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Sample records for extreme daily precipitation

  1. Are hourly precipitation extremes increasing faster than daily precipitation extremes?

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    Barbero, Renaud; Fowler, Hayley; Blenkinsop, Stephen; Lenderink, Geert

    2016-04-01

    Extreme precipitation events appear to be increasing with climate change in many regions of the world, including the United States. These extreme events have large societal impacts, as seen during the recent Texas-Oklahoma flooding in May 2015 which caused several billion in damages and left 47 deaths in its path. Better understanding of past changes in the characteristics of extreme rainfall events is thus critical for reliable projections of future changes. Although it has been documented in several studies that daily precipitation extremes are increasing across parts of the contiguous United States, very few studies have looked at hourly extremes. However, this is of primary importance as recent studies on the temperature scaling of extreme precipitation have shown that increases above the Clausius-Clapeyron (~ 7% °C-1) are possible for hourly precipitation. In this study, we used hourly precipitation data (HPD) from the National Climatic Data Center and extracted more than 1,000 stations across the US with more than 40 years of data spanning the period 1950-2010. As hourly measurements are often associated with a range of issues, the data underwent multiple quality control processes to exclude erroneous data. While no significant changes were found in annual maximum precipitation using both hourly and daily resolution datasets, significant increasing trends in terms of frequency of episodes exceeding present-day 95th percentiles of wet hourly/daily precipitation were observed across a significant portion of the US. The fraction of stations with significant increasing trends falls outside the confidence interval range during all seasons but the summer. While less than 12% of stations exhibit significant trends at the daily scale in the wintertime, more than 45% of stations, mostly clustered in central and Northern United States, show significant increasing trends at the hourly scale. This suggests that short-duration storms have increased faster than daily

  2. Combination of radar and daily precipitation data to estimate meaningful sub-daily point precipitation extremes

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    Bárdossy, András; Pegram, Geoffrey

    2017-01-01

    The use of radar measurements for the space time estimation of precipitation has for many decades been a central topic in hydro-meteorology. In this paper we are interested specifically in daily and sub-daily extreme values of precipitation at gauged or ungauged locations which are important for design. The purpose of the paper is to develop a methodology to combine daily precipitation observations and radar measurements to estimate sub-daily extremes at point locations. Radar data corrected using precipitation-reflectivity relationships lead to biased estimations of extremes. Different possibilities of correcting systematic errors using the daily observations are investigated. Observed gauged daily amounts are interpolated to unsampled points and subsequently disaggregated using the sub-daily values obtained by the radar. Different corrections based on the spatial variability and the subdaily entropy of scaled rainfall distributions are used to provide unbiased corrections of short duration extremes. Additionally a statistical procedure not based on a matching day by day correction is tested. In this last procedure as we are only interested in rare extremes, low to medium values of rainfall depth were neglected leaving a small number of L days of ranked daily maxima in each set per year, whose sum typically comprises about 50% of each annual rainfall total. The sum of these L day maxima is first iterpolated using a Kriging procedure. Subsequently this sum is disaggregated to daily values using a nearest neighbour procedure. The daily sums are then disaggregated by using the relative values of the biggest L radar based days. Of course, the timings of radar and gauge maxima can be different, so the method presented here uses radar for disaggregating daily gauge totals down to 15 min intervals in order to extract the maxima of sub-hourly through to daily rainfall. The methodologies were tested in South Africa, where an S-band radar operated relatively continuously at

  3. 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.

  4. Is the intensification of precipitation extremes with global warming better detected at hourly than daily resolutions?

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    Barbero, R.; Fowler, H. J.; Lenderink, G.; Blenkinsop, S.

    2017-01-01

    Although it has been documented that daily precipitation extremes are increasing worldwide, faster increases may be expected for subdaily extremes. Here after a careful quality control procedure, we compared trends in hourly and daily precipitation extremes using a large network of stations across the United States (U.S.) within the 1950-2011 period. A greater number of significant increasing trends in annual and seasonal maximum precipitation were detected from daily extremes, with the primary exception of wintertime. Our results also show that the mean percentage change in annual maximum daily precipitation across the U.S. per global warming degree is 6.9% °C-1 (in agreement with the Clausius-Clapeyron rate) while lower sensitivities were observed for hourly extremes, suggesting that changes in the magnitude of subdaily extremes in response to global warming emerge more slowly than those for daily extremes in the climate record.

  5. Probabilistic forecast of daily areal precipitation focusing on extreme events

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    Bliefernicht, J.; Bárdossy, A.

    2007-04-01

    A dynamical downscaling scheme is usually used to provide a short range flood forecasting system with high-resolved precipitation fields. Unfortunately, a single forecast of this scheme has a high uncertainty concerning intensity and location especially during extreme events. Alternatively, statistical downscaling techniques like the analogue method can be used which can supply a probabilistic forecasts. However, the performance of the analogue method is affected by the similarity criterion, which is used to identify similar weather situations. To investigate this issue in this work, three different similarity measures are tested: the euclidean distance (1), the Pearson correlation (2) and a combination of both measures (3). The predictor variables are geopotential height at 1000 and 700 hPa-level and specific humidity fluxes at 700 hPa-level derived from the NCEP/NCAR-reanalysis project. The study is performed for three mesoscale catchments located in the Rhine basin in Germany. It is validated by a jackknife method for a period of 44 years (1958-2001). The ranked probability skill score, the Brier Skill score, the Heidke skill score and the confidence interval of the Cramer association coefficient are calculated to evaluate the system for extreme events. The results show that the combined similarity measure yields the best results in predicting extreme events. However, the confidence interval of the Cramer coefficient indicates that this improvement is only significant compared to the Pearson correlation but not for the euclidean distance. Furthermore, the performance of the presented forecasting system is very low during the summer and new predictors have to be tested to overcome this problem.

  6. Analysis of WRF extreme daily precipitation over Alaska using self-organizing maps

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    Glisan, Justin M.; Gutowski, William J.; Cassano, John J.; Cassano, Elizabeth N.; Seefeldt, Mark W.

    2016-07-01

    We analyze daily precipitation extremes from simulations of a polar-optimized version of the Weather Research and Forecasting (WRF) model. Simulations cover 19 years and use the Regional Arctic System Model (RASM) domain. We focus on Alaska because of its proximity to the Pacific and Arctic oceans; both provide large moisture fetch inland. Alaska's topography also has important impacts on orographically forced precipitation. We use self-organizing maps (SOMs) to understand circulation characteristics conducive for extreme precipitation events. The SOM algorithm employs an artificial neural network that uses an unsupervised training process, which results in finding general patterns of circulation behavior. The SOM is trained with mean sea level pressure (MSLP) anomalies. Widespread extreme events, defined as at least 25 grid points experiencing 99th percentile precipitation, are examined using SOMs. Widespread extreme days are mapped onto the SOM of MSLP anomalies, indicating circulation patterns. SOMs aid in determining high-frequency nodes, and hence, circulations are conducive to extremes. Multiple circulation patterns are responsible for extreme days, which are differentiated by where extreme events occur in Alaska. Additionally, several meteorological fields are composited for nodes accessed by extreme and nonextreme events to determine specific conditions necessary for a widespread extreme event. Individual and adjacent node composites produce more physically reasonable circulations as opposed to composites of all extremes, which include multiple synoptic regimes. Temporal evolution of extreme events is also traced through SOM space. Thus, this analysis lays the groundwork for diagnosing differences in atmospheric circulations and their associated widespread, extreme precipitation events.

  7. Trends in daily temperature and precipitation extremes over Georgia, 1971–2010

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    I. Keggenhoff

    2014-08-01

    Full Text Available Annual changes to climate extreme indices in Georgia (Southern Caucasus from 1971 to 2010 are studied using homogenized daily minimum and maximum temperature and precipitation series. Fourteen extreme temperature and 11 extreme precipitation indices are selected from the list of core climate extreme indices recommended by the World Meteorological Organization – Commission for Climatology (WMO-CCL and the research project on Climate Variability and Predictability (CLIVAR of the World Climate Research Programme (WCRP. Trends in the extreme indices are studied for 10 minimum and 11 maximum temperature and 24 precipitation series for the period 1971–2010. Between 1971 and 2010 most of the temperature extremes show significant warming trends. In 2010 there are 13.3 fewer frost days than in 1971. Within the same time frame there are 13.6 more summer days and 7.0 more tropical nights. A large number of stations show significant warming trends for monthly minimum and maximum temperature as well as for cold and warm days and nights throughout the study area, whereas warm extremes and night-time based temperature indices show greater trends than cold extremes and daytime indices. Additionally, the warm spell duration indicator indicates a significant increase in the frequency of warm spells between 1971 and 2010. Cold spells show an insignificant increase with low spatial coherence. Maximum 1-day and 5-day precipitation, the number of very heavy precipitation days, very wet and extremely wet days as well as the simple daily intensity index all show an increase in Georgia, although all trends manifest a low spatial coherence. The contribution of very heavy and extremely heavy precipitation to total precipitation increased between 1971 and 2010, whereas the number of wet days decreases.

  8. Climatology of extreme daily precipitation in Colorado and its diverse spatial and seasonal variability

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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.

  9. Estimating return periods for daily precipitation extreme events over the Brazilian Amazon

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    Santos, Eliane Barbosa; Lucio, Paulo Sérgio; Santos e Silva, Cláudio Moisés

    2016-11-01

    This paper aims to model the occurrence of daily precipitation extreme events and to estimate the return period of these events through the extreme value theory (generalized extreme value distribution (GEV) and the generalized Pareto distribution (GPD)). The GEV and GPD were applied in precipitation series of homogeneous regions of the Brazilian Amazon. The GEV and GPD goodness of fit were evaluated by quantile-quantile (Q-Q) plot and by the application of the Kolmogorov-Smirnov (KS) test, which compares the cumulated empirical distributions with the theoretical ones. The Q-Q plot suggests that the probability distributions of the studied series are appropriated, and these results were confirmed by the KS test, which demonstrates that the tested distributions have a good fit in all sub-regions of Amazon, thus adequate to study the daily precipitation extreme event. For all return levels studied, more intense precipitation extremes is expected to occur within the South sub-regions and the coastal area of the Brazilian Amazon. The results possibly will have some practical application in local extreme weather forecast.

  10. Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

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    Beranová, Romana; Kyselý, Jan; Hanel, Martin

    2017-03-01

    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.

  11. Investigate the impact of climate change on daily extreme precipitation in the eastern U.S.

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    Wang, Y.; Sivandran, G.

    2016-12-01

    Increase in heavy downpours have been observed across the U.S. An extreme index (the number of 2-day precipitation totals in a decade that exceeds a threshold corresponding to 5-year return period) has been shown to increase 30-70% in the eastern U.S. between the decades before 1960 and the 2001-2010 decade [Kunkel et al. 2013]. Intensity-Duration-Frequency (IDF) curve is a descriptive measure of extreme precipitation, and is commonly used to inform urban hydrological design. To understand how IDF curves are influenced by climate change is important for infrastructure planning and adaptation. As a first step towards this objective, this study investigates the potential changes in extreme precipitation at daily level over the eastern U.S. by a combination of statistical and dynamical downscaling approaches. The dynamical downscaling experiment is conducted with the Weather Forecast Model (Version 3.8), on the eastern U.S. domain and driven by a bias-corrected CMIP5 CESM dataset. The relationship between daily precipitation at coarse- and dynamically downscaled fine-grid levels are investigated using quantile-mapping and linear-regression methods with various calibration tweaks. The statistical relationship whose difference between future period and the historical baseline is comparable or smaller than the natural variability during 1950-2005 is then identified as not violating the stationarity assumption on the statistical relationship. The computationally cheaper identified statistical downscaling method is then used to downscale precipitation to station scale at National Weather Service Cooperative Observer Network locations on the domain. In a future study, the downscaled daily precipitation will be disaggregated to hourly level by the k-Nearest Neighbor method, and thus to facilitate construction of IDF curves. Kunkel et al. 2013 Monitoring and Understanding Trends in Extreme Storms: State of Knowledge

  12. Trends in indices of daily temperature and precipitations extremes in Morocco

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    Filahi, S.; Tanarhte, M.; Mouhir, L.; El Morhit, M.; Tramblay, Y.

    2016-05-01

    The purpose of this paper is to provide a summary of Morocco's climate extreme trends during the last four decades. Indices were computed based on a daily temperature and precipitation using a consistent approach recommended by the ETCCDI. Trends in these indices were calculated at 20 stations from 1970 to 2012. Twelve indices were considered to detect trends in temperature. A large number of stations have significant trends and confirm an increase in temperature, showing increased warming during spring and summer seasons. The results also show a decrease in the number of cold days and nights and an increase in the number of warm days and nights. Increasing trends have also been found in the absolute warmest and coldest temperatures of the year. A clear increase is detected for warm nights and diurnal temperature range. Eight indices for precipitation were also analyzed, but the trends for these precipitation indices are much less significant than for temperature indices and show more mixed spatial patterns of change. Heavy precipitation events do not exhibit significant trends except at a few locations, in the north and central parts of Morocco, with a general tendency towards drier conditions. The correlation between these climate indices and the large-scale atmospheric circulations indices such as the NAO, MO, and WEMO were also analyzed. Results show a stronger relationship with these climatic indices for the precipitation indices compared to the temperature indices. The correlations are more significant in the Atlantic regions, but they remain moderate at the whole country scale.

  13. Estimation of extreme daily precipitation: comparison between regional and geostatistical approaches.

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    Hellies, Matteo; Deidda, Roberto; Langousis, Andreas

    2016-04-01

    We study the extreme rainfall regime of the Island of Sardinia in Italy, based on annual maxima of daily precipitation. The statistical analysis is conducted using 229 daily rainfall records with at least 50 complete years of observations, collected at different sites by the Hydrological Survey of the Sardinia Region. Preliminary analysis, and the L-skewness and L-kurtosis diagrams, show that the Generalized Extreme Value (GEV) distribution model performs best in describing daily rainfall extremes. The GEV distribution parameters are estimated using the method of Probability Weighted Moments (PWM). To obtain extreme rainfall estimates at ungauged sites, while minimizing uncertainties due to sampling variability, a regional and a geostatistical approach are compared. The regional approach merges information from different gauged sites, within homogeneous regions, to obtain GEV parameter estimates at ungauged locations. The geostatistical approach infers the parameters of the GEV distribution model at locations where measurements are available, and then spatially interpolates them over the study region. In both approaches we use local rainfall means as index-rainfall. In the regional approach we define homogeneous regions by applying a hierarchical cluster analysis based on Ward's method, with L-moment ratios (i.e. L-CV and L-Skewness) as metrics. The analysis results in four contiguous regions, which satisfy the Hosking and Wallis (1997) homogeneity tests. The latter have been conducted using a Monte-Carlo approach based on a 4-parameter Kappa distribution model, fitted to each station cluster. Note that the 4-parameter Kappa model includes the GEV distribution as a sub-case, when the fourth parameter h is set to 0. In the geostatistical approach we apply kriging for uncertain data (KUD), which accounts for the error variance in local parameter estimation and, therefore, may serve as a useful tool for spatial interpolation of metrics affected by high uncertainty. In

  14. Trends and periodicity of daily temperature and precipitation extremes during 1960-2013 in Hunan Province, central south China

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    Chen, Ajiao; He, Xinguang; Guan, Huade; Cai, Yi

    2017-02-01

    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

  15. Extreme daily precipitation in coastal western Norway and the link to atmospheric rivers

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    Azad, Roohollah; Sorteberg, Asgeir

    2017-02-01

    This work investigates the link between the most extreme daily precipitation (EDP) events observed since 1900 on the west coast of Norway and the large-scale moisture fluxes over the North Atlantic Ocean. Using station precipitation data, vertically integrated water vapor (IWV) from Special Sensors Microwave Imager/Sounder (SSMIS) satellite observations and the state of the art NOAA-twentieth Century (NOAA-20C) reanalysis, it is shown that 55 out of 58 EDPs are associated with narrow plumes of intense low-level moisture defined as atmospheric rivers. Despite the high spatial correlation between IWV fields in the SSMIS and NOAA-20C data sets, the significant positive relationship between the maximum amount of observed precipitation at all stations and the IWV content hitting the coastal terrain is only observed in the SSMIS data set. Further, the composite analyses of synoptic conditions show that the preferred circulation type consists of a mean sea level pressure (MSLP) dipole pattern where a high-pressure system over central Europe and a series of low-pressure systems to the east of Iceland and over the Norwegian Sea are present. The west coast of Norway is located in the exit region of the anticyclonically curved upper tropospheric polar jet stream implying that the coupling of upper troposphere and surface dynamics begins to weaken at the time of EDPs. It is also found that the primary synoptic-scale precursors are persistent positive 500 hPa height geopotential and MSLP anomalies over central Europe up to 10 days before the occurrence of EDP events.

  16. Observed Trends in Indices of Daily Precipitation and Temperature Extremes in Rio de Janeiro State (brazil)

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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

  17. Recent changes in daily precipitation and surface air temperature extremes in mainland Portugal, in the period 1941-2007

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    de Lima, M. Isabel P.; Santo, Fátima Espírito; Ramos, Alexandre M.; de Lima, João L. M. P.

    2013-06-01

    Changes in the climatology of precipitation and surface air temperature are being investigated worldwide, searching for changes in variability, the mean and extreme events (maximum and minimum). By exploring recent adjustments in the climate of mainland Portugal, particularly in the intensity, frequency and duration of extreme events, this study investigates trends in selected specific indices that are calculated from daily precipitation data from 57 and surface air temperature data from 23 measuring stations scattered across the territory. Special attention is paid to regional differences and variations in seasonality. The data cover the periods 1941-2007 for precipitation, and 1941-2006 for temperature. They are explored at the annual and seasonal scales and for different sub-periods. Results show that trends in annual precipitation indices are generally weak and, overall, not statistically significant at the 5% level. Nevertheless, a decreasing trend is revealed by regional indices of total wet-day precipitation and extreme precipitation (above the 99th percentile). Seasonal precipitation exhibits significant decreasing trends in spring precipitation, while extreme heavy precipitation events, in terms of both magnitude and frequency, have become more pronounced in autumn. Results for winter and summer suggest that the extremes have not suffered any significant aggravation. Trends for air temperature are statistically more significant and marked than for precipitation and indicate general warming across the territory. This warming trend is revealed very consistently by the time series of individual stations and regional mean temperature, and is also consistent with the findings reported in other studies for Portugal and at the European scale.

  18. Trends and variability of daily and extreme temperature and precipitation in the Caribbean region, 1961-2010

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    Allen, T. L.; Stephenson, T. S.; Vincent, L.; Van Meerbeeck, C.; McLean, N.

    2013-05-01

    A workshop was held at the University of the West Indies, Jamaica, in May 2012 to build capacity in climate data rescue and to enhance knowledge about climate change in the Caribbean region. Scientists brought their daily surface temperature and precipitation data for an assessment of quality and homogeneity and for the preparation of climate change indices helpful for studying climate change in their region. This study presents the trends in daily and extreme temperature and precipitation indices in the Caribbean region for records spanning the 1961-2010 and 1986-2010 intervals. Overall, the results show a warming of the surface air temperature at land stations. Region-wide, annual means of the daily minimum temperatures (+1.4°C) have increased more than the annual means of the daily maximum temperatures (+0.9°C) leading to significant decrease in the diurnal temperature range. The frequency of warm days and warm nights has increased by more than 15% while 9% fewer cool days and 13% fewer cool night were found over the 50-year interval. These frequency trends are further reflected in a rise of the annual extreme high and low temperatures by ~1°C. Changes in precipitation indices are less consistent and the trends are generally weak. Small positive trends were found in annual total precipitation, daily intensity, maximum number of consecutive dry days and heavy rainfall events particularly during the period 1986- 2010. Finally, aside from the observed climate trends, correlations between these indices and the Atlantic Multidecadal Oscillation (AMO) annual index suggest a coupling between land temperature variability and, to a lesser extent, precipitation extremes on the one hand, and the AMO signal of the North Atlantic surface sea temperatures.

  19. Nonstationary frequency analysis of extreme daily precipitation amounts in Southeastern Canada using a peaks-over-threshold approach

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    Thiombiano, Alida N.; El Adlouni, Salaheddine; St-Hilaire, André; Ouarda, Taha B. M. J.; El-Jabi, Nassir

    2016-04-01

    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.

  20. Nonstationary frequency analysis of extreme daily precipitation amounts in Southeastern Canada using a peaks-over-threshold approach

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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.

  1. Trends and variability of daily temperature and precipitation extremes during 1960-2012 in the Yangtze River Basin, China

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    Guan, Yinghui

    2017-04-01

    The variability of surface air temperature and precipitation extremes has been the focus of attention during the past several decades, and may exert a great influence on the global hydrologic cycle and energy balance through thermal forcing. Using daily minimum (TN), maximum temperature (TX) and precipitation from 143 meteorological stations in the Yangtze River Basin (YRB), a suite of extreme climate indices recommended by the Expert Team on Climate Change Detection and Indices, which has rarely been applied in this region, were computed and analyzed during 1960-2012. The results show widespread significant changes in all temperature indices associated with warming in the YRB during 1960-2012. On the whole, cold-related indices, i.e., cold nights, cold days, frost days, icing days and cold spell duration index significantly decreased by -3.45, -1.03, -3.04, -0.42 and -1.6 days/decade, respectively. In contrast, warm-related indices such as warm nights, warm days, summer days, tropical nights and warm spell duration index significantly increased by 2.95, 1.71, 2.16, 1.05 and 0.73 days/decade. Minimum TN, maximum TN, minimum TX and maximum TX increased significantly by 0.42, 0.18, 0.19 and 0.14 °C/decade. Because of a faster increase in minimum temperature than maximum temperature, the diurnal temperature range (DTR) exhibited a significant decreasing trend of -0.09 °C/decade for the whole YRB during 1960-2012. Geographically, stations in the eastern Tibet Plateau and northeastern YRB showed stronger trends in almost all temperature indices. Time series analysis indicated that the YRB was dominated by a general cooling trend before the mid-1980s, but a warming trend afterwards. For precipitation, simple daily intensity index, very wet day precipitation, extremely wet day precipitation, extremely heavy precipitation days, maximum 1-day precipitation, maximum 5-day precipitation and maximum consecutive dry days all increased significantly during 1960-2012. In

  2. Assessing the importance of spatio-temporal RCM resolution when estimating sub-daily extreme precipitation under current and future climate conditions

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Luchner, J.; Onof, C.

    2017-01-01

    The increase in extreme precipitation is likely to be one of the most significant impacts of climate change in cities due to increased pluvial flood risk. Hence, reliable information on changes in sub-daily extreme precipitation is needed for robust adaptation strategies. This study explores...

  3. Trends in Daily and Extreme Temperature and Precipitation Indices for the Countries of the Western Indian Ocean, 1975-2008

    Science.gov (United States)

    Aguilar, Enric; Vincent, Lucie A.

    2010-05-01

    In the framework of the project "Renforcement des Capacités des Pays de la COI dans le Domaine de l'Adaptation au Changement Climatique (ACCLIMATE)" (Comission de l'Ocean Indien, COI), a workshop on homogenization of climate data and climate change indices analysis was held in Mauritius in October 2009, using the successful format prepared by the CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices. Scientists from the five countries in Western Indian Ocean brought daily climatological data from their region for a meticulous assessment of the data quality and homogeneity, and for the preparation of climate change indices which can be used for analyses of changes in climate extremes. Although the period of analysis is very short, it represents a seminal step for the compilation of longer data set and allows us to examine the evolution of climate extremes in the area during the time period identified as the decades where anthropogenic warming es larger than natural forcings. This study first presents some results of the homogeneity assessment using the software package RHtestV3 (Wang and Feng 2009) which has been developed for the detection of changepoints in climatological datasets. Indices based on homogenized daily temperatures and precipitations were also prepared for the analysis of trends at more than 50 stations across the region. The results show an increase in the percentage of warm days and warm nights over 1975-2008 while changes in extreme precipitations are not as consistent.

  4. Variations in Regional Mean Daily Precipitation Extremes and Related Circulation Anomalies over Central China During Boreal Summer

    Institute of Scientific and Technical Information of China (English)

    柯丹; 管兆勇

    2014-01-01

    The variations of regional mean daily precipitation extreme (RMDPE) events in central China and associated circulation anomalies during June, July, and August (JJA) of 1961-2010 are investigated by using daily in-situ precipitation observations and the NCEP/NCAR reanalysis data. The precipitation data were collected at 239 state-level stations distributed throughout the provinces of Henan, Hubei, and Hunan. During 1961-2010, the 99th percentile threshold for RMDPE is 23.585 mm day-1. The number of RMDPE events varies on both interannual and interdecadal timescales, and increases significantly after the mid 1980s. The RMDPE events happen most frequently between late June and mid July, and are generally associated with anomalous baroclinic tropospheric circulations. The supply of moisture to the southern part of central China comes in a stepping way from the outer-region of an abnormal anticyclone over the Bay of Bengal and the South China Sea. Fluxes of wave activity generated over the northeastern Tibetan Plateau converge over central China, which favors the genesis and maintenance of wave disturbances over the region. RMDPE events typically occur in tandem with a strong heating gradient formed by net heating in central China and the large-scale net cooling in the surrounding area. The occurrence of RMDPE events over central China is tied to anomalous local cyclonic circulations, topographic forcing over the northeast Tibetan Plateau, and anomalous gradients of diabatic heating between central China and the surrounding areas.

  5. Daily extreme precipitation indices and their impacts on rice yield—A case study over the tropical island in China

    Science.gov (United States)

    Li, Mao-Fen; Luo, Wei; Li, Hailiang; Liu, Enping; Li, Yuping

    2017-03-01

    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

  6. The influence of synoptic airflow on UK daily precipitation extremes. Part II: regional climate model and E-OBS data validation

    Energy Technology Data Exchange (ETDEWEB)

    Maraun, Douglas [Leibniz Institute of Marine Sciences (IFM-GEOMAR), Duesternbrooker Weg 20, 24105, Kiel (Germany); Osborn, Timothy J. [School of Environmental Sciences, Climatic Research Unit, Norwich (United Kingdom); Rust, Henning W. [Freie Universitaet Berlin, Institut fuer Meteorologie, Berlin (Germany)

    2012-07-15

    We investigate how well the variability of extreme daily precipitation events across the United Kingdom is represented in a set of regional climate models and the E-OBS gridded data set. Instead of simply evaluating the climatologies of extreme precipitation measures, we develop an approach to validate the representation of physical mechanisms controlling extreme precipitation variability. In part I of this study we applied a statistical model to investigate the influence of the synoptic scale atmospheric circulation on extreme precipitation using observational rain gauge data. More specifically, airflow strength, direction and vorticity are used as predictors for the parameters of the generalised extreme value (GEV) distribution of local precipitation extremes. Here we employ this statistical model for our validation study. In a first step, the statistical model is calibrated against a gridded precipitation data set provided by the UK Met Office. In a second step, the same statistical model is calibrated against 14 ERA40 driven 25 km resolution RCMs from the ENSEMBLES project and the E-OBS gridded data set. Validation indices describing relevant physical mechanisms are derived from the statistical models for observations and RCMs and are compared using pattern standard deviation, pattern correlation and centered pattern root mean squared error as validation measures. The results for the different RCMs and E-OBS are visualised using Taylor diagrams. We show that the RCMs adequately simulate moderately extreme precipitation and the influence of airflow strength and vorticity on precipitation extremes, but show deficits in representing the influence of airflow direction. Also very rare extremes are misrepresented, but this result is afflicted with a high uncertainty. E-OBS shows considerable biases, in particular in regions of sparse data. The proposed approach might be used to validate other physical relationships in regional as well as global climate models. (orig.)

  7. Rising Precipitation Extremes across Nepal

    Directory of Open Access Journals (Sweden)

    Ramchandra Karki

    2017-01-01

    Full Text Available As a mountainous country, Nepal is most susceptible to precipitation extremes and related hazards, including severe floods, landslides and droughts that cause huge losses of life and property, impact the Himalayan environment, and hinder the socioeconomic development of the country. Given that the countrywide assessment of such extremes is still lacking, we present a comprehensive picture of prevailing precipitation extremes observed across Nepal. First, we present the spatial distribution of daily extreme precipitation indices as defined by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI from 210 stations over the period of 1981–2010. Then, we analyze the temporal changes in the computed extremes from 76 stations, featuring long-term continuous records for the period of 1970–2012, by applying a non-parametric Mann−Kendall test to identify the existence of a trend and Sen’s slope method to calculate the true magnitude of this trend. Further, the local trends in precipitation extremes have been tested for their field significance over the distinct physio-geographical regions of Nepal, such as the lowlands, middle mountains and hills and high mountains in the west (WL, WM and WH, respectively, and likewise, in central (CL, CM and CH and eastern (EL, EM and EH Nepal. Our results suggest that the spatial patterns of high-intensity precipitation extremes are quite different to that of annual or monsoonal precipitation. Lowlands (Terai and Siwaliks that feature relatively low precipitation and less wet days (rainy days are exposed to high-intensity precipitation extremes. Our trend analysis suggests that the pre-monsoonal precipitation is significantly increasing over the lowlands and CH, while monsoonal precipitation is increasing in WM and CH and decreasing in CM, CL and EL. On the other hand, post-monsoonal precipitation is significantly decreasing across all of Nepal while winter precipitation is decreasing

  8. Anomalous Circulation Patterns in Association with Two Types of Daily Precipitation Extremes over Southeastern China during Boreal Summer

    Institute of Scientific and Technical Information of China (English)

    李明刚; 管亮勇; 金大超; 韩洁; 张茜

    2016-01-01

    Based on the daily rainfall data from China Meteorological Administration, the tropical cyclone (TC) best track data from Japan Meteorological Agency, and the NCEP-NCAR reanalysis data from NOAA, regional mean daily precipitation extreme (RDPE) events over southeastern China (specifically, the Fujian–Jiangxi region (FJR)) and the associated circulation anomalies are investigated. For the summers of 1979–2011, a total of 105 RDPE events are identified, among which 35 are TC-influenced (TCIn-RDPE) and 70 are TC-free events (TCFr-RDPE). Distinct differences between these two types of RDPEs are found in both their statistical features and the related circulation patterns. TCFr-RDPEs usually occur in June, while TCIn-RDPEs mainly take place during July–August. When TCFr-RDPEs happen, a center of the anomalous cyclonic circulation is observed over the FJR, with an anomalous anticyclonic circulation to the south of this region. The warm/moist air flows from the South China Sea (SCS) and western Pacific meet with colder air from the north, forming a narrow convergent belt of water vapor over the FJR. Simultaneously, positive diabatic forcing anomalies are observed over the FJR, whereas negative anomalies appear over both its south and north sides, facilitating the formation and maintenance of the cyclonic circulation anomaly, as well as the upward motion of the atmosphere, over the FJR. When TCIn-RDPEs occur, southeastern China is dominated by a TC-related stronger anomalous cyclonic circulation. An anomalous anticyclonic circulation in the mid and high latitudes north of the FJR exists in the mid and upper troposphere, opposite to the situation during TCFr-RDPE events. Abundant warm/wet air is carried into the FJR from both the Indian Ocean and the SCS, leading to a large amount of latent heat release over the FJR and inducing strong ascending motion there. Furthermore, large differences are also found in the manifestation of Rossby wave energy propagation between

  9. Anomalous circulation patterns in association with two types of daily precipitation extremes over southeastern China during boreal summer

    Science.gov (United States)

    Li, Minggang; Guan, Zhaoyong; Jin, Dachao; Han, Jie; Zhang, Qian

    2016-04-01

    Based on the daily rainfall data from China Meteorological Administration, the tropical cyclone (TC) best track data from Japan Meteorological Agency, and the NCEP-NCAR reanalysis data from NOAA, regional mean daily precipitation extreme (RDPE) events over southeastern China (specifically, the Fujian-Jiangxi region (FJR)) and the associated circulation anomalies are investigated. For the summers of 1979-2011, a total of 105 RDPE events are identified, among which 35 are TC-influenced (TCIn-RDPE) and 70 are TC-free events (TCFr-RDPE). Distinct differences between these two types of RDPEs are found in both their statistical features and the related circulation patterns. TCFr-RDPEs usually occur in June, while TCIn-RDPEs mainly take place during July-August. When TCFr-RDPEs happen, a center of the anomalous cyclonic circulation is observed over the FJR, with an anomalous anticyclonic circulation to the south of this region. The warm/moist air flows from the South China Sea (SCS) and western Pacific meet with colder air from the north, forming a narrow convergent belt of water vapor over the FJR. Simultaneously, positive diabatic forcing anomalies are observed over the FJR, whereas negative anomalies appear over both its south and north sides, facilitating the formation and maintenance of the cyclonic circulation anomaly, as well as the upward motion of the atmosphere, over the FJR. When TCIn-RDPEs occur, southeastern China is dominated by a TC-related stronger anomalous cyclonic circulation. An anomalous anticyclonic circulation in the mid and high latitudes north of the FJR exists in the mid and upper troposphere, opposite to the situation during TCFr-RDPE events. Abundant warm/wet air is carried into the FJR from both the Indian Ocean and the SCS, leading to a large amount of latent heat release over the FJR and inducing strong ascending motion there. Furthermore, large differences are also found in the manifestation of Rossby wave energy propagation between these

  10. Long-term trends and extremes in observed daily precipitation and near surface air temperature in the Philippines for the period 1951-2010

    Science.gov (United States)

    Cinco, Thelma A.; de Guzman, Rosalina G.; Hilario, Flaviana D.; Wilson, David M.

    2014-08-01

    Observed daily precipitation and near surface air temperature data from 34 synoptic weather stations in the Philippines for the period 1951-2010 were subjected to trend analysis which revealed an overall warming tendency compared to the normal mean values for the period 1961-1990. This warming trend can be observed in the annual mean temperatures, daily minimum mean temperatures and to a lesser extent, daily maximum mean temperatures. Precipitation and temperature extremes for the period 1951-2010 were also analysed relative to the mean 1961-1990 baseline values. Some stations (Cotabato, Iloilo, Laoag and Tacloban,) show increases in both frequency and intensity of extreme daily rainfall events which are significant at the 95% level with none of the stations showing decreasing trends. The frequency of daily temperature maximum above the 99th percentile (hot days) and nights at the 1st percentile (cold nights) suggests that both days and nights in particular are becoming warmer. Such indicators of a warming trend and increase in extreme events in the Philippines are discussed in the context of similar national, regional (Asia Pacific) and global studies. The relevance of such empirically based climatology studies, particularly for nations such as the Philippines which are increasingly vulnerable to the multiple impacts of global climate change, is also considered.

  11. How extreme is extreme hourly precipitation?

    Science.gov (United States)

    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.

  12. Trends in Precipitation Extremes over Southeast Asia

    Science.gov (United States)

    Endo, N.; Matsumoto, J.

    2010-12-01

    Trends in precipitation extremes were examined using daily precipitation data from Southeast Asian countries during 1950's to 2000's. Number of wet day, defined by a day with daily precipitation exceeding 1 mm, tends to decrease over these countries, while average precipitation intensity of wet day shows an increasing trend. Heavy precipitation indices, which are defined by precipitation amount and percentile, demonstrate that the number of stations with significant upward trend is larger than that with significant downward trend. Heavy precipitation increases in southern Vietnam, northern part of Myanmar, and the Visayas and Luzon Islands in the Philippines, while heavy precipitation decreases in northern Vietnam. Annual maximum number of consecutive dry days decreases in the region where winter monsoon precipitation dominates. Prolongation of the dry season is suggested in Myanmar.

  13. Precipitation extremes under climate change

    CERN Document Server

    O'Gorman, Paul A

    2015-01-01

    The response of precipitation extremes to climate change is considered using results from theory, modeling, and observations, with a focus on the physical factors that control the response. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate. However, the sensitivity of precipitation extremes to warming remains uncertain when convection is important, and it may be higher in the tropics than the extratropics. Several physical contributions govern the response of precipitation extremes. The thermodynamic contribution is robust and well understood, but theoretical understanding of the microphysical and dynamical contributions is still being developed. Orographic precipitation extremes and snowfall extremes respond differently from other precipitation extremes and require particular attention. Outstanding research challenges include the influence of mesoscale convective organization, the dependence on the duration considered, and the need to...

  14. Risk assessment of precipitation extremes in northern Xinjiang, China

    Science.gov (United States)

    Yang, Jun; Pei, Ying; Zhang, Yanwei; Ge, Quansheng

    2017-04-01

    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.

  15. 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.

  16. Recent changes in precipitation extremes in Romania

    Directory of Open Access Journals (Sweden)

    Adina-Eliza CROITORU

    2014-11-01

    Full Text Available Changes in daily extreme precipitations have been identified in many studies conducted at local, regional or global scales. In Romania, only little research on this issue has been done so far. The present study is focused on the analysis of the trends in daily extreme precipitations indices over a period of 53 years (1961-2013. Data sets of daily precipitation recorded in 34 weather stations were analyzed. Among them, three are located in the Carpathian Mountains area and four are located on the Black Sea Coast. The main goal was to find changes in extreme daily precipitation using a set of 13 indices adopted from the core indices developed by ETCCDMI with appropriate modifications to suit to the studied area. The series of the indices as well as their trends were generated using RClimDex software. The trends have been calculated using the linear mean square method. The findings are similar to those obtained at the global and European continental scales and the most noteworthy are: increasing trends dominate for the most of the indices, but only about 25% of them are statistically significant at α=0.05; decreasing trends are more specific to southern area of the country; decreasing trends of  R0.1, CDD and CWD dominate for the great majority of locations; the spatial distribution of the significant slopes in the area is extremely irregular.

  17. Grassland responses to precipitation extremes

    Science.gov (United States)

    Grassland ecosystems are naturally subjected to periods of prolonged drought and sequences of wet years. Climate change is expected to enhance the magnitude and frequency of extreme events at the intraannual and multiyear scales. Are grassland responses to extreme precipitation simply a response to ...

  18. 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.

  19. Hourly and Daily Precipitation Data

    Data.gov (United States)

    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.

  20. Creating a global sub-daily precipitation dataset

    Science.gov (United States)

    Lewis, Elizabeth; Blenkinsop, Stephen; Fowler, Hayley

    2016-04-01

    Extremes of precipitation can cause flooding and droughts which can lead to substantial damages to infrastructure and ecosystems and can result in loss of life. 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. The first step towards achieving this is to construct a new global sub-daily precipitation dataset. Data collection is ongoing and already covers North America, Europe, Asia and Australasia. Comprehensive, open source quality control software is being developed to set a new standard for verifying sub-daily precipitation data and a set of global hydroclimatic indices will be produced based upon stakeholder recommendations. This will provide a unique global data resource on sub-daily precipitation whose derived indices, e.g. monthly/annual maxima, will be freely available to the wider scientific community.

  1. Creating a global sub-daily precipitation dataset

    Science.gov (United States)

    Lewis, Elizabeth; Blenkinsop, Stephen; Fowler, Hayley

    2017-04-01

    Extremes of precipitation can cause flooding and droughts which can lead to substantial damages to infrastructure and ecosystems and can result in loss of life. 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. The first step towards achieving this is to construct a new global sub-daily precipitation dataset. Data collection is ongoing and already covers North America, Europe, Asia and Australasia. Comprehensive, open source quality control software is being developed to set a new standard for verifying sub-daily precipitation data and a set of global hydroclimatic indices will be produced based upon stakeholder recommendations. This will provide a unique global data resource on sub-daily precipitation whose derived indices, e.g. monthly/annual maxima, will be freely available to the wider scientific community.

  2. Historical changes and future projection of extreme precipitation in China

    Science.gov (United States)

    Yuan, Zhe; Yang, Zhiyong; Yan, Denghua; Yin, Jun

    2017-01-01

    Investigating changes in extreme precipitation, i.e., maximum precipitation for multiday events, is critical for flood management and risk assessment. Based on the observed daily precipitation from China's Ground Precipitation 0.5° × 0.5° Gridded Dataset (V2.0) and simulated daily precipitation from five general circulation models (GCMs) provided by The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), extreme precipitation indices corresponding to annual maximum 1-, 3-, 15-, and 30-day precipitation across China from 1961 to 2011 and 2011 to 2050 were calculated. Relative changes in the 10-, 20-, and 50-year return period estimates, using 1-, 3-, 15-, and 30-day precipitation, are discussed to represent changes in extreme precipitation in the future. Results show that (1) the spatial distribution of annual maximum precipitation for 1, 3, 15, and 30 days is similar with that of annual precipitation. An increasing trend from the northwest to the southeast was found, with the highest values shown to be in the plain region adjacent to the mountains and coastal area; (2) Comparing the observed and simulated data, it could be seen that climate models have good simulation of 10-, 20-, and 50-year return period events. Absolute relative error is less than 30 % in 80 % in the study area; (3) Extreme precipitation in the future has an increasing trend in China. In the south, extreme precipitation associated with short duration as well as the 50-year return period will likely increase to a comparatively large degree in the future. In the north, extreme precipitation associated with long duration and the 10-year return period will likely see a large increase in the future.

  3. Extreme Precipitation and High-Impact Landslides

    Science.gov (United States)

    Kirschbaum, Dalia; Adler, Robert; Huffman, George; Peters-Lidard, Christa

    2012-01-01

    It is well known that extreme or prolonged rainfall is the dominant trigger of landslides; however, there remain large uncertainties in characterizing the distribution of these hazards and meteorological triggers at the global scale. Researchers have evaluated the spatiotemporal distribution of extreme rainfall and landslides at local and regional scale primarily using in situ data, yet few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This research uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from Tropical Rainfall Measuring Mission (TRMM) data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurence of precipitation and rainfall-triggered landslides globally. The GLC, available from 2007 to the present, contains information on reported rainfall-triggered landslide events around the world using online media reports, disaster databases, etc. When evaluating this database, we observed that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This research also considers the sources for this extreme rainfall, citing

  4. Nonstationary modeling of extreme precipitation in China

    Science.gov (United States)

    Gao, Meng; Mo, Dingyuan; Wu, Xiaoqing

    2016-12-01

    The statistical methods based on extreme value theory have been traditionally used in meteorology and hydrology for a long time. Due to climate change and variability, the hypothesis of stationarity in meteorological or hydrological time series was usually not satisfied. In this paper, a nonstationary extreme value analysis was conducted for annual maximum daily precipitation (AMP) at 631 meteorological stations over China for the period 1951-2013. Stationarity of all 631 AMP time series was firstly tested using KPSS test method, and only 48 AMP time series showed non-stationarity at 5% significance level. The trends of these 48 nonstationary AMP time series were further tested using M-K test method. There were 25 nonstationary AMP time series mainly distributed in southern and western China showing significant positive trend at 5% level. Another 5 nonstationary AMP time series with significant negative trends were near northern urban agglomeration, Sichuan Basin, and central China. For these nonstationary AMP time series with significant positive or negative trends, the location parameter in generalized extreme value (GEV) distribution was assumed to be time-varying, and the trends were successfully characterized by the nonstationary GEV models. For the remaining 18 nonstationary AMP time series mainly in the eastern portion of China, no significant trend was detected. The correlation analysis showed that only 5 nonstationary AMP time series were significantly correlated with one or two of the four climate indices EASMI, WPI, SOI, and PDO. Then, the location and scale parameters in the GEV distribution were modeled as functions of the significantly correlated climate indices. The modeling results in this study showed that the nonstationary GEV distributions performed better than their stationary equivalents. Finally, 20-year and 50-year return levels of precipitation extremes at all 631 stations were estimated using the best fitting distribution for the year 1961

  5. Future increases in extreme precipitation exceed observed scaling rates

    Science.gov (United States)

    Bao, Jiawei; Sherwood, Steven C.; Alexander, Lisa V.; Evans, Jason P.

    2017-01-01

    Models and physical reasoning predict that extreme precipitation will increase in a warmer climate due to increased atmospheric humidity. Observational tests using regression analysis have reported a puzzling variety of apparent scaling rates including strong rates in midlatitude locations but weak or negative rates in the tropics. Here we analyse daily extreme precipitation events in several Australian cities to show that temporary local cooling associated with extreme events and associated synoptic conditions reduces these apparent scaling rates, especially in warmer climatic conditions. A regional climate projection ensemble for Australia, which implicitly includes these effects, accurately and robustly reproduces the observed apparent scaling throughout the continent for daily precipitation extremes. Projections from the same model show future daily extremes increasing at rates faster than those inferred from observed scaling. The strongest extremes (99.9th percentile events) scale significantly faster than near-surface water vapour, between 5.7-15% °C-1 depending on model details. This scaling rate is highly correlated with the change in water vapour, implying a trade-off between a more arid future climate or one with strong increases in extreme precipitation. These conclusions are likely to generalize to other regions.

  6. Does extreme precipitation intensity depend on the emissions scenario?

    Science.gov (United States)

    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.

  7. Streamflow response to increasing precipitation extremes altered by forest management

    Science.gov (United States)

    Kelly, Charlene N.; McGuire, Kevin J.; Miniat, Chelcy Ford; Vose, James M.

    2016-04-01

    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 impact of the interaction between forest management and precipitation. We use daily long-term data from paired watersheds that have undergone forest harvest or species conversion. We find that interactive effects of climate change, represented by changes in observed precipitation trends, and forest management regime, significantly alter expected streamflow most often during extreme events, ranging from a decrease of 59% to an increase of 40% in streamflow, depending upon management. Our results suggest that vegetation might be managed to compensate for hydrologic responses due to climate change to help mitigate effects of extreme changes in precipitation.

  8. Evaluation of extreme precipitation estimates from TRMM in Angola

    Science.gov (United States)

    Pombo, Sandra; de Oliveira, Rodrigo Proença

    2015-04-01

    In situ ground observation measurement of precipitation is difficult in vast and sparsely populated areas, with poor road networks. This paper examines the use of remote sensors installed in satellites and evaluates the accuracy of TRMM 3B42 annual maximum daily precipitation estimates in Angola, in West Africa, a region where ground monitoring networks are generally. TRMM 3B42 estimates of annual maximum daily precipitation are compared to ground observation data from 159 locations. As a direct comparison between the two datasets for a common specific period and sites is not possible, a statistical approach was adopted to test the hypothesis that the TRMM 3B42 estimates and the ground monitoring records exhibit similar statistical characteristics. The study shows that the annual maximum daily precipitation estimates obtained from TRMM 3B42 slightly underestimate the quantiles obtained from the in situ observations. The use of remote sensing products to estimate extreme precipitation values for engineering design purposes is however promising. A maximum daily precipitation map for a return period of 20 years was computed and in the future, as the length of the remote sensing data series increases, it may be possible to estimate annual maximum daily precipitation estimates exclusively from these datasets for larger return periods. The paper also presents maps of the PdT/PDT ratios, where PdT is the annual maximum precipitation for a duration d and a return period of T years, and PDT is the annual maximum daily precipitation for a return period of T years. In conjunction with these maps it is possible to estimate the maximum precipitation for durations between 3 h and 5 days.

  9. Recent and future extreme precipitation over Ukraine

    Science.gov (United States)

    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

  10. Spatially-based quality control for daily precipitation datasets

    Science.gov (United States)

    Serrano-Notivoli, Roberto; de Luis, Martín; Beguería, Santiago; Ángel Saz, Miguel

    2016-04-01

    There are many reasons why wrong data can appear in original precipitation datasets but their common characteristic is that all of them do not correspond to the natural variability of the climate variable. For this reason, is necessary a comprehensive analysis of the data of each station in each day, to be certain that the final dataset will be consistent and reliable. Most of quality control techniques applied over daily precipitation are based on the comparison of each observed value with the rest of values in same series or in reference series built from its nearest stations. These methods are inherited from monthly precipitation studies, but in daily scale the variability is bigger and the methods have to be different. A common character shared by all of these approaches is that they made reconstructions based on the best-correlated reference series, which could be a biased decision because, for example, a extreme precipitation occurred in one day in more than one station could be flagged as erroneous. We propose a method based on the specific conditions of the day and location to determine the reliability of each observation. This method keeps the local variance of the variable and the time-structure independence. To do that, individually for each daily value, we first compute the probability of precipitation occurrence through a multivariate logistic regression using the 10 nearest observations in a binomial mode (0=dry; 1=wet), this produces a binomial prediction (PB) between 0 and 1. Then, we compute a prediction of precipitation magnitude (PM) with the raw data of the same 10 nearest observations. Through these predictions we explore the original data in each day and location by five criteria: 1) Suspect data; 2) Suspect zero; 3) Suspect outlier; 4) Suspect wet and 5) Suspect dry. Tests over different datasets addressed that flagged data depend mainly on the number of available data and the homogeneous distribution of them.

  11. 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.

  12. Conditional simulations for fields of extreme precipitation

    Science.gov (United States)

    Bechler, Aurélien; Vrac, Mathieu; Bel, Liliane

    2014-05-01

    Many environmental models, such as hydrological models, require input data, e.g. precipitation values, correctly simulated and distributed, even at locations where no observation is available. This is particularly true for extreme events that may be of high importance for impact studies. The last decade has seen max-stable processes emerge as a powerful tool for the statistical modeling of spatial extremes. Recently, such processes have been used in climate context to perform simulations at ungauged sites based on empirical distributions of a spatial field conditioned by observed values in some locations. In this work conditional simulations of extremal t process are investigated, taking benefits of its spectral construction. The methodology of conditional simulations proposed by Dombry et al. [2013] for Brown-Resnick and Schlather models is adapted for the extremal t process with some improvements which enlarge the possible number of conditional points. A simulation study enables to highlight the role of the different parameters of the model and to emphasize the importance of the steps of the algorithm. In this work, we focus on the French Mediterranean basin, which is a key spot of occurrences of meteorological extremes such as heavy precipitation. Indeed, major extreme precipitation are regularly observed in this region near the 'cévenol" mountains. The modeling and the understanding of these extreme precipitation - the so-called 'cévenol events" - are of major importance for hydrological studies in this complex terrain since they often trigger major floods in this region. The application of our methodology on real data in this region shows that the model and the algorithm perform well provided the stationary assumptions are fulfilled.

  13. Regional frequency analysis of extremes precipitations in Northern of Mozambique

    Directory of Open Access Journals (Sweden)

    M. Álvarez

    2016-01-01

    Full Text Available Extreme precipitation events that occur over internal basins of Cabo Delgado (Northern Mozambique often result in the occurrence of flood events with associated loss of life and infrastructure. This paper presents a study of regional frequency analysis of maximum daily precipitations based on the index flood procedure with estimated parameters by L-moments approach. Observed annual maximum daily precipitation series of 12 stations with records of more than 20 years were analyzed. The discordancy and heterogeneity measures based on the L-moments suggest that the region can be considered as homogeneous. Among the candidate distributions analyzed Monte Carlo simulations identified the Generalized Logistic distribution function as the best regional fit for the region. The achieved results will be useful in hydrologic and hydraulic studies related to floods and floodplain delineation in the region.

  14. The Role of CO2 Physiological Forcing in Driving Future Precipitation Variability and Precipitation Extremes

    Science.gov (United States)

    Skinner, C. B.; Poulsen, C. J.

    2015-12-01

    Transpired water contributes roughly 25% to total precipitation over the Earth's land surface. In addition to transpiration's impact on climatological mean precipitation, recent work suggests that transpiration reduces daily and intraseasonal precipitation variability in tropical forest regions. Projected increases in the concentration of CO2 are expected to reduce transpiration through changes in plant physiology (termed the CO2 physiological effect). Here, we use an ensemble of climate model experiments to assess the potential contribution of the CO2 physiological effect to future changes in precipitation variability and extreme precipitation events. Within our model simulations, precipitation responses to the physiological effects of increased CO2 concentrations are greatest throughout the tropics. In most tropical forest regions CO2 physiological forcing increases the annual number of dry (less than 0.1 mm/day) and extremely wet (rainfall exceeds 95th percentile) days. Changes in precipitation are primarily driven by an increase in surface temperature and subsequent changes in atmospheric stability and moisture convergence over vegetated tropical land regions. Our results suggest that the plant physiological response to CO2 forcing may serve as an important contributor to future precipitation variability in the tropics, and that future work should aim to reduce uncertainty in the response of plant physiology to changes in climate.

  15. Daily and Sub-daily Precipitation for the Former USSR

    Data.gov (United States)

    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...

  16. Evolution of precipitation extremes in two large ensembles of climate simulations

    Science.gov (United States)

    Martel, Jean-Luc; Mailhot, Alain; Talbot, Guillaume; Brissette, François; Ludwig, Ralf; Frigon, Anne; Leduc, Martin; Turcotte, Richard

    2017-04-01

    Recent studies project significant changes in the future distribution of precipitation extremes due to global warming. It is likely that extreme precipitation intensity will increase in a future climate and that extreme events will be more frequent. In this work, annual maxima daily precipitation series from the Canadian Earth System Model (CanESM2) 50-member large ensemble (spatial resolution of 2.8°x2.8°) and the Community Earth System Model (CESM1) 40-member large ensemble (spatial resolution of 1°x1°) are used to investigate extreme precipitation over the historical (1980-2010) and future (2070-2100) periods. The use of these ensembles results in respectively 1 500 (30 years x 50 members) and 1200 (30 years x 40 members) simulated years over both the historical and future periods. These large datasets allow the computation of empirical daily extreme precipitation quantiles for large return periods. Using the CanESM2 and CESM1 large ensembles, extreme daily precipitation with return periods ranging from 2 to 100 years are computed in historical and future periods to assess the impact of climate change. Results indicate that daily precipitation extremes generally increase in the future over most land grid points and that these increases will also impact the 100-year extreme daily precipitation. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety. Estimated increases in precipitation associated to very extreme precipitation events (e.g. 100 years) will drastically change the likelihood of flooding and their extent in future climate. These results, although interesting, need to be extended to sub-daily durations, relevant for urban flooding protection and urban infrastructure design (e.g. sewer networks, culverts). Models and simulations at finer spatial and temporal resolution are therefore needed.

  17. STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

    Science.gov (United States)

    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

  18. Changes in extreme dry and wet precipitation spell

    Science.gov (United States)

    Papalexiou, Simon Michael; Foufoula-Georgiou, Efi; Onof, Chris

    2016-04-01

    Global warming is expected to alter the behavior of hydroclimatic variables in various ways. Therefore, it is of great importance not only to identify which hydroclimatic variables are going through changes but also which of their specific characteristics change and in what way. For example the major focus regarding precipitation has been on changes or trends in extreme events or in annual totals, obviously, not without a reason. Yet one of the aspects of precipitation we believe is of equal importance and has not been extensively studied is extreme dry and wet spells. Changes in dry and wet spells can severely impact all aspects of human lives, ranging from infrastructure planning and water resources management to agriculture and infectious disease spread. In this study we perform an extensive analysis of extreme dry and wet precipitation spells using tenths of thousands of daily precipitation records in order to identify trends or variability changes in the maximum number of consecutive dry or wet days of each year. Our final goal is to evaluate the percentage of stations globally with positive/negative trends either in the mean value or in variability of extreme dry and wet spells and assess if this percentage is statistically justifiable.

  19. Relating precipitation to fronts at a sub-daily basis

    Science.gov (United States)

    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).

  20. 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.

  1. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Precipitation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  2. Climate Prediction Center (CPC) U.S. Daily Precipitation Observations

    Data.gov (United States)

    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...

  3. Global Precipitation Climatology Project (GPCP) - Daily, Version 1.2

    Data.gov (United States)

    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,...

  4. Exploring the causes of rare extreme precipitation events

    Science.gov (United States)

    Schroeer, Katharina; Kirchengast, Gottfried

    2015-04-01

    Whereas trends of precipitation changes in general are disparate, an increase of extreme intensities of short precipitation events (daily to sub-hourly scale) with increasing temperatures seems unambiguous (e.g. Trenberth et al., Clim. Res. 47, 123-138, 2011; Berg et al., Nat. Clim. Change 13, 181-185, 2013; Kendon et al., Nat. Clim. Change 4, 570-576, 2014). In probability density functions (PDFs) of observed precipitation intensities that are frequently used in science and practice, high magnitude ("extreme") low frequency ("rare") precipitation events naturally appear at the tails of PDFs. Due to the factual data scarcity, rare extreme events ("REEs") are difficult to come by with statistical analyses. Amongst studies of extreme precipitation, statistical work nevertheless makes a major contribution to the research field. Usually as a first step, a threshold is defined to classify extreme events out of a sample (statistical extreme events, "SEEs"), where methods are affected by the sample size. Such thresholds can be described user-defined or constructed. Subsequently, a PDF is sought, fit and applied (e.g. Yilmaz et al., Hydrol. Earth Syst. Sci. 18, 4065-4076, 2014;, Papalexiou et al., Hydrol. Earth Syst. Sci. 17, 851-862, 2013). While these studies respond to the needs of engeneering practice in e.g. infrastructure design, or trend analysis of precipitation in climate studies, they a) have to ignore REEs because of practical or statistical/data limitations (i.e. left out as "residual risk") and b) tell us little about the underlying processes of the climate and weather system causing REEs. We define REEs in contrast to SEEs as to be of such occurrence that they cannot be sufficiently described nor predicted by means of a regular or fat-tailed PDF. We introduce a working hypothesis assuming that REEs are conditioned and caused by a conjunction of specific circumstances on different scales. We differentiate spatio-temporal circumstances of large

  5. Simulation of extreme precipitation over the Yangtze River Basin using Wakeby distribution

    Science.gov (United States)

    Su, Buda; Kundzewicz, Zbigniew W.; Jiang, Tong

    2009-05-01

    Based on the daily observational precipitation data at 147 stations in the Yangtze River Basin during 1960-2005 and projected daily data of 79 grid cells from the ECHAM5/ MPI-OM model in the 20th and 21st century, time series of precipitation extremes which contain AM (Annual Maximum) and MI (Munger Index) are constructed. The distribution feature of precipitation extremes is analyzed based on the two index series. Three principal results were obtained, as stated in the sequel. (i) In the past half century, the intensity of extreme heavy precipitation and drought events was higher in the mid-lower Yangtze than in the upper Yangtze reaches. Although the ECHAM5 model still can’t capture the precipitation extremes over the Yangtze River Basin satisfactorily, spatial pattern of the observed and the simulated precipitation extremes are much similar to each other. (ii) For quantifying the characteristics of extremely high and extremely low precipitation over the Yangtze River Basin, four probability distributions are used, namely: General Extreme Value (GEV), General Pareto (GPA), General Logistic (GLO), and Wakeby (WAK). It was found that WAK can adequately describe the probability distribution of precipitation extremes calculated from both observational and projected data. (iii) Return period of precipitation extremes show spatially different changes under three greenhouse gas emission scenarios. The 50-year heavy precipitation and drought events from simulated data during 1951-2000 will become more frequent, with return period below 25 years, for the most mid-lower Yangtze region in 2001-2050. The changing character of return periods of precipitation extremes should be taken into account for the hydrological design and future water resources management.

  6. Propagation of precipitation extremes into discharge extremes in a changing climate

    Science.gov (United States)

    Piras, Monica; Mascaro, Giuseppe; Deidda, Roberto; Vivoni, Enrique R.

    2015-04-01

    Mediterranean basins are characterized by high precipitation variability, which presents strong seasonality, large inter-annual fluctuations and spatial variations during single events, and by wide spatial differences of terrain and surface properties. As a consequence, these catchments are often prone to the occurrence of hydro-meteorological extremes, including storms, floods and flash-floods. Several climate projections in this area predict a general exacerbation of intensity and frequency of extreme events, thus requiring further analyses to evaluate their impact at the land surface, especially in relatively small watersheds. In this study, we used climate and hydrologic simulations produced within the Climate Induced Changes on the Hydrology of Mediterranean Basins (CLIMB) research project to analyze how precipitation extremes propagate into discharge extremes under changing climate conditions in the Rio Mannu basin (472.5 km2), an agricultural watershed located in Sardinia, Italy. The basin response to climate forcings in a reference (1971-2000; REF) and a future (2041-2070; FUT) period was simulated by using four combinations of global and regional climate models (CMs), statistical downscaling techniques, and a process based distributed hydrologic model. We first conducted statistical analyses based on the General Extreme Value (GEV) distribution on precipitation annual maxima at different durations (daily and hourly), extracted from the grids of the four selected CMs. Results show high uncertainties in climate projections, with GEV parameters differing among CMs, REF and FUT periods, and time duration. Subsequently, we fitted the GEV distribution to the series of maximum annual discharge data at daily and hourly duration, simulated by the hydrologic model at distributed basin locations. The analyses reveal that sub-basins characterized by lower slope and dominated by more impermeable soils have higher probabilities of extreme event occurrence than steeper

  7. Future changes in atmospheric circulation types and related precipitation extremes in Central Europe

    Science.gov (United States)

    Homann, Markus; Jacobeit, Jucundus; Beck, Christoph; Philipp, Andreas

    2016-04-01

    The statistical evaluation of the relationships between atmospheric circulation types and areal precipitation events took place in the context of an international project called WETRAX (Weather patterns, storm tracks and related precipitation extremes). The aim of the project was to estimate the regional flooding potential in Central Europe under enhanced climate change conditions. For parts of southern Central Europe, a gridded daily precipitation set with 6km horizontal resolution has been generated for the period 1951-2006 by the Austrian Zentralanstalt für Meteorologie und Geodynamik (ZAMG). To determine regions with similar precipitation variability, a S-mode principal component analysis has been applied. Extreme precipitation events are defined by the 95% percentile, based on regional arithmetic means of daily precipitation. Large-scale atmospheric circulation types have been derived by different statistical methods and variables using the COST733 classification software and gridded daily NCEP1 reanalysis data. To evaluate the performance of a particular circulation type classification with respect to regional precipitation extremes, multiple regression models have been derived between the circulation type frequencies as predictor variables and monthly frequencies of extreme precipitation as well as monthly rainfall amounts from these events. To estimate the regional flooding potential in Central Europe under enhanced climate change conditions, multiple regression models are applied to different projected GCM predictor data. Thus, future changes in circulation type occurrence frequencies are transferred into assessments of future changes in precipitation extremes on a regional scale.

  8. Increased Stream Temperature in Response to Extreme Precipitation Events

    Science.gov (United States)

    Wilson, C. E.; Gooseff, M. N.

    2016-12-01

    Aquatic ecosystem temperature regulation is essential to the survival of riverine fish species restricted to limited water temperature ranges. Dissolved oxygen levels, similarly necessary to fish health, are decreased by rising temperatures, as warmer waters can hold less oxygen than colder waters. Climate change projections forecast increased precipitation intensities, a trend that has already been observed in the past decade. Though extreme events are becoming more common, the stream temperature response to high-intensity rainfall is not yet completely understood. Precipitation and stream temperature records from gages in the Upper Midwestern United States were analyzed to determine whether there exists a positive relationship between high-intensity rainfall and stream temperature response. This region was chosen for its already observed trends in increasing precipitation intensity, and rural gages were used in order to minimize the effect of impervious surfaces on runoff amounts and temperature. Days with recorded precipitation were divided by an intensity threshold and classified as either high-intensity or low-intensity days. While the effects of rain events on temperature are variable, increases in stream temperature in response to high-intensity rainfall were observed. For some basins, daily maximum rates of stream temperature increase were, on average, greater for higher intensity events. Similarly, the average daily stream temperature range was higher in streams on days of high-intensity precipitation, compared to days of low-intensity events. Understanding the effect of increasing precipitation intensity in conjunction with rising air temperatures will provide insight into the future of aquatic ecosystems and their adaptation to climate change.

  9. Uncertainties of Assessing Projected Changes in Precipitation Extremes

    Science.gov (United States)

    Brekke, L. D.; Barsugli, J. J.

    2011-12-01

    Water resource managers share a common challenge in understanding what climate change could mean for future hydroclimate extremes. Understanding the uncertainty of projected changes in extremes is critical to making decisions about whether to invest in adaptation measures today or delay until more credible information becomes available. Uncertainties arise from several methodological choices including, including criteria that drive selection of global climate projection information to frame the assessment, whether and how to bias-correct global projection information, and how to represent local controls on how to spatially downscale translations of these projections. This presentation highlights such uncertainties, focusing on projected changes in precipitation indicated by two metrics: annual total and annual maximum daily amount. Attention is given to metric conditions varying from typical (i.e. metrics having 0.50 cumulative probability) to extreme (i.e. annual totals having 0.01 and 0.05 cumulative probabilities, which are relevant to drought, and annual maximum daily amounts having 0.95 and 0.99 cumulative probabilities, which are relevant to floods). The assessment is informed by an ensemble of 53 daily CMIP3 precipitation projections from the "Bias Corrected and Downscaled WCRP CMIP3 Climate Projections" web-archive (see URL), regridded over the contiguous United States from native climate model resolution to a common 2° grid and reported during 1961-2000, 2046-2065 and 2081-2100. Focusing on changes between 20-year periods, evaluations include (a) assessing changes in typical metric conditions and determining whether changes in metric distributions are statistically significant, (b) characterizing metric extremes using parametric techniques and assessing for changes in metric extremes, (c) assessing how uncertainties in projected typical and extreme metrics associate with three sources of global climate projection uncertainty (emissions scenario, global

  10. A global survey on the seasonal variation of the marginal distribution of daily precipitation

    Science.gov (United States)

    Papalexiou, Simon Michael; Koutsoyiannis, Demetris

    2016-08-01

    To characterize the seasonal variation of the marginal distribution of daily precipitation, it is important to find which statistical characteristics of daily precipitation actually vary the most from month-to-month and which could be regarded to be invariant. Relevant to the latter issue is the question whether there is a single model capable to describe effectively the nonzero daily precipitation for every month worldwide. To study these questions we introduce and apply a novel test for seasonal variation (SV-Test) and explore the performance of two flexible distributions in a massive analysis of approximately 170,000 monthly daily precipitation records at more than 14,000 stations from all over the globe. The analysis indicates that: (a) the shape characteristics of the marginal distribution of daily precipitation, generally, vary over the months, (b) commonly used distributions such as the Exponential, Gamma, Weibull, Lognormal, and the Pareto, are incapable to describe "universally" the daily precipitation, (c) exponential-tail distributions like the Exponential, mixed Exponentials or the Gamma can severely underestimate the magnitude of extreme events and thus may be a wrong choice, and (d) the Burr type XII and the Generalized Gamma distributions are two good models, with the latter performing exceptionally well.

  11. Changes to the temporal distribution of daily precipitation

    Science.gov (United States)

    Rajah, Kailash; O'Leary, Tess; Turner, Alice; Petrakis, Gabriella; Leonard, Michael; Westra, Seth

    2014-12-01

    Changes to the temporal distribution of daily precipitation were investigated using a data set of 12,513 land-based stations from the Global Historical Climatology Network. The distribution of precipitation was measured using the Gini index (which describes how uniformly precipitation is distributed throughout a year) and the annual number of wet days. The Mann-Kendall test and a regression analysis were used to assess the direction and rate of change to both indices. Over the period of 1976-2000, East Asia, Central America, and Brazil exhibited a decrease in the number of both wet and light precipitation days, and eastern Europe exhibited a decrease in the number of both wet and moderate precipitation days. In contrast, the U.S., southern South America, western Europe, and Australia exhibited an increase in the number of both wet and light precipitation days. Trends in both directions were field significant at the global scale.

  12. Experimental Simulations of Extreme Precipitation Based on the Multi-Status Markov Chain Model

    Institute of Scientific and Technical Information of China (English)

    DING Yuguo; ZHANG Jinling; JIANG Zhihong

    2010-01-01

    A multi-status Markov chain model is proposed to produce daily rainrall, and based on which extreme rainfall is simulated with the generalized Pareto distribution (GPD). The simulated daily rainfall shows high precision at most stations, especially in pluvial regions of East China. The analysis reveals that the multi-status Markov chain model excels the bi-status Markov chain model in simulating climatic features of extreme rainfall. Results from the selected six stations demonstrate excellent simulations in the following aspects: standard deviation of monthly precipitation, daily maximum precipitation, the monthly mean rainfall days, standard deviation of daily precipitation and mean daily precipitation, which are proved to be consistent with the observations. A comparative study involving 78 stations in East China also reveals good consistency in monthly mean rainfall days and mean daily maximum rainfall, except mean daily rainfall. Simulation results at the above 6 stations have shown satisfactory fitting capability of the extreme precipitation GPD method. Good analogy is also found between simulation and observation in threshold and return values. As the errors of the threshold decrease, so do the differences between the return and real values. All the above demonstrates the applicability of the Markov chain model to extreme rainfall simulations.

  13. Stochastic daily precipitation model with a heavy-tailed component

    Science.gov (United States)

    Neykov, N. M.; Neytchev, P. N.; Zucchini, W.

    2014-09-01

    Stochastic daily precipitation models are commonly used to generate scenarios of climate variability or change on a daily timescale. The standard models consist of two components describing the occurrence and intensity series, respectively. Binary logistic regression is used to fit the occurrence data, and the intensity series is modeled using a continuous-valued right-skewed distribution, such as gamma, Weibull or lognormal. The precipitation series is then modeled using the joint density, and standard software for generalized linear models can be used to perform the computations. A drawback of these precipitation models is that they do not produce a sufficiently heavy upper tail for the distribution of daily precipitation amounts; they tend to underestimate the frequency of large storms. In this study, we adapted the approach of Furrer and Katz (2008) based on hybrid distributions in order to correct for this shortcoming. In particular, we applied hybrid gamma-generalized Pareto (GP) and hybrid Weibull-GP distributions to develop a stochastic precipitation model for daily rainfall at Ihtiman in western Bulgaria. We report the results of simulations designed to compare the models based on the hybrid distributions and those based on the standard distributions. Some potential difficulties are outlined.

  14. Changing Temperature and Precipitation Extremes in Europe's Climate of the 20th Century

    NARCIS (Netherlands)

    Klein Tank, Albertus Maria Gerardus

    2004-01-01

    This thesis aims at increasing the knowledge on past changes in extremes through the analysis of historical records of observations at meteorological stations. The key question addressed is: How did the extremes of daily surface air temperature and precipitation change in Europe's climate of the

  15. Corresponding Relation between Warm Season Precipitation Extremes and Surface Air Temperature in South China

    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℃.

  16. Regional Annual Extreme Precipitation Modeling: Choose Your Parents Wisely.

    Science.gov (United States)

    Fennessey, N. M.

    2001-05-01

    A great deal of research has been invested in developing a better understanding of the characteristics of and descriptive models of annual extreme precipitation. Some advocate the analysis of the annual maximum series (AMS) others advocate the analysis of partial duration series (PDS). The former is easy to generate, the latter provides more information, which is advantageous for better estimation. Both schools of thought seem to agree that the generalized extreme value (GEV) distribution is a good choice for the annual extreme precipitation event. Recently published work suggests that the generalized Pareto distribution (GPA) is a good choice for generating a PDS because of its analytical link with the GEV. There are, however, two well-recognized disadvantages to using the GPA for this purpose. The analyst must specify both a sampling threshold/lower-bound and a minimum time between peaks to create an acceptable PDS. Using L-moment diagrams and regional frequency analysis, a paper presented at the 1998 Spring AGU meeting suggests that daily precipitation observed in the northeast U.S. is much better described by a two parameter gamma distribution than the three parameter GPA. The 116 NOAA observatories used have periods-of-record which range from 15 to 60 complete years of no missing daily data. The observed AMS in this region is well described by a GEV. In the present work, using the L-moment estimators developed from these daily observations, serially independent gamma distributed, three parameter Pearson Type III (PE3) distributed and three parameter GPA distributed quantiles are generated for a daily period-of-record equal to that of each parent NOAA observatory. No efforts are made to specify a GPA lower bound, but many synthetic days of rainfall have negative values. The maximum value within each 365-day simulation year is retained to create three synthetic AMS, each with a different parent. L-moment diagrams of the observed, gamma day, PE3 day and GPA day

  17. Precipitation and temperatures extremes in East Africa in past and future climate

    OpenAIRE

    Kuya, Elinah Khasandi

    2016-01-01

    Climate change has increased extreme weather events over the planet. The most robust changes in East Africa (EA) are for daily temperature and precipitation, where high-impact extreme values have become more common. The overall magnitude, seasonal distribution of precipitation and its inter-annual variability have been altered. East Africa experiences some of the most severe convective storms in the world. They can come without warning and are becoming more frequent. These changes present sig...

  18. The Peak Structure and Future Changes of the Relationships Between Extreme Precipitation and Temperature

    Science.gov (United States)

    Wang, Guiling; Wang, Dagang; Trenberth, Kevin E.; Erfanian, Amir; Yu, Miao; Bosilovich, Michael G.; Parr, Dana T.

    2017-01-01

    Theoretical models predict that, in the absence of moisture limitation, extreme precipitation intensity could exponentially increase with temperatures at a rate determined by the Clausius-Clapeyron (C-C) relationship. Climate models project a continuous increase of precipitation extremes for the twenty-first century over most of the globe. However, some station observations suggest a negative scaling of extreme precipitation with very high temperatures, raising doubts about future increase of precipitation extremes. Here we show for the present-day climate over most of the globe,the curve relating daily precipitation extremes with local temperatures has a peak structure, increasing as expected at the low medium range of temperature variations but decreasing at high temperatures. However, this peak-shaped relationship does not imply a potential upper limit for future precipitation extremes. Climate models project both the peak of extreme precipitation and the temperature at which it peaks (T(sub peak)) will increase with warming; the two increases generally conform to the C-C scaling rate in mid- and high-latitudes,and to a super C-C scaling in most of the tropics. Because projected increases of local mean temperature (T(sub mean)) far exceed projected increases of T(sub peak) over land, the conventional approach of relating extreme precipitation to T(sub mean) produces a misleading sub-C-C scaling rate.

  19. Precipitation extreme changes exceeding moisture content increases in MIROC and IPCC climate models.

    Science.gov (United States)

    Sugiyama, Masahiro; Shiogama, Hideo; Emori, Seita

    2010-01-12

    Precipitation extreme changes are often assumed to scale with, or are constrained by, the change in atmospheric moisture content. Studies have generally confirmed the scaling based on moisture content for the midlatitudes but identified deviations for the tropics. In fact half of the twelve selected Intergovernmental Panel on Climate Change (IPCC) models exhibit increases faster than the climatological-mean precipitable water change for high percentiles of tropical daily precipitation, albeit with significant intermodel scatter. Decomposition of the precipitation extreme changes reveals that the variations among models can be attributed primarily to the differences in the upward velocity. Both the amplitude and vertical profile of vertical motion are found to affect precipitation extremes. A recently proposed scaling that incorporates these dynamical effects can capture the basic features of precipitation changes in both the tropics and midlatitudes. In particular, the increases in tropical precipitation extremes significantly exceed the precipitable water change in Model for Interdisciplinary Research on Climate (MIROC), a coupled general circulation model with the highest resolution among IPCC climate models whose precipitation characteristics have been shown to reasonably match those of observations. The expected intensification of tropical disturbances points to the possibility of precipitation extreme increases beyond the moisture content increase as is found in MIROC and some of IPCC models.

  20. Climate changes in temperature and precipitation extremes in an alpine grassland of Central Asia

    Science.gov (United States)

    Hu, Zengyun; Li, Qingxiang; Chen, Xi; Teng, Zhidong; Chen, Changchun; Yin, Gang; Zhang, Yuqing

    2016-11-01

    The natural ecosystem in Central Asia is sensitive and vulnerable to the arid and semiarid climate variations, especially the climate extreme events. However, the climate extreme events in this area are still unclear. Therefore, this study analyzed the climate variability in the temperature and precipitation extreme events in an alpine grassland (Bayanbuluk) of Central Asia based on the daily minimum temperature, daily maximum temperature, and daily precipitation from 1958 to 2012. Statistically significant ( p < 0.01) increasing trends were found in the minimum temperature, maximum temperature at annual, and seasonal time scales except the winter maximum temperature. In the seasonal changes, the winter temperature had the largest contribution to the annual warming. Further, there appeared increasing trends for the warm nights and the warm days and decreasing trends for the cool nights and the cool days at a 99 % confidence level. These trends directly resulted in an increasing trend for the growing season length (GSL) which could have positively influence on the vegetation productivity. For the precipitation, it displayed an increasing trend for the annual precipitation although it was not significant. And the summer precipitation had the same variations as the annual precipitation which indicated that the precipitation in summer made the biggest contribution to the annual precipitation than the other three seasons. The winter precipitation had a significant increasing trend (1.49 mm/10a) and a decreasing trend was found in spring. We also found that the precipitation of the very wet days mainly contributes to the annual precipitation with the trend of 4.5 mm/10a. The maximum 1-day precipitation and the heavy precipitation days only had slight increasing trend. A sharp decreasing trend was found before the early 1980s, and then becoming increase for the above three precipitation indexes. The climate experienced a warm-wet abrupt climate change in the 1980s

  1. Daily precipitation in a changing climate: lessons learnt from Swiss national climate change scenario initiatives

    Science.gov (United States)

    Fischer, Andreas; Liniger, Mark; Zubler, Elias; Keller, Denise; Rajczak, Jan; Schär, Christoph

    2015-04-01

    Precipitation is a key variable in the climate system that affects many aspects of the hydrological cycle such as river runoff, snow amount, or droughts. Climate change projections of precipitation and related impacts are therefore of fundamental concern for multiple sectors in many regions. Within the Swiss national climate change initiatives CH2011 and CH2014, several precipitation-dependent impacts were quantitatively assessed. This included consideration of projections of the mean annual cycle, as well as changes in extremes, wet-day frequency, and spell lengths. To better understand the needs of the primary and intermediary users of climate model data in Switzerland, a dialogue between the climate modeling and impact communities was established over recent years. In this presentation, we like to report about our experience with these needs, and on the steps we undertook to approach the emerging challenges regarding changes in precipitation. In our work beyond CH2011, the multi-faceted characteristics of precipitation change over Switzerland are investigated based on the joint analysis of several regional climate model (RCM) simulations from ENSEMBLES at the A1B emission scenario. In some seasons, changes in precipitation frequency and intensity compensate each other, in other seasons just one of these two components changes. Yet, extreme daily precipitation events are projected to intensify in most seasons. In summer, a reduction of frequency yields an augmented risk of more multi-day dry spells and meteorological summer droughts. It is also in summer, when the model simulations exhibit an elevation-dependent shift in precipitation type toward more convective precipitation. To accommodate the common need of many end-users in obtaining quantitative future projection data at multiple stations, we use a stochastic multi-site precipitation generator as main downscaling technique. In the presentation, we will present first results thereof and discuss, how end

  2. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    Science.gov (United States)

    Hwang, Y.; Clark, M.; 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.

  3. Regional trends of daily precipitation indices in northwest Mexico and southwest United States

    Science.gov (United States)

    Arriaga-RamíRez, Sarahí; Cavazos, Tereza

    2010-07-01

    A regionalization based on a rotated principal component analysis (PCA) was used to produce six precipitation regions in northwest Mexico and the southwest United States. Monthly precipitation data from 184 meteorological stations for the 1960-1997 period were used in the PCA. The aim of this study was to estimate annual and seasonal trends of 10 daily precipitation indices in the six regions, including four indices related with extreme precipitation. The annual indices show a larger number of statistically significant trends than the seasonal indices, especially in Arizona-New Mexico and in the monsoon region in northwest Mexico (MON). Significant positive trends common to these two contiguous regions are extreme precipitation exceeding the 95th (R95p) and 99th (R99p) percentiles. The analysis of summer (June-October) daily precipitation indices also reveals the occurrence of significant positive trends in R95p in MON, mainly due to tropical cyclone activity. With the exception of the trends in MON, the most important contribution to the annual trends comes from the winter indices. Four of the six regions in the study area show significant positive trends in extreme winter precipitation (R10mm, R95p or R99p) during the study period. The variability of the annual indices that show statistically significant trends in extreme precipitation are partially linked to natural variations resulting from the combined effects of El Niño/Southern Oscillation and the Pacific decadal oscillation (PDO) and, in most cases, the trends are explained by the PDO.

  4. High-resolution projections of mean and extreme precipitations over China through PRECIS under RCPs

    Science.gov (United States)

    Zhu, Jinxin; Huang, Gordon; Wang, Xiuquan; Cheng, Guanhui; Wu, Yinghui

    2017-08-01

    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

  5. The nonstationary impact of local temperature changes and ENSO on extreme precipitation at the global scale

    Science.gov (United States)

    Sun, Qiaohong; Miao, Chiyuan; Qiao, Yuanyuan; Duan, Qingyun

    2017-02-01

    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.

  6. More extreme precipitation in the world’s dry and wet regions

    Science.gov (United States)

    Donat, Markus G.; Lowry, Andrew L.; Alexander, Lisa V.; O'Gorman, Paul A.; Maher, Nicola

    2016-05-01

    Intensification of the hydrological cycle is expected to accompany a warming climate. It has been suggested that changes in the spatial distribution of precipitation will amplify differences between dry and wet regions, but this has been disputed for changes over land. Furthermore, precipitation changes may differ not only between regions but also between different aspects of precipitation, such as totals and extremes. Here we investigate changes in these two aspects in the world’s dry and wet regions using observations and global climate models. Despite uncertainties in total precipitation changes, extreme daily precipitation averaged over both dry and wet regimes shows robust increases in both observations and climate models over the past six decades. Climate projections for the rest of the century show continued intensification of daily precipitation extremes. Increases in total and extreme precipitation in dry regions are linearly related to the model-specific global temperature change, so that the spread in projected global warming partly explains the spread in precipitation intensification in these regions by the late twenty-first century. This intensification has implications for the risk of flooding as the climate warms, particularly for the world’s dry regions.

  7. The influence of physics parameterizations on precipitation extremes in the Newcastle east coast low of 2007

    Science.gov (United States)

    Gilmore, J.; Evans, J. P.; Sherwood, S. C.

    2012-12-01

    East coast low (ECL) events are one of the major sources of extreme precipitation on the eastern Australian seaboard. In fact, it is not uncommon for a location to receive a significant portion of its average yearly rainfall in one to two days from an ECL event. Because of this, developing ways to accurately simulate ECL events and compare modeled extreme precipitation to observations is an important and challenging goal. We investigate how the Weather Research and Forecasting (WRF) model simulates extreme precipitation for ECL events with an emphasis on understanding the connection to model physics. We focus on the Newcastle ECL of 2007, which was one of the most powerful ECLs in recent memory, with high precipitation and strong winds in the Newcastle area. We examine the sensitivity of precipitation extremes to microphysical schemes, radiation schemes, boundary and surface layer physics, and cumulus parameterizations. Using the Bureau of Meteorology rain gauge network, we compare the observed hourly accumulations to the model precipitation fields using an ensemble based approach. This comparison shows that WRF, when appropriately configured, does simulate the extreme precipitation well, although there are important differences between the physics parameterizations. Also, we show how the cumulus parametrization, and to a lesser extent the boundary layer, can have a significant impact on the most extreme hourly accumulations. Extreme accumulations on daily and longer time scales are less sensitive to the choice of physical parametrization.

  8. 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.

  9. Comparison of downscaling methods for mean and extreme precipitation in Senegal

    Directory of Open Access Journals (Sweden)

    M.A. Sarr

    2015-09-01

    New hydrological insights for the region: Results show that the two downscaling techniques generally agree on the direction of the change when applied to the outputs of same RCM, but some cases lead to very different projections of the direction and magnitude of the change. Projected changes indicate a decline in mean precipitation except for one RCM over one region in Senegal. Projected changes in extreme precipitations are not consistent across stations and return periods. The choice of the downscaling technique has more effect on the estimation of extreme daily precipitations of return period equal or greater than ten years than the choice of the climate models.

  10. Seasonal Variability of Precipitation Extremes in New York City

    Science.gov (United States)

    Polanco, W.

    2016-12-01

    Precipitation extremes can have very important impacts, and it is not known as to how precipitation extremes might change with global warming. New York City is located in the mid-latitude region where there are specific storms that can cause precipitation extremes, predominantly, hurricanes, extratropical cyclones, and quasi-linear convective systems. These storms preferentially occur during different seasons. Therefore, to understand how these different storms relate to precipitation extremes, this study examines NYC precipitation extremes per season. First, NOAA weather station data from January 1979 to December 2014 from the three NYC airports (JFK, LaGuardia and Newark) will be analyzed to derive the climatology, the counts of non-rain events, and the counts of extreme precipitation events. Next, a multi-station average will be used to compare the precipitation events that occur in Spring, Summer, and Fall. The precipitation strength will be compared as well as the temperature anomalies for each season. Then, using reanalysis, composites of the sea level pressure and temperature fields will be calculated for the top events from each season.

  11. Impacts of extreme precipitation and seasonal changes in precipitation on plants

    Directory of Open Access Journals (Sweden)

    M. J. B. Zeppel

    2013-10-01

    Full Text Available The hydrological cycle is predicted to become more intense in future climates, with both larger precipitation events and longer times between events. Redistribution of precipitation may occur both within and across seasons, and the resulting wide fluctuations in soil water content may dramatically affect plants. Though these responses remain poorly understood, recent research in this emerging field suggests the effects of redistributed precipitation may differ from predictions based on previous drought studies. We review available studies on both extreme precipitation (redistribution within seasons and seasonal changes in precipitation (redistribution across seasons on grasslands and forests. Extreme precipitation differentially affected Aboveground Net Primary Productivity (ANPP, depending on whether extreme precipitation led to increased or decreased soil water content (SWC, which differed based on the current precipitation at the site. Specifically, studies to date reported that extreme precipitation decreased ANPP in mesic sites, but, conversely, increased ANPP in xeric sites, suggesting that plant available water is a key factor driving responses to extreme precipitation. Similarly, the effects of seasonal changes in precipitation on ANPP, phenology, and leaf and fruit development varied with the effect on SWC. Reductions in spring or summer generally had negative effects on plants, associated with reduced SWC, while subsequent reductions in autumn or winter had little effect on SWC or plants. Similarly, increased summer precipitation had a more dramatic impact on plants than winter increases in precipitation. The patterns of response suggest xeric biomes may respond positively to extreme precipitation, while comparatively mesic biomes may be more likely to be negatively affected. And, seasonal changes in precipitation during warm or dry seasons may have larger effects than changes during cool or wet seasons. Accordingly, responses to

  12. Nonstationarity in timing of extreme precipitation across China and impact of tropical cyclones

    Science.gov (United States)

    Gu, Xihui; Zhang, Qiang; Singh, Vijay P.; Shi, Peijun

    2017-02-01

    This study examines the seasonality and nonstationarity in the timing of extreme precipitation obtained by annual maximum (AM) sampling and peak-over-threshold (POT) sampling techniques using circular statistics. Daily precipitation data from 728 stations with record length of at least 55 years across China were analyzed. In general, the average seasonality is subject mainly to summer season (June-July - August), which is potentially related to East Asian monsoon and Indian monsoon activities. The strength of precipitation seasonality varied across China with the highest strength being in northeast, north, and central-north China; whereas the weakest seasonality was found in southeast China. There are three seasonality types: circular uniform, reflective symmetric, and asymmetric. However, the circular uniform seasonality of extreme precipitation was not detected at stations across China. The asymmetric distribution was observed mainly in southeast China, and the reflective distribution of precipitation extremes was also identified the other regions besides the above-mentioned regions. Furthermore, a strong signal of nonstationarity in the seasonality was detected at half of the weather stations considered in the study, exhibiting a significant shift in the timing of extreme precipitation, and also significant trends in the average and strength of seasonality. Seasonal vapor flux and related delivery pathways and also tropical cyclones (TCs) are most probably the driving factors for the shifts or changes in the seasonality of extreme precipitation across China. Timing of precipitation extremes is closely related to seasonal shifts of floods and droughts and which means much for management of agricultural irrigation and water resources management. This study sheds new light on nonstationarity in timing of precipitation extremes which differs from existing ones which focused on precipitation extremes from perspective of magnitude and intensity.

  13. The link between convective organization and extreme precipitation in a warming climate

    Science.gov (United States)

    Pendergrass, Angeline

    2016-04-01

    The rate of increase of extreme precipitation in response to global warming varies dramatically across simulations of warming with different climate models, particularly over the tropical oceans, for reasons that have yet to be established. Here, we propose one possible mechanism: changing organization of convection with climate. Recently, self-organization of convection has been studied in global radiative-convective equilibrium climate model simulations. We analyze a set of 20 simulations forced by fixed SSTs at 2 degree increments from 287 to 307 K with the Community Atmosphere Model version 5 (CAM5). In these simulations, a transition from unorganized to organized convection occurs at just over 300 K. Precipitation extremes increase steadily with warming before and after the transition from unorganized to organized states, but at the transition the change in extreme precipitation is much larger. We develop a metric for convective organization in conjunction with the characteristics of extreme precipitation events (defined as events with precipitation over a percentile threshold of daily rainfall accumulation): the number of events, their area, their lifetime, and their mean rainfall, and use this to explore the connection between extreme precipitation and organization. We also apply this metric to CMIP5 simulations to evaluate whether our mechanism has bearing on the range of tropical ocean extreme precipitation response across this set of comprehensive climate models.

  14. The new record of daily precipitation in Lisbon since 1864: diagnosis and impacts of an exceptional precipitation episode

    Science.gov (United States)

    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

  15. Trend in frequency of extreme precipitation events over Ontario from ensembles of multiple GCMs

    Science.gov (United States)

    Deng, Ziwang; Qiu, Xin; Liu, Jinliang; Madras, Neal; Wang, Xiaogang; Zhu, Huaiping

    2016-05-01

    As one of the most important extreme weather event types, extreme precipitation events have significant impacts on human and natural environment. This study assesses the projected long term trends in frequency of occurrence of extreme precipitation events represented by heavy precipitation days, very heavy precipitation days, very wet days and extreme wet days over Ontario, based on results of 21 CMIP3 GCM runs. To achieve this goal, first, all model data are linearly interpolated onto 682 grid points (0.45° × 0.45°) in Ontario; Next, biases in model daily precipitation amount are corrected with a local intensity scaling method to make the total wet days and total wet day precipitation from each of the GCMs are consistent with that from the climate forecast system reanalysis data, and then the four indices are estimated for each of the 21 GCM runs for 1968-2000, 2046-2065 and 2081-2100. After that, with the assumption that the rate parameter of the Poisson process for the occurrence of extreme precipitation events may vary with time as climate changes, the Poisson regression model which expresses the log rate as a linear function of time is used to detect the trend in frequency of extreme events in the GCMs simulations; Finally, the trends and their uncertainty are estimated. The result shows that in the twenty-first century annual heavy precipitation days, very heavy precipitation days and very wet days and extreme wet days are likely to significantly increase over major parts of Ontario and particularly heavy precipitation days, very wet days are very likely to significantly increase in some sub-regions in eastern Ontario. However, trends of seasonal indices are not significant.

  16. 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...... by extreme precipitation pose a threat to human life and cause high economic losses for society. Thus, strategies to adapt to changes in extreme precipitation are currently being developed and established worldwide. Information on the expected changes in extreme precipitation is required for the development...... 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...

  17. Spatial and temporal variability of daily precipitation concentration in the Lancang River basin, China

    Science.gov (United States)

    Shi, Wanli; Yu, Xuezhong; Liao, Wengen; Wang, Ying; Jia, Baozhen

    2013-07-01

    The Lorenz Curve, a concept used in economic theory, is used to quantify spatial-temporal variability in the daily time series of precipitation concentrations. The Lorenz Curve provides a graphical view of the cumulative percentage of total yearly precipitation. In addition, further extraction of the data using the Gini coefficient and Lorenz asymmetry coefficient provides a two-parameter measure of precipitation concentration and an explanation of the basis for the underlying inequalities in precipitation distribution. Based on the calculation of the precipitation concentration index (CI) and the Lorenz asymmetry coefficient (S) values from 1960 to 2010, variations in the trends and periodic temporal-spatial patterns of precipitation at 31 stations across the Lancang River basin are discussed. The results are as follows: (1) highest precipitation CI values occurred in the southern Lancang River basin, whereas the lowest precipitation CI values were mainly observed in the upper reaches of the Lancang River basin, which features a more homogeneous temporal distribution of rainfall. S values throughout the entire basin were less than one, indicating that minor precipitation events have the highest contribution to overall precipitation inequality. (2) Application of the Mann-Kendall test revealed that a significant, decreasing trend in precipitation CI that exceeding the 95th percentile was detected in the upper and middle reaches of the Lancang River basin. However, there was only one significant (0.05) S value trend throughout the river. (3) Climate jumps in annual CI occurred during the early 1960s, 1970s and 1980s at Jinghong, Deqin and Zaduo stations, respectively. (4) Dominant periodic variations in precipitation CI, with periods of 4-17 years, were found. These results allow for an improved understanding of extreme climate events and improved river basin water resource management.

  18. Temperature and precipitation extremes in century-long gridded observations, reanalyses, and atmospheric model simulations

    Science.gov (United States)

    Donat, Markus G.; Alexander, Lisa V.; Herold, Nicholas; Dittus, Andrea J.

    2016-10-01

    Knowledge about long-term changes in climate extremes is vital to better understand multidecadal climate variability and long-term changes and to place today's extreme events in a historical context. While global changes in temperature and precipitation extremes since the midtwentieth century are well studied, knowledge about century-scale changes is limited. This paper analyses a range of largely independent observations-based data sets covering 1901-2010 for long-term changes and interannual variability in daily scale temperature and precipitation extremes. We compare across data sets for consistency to ascertain our confidence in century-scale changes in extremes. We find consistent warming trends in temperature extremes globally and in most land areas over the past century. For precipitation extremes we find global tendencies toward more intense rainfall throughout much of the twentieth century; however, local changes are spatially more variable. While global time series of the different data sets agree well after about 1950, they often show different changes during the first half of the twentieth century. In regions with good observational coverage, gridded observations and reanalyses agree well throughout the entire past century. Simulations with an atmospheric model suggest that ocean temperatures and sea ice may explain up to about 50% of interannual variability in the global average of temperature extremes, and about 15% in the global average of moderate precipitation extremes, but local correlations are mostly significant only in low latitudes.

  19. Impacts of Irrigation on Daily Extremes in the Coupled Climate System

    Science.gov (United States)

    Puma, Michael J.; Cook, Benjamin I.; Krakauer, Nir; Gentine, Pierre; Nazarenka, Larissa; Kelly, Maxwell; Wada, Yoshihide

    2014-01-01

    Widespread irrigation alters regional climate through changes to the energy and water budgets of the land surface. Within general circulation models, simulation studies have revealed significant changes in temperature, precipitation, and other climate variables. Here we investigate the feedbacks of irrigation with a focus on daily extremes at the global scale. We simulate global climate for the year 2000 with and without irrigation to understand irrigation-induced changes. Our simulations reveal shifts in key climate-extreme metrics. These findings indicate that land cover and land use change may be an important contributor to climate extremes both locally and in remote regions including the low-latitudes.

  20. Extreme precipitation patterns reduced terrestrial ecosystem production across biomes

    Science.gov (United States)

    Zhang, Y.; Moran, S. M.; Nearing, M.; Ponce Campos, G. E.; Huete, A. R.; Buda, A. R.; Bosch, D. D.; Gunter, S. A.; Kitchen, S. G.; McNab, W.; Morgan, J. A.; McClaran, M. P.; Montoya, D. S.; Peters, D. P.; Starks, P. J.

    2012-12-01

    Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more intense 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 novel climatic conditions on aboveground net primary production (ANPP) by combining a greenness index from satellite measurements and climatic records during 2000 to 2009 from 11 long-term experimental sites in multiple biomes and climates. Results showed that extreme precipitation patterns decreased the sensitivity of ANPP to total annual precipitation (PT), at the regional and decadal scales, leading to a mean 20% decrease in rain-use efficiency across biomes. Relative decreases in ANPP were greatest for arid grassland (16%) and Mediterranean forest (20%), and less for mesic grassland and temperate forest (3%). The co-occurrence of more heavy rainfall events and longer dry intervals caused greater water stress that resulted in reduced vegetation production. A new generalized model was developed to improve predictions of the ANPP response to changes in extreme precipitation patterns by using a function of both PT and an index of precipitation extremes. These findings suggest that extreme precipitation patterns have more substantial and complex effects on vegetation production across biomes, and are as important as total annual precipitation in understanding vegetation processes. With predictions of more extreme weather events, forecasts of ecosystem production should consider these non-linear responses to altered precipitation patterns associated with climate change. Figure. Relation of production across precipitation gradients for 11 sites for two groups (Low: R95p% definitions. The relations were significantly different for the two groups (F2, 106 = 18.51, P < 0.0001).

  1. Individual and coupled influences of AMO and ENSO on regional precipitation characteristics and extremes

    Science.gov (United States)

    Goly, Aneesh; Teegavarapu, Ramesh S. V.

    2014-06-01

    Understanding the influences of Atlantic multidecadal oscillation (AMO) and El Niño southern oscillation (ENSO) on regional precipitation extremes and characteristics in the state of Florida is the focus of this study. Exhaustive evaluations of individual and combined influences of these oscillations using, descriptive indices-based assessment of statistically significant changes in rainfall characteristics, identification of spatially varying influences of oscillations on dry and wet spell transition states, antecedent precipitation prior to extreme events, intraevent temporal distribution of precipitation and changes in temporal occurrences of extremes including dry/wet cycles are carried out. Rain gage and gridded precipitation data analysis using parametric hypothesis tests confirm statistically significant changes in the precipitation characteristics from one phase to another of each oscillation and also in coupled phases. Spatially nonuniform and uniform influences of AMO and ENSO, respectively, on precipitation are evident. AMO influences vary in peninsular and continental parts of Florida and the warm (cool) phase of AMO contributes to increased precipitation extremes during wet (dry) season. The influence of ENSO is confined to dry season with El Niño (La Niña) contributing to increase (decrease) in extremes and total precipitation. Wetter antecedent conditions preceding daily extremes are dominant in AMO warm phase compared to the cool and are likely to impact design floods in the region. AMO influence on dry season precipitation extremes is noted for ENSO neutral years. The two oscillations in different phases modulate each other with seasonal and spatially varying impacts and implications on flood control and water supply in the region.

  2. Future Projection of Summer Extreme Precipitation from High Resolution Multi-RCMs over East Asia

    Science.gov (United States)

    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.

  3. 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.

  4. Spatiotemporal variations of precipitation extremes of China during the past 50 years (1960-2009)

    Science.gov (United States)

    Chi, Xiaoxiao; Yin, Zhan'e.; Wang, Xuan; Sun, Yuke

    2016-05-01

    Extreme weather events have become more frequent and intense under global warming in recent years, which has attracted much attention of scholars at home and abroad. In this paper, we used data sets of daily precipitation recorded at 499 meteorological stations to analyze the temporal and spatial variations of precipitation extremes in China over the past 50 years (1960-2009). Through the comparison of detrended fluctuation analysis (DFA) and the percentile method, DFA was selected to define the thresholds of precipitation extremes in China. Temporal variations of extreme precipitation amount, frequency, and intensity were analyzed in four major regions: Northwest China, the Qinghai-Tibet region, North China, and South China. Spatial distributions were obtained by the Kriging interpolation method, and then, we examined the varying tendencies of extreme precipitation amount, frequency, and intensity by the Mann-Kendall test. The results show that increasing trends are dominant for all indices over China; extreme precipitation amount and frequency appear to have risen since 1970-1979, but there are some regional differences. The Qinghai-Tibet region and South China have an ascending trend, and Northwest China maintains balance while North China has a descending trend. The amount and intensity of precipitation extremes are decreasing from southeastern coastal areas to northwestern inlands, and the frequency of precipitation extremes is randomly distributed. However, they are all high in the Sichuan Basin, the middle and lower Yangtze River, and the southern part of South China. Trends of most stations are statistically insignificant, but the percentage of stations with a significant increased trend in the Qinghai-Tibet region is larger than that of other regions.

  5. Predictability and possible earlier awareness of extreme precipitation across Europe

    Science.gov (United States)

    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.

  6. Prediction of Extreme Significant Wave Height from Daily Maxima

    Institute of Scientific and Technical Information of China (English)

    刘德辅; 李华军; 温书勤; 宋艳; 王树青

    2001-01-01

    For prediction of the extreme significant wave height in the ocean areas where long term wave data are not available, the empirical method of extrapolating short term data (1 ~ 3 years) is used in design practice. In this paper two methods are proposed to predict extreme significant wave height based on short-term daily maxima. According to the daa recorded by the Oceanographic Station of Liaodong Bay at the Bohai Sea, it is supposed that daily maximum wave heights are statistically independent. The data show that daily maximum wave heights obey log-normal distribution, and that the numbers of daily maxima vary from year to year, obeying binomial distribution. Based on these statistical characteristics, the binomial-log-normal compound extremum distribution is derived for prediction of extreme significant wave heights (50~ 100 years). For examination of its accuracy and validity, the prediction of extreme wave heights is based on 12 years′ data at this station, and based on each 3 years′ data respectively. The results show that with consideration of confidence intervals, the predicted wave heights based on 3 years′ data are very close to those based on 12 years′data. The observed data in some ocean areas in the Atlantic Ocean and the North Sea show it is not correct to assume that daily maximum wave heights are statistically independent; they are subject to Markov chain condition, obeying log-normal distribution. In this paper an analytical method is derived to predict extreme wave heights in these cases. A comparison of the computations shows that the difference between the extreme wave heights based on the assumption that daily maxima are statistically independent and that they are subject to Markov Chain condition is smaller than 10%.

  7. The 2015 Oklahoma extreme precipitation: attribution of climate change

    Science.gov (United States)

    Nie, J.; Sobel, A. H.; Shaevitz, D.

    2016-12-01

    In a warming climate precipitation extremes increase disproportionally faster than the mean precipitation does. However, there are large uncertainties of the paces of the precipitation extreme increases among General Circulation Models (GCMs) in the tropics and subtropics, largely due to the deficiencies of convective parameterizations. A hierarchy of models, including regional models and cloud resolving models (CRM) with high resolutions to explicitly resolve convection, can provide insights to better constrain the GCM simulations. In this study, we apply a novel CRM modeling approach, the Column Quasi-Geostrophic (CQG) method, to examine responses of precipitation extreme to climate changes. The CQG approach uses a CRM in a relatively small domain with the large-scale vertical motion, which determines vertical advection of temperature and moisture, incorporated using the quasi-geostrophic omega equation. Comparing with other CRM studies that prescribe the large-scale vertical motion, this method allows us to examine the dynamical component of precipitation increases (, to which the GCMs largely disagree with each other) to warming in addition to the thermodynamical component of increases (about 7% per K). We model the 2015 Oklahoma extreme rainfall event with CQG method, with the present climate and two counterfactual environments representing the pre-industry and an even warmer climate. Results are analyzed to attribute the extreme precipitation to climate changes, and to quantify the involved mechanisms.

  8. Influence of Climate Oscillations on Extreme Precipitation in Texas

    Science.gov (United States)

    Bhatia, N.; Singh, V. P.; Srivastav, R. K.

    2016-12-01

    Much research in the field of hydroclimatology is focusing on the impact of climate variability on hydrologic extremes. Recent studies show that the unique geographical location and the enormous areal extent, coupled with extensive variations in climate oscillations, have intensified the regional hydrologic cycle of Texas. The state-wide extreme precipitation events can actually be attributed to sea-surface pressure and temperature anomalies, such as Bermuda High and Jet Streams, which are further triggered by such climate oscillations. This study aims to quantify the impact of five major Atlantic and Pacific Ocean related climate oscillations: (i) Atlantic Multidecadal Oscillation (AMO), (ii) North Atlantic Oscillation (NAO), (iii) Pacific Decadal Oscillation (PDO), (iv) Pacific North American Pattern (PNA), and (v) Southern Oscillation Index (SOI), on extreme precipitation in Texas. Their respective effects will be determined for both climate divisions delineated by the National Climatic Data Centre (NCDC) and climate regions defined by the Köppen Climate Classification System. This study will adopt a weighted correlation approach to attain the robust correlation coefficients while addressing the regionally variable data outliers for extreme precipitation. Further, the variation of robust correlation coefficients across Texas is found to be related to the station elevation, historical average temperature, and total precipitation in the months of extremes. The research will shed light on the relationship between precipitation extremes and climate variability, thus aiding regional water boards in planning, designing, and managing the respective systems as per the future climate change.

  9. A global quantification of compound precipitation and wind extremes

    Science.gov (United States)

    Martius, Olivia; Pfahl, Stephan; Chevalier, Clément

    2016-07-01

    The concomitant occurrence of extreme precipitation and winds can have severe impacts. Here this concomitant occurrence is quantified globally using ERA-Interim reanalysis data. A logistic regression model is used to determine significant changes in the odds of precipitation extremes given a wind extreme that occurs on the same day, the day before, or the day after. High percentages of cooccurring wind and precipitation extremes are found in coastal regions and in areas with frequent tropical cyclones, with maxima of more than 50% of concomitant events. Strong regional-scale variations in this percentage are related to the interaction of weather systems with topography resulting in Föhn winds, gap winds, and orographic drying and the structure and tracks of extratropical and tropical cyclones. The percentage of concomitant events increases substantially if spatial shifts by one grid point are taken into account. Such spatially shifted but cooccurring events are important in insurance applications.

  10. A global quantification of compound precipitation and wind extremes

    Science.gov (United States)

    Martius, Olivia; Pfahl, Stephan; Chevalier, Clément

    2017-04-01

    The concomitant occurrence of extreme precipitation and winds can have severe impacts. Here this concomitant occurrence is quantified globally using ERA-Interim reanalysis data. A logistic regression model is used to determine significant changes in the odds ratio of precipitation extremes given a wind extreme occurs on the same day, the day before or the day after. High percentages of co-occurring wind and precipitation extremes are found in coastal regions and in areas with frequent tropical cyclones, with maxima of more than 50% of concomitant events. Strong regional-scale variations in this percentage are related to the interaction of weather systems with topography resulting in Föhn winds, gap winds, and orographic drying, and the structure and tracks of extratropical and tropical cyclones. The percentage of concomitant events increases substantially if spatial shifts by one grid point are taken into account. Such spatially shifted, but co-occurring events are important in insurance applications.

  11. 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.)

  12. Relationships between interdecadal variability and extreme precipitation events in South America during the monsoon season

    Science.gov (United States)

    Grimm, Alice; Laureanti, Nicole; Rodakoviski, Rodrigo

    2016-04-01

    This study aims to clarify the impact of interdecadal climate oscillations (periods of 8 years and longer) on the frequency of extreme precipitation events over South America in the monsoon season (austral spring and summer), and determine the influence of these oscillations on the daily precipitation frequency distribution. Interdecadal variability modes of precipitation during the monsoon season are provided by a continental-scale rotated empirical orthogonal function analysis for the 60 years period 1950-2009. The main disclosed modes are robust, since they are reproduced for different periods. They can produce differences around 50% in monthly precipitation between opposite phases. Oceanic and atmospheric anomalous fields associated with these modes indicate that they have physical basis. The first modes in spring and summer display highest correlation with the Interdecadal Pacific Oscillation (IPO) SST mode, while the second modes have strongest correlation with the Atlantic Multidecadal Oscillation (AMO) SST mode. However, there are also other influences on these modes. As the most dramatic consequences of climate variability stem from its influence on the frequency of extreme precipitation events, it is important to also assess this influence, since variations in monthly or seasonal precipitation do not necessarily imply significant alterations in their extreme events. This study seeks to answer the questions: i) Do opposite phases of the main interdecadal modes of seasonal precipitation produce significant anomalies in the frequency of extreme events? ii) Does the interdecadal variability of the frequency of extreme events show similar spatial and temporal structure as the interdecadal variability of the seasonal precipitation? iii) Does the interdecadal variability change the daily precipitation probability distribution between opposite phases? iv) In this case, which ranges of daily precipitation are most affected? The significant anomalies of the extreme

  13. Quantifying how the full local distribution of daily precipitation is changing and its uncertainties

    Science.gov (United States)

    Stainforth, David; Chapman, Sandra; Watkins, Nicholas

    2016-04-01

    The study of the consequences of global warming would benefit from quantification of geographical patterns of change at specific thresholds or quantiles, and better understandings of the intrinsic uncertainties in such quantities. For precipitation a range of indices have been developed which focus on high percentiles (e.g. rainfall falling on days above the 99th percentile) and on absolute extremes (e.g. maximum annual one day precipitation) but scientific assessments are best undertaken in the context of changes in the whole climatic distribution. Furthermore, the relevant thresholds for climate-vulnerable policy decisions, adaptation planning and impact assessments, vary according to the specific sector and location of interest. We present a methodology which maintains the flexibility to provide information at different thresholds for different downstream users, both scientists and decision makers. We develop a method[1,2] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes in daily precipitation data. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the amount of precipitation on those days. Our method is a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of how fast different quantiles of precipitation distributions are changing. This involves not only determining which quantiles and geographical locations show the greatest and smallest changes, but also those at which uncertainty undermines the ability to make confident statements about any change there may be. We demonstrate this approach using E-OBS gridded data[3] which are timeseries of local daily

  14. Trends and seasonality of extreme precipitation characteristics related to mid-latitude cyclones in Europe

    Directory of Open Access Journals (Sweden)

    A. Karagiannidis

    2009-03-01

    Full Text Available An attempt is made to study the extreme precipitation characteristics, which are related to the mid-latitude cyclonic systems. Daily pluviometric data, from several stations across the continental Europe and the British Islands, are used. The covered time-period is from 1958 to 2000. Only extreme precipitation events related to mid-latitude cyclonic systems are studied, since thermal thunderstorm episodes are being excluded. To accomplish that, summer months are excluded and a strict criterion for identifying the exact episodes is set, which also defines the episode itself and the extremity of it. A decreasing trend in the cases of extreme precipitation of the European continent was found. It starts in the mid 60's and continues until the mid 70's. After that and until the end of the examined period, no significant trend was found. Seasonality of extreme precipitation cases and episodes is also studied. October and November are the two months that present the higher frequencies of such cases and episodes. In general, autumn months indicate the higher percentages of extreme precipitation, with winter and spring months to follow.

  15. Is climate change modifying precipitation extremes?

    Science.gov (United States)

    Montanari, Alberto; Papalexiou, Simon Michael

    2016-04-01

    The title of the present contribution is a relevant question that is frequently posed to scientists, technicians and managers of local authorities. Although several research efforts were recently dedicated to rainfall observation, analysis and modelling, the above question remains essentially unanswered. The question comes from the awareness that the frequency of floods and the related socio-economic impacts are increasing in many countries, and climate change is deemed to be the main trigger. Indeed, identifying the real reasons for the observed increase of flood risk is necessary in order to plan effective mitigation and adaptation strategies. While mitigation of climate change is an extremely important issue at the global level, at small spatial scales several other triggers may interact with it, therefore requiring different mitigation strategies. Similarly, the responsibilities of administrators are radically different at local and global scales. This talk aims to provide insights and information to address the question expressed by its title. High resolution and long term rainfall data will be presented, as well as an analysis of the frequency of their extremes and its progress in time. The results will provide pragmatic indications for the sake of better planning flood risk mitigation policies.

  16. 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).

  17. Precipitation extremes over La Plata Basin – Review and new results from observations and climate simulations

    Energy Technology Data Exchange (ETDEWEB)

    Cavalcanti, I. F. A.; Carril, A. F.; Penalba, O. C.; Grimm, A. M.; Menéndez, C. G.; Sanchez, E.; Cherchi, A.; Sörensson, A.; Robledo, F.; Rivera, J.; Pántano, V.; Bettolli, L. M.; Zaninelli, P.; Zamboni, L.; Tedeschi, R. G.; Dominguez, M.; Ruscica, R.; Flach, R.

    2015-04-01

    Monthly and daily precipitation extremes over La Plata Basin (LPB) are analyzed in the framework of the CLARIS-LPB Project. A review of the studies developed during the project and results of additional research are presented and discussed. Specific aspects of analysis are focused on large-scale versus local processes impacts on the intensity and frequency of precipitation extremes over LPB, and on the assessment of specific wet and dry spell indices and their changed characteristics in future climate scenarios. The analysis is shown for both available observations of precipitation in the region and ad-hoc global and regional models experiments. The Pacific, Indian and Atlantic Oceans can all impact precipitation intensity and frequency over LPB. In particular, considering the Pacific sector, different types of ENSO events (i.e. canonical vs Modoki or East vs Central) have different influences. Moreover, model projections indicate an increase in the frequency of precipitation extremes over LPB during El Niño and La Ninã events in future climate. Local forcings can also be important for precipitation extremes. Here, the feedbacks between soil moisture and extreme precipitation in LPB are discussed based on hydric conditions in the region and model sensitivity experiments. Concerning droughts, it was found that they were more frequent in the western than in the eastern sector of LPB during the period of 1962–2008. On the other hand, observations and model experiments agree in that the monthly wet extremes were more frequent than the dry extremes in the northern and southern LPB sectors during the period 1979–2001, with higher frequency in the south.

  18. Precipitation extremes over La Plata Basin - Review and new results from observations and climate simulations

    Science.gov (United States)

    Cavalcanti, I. F. A.; Carril, A. F.; Penalba, O. C.; Grimm, A. M.; Menéndez, C. G.; Sanchez, E.; Cherchi, A.; Sörensson, A.; Robledo, F.; Rivera, J.; Pántano, V.; Bettolli, L. M.; Zaninelli, P.; Zamboni, L.; Tedeschi, R. G.; Dominguez, M.; Ruscica, R.; Flach, R.

    2015-04-01

    Monthly and daily precipitation extremes over La Plata Basin (LPB) are analyzed in the framework of the CLARIS-LPB Project. A review of the studies developed during the project and results of additional research are presented and discussed. Specific aspects of analysis are focused on large-scale versus local processes impacts on the intensity and frequency of precipitation extremes over LPB, and on the assessment of specific wet and dry spell indices and their changed characteristics in future climate scenarios. The analysis is shown for both available observations of precipitation in the region and ad-hoc global and regional models experiments. The Pacific, Indian and Atlantic Oceans can all impact precipitation intensity and frequency over LPB. In particular, considering the Pacific sector, different types of ENSO events (i.e. canonical vs Modoki or East vs Central) have different influences. Moreover, model projections indicate an increase in the frequency of precipitation extremes over LPB during El Niño and La Ninã events in future climate. Local forcings can also be important for precipitation extremes. Here, the feedbacks between soil moisture and extreme precipitation in LPB are discussed based on hydric conditions in the region and model sensitivity experiments. Concerning droughts, it was found that they were more frequent in the western than in the eastern sector of LPB during the period of 1962-2008. On the other hand, observations and model experiments agree in that the monthly wet extremes were more frequent than the dry extremes in the northern and southern LPB sectors during the period 1979-2001, with higher frequency in the south.

  19. Characteristic Features of Precipitation Extremes over India in the Warming Scenarios

    Directory of Open Access Journals (Sweden)

    J. V. Revadekar

    2011-01-01

    Full Text Available The detection of possible changes in extreme climate events, in terms of the frequency, intensity as well as duration assumes profound importance on the local, regional, and national scales, due to the associated critical socioeconomic consequences. Therefore, an attempt is made in this paper to evaluate various aspects of future projections of precipitation extremes over India, as projected by a state-of-art regional climate modeling system, known as PRECIS (Providing REgional Climates for Impacts Studies towards the end of the 21st century (that is, 2071–2100 using standardized indices. Study reveals that PRECIS simulations under scenarios of increasing greenhouse gas concentration and sulphate aerosols indicate marked increase in precipitation towards the end of the 21st century and is expected to increase throughout the year. However the changes in daily precipitation and the precipitation extremes during summer monsoon (June through September season are prominent than during the rest of year. PRECIS simulations under both A2 and B2 scenarios indicate increase in frequency of heavy precipitation events and also enhancement in their intensity towards the end of the 21st century. Both A2 and B2 scenarios show similar patterns of projected changes in the precipitation extremes towards the end of the 21st century. However, the magnitudes of changes in B2 scenario are on the lower side.

  20. Will climate change increase the risk for critical infrastructure failures in Europe due to extreme precipitation?

    Science.gov (United States)

    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).

  1. Trend analysis of extreme precipitation in the Northwestern Highlands of Ethiopia with a case study of Debre Markos

    Directory of Open Access Journals (Sweden)

    H. Shang

    2011-06-01

    Full Text Available Understanding extreme precipitation is very important for Ethiopia, which is heavily dependent on low-productivity rainfed agriculture but lacks structural and non-structural water regulating and storage mechanisms. There has been an increasing concern about whether there is an increasing trend in extreme precipitation as the climate changes. Existing analysis of this region has been descriptive, without taking advantage of the advances in extreme value modeling. After reviewing the statistical methodology on extremes, this paper presents an analysis based on the generalized extreme value modeling with daily time series of precipitation records at Debre Markos in the Northwestern Highlands of Ethiopia. We found no strong evidence to reject the null hypothesis that there is no increasing trend in extreme precipitation at this location.

  2. Temporal variation of extreme precipitation events in Lithuania

    Directory of Open Access Journals (Sweden)

    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.

  3. Precipitation Extremes: Considerations for Anthropogenically-forced Future Changes

    Science.gov (United States)

    Kunkel, K.; Young, J.

    2015-12-01

    The Third National Climate Assessment states that "increases in the frequency and intensity of extreme precipitation events are projected for all U.S. regions". While that general statement was made with high confidence, the practical implications for decision-makers are much less clear. In particular, engineering design needs quantitative estimates of probable maximum precipitation (PMP) and intensity-duration-frequency (IDF) values for the future in order to optimize runoff control structures for future climate conditions. This can be realized by simply analyzing the precipitation data from global climate model simulations of the future. However, confidence in the resulting values suffers from the known issues with GCM simulation of precipitation. In addition, skepticism about the accuracy of climate models negatively affects potential adoption of revised values in the engineering design community. We contend that scientists need a multi-pronged approach to develop PMP/IDF values that can be defended, explained, and promoted in order to maximize societal benefits and avoid catastrophic events. This talk will discuss considerations that could/should form the basis for design values. While global-warming induced increases in atmospheric water vapor content are nearly certain and form the foundation for expected increases in extreme precipitation, they most likely will be modulated by changes in global atmospheric dynamics and the consequent effects on local weather system climatology. This can be seen currently in the unexplained regional variations in recent trends in extreme precipitation frequency and intensity. We need to be able to understand recent trends, when greenhouse gas forcing of the climate systems has been rapidly increasing, in order to produce confident projections of future extreme precipitation.

  4. 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.

  5. Corresp onding Relation b etween Warm Season Precipitation Extremes and Surface Air Temp erature in South China

    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◦C, 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◦C, among which the decrease of hourly extremes is much more significant. In order to investigate the effects 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◦C is mainly caused by short duration precipitation, and long duration precipitation extremes rarely occur in South China when surface air temperature surpasses 28◦C.

  6. Horsing Around with Climate: Effect of Technology-Driven Landuse Change on Extreme Precipitation

    Science.gov (United States)

    Sines, T. R.; Arritt, R. W.

    2016-12-01

    The shift from work animals such as horses to mechanized labor and transport led to a decrease in acreage devoted to small grains (primarily oats) in the United States. Land formerly devoted to these crops was converted mostly to soybeans, which saw a forty-fold increase in planted acreage from 1940 to present. The same period saw an increase in extreme precipitation over the continental United States. We investigate possible connections between this agricultural landuse modification and precipitation changes in the central United States using the WRF-ARW model coupled with the Community Land Model. Crop acreages for maize, soybean, winter wheat, spring wheat, and other C3 and C4 crops were reconstructed for 1940-2010 using county-level data. This landuse was then used as surface input for two regional climate simulations, one using constant 1940s landuse and another using constant 2010 landuse. The landuse change was found to produce a shift in the precipitation intensity spectrum, with simulations using 2010 landuse having higher frequencies for heavier precipitation amounts and lower frequencies of light amounts compared to 1940s landuse. The break point for this shift corresponded to daily precipitation of about 24 mm. This indicates that agricultural landuse change has contributed to the observed trend in extreme precipitation, increasing the frequency of heavy daily rainfall.

  7. Seasonal precipitation extreme indices in mainland Portugal: trends and variability in the period 1941-2007

    Science.gov (United States)

    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).

  8. 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.

  9. Projected changes in precipitation extremes linked to temperature over Japan

    Science.gov (United States)

    Nayak, S.; Dairaku, K.; Takayabu, I.; Suzuki-Parker, A.

    2015-12-01

    Recent studies have argued that the extreme precipitation intensities are increasing in many regions across the globe due to atmospheric warming. This argument is based on the principle of Clausius-Clapeyron relationship which states that the atmosphere can hold more moisture in warmer air temperature (~7%/°C). In our study, we have investigated the precipitation extremes linked to temperature in current climate (1981-2000) and their projected changes in late 21st century (2081-2100, RCP4.5) over Japan from multi-model ensemble downscaling experiments by three RCMs (NHRCM, NRAMS, WRF) forced by JRA25 as well as three GCMs (CCSM4, MIROC5, MRI-GCM3). To do this, the precipitation intensities of wet days (defined as ≥ 0.05 mm/d) are stratified to different bins with 1°C temperature interval. We have also identified the occurrences of precipitation extremes in different spell durations and associated peak intensities exceeding various thresholds in two climate periods. We found that extreme precipitation intensities are increased by 5 mm/d in future climate for temperatures above 21°C (Fig. 1). Precipitation extremes of higher percentiles are projected to have larger increase rates in future climate scenarios (3-5%/°C in the current climate and 4-6%/°C in the future climate scenarios). The joint probability distribution of wet hours (≥1mm/h) with various peak intensities under future climate scenarios (RCP4.5) of the late 21st century suggests an increase of long-lived (>10hr) and short-lived (1-2hr) events. On the other hand, a relatively decrease of medium-lived events (3-10hr) are noticed in future climate scenario. The increase of extreme precipitation intensities in future climate is due to the increase in temperature under RCP4.5 (~2°C). Increase in temperature causes more evapotranspiration and subsequently increases the water vapor in the atmosphere.

  10. Trends and variability in total and extreme precipitation over mainland Portugal, 1941-2012

    Science.gov (United States)

    de Lima, Isabel P.; Espírito Santo, Fátima; Silva, Álvaro; Cunha, Sofia

    2014-05-01

    Changes in the climate are expected to affect the occurrence of extreme weather and climate events that might influence significantly the distribution, availability and sustainability of regional water resources. The location of mainland Portugal on the Northeast Atlantic Ocean region, in South-western Europe, together with other geographical features, makes this territory highly vulnerable to extreme hydrological events, such as floods and droughts, driven by the strong variability in precipitation. To study changes in the total and extreme precipitation in this area, at the annual and seasonal scales, 27 daily precipitation time series for the period 1941-2012 were analysed. We applied 8 selected precipitation-related indices of "moderate" extremes that include duration, threshold, absolute and percentile indices. In general, the results found in this study are in agreement with other studies that inspected changes in precipitation in western Iberia. Since the 1980s, it is notable the occurrence of long drought spells, as well as the more intense precipitation events on record; these events distressed more the centre and southern regions of mainland Portugal, which are the most vulnerable and the more affected by these types of events. Moreover, results show regional differences in the indices' trends and also point out to a greater asymmetry in the temporal distribution of precipitation and variations in the intensity, persistence and frequency of extreme events at various scales, which may influence the risk associated with floods and droughts. Overall, while contributing to the increased understanding of local and regional specificities in the study area, and in the context of the Iberian Peninsula, results can also be useful for disaster risk management and definition of adaptation and mitigation measures to climate change.

  11. Summer extreme precipitation in eastern China: mechanisms and impacts

    Science.gov (United States)

    Zhang, Qiang; Zheng, Yongjie; Singh, Vijay P.; Luo, Ming; Xie, Zhenghui

    2017-04-01

    changes and the related mechanisms are of great significance for regional management of water resources and agricultural irrigation. In this study, the impacts of western north Pacific subtropical high (WNPSH) on precipitation changes in eastern China and the underling processes are investigated. The results indicate that the strength and location of WNPSH are in close relations with the changes of summer precipitation in eastern China, and their influences vary across both space and time. In particular, WNPSH exerts remarkable impacts on precipitation in June and July in Jiang-Huai region and precipitation in June in South China such as the Pearl River basin. The inter-annual variations of WNPSH exhibits significant correlations with water vapor flux in East Asia and, and the variations of the location and direction of west flank of WNPSH is well corroborated that influences of East Asia summer monsoon on precipitation in eastern China. The westward extension of WNPSH tends to move the East Asian summer monsoon west and thus increasing water vapor flux in East Asia, which greatly benefits the occurrence of Meiyu regimes in Jiang-huai region. Besides, analysis results also show that the westward extension of WNPSH drives tropical cyclones sourthwards so as to increase the occurrence of extreme precipitation in South China. This study helps to bridge the knowledge gap in the relationship between WNPSH, tropical cyclones, summer precipitation events in eastern China.

  12. Extreme temperatures and precipitation in Poland. An evaluation attempt

    Energy Technology Data Exchange (ETDEWEB)

    Ustrnul, Zbigniew [Institute of Meteorology and Water Management, Krakow (Poland); Wypych, Agnieszka; Kosowski, Marek [Jagiellonian Univ., Krakow (Poland)

    2012-02-15

    Summer (JJA) and winter (DJF) temperature extremes and summer (JJA) precipitation extremes in Poland that occurred in the years 1951-2006 are analyzed in this paper. Diurnal extreme values of air temperature (Tmax, Tmin) and diurnal precipitation totals (P) are considered. The data was obtained from 54 meteorological stations. Extreme values were identified based on different methodological approaches. Advantages and disadvantages of selected methods are shown with respect to both temporal and spatial variability of the data. The differences obtained as a result of the applied criteria confirm that the method of percentiles seems to be the most suitable one to be used in spatial analysis. This is especially relevant in areas with a relatively high variability of absolute values. When it comes to analyses of multi-annual trends, the criterion used plays a less significant role. Regardless of the method, there is a certain direction of changes that is maintained, although their magnitudes may be different. It may be concluded from the conducted analyses that for the full evaluation of both spatial variability and temporal variability of weather extremes, a variety of methods and criteria for identifying extreme values, should be considered. They may significantly influence the final results. (orig.)

  13. Extreme precipitation in WRF during the Newcastle East Coast Low of 2007

    Science.gov (United States)

    Gilmore, James B.; Evans, Jason P.; Sherwood, Steven C.; Ekström, Marie; Ji, Fei

    2016-08-01

    In the context of regional downscaling, we study the representation of extreme precipitation in the Weather Research and Forecasting (WRF) model, focusing on a major event that occurred on the 8th of June 2007 along the coast of eastern Australia (abbreviated "Newy"). This was one of the strongest extra-tropical low-pressure systems off eastern Australia in the last 30 years and was one of several storms comprising a test bed for the WRF ensemble that underpins the regional climate change projections for eastern Australia (New South Wales/Australian Capital Territory Regional Climate Modelling Project, NARCliM). Newy provides an informative case study for examining precipitation extremes as simulated by WRF set up for regional downscaling. Here, simulations from the NARCliM physics ensemble of Newy available at ˜10 km grid spacing are used. Extremes and spatio-temporal characteristics are examined using land-based daily and hourly precipitation totals, with a particular focus on hourly accumulations. Of the different physics schemes assessed, the cumulus and the boundary layer schemes cause the largest differences. Although the Betts-Miller-Janjic cumulus scheme produces better rainfall totals over the entire storm, the Kain-Fritsch cumulus scheme promotes higher and more realistic hourly extreme precipitation totals. Analysis indicates the Kain-Fritsch runs are correlated with larger resolved grid-scale vertical moisture fluxes, which are produced through the influence of parameterized convection on the larger-scale circulation and the subsequent convergence and ascent of moisture. Results show that WRF qualitatively reproduces spatial precipitation patterns during the storm, albeit with some errors in timing. This case study indicates that whilst regional climate simulations of an extreme event such as Newy in WRF may be well represented at daily scales irrespective of the physics scheme used, the representation at hourly scales is likely to be physics scheme

  14. Climatic changes of extreme precipitation in Denmark from 1874 to 2100

    Science.gov (United States)

    Arnbjerg-Nielsen, Karsten; Bülow Gregersen, Ida; Sunyer, Maria; Madsen, Henrik; Rosbjerg, Dan

    2014-05-01

    During the past 30 years rather dramatic changes in extreme precipitation have been observed in Denmark. These changes are mainly in the frequency of extreme events, but there is also a tendency towards more severe events. Both are considered effects of anthropogenic climate change. The increase in precipitation extremes has led to inundations in most of the larger cities during the last 10 years. The flood in Copenhagen in 2011 implied the second highest damage costs measured in Denmark during the last 100 years. To establish cities that are resilient to pluvial floods robust projections of the frequency and intensity of extreme precipitation events in a changing climate are needed. Additionally, it is equally important to understand the natural variation on which the anthropogenic changes are imposed. This study presents the results of a coordinated effort to estimate the changes and uncertainties in Danish design rainfall. Trends and oscillations are identified in five daily precipitation records from 1874 to present, 83 records from high-resolution rain-gauges from 1979 to present and 18 state-of-the-art climate model simulations. It is shown that the frequency of extreme events in the past has oscillated with a cycle of 25-35 years, a behavior that can in part be explained by sea level pressure differences over the Atlantic. Projections based on the historical observations suggest that precipitation extremes in the Eastern part of Denmark should have been ascending in the last two decades. However, the increase has continued longer than expected and with larger amplitude in the most recent years. This indicates a likely influence from anthropogenic greenhouse gas emissions. With the complex combination of general increase and natural variation several additional years of observation are needed before this hypothesis can be evaluated by statistical means. Extensive analysis of 18 different regional climate model (RCM) simulations shows that anthropogenic

  15. Space time disaggregation of precipitation using daily precipitation and radar observations.

    Science.gov (United States)

    Bàrdossy, Andràs; Pegram, Geoffrey

    2016-04-01

    Radar measurements provide useful information on the spatial and temporal distribution of precipitation. Unfortunately the measurements are often erroneous and biased. Traditional raingauge based observations offer point values. The purpose of this contribution is to investigate the possibility of combining high frequency pluviometer rainfall observations, daily data and radar measurements to obtain sets of possible realizations of the "real" space-time distribution of precipitation. The stochastic model uses space-time copulas, and simulates realizations using a random mixing approach. The method does not intend to provide a single best estimate, but instead to generate many realizations of precipitation fields using the stochastic model. The realizations reflect the different sources of information and represent the corresponding uncertainty. Different levels of information derived from considering radar data are investigated starting with the use of (i) radar zeros only, then (ii) intensity classes and (iii) rank based combinations. The methods are tested and compared on selected events recorded by a dense radar network in South-West Germany, which has been carefully bias corrected.

  16. Local impact analysis of climate change on precipitation extremes: are high-resolution climate models needed for realistic simulations?

    Science.gov (United States)

    Tabari, Hossein; De Troch, Rozemien; Giot, Olivier; Hamdi, Rafiq; Termonia, Piet; Saeed, Sajjad; Brisson, Erwan; Van Lipzig, Nicole; Willems, Patrick

    2016-09-01

    This study explores whether climate models with higher spatial resolutions provide higher accuracy for precipitation simulations and/or different climate change signals. The outputs from two convection-permitting climate models (ALARO and CCLM) with a spatial resolution of 3-4 km are compared with those from the coarse-scale driving models or reanalysis data for simulating/projecting daily and sub-daily precipitation quantiles. Validation of historical design precipitation statistics derived from intensity-duration-frequency (IDF) curves shows a better match of the convection-permitting model results with the observations-based IDF statistics compared to the driving GCMs and reanalysis data. This is the case for simulation of local sub-daily precipitation extremes during the summer season, while the convection-permitting models do not appear to bring added value to simulation of daily precipitation extremes. Results moreover indicate that one has to be careful in assuming spatial-scale independency of climate change signals for the delta change downscaling method, as high-resolution models may show larger changes in extreme precipitation. These larger changes appear to be dependent on the timescale, since such intensification is not observed for daily timescales for both the ALARO and CCLM models.

  17. Assessment of climate variations in temperature and precipitation extreme events over Iran

    Science.gov (United States)

    Soltani, M.; Laux, P.; Kunstmann, H.; Stan, K.; Sohrabi, M. M.; Molanejad, M.; Sabziparvar, A. A.; Ranjbar SaadatAbadi, A.; Ranjbar, F.; Rousta, I.; Zawar-Reza, P.; Khoshakhlagh, F.; Soltanzadeh, I.; Babu, C. A.; Azizi, G. H.; Martin, M. V.

    2016-11-01

    In this study, changes in the spatial and temporal patterns of climate extreme indices were analyzed. Daily maximum and minimum air temperature, precipitation, and their association with climate change were used as the basis for tracking changes at 50 meteorological stations in Iran over the period 1975-2010. Sixteen indices of extreme temperature and 11 indices of extreme precipitation, which have been quality controlled and tested for homogeneity and missing data, are examined. Temperature extremes show a warming trend, with a large proportion of stations having statistically significant trends for all temperature indices. Over the last 15 years (1995-2010), the annual frequency of warm days and nights has increased by 12 and 14 days/decade, respectively. The number of cold days and nights has decreased by 4 and 3 days/decade, respectively. The annual mean maximum and minimum temperatures averaged across Iran both increased by 0.031 and 0.059 °C/decade. The probability of cold nights has gradually decreased from more than 20 % in 1975-1986 to less than 15 % in 1999-2010, whereas the mean frequency of warm days has increased abruptly between the first 12-year period (1975-1986) and the recent 12-year period (1999-2010) from 18 to 40 %, respectively. There are no systematic regional trends over the study period in total precipitation or in the frequency and duration of extreme precipitation events. Statistically significant trends in extreme precipitation events are observed at less than 15 % of all weather stations, with no spatially coherent pattern of change, whereas statistically significant changes in extreme temperature events have occurred at more than 85 % of all weather stations, forming strongly coherent spatial patterns.

  18. Regional frequency analysis of extreme precipitation for Sicily (Italy)

    Science.gov (United States)

    Forestieri, Angelo; Blenkinsop, Stephen; Fowler, Hayley; Lo Conti, Francesco; Noto, Leonardo

    2016-04-01

    The analysis of extreme precipitation has always been included among most relevant hydrological applications because of the several important activities linked to the availability of tools for the estimation of extreme rainfall quantiles. These activities include the design of hydraulic civil structures and the evaluation and management of hydraulic and hydrological risk. In this study a frequency analysis of annual maxima precipitation measurements has been carried out for the area of Sicily (Italy). A typical hierarchical regional approach has been adopted for the parameter estimation procedure based on the L-moments method. The identification of homogeneous regions within the procedure has been pursued with a data driven procedure constituted by a principal component analysis of an ensemble of selected auxiliary variables, and a K-means cluster analysis algorithm. Auxiliary variables comprise meteo-climatic information and a representation of the average seasonal distribution of intense events. Results have been evaluated by means of a Monte Carlo experiment based on the comparison between at-site and regional fitted frequency distributions. Moreover, results have been compared with previous analyses performed for the same area. The study provides an updated tool for the modelling of extreme precipitation for the area of Sicily (Italy), with different features respect to previous tools both in terms of definition of homogeneous zones and in terms of parameters of the frequency distribution. Meteo-climatic information and the seasonality of extreme events retrieved from the dataset has been proficuously exploited in the analysis.

  19. Poorest countries experience earlier anthropogenic emergence of daily temperature extremes

    Science.gov (United States)

    Harrington, Luke J.; Frame, David J.; Fischer, Erich M.; Hawkins, Ed; Joshi, Manoj; Jones, Chris D.

    2016-05-01

    Understanding how the emergence of the anthropogenic warming signal from the noise of internal variability translates to changes in extreme event occurrence is of crucial societal importance. By utilising simulations of cumulative carbon dioxide (CO2) emissions and temperature changes from eleven earth system models, we demonstrate that the inherently lower internal variability found at tropical latitudes results in large increases in the frequency of extreme daily temperatures (exceedances of the 99.9th percentile derived from pre-industrial climate simulations) occurring much earlier than for mid-to-high latitude regions. Most of the world’s poorest people live at low latitudes, when considering 2010 GDP-PPP per capita; conversely the wealthiest population quintile disproportionately inhabit more variable mid-latitude climates. Consequently, the fraction of the global population in the lowest socio-economic quintile is exposed to substantially more frequent daily temperature extremes after much lower increases in both mean global warming and cumulative CO2 emissions.

  20. Mechanisms for Amplified Central European Summer Precipitation Extremes in a Warmer Mediterranean Climate

    Science.gov (United States)

    Volosciuk, Claudia; Maraun, Douglas; Semenov, Vladimir; Tilinina, Natalia; Latif, Mojib

    2015-04-01

    Central European climate is influenced by the Mediterranean Sea, where a strong increase in sea surface temperature (SST) has been observed during the last four decades. One example of extreme weather events are cyclones following the "Vb" pathway. These cyclones are generated over the Mediterranean Sea, travel northeastwards around the Alps and then hit central European countries. These cyclones carry large amounts of moisture and cause extreme precipitation, and subsequently flooding, particularly in summer. To investigate the mechanisms causing increased summer extreme precipitation due to increased Mediterranean SST in Europe, we analyze a series of simulations with the atmospheric general circulation model ECHAM5. In the control run, we forced the model with the 1970-1999 SST climatology. In an additional run, we replaced the Mediterranean and Black Sea SST forcing with the climatology of the warmer 2000-2012 period. ECHAM5 was run at high horizontal resolution (T159) and integrated for 40 years in each experiment. 20-season return levels were derived as a measure of extreme precipitation for daily precipitation in JJA (June - August). These return levels are estimated as quantiles of a stationary generalized Pareto distribution, based on exceedances of the 95th precipitation percentile. We have shown in a previous contribution that precipitation return levels in JJA increase along the Vb cyclone track although the number of Vb cyclones does not increase. Here we discuss the mechanisms responsible for this increase. Due to the warmer climate in the Mediterranean region, climatological mean evaporation and precipitable water in the atmosphere are increased. On extreme days, composites show an even further increase in precipitable water over the central European region. On these extreme days, a higher sea level pressure gradient between central Europe and the Atlantic causes enhanced cyclonic flow that transports more moisture from the Mediterranean region to

  1. Detection of Historical and Future Precipitation Variations and Extremes Over the Continental United States

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Bruce T. [Boston Univ., MA (United States)

    2015-12-11

    Problem: The overall goal of this proposal is to detect observed seasonal-mean precipitation variations and extreme event occurrences over the United States. Detection, e.g. the process of demonstrating that an observed change in climate is unusual, first requires some means of estimating the range of internal variability absent any external drivers. Ideally, the internal variability would be derived from the observations themselves, however generally the observed variability is a confluence of both internal variability and variability in response to external drivers. Further, numerical climate models—the standard tool for detection studies—have their own estimates of intrinsic variability, which may differ substantially from that found in the observed system as well as other model systems. These problems are further compounded for weather and climate extremes, which as singular events are particularly ill-suited for detection studies because of their infrequent occurrence, limited spatial range, and underestimation within global and even regional numerical models. Rationale: As a basis for this research we will show how stochastic daily-precipitation models—models in which the simulated interannual-to-multidecadal precipitation variance is purely the result of the random evolution of daily precipitation events within a given time period—can be used to address many of these issues simultaneously. Through the novel application of these well-established models, we can first estimate the changes/trends in various means and extremes that can occur even with fixed daily-precipitation characteristics, e.g. that can occur simply as a result of the stochastic evolution of daily weather events within a given climate. Detection of a change in the observed climate—either naturally or anthropogenically forced—can then be defined as any change relative to this stochastic variability, e.g. as changes/trends in the means and extremes that could only have occurred

  2. Time series requirements and trends of temperature and precipitation extremes over Italy

    Science.gov (United States)

    Fioravanti, Guido; Desiato, Franco; Fraschetti, Piero; Perconti, Walter; Piervitali, Emanuela

    2013-04-01

    Extreme climate events have strong impacts on society and economy; accordingly,the knowledge of their trends on long period is crucial for the definition and implementation of a national adaptation strategy to climate change. The Research Programme on Climate Variability and Predictability (CLIVAR) identified a set of temperature and precipitation indices suited to investigate variability and trends of climate extremes. It is well known that extreme indices calculation is more demanding than first and second order statistics are: daily temperature and precipitation data are required and strict constrains in terms of continuity and completeness must be met. In addition, possible dishomogeneities affecting time series must be identified and adjusted before indices calculation. When metadata are not available, statistical methods can provide scientist a relevant support for homogeneity check; however, ad-hoc decision criteria (sometimes subjective) must be applied whenever contradictory results characterize different statistical homogeneity tests. In this work, a set of daily (minimum and maximum) temperature and precipitation time series for the period 1961-2011 were selected in order to guarantee a quite uniform spatial distribution of the stations over the Italian territory and according to the afore-said continuity and completeness criteria. Following the method described by Vincent, the homogeneity check of temperature time series was run at annual level. Two well-documented tests were employed (F-test and T-test), both implemented in the free R-package RHtestV3. The Vincent method was also used for a further investigation of time series homogeneity. Temperature dishomogeneous series were discarded. For precipitation series, no homogeneity check was run. The selected series were employed at daily level to calculate a reliable set of extreme indices. For each station, a linear model was employed for indices trend estimation. Finally, single station results were

  3. Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

    Science.gov (United States)

    Williams, C.; Kniveton, D.; Layberry, R.

    2007-12-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

  4. Distributing urban resilience to extreme precipitation events with green infrastructure

    Science.gov (United States)

    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.

  5. changes in indices of daily temperature and precipitation extremes ...

    African Journals Online (AJOL)

    Dr A.B.Ahmed

    classified as hotspots to climate change – such as northwest. Nigeria. This study ... poor water supply, sanitation, and overcrowding. Flooding caused ... breakage or contaminations of drinking water with severe impacts to population health.

  6. Effects of Model Resolution and Subgrid-Scale Physics on the Simulation of Daily Precipitation in the Continental United States

    Energy Technology Data Exchange (ETDEWEB)

    Duffy, P B; Iorio, J P; Govindasamy, B; Thompson, S L; Khairoutdinov, M; Randall, D

    2004-07-28

    We analyze simulations of the global climate performed at a range of spatial resolutions to assess the effects of horizontal spatial resolution on the ability to simulate precipitation in the continental United States. The model investigated is the CCM3 general circulation model. We also preliminarily assess the effect of replacing cloud and convective parameterizations in a coarse-resolution (T42) model with an embedded cloud-system resolving model (CSRM). We examine both spatial patterns of seasonal-mean precipitation and daily-timescale temporal variability of precipitation in the continental United States. For DJF and SON, high-resolution simulations produce spatial patterns of seasonal-mean precipitation that agree more closely with observed precipitation patterns than do results from the same model (CCM3) at coarse resolution. However, in JJA and MAM, there is little improvement in spatial patterns of seasonal-mean precipitation with increasing resolution, particularly in the Southeast. This is owed to the dominance of convective (i.e., parameterized) precipitation in these two seasons. We further find that higher-resolution simulations have more realistic daily precipitation statistics. In particular, the well-known tendency at coarse resolution to have too many days with weak precipitation and not enough intense precipitation is partially eliminated in higher-resolution simulations. However, even at the highest resolution examined here (T239), the simulated intensity of the mean and of high-percentile daily precipitation amounts is too low. This is especially true in the Southeast, where the most extreme events occur. A new GCM, in which a cloud-resolving model (CSRM) is embedded in each grid cell and replaces convective and stratiform cloud parameterizations, solves this problem, and actually produces too much precipitation in the form of extreme events. However, in contrast to high-resolution versions of CCM3, this model produces little improvement in

  7. Implementation and validation of a Wilks-type multi-site daily precipitation generator over a typical Alpine river catchment

    Science.gov (United States)

    Keller, D. E.; Fischer, A. M.; Frei, C.; Liniger, M. A.; Appenzeller, C.; Knutti, R.

    2015-05-01

    Many climate impact assessments require high-resolution precipitation time series that have a spatio-temporal correlation structure consistent with observations, for simulating either current or future climate conditions. In this respect, weather generators (WGs) designed and calibrated for multiple sites are an appealing statistical downscaling technique to stochastically simulate multiple realisations of possible future time series consistent with the local precipitation characteristics and their expected future changes. In this study, we present the implementation and validation of a multi-site daily precipitation generator re-built after the methodology described in Wilks (1998). The generator consists of several Richardson-type WGs run with spatially correlated random number streams. This study aims at investigating the capabilities, the added value and the limitations of the precipitation generator for a typical Alpine river catchment in the Swiss Alpine region under current climate. The calibrated multi-site WG is skilful at individual sites in representing the annual cycle of the precipitation statistics, such as mean wet day frequency and intensity as well as monthly precipitation sums. It reproduces realistically the multi-day statistics such as the frequencies of dry and wet spell lengths and precipitation sums over consecutive wet days. Substantial added value is demonstrated in simulating daily areal precipitation sums in comparison to multiple WGs that lack the spatial dependency in the stochastic process. Limitations are seen in reproducing daily and multi-day extreme precipitation sums, observed variability from year to year and in reproducing long dry spell lengths. Given the performance of the presented generator, we conclude that it is a useful tool to generate precipitation series consistent with the mean climatic aspects and likely helpful to be used as a downscaling technique for climate change scenarios.

  8. Changes of precipitation extremes over South Korea projected by the 5 RCMs under RCP scenarios

    Science.gov (United States)

    Ahn, Joong-Bae; Jo, Sera; Suh, Myoung-Seok; Cha, Dong-Hyun; Lee, Dong-Kyou; Hong, Song-You; Min, Seung-Ki; Park, Seong-Chan; Kang, Hyun-Suk; Shim, Kyo-Moon

    2016-05-01

    The change of extreme precipitation is assessed with the HadGEM2-AO - 5 Regional Climate Models (RCMs) chain, which is a national downscaling project undertaken cooperatively by several South Korean institutes aimed at producing regional climate change projection with fine resolution (12.5 km) around the Korean Peninsula. The downscaling domain, resolution and lateral boundary conditions are held the same among the 5 RCMs to minimize the uncertainties from model configuration. Climatological changes reveal a statistically significant increase in the mid-21st century (2046- 2070; Fut1) and the late-21st century (2076-2100; Fut2) precipitation properties related to extreme precipitation, such as precipitation intensity and average of upper 5 percentile daily precipitation, with respect to the reference period (1981-2005). Changes depending on the intensity categories also present a clear trend of decreasing light rain and increasing heavy rain. In accordance with these results, the change of 1-in-50 year maximum precipitation intensity over South Korea is estimated by the GEV method. The result suggests that the 50-year return value (RV50) will change from -32.69% to 72.7% and from -31.6% to 96.32% in Fut1 and from -31.97% to 86.25% and from -19.45% to 134.88% in Fut2 under representative concentration pathway (RCP) 4.5 and 8.5 scenarios, respectively, at the 90% confidence level. This study suggests that multi-RCMs can be used to reduce uncertainties and assess the future change of extreme precipitation more reliably. Moreover, future projection of the regional climate change contains uncertainties evoked from not only driving GCM but also RCM. Therefore, multi-GCM and multi-RCM studies are expected to provide more robust projection.

  9. High resolution modelling of extreme precipitation events in urban areas

    Science.gov (United States)

    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

  10. Characterization of Multi-Scale Atmospheric Conditions Associated with Extreme Precipitation in the Transverse Ranges of Southern California

    Science.gov (United States)

    Oakley, N.; Kaplan, M.; Ralph, F. M.

    2015-12-01

    The east-west oriented Transverse Ranges of Southern California have historically experienced shallow landslides and debris flows that threaten life and property. Steep topography, soil composition, and frequent wildfires make this area susceptible to mass wasting. Extreme rainfall often acts as a trigger for these events. This work characterizes atmospheric conditions at multiple scales during extreme (>99th percentile) 1-day precipitation events in the major sub-ranges of the Transverse Ranges. Totals from these 1-day events generally exceed the established sub-daily intensity-duration thresholds for shallow landslides and debris flows in this region. Daily extreme precipitation values are derived from both gridded and station-based datasets over the period 1958-2014. For each major sub-range, extreme events are clustered by atmospheric feature and direction of moisture transport. A composite analysis of synoptic conditions is produced for each cluster to create a conceptual model of atmospheric conditions favoring extreme precipitation. The vertical structure of the atmosphere during these extreme events is also examined using observed and modeled soundings. Preliminary results show two atmospheric features to be of importance: 1) closed and cutoff low-pressure systems, areas of counter-clockwise circulation that can produce southerly flow orthogonal to the Transverse Range ridge axes; and 2) atmospheric rivers that transport large quantities of water vapor into the region. In some cases, the closed lows and atmospheric rivers work in concert with each other to produce extreme precipitation. Additionally, there is a notable east-west dipole of precipitation totals during some extreme events between the San Gabriel and Santa Ynez Mountains where extreme values are observed in one range and not the other. The cause of this relationship is explored. The results of this work can help forecasters and emergency responders determine the likelihood that an event will

  11. Need for Caution in Interpreting Daily Temperature Extremes

    Science.gov (United States)

    Sardeshmukh, P. D.; Compo, G. P.; Penland, C.

    2014-12-01

    Given the substantial anthropogenic contribution to global warming, it is tempting to seek an anthropogenic component in any unusual recent weather event, or more generally in any recent change in extreme weather statistics. We caution that such detection and attribution efforts may, however, lead to wrong conclusions if the distinctively skewed and heavy-tailed features of the probability distributions of daily weather variations are not properly accounted for. Large deviations from the mean are far more common in such a non-Gaussian world than they are in a Gaussian world. In such a world, a mean climate shift is also generally accompanied by changes in the width and shape of the probability distribution. Consequently, even the sign of the changes in tail probabilities cannot be inferred unequivocally from the mean shift. These realities further complicate the establishment of significant changes in tail probabilities from historical records of limited length and accuracy. A possible solution is to exploit the fact that the salient non-Gaussian features of the observed distributions are captured in a general class of probability distributions introduced in the meteorological literature by Sardeshmukh and Sura (2009). These distributions, called Stochastically Generated Skewed (SGS) distributions (of which Gaussian distributions are special cases), are associated with modified forms of stochastically perturbed damped linear processes, and as such represent perhaps the simplest physically based non-Gaussian prototypes of the observed distributions. Importantly, the distribution of an SGS variable remains an SGS distribution under a mean climate shift. We show further that fitting SGS distributions to all daily values in limited climate records yields extreme value distributions of block maxima with smaller sampling uncertainties than GEV distributions fitted to only the block maxima. Extreme value analysis based on SGS distributions thus provides an attractive

  12. Consequences of more extreme precipitation regimes for terrestrial ecosystems

    Energy Technology Data Exchange (ETDEWEB)

    Knapp, Alan [Colorado State University, Fort Collins; Beier, Claus [Riso National Laboratory, Roskilde, Denmark; Briske, David [Texas A& M University; Classen, Aimee T [ORNL; Luo, Yiqi [University of Oklahoma; Reichstein, Markus [Max Planck Institute for Biogeochemistry; Smith, Melinda D [Yale University; Smith, Stanley D [University of Nevada, Las Vegas; Bell, Jesse E [University of Oklahoma; Fay, Philip [ORNL; Heisler, Jana A [Colorado State University, Fort Collins; Leavitt, Steven W [unknown; Sherry, Rebecca [University of Oklahoma; Smith, Ben [unknown; Weng, Ensheng [University of Oklahoma, Norman; Norby, Richard J [ORNL

    2008-09-01

    Amplification of the hydrological cycle, as a consequence of global warming, is forecast to be manifest not only by alterations in total annual precipitation, but also through more extreme precipitation regimes characterized by larger rainfall events and more severe intervening drought periods. Based on past studies and theory, we present a conceptual framework for predicting the consequences of this projected change in intra-annual rainfall patterns for terrestrial ecosystems arrayed along a broad gradient in water availability. More extreme rainfall regimes are predicted to increase the occurrence of periodic soil water stress in mesic ecosystems due to prolonged dry periods between rainfall events. In contrast, xeric ecosystems may exhibit the opposite response because a shift to a greater proportion of rainfall delivered in large precipitation events will result in reduced proportional evaporative losses per storm event and greater soil water storage, alleviating soil water stress for longer periods of time. Hydric ecosystems may experience reduced periods of anoxia if intervals between rainfall events increase. This contingent effect of the overall soil water balance on ecosystem responses will likely cascade through all hierarchical levels of ecological processes and interact in ways currently unknown with related global change drivers such as elevated atmospheric temperatures and CO2 concentrations. Thus, multi-factor comparative experiments and systems modeling approaches are needed to more fully understand and forecast the potential ecological consequences of this underappreciated aspect of climate change.

  13. Spatiotemporal variability of extreme precipitation in Shaanxi province under climate change

    Science.gov (United States)

    Jiang, Rengui; Xie, Jiancang; Zhao, Yong; He, Hailong; He, Guohua

    2016-09-01

    Extreme climate index is one of the useful tools to monitor and detect climate change. The primary objective of this study is to provide a more comprehensively the changes in extreme precipitation between the periods of 1954-1983 and 1984-2013 in Shaanxi province under climate change, which will hopefully provide a scientific understanding of the precipitation-related natural hazards such as flood and drought. Daily precipitation from 34 surface meteorological stations were used to calculated 13 extreme precipitation indices (EPIs) generated by the joint World Meteorological Organization Commission for Climatology (CCI)/World Climate Research Programme (WCRP) project on Climate Variability and Predictability (CLIVAR) expect Team on climate change Detection, Monitoring and Indices (ETCCDMI). Two periods including 1954-1983 and 1984-2013 were selected and five types of precipitation days (R10mm-R100mm) were defined, to provide more evidences of climate change impacts on the extreme precipitation events, and specially, to investigate the changes in different types of precipitation days. The EPIs were generated using RClimRex software, and the trends were analyzed using Mann-Kendall nonparametric test and Sen's slope estimator. The relationships between the EPIs and the impacts of climate anomalies on typical EPIs were investigated using correlation and composite analysis. The mainly results include: 1) Thirteen EPIs, except consecutive dry day (CDD), were positive trends dominated for the period of 1984-2013, but the trends were not obvious for the period of 1954-1983. Most of the trends were not statistically significant at 5 % significance level. 2) The spatial distributions of stations that exhibited positive and negative trends were scattered. However, the stations that had negative trends mainly distributed in the north of Shaanxi province, and the stations that had positive trends mainly located in the south. 3) The percentage of stations that had positive

  14. Century-long variability and trends in daily precipitation characteristics at three Finnish stations

    Directory of Open Access Journals (Sweden)

    Masoud Irannezhad

    2016-03-01

    Full Text Available Long-term variations and trends in a wide range of statistics for daily precipitation characteristics in terms of intensity, frequency and duration in Finland were analysed using precipitation records during 1908–2008 from 3 meteorological stations in the south (Kaisaniemi, centre (Kajaani and north (Sodankylä. Although precipitation days in northern part were more frequent than in central and southern parts, daily precipitation intensity in the south was generally higher than those in the centre and north of the country. Annual sum of very light precipitation (0 mm < daily precipitation ≤ long-term 50th percentile of daily precipitation more than 0 mm significantly (p < 0.05 decreased over time, with the highest rate in northern Finland. These decreasing trends might be the result of significant increases in frequency of days with very light precipitation at all the stations, with the highest and lowest rates in northern and southern Finland, respectively. Ratio of annual total precipitation to number of precipitation days also declined in Finland over 1908–2008, with a decreasing north to south gradient. However, annual duration indices of daily precipitation revealed no statistically significant trends at any station. Daily precipitation characteristics showed significant relationships with various well-known atmospheric circulation patterns (ACPs. In particular, the East Atlantic/West Russia (EA/WR pattern in summer was the most influential ACP negatively associated with different daily precipitation intensity, frequency and duration indices at all three stations studied.

  15. Temporal and spatial characteristics of extreme precipitation events in the Midwest of Jilin Province based on multifractal detrended fluctuation analysis method and copula functions

    Science.gov (United States)

    Guo, Enliang; Zhang, Jiquan; Si, Ha; Dong, Zhenhua; Cao, Tiehua; Lan, Wu

    2016-08-01

    Environmental changes have brought about significant changes and challenges to water resources and management in the world; these include increasing climate variability, land use change, intensive agriculture, and rapid urbanization and industrial development, especially much more frequency extreme precipitation events. All of which greatly affect water resource and the development of social economy. In this study, we take extreme precipitation events in the Midwest of Jilin Province as an example; daily precipitation data during 1960-2014 are used. The threshold of extreme precipitation events is defined by multifractal detrended fluctuation analysis (MF-DFA) method. Extreme precipitation (EP), extreme precipitation ratio (EPR), and intensity of extreme precipitation (EPI) are selected as the extreme precipitation indicators, and then the Kolmogorov-Smirnov (K-S) test is employed to determine the optimal probability distribution function of extreme precipitation indicators. On this basis, copulas connect nonparametric estimation method and the Akaike Information Criterion (AIC) method is adopted to determine the bivariate copula function. Finally, we analyze the characteristics of single variable extremum and bivariate joint probability distribution of the extreme precipitation events. The results show that the threshold of extreme precipitation events in semi-arid areas is far less than that in subhumid areas. The extreme precipitation frequency shows a significant decline while the extreme precipitation intensity shows a trend of growth; there are significant differences in spatiotemporal of extreme precipitation events. The spatial variation trend of the joint return period gets shorter from the west to the east. The spatial distribution of co-occurrence return period takes on contrary changes and it is longer than the joint return period.

  16. Validation of EURO-CORDEX regional climate models in reproducing the variability of precipitation extremes in Romania

    Science.gov (United States)

    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

  17. MSU (Microwave Sounding Unit) Daily Troposphere Temperatures and Precipitation

    Data.gov (United States)

    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...

  18. Circulation weather types and spatial variability of daily precipitation in the Iberian Peninsula %K circulation weather types, daily gridded precipitation, Iberian Peninsula, spatial variability, seasonal variability

    Science.gov (United States)

    Ramos, Alexandre; Cortesi, Nicola; Trigo, Ricardo

    2014-10-01

    The relationships between atmospheric circulation patterns and daily Iberian rainfall are here explored at high spatial resolution (0.2°) using the Jenkinson and Collison automated classification scheme with 26 Weather Types (WTs). The WTs were computed by means of the daily EMULATE Mean Sea Level Pressure dataset (EMSLP) while the high resolution precipitation database corresponds to the recent Iberia02 daily gridded precipitation dataset over the 1950-2003 period. Six monthly indexes relating the WTs and precipitation were analyzed: their Frequency, the Mean Precipitation, the Percentage Contribution, the Area of Influence, the Precipitation Intensity and Efficiency. Except for the Frequency of the WTs, all other indexes were evaluated studying their spatial distribution over the Iberian Peninsula, focusing on a WT and a month at time. A small number of WTs (7) was found to capture a high percentage (~70%) of monthly Iberian precipitation. The Westerly WT is the most influent one, followed by the Cyclonic, the Northwesterly and the Southwesterly WTs. Westerly flows, however, do not affect the Mediterranean fringe or the Cantabrian coast, which are dominated by the Easterly and Northerly WTs, respectively. Rainfall along the Mediterranean coastline and the Ebro basin depends on a variety of WTs, but their effects are confined to narrow areas and short temporal intervals, suggesting that local factors such as convective processes, orography and the proximity to a warm water body could play a major role in precipitation processes. We show that the use of daily gridded precipitation dataset holds the advantage of measuring the daily rainfall amount due to each WT directly instead to relying on the predicted values of the regression model as done in previous works.

  19. Forecasting daily streamflow using online sequential extreme learning machines

    Science.gov (United States)

    Lima, Aranildo R.; Cannon, Alex J.; Hsieh, William W.

    2016-06-01

    While nonlinear machine methods have been widely used in environmental forecasting, in situations where new data arrive continually, the need to make frequent model updates can become cumbersome and computationally costly. To alleviate this problem, an online sequential learning algorithm for single hidden layer feedforward neural networks - the online sequential extreme learning machine (OSELM) - is automatically updated inexpensively as new data arrive (and the new data can then be discarded). OSELM was applied to forecast daily streamflow at two small watersheds in British Columbia, Canada, at lead times of 1-3 days. Predictors used were weather forecast data generated by the NOAA Global Ensemble Forecasting System (GEFS), and local hydro-meteorological observations. OSELM forecasts were tested with daily, monthly or yearly model updates. More frequent updating gave smaller forecast errors, including errors for data above the 90th percentile. Larger datasets used in the initial training of OSELM helped to find better parameters (number of hidden nodes) for the model, yielding better predictions. With the online sequential multiple linear regression (OSMLR) as benchmark, we concluded that OSELM is an attractive approach as it easily outperformed OSMLR in forecast accuracy.

  20. Predictability of summer extreme precipitation days over eastern China

    Science.gov (United States)

    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.

  1. Extreme precipitation and extreme streamflow in the Dongjiang River Basin in southern China

    Directory of Open Access Journals (Sweden)

    W. Wang

    2007-07-01

    Full Text Available Extreme hydro-meteorological events have become the focus of more and more studies in the last decade. Due to the complexity of the spatial pattern of changes in precipitation processes, it is still hard to establish a clear view of how precipitation has changed and how it will change in the future. In the present study, changes in extreme precipitation and streamflow processes in the Dongjiang River Basin in southern China are investigated. It was shown that little change is observed in annual extreme precipitation in terms of various indices, but some significant changes are found in the precipitation processes on a monthly basis. The result indicates that when detecting climate changes, besides annual indices, seasonal variations in extreme events should be considered as well. Despite of little change in annual extreme precipitation series, significant changes are detected in several annual extreme flood flow and low-flow series, mainly at the stations along the main channel of Dongjiang River, which are affected significantly by the operation of several major reservoirs. The result highlights the importance of evaluating the impacts of human activities in assessing the changes of extreme streamflows. In addition, three non-parametric methods that are not-commonly used by hydro-meteorology community, i.e., Kolmogorov–Smirnov test, Levene's test and quantile test, are introduced and assessed by Monte Carlo simulation in the present study to test for changes in the distribution, variance and the shift of tails of different groups of dataset. Monte Carlo simulation result shows that, while all three methods work well for detecting changes in two groups of data with large data size (e.g., over 200 points in each group and big difference in distribution parameters (e.g., over 100% increase of scale parameter in Gamma distribution, none of them are powerful enough for small data sets (e.g., less than 100 points and small distribution

  2. Seasonal trends in precipitation and surface air temperature extremes in mainland Portugal, 1941-2007

    Science.gov (United States)

    de Lima, M. I. P.; Santo, F. E.; Ramos, A. M.

    2012-04-01

    Several climate models predict, on a global scale, modifications in climate variables that are expected to have impact on society and the environment. The concern is on changes in the variability of processes, the mean and extreme events (maximum and minimum). To explore recent changes in precipitation and near surface air temperature extremes in mainland Portugal, we have inspected trends in time series of specific indices defined for daily data. These indices were recommended by the Commission for Climatology/Climate Variability and Predictability (CCl/CLIVAR) Working Group on Climate Change Detection, and include threshold indices, probability indices, duration indices and other indices. The precipitation and air temperature data used in this study are from, respectively, 57 and 23 measuring stations scattered across mainland Portugal, and cover the periods 1941-2007, for precipitation, and 1941-2006, for temperature. The study focuses on changes at the seasonal scale. Strong seasonality is one of the main features of climate in mainland Portugal. Intensification of the seasonality signal across the territory, particularly in the more sensitive regions, might contribute to endanger already fragile soil and water resources and ecosystems, and the local environmental and economic sustainability. Thus, the understanding of variations in the intensity, frequency and duration of extreme precipitation and air temperature events at the intra-annual scale is particularly important in this geographical area. Trend analyses were conducted over the full period of the records and for sub-periods, exploring patterns of change. Results show, on the one hand, regional differences in the tendency observed in the time series analysed; and, on the other hand, that although trends in annual indices are in general not statistically significant, there are sometimes significant changes over time in the data at the seasonal scale that point out to an increase in the already existing

  3. Extreme precipitation events in the Iberian Peninsula and its association with Atmospheric Rivers

    Science.gov (United States)

    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).

  4. 基于随机重排去趋势波动分析的全国极端日降水事件综合指标%A Composite Index of Daily Extreme Precipitation in China Based on Stochastic Resort Detrended Fluctuation Analysis

    Institute of Scientific and Technical Information of China (English)

    侯威; 钱忠华; 杨萍; 封国林

    2012-01-01

    By combining detrended fluctuation analysis (DFA) method with surrogate data method, and using the heuristic segmentation algorithm as well as ChiSquare statistics, the stochastically resorting detrended fluctuation analysis( S- DFA) method was developed to define the threshold of extreme events. By using S - DFA method, we obtained the thresholds of extreme precipitation events from 1961 to 2006 in China and analyzed its spatial - temporal distribution characteristics. We also validated the effectiveness of S - DFA method through extreme events detection by using precipitation series. The composite index of extreme precipitation events was given in this paper, which integrated the information about frequency and strength of extreme precipitation events, considering the characteristic of regional climate system. Based on the composite index, we divided into three zones according to different precipitation rank of extreme precipitation events from 1961 to 2006 in China. The composite index of extreme precipitation maintained smooth fluctuation with no obvious increasing or decreasing trend on the whole during 1961 -2006 in Chine.%将去趋势波动分析法(Detrended Fluctuation Analysis,DFA)和替代数据法相结合,同时引入启发式分割算法和卡方检验,提出了一种确定极端气候事件阈值的新方法,称为随机重排去趋势波动分析(Stochastic resort detrended Fluctuation Analysis,S-DFA)方法。同百分位阈值方法相比,S-DFA方法明确指出了极端事件和非极端事件之间的临界值。利用随机重排去趋势波动分析(S-DFA)方法计算并分析了中国极端降水事件阈值的空间分布特征,并对S-DFA方法在实际资料中的应用进行了检验。基于极端降水事件综合指标将中国1961~2006年间极端降水事件分为3个不同等级的地区,进一步发现我国1961~2006年间极端降水的综合指标整体没有表现出明显的上升或下降趋势,保持平稳的波动变化。

  5. Spatiotemporal Variability and Trends of Extreme Precipitation in the Huaihe River Basin, a Climatic Transitional Zone in East China

    Directory of Open Access Journals (Sweden)

    Zhengwe Ye

    2017-01-01

    Full Text Available Precipitation data from 30 stations in the Huaihe River basin (HRB, a climatic transitional zone in east China, were used to investigate the spatiotemporal variability and trends of extreme precipitation on multitimescales for the period 1961–2010. Results indicated that (1 the spatial pattern of the annual precipitation, rainy days, extreme precipitation, and maximum daily precipitations shows a clear transitional change from the south (high to the north (low in the HR; it confirmed the conclusion that the HRB is located in the transitional zone of the 800 mm precipitation contour in China, where the 800 mm precipitation contour is considered as the geographical boundary of the south and the north. (2 Higher value of the extreme precipitation intensity mainly occurs in the middle of the east and the central part of the basin; it reveals a relatively distinct west-east spatial disparity, and this is not in line with the spatial pattern of the extreme precipitation total, the sum of the precipitation in 95th precipitation days. (3 Annual precipitation of 22 stations exhibits increasing trend, and these 22 stations are located from the central to the northern part. There is no significant trend detected for the seasonal precipitation. The summer precipitation exhibits a larger change range; this might cause the variation of the flood and drought in the HBR. However, the increasing trend in winter precipitation may be beneficial to the relief of winter agricultural drought. Rainy days in 12 stations, mostly located in and around the central northeastern part, experienced significant decreasing trend. Extreme precipitation days and precipitation intensity have increasing trends, but no station with significant change trend is detected for the maximum precipitation of the basin. (4 The spatiotemporal variability in the HRB is mainly caused by the geographic differences and is largely influenced by the interdecadal variations of East Asian

  6. Changes in precipitation extremes in Brazil (Paraná River Basin)

    Science.gov (United States)

    Zandonadi, Leandro; Acquaotta, Fiorella; Fratianni, Simona; Zavattini, João Afonso

    2016-02-01

    This research was aimed at addressing aspects related to variation in the amount of precipitation during the period from 1986 to 2011 in the Paraná River Hydrographical Basin, Brazil, for 32 meteorological stations using 11 climate indices created by the ETCCDI (Expert Team, ET, on Climate Change Detection and Indices, ETCCDI). The daily rainfall data were organized in spreadsheets, which were subjected to an intense quality control and an accurate historical research. For each pluviometric index, we have estimated the trends and the statistical significant of the slopes have been calculated. The results confirm that an increase in total precipitation in almost all analyzed stations was registered, and the extreme precipitations were the main contributors to such additions. In fact, the significant increase in total annual rainfall in north-central sector of the basin are related to higher rates of heavy rain, mainly above 95th percentile, as well as to the highest event of rainfall above 10 mm. Instead the northern part of the region, showed declining trends of extreme rainfall, caused mainly by the reduction in the rainfall occurrences over 95th percentile. In order to evaluate the impact that the increasing extreme rainfall may cause in large urban centers, we have investigated the data of two municipalities (Curitiba, PR and Goiânia, GO-Brazil), where the positive trend can cause inconvenience to the population (floods and inundations) suggesting, at least, the need of implementation of more effective urban planning for the future.

  7. Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

    Science.gov (United States)

    Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  8. Observed variability of summer precipitation pattern and extreme events in East China associated with variations of the East Asian summer monsoon: VARIABILITY OF SUMMER PRECIPITATION AND EXTREME EVENT IN EAST CHINA

    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.

  9. Global Distribution of Extreme Precipitation and High-Impact Landslides in 2010 Relative to Previous Years

    Science.gov (United States)

    Kirschbaum, Dalia; Adler, Robert; Adler, David; Peters-Lidard, Christa; Huffman, George

    2012-01-01

    It is well known that extreme or prolonged rainfall is the dominant trigger of landslides worldwide. While research has evaluated the spatiotemporal distribution of extreme rainfall and landslides at local or regional scales using in situ data, few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This study uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from TRMM data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurrence of precipitation and landslides globally. Evaluation of the GLC indicates that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This study characterizes the variability of satellite precipitation data and reported landslide activity at the globally scale in order to improve landslide cataloging, forecasting and quantify potential triggering sources at daily, monthly and yearly time scales.

  10. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Evaporation Minus Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Evaporation Minus Precipitation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  11. CPC Unified Gauge-Based Analysis of Daily Precipitation over CONUS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CPC Unified Gauge-Based Analysis of Daily Precipitation over CONUS at PSD: Gridded Monthly Values. Monthly Values after 2006 are from the real time files (RT)

  12. Climate Prediction Center(CPC)Daily U.S. Precipitation and Temperature Summary

    Data.gov (United States)

    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...

  13. Gridded 5km GHCN-Daily Temperature and Precipitation Dataset, Version 1

    Data.gov (United States)

    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,...

  14. Performance comparison of three predictor selection methods for statistical downscaling of daily precipitation

    Science.gov (United States)

    Yang, Chunli; Wang, Ninglian; Wang, Shijin; Zhou, Liang

    2016-10-01

    Predictor selection is a critical factor affecting the statistical downscaling of daily precipitation. This study provides a general comparison between uncertainties in downscaled results from three commonly used predictor selection methods (correlation analysis, partial correlation analysis, and stepwise regression analysis). Uncertainty is analyzed by comparing statistical indices, including the mean, variance, and the distribution of monthly mean daily precipitation, wet spell length, and the number of wet days. The downscaled results are produced by the artificial neural network (ANN) statistical downscaling model and 50 years (1961-2010) of observed daily precipitation together with reanalysis predictors. Although results show little difference between downscaling methods, stepwise regression analysis is generally the best method for selecting predictors for the ANN statistical downscaling model of daily precipitation, followed by partial correlation analysis and then correlation analysis.

  15. Bayesian objective classification of extreme UK daily rainfall for flood risk applications

    Directory of Open Access Journals (Sweden)

    M. A. Little

    2008-11-01

    Full Text Available In this study we describe an objective classification scheme for extreme UK daily precipitation to be used in flood risk analysis applications. We create a simplified representation of the spatial layout of extreme events based on a new digital archive of UK rainfall. This simplification allows a Bayesian clustering algorithm to compress these representations down to eight prototypical patterns of extreme falls. These patterns are then verified against a five-class, manual, subjective typing scheme, produced independently using known meteorological mechanisms, isohyetal maps and additional descriptive text from the archive. Compared against the manual scheme, the new objective scheme can reproduce the known meteorological conditions, both in terms of spatial layout and seasonal timing, and is shown to be of hydrological relevance when matched to several notable flooding events in the past century. Furthermore, it is computationally simple and straightforward to apply in classifying future extreme rainfall events. We discuss the practical use of this new typing scheme in flood simulations and climate change applications.

  16. Slow and fast responses of mean and extreme precipitation to different forcing in CMIP5 simulations

    Science.gov (United States)

    Sillmann, Jana; Stjern, Camilla Weum; Myhre, Gunnar; Forster, Piers M.

    2017-06-01

    We are investigating the fast and slow responses of changes in mean and extreme precipitation to different climate forcing mechanisms, such as greenhouse gas and solar forcing, to understand whether rapid adjustments are important for extreme precipitation. To disentangle the effect of rapid adjustment to a given forcing on the overall change in extreme precipitation, we use a linear regression method that has been previously applied to mean precipitation. Equilibrium experiments with preindustrial CO2 concentrations and reduced solar constant were compared with a four times CO2 concentration experiment for 10 state-of-the-art climate models. We find that the two forcing mechanisms, greenhouse gases and solar, impose clearly different rapid adjustment signals in the mean precipitation, while such difference is difficult to discern for extreme precipitation due to large internal variability. In contrast to mean precipitation, changes in extreme precipitation scale with surface temperature trends and do not seem to depend on the forcing mechanism.

  17. Identifying hydro-meteorological events from precipitation extremes indices and other sources over northern Namibia, Cuvelai Basin

    Directory of Open Access Journals (Sweden)

    Frans C. Persendt

    2015-02-01

    Full Text Available Worldwide, more than 40% of all natural hazards and about half of all deaths are the result of flood disasters. In northern Namibia flood disasters have increased dramatically over the past half-century, along with associated economic losses and fatalities. There is a growing concern to identify these extreme precipitation events that result in many hydro-meteorological disasters. This study presents an up to date and broad analysis of the trends of hydrometeorological events using extreme daily precipitation indices, daily precipitation data from the Grootfontein rainfall station (1917–present, regionally averaged climatologies from the gauged gridded Climate Research Unit (CRU product, archived disasters by global disaster databases, published disaster events in literature as well as events listed by Mendelsohn, Jarvis and Robertson (2013 for the data-sparse Cuvelai river basin (CRB. The listed events that have many missing data gaps were used to reference and validate results obtained from other sources in this study. A suite of ten climate change extreme precipitation indices derived from daily precipitation data (Grootfontein rainfall station, were calculated and analysed. The results in this study highlighted years that had major hydro-meteorological events during periods where no data are available. Furthermore, the results underlined decrease in both the annual precipitation as well as the annual total wet days of precipitation, whilst it found increases in the longest annual dry spell indicating more extreme dry seasons. These findings can help to improve flood risk management policies by providing timely information on historic hydro-meteorological hazard events that are essential for early warning and forecasting.

  18. Characteristics of storms that contribute to extreme precipitation events over the Iberian Peninsula

    Science.gov (United States)

    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

  19. Intensity changes in future extreme precipitation: A statistical event-based approach.

    Science.gov (United States)

    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

  20. Classification of daily precipitation patterns on the basis of radar-derived precipitation rates for Saxony, Germany

    Energy Technology Data Exchange (ETDEWEB)

    Kronenberg, Rico; Franke, Johannes; Bernhofer, Christian [Technische Univ. Dresden (Germany). Inst. fuer Hydrologie und Meteorologie

    2012-10-15

    We present a radar-based climatology of precipitation fields summarised into characteristic daily precipitation patterns. These patterns were derived by temporal classification, applying a neural network and data from Saxony during the period from 2004 to 2010. The properties of the dataset (RADOLAN rw-product) are discussed in detail and reviewed with respect to their adequacy for the intended application. The analysis showed a systematic dependence of the precipitation error on the altitude and aggregation period. Accordingly, for future applications of the considered radar product, we recommend the use of a maximal aggregation time step of 24 hours. The classification reveals significant precipitation patterns. Comparison of the qualitative features exhibited by the precipitation patterns, such as the synoptic scale flow direction, pressure distribution and atmospheric humidity, showed general trends as well as distinct spatial and atmospheric properties in dependence of the incidence rate. The lowest statistical qualities were shown by the patterns with the most distinct spatial characteristics due to a low incidence rate and high standard deviations. Nevertheless, the applied method led to a robust classification and the derived patterns appropriately summarized the mean daily precipitation behaviour in Saxony. (orig.)

  1. Pushing precipitation to the extremes in distributed experiments: Recommendations for simulating wet and dry years

    Science.gov (United States)

    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

  2. Implications of dynamics underlying temperature and precipitation distributions for changes in extremes

    Science.gov (United States)

    Neelin, J. D.; Loikith, P. C.; Stechmann, S. N.; Sahany, S.; Bernstein, D. N.; Quinn, K. M.; Meyerson, J.; Hales, K.; Langenbrunner, B.

    2015-12-01

    Characterizing present-day probability distributions of temperature and precipitation measures are an important part of the pathway to improving quantitative assessment of changes in their extremes. In some cases, relatively simple prototypes for the dynamics underlying these distributions can assist in this characterization, pointing to key physical factors and measures to evaluate even in more complex distributions. In the case of daily temperature distributions, quantifying the widespread occurrence of non-Gaussian tails is motivated in part by tracer-advection across a maintained gradient prototypes. Substantial implications of the shape of these tails for regional changes in probabilities of temperature extremes with large-scale warming motivate measures of non-Gaussianity specific to this problem for assessing climate model present-day simulations. In the case of distributions of precipitation accumulations, simple prototypes yield insights into the form of the present-day distribution and predictions for the form of the global warming changes that can be evaluated in models and observations. Probability drops relatively slowly over a substantial range of accumulation size, followed by a key cutoff scale that limits large event probabilities in current climate but changes under global warming. Precipitation integrated over spatial clusters exhibits similar distribution features.

  3. A space and time scale-dependent nonlinear geostatistical approach for downscaling daily precipitation and temperature

    KAUST Repository

    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.

  4. Assessing changes in extreme precipitation over Xinjiang using regional climate model of PRECIS

    Institute of Scientific and Technical Information of China (English)

    YanWei Zhang; QuanSheng Ge; FengQing Jiang; JingYun Zheng; WenShou Wei

    2015-01-01

    In this paper, an analysis, with the simulation of PRECIS (Providing Regional Climate for Impact Studies), was made for future precipitation extremes, under SRES (Special Report on Emission Scenarios) A2 and B2 in IPCC (Intergovernmental Panel on Climate Change) AR4. The precipitation extremes were calculated and analyzed by ETCCDI (Climate Change Detection and Indices). The results show that: (1) In Present Scenario (1961–1900), PRECIS could capture the spatial pattern of precipitation in Xinjiang. (2) The simulated annual precipitation and seasonal precipitation in Xinjiang had a significantly positive trend and its variability had been deeply impacted by terrain. There was a strong association between increasing trend and the extreme precipitation's increase in frequency and intensity during 1961–2008. Under SRES A2 and B2, extreme precipitation indicated an increasing tendency at the end of the 21st century. The extreme summer pre-cipitation increased prominently in a year. (3) PRECIS's simulation under SRES A2 and B2 indicated increased frequency of heavy precipitation events and also enhancement in their intensity towards the end of the 21st century. Both A2 and B2 scenarios show similar patterns of projected changes in precipitation extremes towards the end of the 21st century. However, the magnitude of changes in B2 scenario was on the lower side. In case of extreme precipitation, variation between models can exceed both internal variability and variability of different SRES.

  5. Atmospheric rivers and cool season extreme precipitation events in Arizona

    Science.gov (United States)

    Rivera Fernandez, Erick Reinaldo

    Atmospheric rivers (ARs) are important contributors to cool season precipitation in the Southwestern US, and in some cases can lead to extreme hydrometeorological events in the region. We performed a climatological analysis and identified two predominant types of ARs that affect the central mountainous region in Arizona: Type 1 ARs originate in the tropics near Hawaii (central Pacific) and enhance their moisture in the midlatitudes, with maximum moisture transport over the ocean at low-levels of the troposphere. On the other hand, moisture in Type 2 ARs has a more direct tropical origin and meridional orientation with maximum moisture transfer at mid-levels. We then analyze future projections of Southwest ARs in a suite of global and regional climate models used in the North American Regional Climate Change Assessment Program (NARCCAP), to evaluate projected future changes in the frequency and intensity of ARs under warmer global climate conditions. We find a consistent and clear intensification of the water vapor transport associated with the ARs that impinge upon Arizona and adjacent regions, however, the response of AR-related precipitation intensity to increased moisture flux and column-integrated water vapor is weak and no robust variations are projected either by the global or the regional NARCCAP models. To evaluate the effect of horizontal resolution and improve our physical understanding of these results, we numerically simulated a historical AR event using the Weather Research and Forecasting (WRF) model at a 3-km resolution. We then performed a pseudo-global warming experiment by modifying the lateral and lower boundary conditions to reflect possible changes in future ARs (as projected by the ensemble of global model simulations used for NARCCAP). Interestingly we find that despite higher specific humidity, some regions still receive less rainfall in the warming climate experiments - partially due to changes in thermodynamics, but primarily due to AR

  6. Circulation weather types and spatial variability of daily precipitation in the Iberian Peninsula

    Directory of Open Access Journals (Sweden)

    Alexandre M. Ramos

    2014-10-01

    Full Text Available The relationships between atmospheric circulation patterns and daily Iberian rainfall are here explored at high spatial resolution (0.2° using the Jenkinson and Collison automated classification scheme with 26 Weather Types (WTs. The WTs were computed by means of the daily EMULATE Mean Sea Level Pressure dataset (EMSLP while the high resolution precipitation database corresponds to the recent Iberia02 daily gridded precipitation dataset over the 1950-2003 period. Six monthly indexes relating the WTs and precipitation were analyzed: their Frequency, the Mean Precipitation, the Percentage Contribution, the Area of Influence, the Precipitation Intensity and Efficiency. Except for the Frequency of the WTs, all other indexes were evaluated studying their spatial distribution over the Iberian Peninsula, focusing on a WT and a month at time. A small number of WTs (7 was found to capture a high percentage (~70% of monthly Iberian precipitation. The Westerly WT is the most influent one, followed by the Cyclonic, the Northwesterly and the Southwesterly WTs. Westerly flows, however, do not affect the Mediterranean fringe or the Cantabrian coast, which are dominated by the Easterly and Northerly WTs, respectively. Rainfall along the Mediterranean coastline and the Ebro basin depends on a variety of WTs, but their effects are confined to narrow areas and short temporal intervals, suggesting that local factors such as convective processes, orography and the proximity to a warm water body could play a major role in precipitation processes.We show that the use of daily gridded precipitation dataset holds the advantage of measuring the daily rainfall amount due to each WT directly instead to relying on the predicted values of the regression model as done in previous works.

  7. An application programming interface for extreme precipitation and hazard products

    Science.gov (United States)

    Kirschbaum, D.; Stanley, T.; Cappelaere, P. G.; Reed, J.; Lammers, M.

    2016-12-01

    Remote sensing data provides situational awareness of extreme events and hazards over large areas in a way that is impossible to achieve with in situ data. However, more valuable than raw data is actionable information based on user needs. This information can take the form of derived products, extraction of a subset of variables in a larger data matrix, or data processing for a specific goal. These products can then stream to the end users, who can use these data to improve local to global decision making. This presentation will outline both the science and methodology of two new data products and tools that can provide relevant climate and hazard data for response and support. The Global Precipitation Measurement (GPM) mission provides near real-time information on rain and snow around the world every thirty minutes. Through a new applications programing interface (API), this data can be freely accessed by consumers to visualize, analyze, and communicate where, when and how much rain is falling worldwide. The second tool is a global landslide model that provides situational awareness of potential landslide activity in near real-time, utilizing several remotely sensed data products. This hazard information is also provided through an API and is being ingested by the emergency response community, international aid organizations, and others around the world. This presentation will highlight lessons learned through the development, implementation, and communication of these products and tools with the goal of enabling better and more effective decision making.

  8. Contribution of large-scale circulation anomalies to changes in extreme precipitation frequency in the United States

    Science.gov (United States)

    Yu, Lejiang; Zhong, Shiyuan; Pei, Lisi; Bian, Xindi; Heilman, Warren E.

    2016-04-01

    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.

  9. Variability of temperature sensitivity of extreme precipitation from a regional-to-local impact scale perspective

    Science.gov (United States)

    Schroeer, K.; Kirchengast, G.

    2016-12-01

    Relating precipitation intensity to temperature is a popular approach to assess potential changes of extreme events in a warming climate. Potential increases in extreme rainfall induced hazards, such as flash flooding, serve as motivation. It has not been addressed whether the temperature-precipitation scaling approach is meaningful on a regional to local level, where the risk of climate and weather impact is dealt with. Substantial variability of temperature sensitivity of extreme precipitation has been found that results from differing methodological assumptions as well as from varying climatological settings of the study domains. Two aspects are consistently found: First, temperature sensitivities beyond the expected consistency with the Clausius-Clapeyron (CC) equation are a feature of short-duration, convective, sub-daily to sub-hourly high-percentile rainfall intensities at mid-latitudes. Second, exponential growth ceases or reverts at threshold temperatures that vary from region to region, as moisture supply becomes limited. Analyses of pooled data, or of single or dispersed stations over large areas make it difficult to estimate the consequences in terms of local climate risk. In this study we test the meaningfulness of the scaling approach from an impact scale perspective. Temperature sensitivities are assessed using quantile regression on hourly and sub-hourly precipitation data from 189 stations in the Austrian south-eastern Alpine region. The observed scaling rates vary substantially, but distinct regional and seasonal patterns emerge. High sensitivity exceeding CC-scaling is seen on the 10-minute scale more than on the hourly scale, in storms shorter than 2 hours duration, and in shoulder seasons, but it is not necessarily a significant feature of the extremes. To be impact relevant, change rates need to be linked to absolute rainfall amounts. We show that high scaling rates occur in lower temperature conditions and thus have smaller effect on absolute

  10. Bias correction of daily precipitation in south-central Chile using NCEP CFSv2

    Science.gov (United States)

    Maass, T.; castro Heredia, L. M.; Suarez, F. I.; Fernandez, B.

    2015-12-01

    Hydroelectric power plant operations are heavily influenced by the streamflow forecasts on their basins. In Chile, these forecasts are based on historical observations. However, this approach has reached its limit of quality and reliability, being difficult to adapt to current weather conditions (climate change), to extreme weather conditions, and to ungauged basins. In this work, we evaluated the bias correction of NCEP-CSv2 daily precipitation with the aim of incorporating this forecast into a real-time hydrological forecasting system. Bias correction was performed using two approaches of the Quantile Mapping (QM) method: a) a polynomial fit (APo) applied to the differences between the forecasted and observed cumulative distribution functions (CDFs) for the training period; and b) using a Gamma probability distribution (APb) to fit the forecasted and observed CDFs. The bias correction was applied at two locations in south-central Chile: over the valley and in the Andes mountains. To estimate the CDFs and the QM fitting models in the training period, historical records and data from the CFSv2 Reforecast model (between 1995 and 2009) were used. The bias correction evaluation was done between 2011 and 2014 with the forecast of the CFSv2 model. The uncorrected CFSv2 results show that the mid-term forecasts (six months) have a high correlation (r>0.5) for the first days of the forecast (2 weeks), but an important underestimation in the observed data from both the valley and the mountain. After applying the bias correction (APo or APb), the errors of the corrected forecasts decrease in relation to the uncorrected CFSv2 forecasts, with a noticeable improvement for the first forecasted days (being the APo errors lower than those of the APb). In the long term, and as might be expected, the errors increase: the peak precipitation is underestimated and the null rainfall is overestimated.

  11. Assessing the impacts of changing precipitation and temperature extremes on the current and future ecohydrology of grassland ecosystems

    Science.gov (United States)

    Brunsell, N. A.; Nippert, J. B.; Ocheltree, T.

    2012-12-01

    Extreme weather events have profound impacts on water and carbon cycling. However, events of similar magnitude may have very different impacts depending upon the timing of the event in the phenological cycle. We assess these impacts of extreme daily weather events including precipitation, maximum and minimum temperature using data collected from the Konza Prairie Long Term Ecological Research site in the central U.S. We utilize the long term weather and biomass collection data at the LTER site to examine the historical variability of extreme events and the impacts on annual carbon dynamics. Timescales of interactions between daily weather and fluxes are quantified through a multiscale information theoretic approach. In addition, we quantify the impacts of the timing and magnitude of extreme events through a Critical Climate Period (CCP) analysis. Results indicate a strong sensitivity to spring precipitation and summer temperature. Using six years of eddy covariance data, we can isolate more of the biophysical mechanisms governing the responses to extreme weather events. Of particular interest is the heat wave of July, 2011, where daily maximum temperatures were over 38 C for 24 consecutive days and resulted in drastically reduced above ground carbon allocation than in previous years. In addition, we employ the Agro-BGC model to assess the biophysical processes responsible for determining the response of water and carbon dynamics to extreme weather events. This is done by employing a stochastic weather generator with prescribed changes in annual precipitation and temperature conistent with GCM projections. Developing a more thorough understanding of extreme events and the differential responses due to the timing and magnitude of the events will potentially assist in the mitigation of future climate change.

  12. Lower Extremity Overuse Conditions Affecting Figure Skaters During Daily Training

    National Research Council Canada - National Science Library

    Campanelli, Valentina; Piscitelli, Francesco; Verardi, Luciano; Maillard, Pauline; Sbarbati, Andrea

    2015-01-01

    Background Most ice figure skaters train and compete with ongoing issues in the lower extremities, which are often overlooked by the skaters and considered injuries only when they prevent the athletes from skating...

  13. Scale parameters in stationary and non-stationary GEV modeling of extreme precipitation

    Science.gov (United States)

    Panagoulia, Dionysia; Economou, Polychronis; Caroni, Chrys

    2013-04-01

    The generalized extreme value (GEV) distribution is often fitted to environmental time series of extreme values such as annual maxima of daily precipitation. We study two methodological issues here. First we compare methods of selecting the best model among a set of 16 GEV models that allow non-stationary scale and location parameters. Results of simulation studies showed that both the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) correctly detected non-stationarity but the BIC was superior in selecting the correct model more often. The second issue is how best to produce confidence intervals (CIs) for the parameters of the model and other quantities such as the return levels that are usually required for hydrological and climatological time series. Four bootstrap CIs - normal, percentile, basic, and bias corrected and accelerated (BCa) - constructed by random-t resampling, fixed-t resampling and the parametric bootstrap methods were compared. CIs for parameters of the stationary model do not present major differences. CIs for the more extreme quantiles tend to become very wide for all bootstrap methods. For non-stationary GEV models with linear time dependence of location or log-linear time dependence of scale, coverage probabilities of the CIs are reasonably accurate for the parameters. For the extreme percentiles, the BCa method is best overall and the fixed-t method also gives good average coverage probabilities.

  14. ECMWF Extreme Forecast Index for water vapor transport: A forecast tool for atmospheric rivers and extreme precipitation

    Science.gov (United States)

    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.

  15. Can reanalysis datasets describe the persistent temperature and precipitation extremes over China?

    Science.gov (United States)

    Zhu, Jian; Huang, Dan-Qing; Yan, Pei-Wen; Huang, Ying; Kuang, Xue-Yuan

    2016-08-01

    The persistent temperature and precipitation extremes may bring damage to the economy and human due to their intensity, duration and areal coverage. Understanding the quality of reanalysis datasets in descripting these extreme events is important for detection, attribution and model evaluation. In this study, the performances of two reanalysis datasets [the twentieth century reanalysis (20CR) and Interim ECMWF reanalysis (ERA-Interim)] in reproducing the persistent temperature and precipitation extremes in China are evaluated. For the persistent temperature extremes, the two datasets can better capture the intensity indices than the frequency indices. The increasing/decreasing trend of persistent warm/cold extremes has been reasonably detected by the two datasets, particularly in the northern part of China. The ERA-Interim better reproduces the climatology and tendency of persistent warm extremes, while the 20CR has better skill to depict the persistent cold extremes. For the persistent precipitation extremes, the two datasets have the ability to reproduce the maximum consecutive 5-day precipitation. The two datasets largely underestimate the maximum consecutive dry days over the northern part of China, while overestimate the maximum consecutive wet days over the southern part of China. For the response of the precipitation extremes against the temperature variations, the ERA-Interim has good ability to depict the relationship among persistent precipitation extremes, local persistent temperature extremes, and global temperature variations over specific regions.

  16. Changes of Frequency of Summer Precipitation Extremes over the Yangtze River in Association with Large-scale Oceanic-atmospheric Conditions

    Institute of Scientific and Technical Information of China (English)

    WANG Yi; YAN Zhongwei

    2011-01-01

    Changes of the frequency of precipitation extremes (the number of days with daily precipitation exceeding the 90th percentile of a daily climatology,referred to as R90N) in summer (June-August) over the mid-lower reaches of the Yangtze River arc analyzed based on daily observations during 1961-2007.The first singular value decomposition (SVD) mode of R90N is linked to an ENSO-like mode of the sea surface temperature anomalies (SSTA) in the previous winter.Responses of different grades of precipitation events to the climatic mode are compared.It is notable that the frequency of summer precipitation extremes is significantly related with the SSTA in the Pacific,while those of light and moderate precipitation are not.It is suggested that the previously well-recognized impact of ENSO on summer rainfall along the Yangtze River is essentially due to a response in summer precipitation extremes in the region,in association with the East Asia-Pacific (EAP) teleconnection pattern.A negative relationship is found between the East Asian Summer Monsoon (EASM) and precipitation extremes over the mid-lower reaches of the Yangtze River.In contrast,light rainfall processes are independent from the SST and EASM variations.

  17. Seasonal and regional variations in extreme precipitation event frequency using CMIP5

    Science.gov (United States)

    Janssen, E.; Sriver, R. L.; Wuebbles, D. J.; Kunkel, K. E.

    2016-05-01

    Understanding how the frequency and intensity of extreme precipitation events are changing is important for regional risk assessments and adaptation planning. Here we use observational data and an ensemble of climate change model experiments (from the Coupled Model Intercomparison Project Phase 5 (CMIP5)) to examine past and potential future seasonal changes in extreme precipitation event frequency over the United States. Using the extreme precipitation index as a metric for extreme precipitation change, we find key differences between models and observations. In particular, the CMIP5 models tend to overestimate the number of spring events and underestimate the number of summer events. This seasonal shift in the models is amplified in projections. These results provide a basis for evaluating climate model skill in simulating observed seasonality and changes in regional extreme precipitation. Additionally, we highlight key sources of variability and uncertainty that can potentially inform regional impact analyses and adaptation planning.

  18. Sensitivity of precipitation extremes to radiative forcing of greenhouse gases and aerosols

    Science.gov (United States)

    Lin, Lei; Wang, Zhili; Xu, Yangyang; Fu, Qiang

    2016-09-01

    Greenhouse gases (GHGs) and aerosols are the two most important anthropogenic forcing agents in the 21st century. The expected declines of anthropogenic aerosols in the 21st century from present-day levels would cause an additional warming of the Earth's climate system, which would aggravate the climate extremes caused by GHG warming. We examine the increased rate of precipitation extremes with global mean surface warming in the 21st century caused by anthropogenic GHGs and aerosols, using an Earth system model ensemble simulation. Similar to mean precipitation, the increased rate of precipitation extremes caused by aerosol forcing is significantly larger than that caused by GHG forcing. The aerosol forcing in the coming decades can play a critical role in inducing change in precipitation extremes if a lower GHG emission pathway is adopted. Our results have implications for policy-making on climate adaptation to extreme precipitation events.

  19. Using damage data to estimate the risk from summer convective precipitation extremes

    Science.gov (United States)

    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

  20. Changes in annual temperature and precipitation extremes in the Carpathians since AD 1961

    Science.gov (United States)

    Dumitrescu, Alexandru; Birsan, Marius-Victor; Magdalena Micu, Dana; Cheval, Sorin

    2014-05-01

    The Carpathians are the largest, longest, most twisted and fragmented segment of the Alpine system, stretching between latitudes 44°N and 50°N, and longitudes 17°E and 27°E. This European mountain range is a climatically transitional region between major atmospheric circulation source areas of the Atlantic Ocean, Mediterranean Sea and continental Europe. The region is a European biodiversity hotspot, containing over one third of all European plant species. It is acknowledged that the mountain regions are particularly sensitive and vulnerable to climate change than any other regions located at the same latitudes. Observational studies on the variability and trends of extreme events suggest an overall consensus towards a significant increase in the frequency, duration and intensity of warm extremes in most of these regions, including the Carpathians. 15 core indices, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), were computed in order to investigate the changes in annual temperature and precipitation extremes, based on their known relevance for the infrastructure, human health and tourism activities in these mountains. The indices were computed from gridded daily datasets of minimum and maximum temperature and precipitation at 0.1° resolution (~10 km), available online within the framework of the project CarpatClim (www.carpatclim-eu.org) for the period 1961-2010. Changes in the annual temperature and precipitation extremes in the last five decades have been identified with the Mann-Kendall non-parametric trend test, at the 90% significance level (two-tail test). The results show decreasing trends in cold-related thermal indices, especially in the number of frost days, and increasing trends in warm-related ones. No consistent trend in precipitation extremes has been found. There is a generally uniform signal of significant increasing trends in the frequency of summer days across the Carpathians, with no obvious differences between

  1. Simulations of The Extreme Precipitation Event Enhanced by Sea Surface Temperature Anomaly over the Black Sea

    Science.gov (United States)

    Hakan Doǧan, Onur; Önol, Barış

    2016-04-01

    Istanbul Technical University, Aeronautics and Astronautics Faculty, Meteorological Engineering, Istanbul, Turkey In this study, we examined the extreme precipitation case over the Eastern Black Sea region of Turkey by using regional climate model, RegCM4. The flood caused by excessive rain in August 26, 2010 killed 12 people and the landslides in Rize province have damaged many buildings. The station based two days total precipitation exceeds 200 mm. One of the usual suspects for this extreme event is positive anomaly of sea surface temperature (SST) over the Black Sea where the significant warming trend is clear in the last three decades. In August 2010, the monthly mean SST is higher than 3 °C with respect to the period of 1981-2010. We designed three sensitivity simulations with RegCM4 to define the effects of the Black Sea as a moisture source. The simulation domain with 10-km horizontal resolution covers all the countries bordering the Black Sea and simulation period is defined for entire August 2010. It is also noted that the spatial variability of the precipitation produced by the reference simulation (Sim-0) is consistent with the TRMM data. In terms of analysis of the sensitivity to SST, we forced the simulations by subtracting 1 °C (Sim-1), 2 °C (Sim-2) and 3 °C (Sim-3) from the ERA-Interim 6-hourly SST data (considering only the Black Sea). The sensitivity simulations indicate that daily total precipitation for all these simulations gradually decreased based on the reference simulation (Sim-0). 3-hourly maximum precipitation rates for Sim-0, Sim-1, Sim-2 and Sim-3 are 32, 25, 13 and 10.5 mm respectively over the hotspot region. Despite the fact that the simulations signal points out the same direction, degradation of the precipitation intensity does not indicate the same magnitude for all simulations. It is revealed that 2 °C (Sim-2) threshold is critical for SST sensitivity. We also calculated the humidity differences from the simulation and these

  2. Different sub-monsoon signals in stable oxygen isotope in daily precipitation to the northeast of the Tibetan Plateau

    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.

  3. Reconstructing missing daily precipitation data using regression trees and artificial neural networks

    Science.gov (United States)

    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)....

  4. Dry and wet spell variability during monsoon in gauge-based gridded daily precipitation datasets over India

    Science.gov (United States)

    Chaudhary, Shushobhit; Dhanya, C. T.; Vinnarasi, R.

    2017-03-01

    Accurate estimates of monsoonal rainfall at daily time scales are essential inputs for various water-related sectors such as drought and flood forecasting, crop and water management for agriculture. To serve this purpose, a variety of rainfall products, especially the gauge based products which serve as the ground-truth for other derived rainfall products, are available over India. In this study, three different daily gauge based gridded rainfall datasets, namely Indian Meteorological Department (IMD), Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APHRODITE) and Climate Prediction Center (CPC) unified rain gauge data are compared over India for the monsoon season of 1979-2007. The comparison among the datasets is based on the duration, frequency and intensity of three different spell characteristics, namely dry, wet and extreme wet spells, and their associated trends. Wet (dry) spells are defined as the consecutive period of wet (dry) days, where a wet (dry) day is defined using rainfall threshold of 1 mm. Extreme wet spells are defined using the 90th percentile of rainfall above the depth of wet day. All datasets capture the spatial distribution of precipitation characteristics, albeit with pronounced differences at heavy rainfall regions. CPC and IMD show a close match in spell characteristics while APHRODITE significantly deviates. APHRODITE shows increased intensity of rainfall during dry periods, leading to over-estimation of wet days and under-estimation of dry days. Northern extreme of India (Jammu and Kashmir) show major differences in replicating the spell characteristics. Trend patterns are also not consistent between the three datasets. The present study will provide information on the spatio-temporal pattern of dry, wet and extreme wet spell characteristics over India and aid in selecting appropriate datasets for studying the Indian monsoon rainfall depending on their scope and application of

  5. Differential imprints of different ENSO flavors in global patterns of seasonal precipitation extremes

    Science.gov (United States)

    Wiedermann, Marc; Siegmund, Jonatan F.; Donges, Jonathan F.; Donner, Reik V.

    2017-04-01

    The El Nino Southern Oscillation (ENSO) with its positive (El Nino) and negative (La Nina) phases is known to trigger climatic responses in various parts of the Earth, an effect commonly attributed to teleconnectivity. A series of studies has demonstrated that El Nino periods exhibits a relatively broad variety of spatial patterns, which can be classified into two main flavors termed East Pacific (EP, canonical) and Central Pacific (CP, Modoki) El Nino, and that both subtypes can trigger distinct climatic responses like droughts vs. precipitation increases at the regional level. More recently, a similar discrimination of La Nina periods into two different flavors has been reported, and it is reasonable to assume that these different expressions are equally accompanied by differential responses of regional climate variability in particularly affected regions. In this work, we study in great detail the imprints of both types of El Nino and La Nina periods in extremal seasonal precipitation sums during fall (SON), winter (DJF) and spring (MAM) around the peak time of the corresponding ENSO phase. For this purpose, we employ a recently developed objective classification of El Nino and La Nina periods into their two respective flavors based on global teleconnectivity patterns in daily surface air temperature anomalies as captured by the associated climate network representations (Wiedermann et al., 2016). In order to study the statistical relevance of the timing of different El Nino and La Nina types on that of seasonal precipitation extremes around the globe (according to the GPCC data set as a reference), we utilize event coincidence analysis (Donges et al., 2016), a new powerful yet conceptually simple and intuitive statistical tool that allows quantifying the degree of simultaneity of distinct events in pairs of time series. Our results provide a comprehensive overview on ENSO related imprints in regional seasonal precipitation extremes. We demonstrate that key

  6. The impact of extreme precipitation on plant growth and water relations

    Science.gov (United States)

    Zeppel, M.; Lehmann, C.; Lewis, J. D.; Medlyn, B. E.

    2012-12-01

    Background The global hydrological cycle is predicted to become more intense, or extreme in future climates, with both larger precipitation events and longer times between events. The resulting wide fluctuations in soil water content (long droughts followed by flooding) may dramatically affect terrestrial ecosystems. Although effects of drought are well studied, tree responses to changed timing of precipitation are mostly unknown. Further, in future extreme precipitation is likely to occur in conjunction with elevated atmospheric CO2 concentrations [CO2]. We tested the impact of extreme precipitation and elevated [CO2] on plant growth and water relations. Methods/results Ten Acacia auriculiformis and Eucalyptus tetradonta saplings were grown in glasshouses, with ambient (380 p.p.m.) and elevated (600 p.p.m.) [CO2] and subject to ambient (1L weekly) and extreme (2L fortnightly) watering conditions (four treatments). We tested whether: (1) plants would show differential water stress and growth under extreme precipitation compared with ambient water treatments; and (2) plants would show differential water stress and growth responses under elevated compared with ambient [CO2] treatments. We found that the extreme precipitation, compared to ambient precipitation, lead to more water stressed plants, with more negative leaf water potential and lower stomatal conductance in both species. Further, plants experiencing extreme precipitation had a higher proportion of root volume at depth within the Eucalyptus. In contrast, the root depth of Acacia was similar across all treatments. Leaf area was smaller in extreme precipitation compared with ambient for Acacias, whereas leaf area was comparable across watering treatments in Eucalypts. Elevated CO2 had no impact on leaf water potential, stomatal conductance during the day or proportion of root depth. The Acacia, from tropical dry forest ecosystems, showed more signs of water stress (more negative leaf water potential and lower

  7. 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.

  8. Comparing regional precipitation and temperature extremes in climate model and reanalysis products.

    Science.gov (United States)

    Angélil, Oliver; Perkins-Kirkpatrick, Sarah; Alexander, Lisa V; Stone, Dáithí; Donat, Markus G; Wehner, Michael; Shiogama, Hideo; Ciavarella, Andrew; Christidis, Nikolaos

    2016-09-01

    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.

  9. Operational quality control of daily precipitation using spatio-climatological consistency testing

    Science.gov (United States)

    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.

  10. Regression model for generating time series of daily precipitation amounts for climate change impact studies

    Science.gov (United States)

    Buishand, T. A.; Klein Tank, A. M. G.

    1996-05-01

    The precipitation amounts on wet days at De Bilt (the Netherlands) are linked to temperature and surface air pressure through advanced regression techniques. Temperature is chosen as a covariate to use the model for generating synthetic time series of daily precipitation in a CO2 induced warmer climate. The precipitation-temperature dependence can partly be ascribed to the phenomenon that warmer air can contain more moisture. Spline functions are introduced to reproduce the non-monotonous change of the mean daily precipitation amount with temperature. Because the model is non-linear and the variance of the errors depends on the expected response, an iteratively reweighted least-squares technique is needed to estimate the regression coefficients. A representative rainfall sequence for the situation of a systematic temperature rise is obtained by multiplying the precipitation amounts in the observed record with a temperature dependent factor based on a fitted regression model. For a temperature change of 3°C (reasonable guess for a doubled CO2 climate according to the present-day general circulation models) this results in an increase in the annual average amount of 9% (20% in winter and 4% in summer). An extended model with both temperature and surface air pressure is presented which makes it possible to study the additional effects of a potential systematic change in surface air pressure on precipitation.

  11. A stage structured mosquito model incorporating effects of precipitation and daily temperature fluctuations.

    Science.gov (United States)

    Wang, Xia; Tang, Sanyi; Cheke, Robert A

    2016-12-21

    An outbreak of dengue fever in Guangdong province in 2014 was the most serious outbreak ever recorded in China. Given the known positive correlation between the abundance of mosquitoes and the number of dengue fever cases, a stage structured mosquito model was developed to investigate the cause of the large abundance of mosquitoes in 2014 and its implications for outbreaks of the disease. Data on the Breteau index (number of containers positive for larvae per 100 premises investigated), temperature and precipitation were used for model fitting. The egg laying rate, the development rate and the mortality rates of immatures and adults were obtained from the estimated parameters. Moreover, effects of daily fluctuations of temperature on these parameters were obtained and the effects of temperature and precipitation were analyzed by simulations. Our results indicated that the abundance of mosquitoes depended not only on the total annual precipitation but also on the distribution of the precipitation. The daily mean temperature had a nonlinear relationship with the abundance of mosquitoes, and large diurnal temperature differences can reduce the abundance of mosquitoes. In addition, effects of increasing precipitation and temperature were interdependent. Our findings suggest that the large abundance of mosquitoes in 2014 was mainly caused by the distribution of the precipitation. In the perspective of mosquito control, our results reveal that it is better to clear water early and spray insecticide between April and August in case of limited resources.

  12. Extreme precipitation events in the Czech Republic in the context of climate change

    Directory of Open Access Journals (Sweden)

    V. Květoň

    2008-04-01

    Full Text Available As an introduction, short survey of two analyses of long-term fluctuations of annual precipitation totals in the Czech Republic is presented. The main focus of this paper is to contribute to investigation of precipitation trends in the Czech Republic by another point of view. For every pixel of 1 km2 size, annual maxima of daily precipitation were obtained for time period of 112 years (1895–2006. Based on these time series, we were trying to answer question if there are some changes of area size/distribution of annual maximum of daily precipitation totals. Courses and trends are analyzed for some parameters of area distribution of annual maximum of daily precipitation totals in the area of the Czech Republic. No significant climate changes of tested precipitation characteristics were found.

  13. Identification of the non-stationarity of extreme precipitation events and correlations with large-scale ocean-atmospheric circulation patterns: A case study in the Wei River Basin, China

    Science.gov (United States)

    Liu, Saiyan; Huang, Shengzhi; Huang, Qiang; Xie, Yangyang; Leng, Guoyong; Luan, Jinkai; Song, Xiaoyu; Wei, Xiu; Li, Xiangyang

    2017-05-01

    The investigation of extreme precipitation events in terms of variation characteristics, stationarity, and their underlying causes is of great significance to better understand the regional response of the precipitation variability to global climate change. In this study, the Wei River Basin (WRB), a typical eco-environmentally vulnerable region of the Loess Plateau in China was selected as the study region. A set of precipitation indices was adopted to study the changing patterns of precipitation extremes and the stationarity of extreme precipitation events. Furthermore, the correlations between the Pacific Decadal Oscillation (PDO)/El Niño-Southern Oscillation (ENSO) events and precipitation extremes were explored using the cross wavelet technique. The results indicate that: (1) extreme precipitation events in the WRB are characterized by a significant decrease of consecutive wet days (CWD) at the 95% confidence level; (2) compared with annual precipitation, daily precipitation extremes are much more sensitive to changing environments, and the assumption of stationarity of extreme precipitation in the WRB is invalid, especially in the upstream, thereby introducing large uncertainty to the design and management of water conservancy engineering; (3) both PDO and ENSO events have a strong influence on precipitation extremes in the WRB. These findings highlight the importance of examining the validity of the stationarity assumption in extreme hydrological frequency analysis, which has great implications for the prediction of extreme hydrological events.

  14. Extreme precipitation and temperature responses to circulation patterns in current climate: statistical approaches

    NARCIS (Netherlands)

    Photiadou, C.

    2015-01-01

    Climate change is likely to influence the frequency of extreme extremes - temperature, precipitation and hydrological extremes, which implies increasing risks for flood and drought events in Europe. In current climate, European countries were often not sufficiently prepared to deal with the great so

  15. Rising Mediterranean Sea Surface Temperatures Amplify Extreme Summer Precipitation in Central Europe

    Science.gov (United States)

    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.

  16. Interpolation of daily precipitation in mountain catchments with limited data availability

    Science.gov (United States)

    Jacquin, Alexandra

    2014-05-01

    Statistical properties of precipitation in mountain catchments are likely to be heterogeneous, due to the effect of orography. The interpolation of precipitation gauge data in these cases requires the application of methods that are able to account for the existence of a spatial trend in the expectation of precipitation. Most studies in this subject have used data from regions with relatively dense meteorological networks and the question of what interpolation methods can provide more reliable results in mountain catchments with limited data availability is largely unexplored. This study evaluates the applicability of the techniques kriging with external drift (KED) and optimal interpolation method (OIM) in this scenario. The Thiessen polygons (TP) method is used as a benchmark. The study area is located in the upper Aconcagua River catchment, in Central Chile. Daily data spanning a period of ten years, from nine stations located between 640[m.a.s.l.] and 2765[m.a.s.l.], are used. Given that precipitation in the area is seasonal with respect to both precipitation amounts and their spatial dependence structure, data from each month of the year are treated separately. Aconcagua at Chacabuquito sub-catchment, with an area of 2110[Km2] and elevation ranging from 950[m.a.s.l.] to 5930[m.a.s.l.], is used as a case study. KED and OIM incorporate the information on the spatial trend of daily precipitation differently. KED postulates that the function that defines the expectation of precipitation at each location is a linear combination of basis function of known type. Preliminary analysis revealed that a logarithmic relationship between the expectation of daily precipitation and elevation was appropriate. The application of the OIM requires prior estimation of both the expectation and the standard deviation of precipitation at the location of interest. For this purpose, logarithmic relationships between long-term mean precipitation and elevation, and between sample

  17. Validation and Development of the GPCP Experimental One-Degree Daily (1DD) Global Precipitation Product

    Science.gov (United States)

    Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Einaud, Franco (Technical Monitor)

    2000-01-01

    The One-Degree Daily (1DD) precipitation dataset has been developed for the Global Precipitation Climatology Project (GPCP) and is currently in beta test preparatory to release as an official GPCP product. The 1DD provides a globally-complete, observation-only estimate of precipitation on a daily 1 deg. x 1 deg. grid for the period 1997 through early 2000 (by the time of the conference). In the latitude band 40N-40S the 1DD uses the Threshold-Matched Precipitation Index (TMPI), a GPI-like IR product with the pixel-level T(sub b) threshold and (single) conditional rain rate determined locally for each month by the frequency of precipitation in the GPROF SSM/I product and by, the precipitation amount in the GPCP monthly satellite-gauge (SG) combination. Outside 40N-40S the 1DD uses a scaled TOVS precipitation estimate that has month-by-month adjustments based on the TMPI and the SG. Early validation results are encouraging. The 1DD shows relatively large scatter about the daily validation values in individual grid boxes, as expected for a technique that depends on cloud-sensing schemes such as the TMPI and TOVS. On the other hand, the time series of 1DD shows good correlation with validation in individual boxes. For example, the 1997-1998 time series of 1DD and Oklahoma Mesonet values in a grid box in northeastern Oklahoma have the correlation coefficient = 0.73. Looking more carefully at these two time series, the number of raining days for the 1DD is within 7% of the Mesonet value, while the distribution of daily rain values is very similar. Other tests indicate that area- or time-averaging improve the error characteristics, making the data set highly attractive to users interested in stream flow, short-term regional climatology, and model comparisons. The second generation of the 1DD product is currently under development; it is designed to directly incorporate TRMM and other high-quality precipitation estimates. These data are generally sparse because they are

  18. Long-term regimes of extreme precipitation and floods across the Alpine-Carpathian Range

    Science.gov (United States)

    Parajka, Juraj

    2010-05-01

    Kohnová, S.(2), Bálint, G. (8), Barbuc, M.(6), Borga, M.(5), Claps, P. (9), Cheval, S.(4), Gaume, E.(3), Hlavčová, K.(2), Merz, R.(1), Pfaundler, M. (7), Stancalie, G.(4), Szolgay, J.(2), Blöschl, G.(1) (2) Slovak University of Technology, Radlinského 11, 813 68 Bratislava, Slovakia, silvia. kohnova@stuba.sk (3) Laboratoire Central des Ponts et Chaussées, BP 4129, 44341 Bouguenais cedex, France (4) National Meteorological Administration 97, Soseaua Bucuresti-Ploiesti, 013686, Bucharest, Romania (5) Department of Land and Agroforest Environments, University of Padova, AGRIPOLIS,via dell'Università 16, Legnaro (PD), IT-35020, Italy (6) Dynamic and Experimental, Hydrology Department, P.C. 013686 P.B. 18, Sos. Bucuresti-Ploiesti 97, Bucharest, Romania (7)Sektion Gewässerbewirtschaftung Abt. Wasser BAFU, Papiermühlestrasse 172, CH-3063 Ittigen, Switzerland (8) VITUKI Environmental Protection and Water Management Institute, Kvassay út 1., H-1095 Budapest, Hungary (9) Dipartimento di Idraulica, Trasporti e Infrastrutture Civili (DITIC), Politecnico di Torino, C.so Duca degli Abruzzi 24, 10129 Torino (Italy) The study of the seasonality of extreme precipitation and floods has recently attracted renewed interest, especially in connection with water resources management, flood and low flow regionalization, and land cover and climate change assessment studies. The aim of this contribution is to present the differences in the long-term regimes of extreme precipitation and floods across the Alpine-Carpathian range. This analysis is based on seasonality indices and a catalogue of atmospheric circulation patterns. The main investigation will focus on the understanding of main flood producing processes and on the identification of regions with similar precipitation forcing and catchment response. The study region covers the South-Eastern part of France, Switzerland, the northern part of Italy, Austria, the southern part of Germany, Slovakia, Romania and a small region

  19. Improved confidence in climate change projections of precipitation evaluated using daily statistics from the PRUDENCE ensemble

    Energy Technology Data Exchange (ETDEWEB)

    Boberg, Fredrik; Berg, Peter; Thejll, Peter; Christensen, Jens H. [Danish Meteorological Institute, Danish Climate Centre, Copenhagen Oe (Denmark); Gutowski, William J. [Iowa State University, Department of Geological and Atmospheric Sciences, Ames, IA (United States)

    2009-06-15

    An ensemble of regional climate modelling simulations from the European framework project PRUDENCE are compared across European sub-regions with observed daily precipitation from the European Climate Assessment dataset by characterising precipitation in terms of probability density functions (PDFs). Models that robustly describe the observations for the control period (1961-1990) in given regions as well as across regions are identified, based on the overlap of normalised PDFs, and then validated, using a method based on bootstrapping with replacement. We also compare the difference between the scenario period (2071-2100) and the control period precipitation using all available models. By using a metric quantifying the deviation over the entire PDF, we find a clearly marked increase in the contribution to the total precipitation from the more intensive events and a clearly marked decrease for days with light precipitation in the scenario period. This change is tested to be robust and found in all models and in all sub-regions. We find a detectable increase that scales with increased warming, making the increase in the PDF difference a relative indicator of climate change level. Furthermore, the crossover point separating decreasing from increasing contributions to the normalised precipitation spectrum when climate changes does not show any significant change which is in accordance with expectations assuming a simple analytical fit to the precipitation spectrum. (orig.)

  20. Intercomparison of PERSIANN-CDR and TRMM-3B42V7 precipitation estimates at monthly and daily time scales

    Science.gov (United States)

    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

  1. 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.

  2. Relationship between extreme Precipitation and Temperature over Japan: An analysis from Multi-GCMs and Multi-RCMs products

    Science.gov (United States)

    Nayak, S.; Dairaku, K.; Takayabu, I.

    2014-12-01

    According to the IPCC reports, the concentration of CO­2 has been increasing and projected to be increased significantly in future (IPCC, 2012). This can have significant impacts on climate. For instance, Dairaku and Emori (2006) examined over south Asia by doubling CO2 and documented an increase in precipitation intensities during Indian summer monsoon. This would increase natural disasters such as floods, landslide, coastal disaster, erosion etc. Recent studies investigated whether the rate of increase of extreme precipitation is related with the rate expected by Clausius-Clapeyron (CC) relationship (approximately 7% per degree temperature rise). In our study, we examine whether this rate can increase or decrease in the future regional climate scenarios over Japan. We have analysed the ensemble experiments by three RCMs(NHRCM, NRAMS, WRF) forced by JRA25 as well as three GCMs (CCSM4, MIROC5, MRI-GCM3) for the current climate (1981-2000) and future scenario (2081-2100, RCP4.5) over Japan. We have stratified the extreme (99th, 95th, 90th, 75th percentile) precipitation of daily sum and daily maximum of hourly precipitation intensities of wet events based on daily mean temperature in bins of 1°C width for annual as well as for each season (DJF, MAM, JJA, SON). The results indicate that precipitation intensity increases when temperature increases roughly up to 22 °C and further increase of temperature decreases the precipitation intensities. The obtained results are consistent and match with the observation (APHRODITE dataset) over Japan. The decrease of precipitation at higher temperature mainly can be found in JJA. It is also noticed that the rate of specific humidity is estimated higher during JJA than other seasons. The rate of increase of extreme precipitation is similar to the rate expected by CC relation except DJF (nearly twice of CC relation) in current climate. This rate becomes to be significantly larger in future scenario for higher temperatures than

  3. Changes in precipitation extremes projected by a 20-km mesh global atmospheric model

    Directory of Open Access Journals (Sweden)

    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.

  4. Stochastic modelling of spatially and temporally consistent daily precipitation time-series over complex topography

    Science.gov (United States)

    Keller, D. E.; Fischer, A. M.; Frei, C.; Liniger, M. A.; Appenzeller, C.; Knutti, R.

    2014-07-01

    Many climate impact assessments over topographically complex terrain require high-resolution precipitation time-series that have a spatio-temporal correlation structure consistent with observations. This consistency is essential for spatially distributed modelling of processes with non-linear responses to precipitation input (e.g. soil water and river runoff modelling). In this regard, weather generators (WGs) designed and calibrated for multiple sites are an appealing technique to stochastically simulate time-series that approximate the observed temporal and spatial dependencies. In this study, we present a stochastic multi-site precipitation generator and validate it over the hydrological catchment Thur in the Swiss Alps. The model consists of several Richardson-type WGs that are run with correlated random number streams reflecting the observed correlation structure among all possible station pairs. A first-order two-state Markov process simulates intermittence of daily precipitation, while precipitation amounts are simulated from a mixture model of two exponential distributions. The model is calibrated separately for each month over the time-period 1961-2011. The WG is skilful at individual sites in representing the annual cycle of the precipitation statistics, such as mean wet day frequency and intensity as well as monthly precipitation sums. It reproduces realistically the multi-day statistics such as the frequencies of dry and wet spell lengths and precipitation sums over consecutive wet days. Substantial added value is demonstrated in simulating daily areal precipitation sums in comparison to multiple WGs that lack the spatial dependency in the stochastic process: the multi-site WG is capable to capture about 95% of the observed variability in daily area sums, while the summed time-series from multiple single-site WGs only explains about 13%. Limitation of the WG have been detected in reproducing observed variability from year to year, a component that has

  5. Joint probability analysis of extreme precipitation and storm tide in a coastal city under changing environment.

    Directory of Open Access Journals (Sweden)

    Kui Xu

    Full Text Available Catastrophic flooding resulting from extreme meteorological events has occurred more frequently and drawn great attention in recent years in China. In coastal areas, extreme precipitation and storm tide are both inducing factors of flooding and therefore their joint probability would be critical to determine the flooding risk. The impact of storm tide or changing environment on flooding is ignored or underestimated in the design of drainage systems of today in coastal areas in China. This paper investigates the joint probability of extreme precipitation and storm tide and its change using copula-based models in Fuzhou City. The change point at the year of 1984 detected by Mann-Kendall and Pettitt's tests divides the extreme precipitation series into two subsequences. For each subsequence the probability of the joint behavior of extreme precipitation and storm tide is estimated by the optimal copula. Results show that the joint probability has increased by more than 300% on average after 1984 (α = 0.05. The design joint return period (RP of extreme precipitation and storm tide is estimated to propose a design standard for future flooding preparedness. For a combination of extreme precipitation and storm tide, the design joint RP has become smaller than before. It implies that flooding would happen more often after 1984, which corresponds with the observation. The study would facilitate understanding the change of flood risk and proposing the adaption measures for coastal areas under a changing environment.

  6. Joint probability analysis of extreme precipitation and storm tide in a coastal city under changing environment.

    Science.gov (United States)

    Xu, Kui; Ma, Chao; Lian, Jijian; Bin, Lingling

    2014-01-01

    Catastrophic flooding resulting from extreme meteorological events has occurred more frequently and drawn great attention in recent years in China. In coastal areas, extreme precipitation and storm tide are both inducing factors of flooding and therefore their joint probability would be critical to determine the flooding risk. The impact of storm tide or changing environment on flooding is ignored or underestimated in the design of drainage systems of today in coastal areas in China. This paper investigates the joint probability of extreme precipitation and storm tide and its change using copula-based models in Fuzhou City. The change point at the year of 1984 detected by Mann-Kendall and Pettitt's tests divides the extreme precipitation series into two subsequences. For each subsequence the probability of the joint behavior of extreme precipitation and storm tide is estimated by the optimal copula. Results show that the joint probability has increased by more than 300% on average after 1984 (α = 0.05). The design joint return period (RP) of extreme precipitation and storm tide is estimated to propose a design standard for future flooding preparedness. For a combination of extreme precipitation and storm tide, the design joint RP has become smaller than before. It implies that flooding would happen more often after 1984, which corresponds with the observation. The study would facilitate understanding the change of flood risk and proposing the adaption measures for coastal areas under a changing environment.

  7. Recent trends in heavy precipitation extremes over Germany: A thorough intercomparison between different statistical approaches

    Science.gov (United States)

    Donner, Reik; Passow, Christian

    2016-04-01

    comparison with GEV and GP-based approaches, quantile regression approaches thus allow for more flexibility and make full use of all available observational values, no matter if extreme or not. Due to the latter fact, trends in extreme values can be more easily assessed based on shorter time series. However, the question under which conditions and to what extent regression and extreme value theory-based approaches provide consistent results has not yet been fully explored. In this study, we provide a thorough inter-comparison between the recent trends in extreme precipitation events (assessed in terms of daily precipitation sums) from a large set of German weather stations as revealed by the classical (monthly) block maxima method with linearly time-dependent GEV parameters and linear quantile regression of the full time series. For the study period from 1951 to 2006, our main findings are as follows: (1) The spatial patterns of quantile trends for various high (>90%) percentiles and trends in the location parameter of the GEV distribution are qualitatively consistent and exhibit significant correlations, which, however, clearly deviate from an ideal correspondence. (2) In comparison with the trend parameters, the intercepts of the respective linear models for the GEV location parameter and different quantiles exhibit considerably larger mutual correlation values. (3) Quantile regression indicates more stations with strongly positive trends in extreme precipitation than the block maxima method. Moreover, the significance statements provided by the GEV statistics are more conservative than those resulting from quantile regression. Significant upward trends are generally restricted to Southern and Western Germany and are almost completely absent in the Northeastern part of the country. (4) More complex GEV models including linear trends in both location and dispersion parameter need to be considered only for a small subset of all stations (202 out of 2342). In most cases

  8. Ferritic Alloys with Extreme Creep Resistance via Coherent Hierarchical Precipitates

    Science.gov (United States)

    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.

    2015-01-01

    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. PMID:26548303

  9. Regional trends in short-duration precipitation extremes: a flexible multivariate monotone quantile regression approach

    Science.gov (United States)

    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.

  10. Changes of temperature and precipitation extremes in China: past and future

    Science.gov (United States)

    Wen, Xin; Fang, Guohua; Qi, Heshuai; Zhou, Lei; Gao, Yuqin

    2016-10-01

    Historical temperature and precipitation extremes and their potential future changes are quantified and evaluated throughout the landmass of China. A statistical model of climate extremes based on generalized extreme value (GEV) distribution is applied to both historical climate data and bias correction and spatial disaggregation (BCSD) downscaled Coupled Model Inter-comparison Project phase 5 (CMIP5) projections. The results indicate relatively moderate historical warm extreme conditions in China with regional means of maximum temperature 28.9, 29.4, and 29.8 °C for 10-, 20-, and 50-year return periods, respectively, whereas the corresponding regional means of minimum temperature are -20.1, -20.8, and -21.5 °C, manifesting a downward trend northwardly with relative larger regional variations in cold extremes. The historical precipitation extremes also decline gradually from south-southeast toward northwest with significant regional differences. As for the future, the warm extremes are expected to aggravate by roughly 1.66-4.92 °C projected by CMIP5, indicating larger increasing rate and spatial differences compared to cold extremes. The extreme precipitation is projected to increase 7.9-13.4 %, the dry regions would see a larger increasing rate compared to wet regions. The increasing radiative forcing concentration would trigger upward variations in both temperature and precipitation extreme magnitudes. Also, the warm extreme changes are more sensitive to the radiative forcing concentration than the cold extremes. The CMIP5 projections basically maintain a favorable inter-model consistency in temperature and rainfall extreme simulation for the future, but the inter-model difference of warm extremes is larger than cold extremes.

  11. Improvement of Hydrological Simulations by Applying Daily Precipitation Interpolation Schemes in Meso-Scale Catchments

    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

  12. Uncertainty in projected point precipitation extremes for hydrological impact analysis of climate change

    Science.gov (United States)

    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

  13. Análisis estacional de la frecuencia diaria y la intensidad de los extremos de precipitación sobre el sudeste de Sudamérica Seasonal analysis of daily frequency and extreme intensity of precipitation in the Southeast of South America

    Directory of Open Access Journals (Sweden)

    Federico A. Robledo

    2007-12-01

    Full Text Available En este trabajo se profundiza en el conocimiento de la variabilidad espacial de la precipitación, estudiando la cantidad de días con precipitación y la intensidad media diaria (en milímetros por día, con énfasis en los extremos, definidos a partir de diferentes umbrales. La base de datos utilizada en este trabajo consta de 58 estaciones pluviométricas ubicadas al sudeste de Sudamérica, para la segunda mitad del siglo XX. De noviembre a marzo, dos áreas núcleos centradas en 68º O - 25º S y 45º O - 22º S, presentan más de 50% de días de precipitación por encima de 0,1 mm, mientras que para el resto de la región no se supera el 32%. El patrón de extremos de precipitación, por encima del percentil 75, no muestra grandes diferencias espaciales y estacionales con respecto a los del umbral 0,1mm. Sin embargo la intensidad media diaria de precipitación extrema se incrementa considerablemente con respecto al umbral 0,1mm. En el área núcleo centrada en 45º O - 22º S, la intensidad es de 36 mm/día en verano, y de 20 mm/día en invierno. Mientras que sobre el noroeste de Argentina, supera 38mm/día (8 mm/día en verano (invierno. En la provincia de Buenos Aires la intensidad media diaria extrema de precipitación es de 32mm/día (20mm/día en verano (invierno.In this paper the climatology of the different components that composed the monthly rainfall was actualized and extended. For this purpose, we calculated the frequency of daily rainfall and the mean daily intensity for the second half of the century. 58 stations were used for this study. In addition we calculated the climatology for the daily extreme rainfall and its intensity, defining different thresholds according to the regions. Between November and March, we observed two centers (65º W -25º S and 45º W - 22º S with more than 50% of days with daily rainfall above 0.1 millimeters (mm , and lower values in the rest of the region. Spatial patterns and seasonal variation

  14. Precipitation Intensity Trend Detection using Hourly and Daily Observations in Portland, Oregon

    Directory of Open Access Journals (Sweden)

    Alexis Cooley

    2017-02-01

    Full Text Available The intensity of precipitation is expected to increase in response to climate change, but the regions where this may occur are unclear. The lack of certainty from climate models warrants an examination of trends in observational records. However, the temporal resolution of records may affect the success of trend detection. Daily observations are often used, but may be too coarse to detect changes. Sub-daily records may improve detection, but their value is not yet quantified. Using daily and hourly records from 24 rain gages in Portland, Oregon (OR, trends in precipitation intensity and volume are examined for the period of 1999–2015. Daily intensity is measured using the Simple Daily Intensity Index, and this method is adapted to measure hourly scale intensity. Kendall’s tau, a non-parametric correlation coefficient, is used for monotonic trend detection. Field significance and tests for spatial autocorrelation using Moran’s Index are used to determine the significance of group hypothesis tests. Results indicate that the hourly data is superior in trend detection when compared with daily data; more trends are detected with hourly scale data at both the 5% and 10% significance levels. Hourly records showed a significant increase in 6 of 12 months, while daily records showed a significant increase in 4 of 12 months at the 10% significance level. At both scales increasing trends were concentrated in spring and summer months, while no winter trends were detected. Volume was shown to be increasing in most months experiencing increased intensity, and is a probable driver of the intensity trends observed.

  15. Combining meteorological and geomorphological expertise to provide better evidences of changes in rainfall precipitation extremes

    Science.gov (United States)

    Grazzini, Federico; Segadelli, Stefano; Chelli, Alessandro

    2017-04-01

    Three extreme intensity precipitation events have been stricken the hilly and mountainous territory of Emilia-Romagna Region (Italy) in the last 4 years. Major effects on the ground were observed: i.e. debris flows, shallow landslides, flash floods and overbank flooding. Some of them (like debris flow) are considered unusual, on such large scale, for this region. Though a detailed meteorological and geomorphological analyses of the last and most devastating event, occurred in Val Trebbia and Nure in September 2015, we show the value of this multidisciplinary analysis conducted in collaboration between the HydroMeteorological service of Emilia-Romagna (ARPAE-SIMC) and the Geological, Sismic and Soil service of the same region (SGSS) and Parma University. A large and stationary mesoscale convective system released more than 300 mm of rain, roughly, in 6 hours. During the first part of the storm, several rain gauges recorded rainfall peaks over 100 mm/hr. The storm caused more than 100 debris flows that were the main cause of damage on man-made structures. A robust quantitative relation between precipitation intensity (estimated trough a combination of radar data and rain gouges) and comprehensive mapping of airborne and satellite imageries acquired by the Emergency Management Service (Copernicus), complemented by fieldwork of geologists, could be built from this event. This accurate analysis, in a particularly rich data area, set an important reference point to search past events of similar amplitude, beyond the short chronological history of observation records of sub-daily precipitation intensity. We will describe in fact how we plan to gain further insights investigating in situ geological records to find analogous high intensity rain effects.

  16. Evaluation of daily precipitation indices over North America in multiple datasets

    Science.gov (United States)

    Diaconescu, Emilia Paula; Gachon, Philippe; Scinocca, John; Laprise, René

    2015-04-01

    The study presents a regional analysis and evaluation of simulations from two Canadian regional climate models (RCMs), CanRCM4 and CRCM5 developed respectively at EC-CCCma and UQAM/ESCER, participating in the CORDEX-North America experiment. The focus is on the models' skill in simulating daily precipitation indices with respect to several sets of gridded observations. The Canadian RCMs are also compared against four reanalyses and six other RCMs that take part to the NARCCAP program. The different configurations of Canadian RCM simulations allow also to evaluate the respective effects of different spatial resolutions, driving fields and nudging procedures on the simulated fields. Results show that, for the winter season, the 0.44 degree CanRCM4 and CRCM5 reproduce quite accurately the cumulative total amount of precipitation, as well as the occurrence of wet days and the 90th, 95th and 99th percentiles of daily precipitation. The increase in resolution is associated with an increase in precipitation of high intensity, while the use of interior spectral nudging or different driving fields influences the dry spells' occurrence, especially over Mexico and central US.

  17. Projections of global changes in precipitation extremes from Coupled Model Intercomparison Project Phase 5 models

    NARCIS (Netherlands)

    Toreti, A.; Naveau, P.; Zampieri, M.; Schindler, A.; Scoccimarro, E.; Xoplaki, E.; Dijkstra, H.A.|info:eu-repo/dai/nl/073504467; Gualdi, S.; Luterbacher, J.

    2013-01-01

    Precipitation extremes are expected to increase in a warming climate; thus, it is essential to characterize their potential future changes. Here we evaluate eight high-resolution global climate model simulations in the twentieth century and provide new evidence on projected global precipitation

  18. Projections of global changes in precipitation extremes from Coupled Model Intercomparison Project Phase 5 models

    NARCIS (Netherlands)

    Toreti, A.; Naveau, P.; Zampieri, M.; Schindler, A.; Scoccimarro, E.; Xoplaki, E.; Dijkstra, H.A.; Gualdi, S.; Luterbacher, J.

    2013-01-01

    Precipitation extremes are expected to increase in a warming climate; thus, it is essential to characterize their potential future changes. Here we evaluate eight high-resolution global climate model simulations in the twentieth century and provide new evidence on projected global precipitation extr

  19. Systematic investigation of gridding-related scaling effects on annual statistics of daily temperature and precipitation maxima: A case study for south-east Australia

    Directory of Open Access Journals (Sweden)

    Francia B. Avila

    2015-09-01

    Full Text Available 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 resolutions ranging from 0.25° to 2.5°. In each case the order of operation in which the grid values of the hottest and wettest day are calculated is varied: either they are estimated from daily grids or from station points and then gridded. We find that the grid resolution-despite showing more regional detail at high resolution – has relatively limited effect when considering regional averages. However, the interpolation method and the order of operation can substantially influence the actual gridded values. And while the difference due to the order of operation is not substantial when using natural neighbor and cubic spline interpolation, it is particularly apparent for indices calculated from daily gridded estimates using the angular distance weighting method. As expected given the high spatial variability of precipitation fields, precipitation extremes are most sensitive to method, but temperature extremes also exhibit substantial differences. For the annual maximum values averaged over the study area, the differences may be up to 2.8 °C for temperature and 60 mm (about a factor 2 for precipitation. Differences are seen most prominently in return period estimates where a 1 in 100 year return value calculated using the angular distance weighting daily gridded method is equivalent to about a 1 in 5 year return value in most of the other methods. Despite substantial differences in the actual values of gridded extremes, analyses suggest that the

  20. Technical Note: Bias correcting climate model simulated daily temperature extremes with quantile mapping

    Directory of Open Access Journals (Sweden)

    B. Thrasher

    2012-09-01

    Full Text Available When applying a quantile mapping-based bias correction to daily temperature extremes simulated by a global climate model (GCM, the transformed values of maximum and minimum temperatures are changed, and the diurnal temperature range (DTR can become physically unrealistic. While causes are not thoroughly explored, there is a strong relationship between GCM biases in snow albedo feedback during snowmelt and bias correction resulting in unrealistic DTR values. We propose a technique to bias correct DTR, based on comparing observations and GCM historic simulations, and combine that with either bias correcting daily maximum temperatures and calculating daily minimum temperatures or vice versa. By basing the bias correction on a base period of 1961–1980 and validating it during a test period of 1981–1999, we show that bias correcting DTR and maximum daily temperature can produce more accurate estimations of daily temperature extremes while avoiding the pathological cases of unrealistic DTR values.

  1. Have precipitation extremes and annual totals been increasing in the world's dry regions over the last 60 years?

    Science.gov (United States)

    Sippel, Sebastian; Zscheischler, Jakob; Heimann, Martin; Lange, Holger; Mahecha, Miguel D.; van Oldenborgh, Geert Jan; Otto, Friederike E. L.; Reichstein, Markus

    2017-01-01

    Daily precipitation extremes and annual totals have increased in large parts of the global land area over the past decades. These observations are consistent with theoretical considerations of a warming climate. However, until recently these trends have not been shown to consistently affect dry regions over land. A recent study, published by Donat et al. (2016), now identified significant increases in annual-maximum daily extreme precipitation (Rx1d) and annual precipitation totals (PRCPTOT) in dry regions. Here, we revisit the applied methods and explore the sensitivity of changes in precipitation extremes and annual totals to alternative choices of defining a dry region (i.e. in terms of aridity as opposed to precipitation characteristics alone). We find that (a) statistical artifacts introduced by data pre-processing based on a time-invariant reference period lead to an overestimation of the reported trends by up to 40 %, and that (b) the reported trends of globally aggregated extremes and annual totals are highly sensitive to the definition of a dry region of the globe. For example, using the same observational dataset, accounting for the statistical artifacts, and based on different aridity-based dryness definitions, we find a reduction in the positive trend of Rx1d from the originally reported +1.6 % decade-1 to +0.2 to +0.9 % decade-1 (period changes for 1981-2010 averages relative to 1951-1980 are reduced to -1.32 to +0.97 % as opposed to +4.85 % in the original study). If we include additional but less homogenized data to cover larger regions, the global trend increases slightly (Rx1d: +0.4 to +1.1 % decade-1), and in this case we can indeed confirm (partly) significant increases in Rx1d. However, these globally aggregated estimates remain uncertain as considerable gaps in long-term observations in the Earth's arid and semi-arid regions remain. In summary, adequate data pre-processing and accounting for uncertainties regarding the definition of dryness are

  2. Scaling of precipitation extremes with temperature in the French Mediterranean region: What explains the hook shape?

    Science.gov (United States)

    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.

  3. Scaling precipitation extremes with temperature in the Mediterranean: past climate assessment and projection in anthropogenic scenarios

    Science.gov (United States)

    Drobinski, Philippe; Silva, Nicolas Da; Panthou, Gérémy; Bastin, Sophie; Muller, Caroline; Ahrens, Bodo; Borga, Marco; Conte, Dario; Fosser, Giorgia; Giorgi, Filippo; Güttler, Ivan; Kotroni, Vassiliki; Li, Laurent; Morin, Efrat; Önol, Bariş; Quintana-Segui, Pere; Romera, Raquel; Torma, Csaba Zsolt

    2016-03-01

    In this study we investigate the scaling of precipitation extremes with temperature in the Mediterranean region by assessing against observations the present day and future regional climate simulations performed in the frame of the HyMeX and MED-CORDEX programs. Over the 1979-2008 period, despite differences in quantitative precipitation simulation across the various models, the change in precipitation extremes with respect to temperature is robust and consistent. The spatial variability of the temperature-precipitation extremes relationship displays a hook shape across the Mediterranean, with negative slope at high temperatures and a slope following Clausius-Clapeyron (CC)-scaling at low temperatures. The temperature at which the slope of the temperature-precipitation extreme relation sharply changes (or temperature break), ranges from about 20 °C in the western Mediterranean to relationship is close to CC-scaling at temperatures below the temperature break, while at high temperatures, the negative slope is close, but somewhat flatter or steeper, than in the current climate depending on the model. Overall, models predict more intense precipitation extremes in the future. Adjusting the temperature-precipitation extremes relationship in the present climate using the CC law and the temperature shift in the future allows the recovery of the temperature-precipitation extremes relationship in the future climate. This implies negligible regional changes of relative humidity in the future despite the large warming and drying over the Mediterranean. This suggests that the Mediterranean Sea is the primary source of moisture which counteracts the drying and warming impacts on relative humidity in parts of the Mediterranean region.

  4. Climatology of Vb-cyclones, physical mechanisms and their impact on extreme precipitation over Central Europe

    Directory of Open Access Journals (Sweden)

    M. Messmer

    2015-05-01

    Full Text Available Cyclones, which develop over the western Mediterranean and move northeastward are a major source of extreme weather and known to be responsible for heavy precipitation over Central Europe and the Alps. As the relevant processes triggering these so-called Vb-events and their impact on extreme precipitation are not yet fully understood, this study focusses on gaining insight into the dynamics of past events. For this, a cyclone detection and tracking tool is applied to the ERA-Interim reanalysis (1979–2013 to identify prominent Vb-situations. Precipitation in the ERA-Interim and the E-OBS datasets is used to evaluate case-to-case precipitation amounts and to assess consistency between the two datasets. Both datasets exhibit high variability in precipitation amounts among different Vb-events. While only 23 % of all Vb-events are associated with extreme precipitation, around 15 % of all extreme precipitation days (99 percentile over the Alpine region are induced by Vb-events, although Vb-cyclones are rare events (2.3 per year. To obtain a better understanding of the variability within Vb-events, the analysis of the 10 heaviest and lowest precipitation Vb-events reveals noticeable differences in the state of the atmosphere. These differences are most pronounced in the geopotential height and potential vorticity field, indicating a much stronger cyclone for heavy precipitation events. The related differences in wind direction are responsible for the moisture transport around the Alps and the orographical lifting along the Alps. These effects are the main reasons for a disastrous outcome of Vb-events, and consequently are absent in the Vb-events associated with low precipitation. Hence, our results point out that heavy precipitation related to Vb-events is mainly related to large-scale dynamics rather than to thermodynamic processes.

  5. Variability and long-term change in Australian temperature and precipitation extremes

    Directory of Open Access Journals (Sweden)

    Dörte Jakob

    2016-12-01

    We conclude that in assessing the likelihood of climate hazards, one needs to consider the modulation of climate extremes due to both long-term change and climate variability. Our findings imply that when planning for adaptation, different emphasis needs to be given to changing temperature and precipitation extremes.

  6. Estimation of regional intensity-duration-frequency curves for extreme precipitation

    DEFF Research Database (Denmark)

    Madsen, Henrik; Mikkelsen, Peter Steen; Rosbjerg, Dan;

    1998-01-01

    Regional estimation of extreme precipitation from a high resolution rain gauge network in Denmark is considered. The applied extreme value model is based on the partial duration series (PDS) approach in which all events above a certain threshold level are modelled. For a preliminary assessment...

  7. Evaluation of interpolating methods for daily precipitation at various station densities

    Science.gov (United States)

    Li, H.; Xu, C.-Y.; Chen, H.; Zhang, Z. X.; Xu, H. L.

    2012-04-01

    Spatial continuous data play a significant role in planning, risk assessment and decision making in climate research and geosciences. It is essential to get accurate grid precipitation data of high resolution in hydrological modeling and water resources management. In recent years, radar and satellite provide an alternative way for spatial precipitation data, but due to technique problems and deficient accuracy, interpolating the observed point data is still the common way to obtain gridding precipitation data for research and management purposes. Many interpolating methods have been proposed and great effort has been made to evaluate and compare them. But by far, no universal method is widely accepted because of the diversity in study regions, difference in climate situations, and differences in data quality and quantity, and selected methods in comparisons. It has been well known that the most paramount factor affecting the performance of interpolating methods is the density of sampling points. However, the performance of different interpolating methods at various sampling densities, which means the performance degradation caused by density changes, has not been deeply examined. This work focuses on the evaluation of interpolating methods in daily precipitation at various station densities and tries to provide guidance on choosing interpolating method under different circumstance. To fill this objective, we choose five commonly used or recommended interpolation methods, i.e. nearest neighbor (NN), inverse distance weighting (IDW), Gradient plus Inverse Distance Squared (GIDS), ordinary kriging (OK) and simple kriging (SK) at five designed sampling densities ranging from 22.6 to 9.8 stations per ten thousand square kilometers at Xiangjiang River basin during 2000 to 2005 when the precipitation data were in the highest density. Four criteria were used for method assessment, i.e., mean error (ME), root mean absolute error (RMSE), model efficient (EF) and index of

  8. Generalized Extreme Value's shape parameter and its nature for extreme precipitation using long time series and Bayesian approach

    Science.gov (United States)

    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.

  9. Daily temperature extremes play an important role in predicting thermal effects.

    Science.gov (United States)

    Ma, Gang; Hoffmann, Ary A; Ma, Chun-Sen

    2015-07-01

    Organisms in natural environments experience diel temperature fluctuations, including sporadic extreme conditions, rather than constant temperatures. Studies based mainly on model organisms have tended to focus on responses to average temperatures or short-term heat stress, which overlooks the potential impact of daily fluctuations, including stressful daytime periods and milder night-time periods. Here, we focus on daily maximum temperatures, while holding night-time temperatures constant, to specifically investigate the effects of high temperature on demographic parameters and fitness in the English grain aphid Sitobion avenae. We then compared the observed effects of different daily maximum temperatures with predictions from constant temperature-performance expectations. Moderate daily maximum temperatures depressed aphid performance while extreme conditions had dramatic effects, even when mean temperatures were below the critical maximum. Predictions based on daily average temperature underestimated negative effects of temperature on performance by ignoring daily maximum temperature, while predictions based on daytime maximum temperatures overestimated detrimental impacts by ignoring recovery under mild night-time temperatures. Our findings suggest that daily maximum temperature will play an important role in regulating natural population dynamics and should be considered in predictions. These findings have implications for natural population dynamics, particularly when considering the expected increase in extreme temperature events under climate change.

  10. Stochastic Modeling based on Dictionary Approach for the Generation of Daily Precipitation Occurrences

    Science.gov (United States)

    Panu, U. S.; Ng, W.; Rasmussen, P. F.

    2009-12-01

    The modeling of weather states (i.e., precipitation occurrences) is critical when the historical data are not long enough for the desired analysis. Stochastic models (e.g., Markov Chain and Alternating Renewal Process (ARP)) of the precipitation occurrence processes generally assume the existence of short-term temporal-dependency between the neighboring states while implying the existence of long-term independency (randomness) of states in precipitation records. Existing temporal-dependent models for the generation of precipitation occurrences are restricted either by the fixed-length memory (e.g., the order of a Markov chain model), or by the reining states in segments (e.g., persistency of homogenous states within dry/wet-spell lengths of an ARP). The modeling of variable segment lengths and states could be an arduous task and a flexible modeling approach is required for the preservation of various segmented patterns of precipitation data series. An innovative Dictionary approach has been developed in the field of genome pattern recognition for the identification of frequently occurring genome segments in DNA sequences. The genome segments delineate the biologically meaningful ``words" (i.e., segments with a specific patterns in a series of discrete states) that can be jointly modeled with variable lengths and states. A meaningful “word”, in hydrology, can be referred to a segment of precipitation occurrence comprising of wet or dry states. Such flexibility would provide a unique advantage over the traditional stochastic models for the generation of precipitation occurrences. Three stochastic models, namely, the alternating renewal process using Geometric distribution, the second-order Markov chain model, and the Dictionary approach have been assessed to evaluate their efficacy for the generation of daily precipitation sequences. Comparisons involved three guiding principles namely (i) the ability of models to preserve the short-term temporal-dependency in

  11. Contemporary changes in precipitation extremes in Poland in comparison to changes in other parts of Baltic Sea Basin

    Science.gov (United States)

    Wibig, Joanna; Jędruszkiewicz, Joanna

    2015-04-01

    The aim of the paper is detection and attribution of changes in precipitation extremes in Poland on the ground of similar changes in the rest of Baltic Sea Basin. The indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) are computed for a number of stations from Poland and surrounding countries. Among them are: Monthly maximum 1-day precipitation (Rx1day), monthly maximum consecutive 5-day precipitation (Rx5day), pricipitation intensity index(RRw,) annual number of days with daily precipitation ≥ 10mm and ≥ 20mm (R10mm and R20mm), maximum length of dry spell (CDD), maximum length of wet spell (CWD), annual total from days when daily total is equal at least 95 percentile and 99 percentile calculated in reference period 1961-1990 from daily totals equal at leat 1 mm (R95pTOT and R99pTOT). The daily precipitation records from more than hundred stations from the period 1951-2012 were used. The changes in annual values and their variability are analysed. The regions of similar changes are distinguished both for Poland and for the whole Baltic Sea Region. In the second part of the paper the attribution of large scale mechanisms causing detected changes is planned. The set of possible large scale predictors is prepared. Among them are indices of atmospheric and oceanic circulation in the European-North Atlantic Region: the North Atlantic Oscillation index, The Scandinavian index, the East Atlantic index, and the Atlantic Multiannual Oscillation. Additionally the large scale fields of sea level pressure and humidity and temperature from low troposphere are used. The records of indices were taken from NCDC (http://www.cpc.ncep.noaa.gov/data/teledoc). The large scale fields data were taken from NCAR/NCEP Reanalysis. Among the methodologies used to detect the mechanisms of precipitation extreme changes are: correlation analysis, composites and Canonical Correlation Analysis. The work is supported by grant 2012/05/B/ST10/00945 founded by

  12. Large-scale drivers of local precipitation extremes in convection-permitting climate simulations

    Science.gov (United States)

    Chan, Steven C.; Kendon, Elizabeth J.; Roberts, Nigel M.; Fowler, Hayley J.; Blenkinsop, Stephen

    2016-04-01

    The Met Office 1.5-km UKV convective-permitting models (CPM) is used to downscale present-climate and RCP8.5 60-km HadGEM3 GCM simulations. Extreme UK hourly precipitation intensities increase with local near-surface temperatures and humidity; for temperature, the simulated increase rate for the present-climate simulation is about 6.5% K**-1, which is consistent with observations and theoretical expectations. While extreme intensities are higher in the RCP8.5 simulation as higher temperatures are sampled, there is a decline at the highest temperatures due to circulation and relative humidity changes. Extending the analysis to the broader synoptic scale, it is found that circulation patterns, as diagnosed by MSLP or circulation type, play an increased role in the probability of extreme precipitation in the RCP8.5 simulation. Nevertheless for both CPM simulations, vertical instability is the principal driver for extreme precipitation.

  13. Robust inferences on climate change patterns of precipitation extremes in the Iberian Peninsula

    Science.gov (United States)

    de Melo-Gonçalves, Paulo; Rocha, Alfredo; Santos, João A.

    2016-08-01

    This work presents a methodology to make statistical significant and robust inferences on climate change from an ensemble of model simulations. This methodology is used to assess climate change projections of the Iberian daily-total precipitation for a near-future (2021-2050) and a distant-future (2069-2098) climates, relatively to a reference past climate (1961-1990). Climate changes of precipitation spatial patterns are estimated for annual and seasonal values of: (i) total amount of precipitation (PRCTOT), (ii) maximum number of consecutive dry days (CDD), (iii) maximum of total amount of 5-consecutive wet days (Rx5day), and (iv) percentage of total precipitation occurred in days with precipitation above the 95th percentile of the reference climate (R95T). Daily-total data were obtained from the multi-model ensemble of fifteen Regional Climate Model simulations provided by the European project ENSEMBLES. These regional models were driven by boundary conditions imposed by Global Climate Models that ran under the 20C3M conditions from 1961 to 2000, and under the A1B scenario, from 2001 to 2100, defined by the Special Report on Emission Scenarios of the Intergovernmental Panel on Climate Change. Non-parametric statistical methods are used for significant climate change detection: linear trends for the entire period (1961-2098) estimated by the Theil-Sen method with a statistical significance given by the Mann-Kendall test, and climate-median differences between the two future climates and the past climate with a statistical significance given by the Mann-Whitney test. Significant inferences of climate change spatial patterns are made after these non-parametric statistics of the multi-model ensemble median, while the associated uncertainties are quantified by the spread of these statistics across the multi-model ensemble. Significant and robust climate change inferences of the spatial patterns are then obtained by building the climate change patterns using only the

  14. A Comparison of Four Precipitation Distribution Models Used in Daily Stochastic Models

    Institute of Scientific and Technical Information of China (English)

    LIU Yonghe; ZHANG Wanchang; SHAO Yuehong; ZHANG Kexin

    2011-01-01

    Stochastic weather generators are statistical models that produce random numbers that resemble the observed weather data on which they have been fitted; thev are widely used in meteorological and hydrological simulations. For modeling daily precipitation in weather generators, first-order Markov chain-dependent exponential, gamma, mixed-exponential, and lognormal distributions can be used. To examine the performance of these four distributions for precipitation simulation, they were fitted to observed data collected at 10 stations in the watershed of Yishu River. The parameters of these models were estimated using a maximum-likelihood technique performed using genetic algorithms. Parameters for each calendar month and the Fourier series describing parameters for the whole year were estimated separately. Bayesian information criterion, simulated monthly mean, maximum daily value, and variance were tested and compared to evaluate the fitness and performance of these models. The results indicate that the lognormal and mixed-exponential distributions give smaller BICs, but their stochastic simulations have overestimation and underestimation respectively, while the gamma and exponential distributions give larger BICs, but their stochastic simulations produced monthly mean precipitation very well. When these distributions were fitted using Fourier series, they all underestimated the above statistics for the months of June, July and August.

  15. Statistical downscaling of daily precipitation over Llobregat river basin in Catalonia (Spain) using three downscaling methods.

    Science.gov (United States)

    Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

    2009-09-01

    Any long-term change in the patterns of average weather in a global or regional scale is called climate change. It may cause a progressive increase of atmospheric temperature and consequently may change the amount, frequency and intensity of precipitation. All these changes of meteorological parameters may modify the water cycle: run-off, infiltration, aquifer recharge, etc. Recent studies in Catalonia foresee changes in hydrological systems caused by climate change. This will lead to alterations in the hydrological cycle that could impact in land use, in the regimen of water extractions, in the hydrological characteristics of the territory and reduced groundwater recharge. Besides, can expect a loss of flow in rivers. In addition to possible increases in the frequency of extreme rainfall, being necessary to modify the design of infrastructure. Because this, it work focuses on studying the impacts of climate change in one of the most important basins in Catalonia, the Llobregat River Basin. The basin is the hub of the province of Barcelona. It is a highly populated and urbanized catchment, where water resources are used for different purposes, as drinking water production, agricultural irrigation, industry and hydro-electrical energy production. In consequence, many companies and communities depend on these resources. To study the impact of climate change in the Llobregat basin, storms (frequency, intensity) mainly, we will need regional climate change information. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and

  16. Rain Characteristics and Large-Scale Environments of Precipitation Objects with Extreme Rain Volumes from TRMM Observations

    Science.gov (United States)

    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.

  17. Assessment of RegCM4 simulated inter-annual variability and daily-scale statistics of temperature and precipitation over Mexico

    Science.gov (United States)

    Fuentes-Franco, Ramón; Coppola, Erika; Giorgi, Filippo; Graef, Federico; Pavia, Edgar G.

    2014-02-01

    The skill of a regional climate model (RegCM4) in capturing the mean patterns, interannual variability and extreme statistics of daily-scale temperature and precipitation events over Mexico is assessed through a comparison of observations and a 27-year long simulation driven by reanalyses of observations covering the Central America CORDEX domain. The analysis also includes the simulation of tropical cyclones. It is found that RegCM4 reproduces adequately the mean spatial patterns of seasonal precipitation and temperature, along with the associated interannual variability characteristics. The main model bias is an overestimation of precipitation in mountainous regions. The 5 and 95 percentiles of daily temperature, as well as the maximum dry spell length are realistically simulated. The simulated distribution of precipitation events as well as the 95 percentile of precipitation shows a wet bias in topographically complex regions. Based on a simple detection method, the model produces realistic tropical cyclone distributions even at its relatively coarse resolution (dx = 50 km), although the number of cyclone days is underestimated over the Pacific and somewhat overestimated over the Atlantic and Caribbean basins. Overall, it is assessed that the performance of RegCM4 over Mexico is of sufficient quality to study not only mean precipitation and temperature patterns, but also higher order climate statistics.

  18. The role of land use change in the recent warming of daily extreme temperatures

    Science.gov (United States)

    Christidis, Nikolaos; Stott, Peter A.; Hegerl, Gabriele C.; Betts, Richard A.

    2013-02-01

    Abstract Understanding how temperature extremes respond in a climate forced by human activity is of great importance, as extreme temperatures are detrimental to health and often responsible for mortality increases. While previous detection and attribution studies demonstrated a significant human influence on the recent warming of daily extremes, contributions of individual anthropogenic forcings like changes in land use have not yet been investigated in such studies. Here we apply an optimal fingerprinting technique to data from observations and experiments with a new earth system model to examine whether changing land use has led to detectable changes in daily extreme temperatures on a quasi-global scale. We find that loss of trees and increase of grassland since preindustrial times has caused an overall cooling trend in both mean and extreme temperatures which is detectable in the observed changes of warm but not cold extremes. The warming in both mean and extreme temperatures due to anthropogenic forcings other than land use is detected in all cases, whereas the weaker effect of natural climatic forcings is not detected in any. This is the first formal attribution of observed climatic changes to changing land use, suggesting further investigations are justified, particularly in studies of warm extremes.

  19. Detecting Climate Signals in Precipitation Extremes from TRMM (1998-2013) - Increasing Contrast Between Wet and Dry Extremes During the "Global Warming Hiatus"

    Science.gov (United States)

    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.

  20. Detecting climate signals in precipitation extremes from TRMM (1998-2013)—Increasing contrast between wet and dry extremes during the "global warming hiatus"

    Science.gov (United States)

    Wu, Huey-Tzu Jenny; Lau, William K.-M.

    2016-02-01

    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.

  1. 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.

  2. The changes in the frequency of daily precipitation in Urmia Lake basin, Iran

    Science.gov (United States)

    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.

  3. Predictions of extreme precipitation and sea-level rise under climate change.

    Science.gov (United States)

    Senior, C A; Jones, R G; Lowe, J A; Durman, C F; Hudson, D

    2002-07-15

    Two aspects of global climate change are particularly relevant to river and coastal flooding: changes in extreme precipitation and changes in sea level. In this paper we summarize the relevant findings of the IPCC Third Assessment Report and illustrate some of the common results found by the current generation of coupled atmosphere-ocean general circulation models (AOGCMs), using the Hadley Centre models. Projections of changes in extreme precipitation, sea-level rise and storm surges affecting the UK will be shown from the Hadley Centre regional models and the Proudman Oceanographic Laboratory storm-surge model. A common finding from AOGCMs is that in a warmer climate the intensity of precipitation will increase due to a more intense hydrological cycle. This leads to reduced return periods (i.e. more frequent occurrences) of extreme precipitation in many locations. The Hadley Centre regional model simulates reduced return periods of extreme precipitation in a number of flood-sensitive areas of the UK. In addition, simulated changes in storminess and a rise in average sea level around the UK lead to reduced return periods of extreme high coastal water events. The confidence in all these results is limited by poor spatial resolution in global coupled models and by uncertainties in the physical processes in both global and regional models, and is specific to the climate change scenario used.

  4. Rivers as archives of paleo-precipitation patterns and extreme precipitation

    Science.gov (United States)

    Plink-Bjorklund, Piret

    2016-04-01

    Fluvial systems commonly experience hysteresis and complex signal buffering effects that complicate tracking of allogenic forcing factors and autogenic processes. This paper presents a study of 52 modern and ancient fluvial datasets where river dynamics are dominated by highly seasonal precipitation pattern, such as in monsoonal domain and the bordering subtropical arid to sub-humid climate zones. Rivers that receive significant amounts of their surface water supply from monsoon precipitation characteristically experience seasonal floods, and display seasonally highly variable discharge, controlled by the monsoon trough passage and its related cyclones. The intense summer rainfall causes high-magnitude floods, whereas rivers only transmit a low base flow during the dry winters. Also for many rivers in the sub-humid to arid subtropics, bordering the monsoon domain, the monsoon rain is the main source of surface water recharge. However, such rivers may receive monsoon rain and transmit discharge only during abnormal or strengthened monsoon seasons. This annual discharge variability or range, as compared to the mean annual discharge, distinguishes the monsoonal and subtropical rivers from the rivers in equatorial tropics and temperate perennial precipitation zones, where the annual range is relatively small compared to the annual mean discharge. The positive deviation is clearly demonstrated by comparing the Q90 values to the mean discharge values, indicating flood discharge or magnitude values of >200-400% as compared to the annual mean discharge. Moreover, Q50 values of rivers that receive their surface water supply from monsoon precipitation are less than 10% of the annual mean discharge in some such rivers, and range from 20-50% in most. In comparison, in perennial precipitation zone rivers the Q90 values are within110-160% as compared to the annual mean, and the Q50 values are very close to the annual mean discharge, within 90-98%. Even Q30 values for the

  5. Multivariate Regression Analysis and Statistical Modeling for Summer Extreme Precipitation over the Yangtze River Basin, China

    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.

  6. Review of trend analysis and climate change projections of extreme precipitation and floods in Europe

    Science.gov (United States)

    Madsen, H.; Lawrence, D.; Lang, M.; Martinkova, M.; Kjeldsen, T. R.

    2014-11-01

    This paper presents a review of trend analysis of extreme precipitation and hydrological floods in Europe based on observations and future climate projections. The review summaries methods and methodologies applied and key findings from a large number of studies. Reported analyses of observed extreme precipitation and flood records show that there is some evidence of a general increase in extreme precipitation, whereas there are no clear indications of significant trends at large-scale regional or national level of extreme streamflow. Several studies from regions dominated by snowmelt-induced peak flows report decreases in extreme streamflow and earlier spring snowmelt peak flows, likely caused by increasing temperature. The review of likely future changes based on climate projections indicates a general increase in extreme precipitation under a future climate, which is consistent with the observed trends. Hydrological projections of peak flows show large impacts in many areas with both positive and negative changes. A general decrease in flood magnitude and earlier spring floods are projected for catchments with snowmelt-dominated peak flows, which is consistent with the observed trends. Finally, existing guidelines in Europe on design flood and design rainfall estimation are reviewed. The review shows that only few countries have developed guidelines that incorporate a consideration of climate change impacts.

  7. Low-pressure systems and extreme precipitation in central India: sensitivity to temperature changes

    Science.gov (United States)

    Sørland, Silje Lund; Sorteberg, Asgeir

    2016-07-01

    Extreme rainfall events in the central Indian region are often related to the passage of synoptic scale monsoon low-pressure systems (LPS). This study uses the surrogate climate change method on ten monsoon LPS cases connected to observed extreme rainfall events, to investigate how sensitive the precipitation and runoff are to an idealized warmer and moister atmosphere. The ten cases are simulated with three different initial and lateral boundary conditions: the unperturbed control run, and two sets of perturbed runs where the atmospheric temperature is increased uniformly throughout the atmosphere, the specific humidity increased according to Clausius Clapeyron's relation, but the large-scale flow is unchanged. The difference between the control and perturbed simulations are mainly due to the imposed warming and feedback influencing the synoptic flow. The mean precipitation change with warming in the central Indian region is 18-20 %/K, with largest changes at the end of the LPS tracks. The LPS in the warmer runs are bringing more moisture further inland that is released as precipitation. In the perturbed runs the precipitation rate is increasing at all percentiles, and there is more frequent rainfall with very heavy intensities. This leads to a shift in which category that contributes most to the total precipitation: more of the precipitation is coming from the category with very heavy intensities. The runoff changes are similar to the precipitation changes, except the response in intensity of very heavy runoff, which is around twice the change in intensity of very heavy precipitation.

  8. Growing season temperature and precipitation variability and extremes in the U.S. Corn Belt from 1981 to 2012

    Science.gov (United States)

    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

  9. Intense precipitation extremes in a warmer climate: results from CMIP5 models

    Science.gov (United States)

    scoccimarro, enrico; gualdi, silvio; bellucci, alessio; zampieri, matteo; navarra, antonio

    2013-04-01

    In this work the authors investigate possible changes in the intensity of extreme precipitation events under a warmer climate, using the results of a set of 20 climate models taking part to the Coupled Model Intercomparison Project phase 5 effort (CMIP5). Future changes are evaluated as the epoch difference between the last four decades of the 21st and the 20th Century assuming the Representative Concentration Pathway RCP8.5 scenario. As a measure of the intensity associated with extreme precipitation events, we use the difference between the 99th and the 90th percentiles. Despite a slight tendency to underestimate the observed extreme precipitation intensity, the considered CMIP5 models well represent the observed patterns during both summer and winter seasons for the 1997-2005 period. Future changes in average precipitation are consistent with previous findings based on CMIP3 models. CMIP5 models show a projected increase for the end of the twenty-first century of the intensity of the extreme precipitations, particularly pronounced over India, South East Asia, Indonesia and Central Africa during boreal summer, as well as over South America and the southern Africa during boreal winter. These changes are consistent with a strong increase of the column integrated water content availability over the afore mentioned regions.

  10. Identifying climate analogues for precipitation extremes for Denmark based on RCM simulations from the ENSEMBLES database

    DEFF Research Database (Denmark)

    Arnbjerg-Nielsen, Karsten; Funder, S. G.; Madsen, H.

    2015-01-01

    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......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...

  11. Estimating statistics of European wet and dry spells and associated precipitation extremes - interannual variability and trends

    Science.gov (United States)

    Zolina, O.; Simmer, C.; Belyaev, K.; Gulev, S.; Koltermann, K. P.

    2013-12-01

    Probability distributions of the durations of wet and dry spells were modeled by applying truncated geometric distribution. It has been also extended to the fractional truncated geometric distribution which allows for the discrimination between the roles of a changing number of wet days and of a regrouping of wet and dry days in forming synoptic structure of precipitation. Analyses were performed using 2 collections of daily rain gauge data namely ECA (about 1000 stations) and regional German DWD network (more than 6000 stations) for the period from 1950 to 2009. Wet spells exhibit a statistically significant lengthening over northern Europe and central European Russia, which is especially pronounced in winter when the mean duration of wet periods increased by 15%-20%. In summer wet spells become shorter over Scandinavia and northern Russia. The duration of dry spells decreases over Scandinavia and southern Europe in both winter and summer. Climate tendencies in extreme wet and dry spell durations may not necessarily follow those in mean characteristics. The changing numbers of wet days cannot explain the long-term variability in the duration of wet and dry periods. The observed changes are mainly due to the regrouping of wet and dry days. The tendencies in duration of wet and dry spells have been analyzed for a number of European areas. Over the Netherlands both wet and dry periods are extended in length during the cold and the warm season. A simultaneous shortening of wet and dry periods is found in southern Scandinavia in summer. Over France and central southern Europe during both winter and summer and over the Scandinavian Atlantic coast in summer, opposite tendencies in the duration of wet and dry spells were identified. Growing durations of wet spells are associated with more intense precipitation events while precipitation during shorter wet spells become weaker. Both analyses of relatively coarse resolution ECA data and high resolution DWD station network

  12. CHARACTERIZATION OF PRECIPITATION EXTREMES AND TRENDS IN TWO REGIONS OF NORTH AFRICA

    Directory of Open Access Journals (Sweden)

    ZEINEDDINE N.

    2015-03-01

    Full Text Available To identify extreme precipitation, we use the “Standardized Precipitation Index” (SPI method designed to determine periods of climatic drought. This research attempts to assess the synchronization of cycles of precipitation and trends in two regions of the Mediterranean basin, the Soummam Valley (north - east of Algeria and the Cap Bon which forming a peninsula in north-east Tunisia. The results show a severe climate drought observed in these regions from the late eighties and a rainfall return observed at end of the series ( but more confirmed in the Cap Bon region.

  13. Daily weather generator with drought properties by copulas and standardized precipitation indices.

    Science.gov (United States)

    Hong, Nien-Ming; Lee, Tsung-Yu; Chen, Yun-Ju

    2016-06-01

    The weather generator is an essential process in water resource assessment. Most weather generators focus on extreme rainfall events and rainfall amounts in a relatively short time scale. However, drought events often last more than several months, which conventional weather generators hardly generate. Conventional weather generators assume that monthly rainfalls are independent, skewing drought event generation. The purpose of this study is to construct a weather generator with improved drought property generation, combining with monthly rainfall data from conventional weather generators and characteristics of standardized precipitation indices. The proposed weather generators employs four drought parameters, namely starting month, duration, average, and minimum standardized precipitation indices, generated using a copula method. Analytical results show that the four parameters generated by the copula method are consistent with historical records. The proposed weather generator overcomes the limitation of conventional weather generators and can generate both rainfall and drought properties. The results also indicate that the assumption of monthly independence in drought generation can cause underestimated occurrence and duration of drought events. The proposed generator is also demonstrated for climate change assessment. The analytical results show that the uncertainties from the selection of weather generators are even higher than those from the selections of global circulation models while applying to water shortage assessment. We therefore suggest that weather generators should consider drought characteristics which can be measured using the standardized precipitation index to reduce the uncertainty.

  14. A strategy for merging objective estimates of global daily precipitation from gauge observations, satellite estimates, and numerical predictions

    Science.gov (United States)

    Nie, Suping; Wu, Tongwen; Luo, Yong; Deng, Xueliang; Shi, Xueli; Wang, Zaizhi; Liu, Xiangwen; Huang, Jianbin

    2016-07-01

    This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates (SEs), and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions (MPs) over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation (OI)-based merging scheme (referred as the HL-OI scheme) is used to combine unbiased gauge observations, SEs, and MPs to reduce random error from each source and to produce a gauge—satellite-model merged daily precipitation analysis, called BMEP-d (Beijing Climate Center Merged Estimation of Precipitation with daily resolution), with complete global coverage. The BMEP-d data from a four-year period (2011-14) demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD (GPCP one-degree daily) show that the consistencies between BMEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.

  15. Variogram analysis of stable oxygen isotope composition of daily precipitation over the British Isles

    Science.gov (United States)

    Kohán, Balázs; Tyler, Jonathan; Jones, Matthew; Kern, Zoltán

    2017-04-01

    Water stable isotopes are important natural tracers in the hydrological cycle on global, regional and local scales. Daily precipitation water samples were collected from 70 sites over the British Isles on the 23rd, 24th, and 25th January, 2012 [1]. Samples were collected as part of a pilot study for the British Isotopes in Rainfall Project, a community engagement initiative, in collaboration with volunteer weather observers and the UK Met Office. Spatial correlation structure of daily precipitation stable oxygen isotope composition (δ18OP) has been explored by variogram analysis [2]. Since the variograms from the raw data suggested a pronounced trend, owing to the spatial trend discussed in the original study [1], a second order polynomial trend was removed from the raw δ18OP data and variograms were calculated on the residuals. Directional experimental semivariograms were calculated (steps: 10°, tolerance: 30°) and aggregated into variogram surface plots to explore the spatial dependence structure of daily δ18OP. Each daily data set produced distinct variogram plots. -A well expressed anisotropic structure can be seen for Jan 23. The lowest and highest variance was observed in the SW-NE and NNE-SSW direction, respectively. Meteorological observations showed that the majority of the atmospheric flow was SW on this day, so the direction of low variance seems to reflect this flow direction, while the maximum variance might reflect the moisture variance near the elongation of the frontal system. -A less characteristic but still expressed anisotropic structure was found for Jan 24 when a warm front passed the British Isles perpendicular to the east coast, leading to a characteristic east-west δ18OP gradient suggestive of progressive rainout. The low variance central zone has a 100 km radius which might correspond well to the width of the warm front zone. Although, the axis of minimum variance was similarly SW-NE, the zone of maximum variance was broader and

  16. Characteristics of autumn-winter extreme precipitation on the Norwegian west coast identified by cluster analysis

    Science.gov (United States)

    Heikkilä, U.; Sorteberg, A.

    2012-08-01

    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 Arpège global atmospheric model (stretched grid with 35-km horizontal resolution over Norway) and the WRF-downscaled Arpège 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 (Arpège 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 Arpège 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.

  17. Recent variability and trends in UK sub-daily rainfall: evidence for more rapidly changing extremes?

    Science.gov (United States)

    Blenkinsop, Stephen; Fowler, Hayley

    2017-04-01

    Recent UK floods have reinforced the need for a better understanding of how its exposure to flooding may change in the future with climate change. Short-duration intense rainfall is responsible for flash flooding, particularly in fast-responding catchments and urban areas. The new generation of very-high resolution climate models are providing better simulations of such rainfall events but an improved understanding of observed variability and trends in short-duration rainfall is also required. To date this has been confounded by the lack of high quality observations but is being addressed by the INTENSE project which is gathering global datasets of sub-daily rainfall. Methods to quality control such data have been tested to produce a high quality dataset of hourly rainfall for the UK. Here we use this dataset to examine trends and variability in seasonal UK hourly rainfall extremes and compare changes with those on daily timescales. In particular we consider whether we can more readily detect changes in hourly extremes than daily extremes in the observed record. This might be expected given that several studies have provided observational evidence of larger changes in hourly and sub-hourly extremes with temperature. We therefore assess evidence for an amplified response to warming on shorter timescales. Such studies may provide additional evidence that complements that derived from climate models.

  18. Trend of monthly temperature and daily extreme temperature during 1951-2012 in New Zealand

    Science.gov (United States)

    Caloiero, Tommaso

    2017-07-01

    Among several variables affecting climate change and climate variability, temperature plays a crucial role in the process because its variations in monthly and extreme values can impact on the global hydrologic cycle and energy balance through thermal forcing. In this study, an analysis of temperature data has been performed over 22 series observed in New Zealand. In particular, to detect possible trends in the time series, the Mann-Kendall non-parametric test was first applied at monthly scale and then to several indices of extreme daily temperatures computed since 1951. The results showed a positive trend in both the maximum and the minimum temperatures, in particular, in the autumn-winter period. This increase has been evaluated faster in maximum temperature than in minimum one. The trend analysis of the temperature indices suggests that there has been an increase in the frequency and intensity of hot extremes, while most of the cold extremes showed a downward tendency.

  19. Precipitation extremes and their relation to climatic indices in the Pacific Northwest, USA

    Science.gov (United States)

    Zarekarizi, Mahkameh; Rana, Arun; Moradkhani, Hamid

    2016-04-01

    Recently research has focused on the influence of climate indices on precipitation extremes. In the current study, we present the analysis of the precipitation-based extremes in Columbia River Basin (CRB) in the Pacific North-West USA. We first analyzed the precipitation-based extreme indices using statistically downscaled past and future climate projections from ten GCMs. Seven different precipitation-based indices that help inform about the flood duration/intensity are used in the study. These indices would give firsthand information on spatial and temporal scales for different service sectors including energy, agriculture, forestry etc. in the area. Temporally, historical and future projections are analyzed over the whole CRB using ten CMIP5 models. For each scenario, we have mapped out these indices over the area to see the spatial variation of past and future extremes. The analysis shows that high values of extreme indices are clustered in either western or southern parts of the basin while northern part of the basin is experiencing high increase in the indices in future scenarios. Here we focus our attention on evaluating the relation of these extreme and climate indices in historical period to understand which climate indices have more impact on 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 fifteen climate indices used in the study, CRB is being most affected negatively by East Pacific (EP), Western Pacific Index (WP), Eastern Asia (EA) and North Atlantic Oscillation (NAO).

  20. Changing precipitation extremes in a warming climate: A basis for design flood estimation

    Science.gov (United States)

    Wasko, Conrad; Sharma, Ashish

    2016-04-01

    The potential for increasing intensity of future rainfall events has significant implications for flooding and the design of infrastructure. However the questions of how precipitation will change in the future, how important these changes are to flooding, and how engineers incorporate these changes into hydrologic design remain as open questions. In the absence of reliable point based estimates of how precipitation will change, many studies investigate the historical relationship between rainfall intensity and temperature as a proxy for what may happen in a warmer climate. Much of the research to date has focussed on changing precipitation intensity, however, temporal and spatial patterns of precipitation are just as important. Here we link higher temperatures to changes in temporal and spatial patterns of extreme precipitation events. We show, using observed high quality precipitation records from Australia covering all major climatic zones, that storms are intensifying in both time and space resulting in a greater potential for flooding especially in urban locales around the world. Given that precipitation and antecedent conditions are changing, and, the impacts to flooding are significant, methods of incorporating these changes in catchment modelling are required. Continuous simulation offers a natural flexibility to incorporate the many correlated changes in precipitation that may occur in a future climate. An argument for such a framework using existing continuous simulation alternatives is articulated in concluding this presentation.

  1. Understanding convective extreme precipitation scaling using observations and an entraining plume model

    NARCIS (Netherlands)

    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

  2. High-resolution analysis of 1 day extreme precipitation in Sicily

    Science.gov (United States)

    Maugeri, M.; Brunetti, M.; Garzoglio, M.; Simolo, C.

    2015-04-01

    Sicily, the major Mediterranean island, experienced several exceptional precipitation episodes and floods during the last century, with dramatic consequences on human life and environment. A long term, rational planning of urban development is mandatory for protecting population and avoiding huge economic losses in the future. This requires a deep knowledge of the distributional features of extreme precipitation over the complex territory of Sicily. In the present study, we address this issue, and attempt a detailed investigation of observed 1-day precipitation extremes and their frequency distribution, based on a dense data-set of high-quality, homogenized station records in 1921-2005. We extrapolate very high quantiles (return levels) corresponding to 10-, 50- and 100-year return periods, as predicted by a generalized extreme value distribution. Return level estimates are produced on a regular high-resolution grid (30 arcsec) using a variant of regional frequency analysis combined with regression techniques. Results clearly reflect the complexity of this region, and make evident the high vulnerability of its eastern and northeastern parts as those prone to the most intense and potentially damaging events. This analysis thus provides an operational tool for extreme precipitation risk assessment and, at the same time, is an useful basis for validation and downscaling of regional climate models.

  3. Future projections of extreme precipitation using Advanced Weather Generator (AWE-GEN) over Peninsular Malaysia

    Science.gov (United States)

    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.

  4. Identifying climate analogues for precipitation extremes for Denmark based on RCM simulations from the ENSEMBLES database.

    Science.gov (United States)

    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.

  5. Subtropical air masses over eastern Canada: Their links to extreme precipitation

    Science.gov (United States)

    Gyakum, John; Wood, Alice; Milrad, Shawn; Atallah, Eyad

    2017-04-01

    We investigate extremely warm, moist air masses with an analysis of 850-hPa equivalent potential temperature (θe) extremes at Montreal, Quebec. The utility of using this metric is that it represents the thermodynamic property of air that ascends during a precipitation event. We produce an analysis of the 40 most extreme cases of positive θe, 10 for each season, based upon standardized anomalies from the 33-year climatology. The analysis shows the cases to be characterized by air masses with distinct subtropical traits for all seasons: reduced static stability, anomalously high precipitable water, and anomalously elevated dynamic tropopause heights. Persistent, slow moving upper- and lower-level features were essential in the build up of high- θe air encompassing much of eastern Canada. The trajectory analysis also showed anticyclonic curvature to all paths in all seasons, implying that the subtropical anticyclone is crucial in the transport of high- θe air. These atmospheric rivers during the winter are characterized by trajectories from the subtropical North Atlantic, and over the Gulf Stream current, northward into Montreal. In contrast, the summer anticyclonic trajectories are primarily continental, traveling from Texas north-northeastward into the Great Lakes, and then eastward into Montreal. The role of the air mass in modulating the strength of a precipitation event is addressed with an analysis of the expression, P = RD, where P is the total precipitation, and R is the precipitation rate, averaged through the duration, D, of the event. Though appearing simple, this expression includes R, (assumed to be same as condensation, with an efficiency of 1), which may be expressed as the product of vertical motion and the change of saturation mixing ratio following a moist adiabat, through the troposphere. This expression for R includes the essential ingredients of lift, air mass temperature, and static stability (implicit in vertical motion). We use this

  6. Large Scale Influences on Drought and Extreme Precipitation Events in the United States

    Science.gov (United States)

    Collow, A.; Bosilovich, M. G.; Koster, R. D.; Eichmann, A.

    2015-12-01

    Observations indicate that extreme weather events are increasing and it is likely that this trend will continue through the 21st century. However, there is uncertainty and disagreement in recent literature regarding the mechanisms by which extreme temperature and precipitation events are increasing, including the suggestion that enhanced Arctic warming has resulted in an increase in blocking events and a more meridional flow. A steady gradual increase in heavy precipitation events has been observed in the Midwestern and Northeastern United States, while the Southwestern United States, particularly California, has experienced suppressed precipitation and an increase in consecutive dry days over the past few years. The frequency, intensity, and duration of heavy precipitation events in the Midwestern United States and Northeastern United States, as well as drought in the Southwestern United States are examined using the Modern Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2). Indices developed by the Expert Team on Climate Change Detection and Indices representing drought and heavy precipitation events have been calculated using the MERRA-2 dataset for the period of 1980 through 2014. Trends in these indices are analyzed and the indices are compared to large scale circulations and climate modes using a composite and statistical linkages approach. Statistically significant correlations are present in the summer months between heavy precipitation events and meridional flow despite the lack of enhanced Arctic warming, contradicting the suggested mechanisms. Weaker, though still significant, correlations are observed in the winter months when the Arctic is warming more rapidly than the Midlatitudes.

  7. On the variability of return periods of European winter precipitation extremes over the last three centuries

    Directory of Open Access Journals (Sweden)

    A. Pauling

    2007-01-01

    Full Text Available We investigate the changes of extreme European winter (December-February precipitation back to 1700 and show for various European regions that return periods of extremely wet and dry winters are subject to significant changes both before and after the onset of anthropogenic influences. Generally, winter precipitation has become more extreme. We also examine the spatial pattern of the changes of the extremes covering the last 300 years where data quality is sufficient. Over central and Eastern Europe dry winters occurred more frequently during the 18th and the second part of the 19th century relative to 1951–2000. Dry winters were less frequent during both the 18th and 19th century over the British Isles and the Mediterranean. Wet winters have been less abundant during the last three centuries compared to 1951–2000 except during the early 18th century in central Europe. Although winter precipitation extremes are affected by climate change, no obvious connection of these changes was found to solar, volcanic or anthropogenic forcing. However, physically meaningful interpretation with atmospheric circulation changes was possible.

  8. Hydrological extremes in hyperarid regions: A diagnostic characterization of intense precipitation over the Central Arabian Peninsula

    Science.gov (United States)

    Kumar, Kondapalli Niranjan; Entekhabi, Dara; Molini, Annalisa

    2015-03-01

    Aridity is typically associated with deep and dry daytime boundary layers, stable nighttime stratification, divergent flows, and limited large-scale moisture advection. All these factors are paramount in regulating the hydroclimatology of hyperarid regions, resulting in extremely intermittent—and often intense—local precipitation patterns. However, the link between synoptic-scale forcing and intense precipitation over arid regions has been scarcely investigated in the literature and still remains exceedingly unexplored. We present here a diagnostic study of intense precipitation in the Central Arabian Peninsula, based on the analysis of local extreme signatures embedded in synoptic patterns. Special emphasis is given to the genesis of winter extremes over the Peninsula, and to possible effects of synchronization between the atmospheric circulation over the Mediterranean and the Indian Ocean. Based on composites of the tropospheric circulation for a large ensemble of intense events, we show that moisture necessary to trigger winter extremes over the Peninsula starts to build up in average 8 days before heavy rainfall occurrence, mainly as a consequence of the interplay between the Mediterranean and the Monsoonal circulation. Moisture advection is in turn associated with an upper troposphere cyclonic circulation and pronounced potential vorticity intrusions. Overall, our results demonstrate how large-scale precursors can be effectively used to improve the predictability of rainfall extremes in hyperarid regions.

  9. Present-day and future mediterranean precipitation extremes assessed by different statistical approaches

    Science.gov (United States)

    Paxian, A.; Hertig, E.; Seubert, S.; Vogt, G.; Jacobeit, J.; Paeth, H.

    2015-02-01

    The Mediterranean area is strongly vulnerable to future changes in temperature and precipitation, particularly concerning extreme events, and has been identified as a climate change hot spot. This study performs a comprehensive investigation of present-day and future Mediterranean precipitation extremes based on station data, gridded observations and simulations of the regional climate model (REMO) driven by the coupled global general circulation model ECHAM5/MPI-OM. Extreme value estimates from different statistical methods—quantile-based indices, generalized pareto distribution (GPD) based return values and data from a weather generator—are compared and evaluated. Dynamical downscaling reveals improved small-scale topographic structures and more realistic higher rainfall totals and extremes over mountain ranges and in summer. REMO tends to overestimate gridded observational data in winter but is closer to local station information. The dynamical-statistical weather generator provides virtual station rainfall from gridded REMO data that overcomes typical discrepancies between area-averaged model rainfall and local station information, e.g. overestimated numbers of rainy days and underestimated extreme intensities. Concerning future rainfall amount, strong summer and winter drying over the northern and southern Mediterranean, respectively, is confronted with winter wetting over the northern part. In contrast, precipitation extremes tend to increase in even more Mediterranean areas, implying regions with decreasing totals but intensifying extremes, e.g. southern Europe and Turkey in winter and the Balkans in summer. The GPD based return values reveal slightly larger regions of increasing rainfall extremes than quantile-based indices, and the virtual stations from the weather generator show even stronger increases.

  10. Extreme Historical Droughts in the South-Eastern Alps - Analyses Based on Standardised Precipitation Index

    Directory of Open Access Journals (Sweden)

    Brenčič Mihael

    2016-10-01

    Full Text Available Droughts are natural phenomena affecting the environment and human activities. There are various drought definitions and quantitative indices; among them is the Standardised Precipitation Index (SPI. In the drought investigations, historical events are poorly characterised and little data are available. To decipher past drought appearances in the southeastern Alps with a focus on Slovenia, precipitation data from HISTALP data repository were taken to identify extreme drought events (SPI ≤ -2.00 from the second half of the 19th century to the present day. Several long-term extreme drought crises were identified in the region (between the years 1888 and 1896; after World War I, during and after World War II. After 1968, drought patterns detected with SPI changed: shorter, extreme droughts with different time patterns appeared. SPI indices of different time spans showed correlated structures in space and between each other, indicating structured relations.

  11. Extreme Historical Droughts in the South-Eastern Alps — Analyses Based on Standardised Precipitation Index

    Science.gov (United States)

    Brenčič, Mihael

    2016-10-01

    Droughts are natural phenomena affecting the environment and human activities. There are various drought definitions and quantitative indices; among them is the Standardised Precipitation Index (SPI). In the drought investigations, historical events are poorly characterised and little data are available. To decipher past drought appearances in the southeastern Alps with a focus on Slovenia, precipitation data from HISTALP data repository were taken to identify extreme drought events (SPI ≤ -2.00) from the second half of the 19th century to the present day. Several long-term extreme drought crises were identified in the region (between the years 1888 and 1896; after World War I, during and after World War II). After 1968, drought patterns detected with SPI changed: shorter, extreme droughts with different time patterns appeared. SPI indices of different time spans showed correlated structures in space and between each other, indicating structured relations.

  12. Representation of extreme precipitation events in Nepal in CMIP5 models

    Science.gov (United States)

    Jung, Woosung; Ryu, Byeong; Yun, Myong

    2016-04-01

    Nepal is highly vulnerable to of extreme climate events due in part to its mountainous terrain and lack of infrastructure. Climate change is projected to increase the frequency and magnitude of extreme temperature and precipitation events worldwide, with particularly severe impacts likely in Nepal. In this study we analyze the performance of general circulation models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) at simulating temperature and precipitation in Nepal relative to the NCEP Reanalysis II and observational data, and we project how extreme events may change during the 21st century. We analyze the uncertainty in our projections, and compare the current generation of models in CMIP5 to prior results in this region using older climate models. Finally, we consider the impact of our projections on Nepal's society and economy.

  13. How to apply the dependence structure analysis to extreme temperature and precipitation for disaster risk assessment

    Science.gov (United States)

    Feng, Jieling; Li, Ning; Zhang, Zhengtao; Chen, Xi

    2017-06-01

    IPCC reports that a changing climate can affect the frequency and the intensity of extreme events. However, the extremes appear in the tail of the probability distribution. In order to know the relationship between extreme events in the tail of temperature and precipitation, an important but previously unobserved dependence structure is analyzed in this paper. Here, we examine the dependence structure by building a bivariate joint of Gumbel copula model for temperature and precipitation using monthly average temperature (T) and monthly precipitation (P) data from Beijing station in China covering a period of 1951-2015 and find the dependence structure can be divided into two sections, they are the middle part and the upper tail. We show that T and P have a strong positive correlation in the high tail section (T > 25.85 °C and P > 171.1 mm) (=0.66, p < 0.01) while they do not demonstrate the same relation in the other section, which suggests that the identification of a strong influence of T on extreme P needs help from the dependence structure analysis. We also find that in the high tail section, every 1 °C increase in T is associated with 73.45 mm increase in P. Our results suggested that extreme precipitation fluctuations by changes in temperature will allow the data dependence structure to be included in extreme affect for the disaster risk assessment under future climate change scenarios. Copula bivariate jointed probability distribution is useful to the dependence structure analysis.

  14. An analysis of the daily precipitation variability in the Himalayan orogen using a statistical parameterisation and its potential in driving landscape evolution models with stochastic climatic forcing

    Science.gov (United States)

    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

  15. Probability Distribution of Precipitation Extremes over the Yangtze River Basin%1960-2005年长江流域降水极值概率分布特征

    Institute of Scientific and Technical Information of China (English)

    苏布达; Marco Gemmer; 姜彤

    2008-01-01

    Based on the daily observational precipitation data of 147 stations in the Yangtze River basin for 1960-2005,and the projected daily data of 79 grids from ECHAM5/MPI-OM in the 20th century,time series of precipitation extremes which contain annual maximum(AM)and Munger index(MI)were constructed.The distribution feature of precipitation extremes was analyzed based on the two index series.Research results show that(1)the intensity and probability of extreme heavy precipitation are higher in the middle Mintuo River sub-catchment,the Dongting Lake area,the mid-lower main stream section of the Yangtze River,and the southeastern Poyang Lake sub-catchment;whereas,the intensity and probability of drought events are higher in the mid-lower Jinsha River sub-catchment and the Jialing River sub-catchment;(2)compared with observational data,the averaged value of AM is higher but the deviation coefficient is lower in projected data,and the center of precipitation extremes moves northwards;(3)in spite of certain differences in the spatial distributions of observed and projected precipitation extremes,by applying General Extreme Value(GEV)and Wakeby(WAK)models with the method of L-Moment Estimator(LME)to the precipitation extremes,it is proved that WAK can simulate the probability distribution of precipitation extremes calculated from both observed and projected data quite well.The WAK could be an important function for estimating the precipitation extreme events in the Yangtze River basin under future climatic scenarios.

  16. Evaluating regional climate models for simulating sub-daily rainfall extremes

    Science.gov (United States)

    Cortés-Hernández, Virginia Edith; Zheng, Feifei; Evans, Jason; Lambert, Martin; Sharma, Ashish; Westra, Seth

    2016-09-01

    Sub-daily rainfall extremes are of significant societal interest, with implications for flash flooding and the design of urban stormwater systems. It is increasingly recognised that extreme subdaily rainfall will intensify as a result of global temperature increases, with regional climate models (RCMs) representing one of the principal lines of evidence on the likely magnitude and spatiotemporal characteristics of these changes. To evaluate the ability of RCMs to simulate subdaily extremes, it is common to compare the simulated statistical characteristics of the extreme rainfall events with those from observational records. While such analyses are important, they provide insufficient insight into whether the RCM reproduces the correct underlying physical processes; in other words, whether the model "gets the right answers for the right reasons". This paper develops a range of metrics to assess the performance of RCMs in capturing the physical mechanisms that produce extreme rainfall. These metrics include the diurnal and seasonal cycles, relationship between rainfall intensity and temperature, temporal scaling, and the spatial structure of extreme rainfall events. We evaluate a high resolution RCM—the Weather Research Forecasting model—over the Greater Sydney region, using three alternative parametrization schemes. The model shows consistency with the observations for most of the proposed metrics. Where differences exist, these are dependent on both the rainfall duration and model parameterization strategy. The use of physically meaningful performance metrics not only enhances the confidence in model simulations, but also provides better diagnostic power to assist with future model improvement.

  17. Using scaling fluctuation analysis to quantify anthropogenic changes in regional and global precipitation, including extremes

    Science.gov (United States)

    de Lima, Isabel; Lovejoy, Shaun

    2016-04-01

    Anthropic precipitation changes affect the mean and the magnitude and frequency of extreme events, and therefore potentially have severe consequences in all aspects of human life. Unfortunately, - unlike the anthropic temperature changes - precipitation changes of anthropic origin have been proven difficult to establish with high statistical significance. For example, when changes have been established for individual precipitation products, the serious divergences found between products reflect our limited ability to estimate areal precipitation even at global scales. In addition to data issues, the usual approaches to assessing changes in precipitation also have methodological issues that hamper their identification. Here we discuss how the situation can be clarified by the systematic application of scaling fluctuation analysis - for example, to determine the scales at which the anthropogenic signal exceeds the natural variability noise (we find that it is roughly 20 years). Following a recent approach for estimating anthropogenic temperature changes we directly determine the effective sensitivity of the precipitation rate to a doubling of CO2. The novelty in this approach is that it takes CO2 as a surrogate for all anthropogenic forcings and estimates the trend based on the forcing rather than time - the usual approach. This leads both to an improved signal to noise ratio and, when compared to the usual estimates of trends, it augments their statistical significance; we further improve the signal to noise ratio by considering precipitation over the ocean where anthropogenic increases are strongest, finding that there are statistically significant trends at the 3 to 4 standard deviation level. This approach also permits the first direct estimate of the increases in global precipitation with temperature: we find 1.71±0.62 %/K which is close to that found by GCM's (2 - 3%/K) and is well below the value of ≈ 6 - 7%/K predicted on the basis of increases in humidity

  18. Evaluation of GRACE daily gravity solutions for hydrological extremes in selected river basins

    Science.gov (United States)

    Gouweleeuw, Ben; Güntner, Andreas; Gain, Animesh; Gruber, Christian; Flechtner, Frank; Kvas, Andreas; Mayer-Gürr, Torsten

    2016-04-01

    Water storage anomalies from the Gravity Recovery And Climate Experiment (GRACE) satellite mission (2002-present) have been shown to be a unique descriptor of large-scale hydrological extreme events. However, possibly due to its coarse temporal (monthly to weekly) and spatial (> 150.000 km2) resolution, the comprehensive information from GRACE on total water storage variations has rarely been evaluated for flood or drought monitoring or forecasting so far. In the context of the Horizon 2020 funded European Gravity Service for Improved Emergency Management (EGSIEM) project, we evaluate two approaches to solve the spatio-temporal variations of the Earth's gravity field as daily solutions through comparison to selected historical extreme events in medium-large river basins (Ganges-Brahmaputra, Lower Mekong, Danube, Elbe). These comparisons show that highs and lows of GRACE-derived total water storage are closely related to the occurrence of hydrological extremes and serve as an early indicator of these events. The degree to which the daily GRACE solutions contain high-frequent temporal hydrological information, e.g. individual flood peaks, is related to the size of the extreme event.

  19. Global-warming-induced Increases in Extreme Precipitation are Smallest over Mountains

    Science.gov (United States)

    Shi, X.; Durran, D. R.

    2015-12-01

    Climate-model simulations predict an intensification of extreme precipitation in almost all areas of the world under global warming. Geographical variations in the magnitude of this intensification are clearly evident in the simulations, but most previous efforts to understand the factors responsible for the changes in extreme precipitation have focused on zonal averages, neglecting the variations that occur in different regions at the same latitude. Here we present climate-model simulations for an ocean-covered earth having simple idealized continents with north-south mountain barriers in its northern midlatitudes. We show that the sensitivity of extreme precipitation to increases in the global mean surface temperature is 3 %/K lower over the mountains than over the oceans and the plains. Fundamental factors responsible for changes in precipitation intensity may be divided between thermodynamic effects, arising through changes in temperature and moisture, and dynamical effects, produced by changes in the ascent rates of saturated air parcels. The difference in sensitivity among these regions is not due to thermodynamic effects, but rather to differences between the gravity-wave dynamics governing vertical velocities over the mountains and the cyclone dynamics governing vertical motions over the oceans and plains.

  20. Proactive modeling of water quality impacts of extreme precipitation events in a drinking water reservoir.

    Science.gov (United States)

    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.

  1. Modelling the extreme precipitation event over Madeira Island on 20 February 2010

    Directory of Open Access Journals (Sweden)

    T. Luna

    2011-09-01

    Full Text Available In the morning of the 20 February of 2010 an extreme precipitation event occurred over Madeira Island. This event triggered several flash floods and mudslides in the southern parts of the island, resulting in 42 confirmed deaths, 100 injured, and at least 8 people still missing. These extreme weather conditions were associated to a weather frontal system moving northeastwards embedded in a low pressure area centered in the Azores archipelago. This storm was one in a series of such storms that affected Portugal, Spain, Morocco and the Canary islands causing flooding and strong winds. These storms were bolstered by an unusually strong sea surface temperature gradient across the Atlantic Ocean.

    In this study, the WRF model is used to evaluate the intensity and predictability of this precipitation extreme event over the island. The synoptic/orographic nature of the precipitation is also evaluated, as well as the sensitivity of the model to horizontal resolution and cumulus parameterization. Orography was found to be the main factor explaining the occurrence, amplitude and phase of precipitation over the Island.

  2. Prepartying, drinking games, and extreme drinking among college students: a daily-level investigation.

    Science.gov (United States)

    Fairlie, Anne M; Maggs, Jennifer L; Lanza, Stephanie T

    2015-03-01

    Daily data collected over 14 consecutive days were used to examine whether extreme drinking was more likely on days college students reported prepartying (i.e., drinking before going out) or playing drinking games in a multi-ethnic sample of college seniors (analysis subsample: N=399; 57% women; M age=21.48years, SD=.40). Multilevel modeling with drinking occasions at Level 1 (1265 drinking days) nested within persons at Level 2 (399 drinkers) was used to predict four extreme drinking behavior outcomes at the daily level: consuming at least 8/10 (women/men) drinks, reaching an estimated blood alcohol concentration (eBAC) of .16% or greater, drinking enough to stumble, and drinking enough to pass out. Prepartying only (29% of drinking days) was more common than playing drinking games only (10%) or engaging in both behaviors on the same day (13%). Odds of extreme drinking were greater among students who frequently engaged in prepartying (ORs: 1.86-2.58) and drinking games (ORs: 1.95-4.16), except prepartying frequency did not predict drinking enough to pass out. On days students prepartied (ORs: 1.58-2.02) and on days they played drinking games (ORs: 1.68-1.78), odds of extreme drinking were elevated, except drinking games did not predict eBAC of .16% or greater. Extreme drinking is attributable to both person-level characteristics (e.g., preparty frequency) and specific drinking behaviors on a given day. Prepartying and drinking games confer elevated risk of extreme drinking and are important targets in alcohol interventions for college seniors. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. CPLFD-GDPT5: high-resolution gridded daily precipitation and temperature dataset for two largest Polish river basins

    Science.gov (United States)

    Berezowski, T.; Szcześniak, M.; Kardel, I.; Michałowski, R.; Okruszko, T.; Mezghani, A.; Piniewski, M.

    2015-12-01

    The CHASE-PL Forcing Data-Gridded Daily Precipitation and Temperature Dataset-5 km (CPLFD-GDPT5) consists of 1951-2013 daily minimum and maximum air temperatures and precipitation totals interpolated onto a 5 km grid based on daily meteorological observations from Institute of Meteorology and Water Management (IMGW-PIB; Polish stations), Deutscher Wetterdienst (DWD, German and Czech stations), ECAD and NOAA-NCDC (Slovak, Ukrainian and Belarus stations). The main purpose for constructing this product was the need for long-term aerial precipitation and temperature data for earth-system modelling, especially hydrological modelling. The spatial coverage is the union of Vistula and Odra basin and Polish territory. The number of available meteorological stations for precipitation and temperature varies in time from about 100 for temperature and 300 for precipitation in 1950 up to about 180 for temperature and 700 for precipitation in 1990. The precipitation dataset was corrected for snowfall and rainfall under-catch with the Richter method. The interpolation methods were: kriging with elevation as external drift for temperatures and indicator kriging combined with universal kriging for precipitation. The kriging cross-validation revealed low root mean squared errors expressed as a fraction of standard deviation (SD): 0.54 and 0.47 for minimum and maximum temperature, respectively and 0.79 for precipitation. The correlation scores were 0.84 for minimum temperatures, 0.88 for maximum temperatures and 0.65 for precipitation. The CPLFD-GDPT5 product is consistent with 1971-2000 climatic data published by IMGW-PIB. We also confirm good skill of the product for hydrological modelling by performing an application using the Soil and Water Assessment Tool (SWAT) in the Vistula and Odra basins. Link to the dataset: http://data.3tu.nl/repository/uuid:e939aec0-bdd1-440f-bd1e-c49ff10d0a07

  4. Causing Factors for Extreme Precipitation in the Western Saudi-Arabian Peninsula

    Science.gov (United States)

    Alharbi, M. M.; Leckebusch, G. C.

    2015-12-01

    In the western coast of Saudi Arabia the climate is in general semi-arid but extreme precipitation events occur on a regular basis: e.g., on 26th November 2009, when 122 people were killed and 350 reported missing in Jeddah following more than 90mm in just four hours. Our investigation will a) analyse major drivers of the generation of extremes and b) investigate major responsible modes of variability for the occurrence of extremes. Firstly, we present a systematic analysis of station based observations of the most relevant extreme events (1985-2013) for 5 stations (Gizan, Makkah, Jeddah, Yenbo and Wejh). Secondly, we investigate the responsible mechanism on the synoptic to large-scale leading to the generation of extremes and will analyse factors for the time variability of extreme event occurrence. Extreme events for each station are identified in the wet season (Nov-Jan): 122 events show intensity above the respective 90th percentile. The most extreme events are systematically investigated with respect to the responsible forcing conditions which we can identify as: The influence of the Soudan Low, active Red-Sea-Trough situations established via interactions with mid-latitude tropospheric wave activity, low pressure systems over the Mediterranean, the influence of the North Africa High, the Arabian Anticyclone and the influence of the Indian monsoon trough. We investigate the role of dynamical forcing factors like the STJ and the upper-troposphere geopotential conditions and the relation to smaller local low-pressure systems. By means of an empirical orthogonal function (EOF) analysis based on MSLP we investigate the possibility to objectively quantify the influence of existing major variability modes and their role for the generation of extreme precipitation events.

  5. The influence of tropical forcing on extreme winter precipitation in the western Himalaya

    Science.gov (United States)

    Cannon, Forest; Carvalho, Leila M. V.; Jones, Charles; Hoell, Andrew; Norris, Jesse; Kiladis, George N.; Tahir, Adnan A.

    2017-02-01

    Within the Karakoram and western Himalaya (KH), snowfall from winter westerly disturbances (WD) maintains the region's snowpack and glaciers, which melt seasonally to sustain water resources for downstream populations. WD activity and subsequent precipitation are influenced by global atmospheric variability and tropical-extratropical interactions. On interannual time-scales, El Niño related changes in tropical diabatic heating induce a Rossby wave response over southwest Asia that is linked with enhanced dynamical forcing of WD and available moisture. Consequently, extreme orographic precipitation events are more frequent during El Niño than La Niña or neutral conditions. A similar spatial pattern of tropical diabatic heating is produced by the MJO at intraseasonal scales. In comparison to El Niño, the Rossby wave response to MJO activity is less spatially uniform over southwest Asia and varies on shorter time-scales. This study finds that the MJO's relationship with WD and KH precipitation is more complex than that of ENSO. Phases of the MJO propagation cycle that favor the dynamical enhancement of WD simultaneously suppress available moisture over southwest Asia, and vice versa. As a result, extreme precipitation events in the KH occur with similar frequency in most phases of the MJO, however, there is a transition in the relative importance of dynamical forcing and moisture in WD to orographic precipitation in the KH as the MJO evolves. These findings give insight into the dynamics and predictability of extreme precipitation events in the KH through their relationship with global atmospheric variability, and are an important consideration in evaluating Asia's water resources.

  6. Statistical downscaling of daily precipitation: A two-step probabilistic approach

    Science.gov (United States)

    Haas, R.; Born, K.

    2010-09-01

    Downscaling of climate data is an important issue in order to obtain high-resolution data desired for most applications in meteorology and hydrology and to gain a better understanding of local climate variability. Statistical downscaling transforms data from large to local scale by relating punctual climate observations, climate model outputs and high-resolution surface data. In this study, a probabilistic downscaling approach is applied on precipitation data from the subtropical mountain environment of the High Atlas in Morocco. The observations were collected within the GLOWA project IMPETUS West Africa. The considered area is characterized by strong NW-SE gradients both of altitude and of precipitation. The method consists of two steps. In order to interpolate between observational sites, the first step applies Multiple Linear Regression (MLR) on observed data taking local topographic information into account. The dependent variable (predictand) is estimated using different explanatory variables (predictors): height, latitude, longitude, slope, aspect, or gradients of height in zonal and meridional direction. For a predictand like temperature, which follows approximately a normal distribution, this method is appropriate. The development of transfer functions for precipitation is challenging, because the empirical distribution is heavily skewed due to many days with marginal or zero amounts and few extreme events. Because an application of MLR on observed values yields partly negative rainfall amounts, a probabilistic approach is utilized. At this, MLR is applied on parameters of a theoretical distribution (e.g. Weibull), which is fit to empirical distributions of precipitation amounts. In the second step, a transfer function between distributions of large-scale predictors, e.g. climate model or reanalysis data, and of local observations is derived. This is achieved by an equal probability mapping between cumulative distributions functions (CDFs) of large

  7. Spatiotemporal patterns of precipitation extremes in the Poyang Lake basin, China: Changing properties and causes

    Science.gov (United States)

    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

  8. Precipitation variability, extremes and uncertainties over southeastern Brazil projected by the Eta regional model

    Science.gov (United States)

    Cavalcanti, Iracema; Silveira, Virginia; Chan, Chou; Marengo, Jose Antonio

    2014-05-01

    Southeastern Brazil is an area affected by extreme precipitation, mainly in the austral summer, associated with frontal systems or the South Atlantic Convergence Zone (SACZ). Flooding and landslides have occurred in the region with serious impact on society and economy. The region has many vulnerable areas, therefore, projections of precipitation and extremes in the future for the region are important to provide information that can be used in adaptations and management decisions. Results of regional models in South America have been analyzed to assess the future climate changes with higher resolution than global models. In this study the Regional Eta model is used with resolution of 40 and 20 Km to analyze the projections of precipitation changes and extremes over Brazil and mainly over the southeastern region. Simulations and projections obtained from four integrations of the Regional Eta model are analyzed to investigate the model behavior during the period of 1961-1990 and the projections in the near (2011 to 2040) and more distant future (2041 to 2100). Results from four integrations with resolution of 40 km with different lateral boundary conditions from the HadCM3 Global Model and one integration with resolution of 20 km are used to give a confidence interval and the related uncertainty. The first analysis was to verify changes in the main mode of precipitation variability in the future projections, compared to the base period. There is a change in the main centers of extremes variability over South America, which was comparable to changes projected in CMIP5 models. The second analysis was related to changes in the position and intensity of the SACZ. Specific locations in southeastern Brazil were analyzed regarding indices of extremes, such as SDII (mean precipitation of rainy days), SDII_10 (mean precipitation of rainy days >=10 mm/day), R10mm (number of days with precipitation >= 10 mm/day), CDD (maximum number of consecutive dry days), CWD (maximum number

  9. Quantification and visualization of the human impacts of anticipated precipitation extremes in South America

    Science.gov (United States)

    Fuller, C. T.; Sabesan, A.; Khan, S.; Kuhn, G.; Ganguly, A. R.; Erickson, D. J.; Ostrouchov, G.

    2006-12-01

    The research described here quantifies and visualizes the human impacts of extreme events, which in turn can lead to enhanced disaster readiness levels as well as response or mitigation strategies. Specifically, we investigate the space-time impact of anticipated precipitation extremes on human population in South America. The research attempts to integrate two recent and ongoing lines of research. In the first study (Sabesan et al., 2006; Abercrombie et al, 2006) LandScan® high-resolution population data sets were used to develop threat metrics in space and time. In the second study (Khan et al, 2006; Kuhn and Ganguly, 2006), grid-based observations of precipitation time series in South America were utilized to quantify the probability of precipitation extremes in space and time and define a geo-referenced "extremes volatility ratio" (EVR) for unanticipated, or the "truly unusual", extremes. Here we define an "extremes volatility index" (EVI) which scales from zero to unity and provides an anticipated measure of surprise corresponding to the truly unusual extremes. An EVI of zero indicates no possibility of surprise with the truly unusual extremes statistically identical to the "typical extremes", or the extremes considered, for example, in engineering design. We investigate the EVI in conjunction with maps for ambient population in South America obtained from a high- resolution global population database called LandScan® to produce a "human risk index" (HRI) in space and time. The EVI is roughly interpreted as a probability number which is multiplied with the population at each grid in space and time to obtain a measure of risk. Future research needs to explore measures of risk that consider other costs of disasters, for example impacts on critical infrastructures. A geo-referenced index, the "disaster impact index" (DII) is proposed. The DII at each grid is computed by dividing the HRI with the Gross Domestic Product (GDP) for each country. The GDP is utilized

  10. Recent trends in pre-monsoon daily temperature extremes over India

    Indian Academy of Sciences (India)

    D R Kothawale; J V Revadekar; K Rupa Kumar

    2010-02-01

    Extreme climate and weather events are increasingly being recognized as key aspects of climate change. Pre-monsoon season (March–May) is the hottest part of the year over almost the entire South Asian region, in which hot weather extremes including heat waves are recurring natural hazards having serious societal impacts, particularly on human health. In the present paper, recent trends in extreme temperature events for the pre-monsoon season have been studied using daily data on maximum and minimum temperatures over a well-distributed network of 121 stations for the period 1970–2005. For this purpose, time series of extreme temperature events have been constructed for India as a whole and seven homogeneous regions, viz., Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP). In general, the frequency of occurrence of hot days and hot nights showed widespread increasing trend, while that of cold days and cold nights has shown widespread decreasing trend. The frequency of the occurrence of hot days is found to have significantly increased over EC, WC and IP, while that of cold days showed significant decreasing trend over WH and WC. The three regions EC, WC and NW showed significant increasing trend in the frequency of hot nights. For India as whole, the frequency of hot days and nights showed increasing trend while cold days and nights showed decreasing trends. Day-to-day fluctuations of pre-monsoon daily maximum and minimum temperatures have also been studied for the above regions. The results show that there is no significant change in day-to-day magnitude of fluctuations of pre-monsoon maximum and minimum temperatures. However, the results generally indicate that the daily maximum and minimum temperatures are becoming less variable within the season.

  11. Comparison of different statistical downscaling methods to estimate changes in hourly extreme precipitation using RCM projections from ENSEMBLES

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Gregersen, Ida Bülow; Rosbjerg, Dan;

    2015-01-01

    Changes in extreme precipitation are expected to be one of the most important impacts of climate change in cities. Urban floods are mainly caused by short duration extreme events. Hence, robust information on changes in extreme precipitation at high-temporal resolution is required for the design...... of climate change adaptation measures. However, the quantification of these changes is challenging and subject to numerous uncertainties. This study assesses the changes and uncertainties in extreme precipitation at hourly scale over Denmark. It explores three statistical downscaling approaches: a delta...

  12. Trends in atmospheric patterns conducive to seasonal precipitation and temperature extremes in California.

    Science.gov (United States)

    Swain, Daniel L; Horton, Daniel E; Singh, Deepti; Diffenbaugh, Noah S

    2016-04-01

    Recent evidence suggests that changes in atmospheric circulation have altered the probability of extreme climate events in the Northern Hemisphere. We investigate northeastern Pacific atmospheric circulation patterns that have historically (1949-2015) been associated with cool-season (October-May) precipitation and temperature extremes in California. We identify changes in occurrence of atmospheric circulation patterns by measuring the similarity of the cool-season atmospheric configuration that occurred in each year of the 1949-2015 period with the configuration that occurred during each of the five driest, wettest, warmest, and coolest years. Our analysis detects statistically significant changes in the occurrence of atmospheric patterns associated with seasonal precipitation and temperature extremes. We also find a robust increase in the magnitude and subseasonal persistence of the cool-season West Coast ridge, resulting in an amplification of the background state. Changes in both seasonal mean and extreme event configurations appear to be caused by a combination of spatially nonuniform thermal expansion of the atmosphere and reinforcing trends in the pattern of sea level pressure. In particular, both thermal expansion and sea level pressure trends contribute to a notable increase in anomalous northeastern Pacific ridging patterns similar to that observed during the 2012-2015 California drought. Collectively, our empirical findings suggest that the frequency of atmospheric conditions like those during California's most severely dry and hot years has increased in recent decades, but not necessarily at the expense of patterns associated with extremely wet years.

  13. Daily precipitation estimation through different microwave sensors: Verification study over Italy

    Science.gov (United States)

    Ciabatta, Luca; Marra, Anna Cinzia; Panegrossi, Giulia; Casella, Daniele; Sanò, Paolo; Dietrich, Stefano; Massari, Christian; Brocca, Luca

    2017-02-01

    The accurate estimation of rainfall from remote sensing is of paramount importance for many applications as, for instance, the mitigation of natural hazards like floods, droughts, and landslides. Traditionally, microwave observations in the frequency between 10 and 183 GHz are used for estimating rainfall based on the direct interaction of radiation with the hydrometeors within precipitating clouds in a so-called top-down approach. Recently, a bottom-up approach was proposed that uses satellite soil moisture products derived from microwave observations (nature. In this study, we perform a long-term (3 years) assessment of different satellite rainfall products exploiting the full range of microwave frequencies over Italy. Specifically, the integration of two top-down algorithms (CDRD, Cloud Dynamics and Radiation Database, and PNPR, Passive microwave Neural network Precipitation Retrieval) for estimating rainfall from conically and cross-track scanning radiometers, and one bottom-up algorithm (SM2RAIN) applied to the Advanced SCATterometer soil moisture product is carried out. The performances of the products, individually and merged together, are assessed at daily time scale. The integration of top-down and bottom-up approaches provides the highest performance both in terms of continuous and categorical scores (i.e., median correlation coefficient and root mean square error values equal to 0.71 and 6.62 mm, respectively). In such a combination, the limitations of the two approaches are compensated allowing a better estimation of ground accumulated rainfall through SM2RAIN while, overcoming the limitations of rainfall estimation for intense events during wet conditions through CDRD-PNPR product. The accuracy and the reliability of the merged product open new possibilities for their testing in hydrological applications, such as the monitoring and prediction of floods and droughts over large areas, including regions where ground-based measurements are sparse or not

  14. Assessment of multiple daily precipitation statistics in ERA-Interim driven Med-CORDEX and EURO-CORDEX experiments against high resolution observations

    Science.gov (United States)

    Fantini, Adriano; Raffaele, Francesca; Torma, Csaba; Bacer, Sara; Coppola, Erika; Giorgi, Filippo; Ahrens, Bodo; Dubois, Clotilde; Sanchez, Enrique; Verdecchia, Marco

    2016-11-01

    We assess the statistics of different daily precipitation indices in ensembles of Med-CORDEX and EURO-CORDEX experiments at high resolution (grid spacing of 0.11°, or RCM11) and medium resolution (grid spacing of 0.44°, or RCM44) with regional climate models (RCMs) driven by the ERA-Interim reanalysis of observations for the period 1989-2008. The assessment is carried out by comparison with a set of high resolution observation datasets for nine European subregions. The statistics analyzed include quantitative metrics for mean precipitation, daily precipitation probability density functions (PDFs), daily precipitation intensity, frequency, 95th percentile and 95th percentile of dry spell length. We assess an ensemble including all Med-CORDEX and EURO-CORDEX models together and others including the Med-CORDEX and EURO-CORDEX separately. For the All Models ensembles, the RCM11 one shows a remarkable performance in reproducing the spatial patterns and seasonal cycle of mean precipitation over all regions, with a consistent and marked improvement compared to the RCM44 ensemble and the ERA-Interim reanalysis. A good consistency with observations by the RCM11 ensemble (and a substantial improvement compared to RCM44 and ERA-Interim) is found also for the daily precipitation PDFs, mean intensity and, to a lesser extent, the 95th percentile. A general improvement by the RCM11 models is also found when the data are upscaled and intercompared at the 0.44° and 1.5° resolutions. For some regions the RCM11 ensemble overestimates the occurrence of very high intensity events while for one region the models underestimate the occurrence of the most intense extremes. The RCM11 ensemble still shows a general tendency to underestimate the dry day frequency and 95th percentile of dry spell length over wetter regions, with only a marginal improvement compared to the lower resolution models. This indicates that the problem of the excessive production of low precipitation events found

  15. Climatic changes of extreme precipitation in Denmark from 1874 to 2100

    DEFF Research Database (Denmark)

    Arnbjerg-Nielsen, Karsten; Gregersen, Ida Bülow; Sunyer Pinya, Maria Antonia

    2014-01-01

    and intensity of extreme precipitation events in a changing climate are needed. Additionally, it is equally important to understand the natural variation on which the anthropogenic changes are imposed. This study presents the results of a coordinated effort to estimate the changes and uncertainties in Danish...... with a cycle of 25-35 years, a behavior that can in part be explained by sea level pressure differences over the Atlantic. Projections based on the historical observations suggest that precipitation extremes in the Eastern part of Denmark should have been ascending in the last two decades. However...... are discussed. Accounting for the uncertainty introduced by these factors a 10-year event is expected to increase by 30% over a projection period of 100 years. This is less than the variation within one natural oscillation cycle, indicating that it is crucial to understand and account for the future multi...

  16. On the importance of observational data properties when assessing regional climate model performance of extreme precipitation

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Sørup, Hjalte Jomo Danielsen; Christensen, Ole Bøssing

    2013-01-01

    In recent years, there has been an increase in the number of climate studies addressing changes in extreme precipitation. A common step in these studies involves the assessment of the climate model performance. This is often measured by comparing climate model output with observational data....... In the majority of such studies the characteristics and uncertainties of the observational data are neglected. This study addresses the influence of using different observational datasets to assess the climate model performance. Four different datasets covering Denmark using different gauge systems and comprising...... both networks of point measurements and gridded datasets are considered. Additionally, the influence of using different performance indices and metrics is addressed. A set of indices ranging from mean to extreme precipitation properties is calculated for all the datasets. For each of the observational...

  17. The Influence of Tropical Forcing on Westerly Disturbances: Implications for Extreme Precipitation in High Asia

    Science.gov (United States)

    Cannon, F.; Carvalho, L. V.; Jones, C.; Norris, J.; Kiladis, G. N.; Hoell, A.

    2015-12-01

    Extratropical cyclones, including winter westerly disturbances (WD) over central Asia, are fundamental features of the atmosphere that redistribute energy, momentum, and moisture from global to regional scales. Within the Karakoram and western Himalaya (KH), snowfall from only a few WD each winter maintains the region's snowpack and its vast network of glaciers, which seasonally melt to sustain water resources for downstream populations across Asia. WD activity and subsequent precipitation in the mountains are influenced by global atmospheric variability and tropical-extratropical interactions. This research explores the independent influences of the Madden Julian Oscillation (MJO) and El Niño Southern Oscillation on WD and extreme precipitation events in the KH. On interannual time-scales, El Niño suppresses convection in the Indian Ocean and induces a Rossby wave response over Southwest Asia that is linked with enhanced dynamical forcing of WD and available moisture content. Consequently, extreme orographic precipitation events are more frequent during El Niño than La Niña or neutral conditions. A similar spatial pattern of tropical diabatic heating anomalies is produced by the MJO at intraseasonal scales. In comparison to El Niño, the Rossby wave response to MJO activity is less spatially uniform over southwest Asia and exists on a much shorter time-scale. Consequently, this mode's relationship with WD behavior and KH precipitation is more complex. Phases of the MJO propagation cycle that favor the dynamical enhancement of WD simultaneously suppress available moisture over southwest Asia, and vice versa. As a result, extreme precipitation events in the KH occur with similar frequency in most phases of the MJO, however, the relative importance of the dynamic and thermodynamic components of WD to orographic precipitation in the KH transitions as the MJO propagates. These findings give insight into the dynamics and predictability of extreme precipitation

  18. Temperature and extreme rainfalls on France in a climatic change scenario; Temperature et precipitations extremes sur la france dans un scenario de changement climatique

    Energy Technology Data Exchange (ETDEWEB)

    Deque, M

    2007-07-01

    Impact of an anthropogenic climate change scenario on the frequency distribution of temperature and precipitation over France is studied with a numerical simulation calibrated with observed daily data from the synoptic network. (author)

  19. Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

    Science.gov (United States)

    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

  20. A hierarchical Bayesian spatio-temporal model for extreme precipitation events

    KAUST Repository

    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..

  1. Attributing extreme precipitation in the Black Sea region to sea surface warming

    Science.gov (United States)

    Meredith, Edmund; Semenov, Vladimir; Maraun, Douglas; Park, Wonsun; Chernokulsky, Alexander

    2016-04-01

    Higher sea surface temperatures (SSTs) warm and moisten the overlying atmosphere, increasing the low-level atmospheric instability, the moisture available to precipitating systems and, hence, the potential for intense convective systems. Both the Mediterranean and Black Sea regions have seen a steady increase in summertime SSTs since the early 1980s, by over 2 K in places. This raises the question of how this SST increase has affected convective precipitation extremes in the region, and through which mechanisms any effects are manifested. In particular, the Black Sea town of Krymsk suffered an unprecedented precipitation extreme in July 2012, which may have been influenced by Black Sea warming, causing over 170 deaths. To address this question, we adopt two distinct modelling approaches to event attribution and compare their relative merits. In the first, we use the traditional probabilistic event attribution approach involving global climate model ensembles representative of the present and a counterfactual past climate where regional SSTs have not increased. In the second, we use the conditional event attribution approach, taking the 2012 Krymsk precipitation extreme as a showcase example. Under the second approach, we carry out ensemble sensitivity experiments of the Krymsk event at convection-permitting resolution with the WRF regional model, and test the sensitivity of the event to a range of SST forcings. Both experiments show the crucial role of recent Black Sea warming in amplifying the 2012 Krymsk precipitation extreme. In the conditional event attribution approach, though, the explicit simulation of convective processes provides detailed insight into the physical mechanisms behind the extremeness of the event, revealing the dominant role of dynamical (i.e. static stability and vertical motions) over thermodynamical (i.e. increased atmospheric moisture) changes. Additionally, the wide range of SST states tested in the regional setup, which would be

  2. 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

    This study presents the results of a coordinated effort to estimate past, present and future changes and uncertainties in Danish design rainfall for urban drainage systems. The performed analyses cover long historical precipitation records, observations from a high‐resolution rain‐gauge network, ...... and changes driven by the anthropogenic forcing is still to be better understood. However, the generated knowledge can assist the design of robust adaptation measures for changes in pluvial flood risk.......This study presents the results of a coordinated effort to estimate past, present and future changes and uncertainties in Danish design rainfall for urban drainage systems. The performed analyses cover long historical precipitation records, observations from a high‐resolution rain‐gauge network...... are considered effects of anthropogenic climate change. The increase in precipitation extremes has led to inundations in most of the larger cities during the last 10 years. To establish cities that are resilient to pluvial floods, robust projections of the frequency and intensity of extreme precipitation events...

  3. Comparing Evaporative Sources of Terrestrial Precipitation and Their Extremes in MERRA Using Relative Entropy

    Science.gov (United States)

    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.

  4. Multi-method attribution analysis of extreme precipitation in Boulder, Colorado

    Science.gov (United States)

    Eden, Jonathan M.; Wolter, Klaus; Otto, Friederike E. L.; van Oldenborgh, Geert Jan

    2016-12-01

    Understanding and attributing the characteristics of extreme events that lead to societal impacts is a key challenge in climate science. Detailed analysis of individual case studies is particularly important in assessing how anthropogenic climate change is changing the likelihood of extreme events and their associated risk at relevant spatial scales. Here, we conduct a comprehensive multi-method attribution analysis of the heavy precipitation that led to widespread flooding in Boulder, Colorado in September 2013. We provide clarification on the source regions of moisture associated with this event in order to highlight the difficulty of separating dynamic and thermodynamic contributions. Using extreme value analysis of, first of all, historical observations, we then assess the influence of anthropogenic climate change on the overall likelihood of one- and five-day precipitation events across the Boulder area. The same analysis is extended to the output of two general circulation model ensembles. By combining the results of different methods we deduce an increase in the likelihood of extreme one-day precipitation but of a smaller magnitude than what would be expected in a warming world according to the Clausius-Clapeyron relation. For five-day extremes, we are unable to detect a change in likelihood. Our results demonstrate the benefits of a multi-method approach to making robust statements about the anthropogenic influence on changes in the overall likelihood of such an event irrespective of its cause. We note that, in this example, drawing conclusions solely on the basis of thermodynamics would have overestimated the increase in risk.

  5. Projection of extreme precipitation in the context of climate change in Huang-Huai-Hai region, China

    Indian Academy of Sciences (India)

    Jun Yin; Denghua Yan; Zhiyong Yang; Zhe Yuan; Yong Yuan; Cheng Zhang

    2016-03-01

    Based on the national precipitation dataset (0.5$^{\\circ }$ × 0.5$^{\\circ }$) 1961–2011, published by the National Meteorological Information Center of China and the five Global Climate Models provided by ISI-MIP, annual maximum precipitation for 1 day, 3 days and 7 days could be calculated. Extreme precipitation was fitted via Generalized Extreme Value (GEV) distribution to explore the changes of extreme precipitation with the return period of 20 years and 50 years during 1961–2000 and 2001–2050. Based on this, extreme precipitation projection in Huang-Huai-Hai region was done. The results showed that the five Global Climate Models could simulate the statistical features of extreme precipitation quite well, in which IPSL-CM5A-LR has the highest precision. Simulation of IPSL-CM5A-LR indicates that precipitation with the return period of 20 years and 50 years in the middle reaches of the Yellow River, middle and lower reaches of Huaihe River and plain area of the southern Haihe River will increase considerably in the future. Extreme precipitation in some of the places will even increase by more than 30%, which means that these places will face larger flood risk and their capacity to respond to flood disasters should be improved.

  6. On the variability of return periods of European winter precipitation extremes over the last five centuries

    Directory of Open Access Journals (Sweden)

    A. Pauling

    2006-04-01

    Full Text Available We investigate the changes of extreme European winter (December–February precipitation over the last half millennium and show for various European regions that return periods of extremely wet and dry winters are subject to significant changes both before and after the onset of anthropogenic influences. Additionally, we examine the spatial pattern of the changes of the extremes covering the last 300 years where data quality is sufficient. Over central and eastern Europe dry winters occurred more frequently during the 18th and the second part of the 19th century relative to 1951–2000. Dry winters were less frequent during both the 18th and 19th century over the British Isles and the Mediterranean. Wet winters have been less abundant during the last three centuries compared to 1951–2000 except during the early 18th century in central Europe. Although winter precipitation extremes are affected by climate change, no obvious connection of these changes was found to solar, volcanic or anthropogenic forcing. However, physically meaningful interpretation with atmospheric circulation changes was possible.

  7. Back to the Future -Precipitation Extremes, Climate Variability, Environmental Planning and Adaptation

    Science.gov (United States)

    Barros, A. P.

    2008-12-01

    --"The last major climatic oscillation peak was about 1856, or 74 years ago. Practically all of our important railroad and public highway work has been done since that time. Most of our parks systems driveways, and roads of all type for auto travel, in the various States, have been completed within the past 30 years, namely, beginning at the very lowest point of our climatic swing (1900-1910). There is every reason to believe, therefore, as the next 20 years comes on apace, we will witness considerable damage to work done during the past regime of weather."-- Schuman, 1931 At the beginning of the 21st century, as at the beginning of the 20th century, the fundamental question is whether the nation is more prepared for natural disasters today than it was eight decades ago. Indeed, the question is whether the best science, engineering and policy tools are in place to prepare for and respond to extreme events. Changes in the risk and magnitude of extreme precipitation events rank among the most studied impacts, and indicators (symptoms) of climatic variations. Extreme precipitation translates generally into extreme flooding, landslides, collapse of lifeline infrastructure, and the breakdown of public health services among others. In approaching the problem of quantifying the risk and magnitude of extreme precipitation events, there are two major challenges: 1) it is difficult to characterize "observed" (20th century) conditions due to the lack of long-term observations - i.e., short and incomplete historical records; and 2) it is difficult to characterize "predicted" (21st century) conditions due to the lack of skill of precipitation forecasts at spatial and temporal scales meaningful for impact studies, and the short-duration of climate model simulations themselves. The first challenge translates in estimating the probability of occurrence (rare) and magnitude (very large) of events that may have not happened yet. The second challenge is that of quantifying

  8. A European daily high-resolution gridded dataset of surface temperature and precipitation for 1950-2006

    NARCIS (Netherlands)

    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

  9. A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006

    NARCIS (Netherlands)

    Haylock, M.R.; Hofstra, N.; Klein Tank, A.M.G.; Klok, E.J.; Jones, P.D.; 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

  10. Building hazard maps of extreme daily rainy events from PDF ensemble, via REA method, on Senegal River Basin

    Directory of Open Access Journals (Sweden)

    J. D. Giraldo

    2011-04-01

    Full Text Available The Sudano-Sahelian zone of West Africa, one of the poorest of the Earth, is characterized by high rainfall variability and rapid population growth. In this region, heavy storm events frequently cause extensive damage. Nonetheless, the projections for change in extreme rainfall values have shown a great divergence between Regional Climate Models (RCM, increasing the forecast uncertainty. Novel methodologies should be applied, taking into account both the variability provided by different RCMs, as well as the non-stationary nature of time series for the building of hazard maps of extreme rainfall events. The present work focuses in the probability density functions (PDFs-based evaluation and a simple quantitative measure of how well each RCM considered can capture the observed annual maximum daily rainfall (AMDR series on the Senegal River basin. Since meaningful trends have been detected in historical rainfall time series for the region, non-stationary probabilistic models were used to fit the PDF parameters to the AMDR time series. In the development of PDF ensemble by bootstrapping techniques, Reliability Ensemble Averaging (REA maps were applied to score the RCMs. The REA factors were computed using a metric to evaluate the agreement between observed -or best estimated- PDFs, and that simulated with each RCM. The assessment of plausible regional trends associated to the return period, from the hazard maps of AMDR, showed a general rise, owing to an increase in the mean and the variability of extreme precipitation. These spatial-temporal distributions could be considered by local stakeholders in such a way as to reach a better balance between mitigation and adaptation.

  11. Building hazard maps of extreme daily rainy events from PDF ensemble, via REA method, on Senegal River Basin

    Directory of Open Access Journals (Sweden)

    J. D. Giraldo Osorio

    2011-11-01

    Full Text Available The Sudano-Sahelian zone of West Africa, one of the poorest of the Earth, is characterized by high rainfall variability and rapid population growth. In this region, heavy storm events frequently cause extensive damage. Nonetheless, the projections for change in extreme rainfall values have shown a great divergence between Regional Climate Models (RCM, increasing the forecast uncertainty. Novel methodologies should be applied, taking into account both the variability provided by different RCMs, as well as the non-stationary nature of time series for the building of hazard maps of extreme rainfall events. The present work focuses on the probability density functions (PDFs-based evaluation and a simple quantitative measure of how well each RCM considered can capture the observed annual maximum daily rainfall (AMDR series on the Senegal River basin. Since meaningful trends have been detected in historical rainfall time series for the region, non-stationary probabilistic models were used to fit the PDF parameters to the AMDR time series. In the development of PDF ensemble by bootstrapping techniques, Reliability Ensemble Averaging (REA maps were applied to score the RCMs. The REA factors were computed using a metric to evaluate the agreement between observed -or best estimated- PDFs, and that simulated with each RCM. The assessment of plausible regional trends associated to the return period, from the hazard maps of AMDR, showed a general rise, owing to an increase in the mean and the variability of extreme precipitation. These spatial-temporal distributions could be considered by Organization for the Development of the Senegal River (Organisation pour la mise en valeur du fleuve Sénégal, OMVS, in such a way as to reach a better balance between mitigation and adaptation.

  12. Building hazard maps of extreme daily rainy events from PDF ensemble, via REA method, on Senegal River Basin

    Science.gov (United States)

    Giraldo Osorio, J. D.; García Galiano, S. G.

    2011-11-01

    The Sudano-Sahelian zone of West Africa, one of the poorest of the Earth, is characterized by high rainfall variability and rapid population growth. In this region, heavy storm events frequently cause extensive damage. Nonetheless, the projections for change in extreme rainfall values have shown a great divergence between Regional Climate Models (RCM), increasing the forecast uncertainty. Novel methodologies should be applied, taking into account both the variability provided by different RCMs, as well as the non-stationary nature of time series for the building of hazard maps of extreme rainfall events. The present work focuses on the probability density functions (PDFs)-based evaluation and a simple quantitative measure of how well each RCM considered can capture the observed annual maximum daily rainfall (AMDR) series on the Senegal River basin. Since meaningful trends have been detected in historical rainfall time series for the region, non-stationary probabilistic models were used to fit the PDF parameters to the AMDR time series. In the development of PDF ensemble by bootstrapping techniques, Reliability Ensemble Averaging (REA) maps were applied to score the RCMs. The REA factors were computed using a metric to evaluate the agreement between observed -or best estimated- PDFs, and that simulated with each RCM. The assessment of plausible regional trends associated to the return period, from the hazard maps of AMDR, showed a general rise, owing to an increase in the mean and the variability of extreme precipitation. These spatial-temporal distributions could be considered by Organization for the Development of the Senegal River (Organisation pour la mise en valeur du fleuve Sénégal, OMVS), in such a way as to reach a better balance between mitigation and adaptation.

  13. Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

    Science.gov (United States)

    Sunyer, M. A.; Hundecha, Y.; Lawrence, D.; Madsen, H.; Willems, P.; Martinkova, M.; Vormoor, K.; Bürger, G.; Hanel, M.; Kriaučiūnienė, J.; Loukas, A.; Osuch, M.; Yücel, I.

    2015-04-01

    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, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods (SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), 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 in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the SDMs vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates 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 for the selection of the most suitable SDMs to include in the analysis.

  14. Simulation of daily streamflow for nine river basins in eastern Iowa using the Precipitation-Runoff Modeling System

    Science.gov (United States)

    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.

  15. Projected changes in mean and extreme precipitation indices over India using PRECIS

    Science.gov (United States)

    Rao, K. Koteswara; Patwardhan, S. K.; Kulkarni, Ashwini; Kamala, K.; Sabade, S. S.; Kumar, K. Krishna

    2014-02-01

    The impact of global warming on the characteristics of mean and extremes of rainfall over India is investigated using a high resolution regional climate model PRECIS developed by Hadley Centre, UK. Five simulations of PRECIS made using the lateral boundary conditions from a suite of Perturbed Physics Ensembles (PPE) generated using Hadley Center Coupled Model (HadCM3) for Quantifying Uncertainty in Model Predictions (QUMP) project corresponding to IPCC A1B emission scenario have been analyzed here for this purpose. The projected changes depict seasonally dependent fine scale structure in response to the topographic forcing and changes in circulation, especially along the west coast and North East (NE) region of India towards the end of the 21st century i.e. 2080s (2071-2098). Analysis of the extreme precipitation indices indicates an increase in the intensity of rainfall on wet days towards 2080s under A1B scenario. Changes in extreme precipitation events and dry spells suggest not only shifts, but also a substantial increase in the spread of the precipitation distribution, with an increased probability of the occurrence of events conducive to both floods and droughts. The projected changes in various precipitation extremes show a large regional variability. Total rainfall on very heavy rainy days (R95p) is projected to increase by around 40-50% over the central parts of the country. The number of rainy days > 10 mm (R10) may increase by 10-20% over west coast, east central India and northeastern parts while over northwest and rain shadow region they may increase by 40-50%. The consecutive dry days (CDDs) may decrease by 10-20% over Indo-Gangetic plain, however over west coast there may not be any significant change. The CDDs are projected to rise by 10-20% over west central and peninsular India. The precipitation per wet day (SDII) may be more intense by 10-40% over the entire land mass, however there may not be any significant change over south peninsular India.

  16. Towards near-real time daily GRACE gravity field solutions for global monitoring of hydrological extremes

    Science.gov (United States)

    Gouweleeuw, B.; Kvas, A.; Gruber, C.; Schumacher, M.; Mayer-Gürr, T.; Flechtner, F.; Kusche, J.; Guntner, A.

    2016-12-01

    Water storage anomalies from the Gravity Recovery and Climate Experiment (GRACE) satellite mission (2002-present) have been shown to be a unique descriptor of large-scale hydrological extreme events. However, possibly due to its coarse temporal (weekly to monthly), spatial (> 150.000 km2) resolution and the latency of standard products of about 2 months, the comprehensive information from GRACE on total water storage variations has rarely been evaluated for near-real time flood or drought monitoring or forecasting so far. The Horizon 2020 funded EGSIEM (European Gravity Service for Improved Emergency Management) project is scheduled to launch a near-real time test run of GRACE gravity field data, which will provide daily solutions with a latency of 5 days. This fast availability allows the monitoring of total water storage variations related to hydrological extreme events as they occur, as opposed to a 'confirmation after occurrence', which is the current situation. A first hydrological evaluation of daily GRACE gravity field solutions for floods in the Ganges-Brahmaputra Delta in 2004 and 2007 confirms their potential for gravity-based large-scale flood monitoring. This particularly applies to short-lived, high-volume floods, as they occur in Bangladesh with a 4-5 year return period. The subsequent assimilation of daily GRACE data into a (global) hydrological model - carried out jointly within the framework of the Belmont Forum funded BanD-AID project - decomposes total water storage into its individual components (e.g., surface water), increases the spatial resolution and opens up the possibility of flood early warning and forecasting.

  17. Projected changes to short- and long-duration precipitation extremes over the Canadian Prairie Provinces

    Science.gov (United States)

    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

  18. Projected changes to short- and long-duration precipitation extremes over the Canadian Prairie Provinces

    Science.gov (United States)

    Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

    2016-10-01

    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

  19. Quantifying the daily economic impact of extreme space weather due to failure in electricity transmission infrastructure

    Science.gov (United States)

    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.

  20. A current precipitation index-based model for continuous daily runoff simulation in seasonally snow covered sub-arctic catchments

    Science.gov (United States)

    Akanegbu, Justice O.; Marttila, Hannu; Ronkanen, Anna-Kaisa; Kløve, Bjørn

    2017-02-01

    A new precipitation index-based model, which includes a snow accumulation and melt component, has been developed to simulate hydrology in high latitude catchments. The model couples a point snowmelt model with a current precipitation index (CPI) formulation to simulate continuous daily runoff from catchments with seasonal snow cover. A new runoff conversion factor: CT and Lf, threshold flow factor ThQ and runoff transformation function Maxbas were introduced into the CPI equation, which converts and transforms the routed daily CPI into daily runoff and maintains the daily base flow in the catchment. The model was developed using twelve sub-arctic boreal catchments located above and below the Arctic Circle in northern Finland, representing a region with considerable seasonal snow cover. The results showed that the model can adequately simulate and produce the dynamics of daily runoff from catchments where the underlying physical conditions are not known. An open-access Excel-based model is provided with this paper for daily runoff simulations. The model can be used to estimate runoff in sub-arctic regions where little data is typically available but significant changes in climate are expected, with considerable shifts in the amount and timing of snowmelt and runoff.

  1. 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.

  2. Assessing the characteristics of extreme precipitation over northeast China using the multifractal detrended fluctuation analysis

    Science.gov (United States)

    Du, Haibo; Wu, Zhengfang; Zong, Shengwei; Meng, Xiangjun; Wang, Lei

    2013-06-01

    Extreme climate events have inflicted severe and adverse effects on human life, social economy, and natural ecosystems. In this study, the precipitation time series from a network of 90 weather stations in Northeast China (NEC) and for the period of 1961-2009 are used. An objective method, the multifractal detrended fluctuation analysis method, is applied to determine the thresholds of extreme events. Notable occurrence frequency and strong intensity of extreme precipitation (EP) mainly occur in Liaoning Province and the piedmont regions in Changbai Mountains and Xiao Hinggan Mountains. Generally, EP frequency shows a nonsignificant negative trend, whereas EP intensity has a weak and nonsignificant positive trend for the entire NEC in the period of 1961-2009. To assess EP severity, we propose an EP severity index (EPSI) combining both EP frequency and intensity, rather than separately analyze the EP frequency or intensity. Spatial gradients of EPSI are observed in northeast-southwest and northwest-southeast directions over NEC. The EPSI in northwestern and southeastern NEC are low (0.02-0.3), whereas high EPSI (0.34-0.83) occurs in the southwestern and northeastern portions of the region. Higher EPSI (0.4-0.83) occurs in southern Liaoning Province, which decreases along the southwest-northeast direction. The spatial patterns of EPSI are associated with the circulation over East Asia. Areas that have a short distance from sea and that locate in the windward slope of mountain will probably accompany high EP severity over NEC.

  3. Impact of temperature and precipitation extremes on the flowering dates of four German wildlife shrub species

    Science.gov (United States)

    Siegmund, Jonatan F.; Wiedermann, Marc; Donges, Jonathan F.; Donner, Reik V.

    2016-10-01

    Ongoing climate change is known to cause an increase in the frequency and amplitude of local temperature and precipitation extremes in many regions of the Earth. While gradual changes in the climatological conditions have already been shown to strongly influence plant flowering dates, the question arises if and how extremes specifically impact the timing of this important phenological phase. Studying this question calls for the application of statistical methods that are tailored to the specific properties of event time series. Here, we employ event coincidence analysis, a novel statistical tool that allows assessing whether or not two types of events exhibit similar sequences of occurrences in order to systematically quantify simultaneities between meteorological extremes and the timing of the flowering of four shrub species across Germany. Our study confirms previous findings of experimental studies by highlighting the impact of early spring temperatures on the flowering of the investigated plants. However, previous studies solely based on correlation analysis do not allow deriving explicit estimates of the strength of such interdependencies without further assumptions, a gap that is closed by our analysis. In addition to direct impacts of extremely warm and cold spring temperatures, our analysis reveals statistically significant indications of an influence of temperature extremes in the autumn preceding the flowering.

  4. CPLFD-GDPT5: High-resolution gridded daily precipitation and temperature data set for two largest Polish river basins

    Science.gov (United States)

    Berezowski, Tomasz; Szcześniak, Mateusz; Kardel, Ignacy; Michałowski, Robert; Okruszko, Tomasz; Mezghani, Abdelkader; Piniewski, Mikołaj

    2016-03-01

    The CHASE-PL (Climate change impact assessment for selected sectors in Poland) Forcing Data-Gridded Daily Precipitation & Temperature Dataset-5 km (CPLFD-GDPT5) consists of 1951-2013 daily minimum and maximum air temperatures and precipitation totals interpolated onto a 5 km grid based on daily meteorological observations from the Institute of Meteorology and Water Management (IMGW-PIB; Polish stations), Deutscher Wetterdienst (DWD, German and Czech stations), and European Climate Assessment and Dataset (ECAD) and National Oceanic and Atmosphere Administration-National Climatic Data Center (NOAA-NCDC) (Slovak, Ukrainian, and Belarusian stations). The main purpose for constructing this product was the need for long-term aerial precipitation and temperature data for earth-system modelling, especially hydrological modelling. The spatial coverage is the union of the Vistula and Oder basins and Polish territory. The number of available meteorological stations for precipitation and temperature varies in time from about 100 for temperature and 300 for precipitation in the 1950s up to about 180 for temperature and 700 for precipitation in the 1990s. The precipitation data set was corrected for snowfall and rainfall under-catch with the Richter method. The interpolation methods were kriging with elevation as external drift for temperatures and indicator kriging combined with universal kriging for precipitation. The kriging cross validation revealed low root-mean-squared errors expressed as a fraction of standard deviation (SD): 0.54 and 0.47 for minimum and maximum temperature, respectively, and 0.79 for precipitation. The correlation scores were 0.84 for minimum temperatures, 0.88 for maximum temperatures, and 0.65 for precipitation. The CPLFD-GDPT5 product is consistent with 1971-2000 climatic data published by IMGW-PIB. We also confirm good skill of the product for hydrological modelling by performing an application using the Soil and Water Assessment Tool (SWAT) in the

  5. Detecting changes in future precipitation extremes over eight river basins in China using RegCM4 downscaling

    Science.gov (United States)

    Qin, Peihua; Xie, Zhenghui

    2016-06-01

    To detect the frequency and intensity of precipitation extremes in China for the middle 21st century, simulations were conducted with the regional climate model RegCM4 forced by the global climate model GFDL_ESM2M under the middle emission scenario (RCP4.5). Compared with observed precipitation extremes for the reference period from 1982 to 2001, RegCM4 generally performed better in most river basins of China relative to GFDL. In the future period 2032-2051, more wet extremes will occur relative to the present period in most study areas, especially in southeast China while significantly less dry extremes will occur in arid and semiarid areas in northwest China. In contrast, areas in northwest China showed an increase in the trend of dry extremes (CDD) and a decrease in the trend of wet extremes (R95p and Rx5day), which might result in more drought in the future. Finally, we discuss in detail the possible reason of these processes, such as zonal wind, vertical wind, and water vapor. In the Huaihe river basin (HU), reduced south winds in summer (June-August) and a decrease of the upward vertical p velocity cause less future precipitation and might lead to changes of extreme events. We also completed correlation analysis between the precipitation extreme indices and the climate factors and found that the precipitation extremes were more sensitive to the annual and seasonal mean precipitation, total water vapor, and upward vertical wind relative to the geopotential height and 2 m temperature over most river basins in China. Perhaps the changes of some wet extremes could be verified partly through changes of annual precipitation due to their high consistence.

  6. Model design for predicting extreme precipitation event impacts on water quality in a water supply reservoir

    Science.gov (United States)

    Hagemann, M.; Jeznach, L. C.; Park, M. H.; Tobiason, J. E.

    2016-12-01

    Extreme precipitation events such as tropical storms and hurricanes are by their nature rare, yet have disproportionate and adverse effects on surface water quality. In the context of drinking water reservoirs, common concerns of such events include increased erosion and sediment transport and influx of natural organic matter and nutrients. As part of an effort to model the effects of an extreme precipitation event on water quality at the reservoir intake of a major municipal water system, this study sought to estimate extreme-event watershed responses including streamflow and exports of nutrients and organic matter for use as inputs to a 2-D hydrodynamic and water quality reservoir model. Since extreme-event watershed exports are highly uncertain, we characterized and propagated predictive uncertainty using a quasi-Monte Carlo approach to generate reservoir model inputs. Three storm precipitation depths—corresponding to recurrence intervals of 5, 50, and 100 years—were converted to streamflow in each of 9 tributaries by volumetrically scaling 2 storm hydrographs from the historical record. Rating-curve models for concentratoin, calibrated using 10 years of data for each of 5 constituents, were then used to estimate the parameters of a multivariate lognormal probability model of constituent concentrations, conditional on each scenario's storm date and streamflow. A quasi-random Halton sequence (n = 100) was drawn from the conditional distribution for each event scenario, and used to generate input files to a calibrated CE-QUAL-W2 reservoir model. The resulting simulated concentrations at the reservoir's drinking water intake constitute a low-discrepancy sample from the estimated uncertainty space of extreme-event source water-quality. Limiting factors to the suitability of this approach include poorly constrained relationships between hydrology and constituent concentrations, a high-dimensional space from which to generate inputs, and relatively long run

  7. Increase of record-breaking temperature and precipitation extremes in a warming world

    Science.gov (United States)

    Coumou, D.; Lehmann, J.; Robinson, A.; Rahmstorf, S.

    2011-12-01

    The last decade has seen many record-breaking weather events, including severe heat waves, as well as rainfall and drought extremes. At the same time, this decade was globally the warmest since accurate measurements started in the 19th century. This raises the question, often asked by public and media directly after the occurrence of a specific extreme, whether these extremes are related to global warming. Here we analyze record-breaking events in the last decade using global gridded datasets of monthly-mean surface temperature and precipitation. We compare the number of observed records with those expected in a stationary climate, for which the simple 1/n relationship holds, with n the number of previous data points (e.g. years). In addition, we develop a first-order theoretical model to quantify the respective contributions of climate change and natural variability to the occurrence of records. World wide the number of monthly heat records is now, on average 5 times larger than expected in a stationary climate. This indicates that record-breaking heat waves lasting for several weeks now have, on average, an 80% chance of being due to climatic warming. Some tropical regions including East-Africa, India and Amazonia have seen an even larger increase in the number of record breaking events, pushing the probability that a record event is due to climatic warming to more than 90%. The high number of observed records is well explained by a model assuming a linear warming over the last 40 years. Precipitation extremes are more complex than heat extremes as different physical processes associated with global warming are likely to affect them. Warmer air can hold more moisture and thus, in principle, enhances extremes in both rainfall maxima and minima. Also, changes in wind patterns will affect precipitation and it is expected that dry areas will become drier and wet areas wetter. We show that, globally averaged the number of observed records, both for minima and maxima

  8. TRMM precipitation analysis of extreme storms in South America: Bias and climatological contribution

    Science.gov (United States)

    Rasmussen, K. L.; Houze, R.; Zuluaga, M. D.; Choi, S. L.; Chaplin, M.

    2013-12-01

    The TRMM (Tropical Rainfall Measuring Mission) satellite was designed both to measure spatial and temporal variation of tropical rainfall around the globe and to understand the factors controlling the precipitation. TRMM observations have led to the realization that storms just east of the Andes in southeastern South America are among the most intense deep convection in the world. For a complete perspective of the impact of intense precipitation systems on the hydrologic cycle in South America, it is necessary to assess the contribution from various forms of extreme storms to the climatological rainfall. However, recent studies have suggested that the TRMM Precipitation Radar (PR) algorithm significantly underestimates surface rainfall in deep convection over land. Prior to investigating the climatological behavior, this research first investigates the range of the rain bias in storms containing four different types of extreme radar echoes: deep convective cores, deep and wide convective cores, wide convective cores, and broad stratiform regions over South America. The TRMM PR algorithm exhibits bias in all four extreme echo types considered here when the algorithm rates are compared to a range of conventional Z-R relations. Storms with deep convective cores, defined as high reflectivity echo volumes that extend above 10 km in altitude, show the greatest underestimation, and the bias is unrelated to their echo top height. The bias in wide convective cores, defined as high reflectivity echo volumes that extend horizontally over 1,000 km2, relates to the echo top, indicating that storms with significant mixed phase and ice hydrometeors are similarly affected by assumptions in the TRMM PR algorithm. The subtropical region tends to have more intense precipitating systems than the tropics, but the relationship between the TRMM PR rain bias and storm type is the same regardless of the climatological regime. The most extreme storms are typically not collocated with

  9. 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

    to inundations in most of the larger cities during the last 10 years; the flood in Copenhagen in 2011 implied the second highest damage costs measured in Denmark during the last 100 years. Hence much effort is directed at explaining the observed increase and to predict future occurrence rates and sizes...... from the structure we observe in historical networks of rain gauges. The results from the analysis will be combined with an analysis of non-stationary behavior in a network of gauges measuring daily precipitation from 1872 to present....

  10. Extreme monsoon precipitation events over South Asia in a warming world

    Science.gov (United States)

    Raghavan, K.; Sabin, T. P.; Mujumdar, M.; Priya, P.

    2012-04-01

    The recent series of flood events over Pakistan and Northwest India during the monsoon seasons of 2010 and 2011 are examples of extreme phenomena during the last century that have evoked considerable interest among various scientific communities. One of the causes for the 2010 intense precipitation over Pakistan has been attributed to the interaction between the tropical monsoon surge and southward intruding extra-tropical circulation anomalies (Hong et al. 2011). On the other hand, it has been hypothesized by Mujumdar et al. (2012) that the westward shift of the West Pacific Subtropical High (WPSH) in response to the strong La Nina conditions during 2010 was instrumental in altering the convection and circulation over the Bay of Bengal and the monsoon trough region, which in turn sustained the moist convective activities over Indo-Pak through transport of moisture from the Arabian Sea. However several aspects of the dynamics of these intense monsoon precipitation events are not adequately understood especially when atmospheric convective instabilities are expected to amplify in the backdrop of the ongoing global warming. Here, we have carried out a set of ensemble simulation experiments using a high-resolution global climate model to understand the evolution of intense monsoon precipitation events over Pakistan and Northwest India as in 2010. The results based on the model simulations indicate that while interactions among the WPSH, the South Asian monsoon trough and sub-tropical westerlies are conducive for development of convective instabilities over the Indo-Pak region, the local convective activities are found to significantly amplify in response to the large build up of moisture associated with global warming. The present results have implications in understanding how extreme monsoon precipitation events in the Indo-Pak region might have responded to past climatic variations.

  11. Multi-model projection of July-August climate extreme changes over China under CO2 doubling. Part I: Precipitation

    Science.gov (United States)

    Li, Hongmei; Feng, Lei; Zhou, Tianjun

    2011-03-01

    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) (1pctto2x) 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 1pctto2x 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.

  12. Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

    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...... be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates...

  13. Modelling precipitation extremes in the Czech Republic: update of intensity–duration–frequency curves

    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.

  14. Scaling and Intensification of Extreme Precipitation in High-Resolution Climate Change Simulations

    Science.gov (United States)

    Ban, Nikolina; Leutwyler, David; Lüthi, Daniel; Schär, Christoph

    2017-04-01

    Climate change projections of extreme precipitation are of great interest due to hydrological impacts such as droughts, floods, erosion, landslides and debris flows. Despite the trend towards dryer conditions over Europe, many climate simulations project increases of heavy precipitation events, while some theoretical studies have raised the possibility of dramatic increases in hourly events (by up to 14% per degree warming). However, conventional climate models are not suited to assess short-term heavy events due to the need to parameterize deep convection. High-resolution climate models with kilometer-scale grid spacing at which parameterization of convection can be switched off, significantly improve the simulation of heavy precipitation and can alter the climate change signal (e.g., Ban et al., 2015). Here we present decade-long high-resolution climate change simulations at horizontal resolution of 2.2 km over Europe on a computational domain with 1536x1536x60 grid points. These simulations have become feasible with a new version of the COSMO model that runs entirely on Graphics Processing Units. We compare a present-day climate simulation, driven by ERA-Interim reanalysis (Leutwyler at al., 2016), with a Pseudo-Global Warming (PGW) simulation The PGW simulation is driven by the slowly evolving mean seasonal cycle of the climate changes (derived from the CMIP5 model), superimposed on the ERA-Interim reanalysis. With this approach, the resulting changes are due to large scale warming of the atmosphere and due to slow-varying circulation changes. We will present the differences in climate change signal between conventional and high-resolution climate models, and discuss the thermodynamic effects on intensification of extreme precipitation. Ban N., J. Schmidli and C. Schär, 2015: Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster? Geophys. Res. Lett., 42 (4), 1165-1172 Leutwyler, D., D. Lüthi, N. Ban, O. Fuhrer and C

  15. Recent trends of extreme precipitation indices in the Iberian Peninsula using observations and WRF model results

    Science.gov (United States)

    Bartolomeu, S.; Carvalho, M. J.; Marta-Almeida, M.; Melo-Gonçalves, P.; Rocha, A.

    2016-08-01

    Spatial and temporal distributions of the trends of extreme precipitation indices were analysed between 1986 and 2005, over the Iberian Peninsula (IP). The knowledge of the patterns of extreme precipitation is important for impacts assessment, development of adaptation and mitigation strategies. As such, there is a growing need for a more detailed knowledge of precipitation climate change. This analysis was performed for Portuguese and Spanish observational datasets and results performed by the Weather Research and Forecast (WRF) model forced by the ERA-Interim reanalysis. Extreme precipitation indices recommended by the Expert Team for Climate Change Detection Monitoring and Indices were computed, by year and season. Then, annual and seasonal trends of the indices were estimated by Theil-Sen method and their significance was tested by the Mann-Kendal test. Additionally, a second simulation forced by the Max Planck Institute Earth System Model (MPI-ESM), was considered. This second modelling configuration was created in order to assess its performance when simulating extremes of precipitation. The annual trends estimated for the 1986-2005, from the observational datasets and from the ERA-driven simulation reveal: 1) negative statistically significant trends of the CWD index in the Galicia and in the centre of the IP; 2) positive statistically significant trends of the CDD index over the south of the IP and negative statistically significant trends in Galicia, north and centre of Portugal; 3) positive statistically significant trends of the R75p index in some regions of the north of the IP; 4) positive statistically significant trends in the R95pTOT index in the Central Mountains Chain, Leon Mountains and in the north of Portugal. Seasonally, negative statistically significant trends of the CWD index were found in Galicia, in winter and in the south of the IP, in summer. Positive statistically significant trends of the CWD index were identified in the Leon Mountains

  16. Estimating the exceedance probability of extreme rainfalls up to the probable maximum precipitation

    Science.gov (United States)

    Nathan, Rory; Jordan, Phillip; Scorah, Matthew; Lang, Simon; Kuczera, George; Schaefer, Melvin; Weinmann, Erwin

    2016-12-01

    If risk-based criteria are used in the design of high hazard structures (such as dam spillways and nuclear power stations), then it is necessary to estimate the annual exceedance probability (AEP) of extreme rainfalls up to and including the Probable Maximum Precipitation (PMP). This paper describes the development and application of two largely independent methods to estimate the frequencies of such extreme rainfalls. One method is based on stochastic storm transposition (SST), which combines the "arrival" and "transposition" probabilities of an extreme storm using the total probability theorem. The second method, based on "stochastic storm regression" (SSR), combines frequency curves of point rainfalls with regression estimates of local and transposed areal rainfalls; rainfall maxima are generated by stochastically sampling the independent variates, where the required exceedance probabilities are obtained using the total probability theorem. The methods are applied to two large catchments (with areas of 3550 km2 and 15,280 km2) located in inland southern Australia. Both methods were found to provide similar estimates of the frequency of extreme areal rainfalls for the two study catchments. The best estimates of the AEP of the PMP for the smaller and larger of the catchments were found to be 10-7 and 10-6, respectively, but the uncertainty of these estimates spans one to two orders of magnitude. Additionally, the SST method was applied to a range of locations within a meteorologically homogenous region to investigate the nature of the relationship between the AEP of PMP and catchment area.

  17. Comparison of extreme precipitation characteristics between the Ore Mountains and the Vosges Mountains (Europe)

    Science.gov (United States)

    Minářová, Jana; Müller, Miloslav; Clappier, Alain; Kašpar, Marek

    2017-08-01

    Understanding the characteristics of extreme precipitation events (EPEs) not only helps in mitigating the hazards associated with it but will also reduce the risks by improved planning based on the detailed information, and provide basis for better engineering decisions which can withstand the recurring and likely more frequent events predicted in future in the context of global climate change. In this study, extremity, temporal and spatial characteristics, and synoptic situation of the 54 EPEs that occurred during 1960-2013 were compared between two low mountain ranges situated in Central Europe: the Ore Mountains (OM) and Vosges Mountains (VG). The EPEs were defined using the Weather Extremity Index, which quantifies the extremity, duration, and spatial extent of events. Comparative analysis of EPE characteristics showed that in both regions the EPEs were mostly short (lasted 1-2 days) and their seasonal occurrence significantly depended on the synoptic situation and duration of EPEs; the low was related to summer short EPEs, while zonal circulation to winter long EPEs. The EPEs were generally related to lows in OM and to troughs in VG. The lows often moved to OM from the Mediterranean area, i.e. along the Vb track. However, five EPEs in VG occurred during a low with Vb track significantly deflected westwards. The EPEs in VG affected smaller area as compared to that in OM. The comparison of EPEs between the two low mountain ranges is first of its kind and contributes to the understanding of EPE characteristics in the regions.

  18. Evaluation of NASA's MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

    Science.gov (United States)

    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

  19. Scaling and trends of hourly precipitation extremes in two different climate zones – Hong Kong and the Netherlands

    Directory of Open Access Journals (Sweden)

    G. Lenderink

    2011-09-01

    Full Text Available Hourly precipitation extremes in very long time series from the Hong Kong Observatory and the Netherlands are investigated. Using the 2 m dew point temperature from 4 h before the rainfall event as a measure of near surface absolute humidity, hourly precipitation extremes closely follow a 14% per degree dependency – a scaling twice as large as following from the Clausius-Clapeyron relation. However, for dew point temperatures above 23 °C no significant dependency on humidity was found. Strikingly, in spite of the large difference in climate, results are almost identical in Hong Kong and the Netherlands for the dew point temperature range where both observational sets have sufficient data. Trends in hourly precipitation extremes show substantial increases over the last century for both De Bilt (the Netherlands and Hong Kong. For De Bilt, not only the long term trend, but also variations in hourly precipitation extremes on an inter-decadal timescale of 30 yr and longer, can be linked very well to the above scaling; there is a very close resemblance between variations in dew point temperature and precipitation intensity with an inferred dependency of hourly precipitation extremes of 10 to 14% per degree. For Hong Kong there is no connection between variations in humidity and those in precipitation intensity in the wet season, May to September. This is consistent with the found zero-dependency of precipitation intensity on humidity for dew points above 23 °C. Yet, outside the wet season humidity changes do appear to explain the positive trend in hourly precipitation extremes, again following a dependency close to twice the Clausius-Clapeyron relation.

  20. Spatiotemporal changes in precipitation extremes over Yangtze River basin, China, considering the rainfall shift in the late 1970s

    Science.gov (United States)

    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.

  1. Spatial analysis of extreme precipitation deficit as an index for atmospheric drought in Belgium

    Science.gov (United States)

    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

  2. Modelling of spatio-temporal precipitation relevant for urban hydrology with focus on scales, extremes and climate change

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen

    Time series of precipitation are necessary for assessment of urban hydrological systems. In a changed climate this is challenging as climate model output is not directly comparable to observations at the scales relevant for urban hydrology. The focus of this PhD thesis is downscaling...... of precipitation to spatio-temporal scales used in urban hydrology. It investigates several observational data products and identifies relevant scales where climate change and precipitation can be assessed for urban use. Precipitation is modelled at different scales using different stochastic techniques. A weather...... generator is used to produce an artificial spatio-temporal precipitation product that can be used both directly in large scale urban hydrological modelling and for derivation of extreme precipitation statistics relevant for urban hydrology. It is discussed why precipitation time series from a changed...

  3. Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

    Science.gov (United States)

    Lorenz, Ruth; Argüeso, Daniel; Donat, Markus G.; Pitman, Andrew J.; Hurk, Bart; Berg, Alexis; Lawrence, David M.; Chéruy, Frédérique; Ducharne, Agnès.; Hagemann, Stefan; Meier, Arndt; Milly, P. 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.

  4. Postprocessing of simulated precipitation for impact research in West Africa. Part II: A weather generator for daily data

    Science.gov (United States)

    Paeth, Heiko; Diederich, Malte

    2011-04-01

    Data from global and regional climate models refer to grid cells and, hence, are basically different from station data. This particularly holds for variables with enhanced spatio-temporal variability like precipitation. On the other hand, many applications like for instance hydrological models require atmospheric data with the statistical characteristics of station data. Here, we present a dynamical-statistical tool to construct virtual station data based on regional climate model output for tropical West Africa. This weather generator (WEGE) incorporates daily gridded rainfall from the model, an orographic term and a stochastic term, accounting for the chaotic spatial distribution of local rain events within a model grid box. In addition, the simulated probability density function of daily precipitation is adjusted to available station data in Benin. It is also assured that the generated data are still consistent with other model parameters like cloudiness and atmospheric circulation. The resulting virtual station data are in excellent agreement with various observed characteristics which are not explicitly addressed by the WEGE algorithm. This holds for the mean daily rainfall intensity and variability, the relative number of rainless days and the scaling of precipitation in time. The data set has already been used successfully for various climate impact studies in Benin.

  5. The use of geoinformatic data and spatial analysis to predict faecal pollution during extreme precipitation events

    Science.gov (United States)

    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

  6. Intensification of the regional scale variability of extreme precipitation derived from RCM simulations and observations

    Science.gov (United States)

    Feldmann, H.; Schädler, G.; Panitz, H.-J.

    2012-04-01

    Future climate change patterns are usually derived from ensembles of coarse global climate model simulations (GCMs), for instance within the Coupled Model Intercomparison Project (CMIP) or from regional climate projections at resolutions of some tens of km, for instance for Europe from the ENSEMBLES or PRUDENCE projects. For regions with complex topography like Central Europe the horizontal resolution of these climate projections is still too coarse to resolve the typical topographical length scales, and therefore the impact of the large scale changes with the regional geography cannot be captured adequately. For this task high resolution ensemble simulations with regional climate models (RCMs) are needed. The generation of an ensemble of such high resolution simulations requires great computational efforts. With the RCM COSMO-CLM several simulations with resolutions down to 7 km have been performed, using different driving GCMs and GCM realisations. This ensemble approach is needed to estimate the robustness of the change signals and to account for the uncertainties introduced by differences in the large scale forcing due to the variability of the climate change signals caused by the different GCMs or the natural variability. The focus of the study is on the changes of extreme precipitation for the near future until the middle of the 21st century. An increase of the temporal and spatial variability is found for the precipitation extremes, especially for summer. The change patterns seem to be statistically robust. Based on long-term observation climatologies for the second half of the 20th century, similar structures where found with areas of decrease and increase only a few tens of kilometres apart from each other. The combination of the findings from the RCM projections and observations suggests a continuation of the trends from the recent past into the near future. Possible causes for the horizontally heterogeneous change patterns are related to weather pattern

  7. Daily Precipitation Sums at Coastal and Island Russian Arctic Stations, 1940-1990

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains precipitation data originally recorded in log books at 65 coastal and island meteorological stations, and later digitized at the Arctic and...

  8. Response of Extreme Precipitation to Solar Activity and El Nino Events in Typical Regions of the Loess Plateau

    Directory of Open Access Journals (Sweden)

    H. J. Li

    2017-01-01

    Full Text Available Extreme climatic oscillation has been the subject of global attention. The purpose of this study is to explore the response of extreme precipitation to solar activity and El Nino events in typical regions of the Loess Plateau—a case study in the Yan’an area. The precipitation data was from nine weather stations in Yan’an and the sunspot number and the Southern Oscillation Index (SOI were from 1951 to 2015. The results show that maximum precipitation occurred mainly at the peak sunspot number or 2a near it and the sunspot number minimum and valley values were not significantly correlated. The results of Morlet wavelet showed that a 41-year period of precipitation was the most obvious within the 64-year scale. Similarly, sunspot number showed a 16-year periodic variability. Correlation analyses of the 16-year and 41-year scales demonstrated that the relationships between precipitation and sunspot number were close. In addition, extreme precipitation often occurred in the year following El Nino events. According to 10-year moving average curves, precipitation generally showed a downward trend when SOI was negative. The results indicate that solar activity and El Nino events had significant impacts on precipitation in typical regions of the Loess Plateau.

  9. The impact of ENSO and the NAO on extreme winter precipitation in North America in observations and regional climate models

    Science.gov (United States)

    Whan, Kirien; Zwiers, Francis

    2017-03-01

    The relationship between winter precipitation in North America and indices of the North Atlantic Oscillation (NAO) and El Niño-Southern Oscillation (ENSO) is evaluated using non-stationary generalized extreme value distributions with the indices as covariates. Both covariates have a statistically significant influence on precipitation that is well simulated by two regional climate models (RCMs), CanRCM4 and CRCM5. The observed influence of the NAO on extreme precipitation is largest in eastern North America, with the likelihood of a negative phase extreme rainfall event decreased in the north and increased in the south under the positive phase of the NAO. This pattern is generally well simulated by the RCMs although there are some differences in the extent of influence, particularly south of the Great Lakes. A La Niña-magnitude extreme event is more likely to occur under El Niño conditions in California and the southern United States, and less likely in most of Canada and a region south of the Great Lakes. This broad pattern is also simulated well by the RCMs but they do not capture the increased likelihood in California. In some places the extreme precipitation response in the RCMs to external forcing from a covariate is of the opposite sign, despite use of the same lateral boundary conditions and dynamical core. This demonstrates the importance of model physics for teleconnections to extreme precipitation.

  10. The impact of ENSO and the NAO on extreme winter precipitation in North America in observations and regional climate models

    Science.gov (United States)

    Whan, Kirien; Zwiers, Francis

    2016-05-01

    The relationship between winter precipitation in North America and indices of the North Atlantic Oscillation (NAO) and El Niño-Southern Oscillation (ENSO) is evaluated using non-stationary generalized extreme value distributions with the indices as covariates. Both covariates have a statistically significant influence on precipitation that is well simulated by two regional climate models (RCMs), CanRCM4 and CRCM5. The observed influence of the NAO on extreme precipitation is largest in eastern North America, with the likelihood of a negative phase extreme rainfall event decreased in the north and increased in the south under the positive phase of the NAO. This pattern is generally well simulated by the RCMs although there are some differences in the extent of influence, particularly south of the Great Lakes. A La Niña-magnitude extreme event is more likely to occur under El Niño conditions in California and the southern United States, and less likely in most of Canada and a region south of the Great Lakes. This broad pattern is also simulated well by the RCMs but they do not capture the increased likelihood in California. In some places the extreme precipitation response in the RCMs to external forcing from a covariate is of the opposite sign, despite use of the same lateral boundary conditions and dynamical core. This demonstrates the importance of model physics for teleconnections to extreme precipitation.

  11. Hadley Cell Variability and Extremes in Reanalysis Data: Links to Tropical and Subtropical Precipitating Systems

    Science.gov (United States)

    Stachnik, J. P.; Schumacher, C.

    2010-12-01

    The tropical Hadley circulation (HC, hereafter) accounts for the largest portion of global overturning in the meridional-vertical plane and is responsible for a significant redistribution of energy and heat throughout the global ocean-atmosphere system. The HC plays an important role in determining both local weather and climate (e.g., tropical rainfall patterns and suppression of precipitation in the subtropics) and can affect weather patterns at higher latitudes due to impacts on the general circulation. Reanalysis data is commonly used to study the behavior of the HC given the lack of observations over the tropical oceans, although previous studies have documented large discrepancies in the strength, location and latitudinal extent of the HC in older datasets. This study presents an HC climatology using multiple next generation and standard reanalysis datasets (including the ERA-Interim, ERA40, JRA25, NCEP/DOE and NCEP/NCAR). Variability in the long-term HC representation is quantified and explained by differences in the precipitation characteristics among datasets. Interannual variability and recent HC extremes are also explored with a new phenomenological approach, identifying changes in occurrence frequency and location of mesoscale precipitating systems as categorized by storm type (e.g., convective-stratiform, shallow-deep, etc.) using data collected by the Precipitation Radar (PR) onboard the TRMM satellite. Finally, satellite observations of storm type and other HC metrics derived from reanalysis are used to better elucidate HC latitudinal variability and determine those local areas of meridional overturning most important to comprising the zonal mean.

  12. Hydroclimatology of Extreme Precipitation and Floods Originating from the North Atlantic Ocean

    Science.gov (United States)

    Nakamura, Jennifer

    This study explores seasonal patterns and structures of moisture transport pathways from the North Atlantic Ocean and the Gulf of Mexico that lead to extreme large-scale precipitation and floods over land. Storm tracks, such as the tropical cyclone tracks in the Northern Atlantic Ocean, are an example of moisture transport pathways. In the first part, North Atlantic cyclone tracks are clustered by the moments to identify common traits in genesis locations, track shapes, intensities, life spans, landfalls, seasonal patterns, and trends. The clustering results of part one show the dynamical behavior differences of tropical cyclones born in different parts of the basin. Drawing on these conclusions, in the second part, statistical track segment model is developed for simulation of tracks to improve reliability of tropical cyclone risk probabilities. Moisture transport pathways from the North Atlantic Ocean are also explored though the specific regional flood dynamics of the U.S. Midwest and the United Kingdom in part three of the dissertation. Part I. Classifying North Atlantic Tropical Cyclones Tracks by Mass Moments. A new method for classifying tropical cyclones or similar features is introduced. The cyclone track is considered as an open spatial curve, with the wind speed or power information along the curve considered as a mass attribute. The first and second moments of the resulting object are computed and then used to classify the historical tracks using standard clustering algorithms. Mass moments allow the whole track shape, length and location to be incorporated into the clustering methodology. Tropical cyclones in the North Atlantic basin are clustered with K-means by mass moments producing an optimum of six clusters with differing genesis locations, track shapes, intensities, life spans, landfalls, seasonality, and trends. Even variables that are not directly clustered show distinct separation between clusters. A trend analysis confirms recent conclusions

  13. On regional dynamical downscaling for the assessment and projection of temperature and precipitation extremes across Tasmania, Australia

    Science.gov (United States)

    White, Christopher J.; McInnes, Kathleen L.; Cechet, Robert P.; Corney, Stuart P.; Grose, Michael R.; Holz, Gregory K.; Katzfey, Jack J.; Bindoff, Nathaniel L.

    2013-12-01

    The ability of an ensemble of six GCMs, downscaled to a 0.1° lat/lon grid using the Conformal Cubic Atmospheric Model over Tasmania, Australia, to simulate observed extreme temperature and precipitation climatologies and statewide trends is assessed for 1961-2009 using a suite of extreme indices. The downscaled simulations have high skill in reproducing extreme temperatures, with the majority of models reproducing the statewide averaged sign and magnitude of recent observed trends of increasing warm days and warm nights and decreasing frost days. The warm spell duration index is however underestimated, while variance is generally overrepresented in the extreme temperature range across most regions. The simulations show a lower level of skill in modelling the amplitude of the extreme precipitation indices such as very wet days, but simulate the observed spatial patterns and variability. In general, simulations of dry extreme precipitation indices are underestimated in dryer areas and wet extremes indices are underestimated in wetter areas. Using two SRES emissions scenarios, the simulations indicate a significant increase in warm nights compared to a slightly more moderate increase in warm days, and an increase in maximum 1- and 5- day precipitation intensities interspersed with longer consecutive dry spells across Tasmania during the twenty-first century.

  14. Max-stable based evaluation of impacts of climate indices on extreme precipitation processes across the Poyang Lake basin, China

    Science.gov (United States)

    Zhang, Qiang; Xiao, Mingzhong; Singh, Vijay P.; Chen, Yongqin David

    2014-11-01

    Monthly precipitation extremes defined by monthly maximum one-day precipitation amount (Rx1day) and maximum consecutive five-day precipitation amount (Rx5day) were analyzed based on daily precipitation data covering a period of 1957 to 2010 across the Poyang Lake basin, the largest freshwater lake basin in the lower Yangtze River basin, China. Based on the max-stable, impacts of El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO) on the annual and seasonal Rx1day and Rx5day regimes in the Poyang Lake basin were evaluated. Results indicated that annual Rx1day and Rx5day were influenced mainly by the ENSO events a year earlier and the relations between annual Rx1day and Rx5day and ENSO were statistically positive. However, influences of climate indices on the seasonal Rx1day and Rx5day are complicated when compared with the influences on annual Rx1day and Rx5day regimes. ENSO and PDO can enhance the spring Rx1day regime of the subsequent year and the same year, respectively, but IOD weakens spring Rx1day in the same year. In summer, ENSO can enhance Rx1day of the subsequent year. However, Rx1day in summer had a decreasing tendency. IOD and NAO influenced the autumn Rx1day in another way, i.e., IOD decreases autumn Rx1day of the subsequent year; while NAO enhances autumn Rx1day of the same year. Meanwhile, ENSO can amplify the summer Rx1day in terms of variability, while IOD and NAO can, respectively, influence autumn and winter Rx1day in terms of mean. Influences of climate indices on annual and seasonal Rx5day are similar to those on Rx1day. Results of this study are of great theoretical as well as practical merit in terms of evaluation of droughts and floods under the influences of climate indices.

  15. A new mean-extreme vector for the trends of temperature and precipitation over China during 1960-2013

    Science.gov (United States)

    Lyra, G. B.; Oliveira-Júnior, J. F.; Gois, G.; Cunha-Zeri, G.; Zeri, M.

    2016-06-01

    A mean-extreme (M-E) vector is defined to combine the changes of climate means and extremes. The direction of the vertical axis represents changes in means, whereas the direction of the horizontal axis represents changes in extremes. Therefore, the M-E vector can clearly reflect both the amplitude and direction of changes in climate means and extremes. Nine types of M-E vectors are defined. They are named as MuEu, MuEd, MuEz, MdEu, MdEd, MdEz, MzEu, MzEd, and MzEz. Here M and E stand for climate means and extremes, respectively, whereas u, d, and z indicate an upward, downward trend and no trend, respectively. Both temperature mean and extremely high temperature days are consistently increased (MuEu) in nearly whole China throughout four seasons. However, the MuEd-type vector dominates in some regions. The MuEd-type vector appears over the Huang Huai river basin in spring, summer and winter. For the M-E vector of temperature mean and extremely low temperature days, the MuEd-type spreads the entire China for all seasons. The M-E vector for precipitation mean and the extreme precipitation days possesses identical trends (MuEu or MdEd) despite of seasons. The MuEu-type dominates in northeastern China and west of 105°E in spring, northwestern and central/southern China in summer, west of 100°E and northeastern China in autumn, and nearly whole China in winter. Precipitation mean and extreme precipitation days are all decreased (MdEd) in the rest of China for all reasons. The trends relationship in means and extremes over China presented herein could provide a scientific foundation to predict change of extremes using change of mean as the predictor.

  16. West African monsoon intraseasonal activity and its daily precipitation indices in regional climate models: diagnostics and challenges

    Science.gov (United States)

    Poan, E. D.; Gachon, P.; Dueymes, G.; Diaconescu, E.; Laprise, R.; Seidou Sanda, I.

    2016-11-01

    The West African monsoon intraseasonal variability has huge socio-economic impacts on local populations but understanding and predicting it still remains a challenge for the weather prediction and climate scientific community. This paper analyses an ensemble of simulations from six regional climate models (RCMs) taking part in the coordinated regional downscaling experiment, the ECMWF ERA-Interim reanalysis (ERAI) and three satellite-based and observationally-constrained daily precipitation datasets, to assess the performance of the RCMs with regard to the intraseasonal variability. A joint analysis of seasonal-mean precipitation and the total column water vapor (also called precipitable water— PW) suggests the existence of important links at different timescales between these two variables over the Sahel and highlights the relevance of using PW to follow the monsoon seasonal cycle. RCMs that fail to represent the seasonal-mean position and amplitude of the meridional gradient of PW show the largest discrepancies with respect to seasonal-mean observed precipitation. For both ERAI and RCMs, spectral decompositions of daily PW as well as rainfall show an overestimation of low-frequency activity (at timescales longer than 10 days) at the expense of the synoptic (timescales shorter than 10 days) activity. Consequently, the effects of the African Easterly Waves and the associated mesoscale convective systems are substantially underestimated, especially over continental regions. Finally, the study investigates the skill of the models with respect to hydro-climatic indices related to the occurrence, intensity and frequency of precipitation events at the intraseasonal scale. Although most of these indices are generally better reproduced with RCMs than reanalysis products, this study indicates that RCMs still need to be improved (especially with respect to their subgrid-scale parameterization schemes) to be able to reproduce the intraseasonal variance spectrum adequately.

  17. Hourly storm characteristics along the U.S. West Coast: Role of atmospheric rivers in extreme precipitation

    Science.gov (United States)

    Lamjiri, Maryam A.; Dettinger, Michael; Ralph, F. Martin; Guan, B.

    2017-01-01

    Gridded hourly precipitation observations over the conterminous U.S., from 1948 to 2002, are analyzed to determine climatological characteristics of storm precipitation totals. Despite generally lower hourly intensities, precipitation totals along the U.S. West Coast (USWC) are comparable to those in southeast U.S. (SEUS). Storm durations, more so than hourly intensities, strongly modulate precipitation-total variability over the USWC, where the correlation coefficients between storm durations and storm totals range from 0.7 to 0.9. Atmospheric rivers (ARs) contribute 30–50% of annual precipitation on the USWC and make such large contributions to extreme storms that 60–100% of the most extreme storms, i.e., storms with precipitation-total return intervals longer than 2 years, are associated with ARs. These extreme storm totals are more strongly tied to storm durations than to storm hourly or average intensities, emphasizing the importance of AR persistence to extreme storms on the USWC.

  18. Effect of latent heating on mesoscale vortex development during extreme precipitation: Colorado, September 2013

    Science.gov (United States)

    Morales, Annareli

    From 9-16 September 2013, a slow-moving cut-off low in the southwestern U.S. funneled unseasonal amounts of moisture to the Colorado Front Range, resulting in extreme precipitation and flooding. The heaviest precipitation during the September 2013 event occurred over the northern Colorado Front Range, producing a 7-day total of over 380 mm of rain. The flash flooding caused over $3 billion in damage to property and infrastructure and resulted in eight fatalities. This study will focus on the precipitation and mesoscale features during 11-12 September 2013 in Boulder, CO. During the evening of 11 September, Boulder experienced flash flooding as a result of high rain rates accumulating over 180 mm of rain in 6 hours. From 0400-0700 UTC 12 September, a mesoscale vortex (mesovortex) was observed to travel northwestward towards Boulder. This circulation enhanced upslope flow and was associated with localized deep convection. The mesovortex originated in an area common for the development of a lee vortex known as the Denver Cyclone. We hypothesize that this mesoscale vortex is not associated with lee vortex formation, such as the Denver Cyclone, but developed through the release of latent heat from microphysical process. The Advanced Research Weather Research and Forecast (ARW) model was used to 1) produce a control simulation that properly represented the evolution and processes of interest during the event and 2) test the importance of latent heating to the development and evolution of the mesovortex. The results from various latent heating experiments suggested that the mesovortex did not develop through lee vortex formation and the latent heat released just before and during the mesovortex event was important to its development. Results also showed latent heating affected the flow field, resulting in a positive feedback between the circulation, associated low-level jet, and convection leading to further upslope flow and precipitation development. Further experiments

  19. 枣庄近44年汛期极端降水指数突变特征分析%Mutation Analysis of Extreme Precipitation Index in Nearly 44 Years at Zaozhuang

    Institute of Scientific and Technical Information of China (English)

    陈连侠; 赵勇; 鹿翠华; 张美玲; 褚涛

    2015-01-01

    为了建立气象枣庄站近1971-2014年汛期极端降水事件各指数的年时间序列,以1971-2000年枣庄58024站逐日降水资料为基础,通过定义95百分位点极端降水事件阈值,利用 m - k 和累积距平等方法对枣庄近44年汛期极端降水指数的突变特征进行分析。结果表明:枣庄汛期极端降水事件阈值为38.7 mm ,近44年枣庄汛期各极端降水指数具有不同的突变特点。日最大降水量在1997发生了增大性突变趋势,没有通过0.05显著性检验;极端降水日数没有发生突变;极端降水量与极端降水强度均发生了3次突变,21世纪以来极端降水量和极端降水强度均出现了增大趋势。日最大降水量、降水日数、降水强度的变化均可引起的极端降水量的变化,三者与降水量成较好的正相关,相关系数均达到了0.01的信度检验。%In order to establish Zaozhuang meteorological station of each index of nearly 1971 - 2014 in extreme precipi‐tation events in time series ,from 1971 to 2000 ,Zaozhuang 58024 stations daily precipitation data as the foundation , through the threshold of extreme precipitation events define 95 percentile using m - k and cumulative distance equal method in Zaozhuang in Recent 44 years in the flood season of extreme precipitation indices mutation characteristics were analyzed. The results showed that :the extreme precipitation events threshold of the flood season in Zaozhuang was 38.7mm ;and the extreme precipitation index of the flood season in Zaozhuang during the past 44 years had differ‐ent features of the mutated change. The maximum daily precipitation at 1997 increased in mutated trend ,it did not pass the significance test of 0.05 ;There was no mutation frequency of extreme precipitation ;Extreme precipitation and ex‐treme precipitation intensity had 3 mutations ,extreme precipitation and extreme precipitation intensity showed a trend of increase since 21

  20. Assessment of daily exposure of endodontic personnel to extremely low frequency magnetic fields.

    Science.gov (United States)

    Kim, D W; Choi, J L; Kwon, M K; Nam, T J; Lee, S J

    2012-08-01

    To measure daily exposure levels to extremely low frequency magnetic fields (ELF MFs) in endodontic clinics. In total, 10 subjects (five endodontic trainees, five hygienists) participated. Each volunteer wore a 60-Hz MF measurement device on the left upper arm during working hours. Measurements were taken continuously throughout the working day except at lunch time. Separate measurements were taken for specific items of equipment at several distances. The average MF exposure for the 10 personnel was 0.03±0.04micro-Tesla (μT) (range, 0.01-6.4μT). The average MF exposure of endodontic personnel was lower than that of other hospital personnel according to the literature. Furthermore, all monitored exposure levels were well below the maximum acute exposure level, 500μT, recommended by the International Committee on Non-ionizing Radiation Protection for the protection of workers against ELF MFs. However, relatively high levels of exposure occurred in an operating room and X-ray room, presumably as a result of the use of surgical equipment such as microscopes and monitors, various motors and power cables of X-ray machines with large current flows. The total average MF exposure level of 0.03μT was lower than the typical background level at home. Although high levels of exposure were measured in an operating room and X-ray room, the MF exposure level to dental personnel was minimal during routine endodontic clinical work. © 2012 International Endodontic Journal.

  1. Assessing upper extremity motor function in practice of virtual activities of daily living.

    Science.gov (United States)

    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.

  2. Stochastic spatial disaggregation of extreme precipitation to validate a Regional Climate Model and to evaluate climate change impacts over a small watershed

    Directory of Open Access Journals (Sweden)

    P. Gagnon

    2013-06-01

    Full Text Available Regional Climate Models (RCMs are valuable tools to evaluate impacts of climate change (CC at regional scale. However, as the size of the area of interest decreases, the ability of a RCM to simulate extreme precipitation events decreases due to the spatial resolution. Thus, it is difficult to evaluate whether a RCM bias on localized extreme precipitation is caused by the spatial resolution or by a misrepresentation of the physical processes in the model. Thereby, it is difficult to trust the CC impact projections for localized extreme precipitation. Stochastic spatial disaggregation models can bring the RCM precipitation data at a finer scale and reduce the bias caused by spatial resolution. In addition, disaggregation models can generate an ensemble of outputs, producing an interval of possible values instead of a unique discrete value. The objective of this work is to evaluate whether a stochastic spatial disaggregation model applied on annual maximum daily precipitation: (i enables the validation of a RCM for a period of reference, and (ii modifies the evaluation of CC impacts over a small area. Three simulations of the Canadian RCM (CRCM covering the period 1961–2099 are used over a small watershed (130 km2 located in southern Québec, Canada. The disaggregation model applied is based on Gibbs sampling and accounts for physical properties of the event (wind speed, wind direction, and convective available potential energy (CAPE, leading to realistic spatial distributions of precipitation. The results indicate that disaggregation has a significant impact on the validation. However it does not provide a precise estimate of the simulation bias because of the difference in resolution between disaggregated values (4 km and observations, and because of the underestimation of the spatial variability by the disaggregation model for the most convective events. Nevertheless, disaggregation permits to determine that the simulations used mostly

  3. Drought, deluge and declines: the impact of precipitation extremes on amphibians in a changing climate.

    Science.gov (United States)

    Walls, Susan C; Barichivich, William J; Brown, Mary E

    2013-03-11

    The Class Amphibia is one of the most severely impacted taxa in an on-going global biodiversity crisis. Because amphibian reproduction is tightly associated with the presence of water, climatic changes that affect water availability pose a particularly menacing threat to both aquatic and terrestrial-breeding amphibians. We explore the impacts that one facet of climate change-that of extreme variation in precipitation-may have on amphibians. This variation is manifested principally as increases in the incidence and severity of both drought and major storm events. We stress the need to consider not only total precipitation amounts but also the pattern and timing of rainfall events. Such rainfall "pulses" are likely to become increasingly more influential on amphibians, especially in relation to seasonal reproduction. Changes in reproductive phenology can strongly influence the outcome of competitive and predatory interactions, thus potentially altering community dynamics in assemblages of co-existing species. We present a conceptual model to illustrate possible landscape and metapopulation consequences of alternative climate change scenarios for pond-breeding amphibians, using the Mole Salamander, Ambystoma talpoideum, as an example. Although amphibians have evolved a variety of life history strategies that enable them to cope with environmental uncertainty, it is unclear whether adaptations can keep pace with the escalating rate of climate change. Climate change, especially in combination with other stressors, is a daunting challenge for the persistence of amphibians and, thus, the conservation of global biodiversity.

  4. Extreme midlatitude cyclones and their implications for precipitation and wind speed extremes in simulations of the Maunder Minimum versus present day conditions

    Energy Technology Data Exchange (ETDEWEB)

    Raible, C.C.; Casty, C. [University of Bern, Climate and Environmental Physics, Physics Institute, Bern (Switzerland); Yoshimori, M. [University of Bern, Climate and Environmental Physics, Physics Institute, Bern (Switzerland); Rutgers University, Center for Environmental Prediction, New Brunswick, NJ (United States); Stocker, T.F. [University of Bern, Climate and Environmental Physics, Physics Institute, Bern (Switzerland); University of Hawaii, International Pacific Research Center, SOEST, Honolulu, HI (United States)

    2007-03-15

    Extreme midlatitude cyclone characteristics, precipitation, wind speed events, their inter-relationships, and the connection to large-scale atmospheric patterns are investigated in simulations of a prolonged cold period, known as the Maunder Minimum from 1640 to 1715 and compared with today. An ensemble of six simulations for the Maunder Minimum as well as a control simulation for perpetual 1990 conditions are carried out with a coupled atmosphere-ocean general circulation model, i.e., the Climate Community System Model (CCSM). The comparison of the simulations shows that in a climate state colder than today the occurrence of cyclones, the extreme events of precipitation and wind speed shift southward in all seasons in the North Atlantic and the North Pacific. The extremes of cyclone intensity increases significantly in winter in almost all regions, which is related to a stronger meridional temperature gradient and an increase in lower tropospheric baroclinicity. Extremes of cyclone intensity in subregions of the North Atlantic are related to extremes in precipitation and in wind speed during winter. Moreover, extremes of cyclone intensity are also connected to distinct large-scale atmospheric patterns for the different subregions, but these relationships vanish during summer. Analyzing the mean 1,000 hPa geopotential height change of the Maunder Minimum simulations compared with the control simulation, we find a similar pattern as the correlation pattern with the cyclone intensity index of the southern Europe cyclones. This illustrates that changes in the atmospheric high-frequency, i.e., the simulated southward shift of cyclones in the North Atlantic and the related increase of extreme precipitation and wind speed in particular in the Mediterranean in winter, are associated with large-scale atmospheric circulation changes. (orig.)

  5. The creation of future daily gridded datasets of precipitation and temperature with a spatial weather generator, Cyprus 2020-2050

    Science.gov (United States)

    Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Pashiardis, Stelios; Lange, Manfred

    2014-05-01

    High-resolution gridded daily datasets are essential for natural resource management and the analysis of climate changes and their effects. This study aimed to create gridded datasets of daily precipitation and daily minimum and maximum temperature, for the future (2020-2050). The horizontal resolution of the developed datasets is 1 x 1 km2, covering the area under control of the Republic of Cyprus (5.760 km2). The study is divided into two parts. The first consists of the evaluation of the performance of different interpolation techniques for daily rainfall and temperature data (1980-2010) for the creation of the gridded datasets. Rainfall data recorded at 145 stations and temperature data from 34 stations were used. For precipitation, inverse distance weighting (IDW) performs best for local events, while a combination of step-wise geographically weighted regression and IDW proves to be the best method for large scale events. For minimum and maximum temperature, a combination of step-wise linear multiple regression and thin plate splines is recognized as the best method. Six Regional Climate Models (RCMs) for the A1B SRES emission scenario from the EU ENSEMBLE project database were selected as sources for future climate projections. The RCMs were evaluated for their capacity to simulate Cyprus climatology for the period 1980-2010. Data for the period 2020-2050 from the three best performing RCMs were downscaled, using the change factors approach, at the location of observational stations. Daily time series were created with a stochastic rainfall and temperature generator. The RainSim V3 software (Burton et al., 2008) was used to generate spatial-temporal coherent rainfall fields. The temperature generator was developed in R and modeled temperature as a weakly stationary process with the daily mean and standard deviation conditioned on the wet and dry state of the day (Richardson, 1981). Finally gridded datasets depicting projected future climate conditions were

  6. Forcings and Feedbacks on Convection in the 2010 Pakistan Flood: Modeling Extreme Precipitation with Interactive Large-Scale Ascent

    CERN Document Server

    Nie, Ji; Sobel, Adam H

    2016-01-01

    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, and 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 the large-scale forcings (other than large-scale vertical motion) computed from the quasi-geostrophic omega equation with 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 li...

  7. Extremes of heat, drought and precipitation depress reproductive performance in shortgrass prairie passerines

    Science.gov (United States)

    Conrey, Reesa Y.; Skagen, Susan; 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.

  8. Examining moisture pathways and extreme precipitation in the U.S. Intermountain West using self-organizing maps

    Science.gov (United States)

    Swales, Dustin; Alexander, Mike; Hughes, Mimi

    2016-02-01

    Self-organizing maps (SOMs) were used to explore relationships between large-scale synoptic conditions, especially vertically integrated water vapor transport (IVT), and extreme precipitation events in the U.S. Intermountain West (IMW). By examining spatial patterns in the IVT, pathways are identified where moisture can penetrate into the IMW. A substantial number of extreme precipitation events in the IMW are associated with infrequently occurring synoptic patterns. The transition frequency between each of the SOM nodes, which indicate temporal relationships between the patterns, identified two synoptic settings associated with extreme precipitation in the IMW: (1) a landfalling, zonally propagating trough that results in a concentrated IVT band that moves southward as the system moves inland and (2) a southwesterly storm track associated with strong ridging over the coast that results in persistent IVT transport into the Pacific Northwest that can last for several days.

  9. The link between extreme precipitation and convective organization in a warming climate: Global radiative-convective equilibrium simulations

    Science.gov (United States)

    Pendergrass, Angeline G.; Reed, Kevin A.; Medeiros, Brian

    2016-11-01

    The rate of increase of extreme precipitation in response to global warming varies dramatically across climate model simulations, particularly over the tropics, for reasons that have yet to be established. Here we propose one potential mechanism: changing organization of convection with climate. We analyze a set of simulations with the Community Atmosphere Model version 5 with an idealized global radiative-convective equilibrium configuration forced by fixed sea surface temperatures varying in 2° increments from 285 to 307 K. In these simulations, convective organization varies from semiorganized in cold simulations, disorganized in warm simulations, and abruptly becomes highly organized at just over 300 K. The change in extreme precipitation with warming also varies across these simulations, including a large increase at the transition from disorganized to organized convection. We develop an extreme precipitation-focused metric for convective organization and use this to explore their connection.

  10. Continuous daily hydrograph simulation using duration curves of a precipitation index

    CSIR Research Space (South Africa)

    Smakhtin, VY

    2000-04-01

    Full Text Available of the catchment areas of the site of interest and the gauged site(s). The other possible alternative is to generate monthly ¯ow time-series and disaggregate it into daily ¯ows. Copyright # 2000 John Wiley & Sons, Ltd. Received 10 March 1999 Accepted 31 August..., but not necessarily sequentially similar to the one that may be expected at a site of interest. This may become a limiting factor in river ecology studies, for example, where the actual sequence of daily ¯ows is of paramount importance. A non-linear spatial...

  11. Analyses of extreme precipitation and runoff events including uncertainties and reliability in design and management of urban water infrastructure

    Science.gov (United States)

    Hailegeorgis, Teklu T.; Alfredsen, Knut

    2017-01-01

    There is a need for assessment of uncertainties and hence effects on reliability of design and management of stormwater pipes due to the prevalence of urban floods trigged by modification of land cover and high precipitation intensities respectively due to increasing urbanization and changing climate. Observed annual maximum series (AMS) of extreme precipitation intensities of 17 durations (1-min to 1440-min) and runoff records of 27 years from a 21.255 ha (23% impervious, 35% built-up and 41% open areas) Risvollan catchment in Trondheim City were used. Using a balanced bootstrap resampling (BBRS) with frequency analysis, we quantified considerable uncertainty in precipitation and runoff quantiles due to the sampling variability of systematic observations (e.g., -43% to +49% relative differences from the quantile estimates for the original sample). These differences are higher than suggested increase in design rainfall and floods by many countries for climate change adjustment. The uncertainties in IDF curves and derived design storm hyetographs are found to have large effects on the reliability of sizing of stormwater pipes. The study also indicated low validity of the assumptions on extreme precipitation and runoff relationships in the return period-based method for the partially paved urban catchment: (i) maximum of only 46% of the AMS of extreme precipitation and runoff events occurred concurrently and (ii) T-year return period extreme precipitation events do not necessarily result in T-year flood events. These indicate that there are effects of snowmelt seasonality, and probably catchment moisture states and interactions between the flows in subsurface media and pipes. The results substantiate the need for better understanding of relationships between precipitation and runoff extremes and urban runoff generation process, and importance of uncertainty assessment and application of reliability-based methods for design and management of water infrastructure.

  12. A Central European precipitation climatology. Pt. I. Generation and validation of a high-resolution gridded daily data set (HYRAS)

    Energy Technology Data Exchange (ETDEWEB)

    Rauthe, Monika; Steiner, Heiko; Riediger, Ulf; Mazurkiewicz, Alex; Gratzki, Annegret [Deutscher Wetterdienst, Offenbach am Main (Germany)

    2013-10-15

    A new precipitation climatology (DWD/BfG-HYRAS-PRE) is presented which covers the river basins in Germany and neighbouring countries. In order to satisfy hydrological requirements, the gridded dataset has a high spatial resolution of 1 km{sup 2} and a daily temporal resolution that is based on up to 6200 precipitation stations within the spatial domain. The period of coverage extends from 1951 to 2006 for which gridded, daily precipitation fields were calculated from the station data using the REGNIE method. This is a combination between multiple linear regression considering orographical conditions and inverse distance weighting. One of the main attributes of the REGNIE method is the preservation of the station values for their respective grid cells. A detailed validation of the data set using cross-validation and Jackknifing showed both seasonally- and spatially-dependent interpolation errors. These errors, through further applications of the HYRAS data set within the KLIWAS project and other studies, provide an estimate of its certainty and quality. The mean absolute error was found to be less than 2 mm/day, but with both spatial and temporal variability. Additionally, the need for a high station network density was shown. Comparisons with other existing data sets show good agreement, with areas of orographical complexity displaying the largest differences within the domain. These errors are largely due to uncertainties caused by differences in the interpolation method, the station network density available, and the topographical information used. First climatological applications are presented and show the high potential of this new, high-resolution data set. Generally significant increases of up to 40% in winter precipitation and light decreases in summer are shown, whereby the spatial variability of the strength and significance of the trends is clearly illustrated. (orig.)

  13. The effect of mirror therapy on upper-extremity function and activities of daily living in stroke patients.

    Science.gov (United States)

    Park, Jin-Young; Chang, Moonyoung; Kim, Kyeong-Mi; Kim, Hee-Jung

    2015-06-01

    The purpose of this study was to examine the effects of mirror therapy on upper-extremity function and activities of daily living in chronic stroke patients. [Subjects and Methods] Fifteen subjects were each assigned to a mirror therapy group and a sham therapy group. The Fugl-Meyer Motor Function Assessment and the Box and Block Test were performed to compare paretic upper-extremity function and hand coordination abilities. The functional independence measurement was conducted to compare abilities to perform activities of daily living. [Results] Paretic upper-extremity function and hand coordination abilities were significantly different between the mirror therapy and sham therapy groups. Intervention in the mirror therapy group was more effective than in the sham therapy group for improving the ability to perform activities of daily living. Self-care showed statistically significant differences between the two groups. [Conclusion] Mirror therapy is effective in improving paretic upper-extremity function and activities of daily living in chronic stroke patients.

  14. Relationship between the Late Spring NAO and Summer Extreme Precipitation Frequency in the Middle and Lower Reaches of the Yangtze River

    Institute of Scientific and Technical Information of China (English)

    TTIAN Bao-Qiang; FAN Ke

    2012-01-01

    The relationship between the late spring North Atlantic Oscillation (NAO) and the summer extreme precipitation frequency (EPF) in the middle and lower reaches of the Yangtze River Valley (MLYRV) is examined using an NECP/NCAR reanalysis dataset and daily precipitation data from 74 stations in the MLYRV. The results show a significant negative correlation between the May NAO index and the EPF over the MLYRV in the subsequent summer. In positive EPF index years, the East Asian westerly jet shifts farther southward, and two blocking high positive anomalies appear over the Sea of Okhotsk and the Ural Mountains. These anomalies are favorable to the cold air from the mid-high latitudes invading the Yangtze River Valley (YRV). The moisture convergence and the ascending motion dominate the MLYRV. The above patterns are reversed in negative EPF index years. A wave train pattern that originates from the North Atlantic extends eastward to the Mediterranean and then moves to the Tibetan Plateau and from there to the YRV, which is an important link in the May NAO and the summer extreme precipitation in the MLYRV. The wave train may be aroused by the tripole pattern of the SST, which can explain why the May NAO affects the summer EPF in the MLYRV.

  15. Contributions of different bias-correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes

    Science.gov (United States)

    Iizumi, Toshichika; Takikawa, Hiroki; Hirabayashi, Yukiko; Hanasaki, Naota; Nishimori, Motoki

    2017-08-01

    The use of different bias-correction methods and global retrospective meteorological forcing data sets as the reference climatology in the bias correction of general circulation model (GCM) daily data is a known source of uncertainty in projected climate extremes and their impacts. Despite their importance, limited attention has been given to these uncertainty sources. We compare 27 projected temperature and precipitation indices over 22 regions of the world (including the global land area) in the near (2021-2060) and distant future (2061-2100), calculated using four Representative Concentration Pathways (RCPs), five GCMs, two bias-correction methods, and three reference forcing data sets. To widen the variety of forcing data sets, we developed a new forcing data set, S14FD, and incorporated it into this study. The results show that S14FD is more accurate than other forcing data sets in representing the observed temperature and precipitation extremes in recent decades (1961-2000 and 1979-2008). The use of different bias-correction methods and forcing data sets contributes more to the total uncertainty in the projected precipitation index values in both the near and distant future than the use of different GCMs and RCPs. However, GCM appears to be the most dominant uncertainty source for projected temperature index values in the near future, and RCP is the most dominant source in the distant future. Our findings encourage climate risk assessments, especially those related to precipitation extremes, to employ multiple bias-correction methods and forcing data sets in addition to using different GCMs and RCPs.

  16. Oxygen and hydrogen stable isotope content in daily-collected precipitation samples at Dome C, East Antarctica

    Science.gov (United States)

    Dreossi, Giuliano; Stenni, Barbara; Del Guasta, Massimo; Bonazza, Mattia; Grigioni, Paolo; Karlicek, Daniele; Mognato, Riccardo; Scarchilli, Claudio; Turchetti, Filippo; Zannoni, Daniele

    2016-04-01

    Antarctic ice cores allow to obtain exceptional past climate records, thanks to their water stable isotope content, which provides integrated tracers of the atmospheric water cycle and local climate. Low accumulation sites of the East Antarctic plateau provide the oldest ice core records, with the record-breaking EPICA Dome C drilling covering the last eight climate cycles. However, the isotope-temperature relationship, commonly used to derive the temperature, may be characterized by significant geographical and temporal variations. Moreover, post-depositional effects may further complicate the climate interpretation. A continuous series of precipitation data is needed in order to gain a better understanding of the factors affecting the water stable isotopes in Antarctic precipitation at a specific site. In this study, we use the first and so-far only multi-year series of daily precipitation sampling and isotope measurements from the French-Italian Concordia Station, located at Dome C in East Antarctica (75°06'S 123°21'E; elevation: 3233 m a.s.l.; mean annual temperature: -54.5°C; snow accumulation rate: 25 kg m-2 yr-1), where the oldest deep Antarctic ice core has been retrieved. Surface air temperature data have been provided by the US automatic weather station (AWS), placed 1.5 km away from the base, while tropospheric temperature profiles are obtained by means of a radiosonde, launched once per day by the IPEV/Italian Antarctic Meteo-climatological Observatory. The new dataset also enables us for the first time to study the isotope-temperature relationship distinguishing between different types of precipitation, namely diamond dust, hoar frost and snowfall, identified by the observations carried out by the winter-over personnel collecting the snow samples. Here we present the complete data series of water stable isotopes in precipitation at Dome C spanning the time period from 2008 to 2014, in the framework of the PNRA PRE-REC project.

  17. Preserving spatial linear correlations between neighboring stations in simulating daily precipitation using extended Markov models

    Science.gov (United States)

    Ababaei, Behnam; Sohrabi, Teymour; Mirzaei, Farhad

    2014-10-01

    Most stochastic weather generators have their focus on precipitation because it is the most important variable affecting environmental processes. One of the methods to reproduce the precipitation occurrence time series is to use a Markov process. But, in addition to the simulation of short-term autocorrelations in one station, it is sometimes important to preserve the spatial linear correlations (SLC) between neighboring stations as well. In this research, an extension of one-site Markov models was proposed to preserve the SLC between neighboring stations. Qazvin station was utilized as the reference station and Takestan (TK), Magsal, Nirougah, and Taleghan stations were used as the target stations. The performances of different models were assessed in relation to the simulation of dry and wet spells and short-term dependencies in precipitation time series. The results revealed that in TK station, a Markov model with a first-order spatial model could be selected as the best model, while in the other stations, a model with the order of two or three could be selected. The selected (i.e., best) models were assessed in relation to preserving the SLC between neighboring stations. The results depicted that these models were very capable in preserving the SLC between the reference station and any of the target stations. But, their performances were weaker when the SLC between the other stations were compared. In order to resolve this issue, spatially correlated random numbers were utilized instead of independent random numbers while generating synthetic time series using the Markov models. Although this method slightly reduced the model performances in relation to dry and wet spells and short-term dependencies, the improvements related to the simulation of the SLC between the other stations were substantial.

  18. Characterization of flood and precipitation events in Southwestern Germany and stochastic simulation of extreme precipitation (Project FLORIS-SV)

    Science.gov (United States)

    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

  19. Changes in extreme temperature and precipitation events in the Loess Plateau (China) during 1960-2013 under global warming

    Science.gov (United States)

    Sun, Wenyi; Mu, Xingmin; Song, Xiaoyan; Wu, Dan; Cheng, Aifang; Qiu, Bing

    2016-02-01

    In recent decades, extreme climatic events have been a major issue worldwide. Regional assessments on various climates and geographic regions are needed for understanding uncertainties in extreme events' responses to global warming. The objective of this study was to assess the annual and decadal trends in 12 extreme temperature and 10 extreme precipitation indices in terms of intensity, frequency, and duration over the Loess Plateau during 1960-2013. The results indicated that the regionally averaged trends in temperature extremes were consistent with global warming. The occurrence of warm extremes, including summer days (SU), tropical nights (TR), warm days (TX90), and nights (TN90) and a warm spell duration indicator (WSDI), increased by 2.76 (P spell duration indicator (CSDI) exhibited decreases of - 3.22 (P wet-day and extremely wet-day precipitation were not significant. Large-scale atmospheric circulation indices, such as the Western Pacific Subtropical High Intensity Index (WPSHII) and Arctic Oscillation (AO), strongly influences warm/cold extremes and contributes significantly to climate changes in the Loess Plateau. The enhanced geopotential height over the Eurasian continent and increase in water vapor divergence in the rainy season have contributed to the changes of the rapid warming and consecutive drying in the Loess Plateau.

  20. Changes in intensity of precipitation extremes in Romania on very hight temporal scale and implications on the validity of the Clausius-Clapeyron relation

    Science.gov (United States)

    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

  1. Predictability of horizontal water vapor transport relative to precipitation: Enhancing situational awareness for forecasting western U.S. extreme precipitation and flooding

    Science.gov (United States)

    Lavers, David A.; Waliser, Duane E.; Ralph, F. Martin; Dettinger, Michael

    2016-01-01

    The western United States is vulnerable to socioeconomic disruption due to extreme winter precipitation and floods. Traditionally, forecasts of precipitation and river discharge provide the basis for preparations. Herein we show that earlier event awareness may be possible through use of horizontal water vapor transport (integrated vapor transport (IVT)) forecasts. Applying the potential predictability concept to the National Centers for Environmental Prediction global ensemble reforecasts, across 31 winters, IVT is found to be more predictable than precipitation. IVT ensemble forecasts with the smallest spreads (least forecast uncertainty) are associated with initiation states with anomalously high geopotential heights south of Alaska, a setup conducive for anticyclonic conditions and weak IVT into the western United States. IVT ensemble forecasts with the greatest spreads (most forecast uncertainty) have initiation states with anomalously low geopotential heights south of Alaska and correspond to atmospheric rivers. The greater IVT predictability could provide warnings of impending storminess with additional lead times for hydrometeorological applications.

  2. Understanding future projected changes and trends in extreme precipitation and streamflow events in ten Polish catchments

    Science.gov (United States)

    Meresa, Hadush; Romanowicz, Renata; Napiorkoski, Jaroslaw

    2016-04-01

    The aim of the study is to investigate methods of trend detection in hydro-climatic high and low indices using novel and conventional tools, for future climate projections in the periods 2021-2050 and 2071-2100. The climate meteorological projections are obtained from regional climate models or/and global circulation models forced with IPCC SRES A1B, RCP4.5 and RCP8.5 emission scenarios. The study area includes ten catchments in Poland. The catchments have diverse hydro-climatic conditions. They are covered mostly by forest and are semi-natural. The flood regime of all the catchments is driven either by rainfall and/or snow-melt. Streamflow projections are provided by running the HBV hydrological model, coupled with climate models for the catchments. The trends are analyzed using a conventional Modified Mann Kendall statistical approach, a time frequency approach based on wavelet discrete transform (DWT) and the Dynamic Harmonic Regression (DHR) method. We address the problems of auto-correlation, seasonality and inter-annual variability of the derived indices. A Modified Mann Kendall (MMK) method is applied to cope with the autocorrelation of the time series. The DHR method is based on the unobserved component approach. Together with estimates of the components, the uncertainty of the estimates is also calculated. The results of the DHR analysis (trend) are compared with the calculated MMK and DWT trends. Among other indices we study the temporal patterns of the Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI) and Standardized Evapotranspiration Index (SPEI), as well as Maximum Annual Flows and Minimum Annual Flows. The results indicate that changes in the trends of the projected indices are more conservative when DHR methods are applied than conventional trend techniques. The wavelet-based approach is the most subjective and gives the least conservative trend estimates. Trends indicate an increase in the amount of precipitation, followed by

  3. High Resolution Modeling in Mountainous Terrain for Water Resource Management: AN Extreme Precipitation Event Case Study

    Science.gov (United States)

    Masarik, M. T.; Watson, K. A.; Flores, A. N.; Anderson, K.; Tangen, S.

    2016-12-01

    The water resources infrastructure of the Western US is designed to deliver reliable water supply to users and provide recreational opportunities for the public, as well as afford flood control for communities by buffering variability in precipitation and snow storage. Thus water resource management is a balancing act of meeting multiple objectives while trying to anticipate and mitigate natural variability of water supply. Currently, the forecast guidance available to personnel managing resources in mountainous terrain is lacking in two ways: the spatial resolution is too coarse, and there is a gap in the intermediate time range (10-30 days). To address this need we examine the effectiveness of using the Weather Research and Forecasting (WRF) model, a state of the art, regional, numerical weather prediction model, as a means to generate high-resolution weather guidance in the intermediate time range. This presentation will focus on a reanalysis and hindcasting case study of the extreme precipitation and flooding event in the Payette River Basin of Idaho during the period of June 2nd-4th, 2010. For the reanalysis exercise we use NCEP's Climate Forecast System Reanalysis (CFSR) and the North American Regional Reanalysis (NARR) data sets as input boundary conditions to WRF. The model configuration includes a horizontal spatial resolution of 3km in the outer nest, and 1 km in the inner nest, with output temporal resolution of 3 hrs and 1 hr, respectively. The hindcast simulations, which are currently underway, will make use of the NCEP Climate Forecast System Reforecast (CFSRR) data. The current state of these runs will be discussed. Preparations for the second of two components in this project, weekly WRF forecasts during the intense portion of the water year, will be briefly described. These forecasts will use the NCEP Climate Forecast System version 2 (CFSv2) operational forecast data as boundary conditions to provide forecast guidance geared towards water resource

  4. Validation and uncertainty analysis for monthly and extreme precipitation in the ERA-20C reanalysis based on the WZN in-situ measurements

    Science.gov (United States)

    Rustemeier, Elke; Ziese, Markus; Raykova, Kristin; Meyer-Christoffer, Anja; Schneider, Udo; Finger, Peter; Becker, Andreas

    2017-04-01

    The proper representation of precipitation, in particular extreme precipitation, in global reanalyses is still challenging. This paper focuses on the potential of the ERA-20C centennial reanalysis to reproduce precipitation events. The global ERA-20C Reanalysis has been developed within the projects ERA-CLIM and its successor ERA-CLIM2 with the aim of a multi-decadal reanalysis of the global climate system. One of the objectives of ERA-CLIM2 is to provide useful information about the uncertainty of the various parameters. Since precipitation is a prognostic variable, it allows for independent validation by in-situ measurements. For this purpose, the Global Precipitation Clim