodology known as the Advanced Weather Generator, AWE-GEN, has been tested at four stations in Peninsular Malaysia using observations available from 1975 to 2005. The methodology involves a stochastic downscaling procedure based on a Bayesian approach. Climate statistics from a multi-model ensemble of General Circulation Model (GCM outputs were calculated and factors of change were derived to produce the probability distribution functions (PDF. New parameters were obtained to project future climate time series. A multi-model ensemble was used in this study. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081–2100. The model was able to simulate both hourly and 24-h extreme precipitation, as well as wet spell durations quite well for almost all regions. However, the performance of GCM models varies significantly in all regions showing high variability of monthly precipitation for both observed and future periods. The extreme precipitation for both hourly and 24-h seems to increase in future, while extreme of wet spells remain unchanged, up to the return periods of 10–40 years.
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Krab, E.J.; Aerts, R.; Berg, M.P.; van Hal, J.R.; Keuper, F.
2014-01-01
Extreme climate events are observed and predicted to increase in frequency and duration in high-latitude ecosystems as a result of global climate change. This includes extreme precipitation events, which may directly impact on belowground food webs and ecosystem functioning by their physical impacts
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Factors favorable to frequent extreme precipitation in the upper Yangtze River Valley
Tian, Baoqiang; Fan, Ke
2013-08-01
Extreme precipitation events in the upper Yangtze River Valley (YRV) have recently become an increasingly important focus in China because they often cause droughts and floods. Unfortunately, little is known about the climate processes responsible for these events. This paper investigates factors favorable to frequent extreme precipitation events in the upper YRV. Our results reveal that a weakened South China Sea summer monsoon trough, intensified Eurasian-Pacific blocking highs, an intensified South Asian High, a southward subtropical westerly jet and an intensified Western North Pacific Subtropical High (WNPSH) increase atmospheric instability and enhance the convergence of moisture over the upper YRV, which result in more extreme precipitation events. The snow depth over the eastern Tibetan Plateau (TP) in winter and sea surface temperature anomalies (SSTAs) over three key regions in summer are important external forcing factors in the atmospheric circulation anomalies. Deep snow on the Tibetan Plateau in winter can weaken the subsequent East Asian summer monsoon circulation above by increasing the soil moisture content in summer and weakening the land-sea thermal contrast over East Asia. The positive SSTA in the western North Pacific may affect southwestward extension of the WNPSH and the blocking high over northeastern Asia by arousing the East Asian-Pacific pattern. The positive SSTA in the North Atlantic can affect extreme precipitation event frequency in the upper YRV via a wave train pattern along the westerly jet between the North Atlantic and East Asia. A tripolar pattern from west to east over the Indian Ocean can strengthen moisture transport by enhancing Somali cross-equatorial flow.
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Felton, A. J.; Smith, M. D.
2016-12-01
Heightened climatic variability due to atmospheric warming is forecast to increase the frequency and severity of climate extremes. In particular, changes to interannual variability in precipitation, characterized by increases in extreme wet and dry years, are likely to impact virtually all terrestrial ecosystem processes. However, to date experimental approaches have yet to explicitly test how ecosystem processes respond to multiple levels of climatic extremity, limiting our understanding of how ecosystems will respond to forecast increases in the magnitude of climate extremes. Here we report the results of a replicated regression experimental approach, in which we imposed 9 and 11 levels of growing season precipitation amount and extremity in mesic grassland during 2015 and 2016, respectively. Each level corresponded to a specific percentile of the long-term record, which produced a large gradient of soil moisture conditions that ranged from extreme wet to extreme dry. In both 2015 and 2016, asymptotic responses to water availability were observed for soil respiration. This asymmetry was driven in part by transitions between soil moisture versus temperature constraints on respiration as conditions became increasingly dry versus increasingly wet. In 2015, aboveground net primary production (ANPP) exhibited asymmetric responses to precipitation that largely mirrored those of soil respiration. In total, our results suggest that in this mesic ecosystem, these two carbon cycle processes were more sensitive to extreme drought than to extreme wet years. Future work will assess ANPP responses for 2016, soil nutrient supply and physiological responses of the dominant plant species. Future efforts are needed to compare our findings across a diverse array of ecosystem types, and in particular how the timing and magnitude of precipitation events may modify the response of ecosystem processes to increasing magnitudes of precipitation extremes.
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Projection of extreme precipitation in the context of climate change ...
Indian Academy of Sciences (India)
tion, maximum 1-day precipitation and simple daily intensity to do ... The study area spans far and wide. It reaches .... design flood, and it is also an important purpose to study the ..... bridge University Press, Cambridge. Jinshan Zhang, Xingju ...
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TAO/TRITON, RAMA, and PIRATA Buoys, Daily, 1997-present, Evaporation Minus Precipitation
National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Evaporation Minus Precipitation data from the TAO/TRITON (Pacific Ocean, https://www.pmel.noaa.gov/gtmba/ ), RAMA (Indian Ocean,...
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Trends in Middle East climate extreme indices from 1950 to 2003
Zhang, Xuebin; Aguilar, Enric; Sensoy, Serhat; Melkonyan, Hamlet; Tagiyeva, Umayra; Ahmed, Nader; Kutaladze, Nato; Rahimzadeh, Fatemeh; Taghipour, Afsaneh; Hantosh, T. H.; Albert, Pinhas; Semawi, Mohammed; Karam Ali, Mohammad; Said Al-Shabibi, Mansoor Halal; Al-Oulan, Zaid; Zatari, Taha; Al Dean Khelet, Imad; Hamoud, Saleh; Sagir, Ramazan; Demircan, Mesut; Eken, Mehmet; Adiguzel, Mustafa; Alexander, Lisa; Peterson, Thomas C.; Wallis, Trevor
2005-11-01
A climate change workshop for the Middle East brought together scientists and data for the region to produce the first area-wide analysis of climate extremes for the region. This paper reports trends in extreme precipitation and temperature indices that were computed during the workshop and additional indices data that became available after the workshop. Trends in these indices were examined for 1950-2003 at 52 stations covering 15 countries, including Armenia, Azerbaijan, Bahrain, Cyprus, Georgia, Iran, Iraq, Israel, Jordan, Kuwait, Oman, Qatar, Saudi Arabia, Syria, and Turkey. Results indicate that there have been statistically significant, spatially coherent trends in temperature indices that are related to temperature increases in the region. Significant, increasing trends have been found in the annual maximum of daily maximum and minimum temperature, the annual minimum of daily maximum and minimum temperature, the number of summer nights, and the number of days where daily temperature has exceeded its 90th percentile. Significant negative trends have been found in the number of days when daily temperature is below its 10th percentile and daily temperature range. Trends in precipitation indices, including the number of days with precipitation, the average precipitation intensity, and maximum daily precipitation events, are weak in general and do not show spatial coherence. The workshop attendees have generously made the indices data available for the international research community.
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Mean annual precipitation predicts primary production resistance and resilience to extreme drought.
Stuart-Haëntjens, Ellen; De Boeck, Hans J; Lemoine, Nathan P; Mänd, Pille; Kröel-Dulay, György; Schmidt, Inger K; Jentsch, Anke; Stampfli, Andreas; Anderegg, William R L; Bahn, Michael; Kreyling, Juergen; Wohlgemuth, Thomas; Lloret, Francisco; Classen, Aimée T; Gough, Christopher M; Smith, Melinda D
2018-04-27
Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitation (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought - a vulnerability that is expected to compound as extreme drought frequency increases in the future. Copyright © 2018. Published by Elsevier B.V.
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Institute of Scientific and Technical Information of China (English)
LI Hongmei; FENG Lei; ZHOU Tianjun
2011-01-01
Potential changes in precipitation extremes in July-August over China in response to CO2 doubling are analyzed based on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models (20C3M) experiment and the 1％ per year CO2 increase experiment (to doubling) (lpctto2x) of phase 3 of the Coupled Model Inter-comparison Project (CMIP3). Evaluation of the models' performance in simulating the mean state shows that the majority of models fairly reproduce the broad spatial pattern of observed precipitation. However, all the models underestimate extreme precipitation by ～50％. The spread among the models over the Tibetan Plateau is ～2-3 times larger than that over the other areas.Models with higher resolution generally perform better than those with lower resolutions in terms of spatial pattern and precipitation amount. Under the lpctto2x scenario, the ratio between the absolute value of MME extreme precipitation change and model spread is larger than that of total precipitation, indicating a relatively robust change of extremes. The change of extreme precipitation is more homogeneous than the total precipitation. Analysis on the output of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 (GFDL-CM2.1) indicates that the spatially consistent increase of surface temperature and water vapor content contribute to the large increase of extreme precipitation over contiguous China,which follows the Clausius-Clapeyron relationship. Whereas, the meridionally tri-polar pattern of mean precipitation change over eastern China is dominated by the change of water vapor convergence, which is determined by the response of monsoon circulation to global warming.
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Mauger, G. S.; Lorente-Plazas, R.; Salathe, E. P., Jr.; Mitchell, T. P.; Simmonds, J.; Lee, S. Y.; Hegewisch, K.; Warner, M.; Won, J.
2017-12-01
King County has experienced 12 federally declared flood disasters since 1990, and tens of thousands of county residents commute through, live, and work in floodplains. In addition to flooding, stormwater is a critical management challenge, exacerbated by aging infrastructure, combined sewer and drainage systems, and continued development. Even absent the effects of climate change these are challenging management issues. Recent studies clearly point to an increase in precipitation extremes for the Pacific Northwest (e.g., Warner et al. 2015). Yet very little information is available on the magnitude and spatial distribution of this change. Others clearly show that local-scale changes in extreme precipitation can only be accurately quantified with dynamical downscaling, i.e.: using a regional climate model. This talk will describe a suite of research and adaptation efforts developed in a close collaboration between King County and the UW Climate Impacts Group. Building on past collaborations, research efforts were defined in collaboration with King County managers, addressing three key science questions: (1) How are the mesoscale variations in extreme precipitation modulated by changes in large-scale weather conditions? (2) How will precipitation extremes change? This was assessed via two new high-resolution regional model projections using the Weather Research and Forecasting (WRF) mesoscale model (Skamarock et al. 2005). (3) What are the implications for stormwater and flooding in King County? This was assessed by both exploring the statistics of hourly precipitation extremes in the new projections, as well as new hydrologic modeling to assess the implications for river flooding. The talk will present results from these efforts, review the implications for King County planning and infrastructure, and synthesize lessons learned and opportunities for additional work.
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Neural network based daily precipitation generator (NNGEN-P)
Energy Technology Data Exchange (ETDEWEB)
Boulanger, Jean-Philippe [LODYC, UMR CNRS/IRD/UPMC, Paris (France); University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Martinez, Fernando; Segura, Enrique C. [University of Buenos Aires, Departamento de Computacion, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Penalba, Olga [University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina)
2007-02-15
Daily weather generators are used in many applications and risk analyses. The present paper explores the potential of neural network architectures to design daily weather generator models. Focusing this first paper on precipitation, we design a collection of neural networks (multi-layer perceptrons in the present case), which are trained so as to approximate the empirical cumulative distribution (CDF) function for the occurrence of wet and dry spells and for the precipitation amounts. This approach contributes to correct some of the biases of the usual two-step weather generator models. As compared to a rainfall occurrence Markov model, NNGEN-P represents fairly well the mean and standard deviation of the number of wet days per month, and it significantly improves the simulation of the longest dry and wet periods. Then, we compared NNGEN-P to three parametric distribution functions usually applied to fit rainfall cumulative distribution functions (Gamma, Weibull and double-exponential). A data set of 19 Argentine stations was used. Also, data corresponding to stations in the United States, in Europe and in the Tropics were included to confirm the results. One of the advantages of NNGEN-P is that it is non-parametric. Unlike other parametric function, which adapt to certain types of climate regimes, NNGEN-P is fully adaptive to the observed cumulative distribution functions, which, on some occasions, may present complex shapes. On-going works will soon produce an extended version of NNGEN to temperature and radiation. (orig.)
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High resolution modelling of extreme precipitation events in urban areas
Siemerink, Martijn; Volp, Nicolette; Schuurmans, Wytze; Deckers, Dave
2015-04-01
The present day society needs to adjust to the effects of climate change. More extreme weather conditions are expected, which can lead to longer periods of drought, but also to more extreme precipitation events. Urban water systems are not designed for such extreme events. Most sewer systems are not able to drain the excessive storm water, causing urban flooding. This leads to high economic damage. In order to take appropriate measures against extreme urban storms, detailed knowledge about the behaviour of the urban water system above and below the streets is required. To investigate the behaviour of urban water systems during extreme precipitation events new assessment tools are necessary. These tools should provide a detailed and integral description of the flow in the full domain of overland runoff, sewer flow, surface water flow and groundwater flow. We developed a new assessment tool, called 3Di, which provides detailed insight in the urban water system. This tool is based on a new numerical methodology that can accurately deal with the interaction between overland runoff, sewer flow and surface water flow. A one-dimensional model for the sewer system and open channel flow is fully coupled to a two-dimensional depth-averaged model that simulates the overland flow. The tool uses a subgrid-based approach in order to take high resolution information of the sewer system and of the terrain into account [1, 2]. The combination of using the high resolution information and the subgrid based approach results in an accurate and efficient modelling tool. It is now possible to simulate entire urban water systems using extreme high resolution (0.5m x 0.5m) terrain data in combination with a detailed sewer and surface water network representation. The new tool has been tested in several Dutch cities, such as Rotterdam, Amsterdam and The Hague. We will present the results of an extreme precipitation event in the city of Schiedam (The Netherlands). This city deals with
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DEFF Research Database (Denmark)
Hundecha, Yeshewatesfa; Sunyer Pinya, Maria Antonia; Lawrence, Deborah
2016-01-01
The effect of methods of statistical downscaling of daily precipitation on changes in extreme flow indices under a plausible future climate change scenario was investigated in 11 catchments selected from 9 countries in different parts of Europe. The catchments vary from 67 to 6171km2 in size...... catchments to simulate daily runoff. A set of flood indices were derived from daily flows and their changes have been evaluated by comparing their values derived from simulations corresponding to the current and future climate. Most of the implemented downscaling methods project an increase in the extreme...... flow indices in most of the catchments. The catchments where the extremes are expected to increase have a rainfall-dominated flood regime. In these catchments, the downscaling methods also project an increase in the extreme precipitation in the seasons when the extreme flows occur. In catchments where...
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Projecting changes in regional temperature and precipitation extremes in the United States
Justin T. Schoof; Scott M. Robeson
2016-01-01
Regional and local climate extremes, and their impacts, result from the multifaceted interplay between large-scale climate forcing, local environmental factors (physiography), and societal vulnerability. In this paper, we review historical and projected changes in temperature and precipitation extremes in the United States, with a focus on strengths and weaknesses of (1) commonly used definitions for extremes such as thresholds and percentiles, (2) statistical approaches to quantifying change...
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Ragulina, Galina; Reitan, Trond
2016-04-01
Assessing the probability of extreme precipitation events is of great importance in civil planning. This requires understanding of how return values change with different return periods, which is essentially described by the Generalized Extreme Value distribution's shape parameter. Some works in the field have suggested a constant shape parameter, while our analysis indicates a non-universal value. We first re-analyse an older precipitation dataset (169 stations) extended by Norwegian data (71 stations). We show that while each set seems to have a constant shape parameter, it differs between the two datasets, indicating regional differences. For a more comprehensive analysis of spatial effects, we examine a global dataset (1495 stations). We provide shape parameter maps for two models. We find clear evidence for the shape parameter being dependent on elevation while the effect of latitude remains uncertain. Our results confirm an explanation in terms of dominating precipitation systems based on a proxy derived from the Köppen-Geiger climate classification.
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Cifelli, R.; Mahoney, K. M.; Webb, R. S.; McCormick, B.
2017-12-01
To ensure structural and operational safety of dams and other water management infrastructure, water resources managers and engineers require information about the potential for heavy precipitation. The methods and data used to estimate extreme rainfall amounts for managing risk are based on 40-year-old science and in need of improvement. The need to evaluate new approaches based on the best science available has led the states of Colorado and New Mexico to engage a body of scientists and engineers in an innovative "ensemble approach" to updating extreme precipitation estimates. NOAA is at the forefront of one of three technical approaches that make up the "ensemble study"; the three approaches are conducted concurrently and in collaboration with each other. One approach is the conventional deterministic, "storm-based" method, another is a risk-based regional precipitation frequency estimation tool, and the third is an experimental approach utilizing NOAA's state-of-the-art High Resolution Rapid Refresh (HRRR) physically-based dynamical weather prediction model. The goal of the overall project is to use the individual strengths of these different methods to define an updated and broadly acceptable state of the practice for evaluation and design of dam spillways. This talk will highlight the NOAA research and NOAA's role in the overarching goal to better understand and characterizing extreme precipitation estimation uncertainty. The research led by NOAA explores a novel high-resolution dataset and post-processing techniques using a super-ensemble of hourly forecasts from the HRRR model. We also investigate how this rich dataset may be combined with statistical methods to optimally cast the data in probabilistic frameworks. NOAA expertise in the physical processes that drive extreme precipitation is also employed to develop careful testing and improved understanding of the limitations of older estimation methods and assumptions. The process of decision making in the
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Characteristics of extreme precipitation in the Vosges Mountains region (north-eastern France)
Czech Academy of Sciences Publication Activity Database
Minářová, Jana; Müller, Miloslav; Clappier, A.; Kašpar, Marek
2017-01-01
Roč. 37, č. 13 (2017), s. 4529-4542 ISSN 0899-8418 Institutional support: RVO:68378289 Keywords : Vosges Mountains * extreme precipitation * heavy rainfall * WEI * synoptic conditions * precipitation * Grosswetterlagen * trend analysis Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 3.760, year: 2016 http://onlinelibrary.wiley.com/doi/10.1002/joc.5102/abstract
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Directory of Open Access Journals (Sweden)
Tao Gao
2014-01-01
Full Text Available Extreme precipitation is likely to be one of the most severe meteorological disasters in China; however, studies on the physical factors affecting precipitation extremes and corresponding prediction models are not accurately available. From a new point of view, the sensible heat flux (SHF and latent heat flux (LHF, which have significant impacts on summer extreme rainfall in Yangtze River basin (YRB, have been quantified and then selections of the impact factors are conducted. Firstly, a regional extreme precipitation index was applied to determine Regions of Significant Correlation (RSC by analyzing spatial distribution of correlation coefficients between this index and SHF, LHF, and sea surface temperature (SST on global ocean scale; then the time series of SHF, LHF, and SST in RSCs during 1967–2010 were selected. Furthermore, other factors that significantly affect variations in precipitation extremes over YRB were also selected. The methods of multiple stepwise regression and leave-one-out cross-validation (LOOCV were utilized to analyze and test influencing factors and statistical prediction model. The correlation coefficient between observed regional extreme index and model simulation result is 0.85, with significant level at 99%. This suggested that the forecast skill was acceptable although many aspects of the prediction model should be improved.
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Responses of Mean and Extreme Precipitation to Deforestation in the Maritime Continent
Chen, C. C.; Lo, M. H.; Yu, J. Y.
2017-12-01
Anthropogenic land use and land cover change, including tropical deforestation, could have substantial effects on local surface energy and water budgets, and thus on the atmospheric stability which may result in changes in precipitation. Maritime Continent has undergone severe deforestation in recent decades but has received less attention than Amazon or Congo rainforests. Therefore, this study is to decipher the precipitation response to deforestation in the Maritime Continent. We conduct deforestation experiments using Community Earth System Model (CESM) and through converting the tropical rainforest into grassland. The results show that deforestation in Maritime Continent leads to an increase in both mean temperature and mean precipitation. Moisture budget analysis indicates that the increase in precipitation is associated with the vertically integrated vertical moisture advection, especially the dynamic component (changes in convection). In addition, through moist static energy (MSE) budget analysis, we find the atmosphere among deforested areas become unstable owing to the combined effects of positive specific humidity anomalies at around 850 hPa and anomalous warming extended from the surface to 750 hPa. This instability will induce anomalous ascending motion, which could enhance the low-level moisture convergence, providing water vapor from the surrounding warm ocean. To further evaluate the precipitation response to deforestation, we examine the precipitation changes under La Niña events and global warming scenario using CESM Atmospheric Model Intercomparison Project (AMIP) simulations and Representative Concentration Pathway (RCP) 8.5 simulations. We find that the precipitation increase caused by deforestation in Maritime Continent is comparable in magnitude to that generated by either natural variability or global warming forcing. Besides the changes in mean precipitation, preliminary results show the extreme precipitation also increases. We will further
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Lorenz, Ruth; Argueso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Cheruy, Frederique; Ducharne, Agnes; Hagemann, Stefan; Meier, Arndt; Milly, Paul C.D.; Seneviratne, Sonia I
2016-01-01
We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.
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Detecting the effect of urban land use on extreme precipitation in the Netherlands
Rahimpour Golroudbary, Vahid; Zeng, Y.; Mannaerts, C.M.; Su, Z.
2017-01-01
A notable increase in heavy precipitation has been observed over the Netherlands in recent decades. The aim of this study was to assess the influences of urban land use on these extreme precipitation patterns. Significant differences between an earlier multi-decadal period and a recent period were
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Qin, P.; Xie, Z.
2017-12-01
Future precipitation extremes in China for the mid and end of 21st century were detected with six simulations using the regional climate model RegCM4 (RCM) and 17 global climate models (GCM) participated in the coupled Model Intercomparison Project Phase 5 (CMIP5). Prior to understanding the future changes in precipitation extremes, we overviewed the performance of precipitation extremes simulated by the CMIP5s and RCMs, and found both CMIP5s and RCMs could capture the temporal and spatial pattern of the historical precipitation extremes in China. In the mid-future period 2039-2058 (MF) and far-future 2079-2098 (FF), more wet precipitation extremes will occur in most area of China relative to the present period 1982-2001 (RF). We quantified the rates of the changes in precipitation extremes in China with the changes in air surface temperature (T2M) for the MF and FF period. Changes in precipitation extremes R95p were found around 5% K-1 for the MF period and 10% K-1 for the FF period, and changes in maximum 5 day precipitation (Rx5day) were detected around 4% K-1 for the MF period and 7% K-1 for the FF period, respectively. Finally, the possible physical mechanisms behind the changes in precipitation extremes in China were also discussed through the changes in specific humidity and vertical wind.
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Van Uytven, Els; Willems, Patrick
2017-04-01
Current trends in the hydro-meteorological variables indicate the potential impact of climate change on hydrological extremes. Therefore, they trigger an increased importance climate adaptation strategies in water management. The impact of climate change on hydro-meteorological and hydrological extremes is, however, highly uncertain. This is due to uncertainties introduced by the climate models, the internal variability inherent to the climate system, the greenhouse gas scenarios and the statistical downscaling methods. In view of the need to define sustainable climate adaptation strategies, there is a need to assess these uncertainties. This is commonly done by means of ensemble approaches. Because more and more climate models and statistical downscaling methods become available, there is a need to facilitate the climate impact and uncertainty analysis. A Climate Perturbation Tool has been developed for that purpose, which combines a set of statistical downscaling methods including weather typing, weather generator, transfer function and advanced perturbation based approaches. By use of an interactive interface, climate impact modelers can apply these statistical downscaling methods in a semi-automatic way to an ensemble of climate model runs. The tool is applicable to any region, but has been demonstrated so far to cases in Belgium, Suriname, Vietnam and Bangladesh. Time series representing future local-scale precipitation, temperature and potential evapotranspiration (PET) conditions were obtained, starting from time series of historical observations. Uncertainties on the future meteorological conditions are represented in two different ways: through an ensemble of time series, and a reduced set of synthetic scenarios. The both aim to span the full uncertainty range as assessed from the ensemble of climate model runs and downscaling methods. For Belgium, for instance, use was made of 100-year time series of 10-minutes precipitation observations and daily
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California Wintertime Precipitation in Regional and Global Climate Models
Energy Technology Data Exchange (ETDEWEB)
Caldwell, P M
2009-04-27
In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California (CA) and compared. Several averaging methodologies are considered and all are found to give similar values when model grid spacing is less than 3{sup o}. This suggests that CA is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict CA precipitation. This appears to be due mainly to overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge/satellite observations which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait which doesn't seem tied to model resolution. GCM daily and interannual variability is generally underpredicted.
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Arnbjerg-Nielsen, K; Funder, S G; Madsen, H
2015-01-01
Climate analogues, also denoted Space-For-Time, may be used to identify regions where the present climatic conditions resemble conditions of a past or future state of another location or region based on robust climate variable statistics in combination with projections of how these statistics change over time. The study focuses on assessing climate analogues for Denmark based on current climate data set (E-OBS) observations as well as the ENSEMBLES database of future climates with the aim of projecting future precipitation extremes. The local present precipitation extremes are assessed by means of intensity-duration-frequency curves for urban drainage design for the relevant locations being France, the Netherlands, Belgium, Germany, the United Kingdom, and Denmark. Based on this approach projected increases of extreme precipitation by 2100 of 9 and 21% are expected for 2 and 10 year return periods, respectively. The results should be interpreted with caution as the best region to represent future conditions for Denmark is the coastal areas of Northern France, for which only little information is available with respect to present precipitation extremes.
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Soneja, Sutyajeet; Jiang, Chengsheng; Fisher, Jared; Upperman, Crystal Romeo; Mitchell, Clifford; Sapkota, Amir
2016-04-27
Several studies have investigated the association between asthma exacerbations and exposures to ambient temperature and precipitation. However, limited data exists regarding how extreme events, projected to grow in frequency, intensity, and duration in the future in response to our changing climate, will impact the risk of hospitalization for asthma. The objective of our study was to quantify the association between frequency of extreme heat and precipitation events and increased risk of hospitalization for asthma in Maryland between 2000 and 2012. We used a time-stratified case-crossover design to examine the association between exposure to extreme heat and precipitation events and risk of hospitalization for asthma (ICD-9 code 493, n = 115,923). Occurrence of extreme heat events in Maryland increased the risk of same day hospitalization for asthma (lag 0) by 3 % (Odds Ratio (OR): 1.03, 95 % Confidence Interval (CI): 1.00, 1.07), with a considerably higher risk observed for extreme heat events that occur during summer months (OR: 1.23, 95 % CI: 1.15, 1.33). Likewise, summertime extreme precipitation events increased the risk of hospitalization for asthma by 11 % in Maryland (OR: 1.11, 95 % CI: 1.06, 1.17). Across age groups, increase in risk for asthma hospitalization from exposure to extreme heat event during the summer months was most pronounced among youth and adults, while those related to extreme precipitation event was highest among ≤4 year olds. Exposure to extreme heat and extreme precipitation events, particularly during summertime, is associated with increased risk of hospitalization for asthma in Maryland. Our results suggest that projected increases in frequency of extreme heat and precipitation event will have significant impact on public health.
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Gao, X.; Schlosser, C. A.
2013-12-01
Global warming is expected to alter the frequency and/or magnitude of extreme precipitation events. Such changes could have substantial ecological, economic, and sociological consequences. However, climate models in general do not correctly reproduce the frequency and intensity distribution of precipitation, especially at the regional scale. In this study, gridded data from a dense network of surface precipitation gauges and a global atmospheric analysis at a coarser scale are combined to develop a diagnostic framework for the large-scale meteorological conditions (i.e. flow features, moisture supply) that dominate during extreme precipitation. Such diagnostic framework is first evaluated with the late 20th century simulations from an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), and is found to produce more consistent (and less uncertain) total and interannaul number of extreme days with the observations than the model-based precipitation over the south-central United States and the Western United States examined in this study. The framework is then applied to the CMIP5 multi-model projections for two radiative forcing scenarios (Representative Concentration Pathways 4.5 and 8.5) to assess the potential future changes in the probability of precipitation extremes over the same study regions. We further analyze the accompanying circulation features and their changes that may be responsible for shifts in extreme precipitation in response to changed climate. The results from this study may guide hazardous weather watches and help society develop adaptive strategies for preventing catastrophic losses.
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Lejiang Yu; Shiyuan Zhong; Lisi Pei; Xindi (Randy) Bian; Warren E. Heilman
2016-01-01
The mean global climate has warmed as a result of the increasing emission of greenhouse gases induced by human activities. This warming is considered the main reason for the increasing number of extreme precipitation events in the US. While much attention has been given to extreme precipitation events occurring over several days, which are usually responsible for...
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Jha, Sanjeev Kumar; Mariethoz, Gregoire; Evans, Jason; McCabe, Matthew; Sharma, Ashish
2015-01-01
precipitation and daily temperature over several years. Here, the training image consists of daily rainfall and temperature outputs from the Weather Research and Forecasting (WRF) model at 50 km and 10 km resolution for a twenty year period ranging from 1985
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de Vries, A. J.
2017-12-26
Extreme precipitation events in the otherwise arid Middle East can cause flooding with dramatic socioeconomic impacts. Most of these events are associated with tropical-extratropical interactions, whereby a stratospheric potential vorticity (PV) intrusion reaches deep into the subtropics and forces an incursion of high poleward vertically integrated water vapor transport (IVT) into the Middle East. This study presents an object-based identification method for extreme precipitation events based on the combination of these two larger-scale meteorological features. The general motivation for this approach is that precipitation is often poorly simulated in relatively coarse weather and climate models, whereas the synoptic-scale circulation is much better represented. The algorithm is applied to ERA-Interim reanalysis data (1979-2015) and detects 90% (83%) of the 99th (97.5th) percentile of extreme precipitation days in the region of interest. Our results show that stratospheric PV intrusions and IVT structures are intimately connected to extreme precipitation intensity and seasonality. The farther south a stratospheric PV intrusion reaches, the larger the IVT magnitude, and the longer the duration of their combined occurrence, the more extreme the precipitation. Our algorithm detects a large fraction of the climatological rainfall amounts (40-70%), heavy precipitation days (50-80%), and the top 10 extreme precipitation days (60-90%) at many sites in southern Israel and the northern and western parts of Saudi Arabia. This identification method provides a new tool for future work to disentangle teleconnections, assess medium-range predictability and improve understanding of climatic changes of extreme precipitation in the Middle East and elsewhere.
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de Vries, A. J.; Ouwersloot, H. G.; Feldstein, S. B.; Riemer, M.; El Kenawy, A. M.; McCabe, M. F.; Lelieveld, J.
2018-01-01
Extreme precipitation events in the otherwise arid Middle East can cause flooding with dramatic socioeconomic impacts. Most of these events are associated with tropical-extratropical interactions, whereby a stratospheric potential vorticity (PV) intrusion reaches deep into the subtropics and forces an incursion of high poleward vertically integrated water vapor transport (IVT) into the Middle East. This study presents an object-based identification method for extreme precipitation events based on the combination of these two larger-scale meteorological features. The general motivation for this approach is that precipitation is often poorly simulated in relatively coarse weather and climate models, whereas the synoptic-scale circulation is much better represented. The algorithm is applied to ERA-Interim reanalysis data (1979-2015) and detects 90% (83%) of the 99th (97.5th) percentile of extreme precipitation days in the region of interest. Our results show that stratospheric PV intrusions and IVT structures are intimately connected to extreme precipitation intensity and seasonality. The farther south a stratospheric PV intrusion reaches, the larger the IVT magnitude, and the longer the duration of their combined occurrence, the more extreme the precipitation. Our algorithm detects a large fraction of the climatological rainfall amounts (40-70%), heavy precipitation days (50-80%), and the top 10 extreme precipitation days (60-90%) at many sites in southern Israel and the northern and western parts of Saudi Arabia. This identification method provides a new tool for future work to disentangle teleconnections, assess medium-range predictability, and improve understanding of climatic changes of extreme precipitation in the Middle East and elsewhere.
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Observed change in extreme daily rainfalls in the French Mediterranean
Ribes, Aurélien; Thao, Soulivanh; Vautard, Robert; Dubuisson, Brigitte; Somot, Samuel; Colin, Jeanne; Planton, Serge; Soubeyroux, Jean-Michel
2017-04-01
In spite of a relatively dry mean climate, the Mediterranean regions in Southern France use to experience heavy rainfalls over short durations - typically a few minutes to one day. Here we examine long-term trends in the historical record of extreme precipitation events occurring over the French Mediterranean area, where many long homogeneous time-series are available. Extreme events are considered in terms of their intensity, frequency, extent and precipitated volume. Changes in intensity are analysed via an original statistical approach where the annual maximum rainfall observed at each measurement station are aggregated into a univariate time-series, according to their statistical dependence. This procedure substantially enhances the signal-to-noise ratio. The mean intensity increase is significant and estimated at +22% (+7% to +39% at the 90% confidence level) over the 1961-2015 period. Given the observed warming over the considered area, this increase is consistent with a rate of about one to three times that implied by the Clausius-Clapeyron relationship. Changes in frequency and other spatial features are investigated through a Generalised Linear Model. Changes in frequencies for events exceeding high thresholds (about 200mm in one day) are found to be significant, typically near a doubling of the frequency, but with large uncertainties in this risk ratio. The area affected by severe events and the water volume precipitated during those events also exhibit significant trends, with an increase by a factor of about 4 for a 200mm threshold, again with large uncertainties. All diagnoses consistently point toward an intensification of the most extreme events during the last decades. We argue that the diagnosed trends can hardly be explained without invoking the human influence on climate.
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Energy Technology Data Exchange (ETDEWEB)
Li, F.; Collins, W.D.; Wehner, M.F.; Williamson, D.L.; Olson, J.G.
2011-04-15
Current climate models produce quite heterogeneous projections for the responses of precipitation extremes to future climate change. To help understand the range of projections from multimodel ensembles, a series of idealized 'aquaplanet' Atmospheric General Circulation Model (AGCM) runs have been performed with the Community Atmosphere Model CAM3. These runs have been analysed to identify the effects of horizontal resolution on precipitation extreme projections under two simple global warming scenarios. We adopt the aquaplanet framework for our simulations to remove any sensitivity to the spatial resolution of external inputs and to focus on the roles of model physics and dynamics. Results show that a uniform increase of sea surface temperature (SST) and an increase of low-to-high latitude SST gradient both lead to increase of precipitation and precipitation extremes for most latitudes. The perturbed SSTs generally have stronger impacts on precipitation extremes than on mean precipitation. Horizontal model resolution strongly affects the global warming signals in the extreme precipitation in tropical and subtropical regions but not in high latitude regions. This study illustrates that the effects of horizontal resolution have to be taken into account to develop more robust projections of precipitation extremes.
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Love, C. A.; Skahill, B. E.; AghaKouchak, A.; Karlovits, G. S.; England, J. F.; Duren, A. M.
2017-12-01
We compare gridded extreme precipitation return levels obtained using spatial Bayesian hierarchical modeling (BHM) with their respective counterparts from a traditional regional frequency analysis (RFA) using the same set of extreme precipitation data. Our study area is the 11,478 square mile Willamette River basin (WRB) located in northwestern Oregon, a major tributary of the Columbia River whose 187 miles long main stem, the Willamette River, flows northward between the Coastal and Cascade Ranges. The WRB contains approximately two thirds of Oregon's population and 20 of the 25 most populous cities in the state. The U.S. Army Corps of Engineers (USACE) Portland District operates thirteen dams and extreme precipitation estimates are required to support risk informed hydrologic analyses as part of the USACE Dam Safety Program. Our intent is to profile for the USACE an alternate methodology to an RFA that was developed in 2008 due to the lack of an official NOAA Atlas 14 update for the state of Oregon. We analyze 24-hour annual precipitation maxima data for the WRB utilizing the spatial BHM R package "spatial.gev.bma", which has been shown to be efficient in developing coherent maps of extreme precipitation by return level. Our BHM modeling analysis involved application of leave-one-out cross validation (LOO-CV), which not only supported model selection but also a comprehensive assessment of location specific model performance. The LOO-CV results will provide a basis for the BHM RFA comparison.
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Energy Technology Data Exchange (ETDEWEB)
Kottek, M.; Rubel, F. [Univ. of Veterinary Medicine, Vienna (Austria). Biometeorology Group
2007-10-15
Global daily precipitation analyses are mainly based on satellite estimates, often calibrated with monthly ground analyses or merged with model predictions. We argue here that an essential improvement of their accuracy is only possible by incorporation of daily ground measurements. In this work we apply geostatistical methods to compile a global precipitation product based on daily rain gauge measurements. The raw ground measurements, disseminated via Global Telecommunication System (GTS), are corrected for their systematic measurement errors and interpolated onto a global 1 degree grid. For interpolation ordinary block kriging is applied, with precalculated spatial auto-correlation functions (ACFs). This technique allows to incorporate additional climate information. First, monthly ACFs are calculated from the daily data; second, they are regionalised according to the five main climatic zones of the Koeppen-Geiger climate classification. The interpolation error, a by-product of kriging, is used to flag grid points as missing if the error is above a predefined threshold. But for many applications missing values constitute a problem. Due to a combination of the ground analyses with the daily multi-satellite product of the Global Precipitation Climatology Project (GPCP-1DD) not only these missing values are replaced but also the spatial structure of the satellite estimates is considered. As merging method bivariate ordinary co-kriging is applied. The ACFs necessary for the gauge and the satellite fields as well as the corresponding spatial cross-correlation functions (CCFs) are again precalculated for each of the five main climatic zones and for each individual month. As a result two new global daily data sets for the period 1996 up to today will be available on the Internet (www.gmes-geoland.info): A precipitation product over land, analysed from ground measurements; and a global precipitation product merged from this and the GPCP-1DD multi-satellite product. (orig.)
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Long-term trend analysis on total and extreme precipitation over Shasta Dam watershed.
Toride, Kinya; Cawthorne, Dylan L; Ishida, Kei; Kavvas, M Levent; Anderson, Michael L
2018-06-01
California's interconnected water system is one of the most advanced water management systems in the world, and understanding of long-term trends in atmospheric and hydrologic behavior has increasingly being seen as vital to its future well-being. Knowledge of such trends is hampered by the lack of long-period observation data and the uncertainty surrounding future projections of atmospheric models. This study examines historical precipitation trends over the Shasta Dam watershed (SDW), which lies upstream of one of the most important components of California's water system, Shasta Dam, using a dynamical downscaling methodology that can produce atmospheric data at fine time-space scales. The Weather Research and Forecasting (WRF) model is employed to reconstruct 159years of long-term hourly precipitation data at 3km spatial resolution over SDW using the 20th Century Reanalysis Version 2c dataset. Trend analysis on this data indicates a significant increase in total precipitation as well as a growing intensity of extreme events such as 1, 6, 12, 24, 48, and 72-hour storms over the period of 1851 to 2010. The turning point of the increasing trend and no significant trend periods is found to be 1940 for annual precipitation and the period of 1950 to 1960 for extreme precipitation using the sequential Mann-Kendall test. Based on these analysis, we find the trends at the regional scale do not necessarily apply to the watershed-scale. The sharp increase in the variability of annual precipitation since 1970s is also detected, which implies an increase in the occurrence of extreme wet and dry conditions. These results inform long-term planning decisions regarding the future of Shasta Dam and California's water system. Copyright © 2018 Elsevier B.V. All rights reserved.
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Evaluation of modeled changes in extreme precipitation in Europe and the Rhine basin
International Nuclear Information System (INIS)
Haren, Ronald van; Oldenborgh, Geert Jan van; Lenderink, Geert; Hazeleger, Wilco
2013-01-01
In this study, we investigate the change in multi-day precipitation extremes in late winter in Europe using observations and climate models. The objectives of the analysis are to determine whether climate models can accurately reproduce observed trends and, if not, to find the causes of the difference in trends. Similarly to an earlier finding for mean precipitation trends, and despite a lower signal to noise ratio, climate models fail to reproduce the increase in extremes in much of northern Europe: the model simulations do not cover the observed trend in large parts of this area. A dipole in the sea-level pressure trend over continental Europe causes positive trends in extremes in northern Europe and negative trends in the Iberian Peninsula. Climate models have a much weaker pressure trend dipole and as a result a much weaker (extreme) precipitation response. The inability of climate models to correctly simulate observed changes in atmospheric circulation is also primarily responsible for the underestimation of trends in the Rhine basin. When it has been adjusted for the circulation trend mismatch, the observed trend is well within the spread of the climate model simulations. Therefore, it is important that we improve our understanding of circulation changes, in particular related to the cause of the apparent mismatch between observed and modeled circulation trends over the past century. (letter)
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Busuioc, Aristita; Baciu, Madalina; Breza, Traian; Dumitrescu, Alexandru; Stoica, Cerasela; Baghina, Nina
2016-04-01
Many observational, theoretical and based on climate model simulation studies suggested that warmer climates lead to more intense precipitation events, even when the total annual precipitation is slightly reduced. In this way, it was suggested that extreme precipitation events may increase at Clausius-Clapeyron (CC) rate under global warming and constraint of constant relative humidity. However, recent studies show that the relationship between extreme rainfall intensity and atmospheric temperature is much more complex than would be suggested by the CC relationship and is mainly dependent on precipitation temporal resolution, region, storm type and whether the analysis is conducted on storm events rather than fixed data. The present study presents the dependence between the very hight temporal scale extreme rainfall intensity and daily temperatures, with respect to the verification of the CC relation. To solve this objective, the analysis is conducted on rainfall event rather than fixed interval using the rainfall data based on graphic records including intensities (mm/min.) calculated over each interval with permanent intensity per minute. The annual interval with available a such data (April to October) is considered at 5 stations over the interval 1950-2007. For Bucuresti-Filaret station the analysis is extended over the longer interval (1898-2007). For each rainfall event, the maximum intensity (mm/min.) is retained and these time series are considered for the further analysis (abbreviated in the following as IMAX). The IMAX data were divided based on the daily mean temperature into bins 2oC - wide. The bins with less than 100 values were excluded. The 90th, 99th and 99.9th percentiles were computed from the binned data using the empirical distribution and their variability has been compared to the CC scaling (e.g. exponential relation given by a 7% increase per temperature degree rise). The results show a dependence close to double the CC relation for
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Marani, M.; Zorzetto, E.; Hosseini, S. R.; Miniussi, A.; Scaioni, M.
2017-12-01
The Generalized Extreme Value (GEV) distribution is widely adopted irrespective of the properties of the stochastic process generating the extreme events. However, GEV presents several limitations, both theoretical (asymptotic validity for a large number of events/year or hypothesis of Poisson occurrences of Generalized Pareto events), and practical (fitting uses just yearly maxima or a few values above a high threshold). Here we describe the Metastatistical Extreme Value Distribution (MEVD, Marani & Ignaccolo, 2015), which relaxes asymptotic or Poisson/GPD assumptions and makes use of all available observations. We then illustrate the flexibility of the MEVD by applying it to daily precipitation, hurricane intensity, and storm surge magnitude. Application to daily rainfall from a global raingauge network shows that MEVD estimates are 50% more accurate than those from GEV when the recurrence interval of interest is much greater than the observational period. This makes MEVD suited for application to satellite rainfall observations ( 20 yrs length). Use of MEVD on TRMM data yields extreme event patterns that are in better agreement with surface observations than corresponding GEV estimates.Applied to the HURDAT2 Atlantic hurricane intensity dataset, MEVD significantly outperforms GEV estimates of extreme hurricanes. Interestingly, the Generalized Pareto distribution used for "ordinary" hurricane intensity points to the existence of a maximum limit wind speed that is significantly smaller than corresponding physically-based estimates. Finally, we applied the MEVD approach to water levels generated by tidal fluctuations and storm surges at a set of coastal sites spanning different storm-surge regimes. MEVD yields accurate estimates of large quantiles and inferences on tail thickness (fat vs. thin) of the underlying distribution of "ordinary" surges. In summary, the MEVD approach presents a number of theoretical and practical advantages, and outperforms traditional
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Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 1.3 (Daily)
National Oceanic and Atmospheric Administration, Department of Commerce — The GPCP Daily analysis is a companion to the GPCP Monthly analysis, and provides globally complete precipitation estimates at a spatial resolution of one degree...
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Incomplete meteorological data has been a problem in environmental modeling studies. The objective of this work was to develop a technique to reconstruct missing daily precipitation data in the central part of Chesapeake Bay Watershed using regression trees (RT) and artificial neural networks (ANN)....
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Gao, Tao; Xie, Lian
2016-12-01
Precipitation extremes are the dominated causes for the formation of severe flood disasters at regional and local scales under the background of global climate change. In the present study, five annual extreme precipitation events, including 1, 7 and 30 day annual maximum rainfall and 95th and 97.5th percentile threshold levels, are analyzed relating to the reference period 1960-2011 from 140 meteorological stations over Yangtze River basin (YRB). A generalized extreme value (GEV) distribution is applied to fit annual and percentile extreme precipitation events at each station with return periods up to 200 years. The entire time period is divided into preclimatic (preceding climatic) period 1960-1980 and aftclimatic (after climatic) period 1981-2011 by considering distinctly abrupt shift of precipitation regime in the late 1970s across YRB. And the Mann-Kendall trend test is adopted to conduct trend analysis during pre- and aftclimatic periods, respectively, for the purpose of exploring possible increasing/decreasing patterns in precipitation extremes. The results indicate that the increasing trends for return values during aftclimatic period change significantly in time and space in terms of different magnitudes of extreme precipitation, while the stations with significantly positive trends are mainly distributed in the vicinity of the mainstream and major tributaries as well as large lakes, this would result in more tremendous flood disasters in the mid-lower reaches of YRB, especially in southeast coastal regions. The increasing/decreasing linear trends based on annual maximum precipitation are also investigated in pre- and aftclimatic periods, respectively, whereas those changes are not significantly similar to the variations of return values during both subperiods. Moreover, spatiotemporal patterns of precipitation extremes become more uneven and unstable in the second half period over YRB.
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Camilo, Daniela Castro
2017-10-02
In order to model the complex non-stationary dependence structure of precipitation extremes over the entire contiguous U.S., we propose a flexible local approach based on factor copula models. Our sub-asymptotic spatial modeling framework yields non-trivial tail dependence structures, with a weakening dependence strength as events become more extreme, a feature commonly observed with precipitation data but not accounted for in classical asymptotic extreme-value models. To estimate the local extremal behavior, we fit the proposed model in small regional neighborhoods to high threshold exceedances, under the assumption of local stationarity. This allows us to gain in flexibility, while making inference for such a large and complex dataset feasible. Adopting a local censored likelihood approach, inference is made on a fine spatial grid, and local estimation is performed taking advantage of distributed computing resources and of the embarrassingly parallel nature of this estimation procedure. The local model is efficiently fitted at all grid points, and uncertainty is measured using a block bootstrap procedure. An extensive simulation study shows that our approach is able to adequately capture complex, non-stationary dependencies, while our study of U.S. winter precipitation data reveals interesting differences in local tail structures over space, which has important implications on regional risk assessment of extreme precipitation events. A comparison between past and current data suggests that extremes in certain areas might be slightly wider in extent nowadays than during the first half of the twentieth century.
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Camilo, Daniela Castro; Huser, Raphaë l
2017-01-01
In order to model the complex non-stationary dependence structure of precipitation extremes over the entire contiguous U.S., we propose a flexible local approach based on factor copula models. Our sub-asymptotic spatial modeling framework yields non-trivial tail dependence structures, with a weakening dependence strength as events become more extreme, a feature commonly observed with precipitation data but not accounted for in classical asymptotic extreme-value models. To estimate the local extremal behavior, we fit the proposed model in small regional neighborhoods to high threshold exceedances, under the assumption of local stationarity. This allows us to gain in flexibility, while making inference for such a large and complex dataset feasible. Adopting a local censored likelihood approach, inference is made on a fine spatial grid, and local estimation is performed taking advantage of distributed computing resources and of the embarrassingly parallel nature of this estimation procedure. The local model is efficiently fitted at all grid points, and uncertainty is measured using a block bootstrap procedure. An extensive simulation study shows that our approach is able to adequately capture complex, non-stationary dependencies, while our study of U.S. winter precipitation data reveals interesting differences in local tail structures over space, which has important implications on regional risk assessment of extreme precipitation events. A comparison between past and current data suggests that extremes in certain areas might be slightly wider in extent nowadays than during the first half of the twentieth century.
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Directory of Open Access Journals (Sweden)
Wei Li
2018-01-01
Full Text Available In this work, we use the gridded precipitation dataset (with a resolution of 0.5° × 0.5° of the eastern part of inland river basin of Inner Mongolian Plateau from 1961–2015 as the basis and adopt the methods of climatic diagnosis (e.g., the Modified Mann-Kendall method, principal component analysis, and correlation analysis to analyze the spatial and temporal variations of six extreme precipitation indices. Furthermore, we analyzed the relationship between El Niño–Southern Oscillation (ENSO events and the observed extreme precipitation. The results indicated that the gridded dataset can be used to describe the precipitation distribution in our study area. In recent 55 years, the inter-annual variation trends of extreme precipitation indices are generally dominated by declination except for the maximum precipitation over five days (RX5DAY and the heavy precipitation (R95P, in particular, the decreasing regions of consecutive dry days (CDD accounts for 91% of the entire basin, 17.28% of which is showing the significant downward trend. Contrary to CDD, the spatial distribution of the other five indices is gradually decreasing from northeast to southwest, and the precipitation intensity (SDII ranges from 3.8–5.3 mm·d−1, with relatively small spatial differences. To some extent, CDD and R95P can used to characterize the extreme precipitation regimes. Moreover, the number of days with heavy precipitation (RR10, SDII, and R95P are more susceptible to the ENSO events. In addition, the moderate El Niño event may increase the probability of CDD, while the La Niña events may increase the risk of the heavy rainfall regime in the study area.
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Parameter uncertainty in simulations of extreme precipitation and attribution studies.
Timmermans, B.; Collins, W. D.; O'Brien, T. A.; Risser, M. D.
2017-12-01
The attribution of extreme weather events, such as heavy rainfall, to anthropogenic influence involves the analysis of their probability in simulations of climate. The climate models used however, such as the Community Atmosphere Model (CAM), employ approximate physics that gives rise to "parameter uncertainty"—uncertainty about the most accurate or optimal values of numerical parameters within the model. In particular, approximate parameterisations for convective processes are well known to be influential in the simulation of precipitation extremes. Towards examining the impact of this source of uncertainty on attribution studies, we investigate the importance of components—through their associated tuning parameters—of parameterisations relating to deep and shallow convection, and cloud and aerosol microphysics in CAM. We hypothesise that as numerical resolution is increased the change in proportion of variance induced by perturbed parameters associated with the respective components is consistent with the decreasing applicability of the underlying hydrostatic assumptions. For example, that the relative influence of deep convection should diminish as resolution approaches that where convection can be resolved numerically ( 10 km). We quantify the relationship between the relative proportion of variance induced and numerical resolution by conducting computer experiments that examine precipitation extremes over the contiguous U.S. In order to mitigate the enormous computational burden of running ensembles of long climate simulations, we use variable-resolution CAM and employ both extreme value theory and surrogate modelling techniques ("emulators"). We discuss the implications of the relationship between parameterised convective processes and resolution both in the context of attribution studies and progression towards models that fully resolve convection.
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Revisiting the 1993 historical extreme precipitation and damaging flood event in Central Nepal
Marahatta, S.; Adhikari, L.; Pokharel, B.
2017-12-01
Nepal is ranked the fourth most climate-vulnerable country in the world and it is prone to different weather-related hazards including droughts, floods, and landslides [Wang et al., 2013; Gillies et al., 2013]. Although extremely vulnerable to extreme weather events, there are no extreme weather warning system established to inform public in Nepal. Nepal has witnessed frequent drought and flood events, however, the extreme precipitation that occurred on 19-20 July 1993 created a devastating flood and landslide making it the worst weather disaster in the history of Nepal. During the second week of July, Nepal and northern India experienced abnormal dry condition due to the shifting of the monsoon trough to central India. The dry weather changed to wet when monsoon trough moved northward towards foothills of the Himalayas. Around the same period, a low pressure center was located over the south-central Nepal. The surface low was supported by the mid-, upper-level shortwave and cyclonic vorticity. A meso-scale convective system created record breaking one day rainfall (540 mm) in the region. The torrential rain impacted the major hydropower reservoir, Bagmati barrage in Karmaiya and triggered many landslides and flash floods. The region had the largest hydropower (Kulekhani hydropower, 92 MW) of the country at that time and the storm event deposited extremely large amount of sediments that reduced one-fourth (4.8 million m3) of reservoir dead storage (12 million m3). The 1-in-1000 years flood damaged the newly constructed barrage and took more than 700 lives. Major highways were damaged cutting off supply of daily needed goods, including food and gas, in the capital city, Kathmandu, for more than a month. In this presentation, the meteorological conditions of the extreme event will be diagnosed and the impact of the sedimentation due to the flood on Kulekhani reservoir and hydropower generation will be discussed.
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Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent
Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen
2014-05-01
Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.
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Liu, Yonghe; Feng, Jinming; Liu, Xiu; Zhao, Yadi
2017-12-01
Statistical downscaling (SD) is a method that acquires the local information required for hydrological impact assessment from large-scale atmospheric variables. Very few statistical and deterministic downscaling models for daily precipitation have been conducted for local sites influenced by the East Asian monsoon. In this study, SD models were constructed by selecting the best predictors and using generalized linear models (GLMs) for Feixian, a site in the Yishu River Basin and Shandong Province. By calculating and mapping Spearman rank correlation coefficients between the gridded standardized values of five large-scale variables and daily observed precipitation, different cyclonic circulation patterns were found for monsoonal precipitation in summer (June-September) and winter (November-December and January-March); the values of the gridded boxes with the highest absolute correlations for observed precipitation were selected as predictors. Data for predictors and predictands covered the period 1979-2015, and different calibration and validation periods were divided when fitting and validating the models. Meanwhile, the bootstrap method was also used to fit the GLM. All the above thorough validations indicated that the models were robust and not sensitive to different samples or different periods. Pearson's correlations between downscaled and observed precipitation (logarithmically transformed) on a daily scale reached 0.54-0.57 in summer and 0.56-0.61 in winter, and the Nash-Sutcliffe efficiency between downscaled and observed precipitation reached 0.1 in summer and 0.41 in winter. The downscaled precipitation partially reflected exact variations in winter and main trends in summer for total interannual precipitation. For the number of wet days, both winter and summer models were able to reflect interannual variations. Other comparisons were also made in this study. These results demonstrated that when downscaling, it is appropriate to combine a correlation
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Herath, Sujeewa Malwila; Sarukkalige, Ranjan; Nguyen, Van Thanh Van
2018-01-01
Understanding the relationships between extreme daily and sub-daily rainfall events and their governing factors is important in order to analyse the properties of extreme rainfall events in a changing climate. Atmospheric temperature is one of the dominant climate variables which has a strong relationship with extreme rainfall events. In this study, a temperature-rainfall binning technique is used to evaluate the dependency of extreme rainfall on daily maximum temperature. The Clausius-Clapeyron (C-C) relation was found to describe the relationship between daily maximum temperature and a range of rainfall durations from 6 min up to 24 h for seven Australian weather stations, the stations being located in Adelaide, Brisbane, Canberra, Darwin, Melbourne, Perth and Sydney. The analysis shows that the rainfall - temperature scaling varies with location, temperature and rainfall duration. The Darwin Airport station shows a negative scaling relationship, while the other six stations show a positive relationship. To identify the trend in scaling relationship over time the same analysis is conducted using data covering 10 year periods. Results indicate that the dependency of extreme rainfall on temperature also varies with the analysis period. Further, this dependency shows an increasing trend for more extreme short duration rainfall and a decreasing trend for average long duration rainfall events at most stations. Seasonal variations of the scale changing trends were analysed by categorizing the summer and autumn seasons in one group and the winter and spring seasons in another group. Most of 99th percentile of 6 min, 1 h and 24 h rain durations at Perth, Melbourne and Sydney stations show increasing trend for both groups while Adelaide and Darwin show decreasing trend. Furthermore, majority of scaling trend of 50th percentile are decreasing for both groups.
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Dirmeyer, Paul A.; Wei, Jiangfeng; Bosilovich, Michael G.; Mocko, David M.
2014-01-01
A quasi-isentropic back trajectory scheme is applied to output from the Modern Era Retrospective-analysis for Research and Applications and a land-only replay with corrected precipitation to estimate surface evaporative sources of moisture supplying precipitation over every ice-free land location for the period 1979-2005. The evaporative source patterns for any location and time period are effectively two dimensional probability distributions. As such, the evaporative sources for extreme situations like droughts or wet intervals can be compared to the corresponding climatological distributions using the method of relative entropy. Significant differences are found to be common and widespread for droughts, but not wet periods, when monthly data are examined. At pentad temporal resolution, which is more able to isolate floods and situations of atmospheric rivers, values of relative entropy over North America are typically 50-400 larger than at monthly time scales. Significant differences suggest that moisture transport may be the key to precipitation extremes. Where evaporative sources do not change significantly, it implies other local causes may underlie the extreme events.
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Brown, R. F.; Collins, S. L.
2017-12-01
Climate is becoming increasingly more variable due to global environmental change, which is evidenced by fewer, but more extreme precipitation events, changes in precipitation seasonality, and longer, higher severity droughts. These changes, combined with a rising incidence of wildfire, have the potential to strongly impact net primary production (NPP) and key biogeochemical cycles, particularly in dryland ecosystems where NPP is sequentially limited by water and nutrient availability. Here we utilize a ten-year dataset from an ongoing long-term field experiment established in 2007 in which we experimentally altered monsoon rainfall variability to examine how our manipulations, along with naturally occurring events, affect NPP and associated biogeochemical cycles in a semi-arid grassland in central New Mexico, USA. Using long-term regional averages, we identified extremely wet monsoon years (242.8 mm, 2013), and extremely dry monsoon years (86.0 mm, 2011; 80.0 mm, 2015) and water years (117.0 mm, 2011). We examined how changes in precipitation variability and extreme events affected ecosystem processes and function particularly in the context of ecosystem recovery following a 2009 wildfire. Response variables included above- and below-ground plant biomass (ANPP & BNPP) and abundance, soil nitrogen availability, and soil CO2 efflux. Mean ANPP ranged from 3.6 g m-2 in 2011 to 254.5 g m-2 in 2013, while BNPP ranged from 23.5 g m-2 in 2015 to 194.2 g m-2 in 2013, demonstrating NPP in our semi-arid grassland is directly linked to extremes in both seasonal and annual precipitation. We also show increased nitrogen deposition positively affects NPP in unburned grassland, but has no significant impact on NPP post-fire except during extremely wet monsoon years. While soil respiration rates reflect lower ANPP post-fire, patterns in CO2 efflux have not been shown to change significantly in that efflux is greatest following large precipitation events preceded by longer drying
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Climate Extreme Events over Northern Eurasia in Changing Climate
Bulygina, O.; Korshunova, N. N.; Razuvaev, V. N.; Groisman, P. Y.
2014-12-01
During the period of widespread instrumental observations in Northern Eurasia, the annual surface air temperature has increased by 1.5°C. Close to the north in the Arctic Ocean, the late summer sea ice extent has decreased by 40% providing a near-infinite source of water vapor for the dry Arctic atmosphere in the early cold season months. The contemporary sea ice changes are especially visible in the Eastern Hemisphere All these factors affect the change extreme events. Daily and sub-daily data of 940 stations to analyze variations in the space time distribution of extreme temperatures, precipitation, and wind over Russia were used. Changing in number of days with thaw over Russia was described. The total seasonal numbers of days, when daily surface air temperatures (wind, precipitation) were found to be above (below) selected thresholds, were used as indices of climate extremes. Changing in difference between maximum and minimum temperature (DTR) may produce a variety of effects on biological systems. All values falling within the intervals ranged from the lowest percentile to the 5th percentile and from the 95th percentile to the highest percentile for the time period of interest were considered as daily extremes. The number of days, N, when daily temperatures (wind, precipitation, DTR) were within the above mentioned intervals, was determined for the seasons of each year. Linear trends in the number of days were calculated for each station and for quasi-homogeneous climatic regions. Regional analysis of extreme events was carried out using quasi-homogeneous climatic regions. Maps (climatology, trends) are presented mostly for visualization purposes. Differences in regional characteristics of extreme events are accounted for over a large extent of the Russian territory and variety of its physical and geographical conditions. The number of days with maximum temperatures higher than the 95% percentile has increased in most of Russia and decreased in Siberia in
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Pántano, Vanesa C.; Penalba, Olga C.
2017-12-01
Projected changes were estimated considering the main variables which take part in soil-atmosphere interaction. The analysis was focused on the potential impact of these changes on soil hydric condition under extreme precipitation and evapotranspiration, using the combination of Global Climate Models (GCMs) and observational data. The region of study is the southern La Plata Basin that covers part of Argentine territory, where rainfed agriculture production is one of the most important economic activities. Monthly precipitation and maximum and minimum temperatures were used from high quality-controlled observed data from 46 meteorological stations and the ensemble of seven CMIP5 GCMs in two periods: 1970-2005 and 2065-2100. Projected changes in monthly effective temperature and precipitation were analysed. These changes were combined with observed series for each probabilistic interval. The result was used as input variables for the water balance model in order to obtain consequent soil hydric condition (deficit or excess). Effective temperature and precipitation are expected to increase according to the projections of GCMs, with few exceptions. The analysis revealed increase (decrease) in the prevalence of evapotranspiration over precipitation, during spring (winter). Projections for autumn months show precipitation higher than potential evapotranspiration more frequently. Under dry extremes, the analysis revealed higher projected deficit conditions, impacting on crop development. On the other hand, under wet extremes, excess would reach higher values only in particular months. During December, projected increase in temperatures reduces the impact of extreme high precipitation but favours deficit conditions, affecting flower-fructification stage of summer crops.
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Extreme precipitation response to climate perturbations in an atmospheric mesoscale model
Attema, J.J.; Loriaux, J.M.; Lenderink, G.
2014-01-01
Observations of extreme (sub) hourly precipitation at midlatitudes show a large dependency on the dew point temperature often close to 14% per degree—2 times the dependency of the specific humidity on dew point temperature which is given by the Clausius–Clapeyron (CC) relation. By simulating a
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Use of the Box-Cox Transformation in Detecting Changepoints in Daily Precipitation Data Series
Wang, X. L.; Chen, H.; Wu, Y.; Pu, Q.
2009-04-01
This study integrates a Box-Cox power transformation procedure into two statistical tests for detecting changepoints in Gaussian data series, to make the changepoint detection methods applicable to non-Gaussian data series, such as daily precipitation amounts. The detection power aspects of transformed methods in a common trend two-phase regression setting are assessed by Monte Carlo simulations for data of a log-normal or Gamma distribution. The results show that the transformed methods have increased the power of detection, in comparison with the corresponding original (untransformed) methods. The transformed data much better approximate to a Gaussian distribution. As an example of application, the new methods are applied to a series of daily precipitation amounts recorded at a station in Canada, showing satisfactory detection power.
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Xiao, M.
2016-12-01
Under the background of climate change, extensive attentions have been paid on the increased extreme precipitation from the public and government. To analyze the influences of large-scale climate indices on the precipitation extremes, the spatiotemporal patterns of precipitation extremes in the Poyang Lake basin have been investigated using the Bayesian hierarchical method. The seasonal maximum one-day precipitation amount (Rx1day) was used to represent the seasonal precipitation extremes. Results indicated that spring Rx1day was affected by El Niño/Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO), a positive ENSO event in the same year tends to decrease the spring Rx1day in the northern part of Poyang Lake Basin while increase the spring Rx1day in southeastern Poyang Lake Basin, a positive NAO events in the same year tends to increase the spring Rx1day in the southwest and northwest part of Poyang Lake basin while decrease the spring Rx1day in the eastern part of Poyang Lake basin; summer Rx1day was affected by Indian Ocean Dipole (IOD), positive IOD events in the same year tend to increase the summer Rx1day of northern Poyang Lake basin while decrease summer Rx1day of southern Poyang Lake basin; autumn Rx1day was affected by ENSO, positive ENSO events in the same year tend to mainly increase the autumn Rx1day in the west part of Poyang Lake basin; winter Rx1day was mainly affected by the NAO, positive NAO events in the same year tend to mainly increase the winter Rx1day of southern Poyang Lake basin, while positive NAO events in the previous year tend to mainly increase the winter Rx1day in the central and northeast part of Poyang Lake basin. It is considered that the region with the negative vertical velocity is dominated by more precipitation and vice versa. Furthermore, field patterns of 500 hPa vertical velocity anomalies related to each climate index have further corroborated the influences of climate indices on the seasonal Rx1day, and
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The changes in the frequency of daily precipitation in Urmia Lake basin, Iran
Salehi Bavil, Sepideh; Zeinalzadeh, Kamran; Hessari, Behzad
2017-06-01
Urmia Lake, as one of the most valuable saline ecosystems in the world, has faced a sharp drop in the water level in recent years. The trend studies of climatic parameters can be effective in identifying the responsible factors and managing this crisis. This research investigated the frequency trend of daily precipitation in the ranges of less than 5 mm, 5-10 mm, 10-15 mm, 15-20 mm, and more than 20 mm in the Urmia Lake basin. The trend was assessed using Mann-Kendall, Spearman Rho and linear regression tests on 60 stations during a period of 30 years (1981 to 2011). The results showed that in all the three tests, the frequency of daily precipitation of less than 5 mm had a significant increase at 1% level. The 5-10 mm range displayed no significant trend, while the 10-15 mm range showed a significantly decreasing trend. The frequency in the 15-20 mm and above 20 mm ranges showed an insignificant falling trend. The analysis also indicated jumps in 1996 and 1999 (almost coinciding with the sharp drop in the lake's water level). In other words, the frequency trends of daily precipitation with small amounts (as a result, high evapotranspiration loss) were increasing and with large amounts were decreasing. This can be a contributor to reduced run-off and, hence, decreased water entering the lake. The results emphasize the need for changes in the management and consumption of water resources in the basin, in order to adapt to the climatic change.
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Extreme precipitation patterns and reductions of terrestrial ecosystem production across biomes
Yongguang Zhang; M. Susan Moran; Mark A. Nearing; Guillermo E. Ponce Campos; Alfredo R. Huete; Anthony R. Buda; David D. Bosch; Stacey A. Gunter; Stanley G. Kitchen; W. Henry McNab; Jack A. Morgan; Mitchel P. McClaran; Diane S. Montoya; Debra P.C. Peters; Patrick J. Starks
2013-01-01
Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more heavy rainfall events and longer dry intervals, yet their ecological impacts on vegetation production remain uncertain across biomes in natural climatic conditions. This in situ study investigated the effects of these climatic conditions on aboveground net primary...
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Climate variations and changes in extreme climate events in Russia
International Nuclear Information System (INIS)
Bulygina, O N; Razuvaev, V N; Korshunova, N N; Groisman, P Ya
2007-01-01
Daily temperature (mean, minimum and maximum) and atmospheric precipitation data from 857 stations are used to analyze variations in the space-time distribution of extreme temperatures and precipitation across Russia during the past six decades. The seasonal numbers of days (N) when daily air temperatures (diurnal temperature range, precipitation) were higher or lower than selected thresholds are used as indices of climatic extremes. Linear trends in N are calculated for each station for the time period of interest. The seasonal numbers of days (for each season) with maximum temperatures higher than the 95th percentile have increased over most of Russia, with minimum temperatures lower than the 5th percentile having decreased. A tendency for the decrease in the number of days with abnormally high diurnal temperature range is observed over most of Russia. In individual regions of Russia, however, a tendency for an increasing number of days with a large diurnal amplitude is found. The largest tendency for increasing number of days with heavy precipitation is observed in winter in Western Siberia and Yakutia
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Gutowski, William J.; Lindemulder, Elizabeth A.; Jovaag, Kari
1995-01-01
We use retrievals of atmospheric precipitable water from satellite microwave observations and analyses of near-surface temperature to examine the relationship between these two fields on daily and longer time scales. The retrieval technique producing the data used here is most effective over the open ocean, so the analysis focuses on the southern hemisphere's extratropics, which have an extensive ocean surface. For both the total and the eddy precipitable water fields, there is a close correspondence between local variations in the precipitable water and near-surface temperature. The correspondence appears particularly strong for synoptic and planetary scale transient eddies. More specifically, the results support a typical modeling assumption that transient eddy moisture fields are proportional to transient eddy temperature fields under the assumption f constant relative humidity.
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Directory of Open Access Journals (Sweden)
Mateusz Szcześniak
2015-02-01
Full Text Available Ground-based precipitation data are still the dominant input type for hydrological models. Spatial variability in precipitation can be represented by spatially interpolating gauge data using various techniques. In this study, the effect of daily precipitation interpolation methods on discharge simulations using the semi-distributed SWAT (Soil and Water Assessment Tool model over a 30-year period is examined. The study was carried out in 11 meso-scale (119–3935 km2 sub-catchments lying in the Sulejów reservoir catchment in central Poland. Four methods were tested: the default SWAT method (Def based on the Nearest Neighbour technique, Thiessen Polygons (TP, Inverse Distance Weighted (IDW and Ordinary Kriging (OK. =The evaluation of methods was performed using a semi-automated calibration program SUFI-2 (Sequential Uncertainty Fitting Procedure Version 2 with two objective functions: Nash-Sutcliffe Efficiency (NSE and the adjusted R2 coefficient (bR2. The results show that: (1 the most complex OK method outperformed other methods in terms of NSE; and (2 OK, IDW, and TP outperformed Def in terms of bR2. The median difference in daily/monthly NSE between OK and Def/TP/IDW calculated across all catchments ranged between 0.05 and 0.15, while the median difference between TP/IDW/OK and Def ranged between 0.05 and 0.07. The differences between pairs of interpolation methods were, however, spatially variable and a part of this variability was attributed to catchment properties: catchments characterised by low station density and low coefficient of variation of daily flows experienced more pronounced improvement resulting from using interpolation methods. Methods providing higher precipitation estimates often resulted in a better model performance. The implication from this study is that appropriate consideration of spatial precipitation variability (often neglected by model users that can be achieved using relatively simple interpolation methods can
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Extreme daily increases in peak electricity demand: Tail-quantile estimation
International Nuclear Information System (INIS)
Sigauke, Caston; Verster, Andréhette; Chikobvu, Delson
2013-01-01
A Generalized Pareto Distribution (GPD) is used to model extreme daily increases in peak electricity demand. The model is fitted to years 2000–2011 recorded data for South Africa to make a comparative analysis with the Generalized Pareto-type (GP-type) distribution. Peak electricity demand is influenced by the tails of probability distributions as well as by means or averages. At times there is a need to depart from the average thinking and exploit information provided by the extremes (tails). Empirical results show that both the GP-type and the GPD are a good fit to the data. One of the main advantages of the GP-type is the estimation of only one parameter. Modelling of extreme daily increases in peak electricity demand helps in quantifying the amount of electricity which can be shifted from the grid to off peak periods. One of the policy implications derived from this study is the need for day-time use of electricity billing system similar to the one used in the cellular telephone/and fixed line-billing technology. This will result in the shifting of electricity demand on the grid to off peak time slots as users try to avoid high peak hour charges. - Highlights: ► Policy makers should design demand response strategies to save electricity. ► Peak electricity demand is influenced by tails of probability distributions. ► Both the GSP and the GPD are a good fit to the data. ► Accurate assessment of level and frequency of extreme load forecasts is important.
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Masud, M. B.; Khaliq, M. N.; Wheater, H. S.
2017-09-01
The effects of climate change on April-October short- and long-duration precipitation extremes over the Canadian Prairie Provinces were evaluated using a multi-Regional Climate Model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. Simulations considered include those performed with six RCMs driven by the National Centre for Environmental Prediction (NCEP) reanalysis II product for the 1981-2000 period and those driven by four Atmosphere-Ocean General Circulation Models (AOGCMs) for the current 1971-2000 and future 2041-2070 periods (i.e. a total of 11 current-to-future period simulation pairs). A regional frequency analysis approach was used to develop 2-, 5-, 10-, 25-, and 50-year return values of precipitation extremes from NCEP and AOGCM-driven current and future period simulations that respectively were used to study the performance of RCMs and projected changes for selected return values at regional, grid-cell and local scales. Performance errors due to internal dynamics and physics of RCMs studied for the 1981-2000 period reveal considerable variation in the performance of the RCMs. However, the performance errors were found to be much smaller for RCM ensemble averages than for individual RCMs. Projected changes in future climate to selected regional return values of short-duration (e.g. 15- and 30-min) precipitation extremes and for longer return periods (e.g. 50-year) were found to be mostly larger than those to the longer duration (e.g. 24- and 48-h) extremes and short return periods (e.g. 2-year). Overall, projected changes in precipitation extremes were larger for southeastern regions followed by southern and northern regions and smaller for southwestern and western regions of the study area. The changes to return values were also found to be statistically significant for the majority of the RCM-AOGCM simulation pairs. These projections might be useful as a key input for the future planning of urban
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Evidences of Significant Nonstationarity in Precipitation Extremes over Urbanizing Areas in India
Singh, J.; H, V.; Karmakar, S.; Ghosh, S.
2014-12-01
The statistical assumption of stationarity in hydrologic extreme time/event series has been relied heavily in frequency analysis. However, due to the analytically perceivable impacts of climate change, urbanization and concomitant land use pattern, assumption of stationarity in hydrologic time series will draw erroneous results, which inturn effects the policy and decision-making. Past studies provided sufficient evidences on changes in the characteristics of Indian monsoon rainfall extremes and further it has been attributed to climate change and urbanization, which indicates the presence of significant nonstationary in the Indian monsoon extremes. Therefore, a comprehensive nonstationary frequency analysis must be conducted all over India to obtain realistic return periods. The present study aims to conduct a nonstationary frequency analysis of the precipitation extremes over India at 1o resolution for a period of 1901-2004, with the implementation of the Generalized Additive Model for Location, Scale and Shape (GAMLSS) parameters. A cluster of 74 GAMLSS models has been developed by considering nonstationary in different combinations of distribution parameters and regression techniques (families of parametric polynomials and nonparametric/smoothing cubic spline), which overcomes the limitations of the previous studies. Further, for identification of urban, urbanizing and rural grids, an population density data has been utilized. The results showed the significant differences in the stationary and nonstationary return periods for the urbanizing grids, when compared to urbanized and rural grids. The results give implications of presence of nonstationary in the precipitation extremes more prominently in urbanizing areas compare to urbanized and rural areas.
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Extreme Precipitation Estimation with Typhoon Morakot Using Frequency and Spatial Analysis
Directory of Open Access Journals (Sweden)
Hone-Jay Chu
2011-01-01
Full Text Available Typhoon Morakot lashed Taiwan and produced copious amounts of precipitation in 2009. From the point view of hydrological statistics, the impact of the precipitation from typhoon Morakot using a frequency analysis can be analyzed and discussed. The frequency curve, which was fitted mathematically to historical observed data, can be used to estimate the probability of exceedance for runoff events of a certain magnitude. The study integrates frequency analysis and spatial analysis to assess the effect of Typhoon Morakot event on rainfall frequency in the Gaoping River basin of southern Taiwan. First, extreme rainfall data are collected at sixteen stations for durations of 1, 3, 6, 12, and 24 hours and then an appropriate probability distribution was selected to analyze the impact of the extreme hydrological event. Spatial rainfall patterns for a return period of 200-yr with 24-hr duration with and without Typhoon Morakot are estimated. Results show that the rainfall amount is significantly different with long duration with and without the event for frequency analysis. Furthermore, spatial analysis shows that extreme rainfall for a return period of 200-yr is highly dependent on topography and is smaller in the southwest than that in the east. The results not only demonstrate the distinct effect of Typhoon Morakot on frequency analysis, but also could provide reference in future planning of hydrological engineering.
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Haj, Adel E.; Christiansen, Daniel E.; Hutchinson, Kasey J.
2015-10-14
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for nine river basins in eastern Iowa that drain into the Mississippi River. The models are part of a suite of methods for estimating daily streamflow at ungaged sites. The Precipitation-Runoff Modeling System is a deterministic, distributed- parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration and validation periods used in each basin mostly were October 1, 2002, through September 30, 2012, but differed depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.
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Jeznach, Lillian C; Hagemann, Mark; Park, Mi-Hyun; Tobiason, John E
2017-10-01
Extreme precipitation events are of concern to managers of drinking water sources because these occurrences can affect both water supply quantity and quality. However, little is known about how these low probability events impact organic matter and nutrient loads to surface water sources and how these loads may impact raw water quality. This study describes a method for evaluating the sensitivity of a water body of interest from watershed input simulations under extreme precipitation events. An example application of the method is illustrated using the Wachusett Reservoir, an oligo-mesotrophic surface water reservoir in central Massachusetts and a major drinking water supply to metropolitan Boston. Extreme precipitation event simulations during the spring and summer resulted in total organic carbon, UV-254 (a surrogate measurement for reactive organic matter), and total algae concentrations at the drinking water intake that exceeded recorded maximums. Nutrient concentrations after storm events were less likely to exceed recorded historical maximums. For this particular reservoir, increasing inter-reservoir transfers of water with lower organic matter content after a large precipitation event has been shown in practice and in model simulations to decrease organic matter levels at the drinking water intake, therefore decreasing treatment associated oxidant demand, energy for UV disinfection, and the potential for formation of disinfection byproducts. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Loriaux, J.M.; Lenderink, G.; De Roode, S.R.; Siebesma, A.P.
2013-01-01
Previously observed twice-Clausius–Clapeyron (2CC) scaling for extreme precipitation at hourly time scales has led to discussions about its origin. The robustness of this scaling is assessed by analyzing a subhourly dataset of 10-min resolution over the Netherlands. The results confirm the validity
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The evolution of extreme precipitations in high resolution scenarios over France
Colin, J.; Déqué, M.; Somot, S.
2009-09-01
Over the past years, improving the modelling of extreme events and their variability at climatic time scales has become one of the challenging issue raised in the regional climate research field. This study shows the results of a high resolution (12 km) scenario run over France with the limited area model (LAM) ALADIN-Climat, regarding the representation of extreme precipitations. The runs were conducted in the framework of the ANR-SCAMPEI national project on high resolution scenarios over French mountains. As a first step, we attempt to quantify one of the uncertainties implied by the use of LAM : the size of the area on which the model is run. In particular, we address the issue of whether a relatively small domain allows the model to create its small scale process. Indeed, high resolution scenarios cannot be run on large domains because of the computation time. Therefore one needs to answer this preliminary question before producing and analyzing such scenarios. To do so, we worked in the framework of a « big brother » experiment. We performed a 23-year long global simulation in present-day climate (1979-2001) with the ARPEGE-Climat GCM, at a resolution of approximately 50 km over Europe (stretched grid). This first simulation, named ARP50, constitutes the « big brother » reference of our experiment. It has been validated in comparison with the CRU climatology. Then we filtered the short waves (up to 200 km) from ARP50 in order to obtain the equivalent of coarse resolution lateral boundary conditions (LBC). We have carried out three ALADIN-Climat simulations at a 50 km resolution with these LBC, using different configurations of the model : * FRA50, run over a small domain (2000 x 2000 km, centered over France), * EUR50, run over a larger domain (5000 x 5000 km, centered over France as well), * EUR50-SN, run over the large domain (using spectral nudging). Considering the facts that ARPEGE-Climat and ALADIN-Climat models share the same physics and dynamics
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Prat, O. P.; Nelson, B. R.
2014-10-01
We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.
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Hawcroft, M.; Hodges, K.; Walsh, E.; Zappa, G.
2017-12-01
For the Northern Hemisphere extratropics, changes in circulation are key to determining the impacts of climate warming. The mechanisms governing these circulation changes are complex, leading to the well documented uncertainty in projections of the future location of the mid-latitude storm tracks simulated by climate models. These storms are the primary source of precipitation for North America and Europe and generate many of the large-scale precipitation extremes associated with flooding and severe economic loss. Here, we show that in spite of the uncertainty in circulation changes, by analysing the behaviour of the storms themselves, we find entirely consistent and robust projections across an ensemble of climate models. In particular, we find that projections of change in the most intensely precipitating storms (above the present day 99th percentile) in the Northern Hemisphere are substantial and consistent across models, with large increases in the frequency of both summer (June-August, +226±68%) and winter (December-February, +186±34%) extreme storms by the end of the century. Regionally, both North America (summer +202±129%, winter +232±135%) and Europe (summer +390±148%, winter +318±114%) are projected to experience large increases in the frequency of intensely precipitating storms. These changes are thermodynamic and driven by surface warming, rather than by changes in the dynamical behaviour of the storms. Such changes in storm behaviour have the potential to have major impacts on society given intensely precipitating storms are responsible for many large-scale flooding events.
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Regional climate scenarios - A study on precipitation
International Nuclear Information System (INIS)
Hesselbjerg Christensen, J.; Boessing Christensen, O.
2001-01-01
A set of nested climate change simulations for the Nordic region and Denmark has been revisited. In the present work we have re-examined the results of CCMB and MBC with special emphasis on precipitation intensity frequencies, in particular the more extreme part of the frequency distribution. It has been demonstrated that the role of extreme precipitation events appears to be more realistically described in a high-resolution model, in terms of numerical agreement as well as seasonal variation. This is mainly due to a better simulation of deep low-pressure systems and mesoscale circulation. Generally, the analysis has confirmed the results from CCMB, but furthermore a resolution effect has been identified which seems essential to the understanding of climate change effects on the extreme end of the precipitation intensity distribution. In order to analyse the role of the model resolution we have aggregated both the nested model data and observational records to the GCM grid from the driving AOGCM. It was found that, in spite of changes in absolute numbers, the seasonal behaviour of decay constants does not change appreciably because of the aggregation. The RCM results show a seasonal behaviour very similar to an observed data set. It is therefore concluded that the GCM has an unrealistic simulation of the dependence of heavy precipitation on climate, as manifested in seasonal variation. In contrast, the regional simulations remain close to observation in this respect. Furthermore, they agree on a conclusion that extreme precipitation generally scales with average precipitation (no significant change in decay constants were detected), but that crucial summer season may be an exception, exhibiting an anomalous increase in heavy precipitation due to the anthropogenic greenhouse effect. The analysis has only been performed over Denmark due to lack of daily observational data for other regions. It is, however, necessary to extend the work to other areas, for instance
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Relationship between the precipitation variability in Montenegro and the Mediterranean oscillation
Directory of Open Access Journals (Sweden)
Burić Dragan
2014-01-01
Full Text Available This study investigates the influence of atmospheric circulation in the Mediterranean region on the precipitation in Montenegro. Nine precipitation parameters have been used in the analysis and the relationship has been investigated by the Mediterranean and West Mediterranean Oscillation change index (MO and WeMO. According to a 60 - year observed period (1951-2010, the research results show that nothing characteristic happens with seasonal and annual precipitation sums because the trend is mainly insignificant. However, precipitation extremes are getting more extreme, which corresponds with a general idea of global warming. Negative consequences of daily intensity increase and frequency of precipitation days above fixed and percentile thresholds have been recorded recently in the form of torrents, floods, intensive erosive processes, etc., but it should be pointed out that human factor is partly a cause of such events. The estimate of the influence of teleconnection patterns primarily related to the Mediterranean Basin has shown that their variability affects the observed precipitation parameters on the territory of Montenegro regarding both seasonal and annual sums and frequency and intensity of extreme events shown by climate indices.
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Grimm, J W; Lynch, J A
2005-06-01
Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate.
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Extreme precipitation response to climate perturbations in an atmospheric mesoscale model
International Nuclear Information System (INIS)
Attema, Jisk J; Loriaux, Jessica M; Lenderink, Geert
2014-01-01
Observations of extreme (sub-)hourly precipitation at mid-latitudes show a large dependency on the dew point temperature often close to 14% per degree—2 times the dependency of the specific humidity on dew point temperature which is given by the Clausius–Clapeyron (CC) relation. By simulating a selection of 11 cases over the Netherlands characterized by intense showers, we investigate this behavior in the non-hydrostatic weather prediction model Harmonie at a resolution of 2.5 km. These experiments are repeated using perturbations of the atmospheric profiles of temperature and humidity: (i) using an idealized approach with a 2° warmer (colder) atmosphere assuming constant relative humidity, and (ii) using changes in temperature and humidity derived from a long climate change simulation at 2° global warming. All perturbations have a difference in the local dew point temperature compared to the reference of approximately 2°. Differences are considerable between the cases, with dependencies ranging from almost zero to an increase of 18% per degree rise of the dew point temperature. On average however, we find an increase of extreme precipitation intensity of 11% per degree for the idealized perturbation, and 9% per degree for the climate change perturbation. For the most extreme events these dependencies appear to approach a rate of 11–14% per degree, in closer agreement with the observed relation. (paper)
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Improved Hourly and Sub-Hourly Gauge Data for Assessing Precipitation Extremes in the U.S.
Lawrimore, J. H.; Wuertz, D.; Palecki, M. A.; Kim, D.; Stevens, S. E.; Leeper, R.; Korzeniewski, B.
2017-12-01
The NOAA/National Weather Service (NWS) Fischer-Porter (F&P) weighing bucket precipitation gauge network consists of approximately 2000 stations that comprise a subset of the NWS Cooperative Observers Program network. This network has operated since the mid-20th century, providing one of the longest records of hourly and 15-minute precipitation observations in the U.S. The lengthy record of this dataset combined with its relatively high spatial density, provides an important source of data for many hydrological applications including understanding trends and variability in the frequency and intensity of extreme precipitation events. In recent years NOAA's National Centers for Environmental Information initiated an upgrade of its end-to-end processing and quality control system for these data. This involved a change from a largely manual review and edit process to a fully automated system that removes the subjectivity that was previously a necessary part of dataset quality control and processing. An overview of improvements to this dataset is provided along with the results of an analysis of observed variability and trends in U.S. precipitation extremes since the mid-20th century. Multi-decadal trends in many parts of the nation are consistent with model projections of an increase in the frequency and intensity of heavy precipitation in a warming world.
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Alexander, Lisa V.; Arblaster, Julie M.
2017-01-01
This study expands previous work on climate extremes in Australia by investigating the simulation of a large number of extremes indices in the CMIP5 multi-model dataset and comparing them to multiple observational datasets over a century of observed data using consistent methods. We calculate 24 indices representing extremes of temperature and precipitation from 1911 to 2010 over Australia and show that there have been significant observed trends in temperature extremes associated with warmin...
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This study aimed to statistically and hydrologically assess the performance of four latest and widely used satellite–gauge combined precipitation estimates (SGPEs), namely CRT, BLD, 3B42CDR, and 3B42 for the extreme precipitation and stream'ow scenarios over the upper Yellow river basin (UYRB) in ch...
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Potential impacts of climate change on extreme precipitation over four African coastal cities
CSIR Research Space (South Africa)
Abiodun, BJ
2017-08-01
Full Text Available This study examines the impacts of climate change on characteristics of extreme precipitation events over four African coastal cities (Cape Town, Maputo, Lagos and Port Said) under two future climate scenarios (RCP4.5 and RCP8.5). Fourteen indices...
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Future Extreme Event Vulnerability in the Rural Northeastern United States
Winter, J.; Bowen, F. L.; Partridge, T.; Chipman, J. W.
2017-12-01
Future climate change impacts on humans will be determined by the convergence of evolving physical climate and socioeconomic systems. Of particular concern is the intersection of extreme events and vulnerable populations. Rural areas of the Northeastern United States have experienced increased temperature and precipitation extremes, especially over the past three decades, and face unique challenges due to their physical isolation, natural resources dependent economies, and high poverty rates. To explore the impacts of future extreme events on vulnerable, rural populations in the Northeast, we project extreme events and vulnerability indicators to identify where changes in extreme events and vulnerable populations coincide. Specifically, we analyze future (2046-2075) maximum annual daily temperature, minimum annual daily temperature, maximum annual daily precipitation, and maximum consecutive dry day length for Representative Concentration Pathways (RCP) 4.5 and 8.5 using four global climate models (GCM) and a gridded observational dataset. We then overlay those projections with estimates of county-level population and relative income for 2060 to calculate changes in person-events from historical (1976-2005), with a focus on Northeast counties that have less than 250,000 people and are in the bottom income quartile. We find that across the rural Northeast for RCP4.5, heat person-events per year increase tenfold, far exceeding decreases in cold person-events and relatively small changes in precipitation and drought person-events. Counties in the bottom income quartile have historically (1976-2005) experienced a disproportionate number of heat events, and counties in the bottom two income quartiles are projected to experience a greater heat event increase by 2046-2075 than counties in the top two income quartiles. We further explore the relative contributions of event frequency, population, and income changes to the total and geographic distribution of climate change
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A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events
Zorzetto, E.; Marani, M.
2017-12-01
The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.
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Jacob A. Zwart; Stephen D. Sebestyen; Christopher T. Solomon; Stuart E. Jones
2016-01-01
The frequency and magnitude of extreme events are expected to increase in the future, yet little is known about effects of such events on ecosystem structure and function. We examined how extreme precipitation events affect exports of terrestrial dissolved organic carbon (t-DOC) from watersheds to lakes as well as in-lake heterotrophy in three north-temperate lakes....
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Changes in Climate Extremes and Catastrophic Events in the Mongolian Plateau from 1951 to 2012
DEFF Research Database (Denmark)
Wang, Lei; Yao, Zhi-Jun; Jiang, Liguang
2016-01-01
The spatiotemporal changes in 21 indices of extreme temperature and precipitation for the Mongolian Plateau from 1951 to 2012 were investigated on the basis of daily temperature and precipitation data from 70 meteorological stations. Changes in catastrophic events, such as droughts, floods, and s...
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Lussana, Cristian; Saloranta, Tuomo; Skaugen, Thomas; Magnusson, Jan; Tveito, Ole Einar; Andersen, Jess
2018-02-01
The conventional climate gridded datasets based on observations only are widely used in atmospheric sciences; our focus in this paper is on climate and hydrology. On the Norwegian mainland, seNorge2 provides high-resolution fields of daily total precipitation for applications requiring long-term datasets at regional or national level, where the challenge is to simulate small-scale processes often taking place in complex terrain. The dataset constitutes a valuable meteorological input for snow and hydrological simulations; it is updated daily and presented on a high-resolution grid (1 km of grid spacing). The climate archive goes back to 1957. The spatial interpolation scheme builds upon classical methods, such as optimal interpolation and successive-correction schemes. An original approach based on (spatial) scale-separation concepts has been implemented which uses geographical coordinates and elevation as complementary information in the interpolation. seNorge2 daily precipitation fields represent local precipitation features at spatial scales of a few kilometers, depending on the station network density. In the surroundings of a station or in dense station areas, the predictions are quite accurate even for intense precipitation. For most of the grid points, the performances are comparable to or better than a state-of-the-art pan-European dataset (E-OBS), because of the higher effective resolution of seNorge2. However, in very data-sparse areas, such as in the mountainous region of southern Norway, seNorge2 underestimates precipitation because it does not make use of enough geographical information to compensate for the lack of observations. The evaluation of seNorge2 as the meteorological forcing for the seNorge snow model and the DDD (Distance Distribution Dynamics) rainfall-runoff model shows that both models have been able to make profitable use of seNorge2, partly because of the automatic calibration procedure they incorporate for precipitation. The seNorge2
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Coplen, T.B.; Neiman, P.J.; White, A.B.; Landwehr, J.M.; Ralph, F.M.; Dettinger, M.D.
2008-01-01
With a new automated precipitation collector we measured a remarkable decrease of 51??? in the hydrogen isotope ratio (?? 2H) of precipitation over a 60-minute period during the landfall of an extratropical cyclone along the California coast on 21 March 2005. The rapid drop in ??2H occurred as precipitation generation transitioned from a shallow to a much deeper cloud layer, in accord with synoptic-scale ascent and deep "seeder-feeder" precipitation. Such unexpected ?? 2H variations can substantially impact widely used isotope-hydrograph methods. From extreme ??2H values of -26 and -78???, we calculate precipitation temperatures of 9.7 and -4.2??C using an adiabatic condensation isotope model, in good agreement with temperatures estimated from surface observations and radar data. This model indicates that 60 percent of the moisture was precipitated during ascent as temperature decreased from 15??C at the ocean surface to -4??C above the measurement site.
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A hierarchical Bayesian spatio-temporal model for extreme precipitation events
Ghosh, Souparno; Mallick, Bani K.
2011-01-01
We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. © 2010 John Wiley & Sons, Ltd..
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A hierarchical Bayesian spatio-temporal model for extreme precipitation events
Ghosh, Souparno
2011-03-01
We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. © 2010 John Wiley & Sons, Ltd..
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Directory of Open Access Journals (Sweden)
E. Schlosser
2016-04-01
Full Text Available At the East Antarctic deep ice core drilling site Dome C, daily precipitation measurements were initiated in 2006 and are being continued until today. The amounts and stable isotope ratios of the precipitation samples as well as crystal types are determined. Within the measuring period, the two years 2009 and 2010 showed striking contrasting temperature and precipitation anomalies, particularly in the winter seasons. The reasons for these anomalies are analysed using data from the mesoscale atmospheric model WRF (Weather Research and Forecasting Model run under the Antarctic Mesoscale Prediction System (AMPS. 2009 was relatively warm and moist due to frequent warm air intrusions connected to amplification of Rossby waves in the circumpolar westerlies, whereas the winter of 2010 was extremely dry and cold. It is shown that while in 2010 a strong zonal atmospheric flow was dominant, in 2009 an enhanced meridional flow prevailed, which increased the meridional transport of heat and moisture onto the East Antarctic plateau and led to a number of high-precipitation/warming events at Dome C. This was also evident in a positive (negative SAM (Southern Annular Mode index and a negative (positive ZW3 (zonal wave number three index during the winter months of 2010 (2009. Changes in the frequency or seasonality of such event-type precipitation can lead to a strong bias in the air temperature derived from stable water isotopes in ice cores.
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Pelt, van S.C.; Beersma, J.J.; Buishand, T.A.; Hurk, van den B.J.J.M.; Kabat, P.
2012-01-01
Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks.
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Fonseca, P. M.; Veiga, J. A.; Correia, F. S.; Brito, A. L.
2013-05-01
The aim of this research was evaluate changes in frequency and intensity of extreme events of precipitation in Brazilian Amazon and Northeast Region, doubling CO2 concentration in agreement of IPCC A2 emissions scenarios (Nakicenovic et al., 2001). For this evaluation was used ETA model (Chou et al., 2011), forced with CCSM3 Global model data (Meehl, 2006) to run 4 experiments, only for January, February and March: 1980-1990, 2000-2010, 2040-2050 and 2090-2100. Using the first decade as reference (1980-1990), was evaluated changes occurred in following decades, with a methodology to classify extremes events adapted from Frich (2002) and Gao (2006). Higher was the class, more intense is the event. An increase of 25% was observed in total precipitation in Brazilian Amazon for the end of XXI century and 12% for extreme events type 1, 9% for events type 2 and 10% for type 3. By the other hand, a 17% decrease of precipitation in Brazilian Northeast was observed, and a pronounced decay of 24% and 15% in extreme events contribution type 1 and 2 to total amount of precipitation, respectively. The difference between total normal type events was positive in this three decades compared with reference decade 1980-1990, varying positively from 4 to 6 thousand events included in normality by decade, these events was decreased in your majority of Class 1 events, which presented a decay of at least 3.500 events by each decade. This suggests an intensification of extreme events, considering that the amount of precipitation by class increased, and the number of events by class decreased. To Northeast region, an increasing in 9% of contribution to events type 3 class was observed, as well as in the frequency of this type of events (about of 700 more events). Major decreasing in number of classes extreme events occur in 2000-2010, to classes 1 and 3, with 7,2 and 5,6%, and by the end of century in class 3, with 4,5%. For the three analyzed decades a total decrease of 8.400 events was
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Hazard analysis of typhoon-related external events using extreme value theory
Energy Technology Data Exchange (ETDEWEB)
Kim, Yo Chan; Jang, Seung Cheol [Integrated Safety Assessment Division, Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Lim, Tae Jin [Dept. of Industrial Information Systems Engineering, Soongsil University, Seoul (Korea, Republic of)
2015-02-15
After the Fukushima accident, the importance of hazard analysis for extreme external events was raised. To analyze typhoon-induced hazards, which are one of the significant disasters of East Asian countries, a statistical analysis using the extreme value theory, which is a method for estimating the annual exceedance frequency of a rare event, was conducted for an estimation of the occurrence intervals or hazard levels. For the four meteorological variables, maximum wind speed, instantaneous wind speed, hourly precipitation, and daily precipitation, the parameters of the predictive extreme value theory models were estimated. The 100-year return levels for each variable were predicted using the developed models and compared with previously reported values. It was also found that there exist significant long-term climate changes of wind speed and precipitation. A fragility analysis should be conducted to ensure the safety levels of a nuclear power plant for high levels of wind speed and precipitation, which exceed the results of a previous analysis.
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Christiansen, Daniel E.; Haj, Adel E.; Risley, John C.
2017-10-24
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for 12 river basins in western Iowa that drain into the Missouri River. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration periods for each basin varied depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.A geographic information system tool was used to delineate each basin and estimate initial values for model parameters based on basin physical and geographical features. A U.S. Geological Survey automatic calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The Precipitation-Runoff Modeling System model was calibrated at 42 sites located in the 12 river basins in western Iowa.The accuracy of the simulated daily streamflow values at the 42 calibration sites varied by river and by site. The models were satisfactory at 36 of the sites based on statistical results. Unsatisfactory performance at the six other sites can be attributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) limited availability and accuracy of meteorological input data. The Precipitation-Runoff Modeling System
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Evaluation of modeled changes in extreme precipitation in Europe and the Rhine basin
Haren, van R.; Oldenborgh, van G.J.; Lenderink, G.; Hazeleger, W.
2013-01-01
In this study, we investigate the change in multi-day precipitation extremes in late winter in Europe using observations and climate models. The objectives of the analysis are to determine whether climate models can accurately reproduce observed trends and, if not, to find the causes of the
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Czech Academy of Sciences Publication Activity Database
Gaál, Ľ.; Beranová, R.; Hlavčová, K.; Kyselý, Jan
2014-01-01
Roč. 2014, č. 943487 (2014), s. 1-14 ISSN 1687-9309 Institutional support: RVO:67179843 ; RVO:68378289 Keywords : precipitation extremes * regional climate models * climate change Subject RIV: EH - Ecology, Behaviour Impact factor: 0.946, year: 2014
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Modeling Precipitation Extremes using Log-Histospline
Huang, W. K.; Nychka, D. W.; Zhang, H.
2017-12-01
One of the commonly used approaches to modeling univariate extremes is the peaks-overthreshold (POT) method. The POT method models exceedances over a (sufficiently high/low) threshold as a generalized Pareto distribution (GPD). To apply this method, a threshold has to be chosen and the estimates might be sensitive to the chosen threshold. Here we propose an alternative, the "Log-Histospline", to explore modeling the tail behavior and the remainder of the density in one step using the full range of the data. Log-Histospline applies a smoothing spline model on a finely binned histogram of the log transformed data to estimate its log density. By construction, we are able to preserve the polynomial upper tail behavior, a feature commonly observed in geophysical observations. The Log-Histospline can be extended to the spatial setting by treating the marginal (log) density at each location as spatially indexed functional data, and perform a dimension reduction and spatial smoothing. We illustrate the proposed method by analyzing precipitation data from regional climate model output (North American Regional Climate Change and Assessment Program (NARCCAP)).
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Cannon, Alex
2017-04-01
univariate technique, and cannot incorporate information from additional covariates, for example ENSO state or physiographic controls on extreme rainfall within a region. Here, the univariate MQR model is extended to allow the use of multiple covariates. Multivariate monotone quantile regression (MMQR) is based on a single hidden-layer feedforward network with the quantile regression error function and partial monotonicity constraints. The MMQR model is demonstrated via Monte Carlo simulations and the estimation and visualization of regional trends in moderate rainfall extremes based on homogenized sub-daily precipitation data at stations in Canada.
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Validation of China-wide interpolated daily climate variables from 1960 to 2011
Yuan, Wenping; Xu, Bing; Chen, Zhuoqi; Xia, Jiangzhou; Xu, Wenfang; Chen, Yang; Wu, Xiaoxu; Fu, Yang
2015-02-01
Temporally and spatially continuous meteorological variables are increasingly in demand to support many different types of applications related to climate studies. Using measurements from 600 climate stations, a thin-plate spline method was applied to generate daily gridded climate datasets for mean air temperature, maximum temperature, minimum temperature, relative humidity, sunshine duration, wind speed, atmospheric pressure, and precipitation over China for the period 1961-2011. A comprehensive evaluation of interpolated climate was conducted at 150 independent validation sites. The results showed superior performance for most of the estimated variables. Except for wind speed, determination coefficients ( R 2) varied from 0.65 to 0.90, and interpolations showed high consistency with observations. Most of the estimated climate variables showed relatively consistent accuracy among all seasons according to the root mean square error, R 2, and relative predictive error. The interpolated data correctly predicted the occurrence of daily precipitation at validation sites with an accuracy of 83 %. Moreover, the interpolation data successfully explained the interannual variability trend for the eight meteorological variables at most validation sites. Consistent interannual variability trends were observed at 66-95 % of the sites for the eight meteorological variables. Accuracy in distinguishing extreme weather events differed substantially among the meteorological variables. The interpolated data identified extreme events for the three temperature variables, relative humidity, and sunshine duration with an accuracy ranging from 63 to 77 %. However, for wind speed, air pressure, and precipitation, the interpolation model correctly identified only 41, 48, and 58 % of extreme events, respectively. The validation indicates that the interpolations can be applied with high confidence for the three temperatures variables, as well as relative humidity and sunshine duration based
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Czech Academy of Sciences Publication Activity Database
Řezáčová, Daniela; Kašpar, Marek; Müller, Miloslav; Sokol, Zbyněk; Kakos, Vilibald; Hanslian, David; Pešice, Petr
2005-01-01
Roč. 77, - (2005), s. 354-366 ISSN 0169-8095 R&D Projects: GA AV ČR(CZ) IBS3042101; GA MŽP(CZ) SA/650/4/03 Institutional research plan: CEZ:AV0Z30420517 Keywords : Precipitation * Summer floods * Czech territory * Hydro-meteorological conditions * Extremeness of meteorological quantities * Distribution function Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.481, year: 2005
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Directory of Open Access Journals (Sweden)
G. Jeelani
2018-06-01
Full Text Available The flow of the Himalayan rivers, a key source of fresh water for more than a billion people primarily depends upon the strength, behaviour and duration of the Indian summer monsoon (ISM and the western disturbances (WD, two contrasting circulation regimes of the regional atmosphere. An analysis of the 2H and 18O isotope composition of daily precipitation collected along the southern foothills of the Himalayas, combined with extensive backward trajectory modelling, was used to gain deeper insight into the mechanisms controlling the isotopic composition of precipitation and the origin of atmospheric moisture and precipitation during ISM and WD periods. Daily precipitation samples were collected during the period from September 2008 to December 2011 at six stations, extending from Srinagar in the west (Kashmir state to Dibrugarh in the east (Assam state. In total, 548 daily precipitation samples were collected and analysed for their stable isotope composition. It is suggested that the gradual reduction in the 2H and 18O content of precipitation in the study region, progressing from δ18O values close to zero down to ca. −10 ‰ in the course of ISM evolution, stems from regional, large-scale recycling of moisture-driven monsoonal circulation. Superimposed on this general trend are short-term fluctuations of the isotopic composition of rainfall, which might have stem from local effects such as enhanced convective activity and the associated higher degree of rainout of moist air masses (local amount effect, the partial evaporation of raindrops, or the impact of isotopically heavy moisture generated in evapotranspiration processes taking place in the vicinity of rainfall sampling sites. Seasonal footprint maps constructed for three stations representing the western, central and eastern portions of the Himalayan region indicate that the influence of monsoonal circulation reaches the western edges of the Himalayan region. While the characteristic
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Lisa V. Alexander
2016-01-01
The Intergovernmental Panel on Climate Change (IPCC) first attempted a global assessment of long-term changes in temperature and precipitation extremes in its Third Assessment Report in 2001. While data quality and coverage were limited, the report still concluded that heavy precipitation events had increased and that there had been, very likely, a reduction in the frequency of extreme low temperatures and increases in the frequency of extreme high temperatures. That overall assessment had ch...
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Yin, Yixing; Chen, Haishan; Xu, Chong-Yu; Xu, Wucheng; Chen, Changchun; Sun, Shanlei
2016-05-01
The regionalization methods, which "trade space for time" by pooling information from different locations in the frequency analysis, are efficient tools to enhance the reliability of extreme quantile estimates. This paper aims at improving the understanding of the regional frequency of extreme precipitation by using regionalization methods, and providing scientific background and practical assistance in formulating the regional development strategies for water resources management in one of the most developed and flood-prone regions in China, the Yangtze River Delta (YRD) region. To achieve the main goals, L-moment-based index-flood (LMIF) method, one of the most popular regionalization methods, is used in the regional frequency analysis of extreme precipitation with special attention paid to inter-site dependence and its influence on the accuracy of quantile estimates, which has not been considered by most of the studies using LMIF method. Extensive data screening of stationarity, serial dependence, and inter-site dependence was carried out first. The entire YRD region was then categorized into four homogeneous regions through cluster analysis and homogenous analysis. Based on goodness-of-fit statistic and L-moment ratio diagrams, generalized extreme-value (GEV) and generalized normal (GNO) distributions were identified as the best fitted distributions for most of the sub-regions, and estimated quantiles for each region were obtained. Monte Carlo simulation was used to evaluate the accuracy of the quantile estimates taking inter-site dependence into consideration. The results showed that the root-mean-square errors (RMSEs) were bigger and the 90 % error bounds were wider with inter-site dependence than those without inter-site dependence for both the regional growth curve and quantile curve. The spatial patterns of extreme precipitation with a return period of 100 years were finally obtained which indicated that there are two regions with highest precipitation
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BACKGROUND: Influenza peaks during the wintertime in temperate regions and during the annual rainy season in tropical regions – however reasons for the observed differences in disease ecology are poorly understood. We hypothesize that episodes of extreme precipitation also result...
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Directory of Open Access Journals (Sweden)
Gyrlene Aparecida Mendes da Silva
2015-04-01
Full Text Available The ability of the Artificial Neural Network (ANN and the Multiple Linear Regression (MLR in reproducing the area-average observed daily precipitation during the rainy season (Feb-Mar-Apr over the north of the Northeast of Brazil (NEB is examined. For the present climate of Dec-Jan-Feb from 1963 to 2003 period these statistical models are developed and validated using the observed daily precipitation and simulated from the historical outputs of 4 models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5. The simulations from all the models during DJF and FMA seasons show an anomalous intensification of the ITCZ and southward displacement in comparison with the climatology. Correlations of 0.54, 0.66 and 0.66 are found between the simulated daily precipitation of the CCSM4, GFDL_ESM2M and MIROC_ESM models during DJF season and the observed values during FMA season. Only the CCSM4 model displays a slightly reasonable agreement with the observations. A comparison between the statistical downscaling using the nonlinear (ANN and linear model (MLR to identify the one most suitable for the analysis of daily precipitation was made. The ANN technique provides more ability to predict the present climate when compared to MLR technique. Based on this result, we examined the accuracy of the ANN model in project the changes for the future climate period from 2055 to 2095 over the same study region. For instance, a comparison between the daily precipitation changes projected indirectly from the ANN during Feb-Mar-Apr with those projected directly from the CMIP5 models forced by RCP 8.5 scenario is made. The results suggest that ANN model weights the CMIP5 projections according to the each model ability in simulating the present climate (and its variability. In others, the ANN model is a potentially promising approach to use as a complementary tool to improvement of the seasonal numerical simulations.
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Evaluation of precipitation extremes and floods and comparison between their temporal distributions
Czech Academy of Sciences Publication Activity Database
Müller, Miloslav; Kašpar, Marek; Valeriánová, A.; Crhová, L.; Holtanová, E.
2015-01-01
Roč. 12, č. 1 (2015), s. 281-310 ISSN 1812-2108 R&D Projects: GA ČR(CZ) GAP209/11/1990 Institutional support: RVO:68378289 Keywords : precipitation extremes * floods Subject RIV: DG - Athmosphere Sci ences, Meteorology OBOR OECD: Meteorology and atmospheric sci ences https://www.hydrol-earth-syst- sci .net/19/4641/2015/hessd-12-281-2015.pdf
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Changes in observed climate extremes in global urban areas
International Nuclear Information System (INIS)
Mishra, Vimal; Ganguly, Auroop R; Nijssen, Bart; Lettenmaier, Dennis P
2015-01-01
Climate extremes have profound implications for urban infrastructure and human society, but studies of observed changes in climate extremes over the global urban areas are few, even though more than half of the global population now resides in urban areas. Here, using observed station data for 217 urban areas across the globe, we show that these urban areas have experienced significant increases (p-value <0.05) in the number of heat waves during the period 1973–2012, while the frequency of cold waves has declined. Almost half of the urban areas experienced significant increases in the number of extreme hot days, while almost 2/3 showed significant increases in the frequency of extreme hot nights. Extreme windy days declined substantially during the last four decades with statistically significant declines in about 60% in the urban areas. Significant increases (p-value <0.05) in the frequency of daily precipitation extremes and in annual maximum precipitation occurred at smaller fractions (17 and 10% respectively) of the total urban areas, with about half as many urban areas showing statistically significant downtrends as uptrends. Changes in temperature and wind extremes, estimated as the result of a 40 year linear trend, differed for urban and non-urban pairs, while changes in indices of extreme precipitation showed no clear differentiation for urban and selected non-urban stations. (letter)
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Brunsell, N. A.; Nippert, J. B.
2011-12-01
As the climate warms, it is generally acknowledged that the number and magnitude of extreme weather events will increase. We examined an ecophysiological model's responses to precipitation and temperature anomalies in relation to the mean and variance of annual precipitation along a pronounced precipitation gradient from eastern to western Kansas. This natural gradient creates a template of potential responses for both the mean and variance of annual precipitation to compare the timescales of carbon and water fluxes. Using data from several Ameriflux sites (KZU and KFS) and a third eddy covariance tower (K4B) along the gradient, BIOME-BGC was used to characterize water and carbon cycle responses to extreme weather events. Changes in the extreme value distributions were based on SRES A1B and A2 scenarios using an ensemble mean of 21 GCMs for the region, downscaled using a stochastic weather generator. We focused on changing the timing and magnitude of precipitation and altering the diurnal and seasonal temperature ranges. Biome-BGC was then forced with daily output from the stochastic weather generator, and we examined how potential changes in these extreme value distributions impact carbon and water cycling at the sites across the Kansas precipitation gradient at time scales ranging from daily to interannual. To decompose the time scales of response, we applied a wavelet based information theory analysis approach. Results indicate impacts in soil moisture memory and carbon allocation processes, which vary in response to both the mean and variance of precipitation along the precipitation gradient. These results suggest a more pronounced focus ecosystem responses to extreme events across a range of temporal scales in order to fully characterize the water and carbon cycle responses to global climate change.
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Miao, Chiyuan; Sun, Qiaohong; Borthwick, Alistair G. L.; Duan, Qingyun
2016-01-01
We investigated changes in the temporospatial features of hourly precipitation during the warm season over mainland China. The frequency and amount of hourly precipitation displayed latitudinal zonation, especially for light and moderate precipitation, which showed successive downward change over time in northeastern and southern China. Changes in the precipitation amount resulted mainly from changes in frequency rather than changes in intensity. We also evaluated the linkage between hourly precipitation and temperature variations and found that hourly precipitation extreme was more sensitive to temperature than other categories of precipitation. A strong dependency of hourly precipitation on temperature occurred at temperatures colder than the median daily temperature; in such cases, regression slopes were greater than the Clausius-Clapeyron (C-C) relation of 7% per degree Celsius. Regression slopes for 31.6%, 59.8%, 96.9%, and 99.1% of all stations were greater than 7% per degree Celsius for the 75th, 90th, 99th, and 99.9th percentiles for precipitation, respectively. The mean regression slopes within the 99.9th percentile of precipitation were three times the C-C rate. Hourly precipitation showed a strong negative relationship with daily maximum temperature and the diurnal temperature range at most stations, whereas the equivalent correlation for daily minimum temperature was weak. PMID:26931350
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Santos, Monica; Fragoso, Marcelo
2010-05-01
Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude
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Polade, Suraj D; Gershunov, Alexander; Cayan, Daniel R; Dettinger, Michael D; Pierce, David W
2017-09-07
In most Mediterranean climate (MedClim) regions around the world, global climate models (GCMs) consistently project drier futures. In California, however, projections of changes in annual precipitation are inconsistent. Analysis of daily precipitation in 30 GCMs reveals patterns in projected hydrometeorology over each of the five MedClm regions globally and helps disentangle their causes. MedClim regions, except California, are expected to dry via decreased frequency of winter precipitation. Frequencies of extreme precipitation, however, are projected to increase over the two MedClim regions of the Northern Hemisphere where projected warming is strongest. The increase in heavy and extreme precipitation is particularly robust over California, where it is only partially offset by projected decreases in low-medium intensity precipitation. Over the Mediterranean Basin, however, losses from decreasing frequency of low-medium-intensity precipitation are projected to dominate gains from intensifying projected extreme precipitation. MedClim regions are projected to become more sub-tropical, i.e. made dryer via pole-ward expanding subtropical subsidence. California's more nuanced hydrological future reflects a precarious balance between the expanding subtropical high from the south and the south-eastward extending Aleutian low from the north-west. These dynamical mechanisms and thermodynamic moistening of the warming atmosphere result in increased horizontal water vapor transport, bolstering extreme precipitation events.
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Haylock, M.; Hofstra, N.; Klein Tank, A.; Klok, L.; Jones, P.; New, M.
2008-01-01
We present a European land-only daily high-resolution gridded data set for precipitation and minimum, maximum, and mean surface temperature for the period 1950–2006. This data set improves on previous products in its spatial resolution and extent, time period, number of contributing stations, and
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Seo, Dong-Jun; Siddique, Ridwan; Zhang, Yu; Kim, Dongsoo
2014-11-01
A new technique for gauge-only precipitation analysis for improved estimation of heavy-to-extreme precipitation is described and evaluated. The technique is based on a novel extension of classical optimal linear estimation theory in which, in addition to error variance, Type-II conditional bias (CB) is explicitly minimized. When cast in the form of well-known kriging, the methodology yields a new kriging estimator, referred to as CB-penalized kriging (CBPK). CBPK, however, tends to yield negative estimates in areas of no or light precipitation. To address this, an extension of CBPK, referred to herein as extended conditional bias penalized kriging (ECBPK), has been developed which combines the CBPK estimate with a trivial estimate of zero precipitation. To evaluate ECBPK, we carried out real-world and synthetic experiments in which ECBPK and the gauge-only precipitation analysis procedure used in the NWS's Multisensor Precipitation Estimator (MPE) were compared for estimation of point precipitation and mean areal precipitation (MAP), respectively. The results indicate that ECBPK improves hourly gauge-only estimation of heavy-to-extreme precipitation significantly. The improvement is particularly large for estimation of MAP for a range of combinations of basin size and rain gauge network density. This paper describes the technique, summarizes the results and shares ideas for future research.
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Bliefernicht, Jan; Waongo, Moussa; Annor, Thompson; Laux, Patrick; Lorenz, Manuel; Salack, Seyni; Kunstmann, Harald
2017-04-01
West Africa is a data sparse region. High quality and long-term precipitation data are often not readily available for applications in hydrology, agriculture, meteorology and other needs. To close this gap, we use multiple data sources to develop a precipitation database with long-term daily and monthly time series. This database was compiled from 16 archives including global databases e.g. from the Global Historical Climatology Network (GHCN), databases from research projects (e.g. the AMMA database) and databases of the national meteorological services of some West African countries. The collection consists of more than 2000 precipitation gauges with measurements dating from 1850 to 2015. Due to erroneous measurements (e.g. temporal offsets, unit conversion errors), missing values and inconsistent meta-data, the merging of this precipitation dataset is not straightforward and requires a thorough quality control and harmonization. To this end, we developed geostatistical-based algorithms for quality control of individual databases and harmonization to a joint database. The algorithms are based on a pairwise comparison of the correspondence of precipitation time series in dependence to the distance between stations. They were tested for precipitation time series from gages located in a rectangular domain covering Burkina Faso, Ghana, Benin and Togo. This harmonized and quality controlled precipitation database was recently used for several applications such as the validation of a high resolution regional climate model and the bias correction of precipitation projections provided the Coordinated Regional Climate Downscaling Experiment (CORDEX). In this presentation, we will give an overview of the novel daily and monthly precipitation database and the algorithms used for quality control and harmonization. We will also highlight the quality of global and regional archives (e.g. GHCN, GSOD, AMMA database) in comparison to the precipitation databases provided by the
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On the daily cycle of the climatological variables in the Municipality of Quibdo
International Nuclear Information System (INIS)
Pabon, Jose Daniel; Reiner Palomino Lemus; William Murillo Lopez
2005-01-01
We analyzed the daily cycle of the climatological variables (solar radiation, air temperature, atmospheric pressure, precipitation and wind) in Quibdo, (5.45 degrades N and 76.39 degrades W, 53m), department of Choco. The analysis is based on hourly data recorded during the period 2000-2004 at the meteorological and radiometric station of the technological university of Choco, Diego Luis Cordoba (UTCH). It is shown that the daily cycle of the climatological variables in the city of Quibdo is typical of the tropical areas and the particularities of the daily pattern of precipitation were found: most of the rains occur during the evening. The seasonal variation of the daily cycle was also established. Finally, an approximation was made to the analyses of the effect of extreme phases of inter annual climate variability associated to El Nino and la Nina
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DEFF Research Database (Denmark)
Sunyer Pinya, Maria Antonia; Hundecha, Y.; Lawrence, D.
impact studies. Four methods are based on change factors and four are bias correction methods. The change factor methods perturb the observations according to changes in precipitation properties estimated from the Regional Climate Models (RCMs). The bias correction methods correct the output from...... the RCMs. The eight methods are used to downscale precipitation output from fifteen RCMs from the ENSEMBLES project for eleven catchments in Europe. The performance of the bias correction methods depends on the catchment, but in all cases they represent an improvement compared to RCM output. The overall...... results point to an increase in extreme precipitation in all the catchments in winter and in most catchments in summer. For each catchment, the results tend to agree on the direction of the change but differ in the magnitude. These differences can be mainly explained due to differences in the RCMs....
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Firpo, M. A.; Sansigolo, C. A.
2011-12-01
One of the most important modes of interannual variability from ocean-atmosphere system is the El Niño/Southern Oscillation - ENSO. The Brazil southern region belongs to the Southeast of South America, where there is a strong signal of ENSO, especially over the precipitation. This phenomenon can be modulated by low frequency climate patterns, especially the dominant pattern of North Pacific, called Pacific Decadal Oscillation (PDO). Attempting to better understand these interactions, the objective of this study was to investigate the seasonal impact of ENSO events over the Southern Brazil precipitation, taking into account the PDO phases. The dataset used in this study, consist of monthly precipitation records of six well distributed stations from southern Brazil (Rio Grande do Sul state). From these series it was calculated a unique index, which was categorized in three classes, in order to obtain the extremes: very below normal precipitation (below the percentile 10), normal precipitation (between percentile 10 and 90) and very above normal precipitation (above the percentile 90). To characterize the ENSO events, it was applied the Trenberth (1997) criteria in the index proposed by Bunge and Clarke (2009), which corrects the inconsistencies between the conventional SST index for Niño 3.4 region and the Southern Oscillation Index before 1950, going beyond the incoherence for decadal scale. For PDO, it was used the index proposed by Mantua et al. (1997). Contingency tables were constructed to analyze the seasonal, simultaneous, and 3, 6, 9 and 12 months lagged relationships between ENSO events (El Niño, neutral, La Niña), and extreme precipitation anomalies (categories), also considering the PDO phases during the 1913-1999 period. Moreover, a wavelet analysis was used to check the coherency and phase among these 3 times series during the 1913-2006 period. The Contingency Tables analysis showed that, generally, there were more positive (negative) precipitation
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Czech Academy of Sciences Publication Activity Database
Müller, Miloslav; Kašpar, Marek; Valeriánová, A.; Crhová, L.; Holtanová, E.; Gvoždíková, B.
2015-01-01
Roč. 19, č. 11 (2015), s. 4641-4652 ISSN 1027-5606 R&D Projects: GA ČR(CZ) GAP209/11/1990 Institutional support: RVO:68378289 Keywords : precipitation extreme * flood * extremity index * Czech Republic Subject RIV: DG - Athmosphere Sci ences, Meteorology Impact factor: 3.990, year: 2015 http://www.hydrol-earth-syst- sci .net/19/4641/2015/hess-19-4641-2015.html
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Daily temperature and precipitation data for 223 USSR Stations
Energy Technology Data Exchange (ETDEWEB)
Razuvaev, V.N.; Apasova, E.G.; Martuganov, R.A. [Research Institute of Hydrometeorological Information, Obninsk (Russian Federation); Vose, R.S. [Univ. of Tennessee, Knoxville, TN (United States); Steurer, P.M. [National Climatic Data Center, Asheville, NC (United States)
1993-11-01
On- May 23, 1972, the United States and the USSR established a bilateral initiative known as the Agreement on Protection of the Environment. Given recent interest in possible greenhouse gas-induced climate change, Working Group VIII (Influence of Environmental Changes on Climate) has become particularly useful to the scientific communities of both nations. Among its many achievements, Working Group VIII has been instrumental in the exchange of climatological information between the principal climate data centers of each country [i.e., the National Climatic Data Center (NCDC) in Asheville, North Carolina, and the Research Institute of Hydrometeorological Information in Obninsk, Russia]. Considering the relative lack of climate records previously available for the USSR, data obtained via this bilateral exchange are particularly valuable to researchers outside the former Soviet Union. To expedite the dissemination of these data, NOAA`s Climate and Global Change Program funded the Carbon Dioxide Information Analysis Center (CDIAC) and NCDC to distribute one of the more useful archives acquired through this exchange: a 223-station daily data set covering the period 1881-1989. This data set contains: (1) daily mean, minimum, and maximum temperature data; (2) daily precipitation data; (3) station inventory information (WMO No., name, coordinates, and elevation); (4) station history information (station relocation and rain gauge replacement dates); and (5) quality assurance information (i.e., flag codes that were assigned as a result of various data checks). The data set is available, free of charge, as a Numeric Data Package (NDP) from CDIAC. The NDP consists of 18 data files and a printed document which describes both the data files and the 223-station network in detail.
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Daily rainfall statistics of TRMM and CMORPH: A case for trans ...
Indian Academy of Sciences (India)
6 product ... TRMM fares better in the prediction of probability of occurrence of high-intensity ... TRMM precipitation estimates can be used for flood-related studies only after bias adjustment for the topography. 1. ... daily time step for climate change and extreme ... spatial distributions of rain gauges and the consis- tency in the ...
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Li, W.; Jiang, Z.
2017-12-01
In order to strengthen the global respond to the dangerous of global warming, Paris Agreement sets out two long-term warming goals: limiting global warming to well below 2˚C and purse effort to below 1.5˚C above pre-industrial levels. However, future climate change risks in those two warming targets show significant regional differences. This article aims to study the intensity and frequency of extreme precipitation change over China under those two global warming targets by using CMIP5 models under RCP4.5 and RCP8.5 scenario. Focus is put on the effects of the additional half degree in changing the extreme precipitation. Results show that the changes of extreme precipitation are independent of the RCP scenarios when global warming reaches the same threshold. Intensity of extreme precipitation averaged over China increase by around 6% and 11% when global warming reaches 1.5˚C and 2˚C, respectively. The additional half a degree increase makes the intensity of extreme precipitation averaged over China to increase by 4.5%, which translates to an increase close to the Clausius-Clapeyron scaling. Return period decreases by 5 years for the extra half degree warming when the 20-year return values are considered at the reference level.
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Mascaro, Giuseppe
2018-04-01
This study uses daily rainfall records of a dense network of 240 gauges in central Arizona to gain insights on (i) the variability of the seasonal distributions of rainfall extremes; (ii) how the seasonal distributions affect the shape of the annual distribution; and (iii) the presence of spatial patterns and orographic control for these distributions. For this aim, recent methodological advancements in peak-over-threshold analysis and application of the Generalized Pareto Distribution (GPD) were used to assess the suitability of the GPD hypothesis and improve the estimation of its parameters, while limiting the effect of short sample sizes. The distribution of daily rainfall extremes was found to be heavy-tailed (i.e., GPD shape parameter ξ > 0) during the summer season, dominated by convective monsoonal thunderstorms. The exponential distribution (a special case of GPD with ξ = 0) was instead showed to be appropriate for modeling wintertime daily rainfall extremes, mainly caused by cold fronts transported by westerly flow. The annual distribution exhibited a mixed behavior, with lighter upper tails than those found in summer. A hybrid model mixing the two seasonal distributions was demonstrated capable of reproducing the annual distribution. Organized spatial patterns, mainly controlled by elevation, were observed for the GPD scale parameter, while ξ did not show any clear control of location or orography. The quantiles returned by the GPD were found to be very similar to those provided by the National Oceanic and Atmospheric Administration (NOAA) Atlas 14, which used the Generalized Extreme Value (GEV) distribution. Results of this work are useful to improve statistical modeling of daily rainfall extremes at high spatial resolution and provide diagnostic tools for assessing the ability of climate models to simulate extreme events.
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Singh, Jitendra; Hari, Vittal; Sharma, Tarul; Karmakar, Subhankar; Ghosh, Subimal
2016-04-01
The statistical assumption of stationarity in hydrologic extreme time/event series has been relied heavily in frequency analysis. However, due to the analytically perceivable impacts of climate change, urbanization and concomitant land use pattern, assumption of stationarity in hydrologic time series will draw erroneous results, which in turn may affect the policy and decision-making. Past studies provided sufficient evidences on changes in the characteristics of Indian monsoon precipitation extremes and further it has been attributed to climate change and urbanization, which shows need of nonstationary analysis on the Indian monsoon extremes. Therefore, a comprehensive multivariate nonstationary frequency analysis has been conducted for the entire India to identify the precipitation characteristics (intensity, duration and depth) responsible for significant nonstationarity in the Indian monsoon. We use 1o resolution of precipitation data for a period of 1901-2004, in a Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework. A cluster of GAMLSS models has been developed by considering nonstationarity in different combinations of distribution parameters through different regression techniques, and the best-fit model is further applied for bivariate analysis. A population density data has been utilized to identify the urban, urbanizing and rural regions. The results showed significant differences in the stationary and nonstationary bivariate return periods for the urbanizing grids, when compared to urbanized and rural grids. A comprehensive multivariate analysis has also been conducted to identify the precipitation characteristics particularly responsible for imprinting signature of nonstationarity.
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José Gómez-Navarro, Juan; Raible, Christoph C.; Blumer, Sandro; Martius, Olivia; Felder, Guido
2016-04-01
Extreme precipitation episodes, although rare, are natural phenomena that can threat human activities, especially in areas densely populated such as Switzerland. Their relevance demands the design of public policies that protect public assets and private property. Therefore, increasing the current understanding of such exceptional situations is required, i.e. the climatic characterisation of their triggering circumstances, severity, frequency, and spatial distribution. Such increased knowledge shall eventually lead us to produce more reliable projections about the behaviour of these events under ongoing climate change. Unfortunately, the study of extreme situations is hampered by the short instrumental record, which precludes a proper characterization of events with return period exceeding few decades. This study proposes a new approach that allows studying storms based on a synthetic, but physically consistent database of weather situations obtained from a long climate simulation. Our starting point is a 500-yr control simulation carried out with the Community Earth System Model (CESM). In a second step, this dataset is dynamically downscaled with the Weather Research and Forecasting model (WRF) to a final resolution of 2 km over the Alpine area. However, downscaling the full CESM simulation at such high resolution is infeasible nowadays. Hence, a number of case studies are previously selected. This selection is carried out examining the precipitation averaged in an area encompassing Switzerland in the ESM. Using a hydrological criterion, precipitation is accumulated in several temporal windows: 1 day, 2 days, 3 days, 5 days and 10 days. The 4 most extreme events in each category and season are selected, leading to a total of 336 days to be simulated. The simulated events are affected by systematic biases that have to be accounted before this data set can be used as input in hydrological models. Thus, quantile mapping is used to remove such biases. For this task
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Kara, Fatih; Yucel, Ismail
2015-09-01
This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960-1990) and scenario (2071-2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained.
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Extreme weather events in Iran under a changing climate
Alizadeh-Choobari, Omid; Najafi, M. S.
2018-01-01
Observations unequivocally show that Iran has been rapidly warming over recent decades, which in sequence has triggered a wide range of climatic impacts. Meteorological records of several ground stations across Iran with daily temporal resolution for the period 1951-2013 were analyzed to investigate the climate change and its impact on some weather extremes. Iran has warmed by nearly 1.3 °C during the period 1951-2013 (+0.2 °C per decade), with an increase of the minimum temperature at a rate two times that of the maximum. Consequently, an increase in the frequency of heat extremes and a decrease in the frequency of cold extremes have been observed. The annual precipitation has decreased by 8 mm per decade, causing an expansion of Iran's dry zones. Previous studies have pointed out that warming is generally associated with more frequent heavy precipitation because a warmer air can hold more moisture. Nevertheless, warming in Iran has been associated with more frequent light precipitation, but less frequent moderate, heavy and extremely heavy precipitation. This is because in the subtropical dry zones, a longer time is required to recharge the atmosphere with water vapour in a warmer climate, causing more water vapour to be transported from the subtropics to high latitudes before precipitations forms. In addition, the altitude of the condensation level increases in a warmer climate in subtropical regions, causing an overall decrease of precipitation. We argue that changing in the frequency of heavy precipitation in response to warming varies depending on the geographical location. Warming over the dry subtropical regions is associated with a decrease in the frequency of heavy precipitation, while an increase is expected over both subpolar and tropical regions. The warmer climate has also led to the increase in the frequency of both thunderstorms (driven by convective heating) and dust events over Iran.
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DEFF Research Database (Denmark)
Madsen, Henrik; Sunyer Pinya, Maria Antonia; Rosbjerg, Dan
projections for estimation of changes in extreme rainfall characteristics. Climate model projections from 20 regional climate models (RCM) from the ENSEMBLES data archive were used in the analysis. Two different estimation methods were applied, using, respectively, a direct estimation of the changes...... in the extreme value statistics of the RCM data, and application of a stochastic weather generator fitted to the changes in rainfall characteristics from the RCM data. The results show a large variability in the projected changes in extreme precipitation between the different RCMs and the two estimation methods...
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Evolution of extreme rainfall in France with a changing climate
International Nuclear Information System (INIS)
Soubeyroux, Jean-Michel; Veysseire, Jean-Michel; Gouget, Viviane; Neppel, Luc; Tramblay, Yves; Carreau, Julie
2015-01-01
This paper focuses a synthesis of the works led within the framework of the French project ANR/Extraflo on the evolution of the daily (and infra daily) extreme rainfall in France. An important dataset of more than 900 series was used. It was shown that a majority of series presented a not significant upward trend in particular in Mediterranean area, in relation with various recent exceptional extreme events. An interesting way to characterize this evolution consists in identifying climatic co-variables associated to heavy rainfall events (weather patterns, average temperatures, flow of humidity) and in taking into account them with a non stationary POT model. The application of this method with climatic projections under scenario A2 from IPCC could lead to a possible increase on extreme precipitation quantiles on the horizon 2070. (authors)
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Long-Term Climate Trends and Extreme Events in Northern Fennoscandia (1914–2013
Directory of Open Access Journals (Sweden)
Sonja Kivinen
2017-02-01
Full Text Available We studied climate trends and the occurrence of rare and extreme temperature and precipitation events in northern Fennoscandia in 1914–2013. Weather data were derived from nine observation stations located in Finland, Norway, Sweden and Russia. The results showed that spring and autumn temperatures and to a lesser extent summer temperatures increased significantly in the study region, the observed changes being the greatest for daily minimum temperatures. The number of frost days declined both in spring and autumn. Rarely cold winter, spring, summer and autumn seasons had a low occurrence and rarely warm spring and autumn seasons a high occurrence during the last 20-year interval (1994–2013, compared to the other 20-year intervals. That period was also characterized by a low number of days with extremely low temperature in all seasons (4–9% of all extremely cold days and a high number of April and October days with extremely high temperature (36–42% of all extremely warm days. A tendency of exceptionally high daily precipitation sums to grow even higher towards the end of the study period was also observed. To summarize, the results indicate a shortening of the cold season in northern Fennoscandia. Furthermore, the results suggest significant declines in extremely cold climate events in all seasons and increases in extremely warm climate events particularly in spring and autumn seasons.
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Hourly and Daily Precipitation Data
National Oceanic and Atmospheric Administration, Department of Commerce — Precipitation reports submitted on many form types, including tabular and autographic charts. Reports are almost exclusively from the US Cooperative Observer Network.
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Llasat, Maria Carmen; Marcos, Raul; Turco, Marco; Gilabert, Joan; Llasat-Botija, Montserrat
2016-10-01
The aim of this paper is to analyse the potential relationship between flash flood events and convective precipitation in Catalonia, as well as any related trends. The paper starts with an overview of flash floods and their trends in the Mediterranean region, along with their associated factors, followed by the definition of, identification of, and trends in convective precipitation. After this introduction the paper focuses on the north-eastern Iberian Peninsula, for which there is a long-term precipitation series (since 1928) of 1-min precipitation from the Fabra Observatory, as well as a shorter (1996-2011) but more extensive precipitation series (43 rain gauges) of 5-min precipitation. Both series have been used to characterise the degree of convective contribution to rainfall, introducing the β parameter as the ratio between convective precipitation versus total precipitation in any period. Information about flood events was obtained from the INUNGAMA database (a flood database created by the GAMA team), with the aim of finding any potential links to convective precipitation. These flood data were gathered using information on damage where flood is treated as a multifactorial risk, and where any trend or anomaly might have been caused by one or more factors affecting hazard, vulnerability or exposure. Trend analysis has shown an increase in flash flood events. The fact that no trends were detected in terms of extreme values of precipitation on a daily scale, nor on the associated ETCCDI (Expert Team on Climate Change Detection and Indices) extreme index, could point to an increase in vulnerability, an increase in exposure, or changes in land use. However, the summer increase in convective precipitation was concentrated in less torrential events, which could partially explain this positive trend in flash flood events. The β parameter has been also used to characterise the type of flood event according to the features of the precipitation. The highest values
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Projections of the Ganges-Brahmaputra precipitation: downscaled from GCM predictors
Pervez, Md Shahriar; Henebry, Geoffrey M.
2014-01-01
Downscaling Global Climate Model (GCM) projections of future climate is critical for impact studies. Downscaling enables use of GCM experiments for regional scale impact studies by generating regionally specific forecasts connecting global scale predictions and regional scale dynamics. We employed the Statistical Downscaling Model (SDSM) to downscale 21st century precipitation for two data-sparse hydrologically challenging river basins in South Asia—the Ganges and the Brahmaputra. We used CGCM3.1 by Canadian Center for Climate Modeling and Analysis version 3.1 predictors in downscaling the precipitation. Downscaling was performed on the basis of established relationships between historical Global Summary of Day observed precipitation records from 43 stations and National Center for Environmental Prediction re-analysis large scale atmospheric predictors. Although the selection of predictors was challenging during the set-up of SDSM, they were found to be indicative of important physical forcings in the basins. The precipitation of both basins was largely influenced by geopotential height: the Ganges precipitation was modulated by the U component of the wind and specific humidity at 500 and 1000 h Pa pressure levels; whereas, the Brahmaputra precipitation was modulated by the V component of the wind at 850 and 1000 h Pa pressure levels. The evaluation of the SDSM performance indicated that model accuracy for reproducing precipitation at the monthly scale was acceptable, but at the daily scale the model inadequately simulated some daily extreme precipitation events. Therefore, while the downscaled precipitation may not be the suitable input to analyze future extreme flooding or drought events, it could be adequate for analysis of future freshwater availability. Analysis of the CGCM3.1 downscaled precipitation projection with respect to observed precipitation reveals that the precipitation regime in each basin may be significantly impacted by climate change
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Extreme precipitation in the Polish Carpathians in the 20th century in the context of last 500 years
Limanowka, Danuta; Cebulak, Elzbieta; Pyrc, Robert
2010-05-01
Extreme weather phenomena together with their exceptional course and intensity have always been dangerous for people. In the historical documents such phenomena were marked as basic disasters. First notes about weather phenomena were made in Polish lands in the 10th century. Most information concerns floods caused by intensive rains. Using the data base created within the Millennium project, extreme precipitation cases exceeding 100 mm were analysed. In each case, the intensive precipitation was followed by a summer flood in the Polish Carpathians in the Upper Vistula River basin. Data from the period of instrumental measurements in the 20th century were studied in detail by the analysis of the frequency of occurrence and the spatial and temporal distribution. The results were referred to last 500 years. The information obtained gives approximate image of extreme precipitation in the historical times in Polish lands. All available multi-proxy data were used. Newspapers' notes concerning described phenomena from 1848-1850 published in Kraków were used to complete and verify the quality of data from the early instrumental period and also to complete the data from the period of the Second World War.
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Directory of Open Access Journals (Sweden)
Lisa V. Alexander
2016-03-01
Full Text Available The Intergovernmental Panel on Climate Change (IPCC first attempted a global assessment of long-term changes in temperature and precipitation extremes in its Third Assessment Report in 2001. While data quality and coverage were limited, the report still concluded that heavy precipitation events had increased and that there had been, very likely, a reduction in the frequency of extreme low temperatures and increases in the frequency of extreme high temperatures. That overall assessment had changed little by the time of the IPCC Special Report on Extremes (SREX in 2012 and the IPCC Fifth Assessment Report (AR5 in 2013, but firmer statements could be added and more regional detail was possible. Despite some substantial progress throughout the IPCC Assessments in terms of temperature and precipitation extremes analyses, there remain major gaps particularly regarding data quality and availability, our ability to monitor these events consistently and our ability to apply the complex statistical methods required. Therefore this article focuses on the substantial progress that has taken place in the last decade, in addition to reviewing the new progress since IPCC AR5 while also addressing the challenges that still lie ahead.
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Climatic changes of extreme precipitation in Denmark from 1874 to 2100
DEFF Research Database (Denmark)
Gregersen, Ida Bülow; Sunyer Pinya, Maria Antonia; Madsen, Henrik
2014-01-01
inundation risk. Hence different statistical downscaling methods have been applied. Furthermore, the effect of the emission scenario, the spatial resolution of the RCM and the interdependency between RCMs are discussed. Taking this information into account a 2‐year event is expected to increase by 20% over...... a projection period of 100 years. This approximates the variation within one natural oscillation cycle, indicating that it is crucial to understand and account for the future multi‐decadal variations of extreme precipitation. The study estimates the expected magnitude of variation in design rainfall for urban...
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Trends in precipitation extremes and long-term memory of runoff records in Zhejiang, East China
Tian, Y.; Tian, Ye; Xu, YuePing; Booij, Martijn J.; Zhang, Qingqing; Lin, Shengji; Franks, Steward W.; Boegh, Eva; Blyth, Eleanor; Hannah, David M.; Yilmaz, Koray K.
2011-01-01
Extreme weather events have a huge impact on human beings and therefore it is of vital importance to investigate trends in relevant climatological and hydrological variables. In this study, precipitation and streamflow trends in Zhejiang Province in east China are analysed. Trends in annual and
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Uncertainties in extreme precipitation under climate change conditions
DEFF Research Database (Denmark)
Sunyer Pinya, Maria Antonia
of adaptation strategies, but these changes are subject to uncertainties. The focus of this PhD thesis is the quantification of uncertainties in changes in extreme precipitation. It addresses two of the main sources of uncertainty in climate change impact studies: regional climate models (RCMs) and statistical...... downscaling methods (SDMs). RCMs provide information on climate change at the regional scale. SDMs are used to bias-correct and downscale the outputs of the RCMs to the local scale of interest in adaptation strategies. In the first part of the study, a multi-model ensemble of RCMs from the European ENSEMBLES...... project was used to quantify the uncertainty in RCM projections over Denmark. Three aspects of the RCMs relevant for the uncertainty quantification were first identified and investigated. These are: the interdependency of the RCMs; the performance in current climate; and the change in the performance...
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Pongracz, R.; Bartholy, J.; Szabo, P.; Pieczka, I.; Torma, C. S.
2009-04-01
Regional climatological effects of global warming may be recognized not only in shifts of mean temperature and precipitation, but in the frequency or intensity changes of different climate extremes. Several climate extreme indices are analyzed and compared for the Carpathian basin (located in Central/Eastern Europe) following the guidelines suggested by the joint WMO-CCl/CLIVAR Working Group on climate change detection. Our statistical trend analysis includes the evaluation of several extreme temperature and precipitation indices, e.g., the numbers of severe cold days, winter days, frost days, cold days, warm days, summer days, hot days, extremely hot days, cold nights, warm nights, the intra-annual extreme temperature range, the heat wave duration, the growing season length, the number of wet days (using several threshold values defining extremes), the maximum number of consecutive dry days, the highest 1-day precipitation amount, the greatest 5-day rainfall total, the annual fraction due to extreme precipitation events, etc. In order to evaluate the future trends (2071-2100) in the Carpathian basin, daily values of meteorological variables are obtained from the outputs of various regional climate model (RCM) experiments accomplished in the frame of the completed EU-project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). Horizontal resolution of the applied RCMs is 50 km. Both scenarios A2 and B2 are used to compare past and future trends of the extreme climate indices for the Carpathian basin. Furthermore, fine-resolution climate experiments of two additional RCMs adapted and run at the Department of Meteorology, Eotvos Lorand University are used to extend the trend analysis of climate extremes for the Carpathian basin. (1) Model PRECIS (run at 25 km horizontal resolution) was developed at the UK Met Office, Hadley Centre, and it uses the boundary conditions from the HadCM3 GCM. (2) Model Reg
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Colmet-Daage, Antoine; Sanchez-Gomez, Emilia; Ricci, Sophie; Llovel, Cécile; Borrell Estupina, Valérie; Quintana-Seguí, Pere; Llasat, Maria Carmen; Servat, Eric
2018-01-01
The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981-2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.
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Nie, Ji; Shaevitz, Daniel A.; Sobel, Adam H.
2016-09-01
Extratropical extreme precipitation events are usually associated with large-scale flow disturbances, strong ascent, and large latent heat release. The causal relationships between these factors are often not obvious, however, the roles of different physical processes in producing the extreme precipitation event can be difficult to disentangle. Here we examine the large-scale forcings and convective heating feedback in the precipitation events, which caused the 2010 Pakistan flood within the Column Quasi-Geostrophic framework. A cloud-revolving model (CRM) is forced with large-scale forcings (other than large-scale vertical motion) computed from the quasi-geostrophic omega equation using input data from a reanalysis data set, and the large-scale vertical motion is diagnosed interactively with the simulated convection. Numerical results show that the positive feedback of convective heating to large-scale dynamics is essential in amplifying the precipitation intensity to the observed values. Orographic lifting is the most important dynamic forcing in both events, while differential potential vorticity advection also contributes to the triggering of the first event. Horizontal moisture advection modulates the extreme events mainly by setting the environmental humidity, which modulates the amplitude of the convection's response to the dynamic forcings. When the CRM is replaced by either a single-column model (SCM) with parameterized convection or a dry model with a reduced effective static stability, the model results show substantial discrepancies compared with reanalysis data. The reasons for these discrepancies are examined, and the implications for global models and theoretical models are discussed.
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Future changes in precipitation and impacts on extreme streamflow over Amazonian sub-basins
International Nuclear Information System (INIS)
Guimberteau, M; Ronchail, J; Lengaigne, M; Sultan, B; Drapeau, G; Espinoza, J C; Polcher, J; Guyot, J-L; Ducharne, A; Ciais, P
2013-01-01
Because of climate change, much attention is drawn to the Amazon River basin, whose hydrology has already been strongly affected by extreme events during the past 20 years. Hydrological annual extreme variations (i.e. low/high flows) associated with precipitation (and evapotranspiration) changes are investigated over the Amazon River sub-basins using the land surface model ORCHIDEE and a multimodel approach. Climate change scenarios from up to eight AR4 Global Climate Models based on three emission scenarios were used to build future hydrological projections in the region, for two periods of the 21st century. For the middle of the century under the SRESA1B scenario, no change is found in high flow on the main stem of the Amazon River (Óbidos station), but a systematic discharge decrease is simulated during the recession period, leading to a 10% low-flow decrease. Contrasting discharge variations are pointed out depending on the location in the basin. In the western upper part of the basin, which undergoes an annual persistent increase in precipitation, high flow shows a 7% relative increase for the middle of the 21st century and the signal is enhanced for the end of the century (12%). By contrast, simulated precipitation decreases during the dry seasons over the southern, eastern and northern parts of the basin lead to significant low-flow decrease at several stations, especially in the Xingu River, where it reaches −50%, associated with a 9% reduction in the runoff coefficient. A 18% high-flow decrease is also found in this river. In the north, the low-flow decrease becomes higher toward the east: a 55% significant decrease in the eastern Branco River is associated with a 13% reduction in the runoff coefficient. The estimation of the streamflow elasticity to precipitation indicates that southern sub-basins (except for the mountainous Beni River), that have low runoff coefficients, will become more responsive to precipitation change (with a 5 to near 35
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Czech Academy of Sciences Publication Activity Database
Kašpar, Marek; Müller, Miloslav
2014-01-01
Roč. 138, March 2014 (2014), s. 205-212 ISSN 0169-8095 R&D Projects: GA ČR(CZ) GAP209/11/1990 Institutional support: RVO:68378289 Keywords : precipitation extreme * synoptic-scale cause * re-analysis * circulation anomaly Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 2.844, year: 2014 http://www.sciencedirect.com/science/article/pii/S0169809513003372
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Yin, Yixing; Chen, Haishan; Xu, Chongyu; Xu, Wucheng; Chen, Changchun
2014-05-01
The regionalization methods which 'trade space for time' by including several at-site data records in the frequency analysis are an efficient tool to improve the reliability of extreme quantile estimates. With the main aims of improving the understanding of the regional frequency of extreme precipitation and providing scientific and practical background and assistance in formulating the regional development strategies for water resources management in one of the most developed and flood-prone regions in China, the Yangtze River Delta (YRD) region, in this paper, L-moment-based index-flood (LMIF) method, one of the popular regionalization methods, is used in the regional frequency analysis of extreme precipitation; attention was paid to inter-site dependence and its influence on the accuracy of quantile estimates, which hasn't been considered for most of the studies using LMIF method. Extensive data screening of stationarity, serial dependence and inter-site dependence was carried out first. The entire YRD region was then categorized into four homogeneous regions through cluster analysis and homogenous analysis. Based on goodness-of-fit statistic and L-moment ratio diagrams, Generalized extreme-value (GEV) and Generalized Normal (GNO) distributions were identified as the best-fit distributions for most of the sub regions. Estimated quantiles for each region were further obtained. Monte-Carlo simulation was used to evaluate the accuracy of the quantile estimates taking inter-site dependence into consideration. The results showed that the root mean square errors (RMSEs) were bigger and the 90% error bounds were wider with inter-site dependence than those with no inter-site dependence for both the regional growth curve and quantile curve. The spatial patterns of extreme precipitation with return period of 100 years were obtained which indicated that there are two regions with the highest precipitation extremes (southeastern coastal area of Zhejiang Province and the
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International Nuclear Information System (INIS)
Bolek, Timothy W.; Marcus, Robert B.; Mendenhall, Nancy Price; Scarborough, Mark T.; Graham-Pole, John
1996-01-01
Purpose: Radiotherapy (RT) has been the predominant local treatment for Ewing's sarcoma of bone at the University of Florida. Twice-daily hyperfractionated RT was initiated in 1982 to improve local control and functional outcome. This retrospective review compares the results of once-daily vs. twice-daily RT in patients with primary Ewing's sarcoma of an extremity, with emphasis on functional outcome. Methods and Materials: Between June 1971 and January 1990, 37 patients were treated at the University of Florida for nonmetastatic Ewing's sarcoma of bone with a primary lesion in an extremity. Three patients underwent amputation. Of 34 patients treated with RT, 31 had RT alone and 3 had a combination of RT and local excision. Before 1982, 14 patients received once-daily RT; since 1982, 17 patients have received twice-daily RT. Doses of once-daily RT varied from 47 to 61 Gy at 1.8-2 Gy per fraction. Doses of twice-daily RT varied, depending on the response of the soft-tissue component of the tumor to chemotherapy, and ranged from 50.4 to 60 Gy at 1.2 Gy per fraction. Some patients in the twice-daily RT group also received total body irradiation 1-3 months after local RT as part of a conditioning regimen before marrow-ablative therapy with stem cell rescue. They received either 8 Gy in two once-daily fractions or 12 Gy in six twice-daily fractions. The six patients who received surgery were excluded from local control analysis. Local control rates were calculated using the Kaplan-Meier (actuarial) method. Fifteen patients had a formal functional evaluation. Results: In the 31 patients treated with RT alone, the actuarial local control rate at 5 years was 81% for patients treated twice daily and 77% for those treated once daily (p = NS). No posttreatment pathologic fractures occurred in patients treated twice daily, whereas five fractures occurred in those treated once daily (p = 0.01). On functional evaluation, less loss in range of motion (15 deg. vs. 28 deg. of loss
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Extreme climate in China. Facts, simulation and projection
Energy Technology Data Exchange (ETDEWEB)
Wang, Hui-Jun; Sun, Jian-Qi; Chen, Huo-Po; Zhu, Ya-Li; Zhang, Ying; Jiang, Da-Bang; Lang, Xian-Mei; Fan, Ke; Yu, En-Tao [Chinese Academy of Sciences, Beijing (China). Inst. of Atmospheric Physics; Yang, Song [NOAA Climate Prediction Center, Camp Springs, MD (United States)
2012-06-15
In this paper, studies on extreme climate in China including extreme temperature and precipitation, dust weather activity, tropical cyclone activity, intense snowfall and cold surge activity, floods, and droughts are reviewed based on the peer-reviewed publications in recent decades. The review is focused first on the climatological features, variability, and trends in the past half century and then on simulations and projections based on global and regional climate models. As the annual mean surface air temperature (SAT) increased throughout China, heat wave intensity and frequency overall increased in the past half century, with a large rate after the 1980s. The daily or yearly minimum SAT increased more significantly than the mean or maximum SAT. The long-term change in precipitation is predominantly characterized by the so-called southern flood and northern drought pattern in eastern China and by the overall increase over Northwest China. The interdecadal variation of monsoon, represented by the monsoon weakening in the end of 1970s, is largely responsible for this change in mean precipitation. Precipitation-related extreme events (e.g., heavy rainfall and intense snowfall) have become more frequent and intense generally over China in the recent years, with large spatial features. Dust weather activity, however, has become less frequent over northern China in the recent years, as result of weakened cold surge activity, reinforced precipitation, and improved vegetation condition. State-of-the-art climate models are capable of reproducing some features of the mean climate and extreme climate events. However, discrepancies among models in simulating and projecting the mean and extreme climate are also demonstrated by many recent studies. Regional models with higher resolutions often perform better than global models. To predict and project climate variations and extremes, many new approaches and schemes based on dynamical models, statistical methods, or their
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Black, R. X.
2017-12-01
We summarize results from a project focusing on regional temperature and precipitation extremes over the continental United States. Our project introduces a new framework for evaluating these extremes emphasizing their (a) large-scale organization, (b) underlying physical sources (including remote-excitation and scale-interaction) and (c) representation in climate models. Results to be reported include the synoptic-dynamic behavior, seasonality and secular variability of cold waves, dry spells and heavy rainfall events in the observational record. We also study how the characteristics of such extremes are systematically related to Northern Hemisphere planetary wave structures and thus planetary- and hemispheric-scale forcing (e.g., those associated with major El Nino events and Arctic sea ice change). The underlying physics of event onset are diagnostically quantified for different categories of events. Finally, the representation of these extremes in historical coupled climate model simulations is studied and the origins of model biases are traced using new metrics designed to assess the large-scale atmospheric forcing of local extremes.
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Xu, Ying; Gao, Xuejie; Giorgi, Filippo; Zhou, Botao; Shi, Ying; Wu, Jie; Zhang, Yongxiang
2018-04-01
Future changes in the 50-yr return level for temperature and precipitation extremes over mainland China are investigated based on a CMIP5 multi-model ensemble for RCP2.6, RCP4.5 and RCP8.5 scenarios. The following indices are analyzed: TXx and TNn (the annual maximum and minimum of daily maximum and minimum surface temperature), RX5day (the annual maximum consecutive 5-day precipitation) and CDD (maximum annual number of consecutive dry days). After first validating the model performance, future changes in the 50-yr return values and return periods for these indices are investigated along with the inter-model spread. Multi-model median changes show an increase in the 50-yr return values of TXx and a decrease for TNn, more specifically, by the end of the 21st century under RCP8.5, the present day 50-yr return period of warm events is reduced to 1.2 yr, while extreme cold events over the country are projected to essentially disappear. A general increase in RX5day 50-yr return values is found in the future. By the end of the 21st century under RCP8.5, events of the present RX5day 50-yr return period are projected to reduce to China. Changes in CDD-50 show a dipole pattern over China, with a decrease in the values and longer return periods in the north, and vice versa in the south. Our study also highlights the need for further improvements in the representation of extreme events in climate models to assess the future risks and engineering design related to large-scale infrastructure in China.
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The use of normalized climatological anomalies to rank precipitation events in the Iberian Peninsula
Ramos, Alexandre M.; Trigo, Ricardo M.; Liberato, Margarida L. R.
2013-04-01
Extreme precipitation events in the Iberian Peninsula during winter months have major socio-economic impacts such as flooding, landslides, extensive property damage and life losses, and are usually associated to deep low pressure systems with Atlantic origin, although some extreme events in summer/autumn months are fed by the Mediterranean. Quite often these events are evaluated on a casuistic base and with relatively few stations. An objective method for ranking daily precipitation events is presented based on the extensive use of the most comprehensive database of daily precipitation available for the Iberian Peninsula (IB02) and spanning from 1950 to 2003, with a resolution of 0.2° (approximately 16 x 22 km at latitude 40°N), for a total of 1673 pixels. This database is based on a dense network of rain gauges, combining two national data sets, 'Spain02' for peninsular Spain and Balearic islands (Herrera et al., 2012), and 'PT02' for mainland Portugal (Belo-Pereira et al., 2011), with a total of more than two thousand stations over Spain and four hundred stations over Portugal, all quality-controlled and homogenized. The daily precipitation data from 1950 to 2003 are compared with a 30-year (1961-90) precipitation climatology to achieve a daily normalized departure from the climatology. The magnitude of an event is given daily by an index that is obtained after multiplying 1) the area (in percentage) that has precipitation anomalies above two standard deviations by 2) the mean values of these anomalies over this area. With this criterion we are able to evaluate not only the spatial extent of the precipitation events but also their spatially integrated intensity. In addition, to stress out the hydrological responses to precipitation, rankings taking into account the sum of the normalized anomalies over different time periods (3 days, 5 days and 10 days) were also computed. Here different precipitation rankings will be presented considering the entire Iberian
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DEFF Research Database (Denmark)
Sunyer Pinya, Maria Antonia; Sørup, Hjalte Jomo Danielsen; Christensen, Ole Bøssing
2013-01-01
datasets, the RCMs are ranked according to their performance using two different metrics. These are based on the error in representing the indices and the spatial correlation. In comparison to the mean, extreme precipitation indices are highly dependent on the spatial resolution of the observations...
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Christiansen, Daniel E.
2012-01-01
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted a study to examine techniques for estimation of daily streamflows using hydrological models and statistical methods. This report focuses on the use of a hydrologic model, the U.S. Geological Survey's Precipitation-Runoff Modeling System, to estimate daily streamflows at gaged and ungaged locations. The Precipitation-Runoff Modeling System is a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The Cedar River Basin was selected to construct a Precipitation-Runoff Modeling System model that simulates the period from January 1, 2000, to December 31, 2010. The calibration period was from January 1, 2000, to December 31, 2004, and the validation periods were from January 1, 2005, to December 31, 2010 and January 1, 2000 to December 31, 2010. A Geographic Information System tool was used to delineate the Cedar River Basin and subbasins for the Precipitation-Runoff Modeling System model and to derive parameters based on the physical geographical features. Calibration of the Precipitation-Runoff Modeling System model was completed using a U.S. Geological Survey calibration software tool. The main objective of the calibration was to match the daily streamflow simulated by the Precipitation-Runoff Modeling System model with streamflow measured at U.S. Geological Survey streamflow gages. The Cedar River Basin daily streamflow model performed with a Nash-Sutcliffe efficiency ranged from 0.82 to 0.33 during the calibration period, and a Nash-Sutcliffe efficiency ranged from 0.77 to -0.04 during the validation period. The Cedar River Basin model is meeting the criteria of greater than 0.50 Nash-Sutcliffe and is a good fit for streamflow conditions for the calibration period at all but one location, Austin, Minnesota
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Lee, Taesam
2018-05-01
Multisite stochastic simulations of daily precipitation have been widely employed in hydrologic analyses for climate change assessment and agricultural model inputs. Recently, a copula model with a gamma marginal distribution has become one of the common approaches for simulating precipitation at multiple sites. Here, we tested the correlation structure of the copula modeling. The results indicate that there is a significant underestimation of the correlation in the simulated data compared to the observed data. Therefore, we proposed an indirect method for estimating the cross-correlations when simulating precipitation at multiple stations. We used the full relationship between the correlation of the observed data and the normally transformed data. Although this indirect method offers certain improvements in preserving the cross-correlations between sites in the original domain, the method was not reliable in application. Therefore, we further improved a simulation-based method (SBM) that was developed to model the multisite precipitation occurrence. The SBM preserved well the cross-correlations of the original domain. The SBM method provides around 0.2 better cross-correlation than the direct method and around 0.1 degree better than the indirect method. The three models were applied to the stations in the Nakdong River basin, and the SBM was the best alternative for reproducing the historical cross-correlation. The direct method significantly underestimates the correlations among the observed data, and the indirect method appeared to be unreliable.
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Ward, Ray; Purnell, Sarah; Ebdon, James; Nnane, Daniel; Taylor, Huw
2013-04-01
The Water Framework Directive (WFD) regulates surface water quality standards in the European Union (EU). The Directive call for the identification and management of point and diffuse sources of pollution and requires the establishment of a 'programme of measures' for identified river basin districts, in order to achieve a "good status" by 2015. The hygienic quality of water is normally monitored using faecal indicator organisms (FIO), such as Escherichia coli, which indicate a potential risk to public health from human waterborne pathogens. Environmental factors influence the transmission of these pathogens and indicator organisms, and statistically significant relationships have been found between rainfall and outbreaks of waterborne disease. Climate change has been predicted to lead to an increase in severe weather events in many parts of Europe, including an increase in the frequency of extreme rainfall events. This in turn is likely to lead to an increase in incidents of human waterborne disease in Europe, unless measures are taken to predict and mitigate for such events. This study investigates a variety of environmental factors that influence the concentration of FIO in surface waters receiving faecal contamination from a variety of sources. Levels of FIO, including Escherichia coli, intestinal enterococci, somatic coliphage and GB124 (a human-specific microbial source tracking marker), were monitored in the Sussex Ouse catchment in Southeast England over a period of 26 months. These data were combined with geoinformatic environmental data within a GIS to map faecal contamination within the river. Previously, precipitation and soil erosion have been identified as major factors that can influence the concentration of these faecal markers, and studies have shown that slope, soil type and vegetation influence both the mechanisms and the rate by which erosion occurs in river catchments. Of the environmental variables studied, extreme precipitation was found to
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Ramos, A. M.; Trigo, R. M.; Lorenzo, M. N.; Vaquero, J. M.; Gallego, M. C.; Valente, M. A.; Gimeno, L.
2009-04-01
In recent years a large number of automated classifications of atmospheric circulation patterns have been published covering the entire European continent or specific sub-regions (Huth et al., 2008). This generalized use of objective classifications results from their relatively straightforward computation but crucially from their capacity to provide simple description of typical synoptic conditions as well as their climatic and environmental impact. For this purpose, the vast majority of authors has employed the Reanalyses datasets, namely from either NCEP/NCAR or ECMWF projects. However, both these widely used datasets suffer from important caveats, namely their restricted temporal coverage, that is limited to the last six decades (NCEP/NCAR since 1948 and ECMWF since 1958). This limitation has been partially mitigated by the recent availability of continuous daily mean sea level pressure obtained within the European project EMULATE, that extended the historic records over the extra-tropical Atlantic and Europe (70°-25° N by 70° W-50° E), for the period 1850 to the present (Ansell, T. J. et al. 2006). Here we have used the extended EMULATE dataset to construct an automated version of the Lamb Weather type (WTs) classification scheme (Jones et al 1993) adapted for the center of the Iberian Peninsula. We have identified 10 basic WTs (Cyclonic, Anticyclonic and 8 directional types) following a similar methodology to that previously adopted by Trigo and DaCamara, 2000 (for Portugal) and Lorenzo et al. 2008 (for Galicia, northwestern Iberia). We have evaluated trends of monthly/seasonal frequency of each WT for the entire period and several shorter periods. Finally, we use the long-term precipitation time series from Lisbon (recently digitized) and Cadiz (southern Spain) to evaluate, the impact of each WT on the precipitation regime. It is shown that the Anticyclonic (A) type, although being the most frequent class in winter, gives a rather small contribution to
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Acharya, N.; Frei, A.; Owens, E. M.; Chen, J.
2015-12-01
Watersheds located in the Catskill Mountains area, part of the eastern plateau climate region of New York, contributes about 90% of New York City's municipal water supply, serving 9 million New Yorkers with about 1.2 billion gallons of clean drinking water each day. The New York City Department of Environmental Protection has an ongoing series of studies to assess the potential impacts of climate change on the availability of high quality water in this water supply system. Recent studies identify increasing trends in total precipitation and in the frequency of extreme precipitation events in this region. The objectives of the present study are: to analyze the probabilistic structure of extreme precipitation based on historical observations: and to evaluate the abilities of stochastic weather generators (WG), statistical models that produce synthetic weather time series based on observed statistical properties at a particular location, to simulate the statistical properties of extreme precipitation events over this region. The generalized extreme value distribution (GEV) has been applied to the annual block maxima of precipitation for 60 years (1950 to 2009) observed data in order to estimate the events with return periods of 50, 75, and 100 years. These results were then used to evaluate a total of 13 WGs were : 12 parametric WGs including all combinations of three different orders of Markov chain (MC) models (1st , 2nd and 3rd) and four different probability distributions (exponential, gamma, skewed normal and mixed exponential); and one semi parametric WG based on k-nearest neighbor bootstrapping. Preliminary results suggest that three-parameter (skewed normal and mixed exponential distribution) and semi-parametric (k-nearest neighbor bootstrapping) WGs are more consistent with observations. It is also found that first order MC models perform as well as second or third order MC models.
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Directory of Open Access Journals (Sweden)
Ricardo Machado Trigo
2014-04-01
Full Text Available The first week of December 1876 was marked by extreme weather conditions that affected the south-western sector of the Iberian Peninsula, leading to an all-time record flow in two large international rivers. As a direct consequence, several Portuguese and Spanish towns and villages located in the banks of both rivers suffered serious flood damage on 7 December 1876. These unusual floods were amplified by the preceding particularly autumn wet months, with October 1876 presenting extremely high precipitation anomalies for all western Iberia stations. Two recently digitised stations in Portugal (Lisbon and Evora, present a peak value on 5 December 1876. Furthermore, the values of precipitation registered between 28 November and 7 December were so remarkable that, the episode of 1876 still corresponds to the maximum average daily precipitation values for temporal scales between 2 and 10 days. Using several different data sources, such as historical newspapers of that time, meteorological data recently digitised from several stations in Portugal and Spain and the recently available 20th Century Reanalysis, we provide a detailed analysis on the socio-economic impacts, precipitation values and the atmospheric circulation conditions associated with this event. The atmospheric circulation during these months was assessed at the monthly, daily and sub-daily scales. All months considered present an intense negative NAO index value, with November 1876 corresponding to the lowest NAO value on record since 1865. We have also computed a multivariable analysis of surface and upper air fields in order to provide some enlightening into the evolution of the synoptic conditions in the week prior to the floods. These events resulted from the continuous pouring of precipitation registered between 28 November and 7 December, due to the consecutive passage of Atlantic low-pressure systems fuelled by the presence of an atmospheric-river tropical moisture flow over
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Analyses of Observed and Anticipated Changes in Extreme Climate Events in the Northwest Himalaya
Directory of Open Access Journals (Sweden)
Dharmaveer Singh
2016-02-01
Full Text Available In this study, past (1970-2005 as well as future long term (2011-2099 trends in various extreme events of temperature and precipitation have been investigated over selected hydro-meteorological stations in the Sutlej river basin. The ensembles of two Coupled Model Intercomparison Project (CMIP3 models: third generation Canadian Coupled Global Climate Model and Hadley Centre Coupled Model have been used for simulation of future daily time series of temperature (maximum and minimum and precipitation under A2 emission scenario. Large scale atmospheric variables of both models and National Centre for Environmental Prediction/National Centre for Atmospheric Research reanalysis data sets have been downscaled using statistical downscaling technique at individual stations. A total number of 25 extreme indices of temperature (14 and precipitation (11 as specified by the Expert Team of the World Meteorological Organization and Climate Variability and Predictability are derived for the past and future periods. Trends in extreme indices are detected over time using the modified Mann-Kendall test method. The stations which have shown either decrease or no change in hot extreme events (i.e., maximum TMax, warm days, warm nights, maximum TMin, tropical nights, summer days and warm spell duration indicators for 1970–2005 and increase in cold extreme events (cool days, cool nights, frost days and cold spell duration indicators are predicted to increase and decrease respectively in the future. In addition, an increase in frequency and intensity of extreme precipitation events is also predicted.
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Performance Assessment of Multi-Source Weighted-Ensemble Precipitation (MSWEP Product over India
Directory of Open Access Journals (Sweden)
Akhilesh S. Nair
2017-01-01
Full Text Available Error characterization is vital for the advancement of precipitation algorithms, the evaluation of numerical model outputs, and their integration in various hydro-meteorological applications. The Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA has been a benchmark for successive Global Precipitation Measurement (GPM based products. This has given way to the evolution of many multi-satellite precipitation products. This study evaluates the performance of the newly released multi-satellite Multi-Source Weighted-Ensemble Precipitation (MSWEP product, whose temporal variability was determined based on several data products including TMPA 3B42 RT. The evaluation was conducted over India with respect to the IMD-gauge-based rainfall for pre-monsoon, monsoon, and post monsoon seasons at daily scale for a 35-year (1979–2013 period. The rainfall climatology is examined over India and over four geographical extents within India known to be subject to uniform rainfall. The performance evaluation of rainfall time series was carried out. In addition to this, the performance of the product over different rainfall classes was evaluated along with the contribution of each class to the total rainfall. Further, seasonal evaluation of the MSWEP products was based on the categorical and volumetric indices from the contingency table. Upon evaluation it was observed that the MSWEP products show large errors in detecting the higher quantiles of rainfall (>75th and > 95th quantiles. The MSWEP precipitation product available at a 0.25° × 0.25° spatial resolution and daily temporal resolution matched well with the daily IMD rainfall over India. Overall results suggest that a suitable region and season-dependent bias correction is essential before its integration in hydrological applications. While the MSWEP was observed to perform well for daily rainfall, it suffered from poor detection capabilities for higher quantiles, making
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Santos, J. A.; Mendes, A. R.
2009-09-01
The occurrence of severe precipitation deficits in the Iberian Peninsula has major socio-economic and environmental impacts. Several previous studies emphasized the leading role of the large-scale atmospheric flow in the occurrence of long periods with significant precipitation lacks. However, due to the high complexity of the Iberian orography, the sensitivity of the local rain-generating mechanisms to large-scale anomalies is remarkably different from region to region. A principal component analysis of the annual precipitation amounts recorded at a network of meteorological stations over the entire peninsula for the period 1961-1998 corroborates this heterogeneity. With particular significance is the contrast between the western and eastern sectors of the peninsula. In fact, taking into account earlier studies, precipitation in western Iberia is strongly related to large-scale atmospheric patterns over the North Atlantic. On the contrary, precipitation over eastern Iberia is much less associated with these large-scale forcing patterns, but much more linked to local/regional mechanisms. In order to test these hypotheses, eight meteorological stations, four in the western half (Porto, Bragança, Lisboa and Beja) and four in the eastern half (Barcelona, Valencia, Tortosa and Zaragoza) of Iberia are selected taking into account, firstly, the geographical location, and secondly the quality and homogeneity of the respective time series. A set of extremely wet/dry seasons was subsequently chosen for each weather station separately, taking into account the 90th percentile of the respective empirical distributions. The analysis of the different atmospheric fields (precipitation rates, convective precipitation, precipitable water, specific humidity, relative humidity, surface temperature, sea surface pressure, geopotential heights, wind components and vorticity at different isobaric levels) is undertaken by using data from the National Centers for Environmental Prediction
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Spatio-temporal variability of several eco-precipitation indicators in China
Guo, B. B.; Zhang, J.; Wang, F.
2016-12-01
Climate change is expected to have large impacts on the eco-hydrological processes. Precipitation as one of the most important meteorological factors is a significant parameter in ecohydrology. Many studies and precipitation indexes focused on the long-term precipitation variability have been put forward. However, these former studies did not consider the vegetation response and these indexes could not reflect it efficiently. Eco-precipitation indicators reflecting the features and patterns of precipitations and serving as significant input parameters of eco-hydrological models are of paramount significance to the studies of these models. Therefore we proposed 4 important eco-precipitation indicators—Precipitation Variability Index (PVI), Precipitation Occurrence Rate (λ), Mean Precipitation Depth (1/θ) and Annual Precipitation (AP). The PVI index depicts the precipitation variability with a value of zero for perfectly uniform and increases as precipitation events become more sporadic. The λ, 1/θ and AP depict the precipitation frequency, intensity and annual amount, respectively. With large precipitation and vegetation discrepancies, China is selected as a study area. Firstly, these indicators are calculated separately with 55-years (1961-2015) daily precipitation time-series from 693 weather stations in China. Then, the temporal trend is analyzed through Mann-Kendall (MK) test and parametric t-test in annual time scale. Furthermore, the spatial distribution is analyzed through the spatial interpolation tools ANUsplin. The result shows that: (1) 1/θ increased significantly (4.59cm/10yr) while λ decreased significantly (1.54 days/10yr), which means there is an increasing trend of extreme precipitation events; (2)there is a significant downward trend of PVI, which means the rhythm of precipitation has a uniform and concentrated trend; (3) AP increased insignificantly (0.57mm/10yr); and (4)the MK test of these indicators shows that there is saltation of
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Deng, Ziwang; Liu, Jinliang; Qiu, Xin; Zhou, Xiaolan; Zhu, Huaiping
2017-10-01
A novel method for daily temperature and precipitation downscaling is proposed in this study which combines the Ensemble Optimal Interpolation (EnOI) and bias correction techniques. For downscaling temperature, the day to day seasonal cycle of high resolution temperature of the NCEP climate forecast system reanalysis (CFSR) is used as background state. An enlarged ensemble of daily temperature anomaly relative to this seasonal cycle and information from global climate models (GCMs) are used to construct a gain matrix for each calendar day. Consequently, the relationship between large and local-scale processes represented by the gain matrix will change accordingly. The gain matrix contains information of realistic spatial correlation of temperature between different CFSR grid points, between CFSR grid points and GCM grid points, and between different GCM grid points. Therefore, this downscaling method keeps spatial consistency and reflects the interaction between local geographic and atmospheric conditions. Maximum and minimum temperatures are downscaled using the same method. For precipitation, because of the non-Gaussianity issue, a logarithmic transformation is used to daily total precipitation prior to conducting downscaling. Cross validation and independent data validation are used to evaluate this algorithm. Finally, data from a 29-member ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5) GCMs are downscaled to CFSR grid points in Ontario for the period from 1981 to 2100. The results show that this method is capable of generating high resolution details without changing large scale characteristics. It results in much lower absolute errors in local scale details at most grid points than simple spatial downscaling methods. Biases in the downscaled data inherited from GCMs are corrected with a linear method for temperatures and distribution mapping for precipitation. The downscaled ensemble projects significant warming with amplitudes of 3
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Daily and Sub-daily Precipitation for the Former USSR
National Oceanic and Atmospheric Administration, Department of Commerce — This dataset is a compilation of in situ daily and hourly meteorological observations for the former USSR initially obtained within the framework of several joint...
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Heat balance structure of canopies at extreme precipitation in view of long-term records
International Nuclear Information System (INIS)
Bubnowska, J.; Gąsiorek, E.; Łabędzki, L.; Musiał, E.
2005-01-01
Increasing frequency of extreme weather conditions is attributed to the global variations in climate. Heat balance of substrate is one of the processes affecting the climate. Variations of heat balance in spring wheat during the growing seasons (April-August) and in potatoes during the growing seasons (May-September) with maximal and minimal precipitation are confronted here with long term changes of the balance. Two regions Wroclaw-Swojec (1964-2000) and Bydgoszcz (1945-2003) were involved in the study [pl
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Development of Sub-Daily Intensity Duration Frequency (IDF) Curves for Major Urban Areas in India
Ali, H.; Mishra, V.
2014-12-01
Extreme precipitation events disrupt urban transportation and cause enormous damage to infrastructure. Urban areas are fast responding catchments due to significant impervious surface. Stormwater designs based on daily rainfall data provide inadequate information. We, therefore, develop intensity-duration-frequency curves using sub-daily (1 hour to 12 hour) rainfall data for 57 major urban areas in India. While rain gage stations data from urban areas are most suitable, but stations are unevenly distributed and their data have gaps and inconsistencies. Therefore, we used hourly rainfall data from the Modern Era Retrospective-analysis for Research and Applications (MERRA), which provides a long term data (1979 onwards). Since reanalysis products have uncertainty associated with them we need to enhance their accuracy before their application. We compared daily rain gage station data obtained from Global Surface Summary of Day Data (GSOD) available for 65 stations for the period of 2000-2010 with gridded daily rainfall data provided by Indian Meteorological Department (IMD). 3-hourly data from NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) were aggregated to daily for comparison with GSOD station data . TMPA is found to be best correlated with GSOD data. We used TMPA data to correct MERRA's hourly precipitation, which were applied to develop IDF curves. We compared results with IDF curves from empirical methods and found substantial disparities in the existing stormwater designs in India.
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Attribution of extreme precipitation in the lower reaches of the Yangtze River during May 2016
Li, Chunxiang; Tian, Qinhua; Yu, Rong; Zhou, Baiquan; Xia, Jiangjiang; Burke, Claire; Dong, Buwen; Tett, Simon F. B.; Freychet, Nicolas; Lott, Fraser; Ciavarella, Andrew
2018-01-01
May 2016 was the third wettest May on record since 1961 over central eastern China based on station observations, with total monthly rainfall 40% more than the climatological mean for 1961-2013. Accompanying disasters such as waterlogging, landslides and debris flow struck part of the lower reaches of the Yangtze River. Causal influence of anthropogenic forcings on this event is investigated using the newly updated Met Office Hadley Centre system for attribution of extreme weather and climate events. Results indicate that there is a significant increase in May 2016 rainfall in model simulations relative to the climatological period, but this increase is largely attributable to natural variability. El Niño years have been found to be correlated with extreme rainfall in the Yangtze River region in previous studies—the strong El Niño of 2015-2016 may account for the extreme precipitation event in 2016. However, on smaller spatial scales we find that anthropogenic forcing has likely played a role in increasing the risk of extreme rainfall to the north of the Yangtze and decreasing it to the south.
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Directory of Open Access Journals (Sweden)
Ali A. Assani
2016-01-01
Full Text Available We compared the spatiotemporal variability of temperatures and precipitation with that of the magnitude and timing of maximum daily spring flows in the geographically adjacent L’Assomption River (agricultural and Matawin River (forested watersheds during the period from 1932 to 2013. With regard to spatial variability, fall, winter, and spring temperatures as well as total precipitation are higher in the agricultural watershed than in the forested one. The magnitude of maximum daily spring flows is also higher in the first watershed as compared with the second, owing to substantial runoff, given that the amount of snow that gives rise to these flows is not significantly different in the two watersheds. These flows occur early in the season in the agricultural watershed because of the relatively high temperatures. With regard to temporal variability, minimum temperatures increased over time in both watersheds. Maximum temperatures in the fall only increased in the agricultural watershed. The amount of spring rain increased over time in both watersheds, whereas total precipitation increased significantly in the agricultural watershed only. However, the amount of snow decreased in the forested watershed. The magnitude of maximum daily spring flows increased over time in the forested watershed.
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Extreme precipitation and floods in the Iberian Peninsula and its socio-economic impacts
Ramos, A. M.; Pereira, S.; Trigo, R. M.; Zêzere, J. L.
2017-12-01
Extreme precipitation events in the Iberian Peninsula can induce floods and landslides that have often major socio-economic impacts. The DISASTER database gathered the basic information on past floods and landslides that caused social consequences in Portugal for the period 1865-2015. This database was built under the assumption that social consequences of floods and landslides are sufficient relevant to be reported by newspapers, that provide the data source. Three extreme historical events were analysed in detail taking into account their associated wide socio-economic impacts. The December 1876 record precipitation and flood event leading to an all-time record flow in two large international rivers (Tagus and Guadiana). As a direct consequence, several Portuguese and Spanish towns and villages located in the banks of both rivers suffered serious flood damage on 7 December 1876. The 20-28 December 1909 event recorded the highest number of flood and landslide cases that occurred in Portugal in the period 1865-2015, having triggered the highest floods in 200 years at the Douro river's mouth and causing 89 fatalities in both Portugal and Spain northern regions. More recently the deadliest flash-flooding event affecting Portugal since, at least, the early 19th century, took place on the 25 and 26 November 1967 causing more than 500 fatalities in the Lisbon region. We provide a detailed analysis of each of these events, including their human impacts, precipitation analyses based on historical datasets and the associated atmospheric circulation conditions from reanalysis datasets. Acknowledgements: This work was supported by the project FORLAND - Hydrogeomorphologic risk in Portugal: driving forces and application for land use planning [PTDC / ATPGEO / 1660/2014] funded by the Portuguese Foundation for Science and Technology (FCT), Portugal. A. M. Ramos was also supported by a FCT postdoctoral grant (FCT/DFRH/ SFRH/BPD/84328/2012). The financial support for attending
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Energy Technology Data Exchange (ETDEWEB)
Jonas, Martin; Staeger, Tim; Schoenwiese, Christian-Dietrich [Frankfurt Univ. (Germany). Inst. fuer Atmosphaere und Umwelt, Arbeitsgruppe Klimaforschung
2005-08-15
The study on the probability of occurrence of extreme weather events in Germany is based on compiled data covering ground-level temperature, precipitation and wind during the time period 1901 to 2000. The data processing approach is based on two methodologies: a time-gliding extreme value analysis and a structure-oriented time-series analysis. The results show a significant increase of very hot months and at the same time a decrease of extreme cold months within the 20th century. In the time period after 1951 the probability of very high daily maximum temperatures increased for all seasons. Concerning the precipitation the increase of extreme values and higher variabilities are observed for the winter period. The results concerning the wind are not so clear. Summarizing the extreme behavior of temperature and precipitation has shown strong variations during the last century.
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Combined Effects of Synoptic-Scale Teleconnection Patterns on Summer Precipitation in Southern China
Directory of Open Access Journals (Sweden)
Chao Wang
2018-04-01
Full Text Available Using ERA-Interim daily reanalysis and precipitation data, the combined effects of East Asia-Pacific (EAP and Silk Road (SR teleconnection patterns on summer precipitation in Southern China were investigated on synoptic to sub-monthly timescales. Combined EAP and SR patterns lead to more persistent and extreme precipitation in the Yangtze River Valley (YRV and exhibit an obvious zonal advance between the South Asia High (SAH and Western Pacific Subtropical High (WPSH prior to its onset. During typical combined events, an overlap between the SAH and WPSH remains in a favorable position for Persistent Extreme Precipitation (PEP. Furthermore, SR-induced acceleration of the westerly jet stream and extra positive vorticity advection provide persistent upper-level divergence for YRV precipitation. An anomalous EAP-related cyclone/anticyclone pair over East Asia induces enhanced low-level southwesterlies to the northern anticyclone flank and northerlies from the mid-latitudes, advecting anomalously abundant moisture toward the YRV, resulting in clear moisture convergence. Moreover, the strong ascent of warmer/moister air along a quasi-stationary front may be crucial for PEP. During decay, the SAH and WPSH diverge from each other and retreat to their normal positions, and the strong ascent of warmer/moister air rapidly weakens to dissipation, terminating PEP in the YRV.
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Nunes, A.; Gomes, G.; Ivanov, V. Y.
2016-12-01
Frequently found in southeastern South America during the warm season from October through May, strong and localized precipitation maxima are usually associated with the presence of mesoscale convective complexes (MCCs) travelling across the region. Flashfloods and landslides can be caused by these extremes in precipitation, with damages to the local communities. Heavily populated, southeastern South America hosts many agricultural activities and hydroelectric production. It encompasses one of the most important river basins in South America, the La Plata River Basin. Therefore, insufficient precipitation is equally prejudicial to the region socio-economic activities. MCCs are originated in the warm season of many regions of the world, however South American MCCs are related to the most severe thunderstorms, and have significantly contributed to the precipitation regime. We used the hourly outputs of Satellite-enhanced Regional Downscaling for Applied Studies (SRDAS), developed at the Federal University of Rio de Janeiro in Brazil, in the analysis of the dynamics and physical characteristics of MCCs in South America. SRDAS is the 25-km resolution downscaling of a global reanalysis available from January 1998 through December 2010. The Regional Spectral Model is the SRDAS atmospheric component and assimilates satellite-based precipitation estimates from the NOAA/Climate Prediction Center MORPHing technique global precipitation analyses. In this study, the SRDAS atmospheric and land-surface variables, global reanalysis products, infrared satellite imagery, and the physical retrievals from the Atmospheric Infrared Sounder (AIRS), on board of the NASA's Aqua satellite, were used in the evaluation of the MCCs developed in southeastern South America from 2008 and 2010. Low-level circulations and vertical profiles were analyzed together to establish the relevance of the moisture transport in connection with the upper-troposphere dynamics to the development of those MCCs.
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The variability of temperature extremes has been the focus of attention during the past few decades, and may exert a great influence on the global hydrologic cycle and energy balance through thermal forcing. Based on daily minimum and maximum temperature observed by the China Meteorological Administ...
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Prat, O. P.; Nelson, B. R.
2013-12-01
We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme
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International Nuclear Information System (INIS)
Van Boxel, John H
2001-01-01
Precipitation is one of the most, if not the most important climate parameter In most studies on climate change the emphasis is on temperature and sea level rise. Often too little attention is given to precipitation. For a large part this is due to the large spatial en temporal variability of precipitation, which makes the detection of changes difficult. This paper describes methods to detect changes in precipitation. In order to arrive at statistically significant changes one must use long time series and spatial averages containing the information from several stations. In the Netherlands the average yearly precipitation increased by 11% during the 20th century .In the temperate latitudes on the Northern Hemisphere (40-60QN) the average increase was about 7% over the 20th century and the globally averaged precipitation increased by about 3%. During the 20th century 38% of the land surface of the earth became wetter, 42% experienced little change (less than 5% change) and 20% became dryer. More important than the average precipitation is the occurrence of extremes. In the Netherlands there is a tendency to more extreme precipitations, whereas the occurrence of relatively dry months has not changed. Also in many other countries increases in heavy precipitation events are observed. All climate models predict a further increase of mean global precipitation if the carbon dioxide concentration doubles. Nevertheless some areas get dryer, others have little change and consequently there are also areas where the increase is much more than the global average. On a regional scale however there are large differences between the models. Climate models do not yet provide adequate information on changes in extreme precipitations
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Choi, Y.; Shin, D. B.; Joh, M.
2015-12-01
Numerical simulations of precipitation depend to a large degree on the assumed cloud microphysics schemes representing the formation, growth and fallout of cloud droplets and ice crystals. Recent studies show that assumed cloud microphysics play a major role not only in forecasting precipitation, especially in cases of extreme precipitation events, but also in the quality of the passive microwave rainfall estimation. Evaluations of the various Weather Research Forecasting (WRF) model microphysics schemes in this study are based on a method that was originally developed to construct the a-priori databases of precipitation profiles and associated brightness temperatures (TBs) for precipitation retrievals. This methodology generates three-dimensional (3D) precipitation fields by matching the GPM dual frequency radar (DPR) reflectivity profiles with those calculated from cloud resolving model (CRM)-derived hydrometeor profiles. The method eventually provides 3D simulated precipitation fields over the DPR scan swaths. That is, atmospheric and hydrometeor profiles can be generated at each DPR pixel based on CRM and DPR reflectivity profiles. The generated raining systems over DPR observation fields can be applied to any radiometers that are unaccompanied with a radar for microwave radiative calculation with consideration of each sensor's channel and field of view. Assessment of the WRF model microphysics schemes for several typhoon cases in terms of emission and scattering signals of GMI will be discussed.
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GCMs-based spatiotemporal evolution of climate extremes during the 21st century in China
Li, Jianfeng; Zhang, Qiang; Chen, Yongqin David; Singh, Vijay P.
2013-10-01
Changes in the hydrological cycle being caused by human-induced global warming are triggering variations in observed spatiotemporal distributions of precipitation and temperature extremes, and hence in droughts and floods across China. Evaluation of future climate extremes based on General Circulation Models (GCMs) outputs will be of great importance in scientific management of water resources and agricultural activities. In this study, five precipitation extreme and five temperature extreme indices are defined. This study analyzes daily precipitation and temperature data for 1960-2005 from 529 stations in China and outputs of GCMs from the Coupled Model Intercomparison Project Phase 3 (CMIP3) and Phase 5 (CMIP5). Downscaling methods, based on QQ-plot and transfer functions, are used to downscale GCMs outputs to the site scale. Performances of GCMs in simulating climate extremes were evaluated using the Taylor diagram. Results showed that: (1) the multimodel CMIP5 ensemble performs the best in simulating observed extreme conditions; (2) precipitation processes are intensifying with increased frequency and intensity across entire China. The southwest China, however, is dominated by lengthening maximum consecutive dry days and also more heavy precipitation extremes; (3) warming processes continue with increasing warm nights, decreasing frost days, and lengthening heat waves during the 21st century; (4) changes in precipitation and temperature extremes exhibit larger changing magnitudes under RCP85 scenario; (5) for the evolution of changes in extremes, in most cases, the spatial pattern keeps the same, even though changing rates vary. In some cases, area with specific changing properties extends or shrinks gradually. The directions of trends may alter during the evolution; and (6) changes under RCP85 become more and more pronounced as time elapses. Under the peak-and-decline RCP26, changes in some cases do not decrease correspondingly during 2070-2099 even though the
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Hereford, Richard
2006-01-01
The software described here is used to process and analyze daily weather and surface-water data. The programs are refinements of earlier versions that include minor corrections and routines to calculate frequencies above a threshold on an annual or seasonal basis. Earlier versions of this software were used successfully to analyze historical precipitation patterns of the Mojave Desert and the southern Colorado Plateau regions, ecosystem response to climate variation, and variation of sediment-runoff frequency related to climate (Hereford and others, 2003; 2004; in press; Griffiths and others, 2006). The main program described here (Day_Cli_Ann_v5.3) uses daily data to develop a time series of various statistics for a user specified accounting period such as a year or season. The statistics include averages and totals, but the emphasis is on the frequency of occurrence in days of relatively rare weather or runoff events. These statistics are indices of climate variation; for a discussion of climate indices, see the Climate Research Unit website of the University of East Anglia (http://www.cru.uea.ac.uk/projects/stardex/) and the Climate Change Indices web site (http://cccma.seos.uvic.ca/ETCCDMI/indices.html). Specifically, the indices computed with this software are the frequency of high intensity 24-hour rainfall, unusually warm temperature, and unusually high runoff. These rare, or extreme events, are those greater than the 90th percentile of precipitation, streamflow, or temperature computed for the period of record of weather or gaging stations. If they cluster in time over several decades, extreme events may produce detectable change in the physical landscape and ecosystem of a given region. Although the software has been tested on a variety of data, as with any software, the user should carefully evaluate the results with their data. The programs were designed for the range of precipitation, temperature, and streamflow measurements expected in the semiarid
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Directory of Open Access Journals (Sweden)
Michal Fusek
2016-11-01
Full Text Available Precipitation records from six stations of the Czech Hydrometeorological Institute were subject to statistical analysis with the objectives of updating the intensity–duration–frequency (IDF curves, by applying extreme value distributions, and comparing the updated curves against those produced by an empirical procedure in 1958. Another objective was to investigate differences between both sets of curves, which could be explained by such factors as different measuring instruments, measuring stations altitudes and data analysis methods. It has been shown that the differences between the two sets of IDF curves are significantly influenced by the chosen method of data analysis.
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Spatial analysis of extreme precipitation deficit as an index for atmospheric drought in Belgium
Zamani, Sepideh; Van De Vyver, Hans; Gobin, Anne
2014-05-01
The growing concern among the climate scientists is that the frequency of weather extremes will increase as a result of climate change. European society, for example, is particularly vulnerable to changes in the frequency and intensity of extreme events such as heat waves, heavy precipitation, droughts, and wind storms, as seen in recent years [1,2]. A more than 50% of the land is occupied by managed ecosystem (agriculture, forestry) in Belgium. Moreover, among the many extreme weather conditions, drought counts to have a substantial impact on the agriculture and ecosystem of the affected region, because its most immediate consequence is a fall in crop production. Besides the technological advances, a reliable estimation of weather conditions plays a crucial role in improving the agricultural productivity. The above mentioned reasons provide a strong motivation for a research on the drought and its impacts on the economical and agricultural aspects in Belgium. The main purpose of the presented work is to map atmospheric drought Return-Levels (RL), as first insight for agricultural drought, employing spatial modelling approaches. The likelihood of future drought is studied on the basis of precipitation deficit indices for four vegetation types: water (W), grass (G), deciduous (D) and coniferous forests (C) is considered. Extreme Value Theory (EVT) [3,4,5] as a branch of probability and statistics, is dedicated to characterize the behaviour of extreme observations. The tail behaviour of the EVT distributions provide important features about return levels. EVT distributions are applicable in many study areas such as: hydrology, environmental research and meteorology, insurance and finance. Spatial Generalized Extreme Value (GEV) distributions, as a branch of EVT, are applied to annual maxima of drought at 13 hydro-meteorological stations across Belgium. Superiority of the spatial GEV model is that a region can be modelled merging the individual time series of
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Climate Prediction Center(CPC)Daily GOES Precipitation Index (GPI)
National Oceanic and Atmospheric Administration, Department of Commerce — GOES Precipitation Index (GPI) is a precipitation estimation algorithm. The GPI technique estimates tropical rainfall using cloud-top temperature as the sole...
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Ricciuto, D. M.; Warren, J.; Guha, A.
2017-12-01
While carbon and energy fluxes in current Earth system models generally have reasonable instantaneous responses to extreme temperature and precipitation events, they often do not adequately represent the long-term impacts of these events. For example, simulated net primary productivity (NPP) may decrease during an extreme heat wave or drought, but may recover rapidly to pre-event levels following the conclusion of the extreme event. However, field measurements indicate that long-lasting damage to leaves and other plant components often occur, potentially affecting the carbon and energy balance for months after the extreme event. The duration and frequency of such extreme conditions is likely to shift in the future, and therefore it is critical for Earth system models to better represent these processes for more accurate predictions of future vegetation productivity and land-atmosphere feedbacks. Here we modify the structure of the Accelerated Climate Model for Energy (ACME) land surface model to represent long-term impacts and test the improved model against observations from experiments that applied extreme conditions in growth chambers. Additionally, we test the model against eddy covariance measurements that followed extreme conditions at selected locations in North America, and against satellite-measured vegetation indices following regional extreme events.
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Vilhar, Urša; Simončič, Primož
2013-04-01
Extreme precipitation in the Alpine region is a major environmental factor due to high frequency of such events and consequences such as flooding of populated valley floors, erosion, avalanches, debris flow and landslides endangering exposed settlements. However, the effects of extreme precipitation are buffered by forest cover, therefore forest management practices should aim towards decreased surface runoff and soil erosion in alpine climates. In Central Europe, many pure Norway spruce stands, established on primary beech sites, were converted into mixed stands over the last 60 years. The conversion of forest management from spruce monocultures into mixed deciduous-coniferous forests changed the forest structure dramatically. This changes could influence the hydrological processes on the catchment scale, associated with major river flooding following extreme precipitation events. In this study, the effect of forest management on the partitioning of rainfall into throughfall and stemflow in coniferous and mixed deciduous-coniferous stands on Pohorje mountains in NE Slovenia were investigated. Four spruce Picea abies (L. Karst) stands were compared to four mixed spruce-beech Fagus sylvatica (L.) stands with prevailing forest plant community Cardamine Savensi Fagetum with small areas of Sphagno - Piceetum, Bazzanio - Piceetum and Rhytidiodelpholorei - Piceetum intermixed. The monthly throughfall from rain collectors and half-hourly throughfall from automated rain gauges in growing seasons from 2008 till 2012 were analyzed in order to estimate the throughfall under forest canopies. In the mixed spruce-beech stands the monthly stemflow on beech trees was also measured. For the precipitation in the open an automated weather station and rainfall collectors in an open area located very close to the research plots were used. There were small differences in seasonal throughfall found between the coniferous and mixed deciduous-coniferous stands. The seasonal throughfall was
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How is climate change impacting precipitation?
Heidari, A.; Houser, P. R.
2015-12-01
Water is an integrating component of the climate, energy and geochemical cycles, regulating biological and ecological activities at all spatial and temporal scales. The most significant climate warming manifestation would be a change in the distribution of precipitation and evaporation, and the exacerbation of extreme hydrologic events. Due to this phenomenon and the fact that precipitation is the most important component of the water cycle, the assumption of its stationarity for water management and engineering design should be examined closely. The precipitation Annual Maximum Series (AMS) over some stations in Virginia based on in situ data were been used as a starting point to examine this important issue. We analyzed the AMS precipitation on NOAA data for the stations close to Fairfax VA, looked for trends in extreme values, and applied our new method of Generalized Extreme Value (GEV) theory based on quadratic forms to address changes in those extreme values and to quantify non-stationarities. It is very important to address the extreme values of precipitation based on several statistical tests to have better understanding of climate change impact on the extreme water cycle events. In our study we compared our results with the conclusion on NOAA atlas 14 Ap.3 which found no sign of precipitation non-stationarity. We then assessed the impact of this uncertainty in IDF curves on the flood map of Fairfax and compared the results with the classic IDF curves.
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Aerenson, Travis; Tebaldi, Claudia; Sanderson, Ben; Lamarque, Jean-François
2018-03-01
Following the 2015 Paris agreement, the Intergovernmental Panel on Climate Change was tasked with assessing climate change impacts and mitigation options for a world that limits warming to 1.5 °C in a special report. To aid the scientific assessment process three low-warming ensembles were generated over the 21st century based on the Paris targets using NCAR-DOE community model, CESM1-CAM5. This study used those simulation results and computed ten extreme climate indices, from definitions created by the Expert Team on Climate Change Detection and Indices, to determine if the three different scenarios cause different intensity and frequency of extreme precipitation or temperature over the 21st century. After computing the indices, statistical tests were used to determine if significant changes affect their characteristics. It was found that at the grid point level significant changes emerge in all scenarios, for nearly all indices. The temperature indices show widespread significant change, while the behavior of precipitation indices reflects the larger role that internal variability plays, even by the end of the century. Nonetheless differences can be assessed, in substantial measure for many of these indices: changes in nearly all indices have a strong correlation to global mean temperature, so that scenarios and times with greater temperature change experience greater index changes for many regions. This is particularly true of the temperature-related indices, but can be assessed for some regions also for the indices related to precipitation intensity. These results thus show that even for scenarios that are separated by only half of a degree in global average temperature, the statistics of extremes are significantly different.
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Stuart-Haëntjens, E. J.; De Boeck, H. J.; Lemoine, N. P.; Gough, C. M.; Kröel-Dulay, G.; Mänd, P.; Jentsch, A.; Schmidt, I. K.; Bahn, M.; Lloret, F.; Kreyling, J.; Wohlgemuth, T.; Stampfli, A.; Anderegg, W.; Classen, A. T.; Smith, M. D.
2017-12-01
Extreme drought is increasing globally in frequency and intensity, with uncertain consequences for the resistance and resilience of key ecosystem functions, including primary production. Primary production resistance, the capacity of an ecosystem to withstand change in primary production following extreme climate, and resilience, the degree to which primary production recovers, vary among and within ecosystem types, obscuring global patterns of resistance and resilience to extreme drought. Past syntheses on resistance have focused climatic gradients or individual ecosystem types, without assessing interactions between the two. Theory and many empirical studies suggest that forest production is more resistant but less resilient than grassland production to extreme drought, though some empirical studies reveal that these trends are not universal. Here, we conducted a global meta-analysis of sixty-four grassland and forest sites, finding that primary production resistance to extreme drought is predicted by a common continuum of mean annual precipitation (MAP). However, grasslands and forests exhibit divergent production resilience relationships with MAP. We discuss the likely mechanisms underlying the mixed production resistance and resilience patterns of forests and grasslands, including different plant species turnover times and drought adaptive strategies. These findings demonstrate the primary production responses of forests and grasslands to extreme drought are mixed, with far-reaching implications for Earth System Models, ecosystem management, and future studies of extreme drought resistance and resilience.
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Okada, Y.; Ishii, M.; Endo, H.; Kawase, H.; Sasaki, H.; Takayabu, I.; Watanabe, S.; Fujita, M.; Sugimoto, S.; Kawazoe, S.
2017-12-01
Precipitation in summer plays a vital role in sustaining life across East Asia, but the heavy rain that is often generated during this period can also cause serious damage. Developing a better understanding of the features and occurrence frequency of this heavy rain is an important element of disaster prevention. We investigated future changes in summer mean and extreme precipitation frequency in Japan using large ensemble dataset which simulated by the Non-Hydrostatic Regional Climate Model with a horizontal resolution of 20km (NHRCM20). This dataset called database for Policy Decision making for Future climate changes (d4PDF), which is intended to be utilized for the impact assessment studies and adaptation planning to global warming. The future climate experiments assume the global mean surface air temperature rise 2K and 4K from the pre-industrial period. We investigated using this dataset future changes of precipitation in summer over the Japanese archipelago based on observational locations. For mean precipitation in the present-day climate, the bias of the rainfall for each month is within 25% even considering all members (30 members). The bias at each location is found to increase by over 50% on the Pacific Ocean side of eastern part of Japan and interior locations of western part of Japan. The result in western part of Japan depends on the effect of the elevations in this model. The future changes in mean precipitation show a contrast between northern and southern Japan, with the north showing a slight increase but the south a decrease. The future changes in the frequency of extreme precipitation in the national average of Japan increase at 2K and 4K simulations compared with the present-day climate, respectively. The authors were supported by the Social Implementation Program on Climate Change Adaptation Technology (SI-CAT), the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.
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Dependence between sea surge, river flow and precipitation in south and west Britain
Directory of Open Access Journals (Sweden)
C. Svensson
2004-01-01
Full Text Available Estuaries around Great Britain may be at heightened risk of flooding because of the simultaneous occurrence of extreme sea surge and river flow, both of which may be caused by mid-latitude cyclones. A measure especially suited for extremes was employed to estimate dependence between river flow and sea surge. To assist in the interpretation of why flow-surge dependence occurs in some areas and not in others, the dependence between precipitation and surge and between precipitation and river flow was also studied. Case studies of the meteorological situations leading to high surges and/or river flows were also carried out. The present study concerns catchments draining to the south and west coasts of Great Britain. Statistically significant dependence between river flow and daily maximum sea surge may be found at catchments spread along most of this coastline. However, higher dependence is generally found in catchments in hilly areas with a southerly to westerly aspect. Here, precipitation in south-westerly airflow, which is generally the quadrant of prevailing winds, will be enhanced orographically as the first higher ground is encountered. The sloping catchments may respond quickly to the abundant rainfall and the flow peak may arrive in the estuary on the same day as a large sea surge is produced by the winds and low atmospheric pressure associated with the cyclone. There are three regions where flow-surge dependence is strong: the western part of the English south coast, southern Wales and around the Solway Firth. To reduce the influence of tide-surge interaction on the dependence analysis, the dependence between river flow and daily maximum surge occurring at high tide was estimated. The general pattern of areas with higher dependence is similar to that using the daily maximum surge. The dependence between river flow and daily maximum sea surge is often strongest when surge and flow occur on the same day. The west coast from Wales and
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de Vries, A. J.; Ouwersloot, H. G.; Feldstein, S. B.; Riemer, M.; El Kenawy, A. M.; McCabe, Matthew; Lelieveld, J.
2017-01-01
) intrusion reaches deep into the subtropics and forces an incursion of high poleward vertically integrated water vapor transport (IVT) into the Middle East. This study presents an object-based identification method for extreme precipitation events based
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Analysis of the Effects of ENSO and Atmospheric Rivers on Precipitation in Los Angeles County
Santacruz, A.; Lamb, K.
2017-12-01
The Winter 2016-2017 season in California was marked by substantial amounts of precipitation; this resulted in critically-low reservoirs filling up and the removal of most of California from drought status. The year prior was characterized by one of the strongest El Nino-Southern Oscillation (ENSO) events, though it did not produce nearly enough precipitation as the 2016-2017 season. The major contributors to the increased rainfall during the 2016-2017 season were climactic phenomenon known as atmospheric rivers (ARs), which transport water vapor through the atmosphere in narrow bands, and are known to produce extreme rain events. Determining the exact timing, landfall areas, and total precipitation amounts of ARs is currently of great interest; a recent study showed that extreme weather events are likely to increase in California in the coming years, which motivates research into how phenomenon such as ENSO and ARs play a role. Using long-term daily rain gauge data provided by the Los Angeles County Department of Public Works, we compute the precipitation volume and storm count for various locations in Los Angeles County and identify anomalies. These data will then be compared with the occurrence and intensity of AR and ENSO events by using NOAA's NOI and ESRL AR data. The results can be used to provide a better grasp of extreme climactic patterns and their effects on the amount of precipitation in the region.
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Precipitation in Madeira island and atmospheric rivers in the winter seasons
Couto, Flavio T.; Salgado, Rui; João Costa, Maria; Prior, Victor
2016-04-01
This study aims to analyse the distribution of the daily accumulated precipitation in the Madeira's highlands over a 10-year period, as well as the main characteristics associated with atmospheric rivers (ARs) affecting the island during 10 winter seasons, and their impact in the rainfall amounts recorded near the mountain crest in the south-eastern part of the island. The period between September 2002 and November 2012 is considered for the analysis. The ARs have been identified from the total precipitable water vapour field extracted from the Atmospheric Infrared Sounder (AIRS). The AIRS observations were downloaded for a domain covering large part of the North Atlantic Ocean. The precipitable water vapour field from the European Centre for Medium-range Weather Forecasts (ECMWF) analysis was also used aiming to support the AIRS data when there was no satellite information over the island. The daily accumulated precipitation at surface showed generally drier summers, while the highest accumulated precipitation are recorded mainly during the winter, although some significant events may occur also in autumn and spring seasons. The patterns of the precipitable water vapour field when ARs reach the island were investigated, and even if great part of the atmospheric rivers reaches the island in a dissipation stage, some rivers are heavy enough to reach the Madeira Island. In this situation, the water vapour transport could be observed in two main configurations and transporting significant water vapour amounts toward the Madeira from the tropical region. This study lead to conclude that the atmospheric rivers, when associated to high values of precipitable water vapour over the island can provide favourable conditions to the development of precipitation, sometimes associated with high amounts. However, it was also found that many cases of high to extreme accumulated precipitation at the surface were not associated to this kind of moisture transport.
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Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.
2013-01-01
The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case
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Peterson, P.; Funk, C. C.; Husak, G. J.; Pedreros, D. H.; Landsfeld, M.; Verdin, J. P.; Shukla, S.
2013-12-01
CHIRP and CHIRPS are new quasi-global precipitation products with daily to seasonal time scales, a 0.05° resolution, and a 1981 to near real-time period of record. Developed by the Climate Hazards Group at UCSB and scientists at the U.S. Geological Survey Earth Resources Observation and Science Center specifically for drought early warning and environmental monitoring, CHIRPS provides moderate latency precipitation estimates that place observed hydrologic extremes in their historic context. Three main types of information are used in the CHIRPS: (1) global 0.05° precipitation climatologies, (2) time-varying grids of satellite-based precipitation estimates, and (3) in situ precipitation observations. CHIRP: The global grids of long-term (1980-2009) average precipitation were estimated for each month based on station data, averaged satellite observations, and physiographic parameters. 1981-present time-varying grids of satellite precipitation were derived from spatially varying regression models based on pentadal cold cloud duration (CCD) values and TRMM V7 training data. The CCD time-series were derived from the CPC and NOAA B1 datasets. Pentadal CCD-percent anomaly values were multiplied by pentadal climatology fields to produce low bias pentadal precipitation estimates. CHIRPS: The CHG station blending procedure uses the satellite-observed spatial covariance structure to assign relative weights to neighboring stations and the CHIRP values. The CHIRPS blending procedure is based on the expected correlation between precipitation at a given target location and precipitation at the locations of the neighboring observation stations. These correlations are estimated using the CHIRP fields. The CHG has developed an extensive archive of in situ daily, pentadal and monthly precipitation totals. The CHG database has over half a billion daily rainfall observations since 1980 and another half billion before 1980. Most of these observations come from four sets of global
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Directory of Open Access Journals (Sweden)
Miles Kirby, PhD
2018-05-01
Full Text Available Background: Enteric infections are a major cause of morbidity and mortality in low-income and middle-income countries, particularly among children younger than 5 years. Climate change projections for Rwanda predict increases in average temperature, along with increases in total precipitation and frequency of extreme rainfall events. Previous research in Rwanda has found that extreme rainfall events increase the risk of contaminated drinking water, a substantial contributor to diarrhoea in this setting. Relatively little is known about the effect of precipitation on more severe clinic-diagnosed infections in rural, low-income settings such as Rwanda. In the context of a randomised controlled trial to assess the effect of a national environmental health campaign in Rwanda, we did a substudy to assess the effect of total and extreme rainfall on enteric infections in children younger than 5 years. Methods: For this observational study, we collected data from all government health facilities in Rusizi District, Western Province, for the year 2015. Patient data for children younger than 5 years from 150 study villages were extracted from paper-based registers. Gridded daily precipitation data were downloaded from the Tropical Applications of Meteorology using SATellite and ground based observations (TAMSAT rainfall dataset in addition to local weather station data. We modelled the effect of total rainfall (in mm and occurrence of an extreme rainfall event (95th percentile in the past 2 years on daily health facility visits for enteric symptoms (diarrhoea, gastroenteritis, or vomiting, using Poisson regression with a Newey-West estimator to adjust for serial autocorrelation. We examined total and extreme rainfall within the previous 1, 2, 3, and 4 weeks, controlling for weekend day because we observed a consistent reduction in case counts on weekends. Findings: Data were extracted from 46 facilities, with a study catchment area of approximately 12
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Rainfall frequency analysis for ungauged sites using satellite precipitation products
Gado, Tamer A.; Hsu, Kuolin; Sorooshian, Soroosh
2017-11-01
The occurrence of extreme rainfall events and their impacts on hydrologic systems and society are critical considerations in the design and management of a large number of water resources projects. As precipitation records are often limited or unavailable at many sites, it is essential to develop better methods for regional estimation of extreme rainfall at these partially-gauged or ungauged sites. In this study, an innovative method for regional rainfall frequency analysis for ungauged sites is presented. The new method (hereafter, this is called the RRFA-S) is based on corrected annual maximum series obtained from a satellite precipitation product (e.g., PERSIANN-CDR). The probability matching method (PMM) is used here for bias correction to match the CDF of satellite-based precipitation data with the gauged data. The RRFA-S method was assessed through a comparative study with the traditional index flood method using the available annual maximum series of daily rainfall in two different regions in USA (11 sites in Colorado and 18 sites in California). The leave-one-out cross-validation technique was used to represent the ungauged site condition. Results of this numerical application have found that the quantile estimates obtained from the new approach are more accurate and more robust than those given by the traditional index flood method.
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Zonneveld, Karin; Clotten, Caroline; Chen, Liang
2015-04-01
Sediments of a tephra-dated marine sediment core located at the distal part of the Po-river discharge plume (southern Italy) have been studied with a three annual resolution. Based on the variability in the dinoflagellate cyst content detailed reconstructions have been established of variability in precipitation related river discharge rates and local air temperature. Furthermore about the variability in distort water quality has been reconstructed. We show that both precipitation and temperature signals vary in tune with cyclic changes in solar insolation. On top of these cyclic changes, short term extremes in temperature and precipitation can be observed that can be interpreted to reflect periods of local weather extremes. Comparison of our reconstructions with historical information suggest that times of high temperatures and maximal precipitation corresponds to the period of maximal expansion of the Roman Empire. We have strong indications that at this time discharge waters might have contained higher nutrient concentrations compared to previous and later time intervals suggesting anthropogenic influence of the water quality. First pilot-results suggest that the decrease in temperature reconstructed just after the "Roman Optimum" corresponds to an increase in numbers of armored conflicts between the Roman and German cultures. Furthermore we observe a resemblance in timing of short-term intervals with cold weather spells during the early so called "Dark-Age-Period" to correspond to epidemic/pandemic events in Europe.
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Hiebl, Johann; Frei, Christoph
2018-04-01
Spatial precipitation datasets that are long-term consistent, highly resolved and extend over several decades are an increasingly popular basis for modelling and monitoring environmental processes and planning tasks in hydrology, agriculture, energy resources management, etc. Here, we present a grid dataset of daily precipitation for Austria meant to promote such applications. It has a grid spacing of 1 km, extends back till 1961 and is continuously updated. It is constructed with the classical two-tier analysis, involving separate interpolations for mean monthly precipitation and daily relative anomalies. The former was accomplished by kriging with topographic predictors as external drift utilising 1249 stations. The latter is based on angular distance weighting and uses 523 stations. The input station network was kept largely stationary over time to avoid artefacts on long-term consistency. Example cases suggest that the new analysis is at least as plausible as previously existing datasets. Cross-validation and comparison against experimental high-resolution observations (WegenerNet) suggest that the accuracy of the dataset depends on interpretation. Users interpreting grid point values as point estimates must expect systematic overestimates for light and underestimates for heavy precipitation as well as substantial random errors. Grid point estimates are typically within a factor of 1.5 from in situ observations. Interpreting grid point values as area mean values, conditional biases are reduced and the magnitude of random errors is considerably smaller. Together with a similar dataset of temperature, the new dataset (SPARTACUS) is an interesting basis for modelling environmental processes, studying climate change impacts and monitoring the climate of Austria.
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Deal, Eric; Braun, Jean
2015-04-01
A current challenge in landscape evolution modelling is to integrate realistic precipitation patterns and behaviour into longterm fluvial erosion models. The effect of precipitation on fluvial erosion can be subtle as well as nonlinear, implying that changes in climate (e.g. precipitation magnitude or storminess) may have unexpected outcomes in terms of erosion rates. For example Tucker and Bras (2000) show theoretically that changes in the variability of precipitation (storminess) alone can influence erosion rate across a landscape. To complicate the situation further, topography, ultimately driven by tectonic uplift but shaped by erosion, has a major influence on the distribution and style of precipitation. Therefore, in order to untangle the coupling between climate, erosion and tectonics in an actively uplifting orogen where fluvial erosion is dominant it is important to understand how the 'rain dial' used in a landscape evolution model (LEM) corresponds to real precipitation patterns. One issue with the parameterisation of rainfall for use in an LEM is the difference between the timescales for precipitation (≤ 1 year) and landscape evolution (> 103 years). As a result, precipitation patterns must be upscaled before being integrated into a model. The relevant question then becomes: What is the most appropriate measure of precipitation on a millennial timescale? Previous work (Tucker and Bras, 2000; Lague, 2005) has shown that precipitation can be properly upscaled by taking into account its variable nature, along with its average magnitude. This captures the relative size and frequency of extreme events, ensuring a more accurate characterisation of the integrated effects of precipitation on erosion over long periods of time. In light of this work, we present a statistical parameterisation that accurately models the mean and daily variability of ground based (APHRODITE) and remotely sensed (TRMM) precipitation data in the Himalayan orogen with only a few
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Ongoma, Victor; Chen, Haishan; Omony, George William
2018-01-01
This study investigates the variability of extreme rainfall events over East Africa (EA), using indices from the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). The analysis was based on observed daily rainfall from 23 weather stations, with length varying within 1961 and 2010. The indices considered are: wet days ( R ≥1 mm), annual total precipitation in wet days (PRCPTOT), simple daily intensity index (SDII), heavy precipitation days ( R ≥ 10 mm), very heavy precipitation days ( R ≥ 20 mm), and severe precipitation ( R ≥ 50 mm). The non-parametric Mann-Kendall statistical analysis was carried out to identify trends in the data. Temporal precipitation distribution was different from station to station. Almost all indices considered are decreasing with time. The analysis shows that the PRCPTOT, very heavy precipitation, and severe precipitation are generally declining insignificantly at 5 % significant level. The PRCPTOT is evidently decreasing over Arid and Semi-Arid Land (ASAL) as compared to other parts of EA. The number of days that recorded heavy rainfall is generally decreasing but starts to rise in the last decade although the changes are insignificant. Both PRCPTOT and heavy precipitation show a recovery in trend starting in the 1990s. The SDII shows a reduction in most areas, especially the in ASAL. The changes give a possible indication of the ongoing climate variability and change which modify the rainfall regime of EA. The results form a basis for further research, utilizing longer datasets over the entire region to reduce the generalizations made herein. Continuous monitoring of extreme events in EA is critical, given that rainfall is projected to increase in the twenty-first century.
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Czech Academy of Sciences Publication Activity Database
Gaál, Ladislav; Beranová, Romana; Hlavčová, K.; Kyselý, Jan
2014-01-01
Roč. 2014, č. 943487 (2014), s. 1-14 ISSN 1687-9309 R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : precipitation extremes * regional climate models * climate change Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.946, year: 2014 http://www.hindawi.com/journals/amete/2014/943487/
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Risser, Mark D.; Wehner, Michael F.
2017-12-01
Record rainfall amounts were recorded during Hurricane Harvey in the Houston, Texas, area, leading to widespread flooding. We analyze observed precipitation from the Global Historical Climatology Network with a covariate-based extreme value statistical analysis, accounting for both the external influence of global warming and the internal influence of El Niño-Southern Oscillation. We find that human-induced climate change likely increased the chances of the observed precipitation accumulations during Hurricane Harvey in the most affected areas of Houston by a factor of at least 3.5. Further, precipitation accumulations in these areas were likely increased by at least 18.8% (best estimate of 37.7%), which is larger than the 6-7% associated with an attributable warming of 1°C in the Gulf of Mexico and Clausius-Clapeyron scaling. In a Granger causality sense, these statements provide lower bounds on the impact of climate change and motivate further attribution studies using dynamical climate models.
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DEFF Research Database (Denmark)
Sunyer Pinya, Maria Antonia; Gregersen, Ida Bülow; Rosbjerg, Dan
2015-01-01
change method for extreme events, a weather generator combined with a disaggregation method and a climate analogue method. All three methods rely on different assumptions and use different outputs from the regional climate models (RCMs). The results of the three methods point towards an increase...... in extreme precipitation but the magnitude of the change varies depending on the RCM used and the spatial location. In general, a similar mean change is obtained for the three methods. This adds confidence in the results as each method uses different information from the RCMs. The results of this study...
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Generation of a stochastic precipitation model for the tropical climate
Ng, Jing Lin; Abd Aziz, Samsuzana; Huang, Yuk Feng; Wayayok, Aimrun; Rowshon, MK
2017-06-01
A tropical country like Malaysia is characterized by intense localized precipitation with temperatures remaining relatively constant throughout the year. A stochastic modeling of precipitation in the flood-prone Kelantan River Basin is particularly challenging due to the high intermittency of precipitation events of the northeast monsoons. There is an urgent need to have long series of precipitation in modeling the hydrological responses. A single-site stochastic precipitation model that includes precipitation occurrence and an intensity model was developed, calibrated, and validated for the Kelantan River Basin. The simulation process was carried out separately for each station without considering the spatial correlation of precipitation. The Markov chains up to the fifth-order and six distributions were considered. The daily precipitation data of 17 rainfall stations for the study period of 1954-2013 were selected. The results suggested that second- and third-order Markov chains were suitable for simulating monthly and yearly precipitation occurrences, respectively. The fifth-order Markov chain resulted in overestimation of precipitation occurrences. For the mean, distribution, and standard deviation of precipitation amounts, the exponential, gamma, log-normal, skew normal, mixed exponential, and generalized Pareto distributions performed superiorly. However, for the extremes of precipitation, the exponential and log-normal distributions were better while the skew normal and generalized Pareto distributions tend to show underestimations. The log-normal distribution was chosen as the best distribution to simulate precipitation amounts. Overall, the stochastic precipitation model developed is considered a convenient tool to simulate the characteristics of precipitation in the Kelantan River Basin.
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Probability Modeling of Precipitation Extremes over Two River Basins in Northwest of China
Directory of Open Access Journals (Sweden)
Zhanling Li
2015-01-01
Full Text Available This paper is focused on the probability modeling with a range of distribution models over two inland river basins in China, together with the estimations of return levels on various return periods. Both annual and seasonal maximum precipitations (MP are investigated based on daily precipitation data at 13 stations from 1960 to 2010 in Heihe River and Shiyang River basins. Results show that GEV, Burr, and Weibull distributions provide the best fit to both annual and seasonal MP. Exponential and Pareto 2 distributions show the worst fit. The estimated return levels for spring MP show decreasing trends from the upper to the middle and then to the lower reaches totally speaking. Summer MP approximates to annual MP both in the quantity and in the spatial distributions. Autumn MP shows a little higher value in the estimated return levels than Spring MP, while keeping consistent with spring MP in the spatial distribution. It is also found that the estimated return levels for annual MP derived from various distributions differ by 22%, 36%, and 53% on average at 20-year, 50-year, and 100-year return periods, respectively.
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Thomas, Z.; Turney, C. S.; Allan, R.; Colwell, S.; Kelly, G.; Lister, D.; Jones, P. D.; Beswick, M.; Alexander, L. V.; Lippmann, T.; Herold, N.; Jones, R. T.
2017-12-01
Although recent work has highlighted a host of significant late 20th century environmental changes across the mid to high latitudes of the Southern Hemisphere, the sparse nature of observational records limits our ability to place these changes in the context of long-term (multi-decadal and centennial) variability. As a result, investigating the impact of anthropogenic forcing on climate modes of variability and ecosystems is particularly challenging. Sub-Antarctic islands are particularly important in this regard, straddling major ocean and atmospheric boundaries and offering the potential to develop highly resolved records of change. In 1905, a whaling and meteorological station was established at Grytviken on Sub-Antarctic South Georgia in the South Atlantic (54°S) providing near-continuous observations through to present day. Although South Georgia lies in a strategic location for understanding Southern Ocean atmosphere-ocean dynamics, only a monthly resolved dataset has until now been available. Here we report a near continuous daily observational record from Grytviken for temperature and precipitation, which we compare to different datasets (including Twentieth Century Reanalysis; 20CR version 2c). A warming trend over the 20th century is observed in mean daily temperature at Grytviken with an average rate of temperature rise of 0.14°C per decade over the period 1907-2016 (p<0.0001). We find a significant trend towards increasingly warmer daytime extremes commencing from the mid-20th century accompanied by warmer night-time temperatures. Analysis of these data, and reanalysis products, suggest a realignment of synoptic conditions across the mid to high-latitudes, with a link between increasing temperature trends and atmospheric circulation dominated by stronger westerly airflow, resulting in significant foehn-related warming.
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Özcan Kahraman, Buse; Özsoy, İsmail; Acar, Serap; Özpelit, Ebru; Akdeniz, Bahri; Sevinç, Can; Savcı, Sema
2017-07-01
Pulmonary arterial hypertension (PAH) is a rare disease. Although muscle strength, exercise capacity, quality of life, and activities of daily living of patients with PAH are affected, it is not known how they are affected by disease severity. The purpose of the present study was to investigate effects of disease severity on upper extremity muscle strength, exercise capacity, and performance of activities of daily living in patients with PAH. Twenty-five patients with disease severity classified according to the New York Heart Association (NYHA) as functional class II (n=14) or class III (n=11) were included in the study. Upper-extremity exercise capacity and limitations in performing activities of daily living were assessed with 6-minute pegboard and ring test (6PBRT) and the Milliken activities of daily living scale (MAS), respectively. Shoulder flexion, elbow extension, elbow flexion muscle strength, and handgrip strength were measured with dynamometer. There were no significant differences in age, gender, body mass index, or mean pulmonary artery pressure between groups (p>0.05). The 6PBRT, MAS, and elbow flexion (right) and grip strength (right and left) results were significantly lower in NYHA III group than in NYHA II group (p=0.004, p=0.002, p=0.043, p=0.002 and p=0.003, respectively). There was no significant difference in shoulder flexion, elbow flexion (left), or elbow extension between groups (p>0.05). Results suggest that upper extremity exercise capacity, elbow flexion muscle strength (right), and handgrip strength decrease and that limitations in activities of daily living grow as disease severity increases in patients with PAH. When planning rehabilitation programs, disease severity should be considered and evaluations and treatments for the upper extremities should be included.
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International Nuclear Information System (INIS)
Kim, Jinwon
2005-01-01
The effects of increased atmospheric CO2 on the frequency of extreme hydrologic events in the Western United States (WUS) for the 10-yr period of 2040-2049 are examined using dynamically downscaled regional climate change signals. For assessing the changes in the occurrence of hydrologic extremes, downscaled climate change signals in daily precipitation and runoff that are likely to indicate the occurrence of extreme events are examined. Downscaled climate change signals in the selected indicators suggest that the global warming induced by increased CO2 is likely to increase extreme hydrologic events in the WUS. The indicators for heavy precipitation events show largest increases in the mountainous regions of the northern California Coastal Range and the Sierra Nevada. Increased cold season precipitation and increased rainfall-portion of precipitation at the expense of snowfall in the projected warmer climate result in large increases in high runoff events in the Sierra Nevada river basins that are already prone to cold season flooding in todays climate. The projected changes in the hydrologic characteristics in the WUS are mainly associated with higher freezing levels in the warmer climate and increases in the cold season water vapor influx from the Pacific Ocean
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Ague, J. J.; Eckert, J. O.
2011-12-01
We report the discovery of oriented needles of rutile and, less commonly, ilmenite in the cores of garnets from northeastern CT, USA. The rocks preserve granulite facies mineral assemblages, form part of the Merrimack Synclinorium, and underwent metamorphism and deformation during the Acadian orogeny. The needles appear identical to those reported from a number of extreme P-T environments worldwide, including UHP metamorphic rocks, high-P granulites, and garnet peridotites. The needles are predominantly oriented along directions in garnet. The long axes of the rutile needles commonly do not go extinct parallel to the cross hairs under cross-polarized light (e.g., Griffin et al., 1971). This anomalous extinction indicates that the needles do not preserve a specific crystallographic relationship with their garnet hosts (e.g., Hwang et al., 2007). The needles range from a few hundred nm to a few um in diameter, and can be mm-scale in length. Micrometer-scale plates of rutile, srilankite and crichtonite have also been observed in some garnets together with the Fe-Ti oxide needles. Several origins for the needles have been proposed in the literature; we investigate the hypothesis that they precipitated in situ from originally Ti-rich garnet. Chemical profiles across garnets indicate that some retain Ti zoning, with elevated-Ti concentrations in the cores dropping to low values in the rims. For these zoned garnets, high-resolution, 2-D chemical mapping using the JEOL JXA-8530F field emission gun electron microprobe at Yale University reveals that the needles are surrounded by well-defined Ti-depletion halos. Chemical profiles also document strong depletions of Cr (which is present in both rutile and ilmenite) directly adjacent to needles. The observed Ti-depletions demonstrate that the needles precipitated from Ti-bearing garnet, probably during cooling and/or decompression associated with exhumation. The rutile precipitates must be largely incoherent with respect to the
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IDF-curves for precipitation In Belgium
International Nuclear Information System (INIS)
Mohymont, Bernard; Demarde, Gaston R.
2004-01-01
The Intensity-Duration-Frequency (IDF) curves for precipitation constitute a relationship between the intensity, the duration and the frequency of rainfall amounts. The intensity of precipitation is expressed in mm/h, the duration or aggregation time is the length of the interval considered while the frequency stands for the probability of occurrence of the event. IDF-curves constitute a classical and useful tool that is primarily used to dimension hydraulic structures in general, as e.g., sewer systems and which are consequently used to assess the risk of inundation. In this presentation, the IDF relation for precipitation is studied for different locations in Belgium. These locations correspond to two long-term, high-quality precipitation networks of the RMIB: (a) the daily precipitation depths of the climatological network (more than 200 stations, 1951-2001 baseline period); (b) the high-frequency 10-minutes precipitation depths of the hydro meteorological network (more than 30 stations, 15 to 33 years baseline period). For the station of Uccle, an uninterrupted time-series of more than one hundred years of 10-minutes rainfall data is available. The proposed technique for assessing the curves is based on maximum annual values of precipitation. A new analytical formula for the IDF-curves was developed such that these curves stay valid for aggregation times ranging from 10 minutes to 30 days (when fitted with appropriate data). Moreover, all parameters of this formula have physical dimensions. Finally, adequate spatial interpolation techniques are used to provide nationwide extreme values precipitation depths for short- to long-term durations With a given return period. These values are estimated on the grid points of the Belgian ALADIN-domain used in the operational weather forecasts at the RMIB.(Author)
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Daily rainfall statistics of TRMM and CMORPH: A case for trans-boundary Gandak River basin
Kumar, Brijesh; Patra, Kanhu Charan; Lakshmi, Venkat
2016-07-01
Satellite precipitation products offer an opportunity to evaluate extreme events (flood and drought) for areas where rainfall data are not available or rain gauge stations are sparse. In this study, daily precipitation amount and frequency of TRMM 3B42V.7 and CMORPH products have been validated against daily rain gauge precipitation for the monsoon months (June-September or JJAS) from 2005-2010 in the trans-boundary Gandak River basin. The analysis shows that the both TRMM and CMORPH can detect rain and no-rain events, but they fail to capture the intensity of rainfall. The detection of precipitation amount is strongly dependent on the topography. In the plains areas, TRMM product is capable of capturing high-intensity rain events but in the hilly regions, it underestimates the amount of high-intensity rain events. On the other hand, CMORPH entirely fails to capture the high-intensity rain events but does well with low-intensity rain events in both hilly regions as well as the plain region. The continuous variable verification method shows better agreement of TRMM rainfall products with rain gauge data. TRMM fares better in the prediction of probability of occurrence of high-intensity rainfall events, but it underestimates intensity at high altitudes. This implies that TRMM precipitation estimates can be used for flood-related studies only after bias adjustment for the topography.
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Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.
2014-05-01
The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall), and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients (called ℓ1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a data base of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case
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Regional climate change: Precipitation variability in mountainous part of Bulgaria
Directory of Open Access Journals (Sweden)
Nikolova Nina
2007-01-01
Full Text Available The aim of paper is to analyze temporal and spatial changes in monthly precipitation as well as extremely dry and wet months in mountainous part of Bulgaria. Study precipitation variability in mountainous part is very important because this part is the region where the rivers take its source from. Extreme values of monthly precipitation are important information for better understanding of the whole variability and trends in precipitation time series. The mean investigated period is 1951-2005 and the reference period is so called temporary climate - 1961- 1990. Extreme dry precipitation months are defined as a month whose monthly precipitation is lower than 10% of gamma distribution in the reference period 1961-1990. Extreme wet months are determined with respect to 90% percentiles of gamma distribution (monthly precipitation is higher than 90%. The result of the research show that in mountainous part of Bulgaria during 1950s and 1960s number of extremely wet months is higher than number of dry months. Decreasing of monthly precipitation is a feature for 1980s. This dry period continues till 2004. The years 2000 makes impression as driest year in high mountains with about 7 extremely dry months. The second dry year is 1993. The negative precipitation anomaly is most clearly determined during last decade at study area. The present research points out that fluctuation of precipitation in mountainous part of Bulgaria are coinciding with regional and global climate trends.
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Beck, F.; Bárdossy, A.
2013-07-01
Many hydraulic applications like the design of urban sewage systems require projections of future precipitation in high temporal resolution. We developed a method to predict the regional distribution of hourly precipitation sums based on daily mean sea level pressure and temperature data from a Global Circulation Model. It is an indirect downscaling method avoiding uncertain precipitation data from the model. It is based on a fuzzy-logic classification of atmospheric circulation patterns (CPs) that is further subdivided by means of the average daily temperature. The observed empirical distributions at 30 rain gauges to each CP-temperature class are assumed as constant and used for projections of the hourly precipitation sums in the future. The method was applied to the CP-temperature sequence derived from the 20th century run and the scenario A1B run of ECHAM5. According to ECHAM5, the summers in southwest Germany will become progressively drier. Nevertheless, the frequency of the highest hourly precipitation sums will increase. According to the predictions, estival water stress and the risk of extreme hourly precipitation will both increase simultaneously during the next decades.
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Directory of Open Access Journals (Sweden)
Shaowei Ning
2016-10-01
Full Text Available The Global Precipitation Mission (GPM Core Observatory that was launched on 27 February 2014 ushered in a new era for estimating precipitation from satellites. Based on their high spatial–temporal resolution and near global coverage, satellite-based precipitation products have been applied in many research fields. The goal of this study was to quantitatively compare two of the latest GPM-era satellite precipitation products (GPM IMERG and GSMap-Gauge Ver. 6 with a network of 840 precipitation gauges over the Chinese mainland. Direct comparisons of satellite-based precipitation products with rain gauge observations over a 20 month period from April 2014 to November 2015 at 0.1° and daily/monthly resolutions showed the following results: Both of the products were capable of capturing the overall spatial pattern of the 20 month mean daily precipitation, which was characterized by a decreasing trend from the southeast to the northwest. GPM IMERG overestimated precipitation by approximately 0.09 mm/day while GSMap-Gauge Ver. 6 underestimated precipitation by −0.04 mm/day. The two satellite-based precipitation products performed better over wet southern regions than over dry northern regions. They also showed better performance in summer than in winter. In terms of mean error, root mean square error, correlation coefficient, and probability of detection, GSMap-Gauge was better able to estimate precipitation and had more stable quality results than GPM IMERG on both daily and monthly scales. GPM IMERG was more sensitive to conditions of no rain or light rainfall and demonstrated good capability of capturing the behavior of extreme precipitation events. Overall, the results revealed some limitations of these two latest satellite-based precipitation products when used over the Chinese mainland, helping to characterize some of the error features in these datasets for potential users.
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Heavy Tail Behavior of Rainfall Extremes across Germany
Castellarin, A.; Kreibich, H.; Vorogushyn, S.; Merz, B.
2017-12-01
Distributions are termed heavy-tailed if extreme values are more likely than would be predicted by probability distributions that have exponential asymptotic behavior. Heavy-tail behavior often leads to surprise, because historical observations can be a poor guide for the future. Heavy-tail behavior seems to be widespread for hydro-meteorological extremes, such as extreme rainfall and flood events. To date there have been only vague hints to explain under which conditions these extremes show heavy-tail behavior. We use an observational data set consisting of 11 climate variables at 1440 stations across Germany. This homogenized, gap-free data set covers 110 years (1901-2010) at daily resolution. We estimate the upper tail behavior, including its uncertainty interval, of daily precipitation extremes for the 1,440 stations at the annual and seasonal time scales. Different tail indicators are tested, including the shape parameter of the Generalized Extreme Value distribution, the upper tail ratio and the obesity index. In a further step, we explore to which extent the tail behavior can be explained by geographical and climate factors. A large number of characteristics is derived, such as station elevation, degree of continentality, aridity, measures for quantifying the variability of humidity and wind velocity, or event-triggering large-scale atmospheric situation. The link between the upper tail behavior and these characteristics is investigated via data mining methods capable of detecting non-linear relationships in large data sets. This exceptionally rich observational data set, in terms of number of stations, length of time series and number of explaining variables, allows insights into the upper tail behavior which is rarely possible given the typical observational data sets available.
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Producing Daily and Embedded Hourly Rainfall Data Using a Novel Weather Generator
Directory of Open Access Journals (Sweden)
Ching-Pin Tung
2013-01-01
Full Text Available The number of worldwide extreme drought and flood events has risen significantly in recent years. Many studies confer that climate change may cause more intensive and extreme events. Simulating the impact of climate change often requires weather data as inputs to assessment models. Stochastic weather generators have been developed to produce weather data with the same temporal resolution based on the outputs of GCMs. Reservoir simulation normally uses operational rules in daily and hourly time steps for water supply and flood reduction, respectively. Simulating consecutive drought and flood events simultaneously requires a weather generator to produce different temporal resolution data. This work develops a continuous weather generator to generate daily and hourly precipitation data for regular wet days and severe storms, respectively. Daily rainfall data is generated for regular wet days using Exponential distribution or Weibull distribution, while the total rainfall data for severe storms is generated using the Pearson type III or Log Pearson type III distribution. Moreover, hourly rainfall is determined based on generated hyetographs. Simulation results indicate that the proposed continuous weather generator can generate daily and hourly rainfall reasonably. The proposed weather generator is thus highly promising for use in evaluating how climate change impacts reservoir operations that are significantly influenced by more frequent and intensive consecutive drought and flood events.
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Risser, MD; Wehner, MF
2017-01-01
©2017. American Geophysical Union. All Rights Reserved. Record rainfall amounts were recorded during Hurricane Harvey in the Houston, Texas, area, leading to widespread flooding. We analyze observed precipitation from the Global Historical Climatology Network with a covariate-based extreme value statistical analysis, accounting for both the external influence of global warming and the internal influence of El Niño–Southern Oscillation. We find that human-induced climate change likely increase...
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Teixeira, J. C.; Carvalho, A. C.; Carvalho, M. J.; Luna, T.; Rocha, A.
2014-08-01
The advances in satellite technology in recent years have made feasible the acquisition of high-resolution information on the Earth's surface. Examples of such information include elevation and land use, which have become more detailed. Including this information in numerical atmospheric models can improve their results in simulating lower boundary forced events, by providing detailed information on their characteristics. Consequently, this work aims to study the sensitivity of the weather research and forecast (WRF) model to different topography as well as land-use simulations in an extreme precipitation event. The test case focused on a topographically driven precipitation event over the island of Madeira, which triggered flash floods and mudslides in the southern parts of the island. Difference fields between simulations were computed, showing that the change in the data sets produced statistically significant changes to the flow, the planetary boundary layer structure and precipitation patterns. Moreover, model results show an improvement in model skill in the windward region for precipitation and in the leeward region for wind, in spite of the non-significant enhancement in the overall results with higher-resolution data sets of topography and land use.
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Future changes of precipitation characteristics in China
Wu, S.; Wu, Y.; Wen, J.
2017-12-01
Global warming has the potential to alter the hydrological cycle, with significant impacts on the human society, the environment and ecosystems. This study provides a detailed assessment of potential changes in precipitation characteristics in China using a suite of 12 high-resolution CMIP5 climate models under a medium and a high Representative Concentration Pathways: RCP4.5 and RCP8.5. We examine future changes over the entire distribution of precipitation, and identify any shift in the shape and/or scale of the distribution. In addition, we use extreme-value theory to evaluate the change in probability and magnitude for extreme precipitation events. Overall, China is going to experience an increase in total precipitation (by 8% under RCP4.5 and 12% under RCP8.5). This increase is uneven spatially, with more increase in the west and less increase in the east. Precipitation frequency is projected to increase in the west and decrease in the east. Under RCP4.5, the overall precipitation frequency for the entire China remains largely unchanged (0.08%). However, RCP8.5 projects a more significant decrease in frequency for large part of China, resulting in an overall decrease of 2.08%. Precipitation intensity is likely increase more uniformly, with an overall increase of 11% for RCP4.5 and 19% for RCP8.5. Precipitation increases for all parts of the distribution, but the increase is more for higher quantiles, i.e. strong events. The relative contribution of small quantiles is likely to decrease, whereas contribution from heavy events is likely to increase. Extreme precipitation increase at much higher rates than average precipitation, and high rates of increase are expected for more extreme events. 1-year events are likely to increase by 15%, but 20-year events are going to increase by 21% under RCP4.5, 26% and 40% respectively under RCP8.5. The increase of extreme events is likely to be more spatially uniform.
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Energy Technology Data Exchange (ETDEWEB)
Paeth, H.; Hense, A. [Meteorological Inst., Univ. Bonn (Germany)
2005-06-01
The Mediterranean region (MTR) has been supposed to be very sensitive to changes in land surface and atmospheric greenhouse-gas (GHG) concentrations. Particularly, an intensification of climate extremes may be associated with severe socio-economic implications. Here, we present an analysis of climate mean and extreme conditions in this subtropical area based on regional climate model experiments, simulating the present-day and possible future climate. The analysis of extreme values (EVs) is based on the assumption that the extremes of daily precipitation and near-surface temperature are well fitted by the Generalized Pareto distribution (GPD). Return values of extreme daily events are determined using the method of L-moments. Particular emphasis is laid on the evaluation of the return values with respect to the uncertainty range of the estimate as derived from a Monte Carlo sampling approach. During the most recent 25 years the MTR has become dryer in spring but more humid especially in the western part in autumn and winter. At the same time, the whole region has been subject to a substantial warming. The strongest rainfall extremes are simulated in autumn over the Mediterranean Sea around Italy. Temperature extremes are most pronounced over the land masses, especially over northern Africa. Given the large uncertainty of the EV estimate, only 1-year return values are further analysed. During recent decades, statistically significant changes in extremes are only found for temperature. Future climate conditions may come along with a decrease in mean and extreme precipitation during the cold season, whereas an intensification of the hydrological cycle is predicted in summer and autumn. Temperature is predominantly affected over the Iberian Peninsula and the eastern part of the MTR. In many grid boxes, the signals are blurred out due to the large amount of uncertainty in the EV estimate. Thus, a careful analysis is required when making inferences about the future
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How extreme is enough to cause a threshold response of ecosystem
Niu, S.; Zhang, F.; Yang, Q.; Song, B.; Sun, J.
2017-12-01
Precipitation is a primary determinant of terrestrial ecosystem productivity over much of the globe. Recent studies have shown asymmetric or threshold responses of ecosystem productivity to precipitation gradient. However, it's not clear how extreme is enough to cause a threshold response of ecosystem. We conducted a global meta-analysis of precipitation experiments, a site level precipitation gradient experiment, and a remote sensing data mining on the relationship between precipitation extreme vs NDVI extreme. The meta-analysis shows that ANPP, BNPP, NEE, and other carbon cycle variables, showed similar response magnitudes to either precipitation increase or decrease when precipitation levels were normalized to the medium value of treatments (40%) across all the studies. Overall, the response ratios of these variables were linearly correlated with changes in precipitation amounts and soil water content. In the field gradient study with treatments of 1/12, 1/8. 1/4, 1/2, control, and 5/4 of ambient precipitation, the threshold of NPP, SR, NEE occurred when precipitation was reduced to the level of 1/8-1/12 of ambient precipitation. This means that only extreme drought can induce a threshold response of ecosystem. The regional remote sensing data showed that climate extremes with yearly low precipitation from 1982 to 2013 rarely cause extreme responses of vegetation, further suggesting that it is very difficult to detect threshold responses to natural climatic fluctuation. Our three studies together indicate that asymmetrical responses of vegetation to precipitation are likely detected, but only in very extreme precipitation events.
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Glisan, J. M.; Gutowski, W. J.; Higgins, M.; Cassano, J. J.
2011-12-01
Pan-Arctic WRF (PAW) simulations produced using the 50-km wr50a domain developed for the fully-coupled Regional Arctic Climate Model (RACM) were found to produce deep atmospheric circulation biases over the northern Pacific Ocean, manifested in pressure, geopotential height, and temperature fields. Various remedies were unsuccessfully tested to correct these large biases, such as modifying the physical domain or using different initial/boundary conditions. Spectral (interior) nudging was introduced as a way of constraining the model to be more consistent with observed behavior. However, such control over numerical model behavior raises concerns over how much nudging may affect unforced variability and extremes. Strong nudging may reduce or filter out extreme events, since the nudging pushes the model toward a relatively smooth, large-scale state. The question then becomes - what is the minimum spectral nudging needed to correct the biases occurring on the RACM domain while not limiting PAW simulation of extreme events? To determine this, case studies were devised, using a six-member PAW ensemble on the RACM grid with varying spectral nudging strength. Two simulations were run, one in the cold season (January 2007) and one in a warm season (July 2007). Precipitation and 2-m temperature fields were extracted from the output and analyzed to determine how changing spectral nudging strength impacts both temporal and spatial temperature and precipitation extremes. The maximum and minimum temperatures at each point from among the ensemble members were examined, on the 95th confidence interval. The maximum and minimums over the simulation period will also be considered. Results suggest that there is a marked lack of sensitivity to the degrees of nudging. Moreover, it appears nudging strength can be considerably smaller than the standard strength and still produce reliably good simulations.
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Global patterns of NDVI-indicated vegetation extremes and their sensitivity to climate extremes
International Nuclear Information System (INIS)
Liu Guo; Liu Hongyan; Yin Yi
2013-01-01
Extremes in climate have significant impacts on ecosystems and are expected to increase under future climate change. Extremes in vegetation could capture such impacts and indicate the vulnerability of ecosystems, but currently have not received a global long-term assessment. In this study, a robust method has been developed to detect significant extremes (low values) in biweekly time series of global normalized difference vegetation index (NDVI) from 1982 to 2006 and thus to acquire a global pattern of vegetation extreme frequency. This pattern coincides with vegetation vulnerability patterns suggested by earlier studies using different methods over different time spans, indicating a consistent mechanism of regulation. Vegetation extremes were found to aggregate in Amazonia and in the semi-arid and semi-humid regions in low and middle latitudes, while they seldom occurred in high latitudes. Among the environmental variables studied, extreme low precipitation has the highest slope against extreme vegetation. For the eight biomes analyzed, these slopes are highest in temperate broadleaf forest and temperate grassland, suggesting a higher sensitivity in these environments. The results presented here contradict the hypothesis that vegetation in water-limited semi-arid and semi-humid regions might be adapted to drought and suggest that vegetation in these regions (especially temperate broadleaf forest and temperate grassland) is highly prone to vegetation extreme events under more severe precipitation extremes. It is also suggested here that more attention be paid to precipitation-induced vegetation changes than to temperature-induced events. (letter)
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Hong-Li Ren; Pengfei Ren
2017-01-01
The impact of Madden–Julian oscillation (MJO) upon extreme rainfall in southern China was studied using the Real-time Multivariate MJO (RMM) index and daily precipitation data from high-resolution stations in China. The probability-distribution function (PDF) of November–March rainfall in southern China was found to be skewed toward larger (smaller) values in phases 2–3 (6–7) of MJO, during which the probability of extreme rainfall events increased (reduced) by 30–50% (20–40%) relative to all...
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Directory of Open Access Journals (Sweden)
Charles Onyutha
2017-10-01
Full Text Available Some of the problems in drought assessments are that: analyses tend to focus on coarse temporal scales, many of the methods yield skewed indices, a few terminologies are ambiguously used, and analyses comprise an implicit assumption that the observations come from a stationary process. To solve these problems, this paper introduces non-stationary frequency analyses of quantiles. How to use non-parametric rescaling to obtain robust indices that are not (or minimally skewed is also introduced. To avoid ambiguity, some concepts on, e.g., incidence, extremity, etc., were revisited through shift from monthly to daily time scale. Demonstrations on the introduced methods were made using daily flow and precipitation insufficiency (precipitation minus potential evapotranspiration from the Blue Nile basin in Africa. Results show that, when a significant trend exists in extreme events, stationarity-based quantiles can be far different from those when non-stationarity is considered. The introduced non-parametric indices were found to closely agree with the well-known standardized precipitation evapotranspiration indices in many aspects but skewness. Apart from revisiting some concepts, the advantages of the use of fine instead of coarse time scales in drought assessment were given. The links for obtaining freely downloadable tools on how to implement the introduced methods were provided.
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Costa, Veber; Fernandes, Wilson
2017-11-01
Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods
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Localized Multi-Model Extremes Metrics for the Fourth National Climate Assessment
Thompson, T. R.; Kunkel, K.; Stevens, L. E.; Easterling, D. R.; Biard, J.; Sun, L.
2017-12-01
We have performed localized analysis of scenario-based datasets for the Fourth National Climate Assessment (NCA4). These datasets include CMIP5-based Localized Constructed Analogs (LOCA) downscaled simulations at daily temporal resolution and 1/16th-degree spatial resolution. Over 45 temperature and precipitation extremes metrics have been processed using LOCA data, including threshold, percentile, and degree-days calculations. The localized analysis calculates trends in the temperature and precipitation extremes metrics for relatively small regions such as counties, metropolitan areas, climate zones, administrative areas, or economic zones. For NCA4, we are currently addressing metropolitan areas as defined by U.S. Census Bureau Metropolitan Statistical Areas. Such localized analysis provides essential information for adaptation planning at scales relevant to local planning agencies and businesses. Nearly 30 such regions have been analyzed to date. Each locale is defined by a closed polygon that is used to extract LOCA-based extremes metrics specific to the area. For each metric, single-model data at each LOCA grid location are first averaged over several 30-year historical and future periods. Then, for each metric, the spatial average across the region is calculated using model weights based on both model independence and reproducibility of current climate conditions. The range of single-model results is also captured on the same localized basis, and then combined with the weighted ensemble average for each region and each metric. For example, Boston-area cooling degree days and maximum daily temperature is shown below for RCP8.5 (red) and RCP4.5 (blue) scenarios. We also discuss inter-regional comparison of these metrics, as well as their relevance to risk analysis for adaptation planning.
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Early warnings of extreme winds using the ECMWF Extreme Forecast Index
Petroliagis, Thomas I.; Pinson, Pierre
2014-01-01
The European FP7 SafeWind Project aims at developing research towards a European vision of wind power forecasting, which requires advanced meteorological support concerning extreme wind events. This study is focused mainly on early warnings of extreme winds in the early medium-range. Three synoptic stations (airports) of North Germany (Bremen, Hamburg and Hannover) were considered for the construction of time series of daily maximum wind speeds. All daily wind extremes were found to be linked...
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changes in indices of daily temperature and precipitation extremes
African Journals Online (AJOL)
Dr A.B.Ahmed
increased risk of more intense, more frequent and longer-lasting heat waves in a ... present climate will experience the greatest increase in heat wave severity in ... often cause population displacement, and diseases outbreaks are very peculiar .... Most of the definitions for the indices were presented in the work of Peterson ...
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Dayan, U.; Nissen, K.; Ulbrich, U.
2015-11-01
This review discusses published studies of heavy rainfall events over the Mediterranean Basin, combining them in a more general picture of the dynamic and thermodynamic factors and processes that produce heavy rain storms. It distinguishes the western and eastern Mediterranean in order to point out specific regional peculiarities. The crucial moisture for developing intensive convection over these regions can be originated not only from the adjacent Mediterranean Sea but also from distant upwind sources. Transport from remote sources is usually in the mid-tropospheric layers and associated with specific features and patterns of the larger-scale circulations. The synoptic systems (tropical and extratropical) that account for most of the major extreme precipitation events and the coupling of circulation and extreme rainfall patterns are presented. Heavy rainfall over the Mediterranean Basin is caused at times in concert by several atmospheric processes working at different atmospheric scales, such as local convection, upper synoptic-scale-level troughs, and mesoscale convective systems. Under tropical air-mass intrusions, convection generated by static instability seems to play a more important role than synoptic-scale vertical motions. Locally, the occurrence of torrential rains and their intensity is dependent on factors such as temperature profiles and implied instability, atmospheric moisture, and lower-level convergence.
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Directory of Open Access Journals (Sweden)
Yong Huang
2013-12-01
Full Text Available The latest Version-7 (V7 Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA products were released by the National Aeronautics and Space Administration (NASA in December of 2012. Their performance on different climatology, locations, and precipitation types is of great interest to the satellite-based precipitation community. This paper presents a study of TMPA precipitation products (3B42RT and 3B42V7 for an extreme precipitation event in Beijing and its adjacent regions (from 00:00 UTC 21 July 2012 to 00:00 UTC 22 July 2012. Measurements from a dense rain gauge network were used as the ground truth to evaluate the latest TMPA products. Results are summarized as follows. Compared to rain gauge measurements, both 3B42RT and 3B42V7 generally captured the rainfall spatial and temporal pattern, having a moderate spatial correlation coefficient (CC, 0.6 and high CC values (0.88 over the broader Hebei, Beijing and Tianjin (HBT regions, but the rainfall peak is 6 h ahead of gauge observations. Overall, 3B42RT showed higher estimation than 3B42V7 over both HBT and Beijing. At the storm center, both 3B42RT and 3B42V7 presented a relatively large deviation from the temporal variation of rainfall and underestimated the storm by 29.02% and 36.07%, respectively. The current study suggests that the latest TMPA products still have limitations in terms of resolution and accuracy, especially for this type of extreme event within a latitude area on the edge of coverage of TRMM precipitation radar and microwave imager. Therefore, TMPA users should be cautious when 3B42RT and 3B42V7 are used to model, monitor, and forecast both flooding hazards in the Beijing urban area and landslides in the mountainous west and north of Beijing.
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INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles
Opitz, Thomas
2018-05-25
This work is motivated by the challenge organized for the 10th International Conference on Extreme-Value Analysis (EVA2017) to predict daily precipitation quantiles at the 99.8% level for each month at observed and unobserved locations. Our approach is based on a Bayesian generalized additive modeling framework that is designed to estimate complex trends in marginal extremes over space and time. First, we estimate a high non-stationary threshold using a gamma distribution for precipitation intensities that incorporates spatial and temporal random effects. Then, we use the Bernoulli and generalized Pareto (GP) distributions to model the rate and size of threshold exceedances, respectively, which we also assume to vary in space and time. The latent random effects are modeled additively using Gaussian process priors, which provide high flexibility and interpretability. We develop a penalized complexity (PC) prior specification for the tail index that shrinks the GP model towards the exponential distribution, thus preventing unrealistically heavy tails. Fast and accurate estimation of the posterior distributions is performed thanks to the integrated nested Laplace approximation (INLA). We illustrate this methodology by modeling the daily precipitation data provided by the EVA2017 challenge, which consist of observations from 40 stations in the Netherlands recorded during the period 1972–2016. Capitalizing on INLA’s fast computational capacity and powerful distributed computing resources, we conduct an extensive cross-validation study to select the model parameters that govern the smoothness of trends. Our results clearly outperform simple benchmarks and are comparable to the best-scoring approaches of the other teams.
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Brett, M.; Mattey, D.; Stephens, M.
2015-12-01
Oxygen isotopes in speleothem provide opportunities to construct precisely dated records of palaeoclimate variability, underpinned by an understanding of both the regional climate and local controls on isotopes in rainfall and groundwater. For tropical islands, a potential means to reconstruct past rainfall variability is to exploit the generally high correlation between rainfall amount and δ18O: the 'amount effect'. The GNIP program provides δ18O data at monthly resolution for several tropical Pacific islands but there are few data for precipitation isotopes at daily resolution, for investigating the amount effect over different timescales in a tropical maritime setting. Timescales are important since meteoric water feeding a speleothem has undergone storage and mixing in the aquifer system and understanding how the isotope amount effect is preserved in aquifer recharge has fundamental implications on the interpretation of speleothem δ18O in terms of palaeo-precipitation. The islands of Fiji host speleothem caves. Seasonal precipitation is related to the movement of the South Pacific Convergence Zone, and interannual variations in rainfall are coupled to ENSO behaviour. Individual rainfall events are stratiform or convective, with proximal moisture sources. We have daily resolution isotope data for rainfall collected at the University of the South Pacific in Suva, covering every rain event in 2012 and 2013. δ18O varies between -18‰ and +3‰ with the annual weighted averages at -7.6‰ and -6.8‰ respectively, while total recorded rainfall amount is similar in both years. We shall present analysis of our data compared with GNIP, meteorological data and back trajectory analyses to demonstrate the nature of the relationship between rainfall amount and isotopic signatures over this short timescale. Comparison with GNIP data for 2012-13 will shed light on the origin of the amount effect at monthly and seasonal timescales in convective, maritime, tropical
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Fung, K. Y.; Tam, C. Y.; Wang, Z.
2017-12-01
It is well known that urban land use can significantly influence the local temperature, precipitation and meteorology through altering land-atmosphere exchange of momentum, moisture and heat in urban areas. In recent decades, there has been a substantial increase ( 5-10%) on the intensity of extreme rainfall over Southeast China; it is projected to increase further according to the latest IPCC reports. In this study, we assess how urbanization and global warming together might impact on heavy precipitation characteristics over the highly urbanized Pearl River Delta (PRD) megacity, located in southern China. This is done by dynamically downscaling GFDL-ESM2M simulations for the present and future (RCP8.5) climate scenarios, using the Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model (UCM). Over the PRD area, the WRF model is integrated at a resolution of 2km x 2km. To focus on extreme events, episodes covering daily rainfall intensity above the 99th percentile in Southeast China in the GFDL-ESM2M daily precipitation datasets were first identified. These extreme episodes were then dynamically downscaled in two parallel experiments with the following model designs: one with anthropogenic heat flux (AH) = 0 Wm-2 and the other with peak AH = 300 Wm-2 in the AH diurnal cycle over the urban domain. Results show that, with AH in urban area, the urban 2m-temperature can rise by about 2oC. This in turn leads to an increase of the mean as well as the extreme rain rates by 10-15% in urban domain. The latter is comparable to the impact of global warming alone, according to downscaling experiments for the RCP8.5 scenario. Implications of our results on urban effects on extreme rainfall under a warming background climate will be discussed.
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Tolen, J.; Kodra, E. A.; Ganguly, A. R.
2011-12-01
The assertion that higher-resolution experiments or more sophisticated process models within the IPCC AR5 CMIP5 suite of global climate model ensembles improves precipitation projections over the IPCC AR4 CMIP3 suite remains a hypothesis that needs to be rigorously tested. The questions are particularly important for local to regional assessments at scales relevant for the management of critical infrastructures and key resources, particularly for the attributes of sever precipitation events, for example, the intensity, frequency and duration of extreme precipitation. Our case study is South America, where precipitation and their extremes play a central role in sustaining natural, built and human systems. To test the hypothesis that CMIP5 improves over CMIP3 in this regard, spatial and temporal measures of prediction skill are constructed and computed by comparing climate model hindcasts with the NCEP-II reanalysis data, considered here as surrogate observations, for the entire globe and for South America. In addition, gridded precipitation observations over South America based on rain gage measurements are considered. The results suggest that the utility of the next-generation of global climate models over the current generation needs to be carefully evaluated on a case-by-case basis before communicating to resource managers and policy makers.
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Carreau, J.; Naveau, P.; Neppel, L.
2017-05-01
The French Mediterranean is subject to intense precipitation events occurring mostly in autumn. These can potentially cause flash floods, the main natural danger in the area. The distribution of these events follows specific spatial patterns, i.e., some sites are more likely to be affected than others. The peaks-over-threshold approach consists in modeling extremes, such as heavy precipitation, by the generalized Pareto (GP) distribution. The shape parameter of the GP controls the probability of extreme events and can be related to the hazard level of a given site. When interpolating across a region, the shape parameter should reproduce the observed spatial patterns of the probability of heavy precipitation. However, the shape parameter estimators have high uncertainty which might hide the underlying spatial variability. As a compromise, we choose to let the shape parameter vary in a moderate fashion. More precisely, we assume that the region of interest can be partitioned into subregions with constant hazard level. We formalize the model as a conditional mixture of GP distributions. We develop a two-step inference strategy based on probability weighted moments and put forward a cross-validation procedure to select the number of subregions. A synthetic data study reveals that the inference strategy is consistent and not very sensitive to the selected number of subregions. An application on daily precipitation data from the French Mediterranean shows that the conditional mixture of GPs outperforms two interpolation approaches (with constant or smoothly varying shape parameter).
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Climate Prediction Center (CPC) Global Precipitation Time Series
National Oceanic and Atmospheric Administration, Department of Commerce — The global precipitation time series provides time series charts showing observations of daily precipitation as well as accumulated precipitation compared to normal...
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Amazon River Basin Precipitation, 1972-1992
National Aeronautics and Space Administration — ABSTRACT: The precipitation data is 0.2 degree gridded monthly precipitation data based upon monthly rain data from Peru and Bolivia and daily rain data from Brazil....
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Dhakal, A. S.; Adera, S.
2017-12-01
Accurate daily streamflow prediction in ungauged watersheds with sparse information is challenging. The ability of a hydrologic model calibrated using nearby gauged watersheds to predict streamflow accurately depends on hydrologic similarities between the gauged and ungauged watersheds. This study examines daily streamflow predictions using the Precipitation-Runoff Modeling System (PRMS) for the largely ungauged San Antonio Creek watershed, a 96 km2 sub-watershed of the Alameda Creek watershed in Northern California. The process-based PRMS model is being used to improve the accuracy of recent San Antonio Creek streamflow predictions generated by two empirical methods. Although San Antonio Creek watershed is largely ungauged, daily streamflow data exists for hydrologic years (HY) 1913 - 1930. PRMS was calibrated for HY 1913 - 1930 using streamflow data, modern-day land use and PRISM precipitation distribution, and gauged precipitation and temperature data from a nearby watershed. The PRMS model was then used to generate daily streamflows for HY 1996-2013, during which the watershed was ungauged, and hydrologic responses were compared to two nearby gauged sub-watersheds of Alameda Creek. Finally, the PRMS-predicted daily flows between HY 1996-2013 were compared to the two empirically-predicted streamflow time series: (1) the reservoir mass balance method and (2) correlation of historical streamflows from 80 - 100 years ago between San Antonio Creek and a nearby sub-watershed located in Alameda Creek. While the mass balance approach using reservoir storage and transfers is helpful for estimating inflows to the reservoir, large discrepancies in daily streamflow estimation can arise. Similarly, correlation-based predicted daily flows which rely on a relationship from flows collected 80-100 years ago may not represent current watershed hydrologic conditions. This study aims to develop a method of streamflow prediction in the San Antonio Creek watershed by examining PRMS
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Sanders, Michael J.; Markstrom, Steven L.; Regan, R. Steven; Atkinson, R. Dwight
2017-09-15
A module for simulation of daily mean water temperature in a network of stream segments has been developed as an enhancement to the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS). This new module is based on the U.S. Fish and Wildlife Service Stream Network Temperature model, a mechanistic, one-dimensional heat transport model. The new module is integrated in PRMS. Stream-water temperature simulation is activated by selection of the appropriate input flags in the PRMS Control File and by providing the necessary additional inputs in standard PRMS input files.This report includes a comprehensive discussion of the methods relevant to the stream temperature calculations and detailed instructions for model input preparation.
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Estimating Tropical Cyclone Precipitation from Station Observations
Institute of Scientific and Technical Information of China (English)
REN Fumin; WANG Yongmei; WANG Xiaoling; LI Weijing
2007-01-01
In this paper, an objective technique for estimating the tropical cyclone (TC) precipitation from station observations is proposed. Based on a comparison between the Original Objective Method (OOM) and the Expert Subjective Method (ESM), the Objective Synoptic Analysis Technique (OSAT) for partitioning TC precipitation was developed by analyzing the western North Pacific (WNP) TC historical track and the daily precipitation datasets. Being an objective way of the ESM, OSAT overcomes the main problems in OOM,by changing two fixed parameters in OOM, the thresholds for the distance of the absolute TC precipitation (D0) and the TC size (D1), into variable parameters.Case verification for OSAT was also carried out by applying CMORPH (Climate Prediction Center MORPHing technique) daily precipitation measurements, which is NOAA's combined satellite precipitation measurement system. This indicates that OSAT is capable of distinguishing simultaneous TC precipitation rain-belts from those associated with different TCs or with middle-latitude weather systems.
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Importance of resolution and model configuration when downscaling extreme precipitation
Directory of Open Access Journals (Sweden)
Adrian J. Champion
2014-07-01
Full Text Available Dynamical downscaling is frequently used to investigate the dynamical variables of extra-tropical cyclones, for example, precipitation, using very high-resolution models nested within coarser resolution models to understand the processes that lead to intense precipitation. It is also used in climate change studies, using long timeseries to investigate trends in precipitation, or to look at the small-scale dynamical processes for specific case studies. This study investigates some of the problems associated with dynamical downscaling and looks at the optimum configuration to obtain the distribution and intensity of a precipitation field to match observations. This study uses the Met Office Unified Model run in limited area mode with grid spacings of 12, 4 and 1.5 km, driven by boundary conditions provided by the ECMWF Operational Analysis to produce high-resolution simulations for the Summer of 2007 UK flooding events. The numerical weather prediction model is initiated at varying times before the peak precipitation is observed to test the importance of the initialisation and boundary conditions, and how long the simulation can be run for. The results are compared to raingauge data as verification and show that the model intensities are most similar to observations when the model is initialised 12 hours before the peak precipitation is observed. It was also shown that using non-gridded datasets makes verification more difficult, with the density of observations also affecting the intensities observed. It is concluded that the simulations are able to produce realistic precipitation intensities when driven by the coarser resolution data.
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Jouve, Guillaume; Vidal, Laurence; Adallal, Rachid; Bard, Edouard; Benkaddour, Abdel; Chapron, Emmanuel; Courp, Thierry; Dezileau, Laurent; Hébert, Bertil; Rhoujjati, Ali; Simonneau, Anaelle; Sonzogni, Corinne; Sylvestre, Florence; Tachikawa, Kazuyo; Viry, Elisabeth
2016-04-01
Since the 1990s, the Mediterranean basin undergoes an increase in precipitation events and extreme droughts likely to intensify in the XXI century, and whose origin is attributable to human activities since 1850 (IPCC, 2013). Regional climate models indicate a strengthening of flood episodes at the end of the XXI century in Morocco (Tramblay et al, 2012). To understand recent hydrological and paleohydrological variability in North Africa, our study focuses on the macro- and micro-scale analysis of sedimentary sequences from Lake Azigza (Moroccan Middle Atlas Mountains) covering the last few centuries. This lake is relevant since local site monitoring revealed that lake water table levels were correlated with precipitation regime (Adallal R., PhD Thesis in progress). The aim of our study is to distinguish sedimentary facies characteristic of low and high lake levels, in order to reconstruct past dry and wet periods during the last two hundred years. Here, we present results from sedimentological (lithology, grain size, microstructures under thin sections), geochemical (XRF) and physical (radiography) analyses on short sedimentary cores (64 cm long) taken into the deep basin of Lake Azigza (30 meters water depth). Cores have been dated (radionuclides 210Pb, 137Cs, and 14C dating). Two main facies were distinguished: one organic-rich facies composed of wood fragments, several reworked layers and characterized by Mn peaks; and a second facies composed of terrigenous clastic sediments, without wood nor reworked layers, and characterized by Fe, Ti, Si and K peaks. The first facies is interpreted as a high lake level stand. Indeed, the highest paleoshoreline is close to the vegetation, and steeper banks can increase the current velocity, allowing the transport of wood fragments in case of extreme precipitation events. Mn peaks are interpreted as Mn oxides precipitations under well-oxygenated deep waters after runoff events. The second facies is linked to periods of
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Ricko, Martina; Adler, Robert F.; Huffman, George J.
2016-01-01
Climatology and variations of recent mean and intense precipitation over a near-global (50 deg. S 50 deg. N) domain on a monthly and annual time scale are analyzed. Data used to derive daily precipitation to examine the effects of spatial and temporal coverage of intense precipitation are from the current Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 version 7 precipitation product, with high spatial and temporal resolution during 1998 - 2013. Intense precipitation is defined by several different parameters, such as a 95th percentile threshold of daily precipitation, a mean precipitation that exceeds that percentile, or a fixed threshold of daily precipitation value [e.g., 25 and 50 mm day(exp -1)]. All parameters are used to identify the main characteristics of spatial and temporal variation of intense precipitation. High correlations between examined parameters are observed, especially between climatological monthly mean precipitation and intense precipitation, over both tropical land and ocean. Among the various parameters examined, the one best characterizing intense rainfall is a fraction of daily precipitation Great than or equal to 25 mm day(exp. -1), defined as a ratio between the intense precipitation above the used threshold and mean precipitation. Regions that experience an increase in mean precipitation likely experience a similar increase in intense precipitation, especially during the El Nino Southern Oscillation (ENSO) events. Improved knowledge of this intense precipitation regime and its strong connection to mean precipitation given by the fraction parameter can be used for monitoring of intense rainfall and its intensity on a global to regional scale.
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PDF added value of a high resolution climate simulation for precipitation
Soares, Pedro M. M.; Cardoso, Rita M.
2015-04-01
dynamical downscaling, based on simple PDF skill scores. The measure can assess the full quality of the PDFs and at the same time integrates a flexible manner to weight differently the PDF tails. In this study we apply the referred method to characaterize the PDF added value of a high resolution simulation with the WRF model. Results from a WRF climate simulation centred at the Iberian Penisnula with two nested grids, a larger one at 27km and a smaller one at 9km. This simulation is forced by ERA-Interim. The observational data used covers from rain gauges precipitation records to observational regular grids of daily precipitation. Two regular gridded precipitation datasets are used. A Portuguese grid precipitation dataset developed at 0.2°× 0.2°, from observed rain gauges daily precipitation. A second one corresponding to the ENSEMBLES observational gridded dataset for Europe, which includes daily precipitation values at 0.25°. The analisys shows an important PDF added value from the higher resolution simulation, regarding the full PDF and the extremes. This method shows higher potential to be applied to other simulation exercises and to evaluate other variables.
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Will the warmer temperature bring the more intensity precipitation?
Yutong, Z., II; Wang, T.
2017-12-01
Will the warmer temperature bring the more intensity precipitation?Over the past several decades, changes in climate are amplified over the Tibetan Plateau(TP), with warming trend almost being twice as large as the global average. In sharp contrast, there is a large spatial discrepancy of the variations in precipitation extremes, with increasing trends found in the southern and decreasing trends in central TP. These features motivate are urgent need for an observation-based understanding of how precipitation extremes respond to climate change. Here we examine the relation between precipitation intensity with atmospheric temperature, dew point temperature (Td) and convective available potential energy (CAPE) in Tibet Plateau. Owing to the influences of the westerlies and Indian monsoon on Tibetan climate, the stations can be divided into three sub-regions in TP: the westerlies region (north of 35°N, N = 28), the monsoon region (south of 30°N in TP, N = 31), and the transition region (located between 30°N and 35°N, N = 48). We found that the intensity precipitation does not follow the C-C relation and there is a mix of positive and negative slope. To better understand why different scaling occurs with temperature in district region, using the dew point temperature replace the temperature, although there is significant variability in relative humidity values, at most stations, there appears to be a general increase in relative humidity associated. It is likely that the observed rise in relative humidity can assist in explaining the negative scaling of extreme precipitation at westerlies domain and monsoon domain, with the primary reason why precipitation extremes expected to increase follows from the fact that a warmer atmosphere can "hold" more moisture. This suggests that not only on how much the moisture the atmosphere can hold, but on how much moisture exits in atmosphere. To understand the role of dynamic on extreme precipitation, we repeat the precipitation
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Background: Combined sewer overflows (CSOs) occur in combined sewer systems when sewage and stormwater runoff discharge into waterbodies potentially contaminating water sources. CSOs are often caused by heavy precipitation and are expected to increase with increasing extreme pre...
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Continuous daily hydrograph simulation using duration curves of a precipitation index
CSIR Research Space (South Africa)
Smakhtin, VY
2000-04-01
Full Text Available precipitation index reflects the current catchment wetness and is defined as a continuous function of precipitation, which accumulates on rainy days and exponentially decays during the periods of no rainfall. The process of rainfall-to-runoff conversion is based...
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Sommer, Philipp S.; Kaplan, Jed O.
2017-10-01
While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject to considerable uncertainty, and represent extremely large data files with associated computational costs of data input/output and file transfer. For periods before the recent past or in the future, global meteorological forcing can be provided by climate model output, but the quality of these data at high temporal resolution is low, particularly for daily precipitation frequency and amount. Here, we present GWGEN, a globally applicable statistical weather generator for the temporal downscaling of monthly climatology to daily meteorology. Our weather generator is parameterized using a global meteorological database and simulates daily values of five common variables: minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN is lightweight, modular, and requires a minimal set of monthly mean variables as input. The weather generator may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models. While GWGEN does not currently perform spatially autocorrelated multi-point downscaling of daily weather, this additional functionality could be implemented in future versions.
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Heating-insensitive scale increase caused by convective precipitation
Haerter, Jan; Moseley, Christopher; Berg, Peter
2017-04-01
The origin of intense convective extremes and their unusual temperature dependence has recently challenged traditional thermodynamic arguments, based on the Clausius-Clapeyron relation. In a sequence of studies (Lenderink and v. Mejgaard, Nat Geosc, 2008; Berg, Haerter, Moseley, Nat Geosc, 2013; and Moseley, Hohenegger, Berg, Haerter, Nat Geosc, 2016) the argument of convective-type precipitation overcoming the 7%/K increase in extremes by dynamical, rather than thermodynamic, processes has been promoted. How can the role of dynamical processes be approached for precipitating convective cloud? One-phase, non-precipitating Rayleigh-Bénard convection is a classical problem in complex systems science. When a fluid between two horizontal plates is sufficiently heated from below, convective rolls spontaneously form. In shallow, non-precipitating atmospheric convection, rolls are also known to form under specific conditions, with horizontal scales roughly proportional to the boundary layer height. Here we explore within idealized large-eddy simulations, how the scale of convection is modified, when precipitation sets in and intensifies in the course of diurnal solar heating. Before onset of precipitation, Bénard cells with relatively constant diameter form, roughly on the scale of the atmospheric boundary layer. We find that the onset of precipitation then signals an approximately linear (in time) increase in horizontal scale. This scale increase progresses at a speed which is rather insensitive to changes in surface temperature or changes in the rate at which boundary conditions change, hinting at spatial characteristics, rather than temperature, as a possible control on spatial scales of convection. When exploring the depth of spatial correlations, we find that precipitation onset causes a sudden disruption of order and a subsequent complete disintegration of organization —until precipitation eventually ceases. Returning to the initial question of convective
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The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields
Zhao, Y.; Estes, L. D.; Vergopolan, N.
2017-12-01
Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water
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Wyard, Coraline; Fettweis, Xavier
2016-04-01
As a consequence of climate change, several studies concluded that winter flood occurrence could increase in the future in many rivers of northern and western Europe in response to an increase in extreme precipitation events. This study aims to determine if trends in extreme hydroclimatic events generating floods can already be detected over the last century. In particular, we focus on the Ourthe River (southeast of Belgium) which is one of the main tributaries of the Meuse River with a catchment area of 3500 km². In this river, most of the floods occur during winter and about 50% of them are due to rainfall events associated with the melting of the snow which covers the Ardennes during winter. In this study, hydroclimatic conditions favorable to flooding were reconstructed over the 20th century using the regional climate model MAR ("Modèle Atmosphérique Régional") forced by the following reanalyses: the ERA-20C, the ERA-Interim and the NCEP/NCAR-v1. The use of the MAR model allows to compute precipitation, snow depth and run-off resulting from precipitation events and snow melting in any part of the Ourthe river catchment area. Therefore, extreme hydroclimatic events, namely extreme run-off events, which could potentially generate floods, can be reconstructed using the MAR model. As validation, the MAR results were compared to weather station-based data. A trend analysis was then performed in order to study the evolution of conditions favorable to flooding in the Ourthe River catchment. The results show that the MAR model allows the detection of more than 95% of the hydroclimatic conditions which effectively generated observed floods in the Ourthe River over the 1974-2014 period. Conditions favorable to flooding present a negative trend over the last 50 years as a result of a decrease in snow accumulation and in extreme precipitation events. However, significance of these trends depends on the reanalysis used to force the regional climate model as well as the
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Bias correction of daily satellite precipitation data using genetic algorithm
Pratama, A. W.; Buono, A.; Hidayat, R.; Harsa, H.
2018-05-01
Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) was producted by blending Satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) with Stasion observations data. The blending process was aimed to reduce bias of CHIRP. However, Biases of CHIRPS on statistical moment and quantil values were high during wet season over Java Island. This paper presented a bias correction scheme to adjust statistical moment of CHIRP using observation precipitation data. The scheme combined Genetic Algorithm and Nonlinear Power Transformation, the results was evaluated based on different season and different elevation level. The experiment results revealed that the scheme robustly reduced bias on variance around 100% reduction and leaded to reduction of first, and second quantile biases. However, bias on third quantile only reduced during dry months. Based on different level of elevation, the performance of bias correction process is only significantly different on skewness indicators.
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Conrey, Reesa Y.; Skagen, Susan K.; Yackel, Amy; Panjabi, Arvind O.
2016-01-01
Climate change elevates conservation concerns worldwide because it is likely to exacerbate many identified threats to animal populations. In recent decades, grassland birds have declined faster than other North American bird species, a loss thought to be due to habitat loss and fragmentation and changing agricultural practices. Climate change poses additional threats of unknown magnitude to these already declining populations. We examined how seasonal and daily weather conditions over 10 years influenced nest survival of five species of insectivorous passerines native to the shortgrass prairie and evaluate our findings relative to future climate predictions for this region. Daily nest survival (n = 870) was best predicted by a combination of daily and seasonal weather variables, age of nest, time in season and bird habitat guild. Within a season, survival rates were lower on very hot days (temperatures ≥ 35 °C), on dry days (with a lag of 1 day) and on stormy days (especially for those species nesting in shorter vegetation). Across years, survival rates were also lower during warmer and drier breeding seasons. Clutch sizes were larger when early spring temperatures were cool and the week prior to egg-laying was wetter and warming. Climate change is likely to exacerbate grassland bird population declines because projected climate conditions include rising temperatures, more prolonged drought and more intense storms as the hydrological cycle is altered. Under varying realistic scenarios, nest success estimates were halved compared to their current average value when models both increased the temperature (3 °C) and decreased precipitation (two additional dry days during a nesting period), thus underscoring a sense of urgency in identifying and addressing the current causes of range-wide declines.
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Intensification of extreme European summer precipitation in a warmer climate
DEFF Research Database (Denmark)
Christensen, O. B.; Christensen, J. H.
2004-01-01
Heavy and/or extended precipitation episodes with subsequent surface runoff can inflict catastrophic property damage and loss of human life. Thus, it is important to determine how the character of such events could change in response to greenhouse gas-induced global warming. Impacts of climate...... warming on severe precipitation events in Europe on a diurnal time scale were investigated with a high-resolution regional climate model for two of the greenhouse gas emission scenarios constructed by the Intergovernmental Panel on Climate Change (IPCC; Nakicenovic, N., et al., 2000, IPCC special report...... models both originating from fully transient climate change simulations. Here, we show that although the summer time precipitation decreases over a substantial part of Europe in the scenarios analysed, an increase in the amount of precipitation exceeding the present-day 99th and in most cases even the 95...
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Sulca, J. C.; Vuille, M. F.; Silva, F. Y.; Takahashi, K.
2013-12-01
Knowledge about changes in regional circulation and physical processes associated with extreme rainfall events in South America is limited. Here we investigate such events over the Mantaro basin (MB) located at (10°S-13°S; 73°W-76°W) in the central Peruvian Andes and Northeastern Brazil (NEB), located at (9°S-15°S; 39°W-46°W). Occasional dry and wet spells can be observed in both areas during the austral summer season. The main goal of this study is to investigate potential teleconnections between extreme rainfall events in MB and NEB during austral summer. We define wet (dry) spells as periods that last for at least 3 (5) consecutive days with rainfall above (below) the 70 (30) percentile. To identify the dates of ocurrence of these events, we used daily accumulated rainfall data from 14 climate stations located in the Mantaro basin for the period 1965 to 2002. In NEB we defined a rainfall index which is based on average daily gridded rainfall data within the region for the same period. Dry (wet spells) in the MB are associated with positive (negative) OLR anomalies which extend over much of the tropical Andes, indicating the large-scale nature of these events. At 200 hPa anomalous easterly (westerly) zonal winds aloft accompany wet (dry) spells. Composite anomalies of dry spells in MB reveal significant contemporaneous precipitation anomalies of the opposite sign over NEB, which suggest that intraseasonal precipitation variability over the two regions may be dynamically linked. Indeed upper-tropospheric circulation anomalies over the central Andes extend across South America and appear to be tied to an adjustment in the Bolivian High-Nordeste Low system. Dry (wet) spells in NEB are equally associated with a large-scale pattern of positive (negative) OLR anomalies; however, there are no related significant OLR anomalies over the MB during these events. Dry (wet) spells are associated with robust patterns of anomalous wind fields at both low and upper
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Atmospheric tides and periodic variations in the precipitation field
International Nuclear Information System (INIS)
Cevolani, G.; Bacci, P.; Bonelli, P.; Isnardi, C.
1986-01-01
The analysis of daily precipitations data at many weather stations in Alpes and Po Valley gives evidence of a ''tidal'' influence from luni-solar gravitational fields. The tidal influence does not appear to be strictly constant with time, as the possible results of a modulation effect of luni-solar cycles having similar periods. Time variations of daily precipitation data as a function of some particular cycles show that gravitational tides effect heavy rainfalls more than mean precipitation values
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MSU (Microwave Sounding Unit) Daily Troposphere Temperatures and Precipitation
National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of two MSU tropospheric temperatures levels and precipitation which are described in detail below. The NOAA satellites contributing to this...
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Mahony, C. R.; Cannon, A. J.
2017-12-01
Climate change can drive local climates outside the range of their historical year-to-year variability, straining the adaptive capacity of ecological and human communities. We demonstrate that interactions between climate variables can produce larger and earlier departures from natural variability than is detectable in individual variables. For example, summer temperature (Tx) and precipitation (Pr) are negatively correlated in most terrestrial regions, such that interannual variability lies along an axis from warm-and-dry to cool-and-wet conditions. A climate change trend perpendicular to this axis, towards warmer-wetter conditions, can depart more quickly from the range of natural variability than a warmer-drier trend. This multivariate "departure intensification" effect is evident in all six CMIP5 models that we examined: 23% (9-34%) of the land area of each model exhibits a pronounced increase in 2σ extremesin the Tx-Pr regime relative to Tx or Pr alone. Observational data suggest that Tx-Pr correlations are sufficient to produce departure intensification in distinct regions on all continents. Departures from the historical Tx-Pr regime may produce ecological disruptions, such as in plant-pathogen interactions and human diseases, that could offset the drought mitigation benefits of increased precipitation. Our study alerts researchers and adaptation practitioners to the presence of multivariate climate change signals and compound extremes that are not detectable in individual climate variables.
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Compound summer temperature and precipitation extremes over central Europe
Sedlmeier, Katrin; Feldmann, H.; Schädler, G.
2018-02-01
Reliable knowledge of the near-future climate change signal of extremes is important for adaptation and mitigation strategies. Especially compound extremes, like heat and drought occurring simultaneously, may have a greater impact on society than their univariate counterparts and have recently become an active field of study. In this paper, we use a 12-member ensemble of high-resolution (7 km) regional climate simulations with the regional climate model COSMO-CLM over central Europe to analyze the climate change signal and its uncertainty for compound heat and drought extremes in summer by two different measures: one describing absolute (i.e., number of exceedances of absolute thresholds like hot days), the other relative (i.e., number of exceedances of time series intrinsic thresholds) compound extreme events. Changes are assessed between a reference period (1971-2000) and a projection period (2021-2050). Our findings show an increase in the number of absolute compound events for the whole investigation area. The change signal of relative extremes is more region-dependent, but there is a strong signal change in the southern and eastern parts of Germany and the neighboring countries. Especially the Czech Republic shows strong change in absolute and relative extreme events.
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Analysis of impacts on hydrometeorological extremes in the Senegal River Basin from REMO RCM
Energy Technology Data Exchange (ETDEWEB)
Galiano, Sandra Garcia; Osorio, Juan Diego Giraldo [Technical Univ. of Cartagena, Dept. of Thermal Engineering and Fluids, Cartagena (Spain)
2010-06-15
West Africa is highly vulnerable to climate variability. The precipitation latitudinal gradient determines agricultural activities. The cultivated area of the Sahel is a densely populated region, whereas flood recession agriculture is practiced in the Senegal River Valley. The present study analyses both spatial-temporal rainfall patterns of the REMO Regional Climate Model (RCM) and observed rainfall data, focusing in particular on extreme hydro-meteorological phenomena. An analysis of simulated daily rainfall data was performed to determine the frequency and magnitude of length of dry spells, as well as the extreme rainfall events. A projected annual decrease in rainfall on horizon 2050 could be explained by two factors: the decrease in the percentage of rainy days on both west and north sides of the basin, and the decrease of precipitation amount for rainy days in the southern basin. Finally, an increase in the frequency of dry spell in the monsoon season by 2050 is projected. Such findings are significant in a framework of strategies for water resources management and planning at basin scale, in order to build adaptive capacity. (orig.)
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Prevailing trends of climatic extremes across Indus-Delta of Sindh-Pakistan
Abbas, Farhat; Rehman, Iqra; Adrees, Muhammad; Ibrahim, Muhammad; Saleem, Farhan; Ali, Shafaqat; Rizwan, Muhammad; Salik, Muhammad Raza
2018-02-01
This study examines the variability and change in the patterns of climatic extremes experienced in Indus-Delta of Sindh province of Pakistan, comprising regions of Karachi, Badin, Mohenjodaro, and Rohri. The homogenized daily minimum and maximum temperature and precipitation data for a 36-year period were used to calculate 13 and 11 indices of temperature and precipitation extremes with the help of RClimDex, a program written in the statistical software package R. A non-parametric Mann-Kendall test and Sen's slope estimates were used to determine the statistical significance and magnitude of the calculated trend. Temperatures of summer days and tropical nights increased in the region with overall significant warming trends for monthly maximum temperature as well as for warm days and nights reflecting dry conditions in the study area. The warm extremes and nighttime temperature indices showed greater trends than cold extremes and daytime indices depicting an overall warming trends in the Delta. Historic decrease in the acreage of major crops and over 33% decrease in agriculture credit for Sindh are the indicators of adverse impacts of warmer and drier weather on Sindh agriculture. Trends reported for Karachi and Badin are expected to decrease rice cultivation, hatching of fisheries, and mangroves forest surrounding these cities. Increase in the prevailing temperature trends will lead to increasingly hotter and drier summers resulting to constraints on cotton, wheat, and rice yield in Rohri and Mohenjodaro areas due to increased crop water requirements that may be met with additional groundwater pumping; nonetheless, the depleted groundwater resources would have a direct impact on the region's economy.
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The synergistic effect of manure supply and extreme precipitation on surface water quality
Motew, Melissa; Booth, Eric G.; Carpenter, Stephen R.; Chen, Xi; Kucharik, Christopher J.
2018-04-01
Over-enrichment of phosphorus (P) in agroecosystems contributes to eutrophication of surface waters. In the Midwest US and elsewhere, climate change is increasing the frequency of high-intensity precipitation events, which can serve as a primary conduit of P transport within watersheds. Despite uncertainty in their estimates, process-based watershed models are important tools that help characterize watershed hydrology and biogeochemistry and scale up important mechanisms affecting water quality. Using one such model developed for an agricultural watershed in Wisconsin, we conducted a 2 × 2 factorial experiment to test the effects of (high/low) terrestrial P supply (PSUP) and (high/low) precipitation intensity (PREC) on surface water quality. Sixty-year simulations were conducted for each of the four runs, with annual results obtained for watershed average P yield and concentration at the field scale (220 × 220 m grid cells), P load and concentration at the stream scale, and summertime total P concentration (TP) in Lake Mendota. ANOVA results were generated for the 2 × 2 factorial design, with PSUP and PREC treated as categorical variables. The results showed a significant, positive interaction (p loss may have important ecological consequences because dissolved P is highly bioavailable. Overall, the results suggest that high levels of terrestrial P supplied as manure can exacerbate water quality problems in the future as the frequency of high-intensity rainfall events increases with a changing climate. Conversely, lowering terrestrial manure P supply may help improve the resilience of surface water quality to extreme events.
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Local short-duration precipitation extremes in Sweden: observations, forecasts and projections
Olsson, Jonas; Berg, Peter; Simonsson, Lennart
2015-04-01
Local short-duration precipitation extremes (LSPEs) are a key driver of hydrological hazards, notably in steep catchments with thin soils and in urban environments. The triggered floodings, landslides, etc., have large consequences for society in terms of both economy and health. Accurate estimations of LSPEs on both climatological time-scales (past, present, future) and in real-time is thus of great importance for improved hydrological predictions as well as design of constructions and infrastructure affected by hydrological fluxes. Analysis of LSPEs is, however, associated with various limitations and uncertainties. These are to a large degree associated with the small-scale nature of the meteorological processes behind LSPEs and the associated requirements on observation sensors as well as model descriptions. Some examples of causes for the limitations involved are given in the following. - Observations: High-resolution data sets available for LSPE analyses are often limited to either relatively long series from one or a few stations or relatively short series from larger station networks. Radar data have excellent resolutions in both time and space but the estimated local precipitation intensity is still highly uncertain. New and promising techniques (e.g. microwave links) are still in their infancy. - Weather forecasts (short-range): Although forecasts with the required spatial resolution for potential generation of LSPEs (around 2-4 km) are becoming operationally available, the actual forecast precision of LSPEs is largely unknown. Forecasted LSPEs may be displaced in time or, more critically, in space which strongly affects the possibility to assess hydrological risk. - Climate projections: The spatial resolution of the current RCM generation (around 25 km) is not sufficient for proper description of LSPEs. Statistical post-processing (i.e. downscaling) is required which adds substantial uncertainty to the final result. Ensemble generation of sufficiently
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Cropp, E. L.; Hazenberg, P.; Castro, C. L.; Demaria, E. M.
2017-12-01
In the southwestern US, the summertime North American Monsoon (NAM) provides about 60% of the region's annual precipitation. Recent research using high-resolution atmospheric model simulations and retrospective predictions has shown that since the 1950's, and more specifically in the last few decades, the mean daily precipitation in the southwestern U.S. during the NAM has followed a decreasing trend. Furthermore, days with more extreme precipitation have intensified. The current work focuses the impact of these long-term changes on the observed small-scale spatial variability of intense precipitation. Since limited long-term high-resolution observational data exist to support such climatological-induced spatial changes in precipitation frequency and intensity, the current work utilizes observations from the USDA-ARS Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Within this 150 km^2 catchment over 90 rain gauges have been installed since the 1950s, measuring at sub-hourly resolution. We have applied geospatial analyses and the kriging interpolation technique to identify long-term changes in the spatial and temporal correlation and anisotropy of intense precipitation. The observed results will be compared with the previously model simulated results, as well as related to large-scale variations in climate patterns, such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).
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Vicente-Serrano, S.; Beguería, S.
2003-01-01
This paper analyses fifty-year time series of daily precipitation in a region of the middle Ebro valley (northern Spain) in order to predict extreme dry-spell risk. A comparison of observed and estimated maximum dry spells (50-year return period) showed that the Generalised Pareto (GP)
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A Non-Stationary Approach for Estimating Future Hydroclimatic Extremes Using Monte-Carlo Simulation
Byun, K.; Hamlet, A. F.
2017-12-01
There is substantial evidence that observed hydrologic extremes (e.g. floods, extreme stormwater events, and low flows) are changing and that climate change will continue to alter the probability distributions of hydrologic extremes over time. These non-stationary risks imply that conventional approaches for designing hydrologic infrastructure (or making other climate-sensitive decisions) based on retrospective analysis and stationary statistics will become increasingly problematic through time. To develop a framework for assessing risks in a non-stationary environment our study develops a new approach using a super ensemble of simulated hydrologic extremes based on Monte Carlo (MC) methods. Specifically, using statistically downscaled future GCM projections from the CMIP5 archive (using the Hybrid Delta (HD) method), we extract daily precipitation (P) and temperature (T) at 1/16 degree resolution based on a group of moving 30-yr windows within a given design lifespan (e.g. 10, 25, 50-yr). Using these T and P scenarios we simulate daily streamflow using the Variable Infiltration Capacity (VIC) model for each year of the design lifespan and fit a Generalized Extreme Value (GEV) probability distribution to the simulated annual extremes. MC experiments are then used to construct a random series of 10,000 realizations of the design lifespan, estimating annual extremes using the estimated unique GEV parameters for each individual year of the design lifespan. Our preliminary results for two watersheds in Midwest show that there are considerable differences in the extreme values for a given percentile between conventional MC and non-stationary MC approach. Design standards based on our non-stationary approach are also directly dependent on the design lifespan of infrastructure, a sensitivity which is notably absent from conventional approaches based on retrospective analysis. The experimental approach can be applied to a wide range of hydroclimatic variables of interest.
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Ebrahimzadeh, Mohammad H; Moradi, Ali; Bozorgnia, Shahram; Hallaj-Moghaddam, Mohammad
2016-02-01
Long-term consequences and the activities of daily living of bilateral lower limb amputation are not well documented. The aims of our study were to identify the long-term effects of bilateral lower extremity amputations on daily activities and understand how these amputees cope with their mobility assistive devices. Cross-sectional study. A total of 291 veterans with war bilateral lower limb amputations accepted to participate in a cross-sectional study. The average of follow-up was 25.4 years. A total of 152 amputees (54%) were involved in sports averagely 6.7 h per week. Bilateral amputees walk 10 m by the average of 15 ± 33 s, and they could walk continuously with their prosthesis 315 ± 295 m. They wore their prosthesis 6.8 ± 1.7 days per week and 7.9 ± 8.1 h per day. Of these, 6.7% of bilateral lower limb amputees needed help to wear their prosthesis; 88.3% of amputees used assistant device for walking. According to this survey, 73 (42%) prostheses in right limb were appropriate, 95 (54.6%) needed to be replaced, and 6 (3.4) needed to be fixed. On the left side, it was 76 (42%), 92 (52.0%), and 9 (5.1%), respectively. A total of 203 (74.9%) amputees reported limitations in at least one domain of the activities of daily living. The most common single item that affected the patients was ascending and descending stairs by the score of 66% of normal population. Veterans with bilateral lower limb amputations suffering from vast categories of daily problems. This study and its results confirm that bilateral lower limb amputees have major progressive disabilities in daily activities and their social performance. This should attract the attention of amputees' administrative organizations, social workers, health-care providers and caregiver providers. © The International Society for Prosthetics and Orthotics 2014.
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Trends in Extreme Climate Indices for Pará State, Brazil
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Carlos Antonio Costa dos Santos
Full Text Available Abstract The present study aimed to analyze trends in air temperature and rainfall for 13 locations in the state of Pará using nonparametric tests. Daily data of maximum and minimum air temperatures and precipitation covering the period 1970-2006, collected by the Instituto Nacional de Meteorologia (INMET have been used. From the results obtained it was observed that the number of warm days and nights per year has increased, thereby providing a significant reduction in the number of cool days and nights in the state. Due to the high space-time variability of precipitation, few localities showed statistically significant trends for indices of extremes dependent on this variable. The days and nights in Belém have been hotter in the last two decades. Therefore, these results are important for future planning of public health and energy for the state of Para, which must adapt to future warming scenarios sectors.
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Extreme pressure differences at 0900 NZST and winds across New Zealand
Salinger, M. James; Griffiths, Georgina M.; Gosai, Ashmita
2005-07-01
Trends in extremes in station daily sea-level pressure differences at 0900 NZST are examined, and extreme daily wind gusts, across New Zealand, since the 1960s. Annual time series were examined (with indices of magnitude and frequency over threshold percentiles) from the daily indices selected. These follow from earlier indices of normalized monthly mean sea-level pressure differences between station pairs, except the daily indices are not normalized. The frequency statistics quantify the number of extreme zonal (westerly and easterly), or extreme meridional (southerly or northerly), pressure gradient events. The frequency and magnitude of extreme westerly episodes has increased slightly over New Zealand, with a significant increase in the westerly extremes to the south of New Zealand. In contrast, the magnitude and frequency of easterly extremes has decreased over New Zealand, but increased to the south, with some trends weakly significant. The frequency and magnitude of daily southerly extremes has decreased significantly in the region.Extreme daily wind gust events at key climate stations in New Zealand and at Hobart, Australia, are highly likely to be associated with an extreme daily pressure difference. The converse was less likely to hold: extreme wind gusts were not always observed on days with extreme daily pressure difference, probably due to the strong influence that topography has on localized station winds. Significant correlations exist between the frequency indices and both annual-average mean sea-level pressures around the Australasian region and annual-average sea surface temperature (SST) anomalies in the Southern Hemisphere. These correlations are generally stronger for indices of extreme westerly or extreme southerly airflows. Annual-average pressures in the Tasman Sea or Southern Ocean are highly correlated to zonal indices (frequency of extreme westerlies). SST anomalies in the NINO3 region or on either side of the South Island are
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ANALYSIS OF PROJECTED FREQUENCY AND INTENSITY CHANGES OF PRECIPITATION IN THE CARPATHIAN REGION
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KIS ANNA
2015-03-01
Full Text Available Precipitation is the major atmospheric source of surface water, thus, in order to build appropriate adaptation strategies for various economic sections related to water resources it is essential to provide projections for precipitation tendencies as exact as possible. Extreme precipitation events are especially important from this point of view since they may result in different environmental, economical, and/or even human health damages. Excessive precipitation for instance may induce floods, flash-floods, landslides, traffic accidents. On the other hand, lack of precipitation is not favorable either: long dry periods affect agricultural production quite negatively, and hence, food safety can be threatened. Several precipitation-related indices (i.e., describing drought or intensity, exceeding different percentile-based or absolute threshold values are analyzed for the Carpathian region for 1961–2100. For this purpose 11 completed regional climate model simulations are used from the ENSEMBLES database. Before the thorough analysis, a percentile-based bias correction method was applied to the raw data, for which the homogenized daily gridded CarpatClim database (1961–2010 served as a reference. Absolute and relative seasonal mean changes of climate indices are calculated for two future time periods (2021–2050 and 2071–2100 and for three subregions within the entire Carpathian region, namely, for Slovakia, Hungary and Romania. According to our results, longer dry periods are estimated for the summer season, mainly in the southern parts of the domain, while precipitation intensity is likely to increase. Heavy precipitation days and high percentile values are projected to increase, especially, in winter and autumn.
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Ferritic Alloys with Extreme Creep Resistance via Coherent Hierarchical Precipitates.
Song, Gian; Sun, Zhiqian; Li, Lin; Xu, Xiandong; Rawlings, Michael; Liebscher, Christian H; Clausen, Bjørn; Poplawsky, Jonathan; Leonard, Donovan N; Huang, Shenyan; Teng, Zhenke; Liu, Chain T; Asta, Mark D; Gao, Yanfei; Dunand, David C; Ghosh, Gautam; Chen, Mingwei; Fine, Morris E; Liaw, Peter K
2015-11-09
There have been numerous efforts to develop creep-resistant materials strengthened by incoherent particles at high temperatures and stresses in response to future energy needs for steam turbines in thermal-power plants. However, the microstructural instability of the incoherent-particle-strengthened ferritic steels limits their application to temperatures below 900 K. Here, we report a novel ferritic alloy with the excellent creep resistance enhanced by coherent hierarchical precipitates, using the integrated experimental (transmission-electron microscopy/scanning-transmission-electron microscopy, in-situ neutron diffraction, and atom-probe tomography) and theoretical (crystal-plasticity finite-element modeling) approaches. This alloy is strengthened by nano-scaled L21-Ni2TiAl (Heusler phase)-based precipitates, which themselves contain coherent nano-scaled B2 zones. These coherent hierarchical precipitates are uniformly distributed within the Fe matrix. Our hierarchical structure material exhibits the superior creep resistance at 973 K in terms of the minimal creep rate, which is four orders of magnitude lower than that of conventional ferritic steels. These results provide a new alloy-design strategy using the novel concept of hierarchical precipitates and the fundamental science for developing creep-resistant ferritic alloys. The present research will broaden the applications of ferritic alloys to higher temperatures.
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Evaluation of Satellite and Model Precipitation Products Over Turkey
Yilmaz, M. T.; Amjad, M.
2017-12-01
Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14
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Precipitation variations recorded in Guliya ice core in the past 400 years
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Based on the Guliya ice core records, the precipitation in the past 400 years was retrieved. Its rela tions with other regions were also analyzed. The results demonstrated that there were two high-precipitation periods and two low-precipitation periods in Guliya ice core since 1571 AD. The average precipitation in the two high-precipitation periods was 42 mm (21%) higher than that in the two low-precipitation periods. The precipitation recorded in the Guliya ice core was consistent with that in Dunde ice core. The variation trends of precipitation in the Guliya ice core and the northern hemisphere are similar. During the extremely wet years in the northern hemisphere, the precipitation recorded in the Guliya ice core was two times the long-term average. However, the annual precipitation was 38% less than that of the long-term average in extremely dry years.
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Tan, Xuezhi; Gan, Thian Yew
2017-05-01
In recent years, because the frequency and severity of floods have increased across Canada, it is important to understand the characteristics of Canadian heavy precipitation. Long-term precipitation data of 463 gauging stations of Canada were analyzed using non-stationary generalized extreme value distribution (GEV), Poisson distribution and generalized Pareto (GP) distribution. Time-varying covariates that represent large-scale climate patterns such as El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific decadal oscillation (PDO) and North Pacific Oscillation (NP) were incorporated to parameters of GEV, Poisson and GP distributions. Results show that GEV distributions tend to under-estimate annual maximum daily precipitation (AMP) of western and eastern coastal regions of Canada, compared to GP distributions. Poisson regressions show that temporal clusters of heavy precipitation events in Canada are related to large-scale climate patterns. By modeling AMP time series with non-stationary GEV and heavy precipitation with non-stationary GP distributions, it is evident that AMP and heavy precipitation of Canada show strong non-stationarities (abrupt and slowly varying changes) likely because of the influence of large-scale climate patterns. AMP in southwestern coastal regions, southern Canadian Prairies and the Great Lakes tend to be higher in El Niño than in La Niña years, while AMP of other regions of Canada tends to be lower in El Niño than in La Niña years. The influence of ENSO on heavy precipitation was spatially consistent but stronger than on AMP. The effect of PDO, NAO and NP on extreme precipitation is also statistically significant at some stations across Canada.
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Assessment of satellite-based precipitation estimates over Paraguay
Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián
2018-04-01
Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.
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Regional estimation of extreme suspended sediment concentrations using watershed characteristics
Tramblay, Yves; Ouarda, Taha B. M. J.; St-Hilaire, André; Poulin, Jimmy
2010-01-01
SummaryThe number of stations monitoring daily suspended sediment concentration (SSC) has been decreasing since the 1980s in North America while suspended sediment is considered as a key variable for water quality. The objective of this study is to test the feasibility of regionalising extreme SSC, i.e. estimating SSC extremes values for ungauged basins. Annual maximum SSC for 72 rivers in Canada and USA were modelled with probability distributions in order to estimate quantiles corresponding to different return periods. Regionalisation techniques, originally developed for flood prediction in ungauged basins, were tested using the climatic, topographic, land cover and soils attributes of the watersheds. Two approaches were compared, using either physiographic characteristics or seasonality of extreme SSC to delineate the regions. Multiple regression models to estimate SSC quantiles as a function of watershed characteristics were built in each region, and compared to a global model including all sites. Regional estimates of SSC quantiles were compared with the local values. Results show that regional estimation of extreme SSC is more efficient than a global regression model including all sites. Groups/regions of stations have been identified, using either the watershed characteristics or the seasonality of occurrence for extreme SSC values providing a method to better describe the extreme events of SSC. The most important variables for predicting extreme SSC are the percentage of clay in the soils, precipitation intensity and forest cover.
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ENSO modulation of seasonal rainfall and extremes in Indonesia
Supari; Tangang, Fredolin; Salimun, Ester; Aldrian, Edvin; Sopaheluwakan, Ardhasena; Juneng, Liew
2017-12-01
This paper provides a detailed description of how ENSO events affect seasonal and extreme precipitation over Indonesia. Daily precipitation data from 97 stations across Indonesia covering the period from 1981 to 2012 were used to investigate the effects of El Niño and La Niña on extreme precipitation characteristics including intensity, frequency and duration, as defined based on a subset of the Expert Team on Climate Change Detection and Indices (ETCCDI). Although anomalous signals in these three indices were consistent with those of total rainfall, anomalies in the duration of extremes [i.e., consecutive dry days (CDD) and consecutive wet days (CWD)] were much more robust. El Niño impacts were particularly prominent during June-July-August (JJA) and September-October-November (SON), when anomalously dry conditions were experienced throughout the country. However, from SON, a wet anomaly appeared over northern Sumatra, later expanding eastward during December-January-February (DJF) and March-April-May (MAM), creating contrasting conditions of wet in the west and dry in the east. We attribute this apparent eastward expansion of a wet anomaly during El Niño progression to the equatorial convergence of two anti-cyclonic circulations, one residing north of the equator and the other south of the equator. These anti-cyclonic circulations strengthen and weaken according to seasonal changes and their coupling with regional seas, hence shaping moisture transport and convergence. During La Niña events, the eastward expansion of an opposite (i.e., dry) anomaly was also present but less prominent than that of El Niño. We attribute this to differences in regional ocean—atmosphere coupling, which result in the contrasting seasonal evolution of the two corresponding anomalous cyclonic circulations and in turn suggests the strong nonlinearity of El Niño and La Niña responses over the Maritime Continent. Based on the seasonal behaviour of anomalous CDD and CWD, we
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Zhao, Yinjun; Xie, Qiongying; Lu, Yuan; Hu, Baoqing
2017-06-01
The accuracy of Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA) daily accumulated precipitation products (3B42RTV7 and 3B42V7) was evaluated for a small basin (the Nanliu river basin). A direct comparison was performed against gauge observations from a period of 9 years (2000-2009) at temporal and spatial scales. The results show that the temporal-spatial precipitation characteristics of the Nanliu river basin are highly consistent with 3B42V7 relative to 3B42RTV7, with higher correlation coefficient (CC) approximately 0.9 at all temporal scales except for the daily scale and a lower relative bias percentage. 3B42V7 slightly overestimates precipitation at all temporal scales except the yearly scale; it slightly underestimates the precipitation at the daily spatial scale. The results also reveal that the precision of TMPA products increases with longer time-aggregated data, and the detection capability of daily TMPA precipitation products are enhanced by augmentation with daily precipitation rates. In addition, daily TMPA products were input into the Xin'anjiang hydrologic model; the results show that 3B42V7-based simulated outputs were well in line with actual stream flow observations, with a high CC (0.90) and Nash-Sutcliffe efficiency coefficient (NSE, 0.79), and the results adequately captured the pattern of the observed flow curve.
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Rough Precipitation Forecasts based on Analogue Method: an Operational System
Raffa, Mario; Mercogliano, Paola; Lacressonnière, Gwendoline; Guillaume, Bruno; Deandreis, Céline; Castanier, Pierre
2017-04-01
specific atmospheric variable without a complete description of the weather situation. In the first phase, the method considers a selection of analogous situations in terms of mean sea level pressure, specific humidity and total precipitation. In the second one, a subset of observations data is extracted according to the analogues found. The research of analogues consists of cascading filters designed to find the most similar weather situation in a historical archive of ECMWF analysis. The method has been calibrated in the period between 2008 and 2011, over different France weather stations (Paris, Meaux, La Londe Les Maures etc) in order to forecast extreme rainfall events. The results of the operational demonstrator, which has been running since September 2016 over the same France weather stations, show good performances in terms of prediction of extreme events at 24hrs horizon, meant as daily quantitative precipitation greater than 93th percentile of distribution, with a relative low false alarm rate.
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Directory of Open Access Journals (Sweden)
P. Quintana-Seguí
2011-05-01
Full Text Available The extremes of precipitation and river flow obtained using three different statistical downscaling methods applied to the same regional climate simulation have been compared. The methods compared are the anomaly method, quantile mapping and a weather typing. The hydrological model used in the study is distributed and it is applied to the Mediterranean basins of France. The study shows that both quantile mapping and weather typing methods are able to reproduce the high and low precipitation extremes in the region of interest. The study also shows that when the hydrological model is forced with these downscaled data, there are important differences in the outputs. This shows that the model amplifies the differences and that the downscaling of other atmospheric variables might be very relevant when simulating river discharges. In terms of river flow, the method of the anomalies, which is very simple, performs better than expected. The methods produce qualitatively similar future scenarios of the extremes of river flow. However, quantitatively, there are still significant differences between them for each individual gauging station. According to these scenarios, it is expected that in the middle of the 21st century (2035–2064, the monthly low flows will have diminished almost everywhere in the region of our study by as much as 20 %. Regarding high flows, there will be important increases in the area of the Cévennes, which is already seriously affected by flash-floods. For some gauging stations in this area, the frequency of what was a 10-yr return flood at the end of the 20th century is expected to increase, with such return floods then occurring every two years in the middle of the 21st century. Similarly, the 10-yr return floods at that time are expected to carry 100 % more water than the 10-yr return floods experienced at the end of the 20th century. In the northern part of the Rhône basin, these extremes will be reduced.
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Hydrological Applications of a High-Resolution Radar Precipitation Data Base for Sweden
Olsson, Jonas; Berg, Peter; Norin, Lars; Simonsson, Lennart
2017-04-01
rainfall-runoff process in large, slow river basins, which traditionally has been the main focus in the national forecasting, an hourly time step (or preferably even shorter) is required to simulate the flow in fast-responding basins. At the daily scale, the PTHBV product is used for model initialization prior to the forecasts but with its daily resolution it is not applicable at the hourly scale. For this purpose, a real-time version of HIPRAD has been developed which is currently running operationally. HIPRAD is also being used for historical simulations with an hourly time step, which is important for e.g. water quality assessment. Finally, we will use HIPRAD to gain an improved knowledge of the short-duration precipitation climate in Sweden. Currently there are many open issues with respect to e.g. geographical differences, spatial correlations and areal extremes. Here we will show and discuss selected results from the ongoing development and validation of HIPRAD as well as its various applications for hydrological forecasting and risk assessment. Further, web resources containing radar-based observation and forecasting for hydrological applications will be demonstrated. Finally, some future research directions will be outlined. Fast responding hydrological catchments require fine spatial and temporal resolution of the precipitation input data to provide realistic results.
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Directory of Open Access Journals (Sweden)
A. J. Pitman
2012-11-01
Full Text Available The impact of historical land use induced land cover change (LULCC on regional-scale climate extremes is examined using four climate models within the Land Use and Climate, IDentification of robust impacts project. To assess those impacts, multiple indices based on daily maximum and minimum temperatures and daily precipitation were used. We contrast the impact of LULCC on extremes with the impact of an increase in atmospheric CO2 from 280 ppmv to 375 ppmv. In general, consistent changes in both high and low temperature extremes are similar to the simulated change in mean temperature caused by LULCC and are restricted to regions of intense modification. The impact of LULCC on both means and on most temperature extremes is statistically significant. While the magnitude of the LULCC-induced change in the extremes can be of similar magnitude to the response to the change in CO2, the impacts of LULCC are much more geographically isolated. For most models, the impacts of LULCC oppose the impact of the increase in CO2 except for one model where the CO2-caused changes in the extremes are amplified. While we find some evidence that individual models respond consistently to LULCC in the simulation of changes in rainfall and rainfall extremes, LULCC's role in affecting rainfall is much less clear and less commonly statistically significant, with the exception of a consistent impact over South East Asia. Since the simulated response of mean and extreme temperatures to LULCC is relatively large, we conclude that unless this forcing is included, we risk erroneous conclusions regarding the drivers of temperature changes over regions of intense LULCC.
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Projected precipitation changes in South America: a dynamical downscaling within CLARIS
Energy Technology Data Exchange (ETDEWEB)
Soerensson, Anna A. [Centra de Investigaciones del Mar y la Atmosfera, CONICET/UBA, Buenos Aires (Argentina); Menendez, Claudio G. [Centra de Investigaciones del Mar y la Atmosfera, CONICET/UBA, Buenos Aires (Argentina); Dept. de Ciencias de la Atmosfera y los Oceanos, FCEN, UBA, Buenos Aires (Argentina); Ruscica, Romina; Alexander, Peter [Dept. de Fisica, FCEN, UBA, Buenos Aires (Argentina); Samuelsson, Patrick; Willen, Ulrika [Rossby Centre, SMHI, Norrkoeping (Sweden)
2010-06-15
Responses of precipitation seasonal means and extremes over South America in a downscaling of a climate change scenario are assessed with the Rossby Centre Regional Atmospheric Model (RCA). The anthropogenic warming under A1B scenario influences more on the likelihood of occurrence of severe extreme events like heavy precipitation and dry spells than on the mean seasonal precipitation. The risk of extreme precipitation increases in the La Plata Basin with a factor of 1.5-2.5 during all seasons and in the northwestern part of the continent with a factor 1.5-3 in summer, while it decreases in central and northeastern Brazil during winter and spring. The maximum amount of 5-days precipitation increases by up to 50% in La Plata Basin, indicating risks of flooding. Over central Brazil and the Bolivian lowland, where present 5-days precipitation is higher, the increases are similar in magnitude and could cause less impacts. In southern Amazonia, northeastern Brazil and the Amazon basin, the maximum number of consecutive dry days increases and mean winter and spring precipitation decreases, indicating a longer dry season. In the La Plata Basin, there is no clear pattern of change for the dry spell duration. (orig.)
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Lorenz, Manuel; Bliefernicht, Jan; Laux, Patrick; Kunstmann, Harald
2017-04-01
future conditions after the bias correction. Also, the effects of the statistical transformation, especially how the climate change signal is affected and how statistics like the average monthly and annual sums of precipitation and the frequency of daily rainfall are changed, are shown.
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Utkuzova, Dilyara; Khan, Valentina
2015-04-01
Synoptical-statistical analysis has been conducted using SPI index calculated for 478 stations with records from 1966 through 2013. Different parameters of SPI frequency distribution and long-term tendencies were calculated as well as spatial characteristics indicating drought and wetness propagation. Results of analysis demonstrate that during last years there is a tendency of increasing of the intensity of draught and wetness extremes over Russia. There are fewer droughts in the northern regions. The drought propagation for the European territory of Russia is decreasing in June and August, and increasing in July. The situation is opposite for the wetness tendencies. For the Asian territory of Russia, the drought propagation is significantly increasing in July along with decreasing wetness trend. Synoptic conditions favorable for the formation of wet and drought extremes were identified by comparing synoptic charts with the spatial patterns of SPI. For synoptic analysis, episodes of extremely wet (6 episodes for the APR and 7 episodes for the EPR) and drought (6 episodes for the APR and 6 for the EPR) events were classified using A. Katz' typology of weather regimes. For European part of Russia, extreme DROUGHT events are linked to the weather type named "MIXED", for Asian part of Russia - the type "CENTRAL". For European part of Russia, extreme WET events associated with "CENTRAL" type. There is a displacement of the planetary frontal zone into southward direction approximately for 5-25 degrees relatively to normal climatological position during WET extreme events linked to «EASTERN» classification type. Intercomparison of SPI calculated on the base of NOAA NCEP CPC CAMS for the same period and with the resolution 0,5 degree, month precipitation data, Era-Interim Daily fields archive for the period 1979-2014 with the resolution 0,5 degree reanalysis and observational precipitation data was done. The results of comparative analysis has been discussed.
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DEFF Research Database (Denmark)
Larsen, A. N.; Mikkelsen, Peter Steen; Arnbjerg-Nielsen, Karsten
Climate change will impact the hydrological cycle greatly and lead to increases in flood hazards due to both pluvial and fluvial floods as well as sea surges in many regions. The impacts of the individual effects are analysed for a catchment in Greater Copenhagen. Based on both the present...... surges. Presently the most important hazard is due to extreme precipitation. However, due to climate change impacts the future most important hazard is due to sea surges. The increase in probability of floods is substantial over a 70 year horizon and actions must be taken to decrease either the hazards...
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Kallache, M.
2012-04-01
Droughts cause important losses. On the Iberian Peninsula, for example, non-irrigated agriculture and the tourism sector are affected in regular intervals. The goal of this study is the description of droughts and their dependence in the Duero basin in Central Spain. To do so, daily or monthly precipitation data is used. Here cumulative precipitation deficits below a threshold define meteorological droughts. This drought indicator is similar to the commonly used standard precipitation index. However, here the focus lies on the modeling of severe droughts, which is done by applying multivariate extreme value theory (MEVT) to model extreme drought events. Data from several stations are assessed jointly, thus the uncertainty of the results is reduced. Droughts are a complex phenomenon, their severity, spatial extension and duration has to be taken into account. Our approach captures severity and spatial extension. In general we find a high correlation between deficit volumes and drought duration, thus the duration is not explicitely modeled. We apply a MEVT model with asymmetric logistic dependence function, which is capable to model asymptotic dependence and independence (cf. Ramos and Ledford, 2009). To summarize the information on the dependence in the joint tail of the extreme drought events, we utilise the fragility index (Geluk et al., 2007). Results show that droughts also occur frequently in winter. Moreover, it is very common for one site to suffer dry conditions, whilst neighboring areas experience normal or even humid conditions. Interpolation is thus difficult. Bivariate extremal dependence is present in the data. However, most stations are at least asymptotically independent. The according fragility indices are important information for risk calculations. The emerging spatial patterns for bivariate dependence are mostly influenced by topography. When looking at the dependence between more than two stations, it shows that joint extremes can occur more
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Westerberg, I.; Walther, A.; Guerrero, J.-L.; Coello, Z.; Halldin, S.; Xu, C.-Y.; Chen, D.; Lundin, L.-C.
2010-08-01
An accurate description of temporal and spatial precipitation variability in Central America is important for local farming, water supply and flood management. Data quality problems and lack of consistent precipitation data impede hydrometeorological analysis in the 7,500 km2 Choluteca River basin in central Honduras, encompassing the capital Tegucigalpa. We used precipitation data from 60 daily and 13 monthly stations in 1913-2006 from five local authorities and NOAA's Global Historical Climatology Network. Quality control routines were developed to tackle the specific data quality problems. The quality-controlled data were characterised spatially and temporally, and compared with regional and larger-scale studies. Two gap-filling methods for daily data and three interpolation methods for monthly and mean annual precipitation were compared. The coefficient-of-correlation-weighting method provided the best results for gap-filling and the universal kriging method for spatial interpolation. In-homogeneity in the time series was the main quality problem, and 22% of the daily precipitation data were too poor to be used. Spatial autocorrelation for monthly precipitation was low during the dry season, and correlation increased markedly when data were temporally aggregated from a daily time scale to 4-5 days. The analysis manifested the high spatial and temporal variability caused by the diverse precipitation-generating mechanisms and the need for an improved monitoring network.
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Schwantes, Amanda M; Swenson, Jennifer J; González-Roglich, Mariano; Johnson, Daniel M; Domec, Jean-Christophe; Jackson, Robert B
2017-12-01
Globally, trees are increasingly dying from extreme drought, a trend that is expected to increase with climate change. Loss of trees has significant ecological, biophysical, and biogeochemical consequences. In 2011, a record drought caused widespread tree mortality in Texas. Using remotely sensed imagery, we quantified canopy loss during and after the drought across the state at 30-m spatial resolution, from the eastern pine/hardwood forests to the western shrublands, a region that includes the boundaries of many species ranges. Canopy loss observations in ~200 multitemporal fine-scale orthophotos (1-m) were used to train coarser Landsat imagery (30-m) to create 30-m binary statewide canopy loss maps. We found that canopy loss occurred across all major ecoregions of Texas, with an average loss of 9.5%. The drought had the highest impact in post oak woodlands, pinyon-juniper shrublands and Ashe juniper woodlands. Focusing on a 100-km by ~1,000-km transect spanning the State's fivefold east-west precipitation gradient (~1,500 to ~300 mm), we compared spatially explicit 2011 climatic anomalies to our canopy loss maps. Much of the canopy loss occurred in areas that passed specific climatic thresholds: warm season anomalies in mean temperature (+1.6°C) and vapor pressure deficit (VPD, +0.66 kPa), annual percent deviation in precipitation (-38%), and 2011 difference between precipitation and potential evapotranspiration (-1,206 mm). Although similarly low precipitation occurred during the landmark 1950s drought, the VPD and temperature anomalies observed in 2011 were even greater. Furthermore, future climate data under the representative concentration pathway 8.5 trajectory project that average values will surpass the 2011 VPD anomaly during the 2070-2099 period and the temperature anomaly during the 2040-2099 period. Identifying vulnerable ecological systems to drought stress and climate thresholds associated with canopy loss will aid in predicting how forests will
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Multidecadal oscillations in rainfall and hydrological extremes
Willems, Patrick
2013-04-01
Many studies have anticipated a worldwide increase in the frequency and intensity of precipitation extremes and floods since the last decade(s). Natural variability by climate oscillations partly determines the observed evolution of precipitation extremes. Based on a technique for the identification and analysis of changes in extreme quantiles, it is shown that hydrological extremes have oscillatory behaviour at multidecadal time scales. Results are based on nearly independent extremes extracted from long-term historical time series of precipitation intensities and river flows. Study regions include Belgium - The Netherlands (Meuse basin), Ethiopia (Blue Nile basin) and Ecuador (Paute basin). For Belgium - The Netherlands, the past 100 years showed larger and more hydrological extremes around the 1910s, 1950-1960s, and more recently during the 1990-2000s. Interestingly, the oscillations for southwestern Europe are anti-correlated with these of northwestern Europe, thus with oscillation highs in the 1930-1940s and 1970s. The precipitation oscillation peaks are explained by persistence in atmospheric circulation patterns over the North Atlantic during periods of 10 to 15 years. References: Ntegeka V., Willems P. (2008), 'Trends and multidecadal oscillations in rainfall extremes, based on a more than 100 years time series of 10 minutes rainfall intensities at Uccle, Belgium', Water Resources Research, 44, W07402, doi:10.1029/2007WR006471 Mora, D., Willems, P. (2012), 'Decadal oscillations in rainfall and air temperature in the Paute River Basin - Southern Andes of Ecuador', Theoretical and Applied Climatology, 108(1), 267-282, doi:0.1007/s00704-011-0527-4 Taye, M.T., Willems, P. (2011). 'Influence of climate variability on representative QDF predictions of the upper Blue Nile Basin', Journal of Hydrology, 411, 355-365, doi:10.1016/j.jhydrol.2011.10.019 Taye, M.T., Willems, P. (2012). 'Temporal variability of hydro-climatic extremes in the Blue Nile basin', Water
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Seasonality of runoff and precipitation regimes along transects in Peru and Austria
Gaudry Maria M. Cárdenas; Gutknecht Dieter; Parajka Juraj; Perdigão Rui A.P.; Blöschl Günter
2017-01-01
The aim of this study is to understand the seasonalities of runoff and precipitation and their controls along two transects in Peru and one transect in Austria. The analysis is based on daily precipitation data at 111 and 61 stations in Peru and Austria, respectively, and daily discharge data at 51 and 110 stations. The maximum Pardé coefficient is used to quantify the strength of the seasonalities of monthly precipitation and runoff. Circular statistics are used to quantify the seasonalities...
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Assessing upper extremity motor function in practice of virtual activities of daily living.
Adams, Richard J; Lichter, Matthew D; Krepkovich, Eileen T; Ellington, Allison; White, Marga; Diamond, Paul T
2015-03-01
A study was conducted to investigate the criterion validity of measures of upper extremity (UE) motor function derived during practice of virtual activities of daily living (ADLs). Fourteen hemiparetic stroke patients employed a Virtual Occupational Therapy Assistant (VOTA), consisting of a high-fidelity virtual world and a Kinect™ sensor, in four sessions of approximately one hour in duration. An unscented Kalman Filter-based human motion tracking algorithm estimated UE joint kinematics in real-time during performance of virtual ADL activities, enabling both animation of the user's avatar and automated generation of metrics related to speed and smoothness of motion. These metrics, aggregated over discrete sub-task elements during performance of virtual ADLs, were compared to scores from an established assessment of UE motor performance, the Wolf Motor Function Test (WMFT). Spearman's rank correlation analysis indicates a moderate correlation between VOTA-derived metrics and the time-based WMFT assessments, supporting the criterion validity of VOTA measures as a means of tracking patient progress during an UE rehabilitation program that includes practice of virtual ADLs.
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A possible constraint on regional precipitation intensity changes under global warming
DEFF Research Database (Denmark)
Gutowski, William J.; Kozak, K. A.; Arritt, R. W.
2007-01-01
Changes in daily precipitation versus intensity under a global warming scenario in two regional climate simulations of the United States show a well-recognized feature of more intense precipitation. More important, by resolving the precipitation intensity spectrum, the changes show a relatively...
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Guilbert, Justin; Betts, Alan K.; Rizzo, Donna M.; Beckage, Brian; Bomblies, Arne
2015-03-01
We present evidence of increasing persistence in daily precipitation in the northeastern United States that suggests that global circulation changes are affecting regional precipitation patterns. Meteorological data from 222 stations in 10 northeastern states are analyzed using Markov chain parameter estimates to demonstrate that a significant mode of precipitation variability is the persistence of precipitation events. We find that the largest region-wide trend in wet persistence (i.e., the probability of precipitation in 1 day and given precipitation in the preceding day) occurs in June (+0.9% probability per decade over all stations). We also find that the study region is experiencing an increase in the magnitude of high-intensity precipitation events. The largest increases in the 95th percentile of daily precipitation occurred in April with a trend of +0.7 mm/d/decade. We discuss the implications of the observed precipitation signals for watershed hydrology and flood risk.
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Directory of Open Access Journals (Sweden)
Andreas Tornevi
Full Text Available BACKGROUND: The river Göta Älv is a source of freshwater for 0.7 million swedes. The river is subject to contamination from sewer systems discharge and runoff from agricultural lands. Climate models projects an increase in precipitation and heavy rainfall in this region. This study aimed to determine how daily rainfall causes variation in indicators of pathogen loads, to increase knowledge of variations in river water quality and discuss implications for risk management. METHODS: Data covering 7 years of daily monitoring of river water turbidity and concentrations of E. coli, Clostridium and coliforms were obtained, and their short-term variations in relation with precipitation were analyzed with time series regression and non-linear distributed lag models. We studied how precipitation effects varied with season and compared different weather stations for predictive ability. RESULTS: Generally, the lowest raw water quality occurs 2 days after rainfall, with poor raw water quality continuing for several more days. A rainfall event of >15 mm/24-h (local 95 percentile was associated with a three-fold higher concentration of E. coli and 30% higher turbidity levels (lag 2. Rainfall was associated with exponential increases in concentrations of indicator bacteria while the effect on turbidity attenuated with very heavy rainfall. Clear associations were also observed between consecutive days of wet weather and decreased water quality. The precipitation effect on increased levels of indicator bacteria was significant in all seasons. CONCLUSIONS: Rainfall elevates microbial risks year-round in this river and freshwater source and acts as the main driver of varying water quality. Heavy rainfall appears to be a better predictor of fecal pollution than water turbidity. An increase of wet weather and extreme events with climate change will lower river water quality even more, indicating greater challenges for drinking water producers, and suggesting better
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Oughton, Edward J.; Skelton, Andrew; Horne, Richard B.; Thomson, Alan W. P.; Gaunt, Charles T.
2017-01-01
Extreme space weather due to coronal mass ejections has the potential to cause considerable disruption to the global economy by damaging the transformers required to operate electricity transmission infrastructure. However, expert opinion is split between the potential outcome being one of a temporary regional blackout and of a more prolonged event. The temporary blackout scenario proposed by some is expected to last the length of the disturbance, with normal operations resuming after a couple of days. On the other hand, others have predicted widespread equipment damage with blackout scenarios lasting months. In this paper we explore the potential costs associated with failure in the electricity transmission infrastructure in the U.S. due to extreme space weather, focusing on daily economic loss. This provides insight into the direct and indirect economic consequences of how an extreme space weather event may affect domestic production, as well as other nations, via supply chain linkages. By exploring the sensitivity of the blackout zone, we show that on average the direct economic cost incurred from disruption to electricity represents only 49% of the total potential macroeconomic cost. Therefore, if indirect supply chain costs are not considered when undertaking cost-benefit analysis of space weather forecasting and mitigation investment, the total potential macroeconomic cost is not correctly represented. The paper contributes to our understanding of the economic impact of space weather, as well as making a number of key methodological contributions relevant for future work. Further economic impact assessment of this threat must consider multiday, multiregional events.
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Florian, Ehmele; Michael, Kunz
2016-04-01
Several major flood events occurred in Germany in the past 15-20 years especially in the eastern parts along the rivers Elbe and Danube. Examples include the major floods of 2002 and 2013 with an estimated loss of about 2 billion Euros each. The last major flood events in the State of Baden-Württemberg in southwest Germany occurred in the years 1978 and 1993/1994 along the rivers Rhine and Neckar with an estimated total loss of about 150 million Euros (converted) each. Flood hazard originates from a combination of different meteorological, hydrological and hydraulic processes. Currently there is no defined methodology available for evaluating and quantifying the flood hazard and related risk for larger areas or whole river catchments instead of single gauges. In order to estimate the probable maximum loss for higher return periods (e.g. 200 years, PML200), a stochastic model approach is designed since observational data are limited in time and space. In our approach, precipitation is linearly composed of three elements: background precipitation, orographically-induces precipitation, and a convectively-driven part. We use linear theory of orographic precipitation formation for the stochastic precipitation model (SPM), which is based on fundamental statistics of relevant atmospheric variables. For an adequate number of historic flood events, the corresponding atmospheric conditions and parameters are determined in order to calculate a probability density function (pdf) for each variable. This method involves all theoretically possible scenarios which may not have happened, yet. This work is part of the FLORIS-SV (FLOod RISk Sparkassen Versicherung) project and establishes the first step of a complete modelling chain of the flood risk. On the basis of the generated stochastic precipitation event set, hydrological and hydraulic simulations will be performed to estimate discharge and water level. The resulting stochastic flood event set will be used to quantify the
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Imani, Moslem; Kao, Huan-Chin; Lan, Wen-Hau; Kuo, Chung-Yen
2018-02-01
The analysis and the prediction of sea level fluctuations are core requirements of marine meteorology and operational oceanography. Estimates of sea level with hours-to-days warning times are especially important for low-lying regions and coastal zone management. The primary purpose of this study is to examine the applicability and capability of extreme learning machine (ELM) and relevance vector machine (RVM) models for predicting sea level variations and compare their performances with powerful machine learning methods, namely, support vector machine (SVM) and radial basis function (RBF) models. The input dataset from the period of January 2004 to May 2011 used in the study was obtained from the Dongshi tide gauge station in Chiayi, Taiwan. Results showed that the ELM and RVM models outperformed the other methods. The performance of the RVM approach was superior in predicting the daily sea level time series given the minimum root mean square error of 34.73 mm and the maximum determination coefficient of 0.93 (R2) during the testing periods. Furthermore, the obtained results were in close agreement with the original tide-gauge data, which indicates that RVM approach is a promising alternative method for time series prediction and could be successfully used for daily sea level forecasts.
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The trend of the multi-scale temporal variability of precipitation in Colorado River Basin
Jiang, P.; Yu, Z.
2011-12-01
Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.
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Increasing precipitation volatility in twenty-first-century California
Swain, Daniel L.; Langenbrunner, Baird; Neelin, J. David; Hall, Alex
2018-05-01
Mediterranean climate regimes are particularly susceptible to rapid shifts between drought and flood—of which, California's rapid transition from record multi-year dryness between 2012 and 2016 to extreme wetness during the 2016-2017 winter provides a dramatic example. Projected future changes in such dry-to-wet events, however, remain inadequately quantified, which we investigate here using the Community Earth System Model Large Ensemble of climate model simulations. Anthropogenic forcing is found to yield large twenty-first-century increases in the frequency of wet extremes, including a more than threefold increase in sub-seasonal events comparable to California's `Great Flood of 1862'. Smaller but statistically robust increases in dry extremes are also apparent. As a consequence, a 25% to 100% increase in extreme dry-to-wet precipitation events is projected, despite only modest changes in mean precipitation. Such hydrological cycle intensification would seriously challenge California's existing water storage, conveyance and flood control infrastructure.
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Merroun, Mohamed L; Nedelkova, Marta; Ojeda, Jesus J; Reitz, Thomas; Fernández, Margarita López; Arias, José M; Romero-González, María; Selenska-Pobell, Sonja
2011-12-15
This work describes the mechanisms of uranium biomineralization at acidic conditions by Bacillus sphaericus JG-7B and Sphingomonas sp. S15-S1 both recovered from extreme environments. The U-bacterial interaction experiments were performed at low pH values (2.0-4.5) where the uranium aqueous speciation is dominated by highly mobile uranyl ions. X-ray absorption spectroscopy (XAS) showed that the cells of the studied strains precipitated uranium at pH 3.0 and 4.5 as a uranium phosphate mineral phase belonging to the meta-autunite group. Transmission electron microscopic (TEM) analyses showed strain-specific localization of the uranium precipitates. In the case of B. sphaericus JG-7B, the U(VI) precipitate was bound to the cell wall. Whereas for Sphingomonas sp. S15-S1, the U(VI) precipitates were observed both on the cell surface and intracellularly. The observed U(VI) biomineralization was associated with the activity of indigenous acid phosphatase detected at these pH values in the absence of an organic phosphate substrate. The biomineralization of uranium was not observed at pH 2.0, and U(VI) formed complexes with organophosphate ligands from the cells. This study increases the number of bacterial strains that have been demonstrated to precipitate uranium phosphates at acidic conditions via the activity of acid phosphatase. Copyright © 2011 Elsevier B.V. All rights reserved.
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Spies, Ryan R.; Over, Thomas M.; Ortel, Terry W.
2018-05-21
In this report, precipitation data from 2002 to 2012 from the hourly gridded Next-Generation Radar (NEXRAD)-based Multisensor Precipitation Estimate (MPE) precipitation product are compared to precipitation data from two rain gage networks—an automated tipping bucket network of 25 rain gages operated by the U.S. Geological Survey (USGS) and 51 rain gages from the volunteer-operated Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network—in and near DuPage County, Illinois, at a daily time step to test for long-term differences in space, time, and distribution. The NEXRAD–MPE data that are used are from the fifty 2.5-mile grid cells overlying the rain gages from the other networks. Because of the challenges of measuring of frozen precipitation, the analysis period is separated between days with or without the chance of freezing conditions. The NEXRAD–MPE and tipping-bucket rain gage precipitation data are adjusted to account for undercatch by multiplying by a previously determined factor of 1.14. Under nonfreezing conditions, the three precipitation datasets are broadly similar in cumulative depth and distribution of daily values when the data are combined spatially across the networks. However, the NEXRAD–MPE data indicate a significant trend relative to both rain gage networks as a function of distance from the NEXRAD radar just south of the study area. During freezing conditions, of the USGS network rain gages only the heated gages were considered, and these gages indicate substantial mean undercatch of 50 and 61 percent compared to the NEXRAD–MPE and the CoCoRaHS gages, respectively. The heated USGS rain gages also indicate substantially lower quantile values during freezing conditions, except during the most extreme (highest) events. Because NEXRAD precipitation products are continually evolving, the report concludes with a discussion of recent changes in those products and their potential for improved precipitation estimation. An appendix
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Directory of Open Access Journals (Sweden)
Domenico Vitale
2010-06-01
Full Text Available The impacts of the climate change for agriculture is an ambitious and unresolved topic due to the complexity of the natural phenomena. The high variability of the Mediterranean basin does not allow us to generalize with enough certainty the results obtained from other researches and other locations. Therefore, a site specific analysis in Capitanata plain was conducted. The aim is to provide a detailed picture of recent change in climate regime in one of the most important agricultural area of South Italy. Climate analysis was carried out and several indices of extreme events were studied on the basis of temperature and precipitation observations registered at experimental station ‘Podere 124’ (CRA-SCA. The period under study is 1979-2008. Increasing trends were identified for the summer season with an intensification of the number of heat waves.
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Implications of a decrease in the precipitation area for the past and the future
Benestad, Rasmus E.
2018-04-01
The total area with 24 hrs precipitation has shrunk by 7% between 50°S–50°N over the period 1998–2016, according to the satellite-based Tropical Rain Measurement Mission data. A decrease in the daily precipitation area is an indication of profound changes in the hydrological cycle, where the global rate of precipitation is balanced by the global rate of evaporation. This decrease was accompanied by increases in total precipitation, evaporation, and wet-day mean precipitation. If these trends are real, then they suggest increased drought frequencies and more intense rainfall. Satellite records, however, may be inhomogeneous because they are synthesised from a number of individual missions with improved technology over time. A linear dependency was also found between the global mean temperature and the 50°S–50°N daily precipitation area with a slope value of ‑17 × 106 km 2/°C. This dependency was used with climate model simulations to make future projections which suggested a continued decrease that will strengthen in the future. The precipitation area evolves differently when the precipitation is accumulated over short and long time scales, however, and there has been a slight increase in the monthly precipitation area while the daily precipitation area decreased. An increase on monthly scale may indicate more pronounced variations in the rainfall patterns due to migrating rain-producing phenomena.
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Improvements to the gridding of precipitation data across Europe under the E-OBS scheme
Cornes, Richard; van den Besselaar, Else; Jones, Phil; van der Schrier, Gerard; Verver, Ge
2016-04-01
Gridded precipitation data are a valuable resource for analyzing past variations and trends in the hydroclimate. Such data also provide a reference against which model simulations may be driven, compared and/or adjusted. The E-OBS precipitation dataset is widely used for such analyses across Europe, and is particularly valuable since it provides a spatially complete, daily field across the European domain. In this analysis, improvements to the E-OBS precipitation dataset will be presented that aim to provide a more reliable estimate of grid-box precipitation values, particularly in mountainous areas and in regions with a relative sparsity of input station data. The established three-stage E-OBS gridding scheme is retained, whereby monthly precipitation totals are gridded using a thin-plate spline; daily anomalies are gridded using indicator kriging; and the final dataset is produced by multiplying the two grids. The current analysis focuses on improving the monthly thin-plate spline, which has overall control on the final daily dataset. The results from different techniques are compared and the influence on the final daily data is assessed by comparing the data against gridded country-wide datasets produced by various National Meteorological Services
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Precipitation increases the occurrence of sporadic legionnaires' disease in Taiwan.
Directory of Open Access Journals (Sweden)
Nai-Tzu Chen
Full Text Available Legionnaires' disease (LD is an acute form of pneumonia, and changing weather is considered a plausible risk factor. Yet, the relationship between weather and LD has rarely been investigated, especially using long-term daily data. In this study, daily data was used to evaluate the impacts of precipitation, temperature, and relative humidity on LD occurrence in Taiwan from 1995-2011. A time-stratified 2:1 matched-period case-crossover design was used to compare each case with self-controlled data using a conditional logistic regression analysis, and odds ratios (ORs for LD occurrence was estimated. The city, gender and age were defined as a stratum for each matched set to modify the effects. For lag day- 0 to 15, the precipitation at lag day-11 significantly affected LD occurrence (p0.05. In conclusion, in warm, humid regions, an increase of daily precipitation is likely to be a critical weather factor triggering LD occurrence where the risk is found particularly significant at an 11-day lag. Additionally, precipitation at 21-40 and 61-80 mm might make LD occurrence more likely.
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Climate impacts on extreme energy consumption of different types of buildings.
Li, Mingcai; Shi, Jun; Guo, Jun; Cao, Jingfu; Niu, Jide; Xiong, Mingming
2015-01-01
Exploring changes of building energy consumption and its relationships with climate can provide basis for energy-saving and carbon emission reduction. Heating and cooling energy consumption of different types of buildings during 1981-2010 in Tianjin city, was simulated by using TRNSYS software. Daily or hourly extreme energy consumption was determined by percentile methods, and the climate impact on extreme energy consumption was analyzed. The results showed that days of extreme heating consumption showed apparent decrease during the recent 30 years for residential and large venue buildings, whereas days of extreme cooling consumption increased in large venue building. No significant variations were found for the days of extreme energy consumption for commercial building, although a decreasing trend in extreme heating energy consumption. Daily extreme energy consumption for large venue building had no relationship with climate parameters, whereas extreme energy consumption for commercial and residential buildings was related to various climate parameters. Further multiple regression analysis suggested heating energy consumption for commercial building was affected by maximum temperature, dry bulb temperature, solar radiation and minimum temperature, which together can explain 71.5 % of the variation of the daily extreme heating energy consumption. The daily extreme cooling energy consumption for commercial building was only related to the wet bulb temperature (R2= 0.382). The daily extreme heating energy consumption for residential building was affected by 4 climate parameters, but the dry bulb temperature had the main impact. The impacts of climate on hourly extreme heating energy consumption has a 1-3 hour delay in all three types of buildings, but no delay was found in the impacts of climate on hourly extreme cooling energy consumption for the selected buildings.