Soil losses from typic cambisols and red latosol as related to three erosive rainfall patterns

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Regimeire Freitas Aquino

2013-02-01

Full Text Available Rainfall erosivity is one of the main factors related to water erosion in the tropics. This work focused on relating soil loss from a typic dystrophic Tb Haplic Cambisol (CXbd and a typic dystrophic Red Latosol (LVdf to different patterns of natural erosive rainfall. The experimental plots of approximately 26 m² (3 x 8.67 m consisted of a CXbd area with a 0.15 m m-1 slope and a LVdf area with 0.12 m m-1 slope, both delimited by galvanized plates. Drainpipes were installed at the lower part of these plots to collect runoff, interconnected with a Geib or multislot divisor. To calculate erosivity (EI30, rainfall data, recorded continuously at a weather station in Lavras, were used. The data of erosive rainfall events were measured (10 mm precipitation intervals, accuracy 0.2 mm, 24 h period, 20 min intervals, characterized as rainfall events with more than 10 mm precipitation, maximum intensity > 24 mm h-1 within 15 min, or kinetic energy > 3.6 MJ, which were used in this study to calculate the rainfall erosivity parameter, were classified according to the moment of peak precipitation intensity in advanced, intermediate and delayed patterns. Among the 139 erosive rainfall events with CXbd soil loss, 60 % were attributed to the advanced pattern, with a loss of 415.9 Mg ha-1, and total losses of 776.0 Mg ha-1. As for the LVdf, of the 93 erosive rainfall events with soil loss, 58 % were listed in the advanced pattern, with 37.8 Mg ha-1 soil loss and 50.9 Mg ha-1 of total soil loss. The greatest soil losses were observed in the advanced rain pattern, especially for the CXbd. From the Cambisol, the soil loss per rainfall event was greatest for the advanced pattern, being influenced by the low soil permeability.

Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

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Kashid, Satishkumar S.; Maity, Rajib

2012-08-01

SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different

Association of Taiwan’s Rainfall Patterns with Large-Scale Oceanic and Atmospheric Phenomena

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Yi-Chun Kuo

2016-01-01

Full Text Available A 50-year (1960–2009 monthly rainfall gridded dataset produced by the Taiwan Climate Change Projection and Information Platform Project was presented in this study. The gridded data (5 × 5 km displayed influence of topography on spatial variability of rainfall, and the results of the empirical orthogonal functions (EOFs analysis revealed the patterns associated with the large-scale sea surface temperature variability over Pacific. The first mode (65% revealed the annual peaks of large rainfall in the southwestern mountainous area, which is associated with southwest monsoons and typhoons during summertime. The second temporal EOF mode (16% revealed the rainfall variance associated with the monsoon and its interaction with the slopes of the mountain range. This pattern is the major contributor to spatial variance of rainfall in Taiwan, as indicated by the first mode (40% of spatial variance EOF analysis. The second temporal EOF mode correlated with the El Niño Southern Oscillation (ENSO. In particular, during the autumn of the La Niña years following the strong El Niño years, the time-varying amplitude was substantially greater than that of normal years. The third temporal EOF mode (7% revealed a north-south out-of-phase rainfall pattern, the slowly evolving variations of which were in phase with the Pacific Decadal Oscillation. Because of Taiwan’s geographic location and the effect of local terrestrial structures, climate variability related to ENSO differed markedly from other regions in East Asia.

Long term spatial and temporal rainfall trends and homogeneity analysis in Wainganga basin, Central India

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Arun Kumar Taxak

2014-08-01

Full Text Available Gridded rainfall data of 0.5×0.5° resolution (CRU TS 3.21 was analysed to study long term spatial and temporal trends on annual and seasonal scales in Wainganga river basin located in Central India during 1901–2012. After testing the presence of autocorrelation, Mann–Kendall (Modified Mann–Kendall test was applied to non-auto correlated (auto correlated series to detect the trends in rainfall data. Theil and Sen׳s slope estimator test was used for finding the magnitude of change over a time period. For detecting the most probable change year, Pettitt–Mann–Whitney test was applied. The Rainfall series was then divided into two partial duration series for finding changes in trends before and after the change year. Arc GIS was used to explore spatial patterns of the trends over the entire basin. Though most of the grid points shows a decreasing trend in annual rainfall, only seven grids has a significant decreasing trend during 1901–2012. On the basis of seasonal trend analysis, non-significant increasing trend is observed only in post monsoon season while seven grid points show significant decreasing trend in monsoon rainfall and non-significant in pre-monsoon and winter rainfall over the last 112 years. During the study period, overall a 8.45% decrease in annual rainfall is estimated. The most probable year of change was found to be 1948 in annual and monsoonal rainfall. There is an increasing rainfall trend in the basin during the period 1901–1948, which is reversed during the period 1949–2012 resulting in decreasing rainfall trend in the basin. Homogeneous trends in annual and seasonal rainfall over a grid points is exhibited in the basin by van Belle and Hughes׳ homogeneity trend test.

Generation of intensity duration frequency curves and intensity temporal variability pattern of intense rainfall for Lages/SC

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Célio Orli Cardoso

2014-04-01

Full Text Available The objective of this work was to analyze the frequency distribution and intensity temporal variability of intense rainfall for Lages/SC from diary pluviograph data. Data on annual series of maximum rainfalls from rain gauges of the CAV-UDESC Weather Station in Lages/SC were used from 2000 to 2009. Gumbel statistic distribution was applied in order to obtain the rainfall height and intensity in the following return periods: 2, 5, 10, 15 and 20 years. Results showed intensity-duration-frequency curves (I-D-F for those return periods, as well as I-D-F equations: i=2050.Tr0,20.(t+30-0,89, where i was the intensity, Tr was the rainfall return periods and t was the rainfall duration. For the intensity of temporal variability pattern along of the rainfall duration time, the convective, or advanced pattern was the predominant, with larger precipitate rainfalls in the first half of the duration. The same pattern presented larger occurrences in the spring and summer stations.

Responses of the sustainable yield of groundwater to annual rainfall and pumping patterns in the Baotou Plain, North China

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Liao, Z.; LONG, Y., Sr.; Wei, Y.; Guo, Z.

2017-12-01

Serious water deficits and deteriorating environmental quality are threatening the sustainable socio-economic development and the protection of the ecology and the environment in North China, especially in Baotou City. There is a common misconception that groundwater extraction can be sustainable if the pumping rate does not exceed the total natural recharge in a groundwater basin. The truth is that the natural recharge is mainly affected by the rainfall and that groundwater withdrawal determines the sustainable yield of the aquifer flow system. The concept of the sustainable yield is defined as the allowance pumping patterns and rates that avoid adverse impacts on the groundwater system. The sustainable yield introduced in this paper is a useful baseline for groundwater management under all rainfall conditions and given pumping scenarios. A dynamic alternative to the groundwater sustainable yield for a given pumping pattern and rate should consider the responses of the recharge, discharge, and evapotranspiration to the groundwater level fluctuation and to different natural rainfall conditions. In this study, methods for determining the sustainable yield through time series data of groundwater recharge, discharge, extraction, and precipitation in an aquifer are introduced. A numerical simulation tool was used to assess and quantify the dynamic changes in groundwater recharge and discharge under excessive pumping patterns and rates and to estimate the sustainable yield of groundwater flow based on natural rainfall conditions and specific groundwater development scenarios during the period of 2007 to 2014. The results of this study indicate that the multi-year sustainable yield only accounts for about one-half of the average annual recharge. The future sustainable yield for the current pumping scenarios affected by rainfall conditions are evaluated quantitatively to obtain long-term groundwater development strategies. The simulation results show that sufficient

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

OpenAIRE

D. C. Verdon-Kidd; A. S. Kiem

2009-01-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a cl...

Modeling and forecasting rainfall patterns of southwest monsoons in North-East India as a SARIMA process

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Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

2018-02-01

Weather forecasting is an important issue in the field of meteorology all over the world. The pattern and amount of rainfall are the essential factors that affect agricultural systems. India experiences the precious Southwest monsoon season for four months from June to September. The present paper describes an empirical study for modeling and forecasting the time series of Southwest monsoon rainfall patterns in the North-East India. The Box-Jenkins Seasonal Autoregressive Integrated Moving Average (SARIMA) methodology has been adopted for model identification, diagnostic checking and forecasting for this region. The study has shown that the SARIMA (0, 1, 1) (1, 0, 1)4 model is appropriate for analyzing and forecasting the future rainfall patterns. The Analysis of Means (ANOM) is a useful alternative to the analysis of variance (ANOVA) for comparing the group of treatments to study the variations and critical comparisons of rainfall patterns in different months of the season.

Animal perception of seasonal thresholds: changes in elephant movement in relation to rainfall patterns.

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Birkett, Patricia J; Vanak, Abi T; Muggeo, Vito M R; Ferreira, Salamon M; Slotow, Rob

2012-01-01

The identification of temporal thresholds or shifts in animal movement informs ecologists of changes in an animal's behaviour, which contributes to an understanding of species' responses in different environments. In African savannas, rainfall, temperature and primary productivity influence the movements of large herbivores and drive changes at different scales. Here, we developed a novel approach to define seasonal shifts in movement behaviour by examining the movements of a highly mobile herbivore (elephant; Loxodonta africana), in relation to local and regional rainfall patterns. We used speed to determine movement changes of between 8 and 14 GPS-collared elephant cows, grouped into five spatial clusters, in Kruger National Park, South Africa. To detect broad-scale patterns of movement, we ran a three-year daily time-series model for each individual (2007-2009). Piecewise regression models provided the best fit for elephant movement, which exhibited a segmented, waveform pattern over time. Major breakpoints in speed occurred at the end of the dry and wet seasons of each year. During the dry season, female elephant are constrained by limited forage and thus the distances they cover are shorter and less variable. Despite the inter-annual variability of rainfall, speed breakpoints were strongly correlated with both local and regional rainfall breakpoints across all three years. Thus, at a multi-year scale, rainfall patterns significantly affect the movements of elephant. The variability of both speed and rainfall breakpoints across different years highlights the need for an objective definition of seasonal boundaries. By using objective criteria to determine behavioural shifts, we identified a biologically meaningful indicator of major changes in animal behaviour in different years. We recommend the use of such criteria, from an animal's perspective, for delineating seasons or other extrinsic shifts in ecological studies, rather than arbitrarily fixed definitions

Animal perception of seasonal thresholds: changes in elephant movement in relation to rainfall patterns.

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Patricia J Birkett

Full Text Available BACKGROUND: The identification of temporal thresholds or shifts in animal movement informs ecologists of changes in an animal's behaviour, which contributes to an understanding of species' responses in different environments. In African savannas, rainfall, temperature and primary productivity influence the movements of large herbivores and drive changes at different scales. Here, we developed a novel approach to define seasonal shifts in movement behaviour by examining the movements of a highly mobile herbivore (elephant; Loxodonta africana, in relation to local and regional rainfall patterns. METHODOLOGY/PRINCIPAL FINDINGS: We used speed to determine movement changes of between 8 and 14 GPS-collared elephant cows, grouped into five spatial clusters, in Kruger National Park, South Africa. To detect broad-scale patterns of movement, we ran a three-year daily time-series model for each individual (2007-2009. Piecewise regression models provided the best fit for elephant movement, which exhibited a segmented, waveform pattern over time. Major breakpoints in speed occurred at the end of the dry and wet seasons of each year. During the dry season, female elephant are constrained by limited forage and thus the distances they cover are shorter and less variable. Despite the inter-annual variability of rainfall, speed breakpoints were strongly correlated with both local and regional rainfall breakpoints across all three years. Thus, at a multi-year scale, rainfall patterns significantly affect the movements of elephant. The variability of both speed and rainfall breakpoints across different years highlights the need for an objective definition of seasonal boundaries. CONCLUSIONS/SIGNIFICANCE: By using objective criteria to determine behavioural shifts, we identified a biologically meaningful indicator of major changes in animal behaviour in different years. We recommend the use of such criteria, from an animal's perspective, for delineating seasons or

Movement response patterns of livestock to rainfall variability in the ...

African Journals Online (AJOL)

Livestock movement patterns indicated that forage is the motivation for winter movements and water is the motivation for summer. The movement followed a predictable ... The latter can be considered as a 'key resource' area to sustain animal numbers through critical periods of low rainfall. Overall, seasonal movement ...

Using Conditional Analysis to Investigate Spatial and Temporal patterns in Upland Rainfall

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Sakamoto Ferranti, Emma Jayne; Whyatt, James Duncan; Timmis, Roger James

2010-05-01

The seasonality and characteristics of rainfall in the UK are altering under a changing climate. Summer rainfall is generally decreasing whereas winter rainfall is increasing, particularly in northern and western areas (Maraun et al., 2008) and recent research suggests these rainfall increases are amplified in upland areas (Burt and Ferranti, 2010). Conditional analysis has been used to investigate these rainfall patterns in Cumbria, an upland area in northwest England. Cumbria was selected as an example of a topographically diverse mid-latitude region that has a predominately maritime and westerly-defined climate. Moreover it has a dense network of more than 400 rain gauges that have operated for periods between 1900 and present day. Cumbria has experienced unprecedented flooding in the past decade and understanding the spatial and temporal changes in this and other upland regions is important for water resource and ecosystem management. The conditional analysis method examines the spatial and temporal variations in rainfall under different synoptic conditions and in different geographic sub-regions (Ferranti et al., 2009). A daily synoptic typing scheme, the Lamb Weather Catalogue, was applied to classify rainfall into different weather types, for example: south-westerly, westerly, easterly or cyclonic. Topographic descriptors developed using GIS were used to classify rain gauges into 6 directionally-dependant geographic sub-regions: coastal, windward-lowland, windward-upland, leeward-upland, leeward-lowland, secondary upland. Combining these classification methods enabled seasonal rainfall climatologies to be produced for specific weather types and sub-regions. Winter rainfall climatologies were constructed for all 6 sub-regions for 3 weather types - south-westerly (SW), westerly (W), and cyclonic (C); these weather types contribute more than 50% of total winter rainfall. The frequency of wet-days (>0.3mm), the total winter rainfall and the average wet day

PATTERNS OF THE MAXIMUM RAINFALL AMOUNTS REGISTERED IN 24 HOURS WITHIN THE OLTENIA PLAIN

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ALINA VLĂDUŢ

2012-03-01

Full Text Available Patterns of the maximum rainfall amounts registered in 24 hours within the Oltenia Plain. The present study aims at rendering the main features of the maximum rainfall amounts registered in 24 h within the Oltenia Plain. We used 30-year time series (1980-2009 for seven meteorological stations. Generally, the maximum amounts in 24 h display the same pattern as the monthly mean amounts, namely higher values in the interval May-October. In terms of mean values, the highest amounts are registered in the western and northern extremity of the plain. The maximum values generally exceed 70 mm at all meteorological stations: D.T. Severin, 224 mm, July 1999; Slatina, 104.8 mm, August 2002; Caracal, 92.2 m, July 1991; Bechet, 80.8 mm, July 2006; Craiova, 77.6 mm, April 2003. During the cold season, there was noticed a greater uniformity all over the plain, due to the cyclonic origin of rainfalls compared to the warm season, when thermal convection is quite active and it triggers local showers. In order to better emphasize the peculiarities of this parameter, we have calculated the frequency on different value classes (eight classes, as well as the probability of appearance of different amounts. Thus, it resulted that the highest frequency (25-35% is held by the first two classes of values (0-10 mm; 10.1-20 mm. The lowest frequency is registered in case of the amounts of more than 100 mm, which generally display a probability of occurrence of less than 1% and only in the western and eastern extremities of the plain.

ANALYSIS OF RAINFALL PATTERN AND FLOOD INCIDENCES IN WARRI METROPOLIS, NIGERIA

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R. Olanrewaju

2017-01-01

Full Text Available Climate change has led to changes in the known patterns of rainfall and other climatic variables as well as increase in the frequency and magnitude of natural disasters including floods in different parts of the world; and flood is indeed a global environmental issue that had destroyed lives and property amidst other untold hardships. The study examined rainfall characteristics in Warri metropolis for the past 30 years (1986-2015 vis-à-vis the flood situation in the metropolis; as well as the factors responsible and adaptation strategies to flood in the area. Dividing the study area into four zones after Sada (1977, the researchers collected rainfall data from the archives of Nigerian Meteorological Agency; 268 copies of questionnaire and oral interview were used. The result of the correlation analysis performed showed a negative relationship of -0.156 between rainfall and time (years, this implies that rainfall is decreasing over time. The trend line regression equation Y=243.75-0.4572X, confirms that rainfall in Warri Metropolis is decreasing at the rate of -0.45 per year. However, the p-value 0.412 is greater than 0.05, hence, the trend is not statistically significant at 95% level of confidence. It was discovered that rainfall, absence of drainage and poor urban planning practices (as factor 1 contributed 51.09% while overflowing of rivers, blocked/ poor drainage and untarred roads (as factor 2 contributed 44.10% variance to flood occurrence in the metropolis. Recommendations given included continual monitoring and study of rainfall characteristics and other climatic data and dissemination of such information for planning purposes; construction of integrated drainage system and river rechannelisation, legislation against dumping of refuse on roads and drainages; proper urban planning including implementation of the metropolitan urban drainage master plan. 

Plant calendar pattern based on rainfall forecast and the probability of its success in Deli Serdang regency of Indonesia

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Darnius, O.; Sitorus, S.

2018-03-01

The objective of this study was to determine the pattern of plant calendar of three types of crops; namely, palawija, rice, andbanana, based on rainfall in Deli Serdang Regency. In the first stage, we forecasted rainfall by using time series analysis, and obtained appropriate model of ARIMA (1,0,0) (1,1,1)12. Based on the forecast result, we designed a plant calendar pattern for the three types of plant. Furthermore, the probability of success in the plant types following the plant calendar pattern was calculated by using the Markov process by discretizing the continuous rainfall data into three categories; namely, Below Normal (BN), Normal (N), and Above Normal (AN) to form the probability transition matrix. Finally, the combination of rainfall forecasting models and the Markov process were used to determine the pattern of cropping calendars and the probability of success in the three crops. This research used rainfall data of Deli Serdang Regency taken from the office of BMKG (Meteorologist Climatology and Geophysics Agency), Sampali Medan, Indonesia.

An analysis of rainfall patterns in Nigeria | Odjugo | Global Journal of ...

African Journals Online (AJOL)

The rainfall pattern has also enhanced wind erosion/desertification, soil erosion and coastal flooding in the north, east and coastal areas of Nigeria respectively. With these impacts, the paper therefore recommends some adaptive and mitigation measures that could help to revert the current situation. Keywords: changing ...

Methods to evvaluate normal rainfall for short-term wetland hydrology assessment

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Jaclyn Sumner; Michael J. Vepraskas; Randall K. Kolka

2009-01-01

Identifying sites meeting wetland hydrology requirements is simple when long-term (>10 years) records are available. Because such data are rare, we hypothesized that a single-year of hydrology data could be used to reach the same conclusion as with long-term data, if the data were obtained during a period of normal or below normal rainfall. Long-term (40-45 years)...

Predictable patterns of the May-June rainfall anomaly over East Asia

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Xing, Wen; Wang, Bin; Yim, So-Young; Ha, Kyung-Ja

2017-02-01

During early summer (May-June, MJ), East Asia (EA) subtropical front is a defining feature of Asian monsoon, which produces the most prominent precipitation band in the global subtropics. Here we show that dynamical prediction of early summer EA (20°N-45°N, 100°E-130°E) rainfall made by four coupled climate models' ensemble hindcast (1979-2010) yields only a moderate skill and cannot be used to estimate predictability. The present study uses an alternative, empirical orthogonal function (EOF)-based physical-empirical (P-E) model approach to predict rainfall anomaly pattern and estimate its potential predictability. The first three leading modes are physically meaningful and can be, respectively, attributed to (a) the interaction between the anomalous western North Pacific subtropical high and underlying Indo-Pacific warm ocean, (b) the forcing associated with North Pacific sea surface temperature (SST) anomaly, and (c) the development of equatorial central Pacific SST anomalies. A suite of P-E models is established to forecast the first three leading principal components. All predictors are 0 month ahead of May, so the prediction here is named as a 0 month lead prediction. The cross-validated hindcast results demonstrate that these modes may be predicted with significant temporal correlation skills (0.48-0.72). Using the predicted principal components and the corresponding EOF patterns, the total MJ rainfall anomaly was hindcasted for the period of 1979-2015. The time-mean pattern correlation coefficient (PCC) score reaches 0.38, which is significantly higher than dynamical models' multimodel ensemble skill (0.21). The estimated potential maximum attainable PCC is around 0.65, suggesting that the dynamical prediction models may have large rooms to improve. Limitations and future work are discussed.

Large Scale Meteorological Pattern of Extreme Rainfall in Indonesia

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Kuswanto, Heri; Grotjahn, Richard; Rachmi, Arinda; Suhermi, Novri; Oktania, Erma; Wijaya, Yosep

2014-05-01

Extreme Weather Events (EWEs) cause negative impacts socially, economically, and environmentally. Considering these facts, forecasting EWEs is crucial work. Indonesia has been identified as being among the countries most vulnerable to the risk of natural disasters, such as floods, heat waves, and droughts. Current forecasting of extreme events in Indonesia is carried out by interpreting synoptic maps for several fields without taking into account the link between the observed events in the 'target' area with remote conditions. This situation may cause misidentification of the event leading to an inaccurate prediction. Grotjahn and Faure (2008) compute composite maps from extreme events (including heat waves and intense rainfall) to help forecasters identify such events in model output. The composite maps show large scale meteorological patterns (LSMP) that occurred during historical EWEs. Some vital information about the EWEs can be acquired from studying such maps, in addition to providing forecaster guidance. Such maps have robust mid-latitude meteorological patterns (for Sacramento and California Central Valley, USA EWEs). We study the performance of the composite approach for tropical weather condition such as Indonesia. Initially, the composite maps are developed to identify and forecast the extreme weather events in Indramayu district- West Java, the main producer of rice in Indonesia and contributes to about 60% of the national total rice production. Studying extreme weather events happening in Indramayu is important since EWEs there affect national agricultural and fisheries activities. During a recent EWE more than a thousand houses in Indramayu suffered from serious flooding with each home more than one meter underwater. The flood also destroyed a thousand hectares of rice plantings in 5 regencies. Identifying the dates of extreme events is one of the most important steps and has to be carried out carefully. An approach has been applied to identify the

The partitioning of litter carbon during litter decomposition under different rainfall patterns: a laboratory study

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Yang, X.; Szlavecz, K. A.; Langley, J. A.; Pitz, S.; Chang, C. H.

2017-12-01

Quantifying litter C into different C fluxes during litter decomposition is necessary to understand carbon cycling under changing climatic conditions. Rainfall patterns are predicted to change in the future, and their effects on the fate of litter carbon are poorly understood. Soils from deciduous forests in Smithsonian Environmental Research Center (SERC) in Maryland, USA were collected to reconstruct soil columns in the lab. 13C labeled tulip poplar leaf litter was used to trace carbon during litter decomposition. Top 1% and the mean of 15-minute historical precipitation data from nearby weather stations were considered as extreme and control rainfall intensity, respectively. Both intensity and frequency of rainfall were manipulated, while the total amount was kept constant. A pulse of CO2 efflux was detected right after each rainfall event in the soil columns with leaf litter. After the first event, CO2 efflux of the control rainfall treatment soils increased to threefold of the CO2 efflux before rain event and that of the extreme treatment soils increased to fivefold. However, in soils without leaf litter, CO2 efflux was suppressed right after rainfall events. After each rainfall event, the leaf litter contribution to CO2 efflux first showed an increase, decreased sharply in the following two days, and then stayed relatively constant. In soil columns with leaf litter, the order of cumulative CO2 efflux was control > extreme > intermediate. The order of cumulative CO2 efflux in the bare soil treatment was extreme > intermediate > control. The order of volume of leachate from different treatments was extreme > intermediate > control. Our initial results suggest that more intense rainfall events result in larger pulses of CO2, which is rarely measured in the field. Additionally, soils with and without leaf litter respond differently to precipitation events. This is important to consider in temperate regions where leaf litter cover changes throughout the year

Short-term ensemble radar rainfall forecasts for hydrological applications

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Codo de Oliveira, M.; Rico-Ramirez, M. A.

2016-12-01

Flooding is a very common natural disaster around the world, putting local population and economy at risk. Forecasting floods several hours ahead and issuing warnings are of main importance to permit proper response in emergency situations. However, it is important to know the uncertainties related to the rainfall forecasting in order to produce more reliable forecasts. Nowcasting models (short-term rainfall forecasts) are able to produce high spatial and temporal resolution predictions that are useful in hydrological applications. Nonetheless, they are subject to uncertainties mainly due to the nowcasting model used, errors in radar rainfall estimation, temporal development of the velocity field and to the fact that precipitation processes such as growth and decay are not taken into account. In this study an ensemble generation scheme using rain gauge data as a reference to estimate radars errors is used to produce forecasts with up to 3h lead-time. The ensembles try to assess in a realistic way the residual uncertainties that remain even after correction algorithms are applied in the radar data. The ensembles produced are compered to a stochastic ensemble generator. Furthermore, the rainfall forecast output was used as an input in a hydrodynamic sewer network model and also in hydrological model for catchments of different sizes in north England. A comparative analysis was carried of how was carried out to assess how the radar uncertainties propagate into these models. The first named author is grateful to CAPES - Ciencia sem Fronteiras for funding this PhD research.

Final Scientific Report for "The Interhemispheric Pattern in 20th Century and Future Abrupt Change in Regional Tropical Rainfall"

Energy Technology Data Exchange (ETDEWEB)

Chiang, John C. H. [University of California, Berkeley, CA (United States); Wehner, Michael F. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2012-10-29

This is the final scientific report for grant DOE-FG02-08ER64588, "The Interhemispheric Pattern in 20th Century and Future Abrupt Change in Regional Tropical Rainfall."The project investigates the role of the interhemispheric pattern in surface temperature – i.e. the contrast between the northern and southern temperature changes – in driving rapid changes to tropical rainfall changes over the 20th century and future climates. Previous observational and modeling studies have shown that the tropical rainband – the Intertropical Convergence Zone (ITCZ) over marine regions, and the summer monsoonal rainfall over land – are sensitive to the interhemispheric thermal contrast; but that the link between the two has not been applied to interpreting long-term tropical rainfall changes over the 20th century and future.The specific goals of the project were to i) develop dynamical mechanisms to explain the link between the interhemispheric pattern to abrupt changes of West African and Asian monsoonal rainfall; ii) Undertake a formal detection and attribution study on the interhemispheric pattern in 20th century climate; and iii) assess the likelihood of changes to this pattern in the future. In line with these goals, our project has produced the following significant results: 1.We have developed a case that suggests that the well-known abrupt weakening of the West African monsoon in the late 1960s was part of a wider co-ordinated weakening of the West African and Asian monsoons, and driven from an abrupt cooling in the high latitude North Atlantic sea surface temperature at the same time. Our modeling work suggests that the high-latitude North Atlantic cooling is effective in driving monsoonal weakening, through driving a cooling of the Northern hemisphere that is amplified by positive radiative feedbacks. 2.We have shown that anthropogenic sulfate aerosols may have partially contributed to driving a progressively southward displacement of the Atlantic Intertropical

Predictability of rainfall and teleconnections patterns influencing on Southwest Europe from sea surfaces temperatures

Science.gov (United States)

Lorenzo, M. N.; Iglesias, I.; Taboada, J. J.; Gómez-Gesteira, M.; Ramos, A. M.

2009-04-01

This work assesses the possibility of doing a forecast of rainfall and the main teleconnections patterns that influences climate in Southwest Europe by using sea surface temperature anomalies (SSTA). The area under study is located in the NW Iberian Peninsula. This region has a great oceanic influence on its climate and has an important dependency of the water resources. In this way if the different SST patterns are known, the different rainfall situations can be predicted. On the other hand, the teleconnection patterns, which have strong weight on rainfall, are influenced by the SSTA of different areas. In the light of this, the aim of this study is to explore the relationship between global SSTAs, rainfall and the main teleconnection patterns influencing on Europe. The SST data with a 2.0 degree resolution was provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA. A monthly averaged data from 1 January 1951 through December 2006 was considered. The monthly precipitation data from 1951-2006 were obtained from the database CLIMA of the University of Santiago de Compostela with data from the Meteorological State Agency (AEMET) and the Regional Government of Galicia. The teleconnection indices were taken of the Climate Prediction Center of the NOAA between 1950 and 2006. A monthly and seasonal study was analysed considering up to three months of delay in the first case and up to four seasons of delay in the second case. The Pearson product-moment correlation coefficient r was considered to quantify linear associations between SSTA and precipitation and/or SSTA and teleconnection indices. A test for field-significance was applied considering the properties of finiteness and interdependence of the spatial grid to avoid spurious correlations. Analysing the results obtained with the global SSTA and the teleconnection indices, a great number of ocean regions with high correlations can be found. The spatial patterns show very high correlations with Indian Ocean waters

Regionalization of monthly rainfall erosivity patternsin Switzerland

Science.gov (United States)

Schmidt, Simon; Alewell, Christine; Panagos, Panos; Meusburger, Katrin

2016-10-01

One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression-kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of

Markov chain analysis of the rainfall patterns of five geographical locations in the south eastern coast of Ghana

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Meshach Tettey

2017-08-01

Full Text Available Abstract This study develops an objective rainfall pattern assessment through Markov chain analysis using daily rainfall data from 1980 to 2010, a period of 30 years, for five cities or towns along the south eastern coastal belt of Ghana; Cape Coast, Accra, Akuse, Akatsi and Keta. Transition matrices were computed for each town and each month using the conditional probability of rain or no rain on a particular day given that it rained or did not rain on the previous day. The steady state transition matrices and the steady state probability vectors were also computed for each town and each month. It was found that, the rainy or dry season pattern observed using the monthly steady state rainfall vectors tended to reflect the monthly rainfall time series trajectory. Overall, the probability of rain on any day was low to average: Keta 0.227, Akuse 0.382, Accra 0.467, Cape Coast, 0.50 and Akatsi 0.50. In particular, for Accra, the rainy season was observed to be in the months of May to June and September to October. We also determined that the probability of rainfall generally tended to increase from east to west along the south eastern coast of Ghana.

Very short-term rainfall forecasting by effectively using the ensemble outputs of numerical weather prediction models

Science.gov (United States)

Wu, Ming-Chang; Lin, Gwo-Fong; Feng, Lei; Hwang, Gong-Do

2017-04-01

In Taiwan, heavy rainfall brought by typhoons often causes serious disasters and leads to loss of life and property. In order to reduce the impact of these disasters, accurate rainfall forecasts are always important for civil protection authorities to prepare proper measures in advance. In this study, a methodology is proposed for providing very short-term (1- to 6-h ahead) rainfall forecasts in a basin-scale area. The proposed methodology is developed based on the use of analogy reasoning approach to effectively integrate the ensemble precipitation forecasts from a numerical weather prediction system in Taiwan. To demonstrate the potential of the proposed methodology, an application to a basin-scale area (the Choshui River basin located in west-central Taiwan) during five typhoons is conducted. The results indicate that the proposed methodology yields more accurate hourly rainfall forecasts, especially the forecasts with a lead time of 1 to 3 hours. On average, improvement of the Nash-Sutcliffe efficiency coefficient is about 14% due to the effective use of the ensemble forecasts through the proposed methodology. The proposed methodology is expected to be useful for providing accurate very short-term rainfall forecasts during typhoons.

The Diurnal and Semidiurnal Patterns of Rainfall and its Correlation to the Stream Flow Characteristic in the Ciliwung Watershed, West Java, Indonesia

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Riawan Edi

2018-01-01

Full Text Available Based on the data analysis of 16 years of TMPA dataset, the common patterns of rainfall over the Ciliwung River Basin are diurnal and semidiurnal. Those patterns can be associated by a stationary or moving rainstorm with different magnitude and direction. Based on hydrological model simulations, both the pattern and movement have a significant role to the discharge. At the downstream area, the discharge that triggered by semidiurnal pattern of rainfall can produces higher peak discharge and longer flood duration than diurnal pattern. This result open possibility to improve our prediction on design discharge.

FROM RAINFALL DATA

Directory of Open Access Journals (Sweden)

Sisuru Sendanayake

2015-01-01

Full Text Available There are many correlations developed to predict incident solar radiation at a givenlocation developed based on geographical and meteorological parameters. However, allcorrelations depend on accurate measurement and availability of weather data such assunshine duration, cloud cover, relative humidity, maximum and minimumtemperatures etc, which essentially is a costly exercise in terms of equipment andlabour. Sri Lanka being a tropical island of latitudinal change of only 30 along thelength of the country, the meteorological factors govern the amount of incidentradiation. Considering the cloud formation and wind patterns over Sri Lanka as well asthe seasonal rainfall patterns, it can be observed that the mean number of rainy dayscan be used to predict the monthly average daily global radiation which can be used forcalculations in solar related activities conveniently.

Impacts of different rainfall patterns on hyporheic zone under transient conditions

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Liu, Suning; Chui, Ting Fong May

2018-06-01

The hyporheic zone (HZ) plays an important role in stream ecology. Previous studies have mainly focused on the factors influencing the HZ in the steady state. However, the exchange between surface water and groundwater in the HZ can become transient during a storm. This study investigates the impacts of different rainfall patterns (varying in intensity and duration) on the HZ under transient conditions. A two-dimensional numerical model of a 10-m long and 2-m deep domain is developed, in which the streambed consists of a series of dunes. Brinkman-Darcy and Navier-Stokes equations are respectively solved for groundwater and surface water, and velocity and pressure are coupled at the interface (i.e., the streambed surface). To compare the results under different transient conditions, this study proposes two indicators, i.e., the influential time (IT, the time required for the HZ to return to its initial state once it starts to change) and the influential depth (ID, the maximum increment in the HZ depth). To detect the extent to which the HZ undergoes significant spatial changes, moving split-window and inflection point tests are conducted. The results indicate that rainfall intensity (RI) and rainfall duration (RD) both display logarithmic relationships with the IT and ID with high coefficients of determination, but only between certain lower and upper thresholds of the RI and RD. Moreover, the distributions of the IT and ID as a function of the RI and RD are mapped using the surface spline and kriging interpolation methods to facilitate future prediction of the IT and ID. In addition, it is observed that the IT has a linear negative correlation with the groundwater response while the ID is not affected by different groundwater responses. All of the derived relationships can be used to predict the impacts of a future rainfall event on the HZ.

Impacts of spectral nudging on the simulation of present-day rainfall patterns over southern Africa

CSIR Research Space (South Africa)

Muthige, Mavhungu S

2016-10-01

Full Text Available on the simulation rainfall patterns in Southern Africa. We use the Conformal-Cubic Atmospheric Model (CCAM) as RCM to downscale ERA-interim reanalysis data to a resolution of 50 km in the horizontal over the globe. A scale-selective filter (spectral nudging...

Assessing Intelligent Models in Forecasting Monthly Rainfall by Means of Teleconnection Patterns (Case Study: Khorasan Razavi Province

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Farzaneh Nazarieh

2016-02-01

Full Text Available Introduction: Rainfall is affected by changes in the global sea level change, especially changes in sea surface temperature SST Sea Surface Temperature and sea level pressure SLP Sea level Pressure. Climate anomalies being related to each other at large distance is called teleconnection. As physical relationships between rainfall and teleconnection patterns are not defined clearly, we used intelligent models for forecasting rainfall. The intelligent models used in this study included Fuzzy Inference Systems, neural network and Neuro-fuzzy. In this study, first the teleconnection indices that could affect rainfall in the study area were identified. Then intelligent models were trained for rainfall forecasting. Finally, the most capable model for forecasting rainfall was presented. The study area for this research is the Khorasan Razavi Province. In order to present a model for rainfall forecasting, rainfall data of seven synoptic stations including Mashhad, Golmakan, Nishapur, Sabzevar, Kashmar, Torbate and Sharks since 1991 to 2010 were used. Materials and Methods: Based on previous studies about Teleconnection Patterns in the study area, effective Teleconnection indexes were identified. After calculating the correlation between the identified teleconnection indices and rainfall in one, two and three months ahead for all stations, fourteen teleconnection indices were chosen as inputs for intelligent models. These indices include, SLP Adriatic , SLP northern Red Sea, SLP Mediterranean Sea, SLP Aral sea, SST Sea surface temperature Labrador sea, SST Oman Sea, SST Caspian Sea, SST Persian Gulf, North Pacific pattern, SST Tropical Pacific in NINO12 and NINO3 regions, North Pacific Oscillation, Trans-Nino Index, Multivariable Enso Index. Inputs of the intelligent models include fourteen teleconnection indices, latitude and altitude of each station and their outputs are the prediction of rainfall for one, two and three months ahead. For calibration of

A comprehensive analysis of coherent rainfall patterns in China and potential drivers. Part I: Interannual variability

Science.gov (United States)

Stephan, Claudia Christine; Klingaman, Nicholas Pappas; Vidale, Pier Luigi; Turner, Andrew George; Demory, Marie-Estelle; Guo, Liang

2018-06-01

Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. To improve its understanding and prediction, many studies have associated precipitation variability with particular causes for specific seasons and regions. Here, a consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to 1951-2007 high-resolution precipitation observations over China in all seasons. Instead of maximizing the explained space-time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. The EOT method is validated by the reproduction of known relationships to the El Niño Southern Oscillation (ENSO): high positive correlations with ENSO are found in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that wintertime rainfall variability along the southeast coast is associated with anomalous convection over the tropical eastern Atlantic and communicated to China through a zonal wavenumber-three Rossby wave. Furthermore, spring rainfall variability in the Yangtze valley is related to upper-tropospheric midlatitude perturbations that are part of a Rossby wave pattern with its origin in the North Atlantic. A circumglobal wave pattern in the northern hemisphere is also associated with autumn precipitation variability in eastern areas. The analysis is objective, comprehensive, and produces timeseries that are tied to specific locations in China. This facilitates the interpretation of associated dynamical processes, is useful for understanding the regional hydrological cycle, and allows the results to serve as a benchmark for assessing general circulation models.

The Role of Indian Ocean SST Anomalies in Modulating Regional Rainfall Variability and Long-term Change

Science.gov (United States)

Ummenhofer, C. C.; Sen Gupta, A.; England, M. H.

2008-12-01

In a series of atmospheric general circulation model simulations, the potential impact of Indian Ocean sea surface temperature (SST) anomalies in modulating low- to mid-latitude precipitation around the Indian Ocean rim countries is explored. The relative importance of various characteristic tropical and subtropical Indian Ocean SST poles, both individually and in combination, to regional precipitation changes is quantified. A mechanism for the rainfall modulation is proposed, by which the SST anomalies induce changes in the thermal properties of the atmosphere, resulting in a reorganization of the large-scale atmospheric circulation across the Indian Ocean basin. Across western and southern regions of Australia, rainfall anomalies are found to be due to modulations in the meridional thickness gradient, thermal wind, and baroclinicity, leading to changes in the moisture flux onto the continent. The pattern of large-scale circulation changes over the tropical Indian Ocean and adjacent land masses is consistent with an anomalous strengthening of the Walker cell, leading to variations in precipitation of opposite sign across western and eastern regions of the basin. Links between long-term changes in Indian Ocean surface properties and regional precipitation changes in Indian Ocean rim countries are also discussed in a broader context with implications for water management and seasonal forecasting.

Rainfall Patterns and U.S. Migration from Rural Mexico

Science.gov (United States)

Hunter, Lori M.; Murray, Sheena; Riosmena, Fernando

2014-01-01

In many rural regions of developing countries, natural resource dependency means changes in climate patterns hold tremendous potential to impact livelihoods. When environmentally-based livelihood options are constrained, migration can become an important adaptive strategy. Using data from the Mexican Migration Project, we model U.S. emigration from rural communities as related to community, household and climate factors. The results suggest that households subjected to recent drought conditions are far more likely to send a U.S. migrant, but only in communities with strong migration histories. In regions lacking such social networks, rainfall deficits actually reduce migration propensities, perhaps reflecting constraints in the ability to engage in migration as a coping strategy. Policy implications emphasize diversification of rural Mexican livelihoods in the face of contemporary climate change. PMID:25473143

Darfur: rainfall and conflict

International Nuclear Information System (INIS)

Kevane, Michael; Gray, Leslie

2008-01-01

Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972-2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa

Darfur: rainfall and conflict

Science.gov (United States)

Kevane, Michael; Gray, Leslie

2008-07-01

Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972 2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa.

Recurrent daily rainfall patterns over South Africa and associated dynamics during the core of the austral summer

CSIR Research Space (South Africa)

Cretat, J

2010-12-01

Full Text Available field instead of atmospheric processes and dynamics. An original agglomerative hierarchical clustering approach is used to classify daily rainfall patterns recorded at 5352 stations from DJF 1971 to DJF 1999. Five clusters are retained for analysis...

The cross wavelet and wavelet coherence analysis of spatio-temporal rainfall-groundwater system in Pingtung plain, Taiwan

Science.gov (United States)

Lin, Yuan-Chien; Yu, Hwa-Lung

2013-04-01

The increasing frequency and intensity of extreme rainfall events has been observed recently in Taiwan. Particularly, Typhoon Morakot, Typhoon Fanapi, and Typhoon Megi consecutively brought record-breaking intensity and magnitude of rainfalls to different locations of Taiwan in these two years. However, records show the extreme rainfall events did not elevate the amount of annual rainfall accordingly. Conversely, the increasing frequency of droughts has also been occurring in Taiwan. The challenges have been confronted by governmental agencies and scientific communities to come up with effective adaptation strategies for natural disaster reduction and sustainable environment establishment. Groundwater has long been a reliable water source for a variety of domestic, agricultural, and industrial uses because of its stable quantity and quality. In Taiwan, groundwater accounts for the largest proportion of all water resources for about 40%. This study plans to identify and quantify the nonlinear relationship between precipitation and groundwater recharge, find the non-stationary time-frequency relations between the variations of rainfall and groundwater levels to understand the phase difference of time series. Groundwater level data and over-50-years hourly rainfall records obtained from 20 weather stations in Pingtung Plain, Taiwan has been collected. Extract the space-time pattern by EOF method, which is a decomposition of a signal or data set in terms of orthogonal basis functions determined from the data for both time series and spatial patterns, to identify the important spatial pattern of groundwater recharge and using cross wavelet and wavelet coherence method to identify the relationship between rainfall and groundwater levels. Results show that EOF method can specify the spatial-temporal patterns which represents certain geological characteristics and other mechanisms of groundwater, and the wavelet coherence method can identify general correlation between

Prediction of meteorological parameters - 3: Rainfall and droughts

International Nuclear Information System (INIS)

Njau, E.C.

1990-11-01

We describe two new methods by which rainfall and hence meteorological droughts at any location on the earth may be predicted. The first method is based upon well supported observations that rainfall distribution at a given location during any local sunspot-related temperature/heat cycle is approximately similar to the distribution during another cycle associated with approximately similar sunspot cycle provided that the two temperature/heat cycles involved are immediately preceded by approximately similar sunspot cycles. The second method is based upon the fact that rainfall belts or patterns seem to be closely related to certain spatial and time-dependent temperature/heat patterns in the earth-atmosphere system. Reasonable predictions of these temperature/heat patterns may be made, and hence the associated rainfall patterns or belts may correspondingly be predicted. Specific examples are given to illustrate the two prediction methods. (author). 12 refs, 11 figs, 1 tab

Monthly Rainfall Erosivity Assessment for Switzerland

Science.gov (United States)

Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

2016-04-01

Water erosion is crucially controlled by rainfall erosivity, which is quantified out of the kinetic energy of raindrop impact and associated surface runoff. Rainfall erosivity is often expressed as the R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). Just like precipitation, the rainfall erosivity of Switzerland has a characteristic seasonal dynamic throughout the year. This inter-annual variability is to be assessed by a monthly and seasonal modelling approach. We used a network of 86 precipitation gauging stations with a 10-minute temporal resolution to calculate long-term average monthly R-factors. Stepwise regression and Monte Carlo Cross Validation (MCCV) was used to select spatial covariates to explain the spatial pattern of R-factor for each month across Switzerland. The regionalized monthly R-factor is mapped by its individual regression equation and the ordinary kriging interpolation of its residuals (Regression-Kriging). As covariates, a variety of precipitation indicator data has been included like snow height, a combination of hourly gauging measurements and radar observations (CombiPrecip), mean monthly alpine precipitation (EURO4M-APGD) and monthly precipitation sums (Rhires). Topographic parameters were also significant explanatory variables for single months. The comparison of all 12 monthly rainfall erosivity maps showed seasonality with highest rainfall erosivity in summer (June, July, and August) and lowest rainfall erosivity in winter months. Besides the inter-annual temporal regime, a seasonal spatial variability was detectable. Spatial maps of monthly rainfall erosivity are presented for the first time for Switzerland. The assessment of the spatial and temporal dynamic behaviour of the R-factor is valuable for the identification of more susceptible seasons and regions as well as for the application of selective erosion control measures. A combination with monthly vegetation

SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture

Science.gov (United States)

Ciabatta, Luca; Massari, Christian; Brocca, Luca; Gruber, Alexander; Reimer, Christoph; Hahn, Sebastian; Paulik, Christoph; Dorigo, Wouter; Kidd, Richard; Wagner, Wolfgang

2018-02-01

Accurate and long-term rainfall estimates are the main inputs for several applications, from crop modeling to climate analysis. In this study, we present a new rainfall data set (SM2RAIN-CCI) obtained from the inversion of the satellite soil moisture (SM) observations derived from the ESA Climate Change Initiative (CCI) via SM2RAIN (Brocca et al., 2014). Daily rainfall estimates are generated for an 18-year long period (1998-2015), with a spatial sampling of 0.25° on a global scale, and are based on the integration of the ACTIVE and the PASSIVE ESA CCI SM data sets.The quality of the SM2RAIN-CCI rainfall data set is evaluated by comparing it with two state-of-the-art rainfall satellite products, i.e. the Tropical Measurement Mission Multi-satellite Precipitation Analysis 3B42 real-time product (TMPA 3B42RT) and the Climate Prediction Center Morphing Technique (CMORPH), and one modeled data set (ERA-Interim). A quality check is carried out on a global scale at 1° of spatial sampling and 5 days of temporal sampling by comparing these products with the gauge-based Global Precipitation Climatology Centre Full Data Daily (GPCC-FDD) product. SM2RAIN-CCI shows relatively good results in terms of correlation coefficient (median value > 0.56), root mean square difference (RMSD, median value test the capabilities of the data set to correctly identify rainfall events under different climate and precipitation regimes.The SM2RAIN-CCI rainfall data set is freely available at https://doi.org/10.5281/zenodo.846259.

[Effects of rainfall intensity on rainfall infiltration and redistribution in soil on Loess slope land].

Science.gov (United States)

Li, Yi; Shao, Ming'an

2006-12-01

With simulation test, this paper studied the patterns of rainfall infiltration and redistribution in soil on typical Loess slope land, and analyzed the quantitative relations between the infiltration and redistribution and the movement of soil water and mass, with rainfall intensity as the main affecting factor. The results showed that rainfall intensity had significant effects on the rainfall infiltration and water redistribution in soil, and the microcosmic movement of soil water. The larger the rainfall intensity, the deeper the wetting front of rainfall infiltration and redistribution was, and the wetting front of soil water redistribution had a slower increase velocity than that of rainfall infiltration. The power function of the wetting front with time, and also with rainfall intensity, was fitted well. There was also a quantitative relation between the wetting front of rainfall redistribution and the duration of rainfall. The larger the rainfall intensity, the higher the initial and steady infiltration rates were, and the cumulative infiltration increased faster with time. Moreover, the larger the rainfall intensity, the smaller the wetting front difference was at the top and the end of the slope. With the larger rainfall intensity, both the difference of soil water content and its descending trend between soil layers became more obvious during the redistribution process on slope land.

Implication of Negative Entropy Flow for Local Rainfall

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Zhaohui Li

2013-08-01

Full Text Available The relation between the atmospheric entropy flow field and local rainfall is examined in terms of the theory of dissipative structures. In this paper, the entropy balance equation in a form suitable for describing the entropy budget of the Earth’s atmosphere is derived starting from the Gibbs relation, and, as examples, the entropy flows of the two severe weather events associated with the development of an extratropical cyclone and a tropical storm are calculated, respectively. The results show that negative entropy flow (NEF has a significant effect on the precipitation intensity and scope with an apparent matching of the NEF’s pattern with the rainfall distribution revealed and, that the diagnosis of NEF is able to provide a good indicator for precipitation forecasting.

Application of hierarchical clustering method to classify of space-time rainfall patterns

Science.gov (United States)

Yu, Hwa-Lung; Chang, Tu-Je

2010-05-01

Understanding the local precipitation patterns is essential to the water resources management and flooding mitigation. The precipitation patterns can vary in space and time depending upon the factors from different spatial scales such as local topological changes and macroscopic atmospheric circulation. The spatiotemporal variation of precipitation in Taiwan is significant due to its complex terrain and its location at west pacific and subtropical area, where is the boundary between the pacific ocean and Asia continent with the complex interactions among the climatic processes. This study characterizes local-scale precipitation patterns by classifying the historical space-time precipitation records. We applied the hierarchical ascending clustering method to analyze the precipitation records from 1960 to 2008 at the six rainfall stations located in Lan-yang catchment at the northeast of the island. Our results identify the four primary space-time precipitation types which may result from distinct driving forces from the changes of atmospheric variables and topology at different space-time scales. This study also presents an important application of the statistical downscaling to combine large-scale upper-air circulation with local space-time precipitation patterns.

Tendencies of extreme values on rainfall and temperature and its relationship with teleconnection patterns

Science.gov (United States)

Taboada, J. J.; Cabrejo, A.; Guarin, D.; Ramos, A. M.

2009-04-01

It is now very well established that yearly averaged temperatures are increasing due to anthropogenic climate change. In the area of Galicia (NW Spain) this trend has also been determined. Rainfall does not show a clear tendency in its yearly accumulated values. The aim of this work is to study different extreme indices of rainfall and temperatures analysing variability and possible trends associated to climate change. Station data for the study was provided by the CLIMA database of the regional government of Galicia (NW Spain). The definition of the extreme indices was taken from the joint CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI) This group has defined a set of standard extreme values to simplify intercomparison of data from different regions of the world. For the temperatures in the period 1960-2006, results show a significant increase of the number of days with maximum temperatures above the 90th percentile. Furthermore, a significant decrease of the days with maximum temperatures below the 10th percentile has been found. The tendencies of minimum temperatures are reverse: fewer nights with minimum temperatures below 10th percentile, and more with minimum temperatures above 90th percentile. Those tendencies can be observed all over the year, but are more pronounced in summer. This trend is expected to continue in the next decades because of anthropogenic climate change. We have also calculated the relationship between the above mentioned extreme values and different teleconnection patterns appearing in the North Atlantic area. Results show that local tendencies are associated with trends of EA (Eastern Atlantic) and SCA (Scandinavian) patterns. NAO (North Atlantic Oscillation) has also some relationship with these tendencies, but only related with cold days and nights in winter. Rainfall index do not show any clear tendency on the annual scale. Nevertheless, the count of days when precipitation is greater than 20mm (R20

Forecasting the heavy rainfall during Himalayan flooding—June 2013

Directory of Open Access Journals (Sweden)

Anumeha Dube

2014-08-01

Verification of the synoptic features in forecasts of the two models suggests that NCUM accurately captures the circulation features as compared to T574. Further verification of this event is carried out based on the contiguous rain area (CRA technique. CRA verification is used in computing the total mean square error (MSE which is based on displacement, volume and pattern errors. This verification technique also, confirms the better skill of NCUM over T574 in terms of forecast peak rainfall amounts, volume and average rain rate, lower MSE and root mean square error (RMSE as well as having higher hit rates and lower misses and false alarm rates for different rainfall thresholds from Day 1 to Day 5 forecasts.

MECO Warming Changes Continental Rainfall Patterns in Eocene Western North America

Science.gov (United States)

Methner, K.; Mulch, A.; Fiebig, J.; Wacker, U.; Gerdes, A.; Graham, S. A.; Chamberlain, C. P.

2016-12-01

Eocene hyperthermals represent temperature extremes superimposed on an existing warm climate. They dramatically affected the marine and terrestrial biosphere, but still remain among the most enigmatic phenomena of Cenozoic climate dynamics. To evaluate the impacts of global warm periods on terrestrial temperature and rainfall records in continental interiors, we sampled a suite of middle Eocene ( 40 Ma) paleosols from a high-elevation mammal fossil locality in the hinterland of the North American Cordillera (Sage Creek Basin, Montana, USA) and integrated laser ablation U-Pb dating of pedogenic carbonate, stable isotope (δ18O) and clumped isotope temperature (Δ47) records. Δ47 temperature data of soil carbonates progressively increase from 23 °C ±3 °C to peak temperatures of 32 °C ±3 °C and subsequently drop to 21 °C ±2 °C and delineate a rapid +9/-11 °C temperature excursion in the paleosol record. This hyperthermal event is accompanied by large and rapid shifts towards low δ18O values and reduced pedogenic CaCO3 contents. U-Pb geochronology of the paleosol carbonate confirms a middle Eocene age for soil carbonate formation (39.5 ±1.4 Ma and 40.1 ±0.8 Ma). Based on U-Pb geochronology, magneto- and biostratigraphy we suggest that the recorded Δ47 temperature excursion reflects peak warming during the Middle Eocene Climatic Optimum (MECO). The MECO in continental western North America appears to be characterized by warmer and wetter (sub-humid) conditions in this high-elevation site. Shifts in δ18O values of precipitation and pedogenic CaCO3 contents parallel temperature changes and require modification of mid-latitude rainfall patterns, indicating a profound impact of the MECO on the hydrological cycle and consequently on atmospheric circulation patterns in the hinterland of the North American Cordillera.

Lysimeter study to investigate the effect of rainfall patterns on leaching of isoproturon.

Science.gov (United States)

Beulke, Sabine; Brown, Colin D; Fryer, Christopher J; Walker, Allan

2002-01-01

The influence of five rainfall treatments on water and solute leaching through two contrasting soil types was investigated. Undisturbed lysimeters (diameter 0.25 m, length 0.5 m) from a sandy loam (Wick series) and a moderately structured clay loam (Hodnet series) received autumn applications of the radio-labelled pesticide isoproturon and bromide tracer. Target rainfall plus irrigation from the end of November 1997 to May 1998 ranged from drier to wetter than average (235 to 414 mm); monthly rainfall was varied according to a pre-selected pattern or kept constant (triplicate lysimeters per regime). Leachate was collected at intervals and concentrations of the solutes were determined. Total flow (0.27-0.94 pore volumes) and losses of bromide (3-80% of applied) increased with increasing inputs of water and were larger from the Wick sandy loam than from the Hodnet clay loam soil. Matrix flow appeared to be the main mechanism for transport of isoproturon through the Wick soil whereas there was a greater influence of preferential flow for the Hodnet lysimeters. The total leached load of isoproturon from the Wick lysimeters was 0.02-0.26% of that applied. There was no clear variation in transport processes between the rainfall treatments investigated for this soil and there was an approximately linear relationship (r2 = 0.81) between leached load and total flow. Losses of isoproturon from the Hodnet soil were 0.03-0.39% of applied and there was evidence of enhanced preferential flow in the driest and wettest treatments. Leaching of isoproturon was best described by an exponential relationship between load and total flow (r2 = 0.62). A 45% increase in flow between the two wettest treatments gave a 100% increase in leaching of isoproturon from the Wick soil. For the Hodnet lysimeters, a 35% increase in flow between the same treatments increased herbicide loss by 325%.

Effect of Variations in Long-Duration Rainfall Intensity on Unsaturated Slope Stability

OpenAIRE

Hsin-Fu Yeh; Yi-Jin Tsai

2018-01-01

In recent years, many scientific methods have been used to prove that the Earth’s climate is changing. Climate change can affect rainfall patterns, which can in turn affect slope safety. Therefore, this study analyzed the effects of climate change on rainfall patterns from the perspective of rainfall intensity. This analysis was combined with numerical model analysis to examine the rainfall patterns of the Zengwen reservoir catchment area and its effects on slope stability. In this study, the...

Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

Science.gov (United States)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

Science.gov (United States)

Hassan, Zulkarnain; Haidir, Ahmad; Saad, Farah Naemah Mohd; Ayob, Afizah; Rahim, Mustaqqim Abdul; Ghazaly, Zuhayr Md.

2018-03-01

The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015) data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM), as compared to Southwest monsoon (SWM). Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

Directory of Open Access Journals (Sweden)

Hassan Zulkarnain

2018-01-01

Full Text Available The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015 data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM, as compared to Southwest monsoon (SWM. Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

Do we really use rainfall observations consistent with reality in hydrological modelling?

Science.gov (United States)

Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

2017-04-01

Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

Teleconnection between sea ice in the Barents Sea in June and the Silk Road, Pacific-Japan and East Asian rainfall patterns in August

Science.gov (United States)

He, Shengping; Gao, Yongqi; Furevik, Tore; Wang, Huijun; Li, Fei

2018-01-01

In contrast to previous studies that have tended to focus on the influence of the total Arctic sea-ice cover on the East Asian summer tripole rainfall pattern, the present study identifies the Barents Sea as the key region where the June sea-ice variability exerts the most significant impacts on the East Asian August tripole rainfall pattern, and explores the teleconnection mechanisms involved. The results reveal that a reduction in June sea ice excites anomalous upward air motion due to strong near-surface thermal forcing, which further triggers a meridional overturning wave-like pattern extending to midlatitudes. Anomalous downward motion therefore forms over the Caspian Sea, which in turn induces zonally oriented overturning circulation along the subtropical jet stream, exhibiting the east-west Rossby wave train known as the Silk Road pattern. It is suggested that the Bonin high, a subtropical anticyclone predominant near South Korea, shows a significant anomaly due to the eastward extension of the Silk Road pattern to East Asia. As a possible descending branch of the Hadley cell, the Bonin high anomaly ultimately triggers a meridional overturning, establishing the Pacific-Japan pattern. This in turn induces an anomalous anticyclone and cyclone pair over East Asia, and a tripole vertical convection anomaly meridionally oriented over East Asia. Consequently, a tripole rainfall anomaly pattern is observed over East Asia. Results from numerical experiments using version 5 of the Community Atmosphere Model support the interpretation of this chain of events.

Effect of variations in rainfall intensity on slope stability in Singapore

OpenAIRE

Christofer Kristo; Harianto Rahardjo; Alfrendo Satyanaga

2017-01-01

Numerous scientific evidence has given credence to the true existence and deleterious impacts of climate change. One aspect of climate change is the variations in rainfall patterns, which affect the flux boundary condition across ground surface. A possible disastrous consequence of this change is the occurrence of rainfall-induced slope failures. This paper aims to investigate the variations in rainfall patterns in Singapore and its effect on slope stability. Singapore's historical rainfall d...

CORRELATION BETWEEN RAINFALL PATTERNS AND THE WATER TABLE IN THE GENERAL SEPARATIONS AREA OF THE SAVANNAH RIVER SITE

International Nuclear Information System (INIS)

Smith, C.

2009-01-01

The objective of the study was to evaluate rainfall and water table elevation data in search of a correlation that could be used to understand and predict water elevation changes. This information will be useful in placing screen zones for future monitoring wells and operations of groundwater treatment units. Fifteen wells in the General Separations Area (GSA) at Savannah River Site were evaluated from 1986 through 2001. The study revealed that the water table does respond to rainfall with minimal delay. (Water level information was available monthly, which restricted the ability to evaluate a shorter delay period.) Water elevations were found to be related to the cumulative sum (Q-Delta Sum) of the difference between the average rainfall for a specific month and the actual rainfall for that month, calculated from an arbitrary starting point. Water table elevations could also be correlated between wells, but using the right well for correlation was very important. The strongest correlation utilized a quadratic equation that takes into account the rainfall in a specific area and the rainfall from an adjacent area that contributes through a horizontal flow. Specific values vary from well to well as a result of geometry and underground variations. R2's for the best models ranged up to 0.96. The data in the report references only GSA wells but other wells (including confined water tables) on the site have been observed to return similar water level fluctuation patterns

Effect of soil warming and rainfall patterns on soil N cycling in northern Europe

DEFF Research Database (Denmark)

Patil, Raveendra Hanumantagoud; Lægdsmand, Mette; Olesen, Jørgen Eivind

2010-01-01

. These changes may affect soil moisture regimes, soil water drainage, soil nitrogen (N) availability and N leaching to aquatic environment and N2O emissions to atmosphere. Thus it is important to study the effects of increased soil temperature and varying rainfall patterns on soil N cycling in arable land from...... temperate climates, which is a major source of N pollution. An open-field lysimeter study was carried out during 2008-2009 in Denmark on loamy sand soil (Typic Hapludult) with three factors: number of rainy days, rainfall amount and soil warming. Number of rainy days included the mean monthly rainy days...... by 5 °C at 0.1 m depth as ‘heated' and non-heated as ‘control' treatments. Automated mobile rain-out shelter and irrigation system, and insulated buried heating cables were used to impose the treatments. Soil warming, compared with unheated control, advanced winter wheat crop development, and increased...

Solar activity and rainfall pattern in Tamil Nadu during the Northeast monsoon

International Nuclear Information System (INIS)

Reddy, R.S.; Mukherjee, B.K.; Ramana Murty, Bh.V.

1976-01-01

An attempt is made to examine the association, of any, between the rainfall, in Tamil Nadu and sunspot activity and if so, whether similar periodicities are also present in the sunspot activity. The daily relative sunspot numbers for the period Oct.-Dec. during 1961-70 and the daily sunspot means for the period Oct.-Dec. 1889-1938, as well as the rainfall series for the period Oct.-Nov., during 1961-70 have been analysed by power spectrum. An anti-phase relation was noticed between the rainfall and the sunspot activity. The 15-day periodicity in the rainfall was significant. The sunspot activity also showed similar periodicities as rainfall. The 30-day periodicity in the sunspot activity was significant. (author)

Solar activity and rainfall pattern in Tamil Nadu during the Northeast monsoon

Energy Technology Data Exchange (ETDEWEB)

Reddy, R S; Mukherjee, B K; Ramana Murty, Bh V [Indian Inst. of Tropical Meteorology, Pune

1976-12-01

An attempt is made to examine the association, of any, between the rainfall, in Tamil Nadu and sunspot activity and if so, whether similar periodicities are also present in the sunspot activity. The daily relative sunspot numbers for the period Oct.-Dec. during 1961-70 and the daily sunspot means for the period Oct.-Dec. 1889-1938, as well as the rainfall series for the period Oct.-Nov., during 1961-70 have been analysed by power spectrum. An anti-phase relation was noticed between the rainfall and the sunspot activity. The 15-day periodicity in the rainfall was significant. The sunspot activity also showed similar periodicities as rainfall. The 30-day periodicity in the sunspot activity was significant.

Rainfall and Development of Zika Virus

African Journals Online (AJOL)

2017-11-01

Nov 1, 2017 ... between rainfall and incidence of arbovirus disease such as dengue is well demonstrated (2). For Zika virus an infection, a similar observation can be expected. A recent report from Thailand can also show the expected pattern of the prevalence of Zika virus infection in the areas with high rainfall (3).

The Spatial Scaling of Global Rainfall Extremes

Science.gov (United States)

Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

Short Term Patterns of Landslides Causing Death in Latin America and the Caribbean

Science.gov (United States)

Sepulveda, S. A.; Petley, D. N.

2015-12-01

Among natural hazards, landslides represent a significant source of loss of life in mountainous terrains. Many regions of Latin America and the Caribbean are prone to landslide activity, due to strong topographic relief, high tectonic uplift rates, seismicity and/or climate. Further, vulnerable populations are often concentrated in deep valleys or mountain foothills susceptible to catastrophic landslides, with vulnerability further increased by dense urbanization and precarious settlements in some large cities. While historic extremely catastrophic events such as the 1999 Vargas flows in Venezuela or the 1970 Huascaran rock avalanche in Peru are commonly cited to characterize landslide hazards in this region, less known is the landslide activity in periods without such large disasters. This study assesses the occurrence of fatal landslides in Latin America and the Caribbean between 2004 and 2013. Over this time period we recorded 611 landslides that caused 11,631 deaths in 25 countries, mostly as a result of rainfall triggers. The countries with the highest number of fatal landslides are Brazil, Colombia, Mexico, Guatemala, Peru and Haiti. The highest death toll for a single event was ca.3000. The dataset has not captured a strong El Niño event or large earthquakes in landslide prone areas, thus the analysis is indicative of short term rather than long term spatial and temporal patterns. Results show that at continental scale, the spatial distribution of landslides in the 2004-2013 period correlates well with relief, precipitation and population density, while the temporal distribution reflects the regional annual rainfall patterns. In urban areas, the presence of informal settlements has a big impact on the number of fatalities, while at national level weaker correlations with gross income, human development and corruption indices can be found. This work was funded by the Durham International Fellowships for Research and Enterprise and Fondecyt project 1140317.

Application of the Hess-Brezowsky classification to the identification of weather patterns causing heavy winter rainfall in Brittany (France

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O. Planchon

2009-07-01

Full Text Available An accurate knowledge of the weather patterns causing winter rainfall over the Scorff watershed in western Brittany (W. France was developed prior to studies of the impact of the climate factor on land use management, and of the hydrological reponses to rain-producing weather patterns. These two studies are carried out in the context of the climate change. The identification of rainy air-circulation types was realized using the objective computational version of the 29-type Hess and Brezowsky Grosswetterlagen system of classifying European synoptic regimes, for the cold season (November-March of the 1958–2005 period at the reference weather station of Lorient, and 13 other stations located in western and southern Brittany, including a more detailed study for the wet 2000–2001 cold season for three reference stations of the Scorff watershed (Lorient, Plouay and Plouray. The precipitation proportion (including the days with rainfall ≥20 mm was calculated by major air-circulation type (GWT: see Appendix A and by individual air-circulation subtype (GWL: see Appendix A for the studied time-period. The most frequently occurrence of rainy days associated with westerly and southerly GWL confirmed well-known observations in western Europe and so justify the use of the Hess-Brezowsky classification in other areas outside Central Europe. The southern or south-western exposure of the watershed with a hilly inland area enhanced the heavy rainfall generated by the SW and S circulation types, and increased the difference between the rainfall amounts of coastal and inland stations during the wettest days.

Fluvial signatures of modern and paleo orographic rainfall gradients

Science.gov (United States)

Schildgen, Taylor; Strecker, Manfred

2016-04-01

The morphology of river profiles is intimately linked to both climate and tectonic forcing. While much interest recently has focused on how river profiles can be inverted to derive uplift histories, here we show how in regions of strong orographic rainfall gradients, rivers may primarily record spatial patterns of precipitation. As a case study, we examine the eastern margin of the Andean plateau in NW Argentina, where the outward (eastward) growth of a broken foreland has led to a eastward shift in the main orographic rainfall gradient over the last several million years. Rivers influenced by the modern rainfall gradient are characterized by normalized river steepness values in tributary valleys that closely track spatial variations in rainfall, with higher steepness values in drier areas and lower steepness values in wetter areas. The same river steepness pattern has been predicted in landscape evolution models that apply a spatial gradient in rainfall to a region of uniform erosivity and uplift rate (e.g., Han et al., 2015). Also, chi plots from river networks on individual ranges affected by the modern orographic rainfall reveal patterns consistent with assymmetric precipitation across the range: the largest channels on the windward slopes are characterized by capture, while the longest channels on the leeward slopes are dominated by beheadings. Because basins on the windward side both lengthen and widen, tributary channels in the lengthening basins are characterized by capture, while tributary channels from neighboring basins on the windward side are dominated by beheadings. These patterns from the rivers influenced by the modern orographic rainfall gradient provide a guide for identifying river morphometric signatures of paleo orographic rainfall gradients. Mountain ranges to the west of the modern orographic rainfall have been interpreted to mark the location of orographic rainfall in the past, but these ranges are now in spatially near-uniform semi-arid to

Watershed soil Cd loss after long-term agricultural practice and biochar amendment under four rainfall levels.

Science.gov (United States)

Ouyang, Wei; Huang, Weijia; Hao, Xin; Tysklind, Mats; Haglund, Peter; Hao, Fanghua

2017-10-01

Some heavy metals in farmland soil can be transported into the waterbody, affecting the water quality and sediment at the watershed outlet, which can be used to determine the historical loss pattern. Cd is a typical heavy metal leached from farmland that is related to phosphate fertilizers and carries serious environmental risk. The spatial-vertical pattern of Cd in soil and the vertical trend of Cd in the river sediment core were analyzed, which showed the migration and accumulation of Cd in the watershed. To prevent watershed Cd loss, biochar was employed, and leaching experiments were conducted to investigate the Cd loss from soil depending on the initial concentration. Four rainfall intensities, 1.25 mm/h, 2.50 mm/h, 5.00 mm/h, and 10.00 mm/h, were used to simulate typical rainfall scenarios for the study area. Biochar was prepared from corn straw after pretreatment with ammonium dihydrogen phosphate (ADP) and pyrolysis at 400 °C under anoxic conditions. To identify the effects of biochar amendment on Cd migration, the biochar was mixed with soil for 90 days at concentrations of 0%, 0.5%, 1.0%, 3.0%, and 5.0% soil by weight. The results showed that the Cd leaching load increased as the initial load and rainfall intensity increased and that eluviation caused surface Cd to diffuse to the deep soils. The biochar application caused more of the heavy metals to be immobilized in the amended soil rather than transported into the waterbody. The sorption efficiency of the biochar for Cd increased as the addition level increased to 3%, which showed better performance than the 5% addition level under some initial concentration and rainfall conditions. The research indicated that biochar is a potential material to prevent diffuse heavy metal pollution and that a lower addition makes the application more feasible. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of a compound distribution based on weather pattern subsampling for extreme rainfall in Norway

Directory of Open Access Journals (Sweden)

J. Blanchet

2015-12-01

SCHADEX method for extreme flood estimation. Regional scores of evaluation are used in a split sample framework to compare the MEWP distribution with more general heavy-tailed distributions, in this case the Multi Generalized Pareto Weather Pattern (MGPWP distribution. The analysis shows the clear benefit obtained from seasonal and weather pattern-based subsampling for extreme value estimation. The MEWP distribution is found to have an overall better performance as compared with the MGPWP, which tends to overfit the data and lacks robustness. Finally, we take advantage of the split sample framework to present evidence for an increase in extreme rainfall in the southwestern part of Norway during the period 1979–2009, relative to 1948–1978.

Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

Science.gov (United States)

Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

2012-04-01

During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and

Interdecadal change of the controlling mechanisms for East Asian early summer rainfall variation around the mid-1990s

Science.gov (United States)

Yim, So-Young; Wang, Bin; Kwon, MinHo

2014-03-01

East Asian (EA) summer monsoon shows considerable differences in the mean state and principal modes of interannual variation between early summer (May-June, MJ) and late summer (July-August, JA). The present study focuses on the early summer (MJ) precipitation variability. We find that the interannual variation of the MJ precipitation and the processes controlling the variation have been changed abruptly around the mid-1990s. The rainfall anomaly represented by the leading empirical orthogonal function has changed from a dipole-like pattern in pre-95 epoch (1979-1994) to a tripole-like pattern in post-95 epoch (1995-2010); the prevailing period of the corresponding principal component has also changed from 3-5 to 2-3 years. These changes are concurrent with the changes of the corresponding El Nino-Southern Oscillation (ENSO) evolutions. During the pre-95 epoch, the MJ EA rainfall anomaly is coupled to a slow decay of canonical ENSO events signified by an eastern Pacific warming, which induces a dipole rainfall feature over EA. On the other hand, during the post-95 epoch the anomalous MJ EA rainfall is significantly linked to a rapid decay of a central Pacific warming and a distinct tripolar sea surface temperature (SST) in North Atlantic. The central Pacific warming-induced Philippine Sea anticyclone induces an increased rainfall in southern China and decreased rainfall in central eastern China. The North Atlantic Oscillation-related tripolar North Atlantic SST anomaly induces a wave train that is responsible for the increase northern EA rainfall. Those two impacts form the tripole-like rainfall pattern over EA. Understanding such changes is important for improving seasonal to decadal predictions and long-term climate change in EA.

Seasonality in cholera dynamics: A rainfall-driven model explains the wide range of patterns in endemic areas

Science.gov (United States)

Baracchini, Theo; King, Aaron A.; Bouma, Menno J.; Rodó, Xavier; Bertuzzo, Enrico; Pascual, Mercedes

2017-10-01

Seasonal patterns in cholera dynamics exhibit pronounced variability across geographical regions, showing single or multiple peaks at different times of the year. Although multiple hypotheses related to local climate variables have been proposed, an understanding of this seasonal variation remains incomplete. The historical Bengal region, which encompasses the full range of cholera's seasonality observed worldwide, provides a unique opportunity to gain insights on underlying environmental drivers. Here, we propose a mechanistic, rainfall-temperature driven, stochastic epidemiological model which explicitly accounts for the fluctuations of the aquatic reservoir, and analyze with this model the historical dataset of cholera mortality in the Bengal region. Parameters are inferred with a recently developed sequential Monte Carlo method for likelihood maximization in partially observed Markov processes. Results indicate that the hydrological regime is a major driver of the seasonal dynamics of cholera. Rainfall tends to buffer the propagation of the disease in wet regions due to the longer residence times of water in the environment and an associated dilution effect, whereas it enhances cholera resurgence in dry regions. Moreover, the dynamics of the environmental water reservoir determine whether the seasonality is unimodal or bimodal, as well as its phase relative to the monsoon. Thus, the full range of seasonal patterns can be explained based solely on the local variation of rainfall and temperature. Given the close connection between cholera seasonality and environmental conditions, a deeper understanding of the underlying mechanisms would allow the better management and planning of public health policies with respect to climate variability and climate change.

Rainfall during parental care reduces reproductive and survival components of fitness in a passerine bird.

Science.gov (United States)

Öberg, Meit; Arlt, Debora; Pärt, Tomas; Laugen, Ane T; Eggers, Sönke; Low, Matthew

2015-01-01

Adverse weather conditions during parental care may have direct consequences for offspring production, but longer-term effects on juvenile and parental survival are less well known. We used long-term data on reproductive output, recruitment, and parental survival in northern wheatears (Oenanthe oenanthe) to investigate the effects of rainfall during parental care on fledging success, recruitment success (juvenile survival), and parental survival, and how these effects related to nestling age, breeding time, habitat quality, and parental nest visitation rates. While accounting for effects of temperature, fledging success was negatively related to rainfall (days > 10 mm) in the second half of the nestling period, with the magnitude of this effect being greater for breeding attempts early in the season. Recruitment success was, however, more sensitive to the number of rain days in the first half of the nestling period. Rainfall effects on parental survival differed between the sexes; males were more sensitive to rain during the nestling period than females. We demonstrate a probable mechanism driving the rainfall effects on reproductive output: Parental nest visitation rates decline with increasing amounts of daily rainfall, with this effect becoming stronger after consecutive rain days. Our study shows that rain during the nestling stage not only relates to fledging success but also has longer-term effects on recruitment and subsequent parental survival. Thus, if we want to understand or predict population responses to future climate change, we need to consider the potential impacts of changing rainfall patterns in addition to temperature, and how these will affect target species' vital rates.

Effect of Variations in Long-Duration Rainfall Intensity on Unsaturated Slope Stability

Directory of Open Access Journals (Sweden)

Hsin-Fu Yeh

2018-04-01

Full Text Available In recent years, many scientific methods have been used to prove that the Earth’s climate is changing. Climate change can affect rainfall patterns, which can in turn affect slope safety. Therefore, this study analyzed the effects of climate change on rainfall patterns from the perspective of rainfall intensity. This analysis was combined with numerical model analysis to examine the rainfall patterns of the Zengwen reservoir catchment area and its effects on slope stability. In this study, the Mann–Kendall test and the Theil–Sen estimator were used to analyze the rainfall records of rainfall stations at Da-Dong-Shan, Ma-To-Shan, and San-Jiao-Nan-Shan. The rainfall intensity of the Zengwen reservoir catchment area showed an increasing trend from 1990–2016. In addition, the analysis results of rainfall intensity trends were used for qualitative analysis of seepage and slope stability. The trend analysis result showed that in the future, from 2017–2100, if the amount of rainfall per hour continues to rise at about 0.1 mm per year, the amount of seepage will increase at the slope surface boundary and significantly change pore water pressure in the soil. As a result, the time of the occurrence of slope instability after the start of rainfall will decrease from 20 to 13 h, and the reduction in the safety coefficient will increase from 32 to 41%. Therefore, to decrease the effects of slope disasters on the safety of the Zengwen reservoir and its surrounding areas, changes in rainfall intensity trends should be considered for slope safety in this region. However, the results of trend analyses were weak and future research is needed using a wider range of precipitation data and detailed hydrological analysis to better predict rainfall pattern variations.

Extreme Rainfall In A City

Science.gov (United States)

Nkemdirim, Lawrence

Cities contain many structures and activities that are vulnerable to severe weather. Heavy precipitation cause floods which can damage structures, compromise transportation and water supply systems, and slow down economic and social activities. Rain induced flood patterns in cities must be well understood to enable effective placement of flood control and other regulatory measures. The planning goal is not to eliminate all floods but to reduce their frequency and resulting damage. Possible approaches to such planning include probability based extreme event analysis. Precipitation is normally the most variable hydrologic element over a given area. This variability results from the distribution of clouds and in cloud processes in the atmosphere, the storm path, and the distribution of topographical features on the ground along path. Some studies suggest that point rainfall patterns are also affected by urban industrial effects hence some agreement that cities are wetter than the country surrounding them. However, there are still questions regarding the intra- urban distribution of precipitation. The sealed surfaces, urban structures, and the urban heat anomaly increase convection in cities which may enhance the generation of clouds. Increased dust and gaseous aerosols loads are effective condensation and sublimation nuclei which may also enhance the generation of precipitation. Based on these associations, the greatest amount of convection type rainfall should occur at city center. A study of summer rainfall in Calgary showed that frequencies of trace amounts of rainfall and events under 0.2mm are highest downtown than elsewhere. For amounts greater than than 0.2 mm, downtown sites were not favored. The most compelling evidence for urban-industrial precipitation enhancement came from the Metromex project around St. Loius, Missouri where maximum increases of between 5 to 30 per cent in summer rainfall downwind of the city was linked to urbanization and

Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

Science.gov (United States)

Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

2017-04-01

In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a

Long term variations of extreme rainfall in Denmark and southern Sweden

DEFF Research Database (Denmark)

Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan

2015-01-01

A high number of studies have detected changes in the observed heavy rainfall in Northern and Central Europe, all adding to the debate on anthropogenic climate change and its potential impact on rainfall extremes. However, it is equally relevant to understand natural variations on which...... the anthropogenic changes are imposed. This study identifies multi-decadal variations in daily rainfall extremes from Denmark and southern Sweden, with a recurrence level relevant for flood hazard analysis. Based on smoothed series it is concluded that the frequency of the extreme events shows both a general...

Continuous rainfall simulation for regional flood risk assessment - application in the Austrian Alps

Science.gov (United States)

Salinas, Jose Luis; Nester, Thomas; Komma, Jürgen; Blöschl, Günter

2017-04-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of the observed rainfall characteristics, such as regional intensity-duration-frequency curves, is necessary to adequately model the magnitude and frequency of the flood peaks. Furthermore, the replication of the observed rainfall spatial and temporal correlations allows to model important other hydrological features like antecedent soil moisture conditions before extreme rainfall events. In this work, we present an application in the Tirol region (Austrian alps) of a modification of the model presented by Bardossy and Platte (1992), where precipitation is modeled on a station basis as a mutivariate autoregressive model (mAr) in a Normal space, and then transformed to a Gamma-distributed space. For the sake of simplicity, the parameters of the Gamma distributions are assumed to vary monthly according to a sinusoidal function, and are calibrated trying to simultaneously reproduce i) mean annual rainfall, ii) mean daily rainfall amounts, iii) standard deviations of daily rainfall amounts, and iv) 24-hours intensity duration frequency curve. The calibration of the spatial and temporal correlation parameters is performed in a way that the intensity-duration-frequency curves aggregated at different spatial and temporal scales reproduce the measured ones. Bardossy, A., and E. J. Plate (1992), Space-time model for daily rainfall using atmospheric circulation patterns, Water Resour. Res., 28(5), 1247-1259, doi:10.1029/91WR02589.

Effect of variations in rainfall intensity on slope stability in Singapore

Directory of Open Access Journals (Sweden)

Christofer Kristo

2017-12-01

Full Text Available Numerous scientific evidence has given credence to the true existence and deleterious impacts of climate change. One aspect of climate change is the variations in rainfall patterns, which affect the flux boundary condition across ground surface. A possible disastrous consequence of this change is the occurrence of rainfall-induced slope failures. This paper aims to investigate the variations in rainfall patterns in Singapore and its effect on slope stability. Singapore's historical rainfall data from Seletar and Paya Lebar weather stations for the period of 1985–2009 were obtained and analysed by duration using linear regression. A general increasing trend was observed in both weather stations, with a possible shift to longer duration rainfall events, despite being statistically insignificant according to the Mann-Kendall test. Using the derived trends, projected rainfall intensities in 2050 and 2100 were used in the seepage and slope stability analyses performed on a typical residual soil slope in Singapore. A significant reduction in factor of safety was observed in the next 50 years, with only a marginal decrease in factor of safety in the subsequent 50 years. This indicates a possible detrimental effect of variations in rainfall patterns on slope stability in Singapore, especially in the next 50 years. The statistical analyses on rainfall data from Seletar and Paya Lebar weather stations for the period of 1985–2009 indicated that rainfall intensity tend to increase over the years, with a possible shift to longer duration rainfall events in the future. The stability analyses showed a significant decrease in factor of safety from 2003 to 2050 due to increase in rainfall intensity, suggesting that a climate change might have existed beyond 2009 with possibly detrimental effects to slope stability. Keywords: Climate change, Rainfall, Seepage, Slope stability

Simulation of heavy, long-term rainfall over low mountain ranges; Simulation von Starkniederschlaegen mit langer Andauer ueber Mittelgebirgen

Energy Technology Data Exchange (ETDEWEB)

Kunz, M.

2003-03-01

A diagnostic model for the estimation of orographic precipitation during large-scale upslide motions is presented. It is based on linear theory for 3-D mountain overflow. From the simulated vertical velocities rain intensities at the ground are calculated using a model for precipitation formation. Due to the small number of free parameters and because of the simple initialisation method, e.g. with single radiosonde data, the model is used for regionalisation of precipitation from rain gauge observations as well as for deriving its statistics under dynamical constraints. For Southwest Germany and Eastern France, with the low mountain ranges of the Vosges, Black Forest and Swabian Alb, model simulations are performed for individual events with heavy rainfall. Thereby it is evaluated, how realistic rainfall patterns can be obtained with a combination of model simulations and measurement data. Mean rainfall distributions are derived from simulations of all extreme events with 24-h totals over 60 mm at selected rain gauge stations between 1971 and 2000. Furthermore the calculation of rain sums for different return periods is performed using extreme value statistics. So it is possible to quantify the hazard potential of heavy rainfall, which may cause flooding or landslides, in high spatial resolution (2.5 x 2.5 km). (orig.)

Validation of Satellite Estimates (Tropical Rainfall Measuring Mission, TRMM for Rainfall Variability over the Pacific Slope and Coast of Ecuador

Directory of Open Access Journals (Sweden)

Bolívar Erazo

2018-02-01

Full Text Available A dense rain-gauge network within continental Ecuador was used to evaluate the quality of various products of rainfall data over the Pacific slope and coast of Ecuador (EPSC. A cokriging interpolation method is applied to the rain-gauge data yielding a gridded product at 5-km resolution covering the period 1965–2015. This product is compared with the Global Precipitation Climatology Centre (GPCC dataset, the Climatic Research Unit–University of East Anglia (CRU dataset, the Tropical Rainfall Measuring Mission (TRMM/TMPA 3B43 Version 7 dataset and the ERA-Interim Reanalysis. The analysis reveals that TRMM data show the most realistic features. The relative bias index (Rbias indicates that TRMM data is closer to the observations, mainly over lowlands (mean Rbias of 7% but have more limitations in reproducing the rainfall variability over the Andes (mean Rbias of −28%. The average RMSE and Rbias of 68.7 and −2.8% of TRMM are comparable with the GPCC (69.8 and 5.7% and CRU (102.3 and −2.3% products. This study also focuses on the rainfall inter-annual variability over the study region which experiences floods that have caused high economic losses during extreme El Niño events. Finally, our analysis evaluates the ability of TRMM data to reproduce rainfall events during El Niño years over the study area and the large basins of Esmeraldas and Guayas rivers. The results show that TRMM estimates report reasonable levels of heavy rainfall detection (for the extreme 1998 El Niño event over the EPSC and specifically towards the center-south of the EPSC (Guayas basin but present underestimations for the moderate El Niño of 2002–2003 event and the weak 2009–2010 event. Generally, the rainfall seasonal features, quantity and long-term climatology patterns are relatively well estimated by TRMM.

The Use of Rainfall Variability in Flood Countermeasure Planning

Directory of Open Access Journals (Sweden)

Iis Catur Wulan Dhari

2017-09-01

Full Text Available One of the impacts of climate change is the unpredictable shifting of seasons and rainfall patterns which caused flooding. Rejoso Watershed in Pasuruan Regency is one of the watersheds that suffer from flooding almost every year due to watershed degradation characterized by land conversion and changes in the hydrological behavior including the extreme rainfall pattern. This research was aimed to investigate the effect of rainfall variability on runoff and floodwater level profile along the river channel to provide technical and non-technical recommendation for handling flood problems. The hydrological analysis was performed using HEC-HMS version 4.0 software and the hydraulic analysis was conducted using HEC-RAS version 5.0.3 software. Several variations of extreme rainfall pattern were applied in the rainfall-runoff calculation to determine the representative flood discharges that will be used as input to the hydraulic simulation for evaluating the characteristics of flood water level. The result of the research shows that rainfall with the same depth yet varies in duration and starting time generate different flood hydrographs. Rejoso River could not store flood discharge with return period of 2 years with peak discharge of 201.46 m3/s that causing overflow along the stream. The recommendation to handle flood problems is by normalization, which could reduce the overtopping at several river reaches of 4,927 m, while the combination of normalization and embankment could reduce 7,843 m from the existing river length of 12,396 m.

Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann-Kendall test

Science.gov (United States)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

2017-11-01

This study assesses the spatial pattern of changes in rainfall extremes of Sarawak in recent years (1980-2014). The Mann-Kendall (MK) test along with modified Mann-Kendall (m-MK) test, which can discriminate multi-scale variability of unidirectional trend, was used to analyze the changes at 31 stations. Taking account of the scaling effect through eliminating the effect of autocorrelation, m-MK was employed to discriminate multi-scale variability of the unidirectional trends of the annual rainfall in Sarawak. It can confirm the significance of the MK test. The annual rainfall trend from MK test showed significant changes at 95% confidence level at five stations. The seasonal trends from MK test indicate an increasing rate of rainfall during the Northeast monsoon and a decreasing trend during the Southwest monsoon in some region of Sarawak. However, the m-MK test detected an increasing trend in annual rainfall only at one station and no significant trend in seasonal rainfall at any stations. The significant increasing trends of the 1-h maximum rainfall from the MK test are detected mainly at the stations located in the urban area giving concern to the occurrence of the flash flood. On the other hand, the m-MK test detected no significant trend in 1- and 3-h maximum rainfalls at any location. On the contrary, it detected significant trends in 6- and 72-h maximum rainfalls at a station located in the Lower Rajang basin area which is an extensive low-lying agricultural area and prone to stagnant flood. These results indicate that the trends in rainfall and rainfall extremes reported in Malaysia and surrounding region should be verified with m-MK test as most of the trends may result from scaling effect.

Topographic relationships for design rainfalls over Australia

Science.gov (United States)

Johnson, F.; Hutchinson, M. F.; The, C.; Beesley, C.; Green, J.

2016-02-01

Design rainfall statistics are the primary inputs used to assess flood risk across river catchments. These statistics normally take the form of Intensity-Duration-Frequency (IDF) curves that are derived from extreme value probability distributions fitted to observed daily, and sub-daily, rainfall data. The design rainfall relationships are often required for catchments where there are limited rainfall records, particularly catchments in remote areas with high topographic relief and hence some form of interpolation is required to provide estimates in these areas. This paper assesses the topographic dependence of rainfall extremes by using elevation-dependent thin plate smoothing splines to interpolate the mean annual maximum rainfall, for periods from one to seven days, across Australia. The analyses confirm the important impact of topography in explaining the spatial patterns of these extreme rainfall statistics. Continent-wide residual and cross validation statistics are used to demonstrate the 100-fold impact of elevation in relation to horizontal coordinates in explaining the spatial patterns, consistent with previous rainfall scaling studies and observational evidence. The impact of the complexity of the fitted spline surfaces, as defined by the number of knots, and the impact of applying variance stabilising transformations to the data, were also assessed. It was found that a relatively large number of 3570 knots, suitably chosen from 8619 gauge locations, was required to minimise the summary error statistics. Square root and log data transformations were found to deliver marginally superior continent-wide cross validation statistics, in comparison to applying no data transformation, but detailed assessments of residuals in complex high rainfall regions with high topographic relief showed that no data transformation gave superior performance in these regions. These results are consistent with the understanding that in areas with modest topographic relief, as

Analysis and prediction of rainfall trends over Bangladesh using Mann-Kendall, Spearman's rho tests and ARIMA model

Science.gov (United States)

Rahman, Mohammad Atiqur; Yunsheng, Lou; Sultana, Nahid

2017-08-01

In this study, 60-year monthly rainfall data of Bangladesh were analysed to detect trends. Modified Mann-Kendall, Spearman's rho tests and Sen's slope estimators were applied to find the long-term annual, dry season and monthly trends. Sequential Mann-Kendall analysis was applied to detect the potential trend turning points. Spatial variations of the trends were examined using inverse distance weighting (IDW) interpolation. AutoRegressive integrated moving average (ARIMA) model was used for the country mean rainfall and for other two stations data which depicted the highest and the lowest trend in the Mann-Kendall and Spearman's rho tests. Results showed that there is no significant trend in annual rainfall pattern except increasing trends for Cox's Bazar, Khulna, Satkhira and decreasing trend for Srimagal areas. For the dry season, only Bogra area represented significant decreasing trend. Long-term monthly trends demonstrated a mixed pattern; both negative and positive changes were found from February to September. Comilla area showed a significant decreasing trend for consecutive 3 months while Rangpur and Khulna stations confirmed the significant rising trends for three different months in month-wise trends analysis. Rangpur station data gave a maximum increasing trend in April whereas a maximum decreasing trend was found in August for Comilla station. ARIMA models predict +3.26, +8.6 and -2.30 mm rainfall per year for the country, Cox's Bazar and Srimangal areas, respectively. However, all the test results and predictions revealed a good agreement among them in the study.

Study of Climate Change Impact to Local Rainfall Distribution in Lampung Provinces

Directory of Open Access Journals (Sweden)

Tumiar Katarina Manik

2016-08-01

Full Text Available Global warming which leads to climate change has potential affect to Indonesia agriculture activities and production. Analyzing rainfall pattern and distribution is important to investigate the impact of global climate change to local climate. This study using rainfall data from 1976-2010 from both lowland and upland area of Lampung Province. The results show that rainfall tends to decrease since the 1990s which related to the years with El Nino event. Monsoonal pattern- having rain and dry season- still excist in Lampung; however, since most rain fell below the average, it could not meet crops water need. Farmers conclude that dry seasons were longer and seasonal pattern has been changed. Global climate change might affect Lampung rainfall distribution through changes on sea surface temperature which could intensify the El Nino effect. Therefore, watching the El Nino phenomena and how global warming affects it, is important in predicting local climate especially the rainfall distribution in order to prevent significant loss in agriculture productivities.

Bias adjustment and advection interpolation of long-term high resolution radar rainfall series

DEFF Research Database (Denmark)

Thorndahl, Søren Liedtke; Nielsen, Jesper Ellerbæk; Rasmussen, Michael R.

2014-01-01

It is generally acknowledged that in order to apply radar rainfall data for hydrological proposes adjustment against ground observations are crucial. Traditionally, radar reflectivity is transformed into rainfall rates applying a fixed reflectivity – rainfall rate relationship even though...... this is known to depend on the changing drop size distribution of the specific rain. This creates a transient bias between the radar rainfall and the ground observations due to seasonal changes of the drop size distribution as well as other atmospheric effects and effects related to the radar observational...

Tree rings and rainfall in the equatorial Amazon

Science.gov (United States)

Granato-Souza, Daniela; Stahle, David W.; Barbosa, Ana Carolina; Feng, Song; Torbenson, Max C. A.; de Assis Pereira, Gabriel; Schöngart, Jochen; Barbosa, Joao Paulo; Griffin, Daniel

2018-05-01

The Amazon basin is a global center of hydroclimatic variability and biodiversity, but there are only eight instrumental rainfall stations with continuous records longer than 80 years in the entire basin, an area nearly the size of the coterminous US. The first long moisture-sensitive tree-ring chronology has been developed in the eastern equatorial Amazon of Brazil based on dendrochronological analysis of Cedrela cross sections cut during sustainable logging operations near the Rio Paru. The Rio Paru chronology dates from 1786 to 2016 and is significantly correlated with instrumental precipitation observations from 1939 to 2016. The strength and spatial scale of the precipitation signal vary during the instrumental period, but the Rio Paru chronology has been used to develop a preliminary reconstruction of February to November rainfall totals from 1786 to 2016. The reconstruction is related to SSTs in the Atlantic and especially the tropical Pacific, similar to the stronger pattern of association computed for the instrumental rainfall data from the eastern Amazon. The tree-ring data estimate extended drought and wet episodes in the mid- to late-nineteenth century, providing a valuable, long-term perspective on the moisture changes expected to emerge over the Amazon in the coming century due to deforestation and anthropogenic climate change.

Climate change and the impact of increased rainfall variability on sediment transport and catchment scale water quality

Science.gov (United States)

Hancock, G. R.; Willgoose, G. R.; Cohen, S.

2009-12-01

Recently there has been recognition that changing climate will affect rainfall and storm patterns with research directed to examine how the global hydrological cycle will respond to climate change. This study investigates the effect of different rainfall patterns on erosion and resultant water quality for a well studied tropical monsoonal catchment that is undisturbed by Europeans in the Northern Territory, Australia. Water quality has a large affect on a range of aquatic flora and fauna and a significant change in sediment could have impacts on the aquatic ecosystems. There have been several studies of the effect of climate change on rainfall patterns in the study area with projections indicating a significant increase in storm activity. Therefore it is important that the impact of this variability be assessed in terms of catchment hydrology, sediment transport and water quality. Here a numerical model of erosion and hydrology (CAESAR) is used to assess several different rainfall scenarios over a 1000 year modelled period. The results show that that increased rainfall amount and intensity increases sediment transport rates but predicted water quality was variable and non-linear but within the range of measured field data for the catchment and region. Therefore an assessment of sediment transport and water quality is a significant and complex issue that requires further understandings of the role of biophysical feedbacks such as vegetation as well as the role of humans in managing landscapes (i.e. controlled and uncontrolled fire). The study provides a robust methodology for assessing the impact of enhanced climate variability on sediment transport and water quality.

Rainfall reliability, drought and flood vulnerability in Botswana ...

African Journals Online (AJOL)

Rainfall data from 14 stations (cities, towns and major villages) spanning 26 years (1970 to 1995) were used to calculate reliability and vulnerability of rainfall in Botswana. Time series data for 72 years were generated from the long-term rainfall gauging stations and the number of wet and dry years determined. Apart from ...

Prediction of Annual Rainfall Pattern Using Hidden Markov Model ...

African Journals Online (AJOL)

ADOWIE PERE

Hidden Markov model is very influential in stochastic world because of its ... the earth from the clouds. The usual ... Rainfall modelling and ... Markov Models have become popular tools ... environment sciences, University of Jos, plateau state,.

Short-Term Forecasting of Urban Storm Water Runoff in Real-Time using Extrapolated Radar Rainfall Data

DEFF Research Database (Denmark)

Thorndahl, Søren Liedtke; Rasmussen, Michael R.

2013-01-01

Model based short-term forecasting of urban storm water runoff can be applied in realtime control of drainage systems in order to optimize system capacity during rain and minimize combined sewer overflows, improve wastewater treatment or activate alarms if local flooding is impending. A novel onl....... The radar rainfall extrapolation (nowcast) limits the lead time of the system to two hours. In this paper, the model set-up is tested on a small urban catchment for a period of 1.5 years. The 50 largest events are presented....... online system, which forecasts flows and water levels in real-time with inputs from extrapolated radar rainfall data, has been developed. The fully distributed urban drainage model includes auto-calibration using online in-sewer measurements which is seen to improve forecast skills significantly...

The spatial return level of aggregated hourly extreme rainfall in Peninsular Malaysia

Science.gov (United States)

Shaffie, Mardhiyyah; Eli, Annazirin; Wan Zin, Wan Zawiah; Jemain, Abdul Aziz

2015-07-01

This paper is intended to ascertain the spatial pattern of extreme rainfall distribution in Peninsular Malaysia at several short time intervals, i.e., on hourly basis. Motivation of this research is due to historical records of extreme rainfall in Peninsular Malaysia, whereby many hydrological disasters at this region occur within a short time period. The hourly periods considered are 1, 2, 3, 6, 12, and 24 h. Many previous hydrological studies dealt with daily rainfall data; thus, this study enables comparison to be made on the estimated performances between daily and hourly rainfall data analyses so as to identify the impact of extreme rainfall at a shorter time scale. Return levels based on the time aggregate considered are also computed. Parameter estimation using L-moment method for four probability distributions, namely, the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Pearson type III (PE3) distributions were conducted. Aided with the L-moment diagram test and mean square error (MSE) test, GLO was found to be the most appropriate distribution to represent the extreme rainfall data. At most time intervals (10, 50, and 100 years), the spatial patterns revealed that the rainfall distribution across the peninsula differ for 1- and 24-h extreme rainfalls. The outcomes of this study would provide additional information regarding patterns of extreme rainfall in Malaysia which may not be detected when considering only a higher time scale such as daily; thus, appropriate measures for shorter time scales of extreme rainfall can be planned. The implementation of such measures would be beneficial to the authorities to reduce the impact of any disastrous natural event.

A stochastic assessment of the effect of global warming on rainfall ...

African Journals Online (AJOL)

Crop production depends on rainfall, and rainfall is affected by extreme weather conditions. Markov chain and time series model are adapted for the study of the pattern of rainfall in the North Central Region of Nigeria. Results reveal the long run distributions of the dry and wet days to be 0.7841, and 0.2159 respectively.

Development and evaluation of a stochastic daily rainfall model with long-term variability

Science.gov (United States)

Kamal Chowdhury, A. F. M.; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony S.; Parana Manage, Nadeeka

2017-12-01

The primary objective of this study is to develop a stochastic rainfall generation model that can match not only the short resolution (daily) variability but also the longer resolution (monthly to multiyear) variability of observed rainfall. This study has developed a Markov chain (MC) model, which uses a two-state MC process with two parameters (wet-to-wet and dry-to-dry transition probabilities) to simulate rainfall occurrence and a gamma distribution with two parameters (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. Starting with the traditional MC-gamma model with deterministic parameters, this study has developed and assessed four other variants of the MC-gamma model with different parameterisations. The key finding is that if the parameters of the gamma distribution are randomly sampled each year from fitted distributions rather than fixed parameters with time, the variability of rainfall depths at both short and longer temporal resolutions can be preserved, while the variability of wet periods (i.e. number of wet days and mean length of wet spell) can be preserved by decadally varied MC parameters. This is a straightforward enhancement to the traditional simplest MC model and is both objective and parsimonious.

Comparing Approaches to Deal With Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

Science.gov (United States)

Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

2017-11-01

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.

Observed daily large-scale rainfall patterns during BOBMEX-1999

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

. Individual sci- entists and research institutes use these special datasets to ... including the data reporting no rain is very impor- tant to make the final merged dataset. Figures 2 and 3 show the total weekly rainfall amounts for different weeks in ...

Mixed memory, (non) Hurst effect, and maximum entropy of rainfall in the tropical Andes

Science.gov (United States)

Poveda, Germán

2011-02-01

Diverse linear and nonlinear statistical parameters of rainfall under aggregation in time and the kind of temporal memory are investigated. Data sets from the Andes of Colombia at different resolutions (15 min and 1-h), and record lengths (21 months and 8-40 years) are used. A mixture of two timescales is found in the autocorrelation and autoinformation functions, with short-term memory holding for time lags less than 15-30 min, and long-term memory onwards. Consistently, rainfall variance exhibits different temporal scaling regimes separated at 15-30 min and 24 h. Tests for the Hurst effect evidence the frailty of the R/ S approach in discerning the kind of memory in high resolution rainfall, whereas rigorous statistical tests for short-memory processes do reject the existence of the Hurst effect. Rainfall information entropy grows as a power law of aggregation time, S( T) ˜ Tβ with = 0.51, up to a timescale, TMaxEnt (70-202 h), at which entropy saturates, with β = 0 onwards. Maximum entropy is reached through a dynamic Generalized Pareto distribution, consistently with the maximum information-entropy principle for heavy-tailed random variables, and with its asymptotically infinitely divisible property. The dynamics towards the limit distribution is quantified. Tsallis q-entropies also exhibit power laws with T, such that Sq( T) ˜ Tβ( q) , with β( q) ⩽ 0 for q ⩽ 0, and β( q) ≃ 0.5 for q ⩾ 1. No clear patterns are found in the geographic distribution within and among the statistical parameters studied, confirming the strong variability of tropical Andean rainfall.

Significant Features of Warm Season Water Vapor Flux Related to Heavy Rainfall and Draught in Japan

Science.gov (United States)

Nishiyama, Koji; Iseri, Yoshihiko; Jinno, Kenji

2009-11-01

In this study, our objective is to reveal complicated relationships between spatial water vapor inflow patterns and heavy rainfall activities in Kyushu located in the western part of Japan, using the outcomes of pattern recognition of water vapor inflow, based on the Self-Organizing Map. Consequently, it could be confirmed that water vapor inflow patterns control the distribution and the frequency of heavy rainfall depending on the direction of their fluxes and the intensity of Precipitable water. Historically serious flood disasters in South Kyushu in 1993 were characterized by high frequency of the water vapor inflow patterns linking to heavy rainfall. On the other hand, severe draught in 1994 was characterized by inactive frontal activity that do not related to heavy rainfall.

Trends of rainfall regime in Peninsular Malaysia during northeast and southwest monsoons

Science.gov (United States)

Chooi Tan, Kok

2018-04-01

The trends of rainfall regime in Peninsular Malaysia is mainly affected by the seasonal monsoon. The aim of this study is to investigate the impact of northeast and southwest monsoons on the monthly rainfall patterns over Badenoch Estate, Kedah. In addition, the synoptic maps of wind vector also being developed to identify the wind pattern over Peninsular Malaysia from 2007 – 2016. On the other hand, the archived daily rainfall data is acquired from Malaysian Meteorological Department. The temporal and trends of the monthly and annual rainfall over the study area have been analysed from 2007 to 2016. Overall, the average annual precipitation over the study area from 2007 to 2016 recorded by rain gauge is 2562.35 mm per year.

Enhancement of vegetation-rainfall feedbacks on the Australian summer monsoon by the Madden-Julian Oscillation

Science.gov (United States)

Notaro, Michael

2018-01-01

A regional climate modeling analysis of the Australian monsoon system reveals a substantial modulation of vegetation-rainfall feedbacks by the Madden Julian Oscillation (MJO), both of which operate at similar sub-seasonal time scales, as evidence that the intensity of land-atmosphere interactions is sensitive to the background atmospheric state. Based on ensemble experiments with imposed modification of northern Australian leaf area index (LAI), the atmospheric responses to LAI anomalies are composited for negative and positive modes of the propagating MJO. In the regional climate model (RCM), northern Australian vegetation feedbacks are characterized by evapotranspiration (ET)-driven rainfall responses, with the moisture feedback mechanism dominating over albedo and roughness feedback mechanisms. During November-April, both Tropical Rainfall Measuring Mission and RCM data reveal MJO's pronounced influence on rainfall patterns across northern Australia, tropical Indian Ocean, Timor Sea, Arafura Sea, and Gulf of Carpentaria, with the MJO dominating over vegetation feedbacks in terms of regulating monsoon rainfall variability. Convectively-active MJO phases support an enhancement of positive vegetation feedbacks on monsoon rainfall. While the MJO imposes minimal regulation of ET responses to LAI anomalies, the vegetation feedback-induced responses in precipitable water, cloud water, and rainfall are greatly enhanced during convectively-active MJO phases over northern Australia, which are characterized by intense low-level convergence and efficient precipitable water conversion. The sub-seasonal response of vegetation-rainfall feedback intensity to the MJO is complex, with significant enhancement of rainfall responses to LAI anomalies in February during convectively-active MJO phases compared to minimal modulation by the MJO during prior and subsequent calendar months.

Derivation of critical rainfall thresholds for landslide in Sicily

Science.gov (United States)

Caracciolo, Domenico; Arnone, Elisa; Noto, Leonardo V.

2015-04-01

Rainfall is the primary trigger of shallow landslides that can cause fatalities, damage to properties and economic losses in many areas of the world. For this reason, determining the rainfall amount/intensity responsible for landslide occurrence is important, and may contribute to mitigate the related risk and save lives. Efforts have been made in different countries to investigate triggering conditions in order to define landslide-triggering rainfall thresholds. The rainfall thresholds are generally described by a functional relationship of power in terms of cumulated or intensity event rainfall-duration, whose parameters are estimated empirically from the analysis of historical rainfall events that triggered landslides. The aim of this paper is the derivation of critical rainfall thresholds for landslide occurrence in Sicily, southern Italy, by focusing particularly on the role of the antecedent wet conditions. The creation of the appropriate landslide-rainfall database likely represents one of main efforts in this type of analysis. For this work, historical landslide events occurred in Sicily from 1919 to 2001 were selected from the archive of the Sistema Informativo sulle Catastrofi Idrogeologiche, developed under the project Aree Vulnerabili Italiane. The corresponding triggering precipitations were screened from the raingauges network in Sicily, maintained by the Osservatorio delle Acque - Agenzia Regionale per i Rifiuti e le Acque. In particular, a detailed analysis was carried out to identify and reconstruct the hourly rainfall events that caused the selected landslides. A bootstrapping statistical technique has been used to determine the uncertainties associated with the threshold parameters. The rainfall thresholds at different exceedance probability levels, from 1% to 10%, were defined in terms of cumulated event rainfall, E, and rainfall duration, D. The role of rainfall prior to the damaging events was taken into account by including in the analysis

Long term high resolution rainfall runoff observations for improved water balance uncertainty and database QA-QC in the Walnut Gulch Experimental Watershed.

Science.gov (United States)

Bitew, M. M.; Goodrich, D. C.; Demaria, E.; Heilman, P.; Kautz, M. A.

2017-12-01

Walnut Gulch is a semi-arid environment experimental watershed and Long Term Agro-ecosystem Research (LTAR) site managed by USDA-ARS Southwest Watershed Research Center for which high-resolution long-term hydro-climatic data are available across its 150 km2 drainage area. In this study, we present the analysis of 50 years of continuous hourly rainfall data to evaluate runoff control and generation processes for improving the QA-QC plans of Walnut Gulch to create high-quality data set that is critical for reducing water balance uncertainties. Multiple linear regression models were developed to relate rainfall properties, runoff characteristics and watershed properties. The rainfall properties were summarized to event based total depth, maximum intensity, duration, the location of the storm center with respect to the outlet, and storm size normalized to watershed area. We evaluated the interaction between the runoff and rainfall and runoff as antecedent moisture condition (AMC), antecedent runoff condition (ARC) and, runoff depth and duration for each rainfall events. We summarized each of the watershed properties such as contributing area, slope, shape, channel length, stream density, channel flow area, and percent of the area of retention stock ponds for each of the nested catchments in Walnut Gulch. The evaluation of the model using basic and categorical statistics showed good predictive skill throughout the watersheds. The model produced correlation coefficients ranging from 0.4-0.94, Nash efficiency coefficients up to 0.77, and Kling-Gupta coefficients ranging from 0.4 to 0.98. The model predicted 92% of all runoff generations and 98% of no-runoff across all sub-watersheds in Walnut Gulch. The regression model also indicated good potential to complement the QA-QC procedures in place for Walnut Gulch dataset publications developed over the years since the 1960s through identification of inconsistencies in rainfall and runoff relations.

Rainfall distribution and change detection across climatic zones in Nigeria

OpenAIRE

Stephen Bunmi Ogungbenro; Tobi Eniolu Morakinyo

2014-01-01

Nigerian agriculture is mainly rain-fed and basically dependent on the vagaries of weather especially rainfall. Nigeria today has about forty-four (44) weather observation stations which provide measurement of rainfall amount for different locations across the country. Hence, this study investigates change detection in rainfall pattern over each climatic zone of Nigeria. Data were collected for 90 years (1910–1999) period for all the weather observation stations in Nigeria, while a subdivisio...

Multivariate analysis applied to monthly rainfall over Rio de Janeiro state, Brazil

Science.gov (United States)

Brito, Thábata T.; Oliveira-Júnior, José F.; Lyra, Gustavo B.; Gois, Givanildo; Zeri, Marcelo

2017-10-01

Spatial and temporal patterns of rainfall were identified over the state of Rio de Janeiro, southeast Brazil. The proximity to the coast and the complex topography create great diversity of rainfall over space and time. The dataset consisted of time series (1967-2013) of monthly rainfall over 100 meteorological stations. Clustering analysis made it possible to divide the stations into six groups (G1, G2, G3, G4, G5 and G6) with similar rainfall spatio-temporal patterns. A linear regression model was applied to a time series and a reference. The reference series was calculated from the average rainfall within a group, using nearby stations with higher correlation (Pearson). Based on t-test ( p River (G5) and the metropolitan area of the city of Rio de Janeiro (G6). The driest months in all regions were June, July and August, while November, December and January were the rainiest months. Sharp transitions occurred when considering monthly accumulated rainfall: from January to February, and from February to March, likely associated with episodes of "veranicos", i.e., periods of 4-15 days of duration with no rainfall.

TEMPORAL AND SPATIAL ANALYSIS OF EXTREME RAINFALL ON THE SLOPE AREA OF MT. MERAPI

Directory of Open Access Journals (Sweden)

Dhian Dharma Prayuda

2015-02-01

Full Text Available Rainfall has temporal and spatial characteristics with certain pattern which are affected by topographic variations and climatology of an area. The intensity of extreme rainfall is one of important characteristics related to the trigger factors for debris flow. This research will discuss the result of analysis on short duration rainfall data in the south and west slope of Mt. Merapi. Measured hourly rainfall data in 14 rainfall stations for the last 27 years were used as analysis input. The rainfall intensity-duration-frequency relationship (IDF was derived using empirical formula of Sherman, Kimijima, Haspers, and Mononobe method. The analysis on the characteristics of extreme rainfall intensity was performed by conducting spatial interpolation using Inverse Distance Weighted (IDW method. Result of analysis shows that IDF of rainfall in the research area fits to Sherman’s formula. Besides, the spatial distribution pattern of maximum rainfall intensity was assessed on the basis of area rainfall. Furthermore, the difference on the result of spatial map for one hour extreme rainfall based on isolated event and non-isolated event method can be evaluated. The result of this preliminary research is expected to be inputs in the establishment of debris flow early warning in Mt. Merapi slope area.

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

Science.gov (United States)

Kashid, S. S.; Ghosh, Subimal; Maity, Rajib

2010-12-01

SummarySimultaneous variations in weather and climate over widely separated regions are commonly known as "hydroclimatic teleconnections". Rainfall and runoff patterns, over continents, are found to be significantly teleconnected, with large-scale circulation patterns, through such hydroclimatic teleconnections. Though such teleconnections exist in nature, it is very difficult to model them, due to their inherent complexity. Statistical techniques and Artificial Intelligence (AI) tools gain popularity in modeling hydroclimatic teleconnection, based on their ability, in capturing the complicated relationship between the predictors (e.g. sea surface temperatures) and predictand (e.g., rainfall). Genetic Programming is such an AI tool, which is capable of capturing nonlinear relationship, between predictor and predictand, due to its flexible functional structure. In the present study, gridded multi-site weekly rainfall is predicted from El Niño Southern Oscillation (ENSO) indices, Equatorial Indian Ocean Oscillation (EQUINOO) indices, Outgoing Longwave Radiation (OLR) and lag rainfall at grid points, over the catchment, using Genetic Programming. The predicted rainfall is further used in a Genetic Programming model to predict streamflows. The model is applied for weekly forecasting of streamflow in Mahanadi River, India, and satisfactory performance is observed.

Long term oscillations in Danish rainfall extremes

DEFF Research Database (Denmark)

Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan

The frequent flooding of European cities within the last decade has motivated a vast number of studies, among others addressing the non-stationary behaviour of hydrological extremes driven by anthropogenic climate change. However, when considering future extremes it also becomes relevant to search...... for and understand natural variations on which the anthropogenic changes are imposed. This study identifies multi-decadal variations in six 137-years-long diurnal rainfall series from Denmark and southern Sweden, focusing on extremes with a reoccurrence level relevant for Danish drainage design. By means of a Peak...

Rainfall Simulations of Typhoon Morakot with Controlled Translation Speed Based on EnKF Data Assimilation

Directory of Open Access Journals (Sweden)

Tzu-Hsiung Yen

2011-01-01

Full Text Available Typhoon Morakot produced record-breaking accumulated rainfall over southern Taiwan in August 2009. The combination of several factors resulted in this extreme weather event: the steep terrain in Taiwan, the prevailing south-westerly flow in the monsoon trough, Typhoon Goni over the northern South China Sea, and the slow translation speed of Morakot itself over Taiwan. In this study, the influence of the translation speed is particularly emphasized. Based on the EnKF data assimilation, an innovative method is applied to perform ensemble simulations with several designated translation speeds of Morakot using the WRF model. Thus the influence of the translation speed on the amount of accumulated rainfall over Taiwan can be quantitatively evaluated. In the control simulation with observed translation speed, the maximum amount and geographic pattern of accumulated rainfall during the landfall period of Morakot are generally consistent with the observations, though the detailed overall distributions of accumulated rainfall is mostly underestimated, resulting in the low bias of the frequency distribution of the accumulated rainfall. In a simulation with nearly-doubled translation speed of Morakot, the maximum accumulated rainfall is decreased by 33% than that in the control simulation, while the rainfall distribution over Taiwan remains similar. In addition, the 28 ensemble members can further provide additional information in terms of their spread and other statistics. The results from ensemble members reveal the usefulness of ensemble simulations for the quantitative precipitation forecast.

Long-term patterns and short-term dynamics of stream solutes and suspended sediment in a rapidly weathering tropical watershed

Science.gov (United States)

Shanley, James B.; McDowell, William H.; Stallard, Robert F.

2011-07-01

The 326 ha Río Icacos watershed in the tropical wet forest of the Luquillo Mountains, northeastern Puerto Rico, is underlain by granodiorite bedrock with weathering rates among the highest in the world. We pooled stream chemistry and total suspended sediment (TSS) data sets from three discrete periods: 1983-1987, 1991-1997, and 2000-2008. During this period three major hurricanes crossed the site: Hugo in 1989, Hortense in 1996, and Georges in 1998. Stream chemistry reflects sea salt inputs (Na, Cl, and SO4), and high weathering rates of the granodiorite (Ca, Mg, Si, and alkalinity). During rainfall, stream composition shifts toward that of precipitation, diluting 90% or more in the largest storms, but maintains a biogeochemical watershed signal marked by elevated K and dissolved organic carbon (DOC) concentration. DOC exhibits an unusual "boomerang" pattern, initially increasing with flow but then decreasing at the highest flows as it becomes depleted and/or vigorous overland flow minimizes contact with watershed surfaces. TSS increased markedly with discharge (power function slope 1.54), reflecting the erosive power of large storms in a landslide-prone landscape. The relations of TSS and most solute concentrations with stream discharge were stable through time, suggesting minimal long-term effects from repeated hurricane disturbance. Nitrate concentration, however, increased about threefold in response to hurricanes then returned to baseline over several years following a pseudo first-order decay pattern. The combined data sets provide insight about important hydrologic pathways, a long-term perspective to assess response to hurricanes, and a framework to evaluate future climate change in tropical ecosystems.

Kin term patterns and language familie

Directory of Open Access Journals (Sweden)

Vladimir Borissov Pericliev

2017-12-01

Full Text Available Kin term patterns and language familie The anthropologist G. P. Murdock has found a strong correlation between the kin term patterns (or feature-values for the relative (feature “sibling” and language families. This important finding for language classification, however, has not been pursued further. In particular, it has not yet been tested whether the kin term patterns domain as a whole, including the patterns for other features (“grandparents”, “uncles”, “aunts”, “nephews and nieces”, etc., is sufficient to demarcate all language families from one another. This paper presents a large-scale computational profiling of all language families in terms of their kin term patterns. The most significant findings are: (i that language families can be quite neatly differentiated on the basis of their kin term patterns, and therefore these patterns may be considered as strong indicators of genetic affiliation, and (ii that the kin term patterns for the features “nephews and nieces (= siblings' children”, “siblings”, and “siblings-in-law” — i.e. all features including the idea of siblings — are the best predictors of genetic affiliation, as they are significantly more frequently used in the profiles than any other feature.    Modele terminologii powinowactwa i pokrewieństwa a rodzina językowa Antropolog G. P. Murdock odkrył silny związek między modelami powinowactwa i pokrewieństwa dla krewnych (rodzeństwa a rodzinami językowymi. To ważne odkrycie w klasyfikacji języków nie było odpowiednio dalej wykorzystywane. W szczególności nie sprawdzono jeszcze, czy domena modeli powinowactwa i pokrewieństwa jako całości, w tym modele dla innych cech („dziadkowie”, „wujkowie”, „ciotki”, „siostrzeńcy i siostrzenice” itp. są wystarczająco ukształtowane we wszystkich rodzinach językowych. W niniejszym artykule przedstawiono profilowanie komputerowe na dużą skalę wszystkich rodzin j

Entropy of stable seasonal rainfall distribution in Kelantan

Science.gov (United States)

Azman, Muhammad Az-zuhri; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Radi, Noor Fadhilah Ahmad

2017-05-01

Investigating the rainfall variability is vital for any planning and management in many fields related to water resources. Climate change can gives an impact of water availability and may aggravate water scarcity in the future. Two statistics measurements which have been used by many researchers to measure the rainfall variability are variance and coefficient of variation. However, these two measurements are insufficient since rainfall distribution in Malaysia especially in the East Coast of Peninsular Malaysia is not symmetric instead it is positively skewed. In this study, the entropy concept is used as a tool to measure the seasonal rainfall variability in Kelantan and ten rainfall stations were selected. In previous studies, entropy of stable rainfall (ESR) and apportionment entropy (AE) were used to describe the rainfall amount variability during years for Australian rainfall data. In this study, the entropy of stable seasonal rainfall (ESSR) is suggested to model rainfall amount variability during northeast monsoon (NEM) and southwest monsoon (SWM) seasons in Kelantan. The ESSR is defined to measure the long-term average seasonal rainfall amount variability within a given year (1960-2012). On the other hand, the AE measures the rainfall amounts variability across the months. The results of ESSR and AE values show that stations in east coastline are more variable as compared to other stations inland for Kelantan rainfall. The contour maps of ESSR for Kelantan rainfall stations are also presented.

Long-term trends of typhoon-induced rainfall over Taiwan: in situ evidence of poleward shift of typhoons in western North Pacific in recent decades

Science.gov (United States)

Liang, Ting-Yu; Oey, Leo; Huang, Shiming; Chou, Simon

2017-04-01

Tracks of tropical cyclones or typhoons in the western North Pacific have recently been shown to shift northward in the past several decades; the poleward shift has been attributed to the expansion of the tropics due to climate warming. Here we use 64-year, hourly rainfall observations around Taiwan, and take advantage of the unique terrain and geographic location of the island with respect to typhoon tracks, to show that since 1950 the typhoon-related rainfalls have been rising on the western side of the island, but decreasing on the eastern side. We show that these extraordinary rainfall patterns, despite the smallness of Taiwan, are indicative of a northward shift of typhoons related to the changes in the wind fields and surface warming over the Indian and Pacific tropical/subtropical regions.

Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is ...

Indian Academy of Sciences (India)

Jitendra Singh

J. Earth Syst. ... 3Interdisciplinary Program in Climate Studies, Indian Institute of Technology Bombay, ... Correlogram cloud indicated no pattern of significant correlation when we considered ... in Mumbai rainfall data signifies the futility of independently applying advanced ... of the rainfall by existing weather-forecast models.

Unusual rainfall shift during monsoon period of 2010 in Pakistan ...

African Journals Online (AJOL)

Floods due to “blocking event” in the jet stream during 2010 caused intense rainfall and flash floods in northern Pakistan which resulted to riverine flooding in southern Pakistan. In the beginning of July 2010, changes in summer monsoon rainfall patterns caused the most severe flooding in Pakistan history. Process control ...

Seasonal prediction of East Asian summer rainfall using a multi-model ensemble system

Science.gov (United States)

Ahn, Joong-Bae; Lee, Doo-Young; Yoo, Jin‑Ho

2015-04-01

Using the retrospective forecasts of seven state-of-the-art coupled models and their multi-model ensemble (MME) for boreal summers, the prediction skills of climate models in the western tropical Pacific (WTP) and East Asian region are assessed. The prediction of summer rainfall anomalies in East Asia is difficult, while the WTP has a strong correlation between model prediction and observation. We focus on developing a new approach to further enhance the seasonal prediction skill for summer rainfall in East Asia and investigate the influence of convective activity in the WTP on East Asian summer rainfall. By analyzing the characteristics of the WTP convection, two distinct patterns associated with El Niño-Southern Oscillation developing and decaying modes are identified. Based on the multiple linear regression method, the East Asia Rainfall Index (EARI) is developed by using the interannual variability of the normalized Maritime continent-WTP Indices (MPIs), as potentially useful predictors for rainfall prediction over East Asia, obtained from the above two main patterns. For East Asian summer rainfall, the EARI has superior performance to the East Asia summer monsoon index or each MPI. Therefore, the regressed rainfall from EARI also shows a strong relationship with the observed East Asian summer rainfall pattern. In addition, we evaluate the prediction skill of the East Asia reconstructed rainfall obtained by hybrid dynamical-statistical approach using the cross-validated EARI from the individual models and their MME. The results show that the rainfalls reconstructed from simulations capture the general features of observed precipitation in East Asia quite well. This study convincingly demonstrates that rainfall prediction skill is considerably improved by using a hybrid dynamical-statistical approach compared to the dynamical forecast alone. Acknowledgements This work was carried out with the support of Rural Development Administration Cooperative Research

Trends in total rainfall, heavy rain events, and number of dry days in San Juan, Puerto Rico, 1955-2009

Directory of Open Access Journals (Sweden)

Pablo A. Méndez-Lázaro

2014-06-01

Full Text Available Climate variability is a threat to water resources on a global scale and in tropical regions in particular. Rainfall events and patterns are associated worldwide with natural disasters like mudslides and landslides, meteorological phenomena like hurricanes, risks/hazards including severe storms and flooding, and health effects like vector-borne and waterborne diseases. Therefore, in the context of global change, research on rainfall patterns and their variations presents a challenge to the scientific community. The main objective of this research was to analyze recent trends in precipitation in the San Juan metropolitan area in Puerto Rico and their relationship with regional and global climate variations. The statistical trend analysis of precipitation was performed with the nonparametric Mann-Kendall test. All stations showed positive trends of increasing annual rainfall between 1955 and 2009. The winter months of January and February had an increase in monthly rainfall, although winter is normally a dry season on the island. Regarding dry days, we found an annual decreasing trend, also specifically in winter. In terms of numbers of severe rainfall events described as more than 78 mm in 24 hours, 63 episodes have occurred in the San Juan area in the last decade, specifically in the 2000-2009 time frame, with an average of 6 severe events per year. The majority of the episodes occurred in summer, more frequently in August and September. These results can be seen as a clear example of the complexity of spatial and temporal of rainfall distribution over a tropical city.

Erosividade, coeficiente de chuva, padrões e período de retorno das chuvas de Quaraí, RS Erosivity, rainfall coefficient and patterns and return period in Quarai, RS, Brazi

Directory of Open Access Journals (Sweden)

Marcos Gabriel Peñalva Bazzano

2007-10-01

intermediário e 18 % do atrasado. Das chuvas erosivas, 57 % da erosividade correspondeu a chuvas do padrão avançado, 25 % a chuvas do padrão intermediário e 18 % a chuvas do padrão atrasado.The planning of agricultural and civil engineering activities must be based on knowledge of rainfall erosion potential. For Quarai, RS, Brazil, the rainfall erosivity and its relationship with precipitation and rainfall coefficient, rainfall patterns and rainfall return period were determined. Daily rainfall data from the 1966-2003 period were used. For each erosive rainfall the segments of the rainfall chart with the same intensity were separated and the data recorded in a worksheet. The mean precipitation and rainfall patterns were estimated, as well as the monthly and annual erosivity by the EI30 index (International System of Units, using the software Chuveros. The rainfall coefficient was calculated. Pearson correlations and linear regressions between the erosivity index EI30 and the mean annual precipitation and rainfall coefficient (Rc were performed. The rainfall maximum intensity was calculated by the method of extreme distribution type I for different rainfall durations (1/6, 1/3, 1/2, 1, 2, 4, 8, 12, 24 and 48 h and rainfall return periods (2, 5, 10, 20, 50 and 100 years. Equations were adjusted that relate the maximum intensity and rainfall duration to all return periods, by the method of simple linear regression, and the rainfall characteristics related in a graph. The mean annual values of EI30 (R factor of USLE determined for Quarai, RS, Brazil, was 9,292 MJ mm ha-1 h-1 year-1. The following equations were obtained: EI30 = -754.37 + 13.50 p (r² = 0.85 and EI30 = -47.35 + 82.72 Rc (r² = 0.84. In relation to the total precipitation studied, 44 % of the number of rainfalls and 90 % of the volume were erosive. Of the total rainfalls evaluated, 44 % of the number and 90 % of the volume were erosive. Of the total erosive rainfall events, 51 % had an advanced, 25 % had an

Spatial and temporal variation in rainfall erosivity in a Himalayan watershed

NARCIS (Netherlands)

Ma, X.; Noordwijk, van M.; Xu, J.; Lu, X.

2014-01-01

Global climate change can modify rainfall patterns, leading to more extremes with associated erosion events. Rainfall erosivity, or the R-factor based on the Revised Universal Soil Loss Equation (RUSLE), indicates the potential water erosion risk and it plays an important role in water and soil

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

KAUST Repository

Konda, Gopinadh; Chowdary, Jasti S.; Srinivas, G; Gnanaseelan, C; Parekh, Anant; Attada, Raju; Rama Krishna, S S V S

2018-01-01

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

Science.gov (United States)

Konda, Gopinadh; Chowdary, J. S.; Srinivas, G.; Gnanaseelan, C.; Parekh, Anant; Attada, Raju; Rama Krishna, S. S. V. S.

2018-06-01

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

KAUST Repository

Konda, Gopinadh

2018-05-22

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Automatic Extraction of High-Resolution Rainfall Series from Rainfall Strip Charts

Science.gov (United States)

Saa-Requejo, Antonio; Valencia, Jose Luis; Garrido, Alberto; Tarquis, Ana M.

2015-04-01

those have been scanned in two parts, detect and cut the borders of bands not used (demanded by the software). Also some variations in which colour system is tried basing in HUE or RGB colour have been included. Thanks to apply this digitization rainfall strip charts 209 station-years of three locations in the centre of Spain have been transformed to long-term rainfall time series with 5-min resolution. References van Piggelen, H.E., T. Brandsma, H. Manders, and J. F. Lichtenauer, 2011: Automatic Curve Extraction for Digitizing Rainfall Strip Charts. J. Atmos. Oceanic Technol., 28, 891-906. Acknowledgements Financial support for this research by DURERO Project (Env.C1.3913442) is greatly appreciated.

Temporal characteristics of rainfall events under three climate types in Slovenia

Science.gov (United States)

Dolšak, Domen; Bezak, Nejc; Šraj, Mojca

2016-10-01

Temporal rainfall distribution can often have significant influence on other hydrological processes such as runoff generation or rainfall interception. High-frequency rainfall data from 30 stations in Slovenia were analysed in order to improve the knowledge about the temporal rainfall distribution within a rainfall event. Using the pre-processed rainfall data Huff curves were determined and the binary shape code (BSC) methodology was applied. Although Slovenia covers only about 20,000 km2, results indicate large temporal and spatial variability in the precipitation pattern of the analysed stations, which is in agreement with the different Slovenian climate types: sub-Mediterranean, temperate continental, and mountain climate. Statistically significant correlation was identified between the most frequent BSC types, mean annual precipitation, and rainfall erosivity for individual rainfall stations. Moreover, different temporal rainfall distributions were observed for rainfall events with shorter duration (less than 12 h) than those with longer duration (more than 24 h). Using the analysis of the Huff curves it was shown that the variability in the Huff curves decreases with increasing rainfall duration. Thus, it seems that for shorter duration convective storms a more diverse temporal rainfall distribution can be expected than for the longer duration frontal precipitation where temporal rainfall distribution shows less variability.

Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010.

Science.gov (United States)

Mukabutera, Assumpta; Thomson, Dana; Murray, Megan; Basinga, Paulin; Nyirazinyoye, Laetitia; Atwood, Sidney; Savage, Kevin P; Ngirimana, Aimable; Hedt-Gauthier, Bethany L

2016-08-05

Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age. Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff) but had no impact among children in household with improved toilets. Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

Could the long term cover change of three Mediterranean shrubs be explained by their photosynthetic responses to drought in a rainfall exclusion experiment ?

Science.gov (United States)

Liberati, Dario; De Dato, Giovanbattista; Guidolotti, Gabriele; De Angelis, Paolo

2013-04-01

connected to the different ability of the two species in keeping high photosynthesis rates during the Autumn period, that could imply a limitation in the growth and therefore in the competitive ability of H. italicum. The lower ability of D. pentaphyllum in gain cover with respect to C. monspeliensis, despite the similar photosynthetic seasonal trend, could be related to the different resource allocation pattern connected to the deep root system, that only characterize this species. The strong effect of the rainfall exclusion on the cover trend of C. monspeliensis , compared to no effect observed in H. italicum, could be explained by the timing of the drought treatment, affecting C. monspeliensis during one of the two annual photosynthetic peaks, H. italicum during a period of low photosynthetic activity. It seems therefore possible to find some connection between the population dynamics of the studied species and their ability in recovering after the drought stress; furthermore, the lengthening of the dry season, as simulated by the rainfall exclusion system, in the long term seems to impact more on those species, like C. monspeliensis, relying on Autumn period to perform a significant part of their annual assimilation.

El Niño, Rainfall, and the Shifting Geography of Cholera in Africa

Science.gov (United States)

Moore, S.; Azman, A. S.; Zaitchik, B. F.; McKay, H.; Lessler, J.

2017-12-01

The El Niño Southern Oscillation (ENSO) and other climate patterns can have profound impacts on the occurrence of infectious diseases. Because of the key role of water supplies in cholera transmission, a relationship between El Niño events and cholera incidence is highly plausible, and previous research has shown a link between El Niño patterns and cholera in Bangladesh. However, there is little systematic evidence for this link in Africa where many cholera cases and deaths are reported. To understand how ENSO affects the geographic distribution of cholera incidence in Africa, we used a hierarchical Bayesian approach to integrate over 17,000 annual observations of cholera incidence from 2000-2014 in over 3,000 unique locations of varying spatial extent, ranging from entire countries to neighborhoods. The resulting maps reflect modeled cholera incidence at a fine spatial resolution using reported counts of cholera cases, key explanatory variables, and a spatially-dependent covariance term. We then examined the potential mechanistic association between ENSO-related changes in cholera incidence and several environmental variables including rainfall. El Niño profoundly changed the annual geographic distribution of cholera in Africa from 2000-2014, shifting the burden to continental East Africa, where almost 50,000 additional cases occur during El Niño years. Cholera incidence during El Niño years was higher in regions of East Africa with increased rainfall, but incidence was also higher in some areas with decreased rainfall suggesting a complex relationship between rainfall and cholera incidence. Here we show clear evidence for a shift in the distribution of cholera incidence throughout Africa in El Niño and non-El Niño years, likely mediated by El Niño's impact on local climatic factors. Knowledge of this relationship between cholera and climate patterns coupled with El Niño forecasting could be used to notify countries in Africa when they are likely to see

Modeling rainfall-runoff relationship using multivariate GARCH model

Science.gov (United States)

Modarres, R.; Ouarda, T. B. M. J.

2013-08-01

The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.

Changing character of rainfall in eastern China, 1951–2007

Science.gov (United States)

Day, Jesse A.; Fung, Inez; Liu, Weihan

2018-03-01

The topography and continental configuration of East Asia favor the year-round existence of storm tracks that extend thousands of kilometers from China into the northwestern Pacific Ocean, producing zonally elongated patterns of rainfall that we call “frontal rain events.” In spring and early summer (known as “Meiyu Season”), frontal rainfall intensifies and shifts northward during a series of stages collectively known as the East Asian summer monsoon. Using a technique called the Frontal Rain Event Detection Algorithm, we create a daily catalog of all frontal rain events in east China during 1951–2007, quantify their attributes, and classify all rainfall on each day as either frontal, resulting from large-scale convergence, or nonfrontal, produced by local buoyancy, topography, or typhoons. Our climatology shows that the East Asian summer monsoon consists of a series of coupled changes in frontal rain event frequency, latitude, and daily accumulation. Furthermore, decadal changes in the amount and distribution of rainfall in east China are overwhelmingly due to changes in frontal rainfall. We attribute the “South Flood–North Drought” pattern observed beginning in the 1980s to changes in the frequency of frontal rain events, while the years 1994–2007 witnessed an uptick in event daily accumulation relative to the rest of the study years. This particular signature may reflect the relative impacts of global warming, aerosol loading, and natural variability on regional rainfall, potentially via shifting the East Asian jet stream.

TRMM Applications for Rainfall-Induced Landslide Early Warning

Science.gov (United States)

Dok, A.; Fukuoka, H.; Hong, Y.

2012-04-01

(snake line) were independently plotted to investigate the impact of short-term rainfall intensity and accumulated effective rainfall volume respectively for obtaining some probabilistic threshold. Japanese SWI was also tested to distribute threshold regarding to highly nonlinear rainfall patterns in predicting the landslide occurrence through the plot of total water of 3 serial tank models and daily precipitation. As a result, the snake line plots using TMPA work well for landslide warning in the selected cities; while SWI plots shows unusual peak value on the day of the debris flow occurrence. Graph of daily precipitation vs SWI implies possible zone of critical line, and second peak appearance 1 day before, indicating possibility of early warning.

ICUD-0471 Weather radar rainfall for design of urban storm water systems

DEFF Research Database (Denmark)

Thorndahl, Søren Liedtke; Wright, D. B.; Nielsen, Jesper Ellerbæk

2017-01-01

Long continuous series of high-resolution radar rainfall series provides valuable information on spatial and temporal variability of rainfall, which can be used in design of urban drainage systems. In design of especially large drainage systems with complex flow patterns (and potentially surface ...

Rainfall Erosivity Database on the European Scale (REDES): A product of a high temporal resolution rainfall data collection in Europe

Science.gov (United States)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

2016-04-01

The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511, 801-815). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the

Raingauge-Based Rainfall Nowcasting with Artificial Neural Network

Science.gov (United States)

Liong, Shie-Yui; He, Shan

2010-05-01

Rainfall forecasting and nowcasting are of great importance, for instance, in real-time flood early warning systems. Long term rainfall forecasting demands global climate, land, and sea data, thus, large computing power and storage capacity are required. Rainfall nowcasting's computing requirement, on the other hand, is much less. Rainfall nowcasting may use data captured by radar and/or weather stations. This paper presents the application of Artificial Neural Network (ANN) on rainfall nowcasting using data observed at weather and/or rainfall stations. The study focuses on the North-East monsoon period (December, January and February) in Singapore. Rainfall and weather data from ten stations, between 2000 and 2006, were selected and divided into three groups for training, over-fitting test and validation of the ANN. Several neural network architectures were tried in the study. Two architectures, Backpropagation ANN and Group Method of Data Handling ANN, yielded better rainfall nowcasting, up to two hours, than the other architectures. The obtained rainfall nowcasts were then used by a catchment model to forecast catchment runoff. The results of runoff forecast are encouraging and promising.With ANN's high computational speed, the proposed approach may be deliverable for creating the real-time flood early warning system.

Aerosol and rainfall variability over the Indian monsoon region: distributions, trends and coupling

Directory of Open Access Journals (Sweden)

R. Gautam

2009-09-01

Full Text Available Aerosol solar absorption over the Indian monsoon region has a potential role of modulating the monsoon circulation and rainfall distribution as suggested by recent studies based on model simulations. Prior to the onset of the monsoon, northern India is influenced by significant dust transport that constitutes the bulk of the regional aerosol loading over the Gangetic-Himalayan region. In this paper, a multi-sensor characterization of the increasing pre-monsoon aerosol loading over northern India, in terms of their spatial, temporal and vertical distribution is presented. Aerosol transport from the northwestern arid regions into the Indo-Gangetic Plains and over the foothills of the Himalayas is found to be vertically extended to elevated altitudes (up to 5 km as observed from the space-borne lidar measurements (CALIPSO. In relation with the enhanced pre-monsoon aerosol loading and the associated solar absorption effects on tropospheric temperature anomalies, this paper investigates the monsoon rainfall variability over India in recent past decades from an observational viewpoint. It is found that the early summer monsoon rainfall over India is on the rise since 1950s, as indicated by historical rainfall data, with over 20% increase for the period 1950–2004. This large sustained increase in the early summer rainfall is led by the observed strengthening of the pre-monsoon tropospheric land-sea thermal gradient over the Indian monsoon region as indicated by microwave satellite measurements (MSU of tropospheric temperatures from 1979–2007. Combined analysis of changes in tropospheric temperatures and summer monsoon rainfall in the past three decades, suggest a future possibility of an emerging rainfall pattern of a wetter monsoon over South Asia in early summer followed by a drier period.

Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

Science.gov (United States)

Yunus, R. M.; Hasan, M. M.; Zubairi, Y. Z.

2017-09-01

In this study, the Tweedie distribution was used to fit the monthly rainfall data from 24 monitoring stations of Peninsula Malaysia for the period from January, 2008 to April, 2015. The aim of the study is to determine whether the distributions within the Tweedie family fit well the monthly Malaysian rainfall data. Within the Tweedie family, the gamma distribution is generally used for fitting the rainfall totals, however the Poisson-gamma distribution is more useful to describe two important features of rainfall pattern, which are the occurrences (dry months) and the amount (wet months). First, the appropriate distribution of the monthly rainfall was identified within the Tweedie family for each station. Then, the Tweedie Generalised Linear Model (GLM) with no explanatory variable was used to model the monthly rainfall data. Graphical representation was used to assess model appropriateness. The QQ plots of quantile residuals show that the Tweedie models fit the monthly rainfall data better for majority of the stations in the west coast and mid land than those in the east coast of Peninsula. This significant finding suggests that the best fitted distribution depends on the geographical location of the monitoring station. In this paper, a simple model is developed for generating synthetic rainfall data for use in various areas, including agriculture and irrigation. We have showed that the data that were simulated using the Tweedie distribution have fairly similar frequency histogram to that of the actual data. Both the mean number of rainfall events and mean amount of rain for a month were estimated simultaneously for the case that the Poisson gamma distribution fits the data reasonably well. Thus, this work complements previous studies that fit the rainfall amount and the occurrence of rainfall events separately, each to a different distribution.

Random Modeling of Daily Rainfall and Runoff Using a Seasonal Model and Wavelet Denoising

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Chien-ming Chou

2014-01-01

Full Text Available Instead of Fourier smoothing, this study applied wavelet denoising to acquire the smooth seasonal mean and corresponding perturbation term from daily rainfall and runoff data in traditional seasonal models, which use seasonal means for hydrological time series forecasting. The denoised rainfall and runoff time series data were regarded as the smooth seasonal mean. The probability distribution of the percentage coefficients can be obtained from calibrated daily rainfall and runoff data. For validated daily rainfall and runoff data, percentage coefficients were randomly generated according to the probability distribution and the law of linear proportion. Multiplying the generated percentage coefficient by the smooth seasonal mean resulted in the corresponding perturbation term. Random modeling of daily rainfall and runoff can be obtained by adding the perturbation term to the smooth seasonal mean. To verify the accuracy of the proposed method, daily rainfall and runoff data for the Wu-Tu watershed were analyzed. The analytical results demonstrate that wavelet denoising enhances the precision of daily rainfall and runoff modeling of the seasonal model. In addition, the wavelet denoising technique proposed in this study can obtain the smooth seasonal mean of rainfall and runoff processes and is suitable for modeling actual daily rainfall and runoff processes.

Deterministic Approach for Estimating Critical Rainfall Threshold of Rainfall-induced Landslide in Taiwan

Science.gov (United States)

Chung, Ming-Chien; Tan, Chih-Hao; Chen, Mien-Min; Su, Tai-Wei

2013-04-01

Taiwan is an active mountain belt created by the oblique collision between the northern Luzon arc and the Asian continental margin. The inherent complexities of geological nature create numerous discontinuities through rock masses and relatively steep hillside on the island. In recent years, the increase in the frequency and intensity of extreme natural events due to global warming or climate change brought significant landslides. The causes of landslides in these slopes are attributed to a number of factors. As is well known, rainfall is one of the most significant triggering factors for landslide occurrence. In general, the rainfall infiltration results in changing the suction and the moisture of soil, raising the unit weight of soil, and reducing the shear strength of soil in the colluvium of landslide. The stability of landslide is closely related to the groundwater pressure in response to rainfall infiltration, the geological and topographical conditions, and the physical and mechanical parameters. To assess the potential susceptibility to landslide, an effective modeling of rainfall-induced landslide is essential. In this paper, a deterministic approach is adopted to estimate the critical rainfall threshold of the rainfall-induced landslide. The critical rainfall threshold is defined as the accumulated rainfall while the safety factor of the slope is equal to 1.0. First, the process of deterministic approach establishes the hydrogeological conceptual model of the slope based on a series of in-situ investigations, including geological drilling, surface geological investigation, geophysical investigation, and borehole explorations. The material strength and hydraulic properties of the model were given by the field and laboratory tests. Second, the hydraulic and mechanical parameters of the model are calibrated with the long-term monitoring data. Furthermore, a two-dimensional numerical program, GeoStudio, was employed to perform the modelling practice. Finally

Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

Science.gov (United States)

Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

2017-04-01

Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

Distributional changes in rainfall and river flow in Sarawak, Malaysia

Science.gov (United States)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

2017-11-01

Climate change may not change the rainfall mean, but the variability and extremes. Therefore, it is required to explore the possible distributional changes of rainfall characteristics over time. The objective of present study is to assess the distributional changes in annual and northeast monsoon rainfall (November-January) and river flow in Sarawak where small changes in rainfall or river flow variability/distribution may have severe implications on ecology and agriculture. A quantile regression-based approach was used to assess the changes of scale and location of empirical probability density function over the period 1980-2014 at 31 observational stations. The results indicate that diverse variation patterns exist at all stations for annual rainfall but mainly increasing quantile trend at the lowers, and higher quantiles for the month of January and December. The significant increase in annual rainfall is found mostly in the north and central-coastal region and monsoon month rainfalls in the interior and north of Sarawak. Trends in river flow data show that changes in rainfall distribution have affected higher quantiles of river flow in monsoon months at some of the basins and therefore more flooding. The study reveals that quantile trend can provide more information of rainfall change which may be useful for climate change mitigation and adaptation planning.

Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010

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Assumpta Mukabutera

2016-08-01

Full Text Available Abstract Background Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. Methods We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age. Results Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff but had no impact among children in household with improved toilets. Conclusion Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

Statistical Analysis of 30 Years Rainfall Data: A Case Study

Science.gov (United States)

Arvind, G.; Ashok Kumar, P.; Girish Karthi, S.; Suribabu, C. R.

2017-07-01

Rainfall is a prime input for various engineering design such as hydraulic structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. A rain gauge station located closely in Trichy district is selected for statistical analysis where agriculture is the prime occupation. The daily rainfall data for a period of 30 years is used to understand normal rainfall, deficit rainfall, Excess rainfall and Seasonal rainfall of the selected circle headquarters. Further various plotting position formulae available is used to evaluate return period of monthly, seasonally and annual rainfall. This analysis will provide useful information for water resources planner, farmers and urban engineers to assess the availability of water and create the storage accordingly. The mean, standard deviation and coefficient of variation of monthly and annual rainfall was calculated to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The scientific results and the analysis paved the way to determine the proper onset and withdrawal of monsoon results which were used for land preparation and sowing.

Rainfall Downscaling Conditional on Upper-air Variables: Assessing Rainfall Statistics in a Changing Climate

Science.gov (United States)

Langousis, Andreas; Deidda, Roberto; Marrocu, Marino; Kaleris, Vassilios

2014-05-01

Due to its intermittent and highly variable character, and the modeling parameterizations used, precipitation is one of the least well reproduced hydrologic variables by both Global Climate Models (GCMs) and Regional Climate Models (RCMs). This is especially the case at a regional level (where hydrologic risks are assessed) and at small temporal scales (e.g. daily) used to run hydrologic models. In an effort to remedy those shortcomings and assess the effect of climate change on rainfall statistics at hydrologically relevant scales, Langousis and Kaleris (2013) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables. The developed downscaling scheme was tested using atmospheric data from the ERA-Interim archive (http://www.ecmwf.int/research/era/do/get/index), and daily rainfall measurements from western Greece, and was proved capable of reproducing several statistical properties of actual rainfall records, at both annual and seasonal levels. This was done solely by conditioning rainfall simulation on a vector of atmospheric predictors, properly selected to reflect the relative influence of upper-air variables on ground-level rainfall statistics. In this study, we apply the developed framework for conditional rainfall simulation using atmospheric data from different GCM/RCM combinations. This is done using atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com), and daily rainfall measurements for an intermediate-sized catchment in Italy; i.e. the Flumendosa catchment. Since GCM/RCM products are suited to reproduce the local climatology in a statistical sense (i.e. in terms of relative frequencies), rather than ensuring a one-to-one temporal correspondence between observed and simulated fields (i.e. as is the case for ERA-interim reanalysis data), we proceed in three steps: a) we use statistical tools to establish a linkage between ERA-Interim upper-air atmospheric forecasts and

Detecting Climate Variability in Tropical Rainfall

Science.gov (United States)

Berg, W.

2004-05-01

El Niño is substantially smaller due to decreased rainfall in the west Pacific partially canceling increases in the central and east Pacific. These differences are not limited to the long-term merged rainfall products using infrared data, but are also exist in state-of-the-art rainfall retrievals from the active and passive microwave sensors on board the Tropical Rainfall Measuring Mission (TRMM). For example, large differences exist in the response of tropical mean rainfall retrieved from the TRMM microwave imager (TMI) 2A12 algorithm and the precipitation radar (PR) 2A25 algorithm to the 1997/98 El Niño. To assist scientists attempting to wade through the vast array of climate rainfall products currently available, and to help them determine whether systematic biases in these rainfall products impact the conclusions of a given study, we have developed a Climate Rainfall Data Center (CRDC). The CRDC web site (rain.atmos.colostate.edu/CRDC) provides climate researchers information on the various rainfall datasets available as well as access to experts in the field of satellite rainfall retrievals to assist them in the appropriate selection and use of climate rainfall products.

Analysis of Rainfall Intensity in Madiun Watershed, East Java

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Muttaqin Muttaqin

2004-01-01

Full Text Available The aim of the reasearch in the area of Madiun River Basin is to make and to analyze the Intensity Duration Curve (IDC i.e. the curve describing graphically the relation between rainfall intensity and rainfall duration in a certain frequent period. Formulation used in the research was Talbot Formula and Ishiguro’s. In the drafting of Intensity Duration Curve it was used specific coefficient i.e by using the rainfall data of fifteen and sixty duration for both applied formulations. The IDC recorded has not mean difference because in both formulation was used coefficient of the same value. The pattern of the rainfall intensity occured directed toward Nort East. It was happened because of the moving clouds directed toward that course. Depression occured at the backward of Mount Lawu, exactly toward East.

Monthly Rainfall Erosivity: Conversion Factors for Different Time Resolutions and Regional Assessments

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Panos Panagos

2016-03-01

Full Text Available As a follow up and an advancement of the recently published Rainfall Erosivity Database at European Scale (REDES and the respective mean annual R-factor map, the monthly aspect of rainfall erosivity has been added to REDES. Rainfall erosivity is crucial to be considered at a monthly resolution, for the optimization of land management (seasonal variation of vegetation cover and agricultural support practices as well as natural hazard protection (landslides and flood prediction. We expanded REDES by 140 rainfall stations, thus covering areas where monthly R-factor values were missing (Slovakia, Poland or former data density was not satisfactory (Austria, France, and Spain. The different time resolutions (from 5 to 60 min of high temporal data require a conversion of monthly R-factor based on a pool of stations with available data at all time resolutions. Because the conversion factors show smaller monthly variability in winter (January: 1.54 than in summer (August: 2.13, applying conversion factors on a monthly basis is suggested. The estimated monthly conversion factors allow transferring the R-factor to the desired time resolution at a European scale. The June to September period contributes to 53% of the annual rainfall erosivity in Europe, with different spatial and temporal patterns depending on the region. The study also investigated the heterogeneous seasonal patterns in different regions of Europe: on average, the Northern and Central European countries exhibit the largest R-factor values in summer, while the Southern European countries do so from October to January. In almost all countries (excluding Ireland, United Kingdom and North France, the seasonal variability of rainfall erosivity is high. Very few areas (mainly located in Spain and France show the largest from February to April. The average monthly erosivity density is very large in August (1.67 and July (1.63, while very small in January and February (0.37. This study addresses

Rainfall Distributions in Sri Lanka in Time and Space: An Analysis Based on Daily Rainfall Data

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T. P. Burt

2014-09-01

Full Text Available Daily rainfall totals are analyzed for the main agro-climatic zones of Sri Lanka for the period 1976–2006. The emphasis is on daily rainfall rather than on longer-period totals, in particular the number of daily falls exceeding given threshold totals. For one station (Mapalana, where a complete daily series is available from 1950, a longer-term perspective on changes over half a century is provided. The focus here is particularly on rainfall in March and April, given the sensitivity of agricultural decisions to early southwest monsoon rainfall at the beginning of the Yala cultivation season but other seasons are also considered, in particular the northeast monsoon. Rainfall across Sri Lanka over three decades is investigated in relation to the main atmospheric drivers known to affect climate in the region: sea surface temperatures in the Pacific and Indian Oceans, of which the former are shown to be more important. The strong influence of El Niño and La Niña phases on various aspects of the daily rainfall distribution in Sri Lanka is confirmed: positive correlations with Pacific sea-surface temperatures during the north east monsoon and negative correlations at other times. It is emphasized in the discussion that Sri Lanka must be placed in its regional context and it is important to draw on regional-scale research across the Indian subcontinent and the Bay of Bengal.

Future changes in rainfall associated with ENSO, IOD and changes in the mean state over Eastern Africa

Science.gov (United States)

Endris, Hussen Seid; Lennard, Christopher; Hewitson, Bruce; Dosio, Alessandro; Nikulin, Grigory; Artan, Guleid A.

2018-05-01

This study examines the projected changes in the characteristics of the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) in terms of mean state, intensity and frequency, and associated rainfall anomalies over eastern Africa. Two regional climate models driven by the same four global climate models (GCMs) and the corresponding GCM simulations are used to investigate projected changes in teleconnection patterns and East African rainfall. The period 1976-2005 is taken as the reference for present climate and the far-future climate (2070-2099) under Representative Concentration Pathway 8.5 (RCP8.5) is analyzed for projected change. Analyses of projections based on GCMs indicate an El Niño-like (positive IOD-like) warming pattern over the tropical Pacific (Indian) Ocean. However, large uncertainties remain in the projected future changes in ENSO/IOD frequency and intensity with some GCMs show increase of ENSO/IOD frequency and intensity, and others a decrease or no/small change. Projected changes in mean rainfall over eastern Africa based on the GCM and RCM data indicate a decrease in rainfall over most parts of the region during JJAS and MAM seasons, and an increase in rainfall over equatorial and southern part of the region during OND, with the greatest changes in equatorial region. During ENSO and IOD years, important changes in the strength of the teleconnections are found. During JJAS, when ENSO is an important driver of rainfall variability over the region, both GCM and RCM projections show an enhanced La Niña-related rainfall anomaly compared to the present period. Although the long rains (MAM) have little association with ENSO in the reference period, both GCMs and RCMs project stronger ENSO teleconnections in the future. On the other hand, during the short rains (OND), a dipole future change in rainfall teleconnection associated with ENSO and IOD is found, with a stronger ENSO/IOD related rainfall anomaly over the eastern part of the domain

Extreme flood event analysis in Indonesia based on rainfall intensity and recharge capacity

Science.gov (United States)

Narulita, Ida; Ningrum, Widya

2018-02-01

Indonesia is very vulnerable to flood disaster because it has high rainfall events throughout the year. Flood is categorized as the most important hazard disaster because it is causing social, economic and human losses. The purpose of this study is to analyze extreme flood event based on satellite rainfall dataset to understand the rainfall characteristic (rainfall intensity, rainfall pattern, etc.) that happened before flood disaster in the area for monsoonal, equatorial and local rainfall types. Recharge capacity will be analyzed using land cover and soil distribution. The data used in this study are CHIRPS rainfall satellite data on 0.05 ° spatial resolution and daily temporal resolution, and GSMap satellite rainfall dataset operated by JAXA on 1-hour temporal resolution and 0.1 ° spatial resolution, land use and soil distribution map for recharge capacity analysis. The rainfall characteristic before flooding, and recharge capacity analysis are expected to become the important information for flood mitigation in Indonesia.

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

Science.gov (United States)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Detecting changes in rainfall pattern and seasonality index vis-`a-vis ...

Indian Academy of Sciences (India)

index vis-`a-vis increasing water scarcity in Maharashtra ... in the district scale are identified by trend analysis of rainfall time series. ... for better disaster management and water resource ..... productivity and irrigation water supply in the con-.

Spatial Scaling of Global Rainfall and Flood Extremes

Science.gov (United States)

Devineni, Naresh; Lall, Upmanu; Xi, Chen; Ward, Philip

2014-05-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration and spatial extent of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (up to 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances and floods. We present the first ever results on a global analysis of the scaling characteristics of extreme rainfall and flood event duration, volumes and contiguous flooded areas as a result of large scale organization of long duration rainfall events. Results are organized by latitude and with reference to the phases of ENSO, and reveal surprising invariance across latitude. Speculation as to the potential relation to the dynamical factors is presented

Observations of cloud and rainfall enhancement over irrigated agriculture in an arid environment

Science.gov (United States)

Garcia-Carreras, Luis; Marsham, John H.; Spracklen, Dominick V.

2017-04-01

The impact of irrigated agriculture on clouds and rainfall remains uncertain, particularly in less studied arid regions. Irrigated crops account for 20% of global cropland area, and non-renewable groundwater accounts for 20% of global irrigation water demand. Quantifying the feedbacks between agriculture and the atmosphere are therefore not only necessary to better understand the climate impacts of land-use change, but are also crucial for predicting long-term water use in water-scarce regions. Here we use high spatial-resolution satellite data to show the impact of irrigated crops in the arid environment of northern Saudi Arabia on cloud cover and rainfall patterns. Land surface temperatures over the crops are 5-10 K lower than their surroundings, linked to evapotranspiration rates of up to 20 mm/ month. Daytime cloud cover is up to 30% higher over the cropland compared to its immediate surroundings, and this enhancement is highly correlated with the seasonal variability in leaf area index. The cloud enhancement is associated with a much more rapid cloud cloud development during the morning. Afternoon rainfall is 85% higher over, and just downwind, of the cropland during the growing season, although rainfall remains very low in absolute terms. The feedback sign we find is the opposite to what has been observed in tropical and semiarid regions, where temperature gradients promote convergence and clouds on the warmer side of land-surface type discontinuities. This suggests that different processes are responsible for the land-atmosphere feedback in very dry environments, where lack of moisture may be a stronger constraint. Increased cloud and rainfall, and associated increases in diffuse radiation and reductions in temperature, can affect vegetation growth thus producing an internal feedback. These effects will therefore need to be taken into account to properly assess the impact of climate change on crop productivity and water use, as well as how global land

River catchment rainfall series analysis using additive Holt-Winters method

Science.gov (United States)

Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

2016-03-01

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

Pattern Analysis of El Nino and La Nina Phenomenon Based on Sea Surface Temperature (SST) and Rainfall Intensity using Oceanic Nino Index (ONI) in West Java Area

Science.gov (United States)

Prasetyo, Yudo; Nabilah, Farras

2017-12-01

Climate change occurs in 1998-2016 brings significant alteration in the earth surface. It is affects an extremely anomaly temperature such as El Nino and La Nina or mostly known as ENSO (El Nino Southern Oscillation). West Java is one of the regions in Indonesia that encounters the impact of this phenomenon. Climate change due to ENSO also affects food production and other commodities. In this research, processing data method is conducted using programming language to process SST data and rainfall data from 1998 to 2016. The data are sea surface temperature from NOAA satellite, SST Reynolds (Sea Surface Temperature) and daily rainfall temperature from TRMM satellite. Data examination is done using analysis of rainfall spatial pattern and sea surface temperature (SST) where is affected by El Nino and La Nina phenomenon. This research results distribution map of SST and rainfall for each season to find out the impacts of El Nino and La Nina around West Java. El Nino and La Nina in Java Sea are occurring every August to February. During El Nino, sea surface temperature is between 27°C - 28°C with average temperature on 27.71°C. Rainfall intensity is 1.0 mm/day - 2.0 mm/day and the average are 1.63 mm/day. During La Nina, sea surface temperature is between 29°C - 30°C with average temperature on 29.06°C. Rainfall intensity is 9.0 mm/day - 10 mm/day, and the average is 9.74 mm/day. The correlation between rainfall and SST is 0,413 which is expresses a fairly strong correlation between parameters. The conclusion is, during La Nina SST and rainfall increase. While during El Nino SST and rainfall decrease. Hopefully this research could be a guideline to plan disaster mitigation in West Java region that is related extreme climate change.

Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula

Science.gov (United States)

Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.

2012-08-01

This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.

Radar-based rainfall estimation: Improving Z/R relations through comparison of drop size distributions, rainfall rates and radar reflectivity patterns

Science.gov (United States)

Neuper, Malte; Ehret, Uwe

2014-05-01

The relation between the measured radar reflectivity factor Z and surface rainfall intensity R - the Z/R relation - is profoundly complex, so that in general one speaks about radar-based quantitative precipitation estimation (QPE) rather than exact measurement. Like in Plato's Allegory of the Cave, what we observe in the end is only the 'shadow' of the true rainfall field through a very small backscatter of an electromagnetic signal emitted by the radar, which we hope has been actually reflected by hydrometeors. The meteorological relevant and valuable Information is gained only indirectly by more or less justified assumptions. One of these assumptions concerns the drop size distribution, through which the rain intensity is finally associated with the measured radar reflectivity factor Z. The real drop size distribution is however subject to large spatial and temporal variability, and consequently so is the true Z/R relation. Better knowledge of the true spatio-temporal Z/R structure therefore has the potential to improve radar-based QPE compared to the common practice of applying a single or a few standard Z/R relations. To this end, we use observations from six laser-optic disdrometers, two vertically pointing micro rain radars, 205 rain gauges, one rawindsonde station and two C-band Doppler radars installed or operated in and near the Attert catchment (Luxembourg). The C-band radars and the rawindsonde station are operated by the Belgian and German Weather Services, the rain gauge data was partly provided by the French, Dutch, Belgian, German Weather Services and the Ministry of Agriculture of Luxembourg and the other equipment was installed as part of the interdisciplinary DFG research project CAOS (Catchment as Organized Systems). With the various data sets correlation analyzes were executed. In order to get a notion on the different appearance of the reflectivity patterns in the radar image, first of all various simple distribution indices (for example the

An Atlantic influence on Amazon rainfall

Energy Technology Data Exchange (ETDEWEB)

Yoon, Jin-Ho [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Zeng, Ning [University of Maryland, Earth System Science Interdisciplinary Center, College Park, MD (United States); University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States)

2010-02-15

Rainfall variability over the Amazon basin has often been linked to variations in Pacific sea surface temperature (SST), and in particular, to the El Nino/Southern Oscillation (ENSO). However, only a fraction of Amazon rainfall variability can be explained by ENSO. Building upon the recent work of Zeng (Environ Res Lett 3:014002, 2008), here we provide further evidence for an influence on Amazon rainfall from the tropical Atlantic Ocean. The strength of the North Atlantic influence is found to be comparable to the better-known Pacific ENSO connection. The tropical South Atlantic Ocean also shows some influence during the wet-to-dry season transition period. The Atlantic influence is through changes in the north-south divergent circulation and the movement of the ITCZ following warm SST. Therefore, it is strongest in the southern part of the Amazon basin during the Amazon's dry season (July-October). In contrast, the ENSO related teleconnection is through anomalous east-west Walker circulation with largely concentrated in the eastern (lower) Amazon. This ENSO connection is seasonally locked to boreal winter. A complication due to the influence of ENSO on Atlantic SST causes an apparent North Atlantic SST lag of Amazon rainfall. Removing ENSO from North Atlantic SST via linear regression resolves this causality problem in that the residual Atlantic variability correlates well and is in phase with the Amazon rainfall. A strong Atlantic influence during boreal summer and autumn is particularly significant in terms of the impact on the hydro-ecosystem which is most vulnerable during the dry season, as highlighted by the severe 2005 Amazon drought. Such findings have implications for both seasonal-interannual climate prediction and understanding the longer-term changes of the Amazon rainforest. (orig.)

Changes in rainfall patterns in Mediterranean ecosystems: the MIND project

Directory of Open Access Journals (Sweden)

Papale D

2007-12-01

Full Text Available Will Mediterranean terrestrial ecosystems be affected by the expected changes in precipitation regimes? If so, by how much and in which direction? These questions are at the basis of the research performed in context of the EU MIND project, whose key objectives were: i to investigate the potential effects of increasing drought on Mediterranean terrestrial ecosystems at the process, ecosystem and regional scales and ii to assess ecosystem vulnerability to changes in rainfall patterns. A network of experimental study sites has been created in Portugal, Spain, France and Italy, where field manipulations alter the amount of water available to the ecosystem. The most up-to-date methods of ecophysiology, micrometeorology, soil ecology and remote sensing have been used to elucidate the mechanisms that regulate the response of vegetation and soil to changes in water availability. This information is providing the basis for the implementation and validation of simulation models capable of predicting the drought response of Mediterranean terrestrial ecosystems, and their vulnerability to future climate change, on a larger scale. The out-coming results are elucidating how water availability affects plant ecophysiological processes, the dynamics of soil carbon and the overall exchange of mass and energy between the land and the atmosphere. This paper focuses on some of the important, yet preliminary, results on C and energy fluxes that have been obtained at the large scale troughfall manipulation experiment (Tolfa, Italy, in a forest dominated by Arbutus unedo L.

Congo Basin rainfall climatology: can we believe the climate models?

Science.gov (United States)

Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M; Moufouma-Okia, Wilfran

2013-01-01

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

OpenAIRE

Ayehu, Getachew Tesfaye; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

2018-01-01

Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through...

Gross rainfall amount and maximum rainfall intensity in 60-minute influence on interception loss of shrubs: a 10-year observation in the Tengger Desert.

Science.gov (United States)

Zhang, Zhi-Shan; Zhao, Yang; Li, Xin-Rong; Huang, Lei; Tan, Hui-Juan

2016-05-17

In water-limited regions, rainfall interception is influenced by rainfall properties and crown characteristics. Rainfall properties, aside from gross rainfall amount and duration (GR and RD), maximum rainfall intensity and rainless gap (RG), within rain events may heavily affect throughfall and interception by plants. From 2004 to 2014 (except for 2007), individual shrubs of Caragana korshinskii and Artemisia ordosica were selected to measure throughfall during 210 rain events. Various rainfall properties were auto-measured and crown characteristics, i.e., height, branch and leaf area index, crown area and volume of two shrubs were also measured. The relative interceptions of C. korshinskii and A. ordosica were 29.1% and 17.1%, respectively. Rainfall properties have more contributions than crown characteristics to throughfall and interception of shrubs. Throughfall and interception of shrubs can be explained by GR, RI60 (maximum rainfall intensities during 60 min), RD and RG in deceasing importance. However, relative throughfall and interception of two shrubs have different responses to rainfall properties and crown characteristics, those of C. korshinskii were closely related to rainfall properties, while those of A. ordosica were more dependent on crown characteristics. We highlight long-term monitoring is very necessary to determine the relationships between throughfall and interception with crown characteristics.

Engineering of an Extreme Rainfall Detection System using Grid Computing

Directory of Open Access Journals (Sweden)

Olivier Terzo

2012-10-01

Full Text Available This paper describes a new approach for intensive rainfall data analysis. ITHACA's Extreme Rainfall Detection System (ERDS is conceived to provide near real-time alerts related to potential exceptional rainfalls worldwide, which can be used by WFP or other humanitarian assistance organizations to evaluate the event and understand the potentially floodable areas where their assistance is needed. This system is based on precipitation analysis and it uses rainfall data from satellite at worldwide extent. This project uses the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis dataset, a NASA-delivered near real-time product for current rainfall condition monitoring over the world. Considering the great deal of data to process, this paper presents an architectural solution based on Grid Computing techniques. Our focus is on the advantages of using a distributed architecture in terms of performances for this specific purpose.

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

Science.gov (United States)

Msongaleli, Barnabas M; Tumbo, S D; Kihupi, N I; Rwehumbiza, Filbert B

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly.

Long-term changes in the water quality of rainfall, cloud water and stream water for moorland, forested and clear-felled catchments at Plynlimon, mid-Wales

Directory of Open Access Journals (Sweden)

C. Neal

2001-01-01

Full Text Available Long term changes in the water quality of rainfall, cloud water and stream waters draining acidic and acid sensitive moorland and forested catchments at Plynlimon, mid-Wales, are examined for the period 1983 to 2001. Atmospheric inputs of chloride and sulphate are influenced by the relative inputs of clean maritime and polluted land based air masses. There is no systematic increase or decrease over time for chloride and non-sea-salt sulphate. Rather, there is a decadal scale process possibly representative of the influence of the North Atlantic Oscillation that affects the maritime and pollution climate of the Atlantic seaboard of the UK. Over 17 years of study, there may be a small decrease in non-sea-salt sulphate of about 10 μeq l-1 and a small improvement in acid neutralising capacity of about 20 to 30 μeq l-1 in rainfall. There is a clear improvement in cloud water chemistry with respect to pollutant components (ammonium, nitrate, non-sea-salt sulphate and acidity (acid neutralising capacity improved by about 300 μeq l-1 through the study period. Many of the changes in cloud water chemistry are similar to rainfall over the same period except the magnitude of change is larger for the cloud water. Within the streams, there is some evidence for reductions in acidity as reflected by acid neutralising capacity becoming less negative. For one stream, deforestation occurred during the sampling period and this led to large increases in nitrate and smaller increases in aluminium midway through the study period. However, the climate and hydrological variability largely masked out other changes. The current analysis provides only a start to identifying trends for such a complex and variable environmental system. The need for strong statistical tools is emphasised to resolve issues of: (a hydrological induced water quality variability, (b changing soil and groundwater "endmember" chemistry contribution to the stream and (c the non-linear patterns of

Enhancement of seasonal prediction of East Asian summer rainfall related to the western tropical Pacific convection

Science.gov (United States)

Lee, D. Y.; Ahn, J. B.; Yoo, J. H.

2014-12-01

The prediction skills of climate model simulations in the western tropical Pacific (WTP) and East Asian region are assessed using the retrospective forecasts of seven state-of-the-art coupled models and their multi-model ensemble (MME) for boreal summers (June-August) during the period 1983-2005, along with corresponding observed and reanalyzed data. The prediction of summer rainfall anomalies in East Asia is difficult, while the WTP has a strong correlation between model prediction and observation. We focus on developing a new approach to further enhance the seasonal prediction skill for summer rainfall in East Asia and investigate the influence of convective activity in the WTP on East Asian summer rainfall. By analyzing the characteristics of the WTP convection, two distinct patterns associated with El Niño-Southern Oscillation (ENSO) developing and decaying modes are identified. Based on the multiple linear regression method, the East Asia Rainfall Index (EARI) is developed by using the interannual variability of the normalized Maritime continent-WTP indices (MPIs), as potentially useful predictors for rainfall prediction over East Asia, obtained from the above two main patterns. For East Asian summer rainfall, the EARI has superior performance to the East Asia summer monsoon index (EASMI) or each MP index (MPI). Therefore, the regressed rainfall from EARI also shows a strong relationship with the observed East Asian summer rainfall pattern. In addition, we evaluate the prediction skill of the East Asia reconstructed rainfall obtained by statistical-empirical approach using the cross-validated EARI from the individual models and their MME. The results show that the rainfalls reconstructed from simulations capture the general features of observed precipitation in East Asia quite well. This study convincingly demonstrates that rainfall prediction skill is considerably improved by using the statistical-empirical method compared to the dynamical models

Dryland ecosystem responses to precipitation extremes and wildfire at a long-term rainfall manipulation experiment

Science.gov (United States)

Brown, R. F.; Collins, S. L.

2017-12-01

Climate is becoming increasingly more variable due to global environmental change, which is evidenced by fewer, but more extreme precipitation events, changes in precipitation seasonality, and longer, higher severity droughts. These changes, combined with a rising incidence of wildfire, have the potential to strongly impact net primary production (NPP) and key biogeochemical cycles, particularly in dryland ecosystems where NPP is sequentially limited by water and nutrient availability. Here we utilize a ten-year dataset from an ongoing long-term field experiment established in 2007 in which we experimentally altered monsoon rainfall variability to examine how our manipulations, along with naturally occurring events, affect NPP and associated biogeochemical cycles in a semi-arid grassland in central New Mexico, USA. Using long-term regional averages, we identified extremely wet monsoon years (242.8 mm, 2013), and extremely dry monsoon years (86.0 mm, 2011; 80.0 mm, 2015) and water years (117.0 mm, 2011). We examined how changes in precipitation variability and extreme events affected ecosystem processes and function particularly in the context of ecosystem recovery following a 2009 wildfire. Response variables included above- and below-ground plant biomass (ANPP & BNPP) and abundance, soil nitrogen availability, and soil CO2 efflux. Mean ANPP ranged from 3.6 g m-2 in 2011 to 254.5 g m-2 in 2013, while BNPP ranged from 23.5 g m-2 in 2015 to 194.2 g m-2 in 2013, demonstrating NPP in our semi-arid grassland is directly linked to extremes in both seasonal and annual precipitation. We also show increased nitrogen deposition positively affects NPP in unburned grassland, but has no significant impact on NPP post-fire except during extremely wet monsoon years. While soil respiration rates reflect lower ANPP post-fire, patterns in CO2 efflux have not been shown to change significantly in that efflux is greatest following large precipitation events preceded by longer drying

Contribution of tropical cyclones to global rainfall

Science.gov (United States)

Khouakhi, Abdou; Villarini, Gabriele; Vecchi, Gabriel; Smith, James

2016-04-01

patterns using the POT approach to identify extremes. The fractional contributions decrease as we move inland from the coast. Moreover, the relationship between TC-induced extreme rainfall and the El Niño-Southern Oscillation is also examined using logistic and Poisson regression. Results indicate that TC-induced extreme rainfall tends to occur more frequently in Australia and along the U.S. East Coast during La Niña, and along eastern Asia and northwestern Pacific islands during El Niño.

Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

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Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

2015-12-01

Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is

Rainfall simulation experiments in the southwestern USA using the Walnut Gulch Rainfall Simulator

Science.gov (United States)

Polyakov, Viktor; Stone, Jeffry; Holifield Collins, Chandra; Nearing, Mark A.; Paige, Ginger; Buono, Jared; Gomez-Pond, Rae-Landa

2018-01-01

This dataset contains hydrological, erosion, vegetation, ground cover, and other supplementary information from 272 rainfall simulation experiments conducted on 23 semiarid rangeland locations in Arizona and Nevada between 2002 and 2013. On 30 % of the plots, simulations were conducted up to five times during the decade of study. The rainfall was generated using the Walnut Gulch Rainfall Simulator on 2 m by 6 m plots. Simulation sites included brush and grassland areas with various degrees of disturbance by grazing, wildfire, or brush removal. This dataset advances our understanding of basic hydrological and biological processes that drive soil erosion on arid rangelands. It can be used to estimate runoff, infiltration, and erosion rates at a variety of ecological sites in the Southwestern USA. The inclusion of wildfire and brush treatment locations combined with long-term observations makes it important for studying vegetation recovery, ecological transitions, and the effect of management. It is also a valuable resource for erosion model parameterization and validation. The dataset is available from the National Agricultural Library at https://data.nal.usda.gov/search/type/dataset (DOI: https://doi.org/10.15482/USDA.ADC/1358583).

Runoff prediction using rainfall data from microwave links: Tabor case study.

Science.gov (United States)

Stransky, David; Fencl, Martin; Bares, Vojtech

2018-05-01

Rainfall spatio-temporal distribution is of great concern for rainfall-runoff modellers. Standard rainfall observations are, however, often scarce and/or expensive to obtain. Thus, rainfall observations from non-traditional sensors such as commercial microwave links (CMLs) represent a promising alternative. In this paper, rainfall observations from a municipal rain gauge (RG) monitoring network were complemented by CMLs and used as an input to a standard urban drainage model operated by the water utility of the Tabor agglomeration (CZ). Two rainfall datasets were used for runoff predictions: (i) the municipal RG network, i.e. the observation layout used by the water utility, and (ii) CMLs adjusted by the municipal RGs. The performance was evaluated in terms of runoff volumes and hydrograph shapes. The use of CMLs did not lead to distinctively better predictions in terms of runoff volumes; however, CMLs outperformed RGs used alone when reproducing a hydrograph's dynamics (peak discharges, Nash-Sutcliffe coefficient and hydrograph's rising limb timing). This finding is promising for number of urban drainage tasks working with dynamics of the flow. Moreover, CML data can be obtained from a telecommunication operator's data cloud at virtually no cost. That makes their use attractive for cities unable to improve their monitoring infrastructure for economic or organizational reasons.

Comparison of short-term rainfall forecasts for modelbased flow prediction in urban drainage systems

DEFF Research Database (Denmark)

Thorndahl, Søren; Ahm, Malte; Nielsen, Jesper Ellerbek

2013-01-01

Forecast-based flow prediction in drainage systems can be used to implement real-time control of drainage systems. This study compares two different types of rainfall forecast - a radar rainfall extrapolation-based nowcast model and a numerical weather prediction model. The models are applied...... performance of the system is found using the radar nowcast for the short lead times and the weather model for larger lead times....

Long-term stability of tidal and diel-related patterns in mangrove creek fish assemblages in North Brazil

Science.gov (United States)

Castellanos-Galindo, G. A.; Krumme, U.

2014-08-01

Intertidal fish assemblages are thought to respond to tidal and diel rhythms although the assumption that these patterns are stable over long time scales (>1 year) is largely untested. Testing the validity of this assumption is necessary to assess whether short-term temporal patterns, once established, can be extrapolated over time and give a better understanding of the temporal dynamics of fish assemblages in coastal habitats. Here, we compare the fish assemblage structure from two intertidal mangrove creeks in North Brazil (Bragança Peninsula, Caeté estuary) sampled with the same sampling methodology (block nets), effort (two lunar cycles) and design (accounting for the combination of tidal and diel cycle) in the rainy seasons of 1999 and 2012 to evaluate the persistence, stability and recurrence of short-term patterns in the fish community organization. The interaction of tidal and diel cycles (inundations at spring tide-night, spring tide-day, neap tide-night, neap tide-day), found to be stable after 13 years, resulted in recurrent and stable intertidal mangrove fish assemblage compositions. The intertidal mangrove creek fish assemblage consisted of a persistent number of dominant species (seven). However, there were notable changes in fish catch mass, abundance and species dominance between 1999 and 2012. The most severe drought in North Brazil in 30 years, linked to lower precipitation and river runoff in the rainy season of 2012, may have resulted in (1) lower abundance of small juveniles of several dominant species in this assemblage (especially Ariidae - Cathorops agassizii and Sciades herzbergii) and (2) increased dominance of large-sized specimens of the tetraodontid Colomesus psittacus. Our findings highlight: (1) the overriding importance and stability of the interactive pulse of the tidal and diel cycles in determining short-term temporal patterns in intertidal mangrove fish assemblages in neotropical macrotidal estuaries despite the occurrence of

Predicted disappearance of Cephalantheropsis obcordata in Luofu Mountain due to changes in rainfall patterns.

Directory of Open Access Journals (Sweden)

Xin-Ju Xiao

Full Text Available BACKGROUND: In the past century, the global average temperature has increased by approximately 0.74°C and extreme weather events have become prevalent. Recent studies have shown that species have shifted from high-elevation areas to low ones because the rise in temperature has increased rainfall. These outcomes challenge the existing hypothesis about the responses of species to climate change. METHODOLOGY/PRINCIPAL FINDINGS: With the use of data on the biological characteristics and reproductive behavior of Cephalantheropsis obcordata in Luofu Mountain, Guangdong, China, trends in the population size of the species were predicted based on several factors. The response of C. obcordata to climate change was verified by integrating it with analytical findings on meteorological data and an artificially simulated environment of water change. The results showed that C. obcordata can grow only in waterlogged streams. The species can produce fruit with many seeds by insect pollination; however, very few seeds can burgeon to become seedlings, with most of those seedlings not maturing into the sexually reproductive phase, and grass plants will die after reproduction. The current population's age pyramid is kettle-shaped; it has a Deevey type I survival curve; and its net reproductive rate, intrinsic rate of increase, as well as finite rate of increase are all very low. The population used in the artificial simulation perished due to seasonal drought. CONCLUSIONS: The change in rainfall patterns caused by climate warming has altered the water environment of C. obcordata in Luofu Mountain, thereby restricting seed burgeoning as well as seedling growth and shortening the life span of the plant. The growth rate of the C. obcordata population is in descending order, and models of population trend predict that the population in Luofu Mountain will disappear in 23 years.

A simple stochastic rainstorm generator for simulating spatially and temporally varying rainfall

Science.gov (United States)

Singer, M. B.; Michaelides, K.; Nichols, M.; Nearing, M. A.

2016-12-01

In semi-arid to arid drainage basins, rainstorms often control both water supply and flood risk to marginal communities of people. They also govern the availability of water to vegetation and other ecological communities, as well as spatial patterns of sediment, nutrient, and contaminant transport and deposition on local to basin scales. All of these landscape responses are sensitive to changes in climate that are projected to occur throughout western North America. Thus, it is important to improve characterization of rainstorms in a manner that enables statistical assessment of rainfall at spatial scales below that of existing gauging networks and the prediction of plausible manifestations of climate change. Here we present a simple, stochastic rainstorm generator that was created using data from a rich and dense network of rain gauges at the Walnut Gulch Experimental Watershed (WGEW) in SE Arizona, but which is applicable anywhere. We describe our methods for assembling pdfs of relevant rainstorm characteristics including total annual rainfall, storm area, storm center location, and storm duration. We also generate five fitted intensity-duration curves and apply a spatial rainfall gradient to generate precipitation at spatial scales below gauge spacing. The model then runs by Monte Carlo simulation in which a total annual rainfall is selected before we generate rainstorms until the annual precipitation total is reached. The procedure continues for decadal simulations. Thus, we keep track of the hydrologic impact of individual storms and the integral of precipitation over multiple decades. We first test the model using ensemble predictions until we reach statistical similarity to the input data from WGEW. We then employ the model to assess decadal precipitation under simulations of climate change in which we separately vary the distribution of total annual rainfall (trend in moisture) and the intensity-duration curves used for simulation (trends in storminess). We

What aspects of future rainfall changes matter for crop yields in West Africa?

Science.gov (United States)

Guan, Kaiyu; Sultan, Benjamin; Biasutti, Michela; Baron, Christian; Lobell, David B.

2015-10-01

How rainfall arrives, in terms of its frequency, intensity, the timing and duration of rainy season, may have a large influence on rainfed agriculture. However, a thorough assessment of these effects is largely missing. This study combines a new synthetic rainfall model and two independently validated crop models (APSIM and SARRA-H) to assess sorghum yield response to possible shifts in seasonal rainfall characteristics in West Africa. We find that shifts in total rainfall amount primarily drive the rainfall-related crop yield change, with less relevance to intraseasonal rainfall features. However, dry regions (total annual rainfall below 500 mm/yr) have a high sensitivity to rainfall frequency and intensity, and more intense rainfall events have greater benefits for crop yield than more frequent rainfall. Delayed monsoon onset may negatively impact yields. Our study implies that future changes in seasonal rainfall characteristics should be considered in designing specific crop adaptations in West Africa.

Multidecadal oscillations in rainfall and hydrological extremes

Science.gov (United States)

Willems, Patrick

2013-04-01

Many studies have anticipated a worldwide increase in the frequency and intensity of precipitation extremes and floods since the last decade(s). Natural variability by climate oscillations partly determines the observed evolution of precipitation extremes. Based on a technique for the identification and analysis of changes in extreme quantiles, it is shown that hydrological extremes have oscillatory behaviour at multidecadal time scales. Results are based on nearly independent extremes extracted from long-term historical time series of precipitation intensities and river flows. Study regions include Belgium - The Netherlands (Meuse basin), Ethiopia (Blue Nile basin) and Ecuador (Paute basin). For Belgium - The Netherlands, the past 100 years showed larger and more hydrological extremes around the 1910s, 1950-1960s, and more recently during the 1990-2000s. Interestingly, the oscillations for southwestern Europe are anti-correlated with these of northwestern Europe, thus with oscillation highs in the 1930-1940s and 1970s. The precipitation oscillation peaks are explained by persistence in atmospheric circulation patterns over the North Atlantic during periods of 10 to 15 years. References: Ntegeka V., Willems P. (2008), 'Trends and multidecadal oscillations in rainfall extremes, based on a more than 100 years time series of 10 minutes rainfall intensities at Uccle, Belgium', Water Resources Research, 44, W07402, doi:10.1029/2007WR006471 Mora, D., Willems, P. (2012), 'Decadal oscillations in rainfall and air temperature in the Paute River Basin - Southern Andes of Ecuador', Theoretical and Applied Climatology, 108(1), 267-282, doi:0.1007/s00704-011-0527-4 Taye, M.T., Willems, P. (2011). 'Influence of climate variability on representative QDF predictions of the upper Blue Nile Basin', Journal of Hydrology, 411, 355-365, doi:10.1016/j.jhydrol.2011.10.019 Taye, M.T., Willems, P. (2012). 'Temporal variability of hydro-climatic extremes in the Blue Nile basin', Water

Study of acid mine drainage management with evaluating climate and rainfall in East Pit 3 West Banko coal mine

Science.gov (United States)

Rochyani, Neny

2017-11-01

Acid mine drainage is a major problem for the mining environment. The main factor that formed acid mine drainage is the volume of rainfall. Therefore, it is important to know clearly the main climate pattern of rainfall and season on the management of acid mine drainage. This study focuses on the effects of rainfall on acid mine water management. Based on daily rainfall data, monthly and seasonal patterns by using Gumbel approach is known the amount of rainfall that occurred in East Pit 3 West Banko area. The data also obtained the highest maximum daily rainfall on 165 mm/day and the lowest at 76.4 mm/day, where it is known that the rainfall conditions during the period 2007 - 2016 is from November to April so the use of lime is also slightly, While the low rainfall is from May to October and the use of lime will be more and more. Based on calculation of lime requirement for each return period, it can be seen the total of lime and financial requirement for treatment of each return period.

Modelling rainfall erosion resulting from climate change

Science.gov (United States)

Kinnell, Peter

2016-04-01

It is well known that soil erosion leads to agricultural productivity decline and contributes to water quality decline. The current widely used models for determining soil erosion for management purposes in agriculture focus on long term (~20 years) average annual soil loss and are not well suited to determining variations that occur over short timespans and as a result of climate change. Soil loss resulting from rainfall erosion is directly dependent on the product of runoff and sediment concentration both of which are likely to be influenced by climate change. This presentation demonstrates the capacity of models like the USLE, USLE-M and WEPP to predict variations in runoff and erosion associated with rainfall events eroding bare fallow plots in the USA with a view to modelling rainfall erosion in areas subject to climate change.

Examining spatial-temporal variability and prediction of rainfall in North-eastern Nigeria

Science.gov (United States)

Muhammed, B. U.; Kaduk, J.; Balzter, H.

2012-12-01

In the last 50 years rainfall in North-eastern Nigeria under the influence of the West African Monsoon (WAM) has been characterised by large annual variations with severe droughts recorded in 1967-1973, and 1983-1987. This variability in rainfall has a large impact on the regions agricultural output, economy and security where the majority of the people depend on subsistence agriculture. In the 1990s there was a sign of recovery with higher annual rainfall totals compared to the 1961-1990 period but annual totals were slightly above the long term mean for the century. In this study we examine how significant this recovery is by analysing medium-term (1980-2006) rainfall of the region using the Climate Research Unit (CRU) and National Centre for Environment Prediction (NCEP) precipitation ½ degree, 6 hourly reanalysis data set. Percentage coefficient of variation increases northwards for annual rainfall (10%-35%) and the number of rainy days (10%-50%). The standardized precipitation index (SPI) of the area shows 7 years during the period as very wet (1996, 1999, 2003 and 2004) with SPI≥1.5 and moderately wet (1993, 1998, and 2006) with values of 1.0≥SPI≤1.49. Annual rainfall indicates a recovery from the 1990s and onwards but significant increases (in the amount of rainfall and number of days recorded with rainfall) is only during the peak of the monsoon season in the months of August and September (pARIMA) model. The model is further evaluated using 24 months rainfall data yielding r=0.79 (regression slope=0.8; pARIMA model and the rainfall data used for this study indicates that the model can be satisfactorily used in forecasting rainfall in the in the sub-humid part of North-eastern Nigeria over a 24 months period.

Rainfall simulators - innovations seeking rainfall uniformity and automatic flow rate measurements

Science.gov (United States)

Bauer, Miroslav; Kavka, Petr; Strouhal, Luděk; Dostál, Tomáš; Krása, Josef

2016-04-01

single pressure operating mode, which is ensured by the pressure probe controlled electromagnetic valve. Previous experiments implied the need of automatic continuous measurements of selected variables. To this end the control unit was equipped with a datalogger. In a several seconds time step it collects the values of water pressure, nozzle-valves operation, control point rainfall intensity from a tipping bucket rain gauge, topsoil moisture from several Theta ML2x probes and most recently the plot outlet runoff rate. For a continuous runoff rate measurement a 0,4-foot HS-flume was constructed and equipped with S18U ultrasonic sensor. Assemble setting was optimised both in flow rate laboratory flume and in laboratory rainfall simulator. Namely the rating curves for particular flume bottom slopes were derived. Employment of the flume in the terrain is scheduled for the experimental season 2016, but laboratory results already show sufficient measurement accuracy and are promising in terms of experimental campaigns simplification. The abovementioned activities have been supported by the research grants SGS14/180/OHK1/3T/11, QJ1530181, QJ1520265 and QJ1330118.

Heterogeneity of Dutch rainfall

NARCIS (Netherlands)

Witter, J.V.

1984-01-01

Rainfall data for the Netherlands have been used in this study to investigate aspects of heterogeneity of rainfall, in particular local differences in rainfall levels, time trends in rainfall, and local differences in rainfall trend. The possible effect of urbanization and industrialization on the

Assessment of satellite rainfall products over the Andean plateau

Science.gov (United States)

Satgé, Frédéric; Bonnet, Marie-Paule; Gosset, Marielle; Molina, Jorge; Hernan Yuque Lima, Wilson; Pillco Zolá, Ramiro; Timouk, Franck; Garnier, Jérémie

2016-01-01

Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north-south gradient and a lighter east-west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (- 42%) and moderately negative for GSMaP (- 18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2 mm day- 1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a

Feasibility Study on the Satellite Rainfall Data for Prediction of Sediment- Related Disaster by the Japanese Prediction Methodology

Science.gov (United States)

Shimizu, Y.; Ishizuka, T.; Osanai, N.; Okazumi, T.

2014-12-01

In this study, the sediment-related disaster prediction method which based ground gauged rainfall-data, currently practiced in Japan was coupled with satellite rainfall data and applied to domestic large-scale sediment-related disasters. The study confirmed the feasibility of this integrated method. In Asia, large-scale sediment-related disasters which can sweep away an entire settlement occur frequently. Leyte Island suffered from a huge landslide in 2004, and Typhoon Molakot in 2009 caused huge landslides in Taiwan. In the event of these sediment-related disasters, immediate responses by central and local governments are crucial in crisis management. In general, there are not enough rainfall gauge stations in developing countries. Therefore national and local governments have little information to determine the risk level of water induced disasters in their service areas. In the Japanese methodology, a criterion is set by combining two indices: the short-term rainfall index and long-term rainfall index. The short-term rainfall index is defined as the 60-minute total rainfall; the long-term rainfall index as the soil-water index, which is an estimation of the retention status of fallen rainfall in soil. In July 2009, a high-density sediment related disaster, or a debris flow, occurred in Hofu City of Yamaguchi Prefecture, in the western region of Japan. This event was calculated by the Japanese standard methodology, and then analyzed for its feasibility. Hourly satellite based rainfall has underestimates compared with ground based rainfall data. Long-term index correlates with each other. Therefore, this study confirmed that it is possible to deliver information on the risk level of sediment-related disasters such as shallow landslides and debris flows. The prediction method tested in this study is expected to assist for timely emergency responses to rainfall-induced natural disasters in sparsely gauged areas. As the Global Precipitation Measurement (GPM) Plan

[Response of sloping water erosion to rainfall and micro-earth pattern in the loess hilly area].

Science.gov (United States)

Wei, Wei; Jia, Fu-yan; Chen, Li-ding; Wu, Dong-ping; Chen, Jin

2012-08-01

Severe water erosion in the key loess hilly area is affected by the coupling role of rainfall and earth surface features. In this study, rainfall simulation techniques at the micro-plot scale (1.2 m x 1.2 m; 2 m x 1.2 m) was used as the basic measures, the relations between rainfall depth, intensity and runoff-erosion under different plant morphology features as well as micro-landscape positions were quantified and analyzed. Several key findings were captured. Firstly, rainfall depth and intensity both affected water erosion significantly, while the role of the rainfall intensity was more important than that of the depth. Secondly, a strong negative correlation was found between the antecedent soil moisture content and the generation timing of surface runoff, while water erosion had a positive relation with the antecedent soil moisture. Thirdly, different plant morphology and micro-landscape positions of shrub plant (seabuckthorn) played different roles leading to different rates of surface runoff and soil erosion. Dominated by a rainfall intensity ranging from 50 to 60 mm x h(-1), runoff coefficient in those micro-plots covered by seabuckthorn was about 5%-8%, and changed into 25%, 45% and 63% in grassland-plots, bared plots covered by biological-crust and bared plots without any coverage, respectively. Fourthly, the specific landscape position of seabuckthorn in the plots was also found to play a key role in affecting water erosion processes, and seabuckthorn at the lower landscape position, rather than the upper and middle position, played a better buffering role in reducing runoff and soil loss.

Numerical simulation of rainfall and temperature over Kenya using weather research and forecasting-environmental modelling system (WRF-EMS

Directory of Open Access Journals (Sweden)

Sagero Obaigwa Philip

2016-01-01

Full Text Available This paper focuses on one of the high resolution models used for weather forecasting at Kenya Meteorological Department (KMD. It reviews the skill and accuracy of the Weather Research and Forecasting (WRF - Environmental Modeling System (EMS model, in simulating weather over Kenya. The study period was March to May 2011, during the rainy season over Kenya. The model output was compared with the observed data from 27 synoptic stations spread over the study area, to determine the performance of the model in terms of its skill and accuracy in forecasting. The spatial distribution of rainfall and temperature showed that the WRF model was capable of reproducing the observed general pattern especially for temperature. The model has skill in forecasting both rainfall and temperature over the study area. However, the model may underestimate rainfall of more than 10 mm/day and displace its location and overestimate rainfall of less than 1 mm/day. Therefore, during the period of enhanced rainfall especially in the month of April and part of May the model forecast needs to be complemented by other models or forecasting methods before giving a forecast. There is need to improve its performance over the domain through review of the parameterization of small scale physical processes and more observed data need to be simulated into the model.

Analysis of rainfall and temperature time series to detect long-term climatic trends and variability over semi-arid Botswana

Science.gov (United States)

Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.

2018-03-01

Arid and semi-arid environments have been identified with locations prone to impacts of climate variability and change. Investigating long-term trends is one way of tracing climate change impacts. This study investigates variability through annual and seasonal meteorological time series. Possible inhomogeneities and years of intervention are analysed using four absolute homogeneity tests. Trends in the climatic variables were determined using Mann-Kendall and Sen's Slope estimator statistics. Association of El Niño Southern Oscillation (ENSO) with local climate is also investigated through multivariate analysis. Results from the study show that rainfall time series are fully homogeneous with 78.6 and 50% of the stations for maximum and minimum temperature, respectively, showing homogeneity. Trends also indicate a general decrease of 5.8, 7.4 and 18.1% in annual, summer and winter rainfall, respectively. Warming trends are observed in annual and winter temperature at 0.3 and 1.5% for maximum temperature and 1.7 and 6.5% for minimum temperature, respectively. Rainfall reported a positive correlation with Southern Oscillation Index (SOI) and at the same time negative association with Sea Surface Temperatures (SSTs). Strong relationships between SSTs and maximum temperature are observed during the El Niño and La Niña years. These study findings could facilitate planning and management of agricultural and water resources in Botswana.

Different impacts of mega-ENSO and conventional ENSO on the Indian summer rainfall: developing phase

Science.gov (United States)

Zhang, Lei; Wu, Zhiwei; Zhou, Yefan

2016-04-01

Mega-El Niño-Southern Oscillation (ENSO), a boarder version of conventional ENSO, is found to be a main driving force of Northern Hemisphere summer monsoon rainfall including the Indian summer rainfall (ISR). The simultaneous impacts of "pure" mega-ENSO and "pure" conventional ENSO events on the ISR in its developing summer remains unclear. This study examines the different linkages between mega-ENSO-ISR and conventional ENSO-ISR. During the developing summer of mega-El Niño, negative rainfall anomalies are seen over the northeastern Indian subcontinent, while the anomalous rainfall pattern is almost the opposite for mega-La Niña; as for the conventional ENSO, the approximate "linear opposite" phenomenon vanishes. Furthermore, the global zonal wave trains anomalous are found at mid-latitude zones, with a local triple circulation pattern over the central-east Eurasia during mega-ENSO events, which might be an explanation of corresponding rainfall response over the Indian Peninsula. Among 106-year historical run (1900-2005) of 9 state-of-the-art models from the Coupled Model Inter-comparison Project Phase 5 (CMIP5), HadGEM2-ES performs a promising skill in simulating the anomalous circulation pattern over mid-latitude and central-east Eurasia while CanESM2 cannot. Probably, it is the models' ability of capturing the mega-ENSO-ISR linkage and the characteristic of mega-ENSO that make the difference.

Climate downscaling over South America for 1971-2000: application in SMAP rainfall-runoff model for Grande River Basin

Science.gov (United States)

da Silva, Felipe das Neves Roque; Alves, José Luis Drummond; Cataldi, Marcio

2018-03-01

This paper aims to validate inflow simulations concerning the present-day climate at Água Vermelha Hydroelectric Plant (AVHP—located on the Grande River Basin) based on the Soil Moisture Accounting Procedure (SMAP) hydrological model. In order to provide rainfall data to the SMAP model, the RegCM regional climate model was also used working with boundary conditions from the MIROC model. Initially, present-day climate simulation performed by RegCM model was analyzed. It was found that, in terms of rainfall, the model was able to simulate the main patterns observed over South America. A bias correction technique was also used and it was essential to reduce mistakes related to rainfall simulation. Comparison between rainfall simulations from RegCM and MIROC showed improvements when the dynamical downscaling was performed. Then, SMAP, a rainfall-runoff hydrological model, was used to simulate inflows at Água Vermelha Hydroelectric Plant. After calibration with observed rainfall, SMAP simulations were evaluated in two different periods from the one used in calibration. During calibration, SMAP captures the inflow variability observed at AVHP. During validation periods, the hydrological model obtained better results and statistics with observed rainfall. However, in spite of some discrepancies, the use of simulated rainfall without bias correction captured the interannual flow variability. However, the use of bias removal in the simulated rainfall performed by RegCM brought significant improvements to the simulation of natural inflows performed by SMAP. Not only the curve of simulated inflow became more similar to the observed inflow, but also the statistics improved their values. Improvements were also noticed in the inflow simulation when the rainfall was provided by the regional climate model compared to the global model. In general, results obtained so far prove that there was an added value in rainfall when regional climate model was compared to global climate

Spatio-temporal trends of rainfall across Indian river basins

Science.gov (United States)

Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, Narendra Singh; Sridhar, Venkataramana

2018-04-01

Daily gridded high-resolution rainfall data of India Meteorological Department at 0.25° spatial resolution (1901-2015) was analyzed to detect the trend in seasonal, annual, and maximum cumulative rainfall for 1, 2, 3, and 5 days. The present study was carried out for 85 river basins of India during 1901-2015 and pre- and post-urbanization era, i.e., 1901-1970 and 1971-2015, respectively. Mann-Kendall ( α = 0.05) and Theil-Sen's tests were employed for detecting the trend and percentage of change over the period of time, respectively. Daily extreme rainfall events, above 95 and 99 percentile threshold, were also analyzed to detect any trend in their magnitude and number of occurrences. The upward trend was found for the majority of the sub-basins for 1-, 2-, 3-, and 5-day maximum cumulative rainfall during the post-urbanization era. The magnitude of extreme threshold events is also found to be increasing in the majority of the river basins during the post-urbanization era. A 30-year moving window analysis further revealed a widespread upward trend in a number of extreme threshold rainfall events possibly due to urbanization and climatic factors. Overall trends studied against intra-basin trend across Ganga basin reveal the mixed pattern of trends due to inherent spatial heterogeneity of rainfall, therefore, highlighting the importance of scale for such studies.

Should seasonal rainfall forecasts be used for flood preparedness?

Directory of Open Access Journals (Sweden)

E. Coughlan de Perez

2017-09-01

Full Text Available In light of strong encouragement for disaster managers to use climate services for flood preparation, we question whether seasonal rainfall forecasts should indeed be used as indicators of the likelihood of flooding. Here, we investigate the primary indicators of flooding at the seasonal timescale across sub-Saharan Africa. Given the sparsity of hydrological observations, we input bias-corrected reanalysis rainfall into the Global Flood Awareness System to identify seasonal indicators of floodiness. Results demonstrate that in some regions of western, central, and eastern Africa with typically wet climates, even a perfect tercile forecast of seasonal total rainfall would provide little to no indication of the seasonal likelihood of flooding. The number of extreme events within a season shows the highest correlations with floodiness consistently across regions. Otherwise, results vary across climate regimes: floodiness in arid regions in southern and eastern Africa shows the strongest correlations with seasonal average soil moisture and seasonal total rainfall. Floodiness in wetter climates of western and central Africa and Madagascar shows the strongest relationship with measures of the intensity of seasonal rainfall. Measures of rainfall patterns, such as the length of dry spells, are least related to seasonal floodiness across the continent. Ultimately, identifying the drivers of seasonal flooding can be used to improve forecast information for flood preparedness and to avoid misleading decision-makers.

Rainfall Modification by Urban Areas: New Perspectives from TRMM

Science.gov (United States)

Shepherd, J. Marshall; Pierce, Harold F.; Negri, Andrew

2002-01-01

Data from the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48% - 116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. Future work is extending the investigation to Phoenix, Arizona, an arid U.S. city, and several international cities like Mexico City, Johannesburg, and Brasilia. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Evaluate Hydrologic Response on Spatiotemporal Characteristics of Rainfall Using High Resolution Radar Rainfall Data and WRF-Hydro Model

Science.gov (United States)

Gao, S.; Fang, N. Z.

2017-12-01

A previously developed Dynamic Moving Storm (DMS) generator is a multivariate rainfall model simulating the complex nature of precipitation field: spatial variability, temporal variability, and storm movement. Previous effort by the authors has investigated the sensitivity of DMS parameters on corresponding hydrologic responses by using synthetic storms. In this study, the DMS generator has been upgraded to generate more realistic precipitation field. The dependence of hydrologic responses on rainfall features was investigated by dissecting the precipitation field into rain cells and modifying their spatio-temporal specification individually. To retrieve DMS parameters from radar rainfall data, rain cell segmentation and tracking algorithms were respectively developed and applied on high resolution radar rainfall data (1) to spatially determine the rain cells within individual radar image and (2) to temporally analyze their dynamic behavior. Statistics of DMS parameters were established by processing a long record of rainfall data (10 years) to keep the modification on real storms within the limit of regional climatology. Empirical distributions of the DMS parameters were calculated to reveal any preferential pattern and seasonality. Subsequently, the WRF-Hydro model forced by the remodeled and modified precipitation was used for hydrologic simulation. The study area was the Upper Trinity River Basin (UTRB) watershed, Texas; and two kinds of high resolution radar data i.e. the Next-Generation Radar (NEXRAD) level III Digital Hybrid Reflectivity (DHR) product and Multi-Radar Multi-Sensor (MRMS) precipitation rate product, were utilized to establish parameter statistics and to recreate/remodel historical events respectively. The results demonstrated that rainfall duration is a significant linkage between DMS parameters and their hydrologic impacts—any combination of spatiotemporal characteristics that keep rain cells longer over the catchment will produce higher

Rainfall Erosivity in Europe

DEFF Research Database (Denmark)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale

2015-01-01

Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the Rfactor in the USLE model and its revised version, RUSLE. At national...... and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based...

Long term changes in flooding and heavy rainfall associated with North Atlantic tropical cyclones: Roles of the North Atlantic Oscillation and El Niño-Southern Oscillation

Science.gov (United States)

Aryal, Yog N.; Villarini, Gabriele; Zhang, Wei; Vecchi, Gabriel A.

2018-04-01

The aim of this study is to examine the contribution of North Atlantic tropical cyclones (TCs) to flooding and heavy rainfall across the continental United States. Analyses highlight the spatial variability in these hazards, their temporal changes in terms of frequency and magnitude, and their connection to large-scale climate, in particular to the North Atlantic Oscillation (NAO) and El Niño-Southern Oscillation (ENSO). We use long-term stream and rain gage measurements, and our analyses are based on annual maxima (AMs) and peaks-over-threshold (POTs). TCs contribute to ∼20-30% of AMs and POTs over Florida and coastal areas of the eastern United States, and the contribution decreases as we move inland. We do not detect statistically significant trends in the magnitude or frequency of TC floods. Regarding the role of climate, NAO and ENSO do not play a large role in controlling the frequency and magnitude of TC flooding. The connection between heavy rainfall and TCs is comparable to what observed in terms of flooding. Unlike flooding, NAO plays a significant role in TC-related extreme rainfall along the U.S. East Coast, while ENSO is most strongly linked to the TC precipitation in Texas.

Damaging Rainfall and Flooding. The Other Sahel Hazards

Energy Technology Data Exchange (ETDEWEB)

Tarhule, A. [Department of Geography, University of Oklahoma, 100 East Boyd Street, Norman, OK, 73079 (United States)

2005-10-01

Damaging rainfall and rain-induced flooding occur from time to time in the drought-prone Sahel savannah zone of Niger in West Africa but official records of these events and their socioeconomic impacts do not exist. This paper utilized newspaper accounts between 1970 and 2000 to survey and illustrate the range of these flood hazards in the Sahel. During the study interval, 53 newspaper articles reported 79 damaging rainfall and flood events in 47 different communities in the Sahel of Niger. Collectively, these events destroyed 5,580 houses and rendered 27,289 people homeless. Cash losses and damage to infrastructure in only three events exceeded $4 million. Sahel residents attribute these floods to five major causes including both natural and anthropogenic, but they view the flood problem as driven primarily by land use patterns. Despite such awareness, traditional coping strategies appear inadequate for dealing with the problems in part because of significant climatic variability. Analysis of several rainfall measures indicates that the cumulative rainfall in the days prior to a heavy rain event is an important factor influencing whether or not heavy rainfall results in flooding. Thus, despite some limitations, newspaper accounts of historical flooding are largely consistent with measured climatic variables. The study demonstrates that concerted effort is needed to improve the status of knowledge concerning flood impacts and indeed other natural and human hazards in the Sahel.

Performance of CMORPH, TMPA, and PERSIANN rainfall datasets over plain, mountainous, and glacial regions of Pakistan

Science.gov (United States)

Hussain, Yawar; Satgé, Frédéric; Hussain, Muhammad Babar; Martinez-Carvajal, Hernan; Bonnet, Marie-Paule; Cárdenas-Soto, Martin; Roig, Henrique Llacer; Akhter, Gulraiz

2018-02-01

The present study aims at the assessment of six satellite rainfall estimates (SREs) in Pakistan. For each assessed products, both real-time (RT) and post adjusted (Adj) versions are considered to highlight their potential benefits in the rainfall estimation at annual, monthly, and daily temporal scales. Three geomorphological climatic zones, i.e., plain, mountainous, and glacial are taken under considerations for the determination of relative potentials of these SREs over Pakistan at global and regional scales. All SREs, in general, have well captured the annual north-south rainfall decreasing patterns and rainfall amounts over the typical arid regions of the country. Regarding the zonal approach, the performance of all SREs has remained good over mountainous region comparative to arid regions. This poor performance in accurate rainfall estimation of all the six SREs over arid regions has made their use questionable in these regions. Over glacier region, all SREs have highly overestimated the rainfall. One possible cause of this overestimation may be due to the low surface temperature and radiation absorption over snow and ice cover, resulting in their misidentification with rainy clouds as daily false alarm ratio has increased from mountainous to glacial regions. Among RT products, CMORPH-RT is the most biased product. The Bias was almost removed on CMORPH-Adj thanks to the gauge adjustment. On a general way, all Adj versions outperformed their respective RT versions at all considered temporal scales and have confirmed the positive effects of gauge adjustment. CMORPH-Adj and TMPA-Adj have shown the best agreement with in situ data in terms of Bias, RMSE, and CC over the entire study area.

Mapping monthly rainfall erosivity in Europe.

Science.gov (United States)

Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan; Meusburger, Katrin; Michaelides, Silas; Beguería, Santiago; Klik, Andreas; Petan, Sašo; Janeček, Miloslav; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Tadić, Melita Perčec; Diodato, Nazzareno; Kostalova, Julia; Rousseva, Svetla; Banasik, Kazimierz; Alewell, Christine; Panagos, Panos

2017-02-01

Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha -1 h -1 ) compared to winter (87MJmmha -1 h -1 ). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R 2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be

Spatiotemporal Interpolation of Rainfall by Combining BME Theory and Satellite Rainfall Estimates

Directory of Open Access Journals (Sweden)

Tingting Shi

2015-09-01

Full Text Available The accurate assessment of spatiotemporal rainfall variability is a crucial and challenging task in many hydrological applications, mainly due to the lack of a sufficient number of rain gauges. The purpose of the present study is to investigate the spatiotemporal variations of annual and monthly rainfall over Fujian province in China by combining the Bayesian maximum entropy (BME method and satellite rainfall estimates. Specifically, based on annual and monthly rainfall data at 20 meteorological stations from 2000 to 2012, (1 the BME method with Tropical Rainfall Measuring Mission (TRMM estimates considered as soft data, (2 ordinary kriging (OK and (3 cokriging (CK were employed to model the spatiotemporal variations of rainfall in Fujian province. Subsequently, the performance of these methods was evaluated using cross-validation statistics. The results demonstrated that BME with TRMM as soft data (BME-TRMM performed better than the other two methods, generating rainfall maps that represented the local rainfall disparities in a more realistic manner. Of the three interpolation (mapping methods, the mean absolute error (MAE and root mean square error (RMSE values of the BME-TRMM method were the smallest. In conclusion, the BME-TRMM method improved spatiotemporal rainfall modeling and mapping by integrating hard data and soft information. Lastly, the study identified new opportunities concerning the application of TRMM rainfall estimates.

Seasonal rainfall-runoff relationships in a lowland forested watershed in the southeastern USA

Science.gov (United States)

Ileana La Torre Torres; Devendra Amatya; Ge Sun; Timothy Callahan

2011-01-01

Hydrological processes of lowland watersheds of the southern USA are not well understood compared to a hilly landscape due to their unique topography, soil compositions, and climate. This study describes the seasonal relationships between rainfall patterns and runoff (sum of storm flow and base flow) using 13 years (1964–1976) of rainfall and stream flow data for a low...

Projections of West African summer monsoon rainfall extremes from two CORDEX models

Science.gov (United States)

Akinsanola, A. A.; Zhou, Wen

2018-05-01

Global warming has a profound impact on the vulnerable environment of West Africa; hence, robust climate projection, especially of rainfall extremes, is quite important. Based on two representative concentration pathway (RCP) scenarios, projected changes in extreme summer rainfall events over West Africa were investigated using data from the Coordinated Regional Climate Downscaling Experiment models. Eight (8) extreme rainfall indices (CDD, CWD, r10mm, r20mm, PRCPTOT, R95pTOT, rx5day, and sdii) defined by the Expert Team on Climate Change Detection and Indices were used in the study. The performance of the regional climate model (RCM) simulations was validated by comparing with GPCP and TRMM observation data sets. Results show that the RCMs reasonably reproduced the observed pattern of extreme rainfall over the region and further added significant value to the driven GCMs over some grids. Compared to the baseline period 1976-2005, future changes (2070-2099) in summer rainfall extremes under the RCP4.5 and RCP8.5 scenarios show statistically significant decreasing total rainfall (PRCPTOT), while consecutive dry days and extreme rainfall events (R95pTOT) are projected to increase significantly. There are obvious indications that simple rainfall intensity (sdii) will increase in the future. This does not amount to an increase in total rainfall but suggests a likelihood of greater intensity of rainfall events. Overall, our results project that West Africa may suffer more natural disasters such as droughts and floods in the future.

The rainfall plot: its motivation, characteristics and pitfalls.

Science.gov (United States)

Domanska, Diana; Vodák, Daniel; Lund-Andersen, Christin; Salvatore, Stefania; Hovig, Eivind; Sandve, Geir Kjetil

2017-05-18

A visualization referred to as rainfall plot has recently gained popularity in genome data analysis. The plot is mostly used for illustrating the distribution of somatic cancer mutations along a reference genome, typically aiming to identify mutation hotspots. In general terms, the rainfall plot can be seen as a scatter plot showing the location of events on the x-axis versus the distance between consecutive events on the y-axis. Despite its frequent use, the motivation for applying this particular visualization and the appropriateness of its usage have never been critically addressed in detail. We show that the rainfall plot allows visual detection even for events occurring at high frequency over very short distances. In addition, event clustering at multiple scales may be detected as distinct horizontal bands in rainfall plots. At the same time, due to the limited size of standard figures, rainfall plots might suffer from inability to distinguish overlapping events, especially when multiple datasets are plotted in the same figure. We demonstrate the consequences of plot congestion, which results in obscured visual data interpretations. This work provides the first comprehensive survey of the characteristics and proper usage of rainfall plots. We find that the rainfall plot is able to convey a large amount of information without any need for parameterization or tuning. However, we also demonstrate how plot congestion and the use of a logarithmic y-axis may result in obscured visual data interpretations. To aid the productive utilization of rainfall plots, we demonstrate their characteristics and potential pitfalls using both simulated and real data, and provide a set of practical guidelines for their proper interpretation and usage.

Mapping monthly rainfall erosivity in Europe

DEFF Research Database (Denmark)

Ballabio, C; Meusburger, K; Klik, A

2017-01-01

to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive...... and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part...... selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency...

Rainfall simulators in hydrological and geomorphological sciences: benefits, applications and future research directions

Science.gov (United States)

Iserloh, Thomas; Cerdà, Artemi; Fister, Wolfgang; Seitz, Steffen; Keesstra, Saskia; Green, Daniel; Gabriels, Donald

2017-04-01

Rainfall simulators are used extensively within the hydrological and geomorphological sciences and provide a useful investigative tool to understand many processes, such as: (i) plot-scale runoff, infiltration and erosion; (ii) irrigation and crop management, and; (iii) investigations into flooding within a laboratory setting. Although natural rainfall is desirable as it represents actual conditions in a given geographic location, data acquisition relying on natural rainfall is often hindered by its unpredictable nature. Furthermore, rainfall characteristics such as the intensity, duration, drop size distribution and kinetic energy cannot be spatially or temporally regulated or repeated between experimentation. Rainfall simulators provide a suitable method to overcome the issues associated with depending on potentially erratic and unpredictable natural rainfall as they allow: (i) multiple measurements to be taken quickly without waiting for suitable natural rainfall conditions; (ii) the simulation of spatially and/or temporally controlled rainfall patterns over a given plot area, and; (iii) the creation of a closed environment, allowing simplified measurement of input and output conditions. There is no standardisation of rainfall simulation and as such, rainfall simulators differ in their design, rainfall characteristics and research application. Although this impedes drawing meaningful comparisons between studies, this allows researchers to create a bespoke and tailored rainfall simulator for the specific research application. This paper summarises the rainfall simulators used in European research institutions (Universities of Trier, Valencia, Basel, Tuebingen, Wageningen, Loughborough and Ghent) to investigate a number of hydrological and geomorphological issues and includes details on the design specifications (such as the extent and characteristics of simulated rainfall), as well as a discussion of the purpose and application of the rainfall simulator.

Comparison of short term rainfall forecasts for model based flow prediction in urban drainage systems

DEFF Research Database (Denmark)

Thorndahl, Søren; Poulsen, Troels Sander; Bøvith, Thomas

2012-01-01

Forecast based flow prediction in drainage systems can be used to implement real time control of drainage systems. This study compares two different types of rainfall forecasts – a radar rainfall extrapolation based nowcast model and a numerical weather prediction model. The models are applied...... performance of the system is found using the radar nowcast for the short leadtimes and weather model for larger lead times....

Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

Science.gov (United States)

Santos, Monica; Fragoso, Marcelo

2010-05-01

Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude

Global Climatic Indices Influence on Rainfall Spatiotemporal Distribution : A Case Study from Morocco

Science.gov (United States)

Elkadiri, R.; Zemzami, M.; Phillips, J.

2017-12-01

The climate of Morocco is affected by the Mediterranean Sea, the Atlantic Ocean the Sahara and the Atlas mountains, creating a highly variable spatial and temporal distribution. In this study, we aim to decompose the rainfall in Morocco into global and local signals and understand the contribution of the climatic indices (CIs) on rainfall. These analyses will contribute in understanding the Moroccan climate that is typical of other Mediterranean and North African climatic zones. In addition, it will contribute in a long-term prediction of climate. The constructed database ranges from 1950 to 2013 and consists of monthly data from 147 rainfall stations and 37 CIs data provided mostly by the NOAA Climate Prediction Center. The next general steps were followed: (1) the study area was divided into 9 homogenous climatic regions and weighted precipitation was calculated for each region to reduce the local effects. (2) Each CI was decomposed into nine components of different frequencies (D1 to D9) using wavelet multiresolution analysis. The four lowest frequencies of each CI were selected. (3) Each of the original and resulting signals were shifted from one to six months to account for the effect of the global patterns. The application of steps two and three resulted in the creation of 1225 variables from the original 37 CIs. (4) The final 1225 variables were used to identify links between the global and regional CIs and precipitation in each of the nine homogenous regions using stepwise regression and decision tree. The preliminary analyses and results were focused on the north Atlantic zone and have shown that the North Atlantic Oscillation (PC-based) from NCAR (NAOPC), the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the Western Mediterranean Oscillation (WMO) and the Extreme Eastern Tropical Pacific Sea Surface Temperature (NINO12) have the highest correlation with rainfall (33%, 30%, 27%, 21% and -20%, respectively). In addition the 4-months lagged

Multi-century cool- and warm-season rainfall reconstructions for Australia's major climatic regions

Science.gov (United States)

Freund, Mandy; Henley, Benjamin J.; Karoly, David J.; Allen, Kathryn J.; Baker, Patrick J.

2017-11-01

Australian seasonal rainfall is strongly affected by large-scale ocean-atmosphere climate influences. In this study, we exploit the links between these precipitation influences, regional rainfall variations, and palaeoclimate proxies in the region to reconstruct Australian regional rainfall between four and eight centuries into the past. We use an extensive network of palaeoclimate records from the Southern Hemisphere to reconstruct cool (April-September) and warm (October-March) season rainfall in eight natural resource management (NRM) regions spanning the Australian continent. Our bi-seasonal rainfall reconstruction aligns well with independent early documentary sources and existing reconstructions. Critically, this reconstruction allows us, for the first time, to place recent observations at a bi-seasonal temporal resolution into a pre-instrumental context, across the entire continent of Australia. We find that recent 30- and 50-year trends towards wetter conditions in tropical northern Australia are highly unusual in the multi-century context of our reconstruction. Recent cool-season drying trends in parts of southern Australia are very unusual, although not unprecedented, across the multi-century context. We also use our reconstruction to investigate the spatial and temporal extent of historical drought events. Our reconstruction reveals that the spatial extent and duration of the Millennium Drought (1997-2009) appears either very much below average or unprecedented in southern Australia over at least the last 400 years. Our reconstruction identifies a number of severe droughts over the past several centuries that vary widely in their spatial footprint, highlighting the high degree of diversity in historical droughts across the Australian continent. We document distinct characteristics of major droughts in terms of their spatial extent, duration, intensity, and seasonality. Compared to the three largest droughts in the instrumental period (Federation Drought

Multi-century cool- and warm-season rainfall reconstructions for Australia's major climatic regions

Directory of Open Access Journals (Sweden)

M. Freund

2017-11-01

Full Text Available Australian seasonal rainfall is strongly affected by large-scale ocean–atmosphere climate influences. In this study, we exploit the links between these precipitation influences, regional rainfall variations, and palaeoclimate proxies in the region to reconstruct Australian regional rainfall between four and eight centuries into the past. We use an extensive network of palaeoclimate records from the Southern Hemisphere to reconstruct cool (April–September and warm (October–March season rainfall in eight natural resource management (NRM regions spanning the Australian continent. Our bi-seasonal rainfall reconstruction aligns well with independent early documentary sources and existing reconstructions. Critically, this reconstruction allows us, for the first time, to place recent observations at a bi-seasonal temporal resolution into a pre-instrumental context, across the entire continent of Australia. We find that recent 30- and 50-year trends towards wetter conditions in tropical northern Australia are highly unusual in the multi-century context of our reconstruction. Recent cool-season drying trends in parts of southern Australia are very unusual, although not unprecedented, across the multi-century context. We also use our reconstruction to investigate the spatial and temporal extent of historical drought events. Our reconstruction reveals that the spatial extent and duration of the Millennium Drought (1997–2009 appears either very much below average or unprecedented in southern Australia over at least the last 400 years. Our reconstruction identifies a number of severe droughts over the past several centuries that vary widely in their spatial footprint, highlighting the high degree of diversity in historical droughts across the Australian continent. We document distinct characteristics of major droughts in terms of their spatial extent, duration, intensity, and seasonality. Compared to the three largest droughts in the instrumental

Understanding extreme rainfall events in Australia through historical data

Science.gov (United States)

Ashcroft, Linden; Karoly, David John

2016-04-01

Historical climate data recovery is still an emerging field in the Australian region. The majority of Australia's instrumental climate analyses begin in 1900 for rainfall and 1910 for temperature, particularly those focussed on extreme event analysis. This data sparsity for the past in turn limits our understanding of long-term climate variability, constraining efforts to predict the impact of future climate change. To address this need for improved historical data in Australia, a new network of recovered climate observations has recently been developed, centred on the highly populated southeastern Australian region (Ashcroft et al., 2014a, 2014b). The dataset includes observations from more than 39 published and unpublished sources and extends from British settlement in 1788 to the formation of the Australian Bureau of Meteorology in 1908. Many of these historical sources provide daily temperature and rainfall information, providing an opportunity to improve understanding of the multidecadal variability of Australia's extreme events. In this study we combine the historical data for three major Australian cities - Melbourne, Sydney and Adelaide - with modern observations to examine extreme rainfall variability over the past 174 years (1839-2013). We first explore two case studies, combining instrumental and documentary evidence to support the occurrence of severe storms in Sydney in 1841 and 1844. These events appear to be at least as extreme as Sydney's modern 24-hour rainfall record. Next we use a suite of rainfall indices to assess the long-term variability of rainfall in southeastern Australia. In particular, we focus on the stationarity of the teleconnection between the El Niño-Southern Oscillation (ENSO) phenomenon and extreme rainfall events. Using ENSO reconstructions derived from both palaeoclimatic and documentary sources, we determine the historical relationship between extreme rainfall in southeastern Australia and ENSO, and examine whether or not this

Unusual rainfall shift during monsoon period of 2010 in Pakistan ...

African Journals Online (AJOL)

Arslan

2013-09-04

Sep 4, 2013 ... Key words: Indus River, monsoon, flooding in 2010, rainfall pattern, Climate ... data was plotted in excel sheet with upper and lower limits defined .... Houze Jr, Rasmussen R, Medina K, Brodzik S, Romatschke SU (2011).

Estimating impact of rainfall change on hydrological processes in Jianfengling rainforest watershed, China using BASINS-HSPF-CAT modeling system

Science.gov (United States)

Zhang Zhou; Ying Ouyang; Yide Li; Zhijun Qiu; Matt Moran

2017-01-01

Climate change over the past several decades has resulted in shifting rainfall pattern and modifying rain-fall intensity, which has exacerbated hydrological processes and added the uncertainty and instability tothese processes. This study ascertained impacts of potential future rainfall change on hydrological pro-cesses at the Jianfengling (JFL) tropical mountain...

Rainfall mediations in the spreading of epidemic cholera

Science.gov (United States)

Righetto, L.; Bertuzzo, E.; Mari, L.; Schild, E.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

2013-10-01

the eradication of the disease in Haiti. The projections, although strongly depending on still uncertain epidemiological processes, show an endemic, seasonal pattern establishing in the region, which can be better forestalled by an improvement of the sanitation system only, rather than by vaccination alone. We thus conclude that hydrologic drivers and water resources management prove central to prediction, emergency management and long-term control of epidemic cholera.

Rainfall simulation in education

Science.gov (United States)

Peters, Piet; Baartman, Jantiene; Gooren, Harm; Keesstra, Saskia

2016-04-01

Rainfall simulation has become an important method for the assessment of soil erosion and soil hydrological processes. For students, rainfall simulation offers an year-round, attractive and active way of experiencing water erosion, while not being dependent on (outdoors) weather conditions. Moreover, using rainfall simulation devices, they can play around with different conditions, including rainfall duration, intensity, soil type, soil cover, soil and water conservation measures, etc. and evaluate their effect on erosion and sediment transport. Rainfall simulators differ in design and scale. At Wageningen University, both BSc and MSc student of the curriculum 'International Land and Water Management' work with different types of rainfall simulation devices in three courses: - A mini rainfall simulator (0.0625m2) is used in the BSc level course 'Introduction to Land Degradation and Remediation'. Groups of students take the mini rainfall simulator with them to a nearby field location and test it for different soil types, varying from clay to more sandy, slope angles and vegetation or litter cover. The groups decide among themselves which factors they want to test and they compare their results and discuss advantage and disadvantage of the mini-rainfall simulator. - A medium sized rainfall simulator (0.238 m2) is used in the MSc level course 'Sustainable Land and Water Management', which is a field practical in Eastern Spain. In this course, a group of students has to develop their own research project and design their field measurement campaign using the transportable rainfall simulator. - Wageningen University has its own large rainfall simulation laboratory, in which a 15 m2 rainfall simulation facility is available for research. In the BSc level course 'Land and Water Engineering' Student groups will build slopes in the rainfall simulator in specially prepared containers. Aim is to experience the behaviour of different soil types or slope angles when (heavy) rain

Developing Methods For Linking Surficial Aquifers With Localized Rainfall Data

Science.gov (United States)

Lafrenz, W. B.; van Gaalen, J. F.

2008-12-01

Water level hydrographs of the surficial aquifer can be evaluated to identify both the cause and consequence of water supply development. Rainfall, as a source of direct recharge and as a source of delayed or compounded recharge, is often the largest influence on surficial aquifer water level responses. It is clear that proximity of the rain gauge to the observation well is a factor in the degree of correlation, but in central Florida, USA, rainfall patterns change seasonally, with latitude, and with distance from the coast . Thus, for a location in central Florida, correlation of rain events with observed hydrograph responses depends on both distance and direction from an observation well to a rain gauge. In this study, we examine the use of extreme value analysis as a method of selecting the best rainfall data set for describing a given surficial aquifer monitor well. A surficial aquifer monitor well with a substantial suite of data is compared to a series of rainfall data sets from gauges ranging from meters to tens of kilometers in distance from the monitor well. The gauges vary in a wide range of directions from the monitor well in an attempt to identify both a method for rainfall gauge selection to be associated with the monitor well. Each rainfall gauge is described by a correlation coefficient with respect to the surficial aquifer water level data.

Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System

Science.gov (United States)

Fallah-Ghalhary, G.-A.; Habibi Nokhandan, M.; Mousavi Baygi, M.

2009-04-01

Long-term rainfall prediction is very important to countries thriving on agro-based economy. In general, climate and rainfall are highly non-linear phenomena in nature giving rise to what is known as "butterfly effect". The parameters that are required to predict the rainfall are enormous even for a short period. Soft computing is an innovative approach to construct computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments, and explain how they make decisions. Unlike conventional artificial intelligence techniques the guiding principle of soft computing is to exploit tolerance for imprecision, uncertainty, robustness, partial truth to achieve tractability, and better rapport with reality. In this paper, 33 years of rainfall data analyzed in khorasan state, the northeastern part of Iran situated at latitude-longitude pairs (31°-38°N, 74°- 80°E). this research attempted to train Fuzzy Inference System (FIS) based prediction models with 33 years of rainfall data. For performance evaluation, the model predicted outputs were compared with the actual rainfall data. Simulation results reveal that soft computing techniques are promising and efficient. The test results using by FIS model showed that the RMSE was obtained 52 millimeter.

On the dust load and rainfall relationship in South Asia: an analysis from CMIP5

Science.gov (United States)

Singh, Charu; Ganguly, Dilip; Dash, S. K.

2018-01-01

This study is aimed at examining the consistency of the relationship between load of dust and rainfall simulated by different climate models and its implication for the Indian summer monsoon system. Monthly mean outputs of 12 climate models, obtained from the archive of the Coupled Model Intercomparison Project phase 5 (CMIP5) for the period 1951-2004, are analyzed to investigate the relationship between dust and rainfall. Comparative analysis of the model simulated precipitation with the India Meteorological Department (IMD) gridded rainfall, CRU TS3.21 and GPCP version 2.2 data sets show significant differences between the spatial patterns of JJAS rainfall as well as annual cycle of rainfall simulated by various models and observations. Similarly, significant inter-model differences are also noted in the simulation of load of dust, nevertheless it is further noted that most of the CMIP5 models are able to capture the major dust sources across the study region. Although the scatter plot analysis and the lead-lag pattern correlation between the dust load and the rainfall show strong relationship between the dust load over distant sources and the rainfall in the South Asian region in individual models, the temporal scale of this association indicates large differences amongst the models. Our results caution that it would be pre-mature to draw any robust conclusions on the time scale of the relationship between dust and the rainfall in the South Asian region based on either CMIP5 results or limited number of previous studies. Hence, we would like to emphasize upon the fact that any conclusions drawn on the relationship between the dust load and the South Asian rainfall using model simulation is highly dependent on the degree of complexity incorporated in those models such as the representation of aerosol life cycle, their interaction with clouds, precipitation and other components of the climate system.

The effects of long-term variation in rainfall and dry matter ...

African Journals Online (AJOL)

track herds or flocks and associated cash flows through sequences of different climatic years, or years of different bio- logical quality (Foran & Stafford Smith, l99l). Procedure. In the more arid grazing zones of South Africa, many of the problems faced by livestock producers can be related to the effects of rainfall, both the ...

Rainfall: State of the Science

Science.gov (United States)

Testik, Firat Y.; Gebremichael, Mekonnen

Rainfall: State of the Science offers the most up-to-date knowledge on the fundamental and practical aspects of rainfall. Each chapter, self-contained and written by prominent scientists in their respective fields, provides three forms of information: fundamental principles, detailed overview of current knowledge and description of existing methods, and emerging techniques and future research directions. The book discusses • Rainfall microphysics: raindrop morphodynamics, interactions, size distribution, and evolution • Rainfall measurement and estimation: ground-based direct measurement (disdrometer and rain gauge), weather radar rainfall estimation, polarimetric radar rainfall estimation, and satellite rainfall estimation • Statistical analyses: intensity-duration-frequency curves, frequency analysis of extreme events, spatial analyses, simulation and disaggregation, ensemble approach for radar rainfall uncertainty, and uncertainty analysis of satellite rainfall products The book is tailored to be an indispensable reference for researchers, practitioners, and graduate students who study any aspect of rainfall or utilize rainfall information in various science and engineering disciplines.

Trends in rainfall and rainfall-related extremes in the east coast of peninsular Malaysia

Science.gov (United States)

Mayowa, Olaniya Olusegun; Pour, Sahar Hadi; Shahid, Shamsuddin; Mohsenipour, Morteza; Harun, Sobri Bin; Heryansyah, Arien; Ismail, Tarmizi

2015-12-01

The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfall- related extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971-2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann-Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.

Observed magnified runoff response to rainfall intensification under global warming

International Nuclear Information System (INIS)

Huang, Jr-Chuan; Lee, Tsung-Yu; Lee, Jun-Yi

2014-01-01

Runoff response to rainfall intensification under global warming is crucial, but is poorly discussed due to the limited data length and human alteration. Historical rainfall and runoff records in pristine catchments in Taiwan were investigated through trend analysis and cross temperature difference analysis. Trend analysis showed that both rainfall and runoff in the 99.9-percentile have been significantly increasing in terms of frequency and intensity over the past four decades. Cross temperature difference analysis quantified that the rainfall and runoff extremes (including the 99.0–99.9-percentiles) may increase by 69.5% and 99.8%, respectively, under a future scenario of 1  ° C increase in temperature. This increase in intensity resembles the increase in intensity observed between 1971–1990 and 1991–2010. The amplified runoff response can be related to the limited catchment storage capacity being preoccupied by rainfall extremes. The quantified temperature effect on rainfall and runoff intensification can be a strong basis for designing scenarios, confirming and fusing GCMs’ results. In addition, the runoff amplification should be a warning for other regions with significant rainfall intensification. Appropriate strategies are indispensable and urgently needed to maintain and protect the development of societies. (paper)

Application of Statistical Downscaling Techniques to Predict Rainfall and Its Spatial Analysis Over Subansiri River Basin of Assam, India

Science.gov (United States)

Barman, S.; Bhattacharjya, R. K.

2017-12-01

The River Subansiri is the major north bank tributary of river Brahmaputra. It originates from the range of Himalayas beyond the Great Himalayan range at an altitude of approximately 5340m. Subansiri basin extends from tropical to temperate zones and hence exhibits a great diversity in rainfall characteristics. In the Northern and Central Himalayan tracts, precipitation is scarce on account of high altitudes. On the other hand, Southeast part of the Subansiri basin comprising the sub-Himalayan and the plain tract in Arunachal Pradesh and Assam, lies in the tropics. Due to Northeast as well as Southwest monsoon, precipitation occurs in this region in abundant quantities. Particularly, Southwest monsoon causes very heavy precipitation in the entire Subansiri basin during May to October. In this study, the rainfall over Subansiri basin has been studied at 24 different locations by multiple linear and non-linear regression based statistical downscaling techniques and by Artificial Neural Network based model. APHRODITE's gridded rainfall data of 0.25˚ x 0.25˚ resolutions and climatic parameters of HadCM3 GCM of resolution 2.5˚ x 3.75˚ (latitude by longitude) have been used in this study. It has been found that multiple non-linear regression based statistical downscaling technique outperformed the other techniques. Using this method, the future rainfall pattern over the Subansiri basin has been analyzed up to the year 2099 for four different time periods, viz., 2020-39, 2040-59, 2060-79, and 2080-99 at all the 24 locations. On the basis of historical rainfall, the months have been categorized as wet months, months with moderate rainfall and dry months. The spatial changes in rainfall patterns for all these three types of months have also been analyzed over the basin. Potential decrease of rainfall in the wet months and months with moderate rainfall and increase of rainfall in the dry months are observed for the future rainfall pattern of the Subansiri basin.

Landslide prediction system for rainfall induced landslides in Slovenia (Masprem

Directory of Open Access Journals (Sweden)

Mateja Jemec Auflič

2016-12-01

Full Text Available In this paper we introduce a landslide prediction system for modelling the probabilities of landslides through time in Slovenia (Masprem. The system to forecast rainfall induced landslides is based on the landslide susceptibility map, landslide triggering rainfall threshold values and the precipitation forecasting model. Through the integrated parameters a detailed framework of the system, from conceptual to operational phases, is shown. Using fuzzy logic the landslide prediction is calculated. Potential landslide areas are forecasted on a national scale (1: 250,000 and on a local scale (1: 25,000 for fie selected municipalities where the exposure of inhabitants, buildings and different type of infrastructure is displayed, twice daily. Due to different rainfall patterns that govern landslide occurrences, the system for landslide prediction considers two different rainfall scenarios (M1 and M2. The landslides predicted by the two models are compared with a landslide inventory to validate the outputs. In this study we highlight the rainfall event that lasted from the 9th to the 14th of September 2014 when abundant precipitation triggered over 800 slope failures around Slovenia and caused large material damage. Results show that antecedent rainfall plays an important role, according to the comparisons of the model (M1 where antecedent rainfall is not considered. Although in general the landslides areas are over-predicted and largely do not correspond to the landslide inventory, the overall performance indicates that the system is able to capture the crucial factors in determining the landslide location. Additional calibration of input parameters and the landslide inventory as well as improved spatially distributed rainfall forecast data can further enhance the model's prediction.

Rainfall leaching is critical for long-term use of recycled water in the Salinas Valley

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Belinda E. Platts

2014-07-01

Full Text Available In 1998, Monterey County Water Recycling Projects began delivering water to 12,000 acres in the northern Salinas Valley. Two years later, an ongoing study began assessing the effects of the recycled water on soil salinity. Eight sites are receiving recycled water and a control site is receiving only well water. In data collected from 2000 to 2012, soil salinity of the 36-inch-deep profile was on average approximately double that of the applied water, suggesting significant leaching from applied water (irrigation or rainfall. In this study, we investigated some of the soil water hydrology factors possibly controlling the soil salinity results. Using soil water balance modeling, we found that rainfall had more effect on soil salinity than did leaching from irrigation. Increasing applied water usually only correlated significantly with soil salinity parameters in the shallow soil profile (1 to 12 inches depth and at 24 to 36 inches at sites receiving fairly undiluted recycled water. Winter rains, though, had a critical effect. Increasing rainfall depths were significantly correlated with decreasing soil salinity of the shallow soil at all test sites, though this effect also diminished with increased soil depth. When applied water had high salinity levels, winter rainfall in this area was inadequate to prevent soil salinity from increasing.

Synoptic aspects of the central Chile rainfall variability associated with the southern oscillation

International Nuclear Information System (INIS)

Rutllant, J.; Fuenzalida, H.

1988-07-01

Central Chile winter rainfall patterns show a positive anomaly during the developing stage of warm events associated to the negative phase of the Southern Oscillation. On the other hand, cold events during the positive phase of the Southern Oscillation, correspond quite closely to dry conditions. However, several dry years seem to precede or follow warm events without being necessarily classified as cold events. A synoptic characterization of major winter storms during the development of the most recent warm events in 1972, 1982 and 1987, is presented. Dry winter months during cold-event years are described in terms of average 500 hPa contour anomaly fields. Significant departures from this general behavior, as storms not associated to warm events and extended dry periods during otherwise wet winters, are also analyzed. It is found that major winter storms occurring during the developing phase of warm events are related to hemispheric types of blocking and anomaly patterns where sonal wavenumber 4 and a particular phase of wavenumber 3 dominate. The blockings, located in the Bellingshausen sea area, split the westerly flow diverting the storm tracks towards central Chile. Cold years, often immediately preceding or following a warm event, bring dry conditions in the study area due to a well developed subtropical anticyclonic belt and predominantly sonal westerly flow. Superimposed on these general conditions, anomaly contour patterns in southern South America reveal opposite signs with respect to those associated to warm events. Heavy winter storms not coinciding with warm events show local types of blocking in the Antartic peninsula area, with meridionally or slightly NE-SW oriented troughs and ridges. Extended dry spells and rainfall episodes during warm-event winters seem to be connected with alternating subtropical anomalies moving east with an intraseasonal time scale, superimposed on the aforementioned anomaly pattern at high latitudes. 21 refs, 17 figs, 1 tab

Exploring the Variability of Short-term Precipitation and Hydrological Response of Small Czech Watersheds

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Kavka, Petr; Strouhal, Ludek; Weyskrabova, Lenka; Müller, Miloslav; Kozant, Petr

2017-04-01

The short-term rainfall temporal distribution is known to have a significant effect on the small watersheds' hydrological response. In Czech Republic there are limited publicly available data on rainfall patterns of short-term precipitation. On one side there are catalogues of very short-term synthetic rainfalls used in urban drainage planning and on the other side hourly distribution of daily totals of rainfalls with long return period for larger catchments analyses. This contribution introduces the preliminary outcomes of a running three years' project, which should bridge this gap and provide such data and methodology to the community of scientists, state administration as well as design planners. Six generalized 6-hours hyetographs with 1 minute resolution were derived from 10 years of radar and gauging stations data. These hyetographs are accompanied with information concerning the region of occurrence as well as their frequency related to the rainfall amount. In the next step these hyetographs are used in a complex sensitivity analysis focused on a rainfall-runoff response of small watersheds. This analysis takes into account the uncertainty related to type of the hydrological model, watershed characteristics and main model routines parameterization. Five models with different methods and structure are considered and each model is applied on 5 characteristic watersheds selected from a classification of 7700 small Czech watersheds. For each combination of model and watershed 30, rainfall scenarios were simulated and other scenarios will be used to address the parameters uncertainty. In the last step the variability of outputs will be assessed in the context of economic impacts on design of landscape water structures or mitigation measures. The research is supported by the grant QJ1520265 of the Czech Ministry of Agriculture, rainfall data were provided by the Czech Hydrometeorological Institute.

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

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Carolien Toté

2015-02-01

Full Text Available Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT v2.0, Famine Early Warning System NETwork (FEWS NET Rainfall Estimate (RFE v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS are compared to independent gauge data (2001–2012. This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

Science.gov (United States)

Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Science.gov (United States)

Tesfaye Ayehu, Getachew; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

2018-04-01

Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days) and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD = 0.99, 1.00) and measure of volumetric rainfall (VHI = 1.00, 1.00), the highest correlation coefficients (r = 0.81, 0.88), better bias values (0.96, 0.96), and the lowest RMSE (28.45 mm dekad-1, 59.03 mm month-1) than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale), although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance underestimating rain gauge observed rainfall by

Influence of southern oscillation on autumn rainfall in Iran (1951-2011)

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Roghani, Rabbaneh; Soltani, Saeid; Bashari, Hossein

2016-04-01

This study aimed to investigate the relationships between southern oscillation and autumn (October-December) rainfall in Iran. It also sought to identify the possible physical mechanisms involved in the mentioned relationships by analyzing observational atmospheric data. Analyses were based on monthly rainfall data from 50 synoptic stations with at least 35 years of records up to the end of 2011. Autumn rainfall time series were grouped by the average Southern Oscillation Index (SOI) and SOI phase methods. Significant differences between rainfall groups in each method were assessed by Kruskal-Wallis and Kolmogorov-Smirnov non-parametric tests. Their relationships were also validated using the linear error in probability space (LEPS) test. The results showed that average SOI and SOI phases during July-September were related with autumn rainfall in some regions located in the west and northwest of Iran, west coasts of the Caspian Sea and southern Alborz Mountains. The El Niño (negative) and La Niña (positive) phases were associated with increased and decreased autumn rainfall, respectively. Our findings also demonstrated the persistence of Southern Pacific Ocean's pressure signals on autumn rainfall in Iran. Geopotential height patterns were totally different in the selected El Niño and La Niña years over Iran. During the El Niño years, a cyclone was formed over the north of Iran and an anticyclone existed over the Mediterranean Sea. During La Niña years, the cyclone shifted towards the Mediterranean Sea and an anticyclone developed over Iran. While these El Niño conditions increased autumn rainfall in Iran, the opposite conditions during the La Niña phase decreased rainfall in the country. In conclusion, development of rainfall prediction models based on the SOI can facilitate agricultural and water resources management in Iran.

Traffic Flow Prediction with Rainfall Impact Using a Deep Learning Method

Directory of Open Access Journals (Sweden)

Yuhan Jia

2017-01-01

Full Text Available Accurate traffic flow prediction is increasingly essential for successful traffic modeling, operation, and management. Traditional data driven traffic flow prediction approaches have largely assumed restrictive (shallow model architectures and do not leverage the large amount of environmental data available. Inspired by deep learning methods with more complex model architectures and effective data mining capabilities, this paper introduces the deep belief network (DBN and long short-term memory (LSTM to predict urban traffic flow considering the impact of rainfall. The rainfall-integrated DBN and LSTM can learn the features of traffic flow under various rainfall scenarios. Experimental results indicate that, with the consideration of additional rainfall factor, the deep learning predictors have better accuracy than existing predictors and also yield improvements over the original deep learning models without rainfall input. Furthermore, the LSTM can outperform the DBN to capture the time series characteristics of traffic flow data.

The Impact of a Amazonian Deforestation on Dry-Season Rainfall

Science.gov (United States)

Negri, Andrew J.; Adler, Robert F.; Xu, Liming; Surratt, Jason

2003-01-01

Many modeling studies have concluded that widespread deforestation of Amazonia would lead to decreased rainfall. We analyze geosynchronous infrared satellite data with respect to percent cloudiness, and analyze rain estimates from microwave sensors aboard the Tropical Rainfall Measuring Mission satellite. We conclude that in the dry-season, when the effects of the surface are not overwhelmed by synoptic-scale weather disturbances, shallow cumulus cloudiness, deep convective cloudiness, and rainfall occurrence all are larger over the deforested and non-forested (savanna) regions than over areas of dense jungle. This difference is in response to a local circulation initiated by the differential heating of the region s varying forestation. Analysis of the diurnal cycle of cloudiness reveals a shift in the onset of convection toward afternoon hours in the deforested and towards the morning hours in the savanna regions when compared to the neighboring forested regions. Analysis of 14 years of monthly estimates from the Special Sensor Microwave/Imager data revealed that in only in August was there a pattern of higher monthly rainfall amounts over the deforested region.

Exogenous factors matter when interpreting the results of an impact evaluation: a case study of rainfall and child health programme intervention in Rwanda.

Science.gov (United States)

Mukabutera, Assumpta; Thomson, Dana R; Hedt-Gauthier, Bethany L; Atwood, Sidney; Basinga, Paulin; Nyirazinyoye, Laetitia; Savage, Kevin P; Habimana, Marcellin; Murray, Megan

2017-12-01

Public health interventions are often implemented at large scale, and their evaluation seems to be difficult because they are usually multiple and their pathways to effect are complex and subject to modification by contextual factors. We assessed whether controlling for rainfall-related variables altered estimates of the efficacy of a health programme in rural Rwanda and have a quantifiable effect on an intervention evaluation outcomes. We conducted a retrospective quasi-experimental study using previously collected cross-sectional data from the 2005 and 2010 Rwanda Demographic and Health Surveys (DHS), 2010 DHS oversampled data, monthly rainfall data collected from meteorological stations over the same period, and modelled output of long-term rainfall averages, soil moisture, and rain water run-off. Difference-in-difference models were used. Rainfall factors confounded the PIH intervention impact evaluation. When we adjusted our estimates of programme effect by controlling for a variety of rainfall variables, several effectiveness estimates changed by 10% or more. The analyses that did not adjust for rainfall-related variables underestimated the intervention effect on the prevalence of ARI by 14.3%, fever by 52.4% and stunting by 10.2%. Conversely, the unadjusted analysis overestimated the intervention's effect on diarrhoea by 56.5% and wasting by 80%. Rainfall-related patterns have a quantifiable effect on programme evaluation results and highlighted the importance and complexity of controlling for contextual factors in quasi-experimental design evaluations. © 2017 John Wiley & Sons Ltd.

Quality-control of an hourly rainfall dataset and climatology of extremes for the UK.

Science.gov (United States)

Blenkinsop, Stephen; Lewis, Elizabeth; Chan, Steven C; Fowler, Hayley J

2017-02-01

Sub-daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non-operation of gauges. Given the prospect of an intensification of short-duration rainfall in a warming climate, the identification of such errors is essential if sub-daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near-complete hourly records for 1992-2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n-largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north-south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub-daily rainfall, with convection dominating during summer. The resulting quality-controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality-control procedures for sub-daily data, the validation of the new generation of very high

South Asian Summer Monsoon Rainfall Variability and Trend: Its Links to Indo-Pacific SST Anomalies and Moist Processes

Science.gov (United States)

Prasanna, V.

2016-06-01

The warm (cold) phase of El Niño (La Niña) and its impact on all Indian Summer Monsoon rainfall (AISMR) relationship is explored for the past 100 years. The 103-year (1901-2003) data from the twentieth century reanalysis datasets (20CR) and other major reanalysis datasets for southwest monsoon season (JJAS) is utilized to find out the simultaneous influence of the El Niño Southern Oscillation (ENSO)-AISMR relationship. Two cases such as wet, dry monsoon years associated with ENSO(+) (El Niño), ENSO(-) (La Niña) and Non-ENSO (neutral) events have been discussed in detail using observed rainfall and three-dimensional 20CR dataset. The dry and wet years associated with ENSO and Non-ENSO periods show significant differences in the spatial pattern of rainfall associated with three-dimensional atmospheric composite, the 20CR dataset has captured the anomalies quite well. During wet (dry) years, the rainfall is high (low), i.e. 10 % above (below) average from the long-term mean and this wet or dry condition occur both during ENSO and Non-ENSO phases. The Non-ENSO year dry or wet composites are also focused in detail to understand, where do the anomalous winds come from unlike in the ENSO case. The moisture transport is coherent with the changes in the spatial pattern of AISMR and large-scale feature in the 20CR dataset. Recent 50-year trend (1951-2000) is also analyzed from various available observational and reanalysis datasets to see the influence of Indo-Pacific SST and moist processes on the South Asian summer monsoon rainfall trend. Apart from the Indo-Pacific sea surface temperatures (SST), the moisture convergence and moisture transport among India (IND), Equatorial Indian Ocean (IOC) and tropical western pacific (WNP) is also important in modifying the wet or dry cycles over India. The mutual interaction among IOC, WNP and IND in seasonal timescales is significant in modifying wet and dry cycles over the Indian region and the seasonal anomalies.

Diagnostics of Rainfall Anomalies in the Nordeste During the Global Weather Experiment

Science.gov (United States)

Sikdar, D. M.

1984-01-01

The relationship of the daily variability of large-scale pressure, cloudiness and upper level wind patterns over the Brazil-Atlantic sector during March/April 1979 to rainfall anomalies in northern Nordeste was investigated. The experiment divides the rainy season (March/April) of 1979 into wet and dry days, then composites bright cloudiness, sea level pressure, and upper level wind fields with respect to persistent rainfall episodes. Wet and dry anomalies are analyzed along with seasonal mean conditions.

Estimation of Rainfall Erosivity via 1-Minute to Hourly Rainfall Data from Taipei, Taiwan

Science.gov (United States)

Huang, Ting-Yin; Yang, Ssu-Yao; Jan, Chyan-Deng

2017-04-01

Soil erosion is a natural process on hillslopes that threats people's life and properties, having a considerable environmental and economic implications for soil degradation, agricultural activity and water quality. The rainfall erosivity factor (R-factor) in the Universal Soil Loss Equation (USLE), composed of total kinetic energy (E) and the maximum 30-min rainfall intensity (I30), is widely used as an indicator to measure the potential risks of soil loss caused by rainfall at a regional scale. This R factor can represent the detachment and entrainment involved in climate conditions on hillslopes, but lack of 30-min rainfall intensity data usually lead to apply this factor more difficult in many regions. In recent years, fixed-interval, hourly rainfall data is readily available and widely used due to the development of automatic weather stations. Here we assess the estimations of R, E, and I30 based on 1-, 5-, 10-, 15-, 30-, 60-minute rainfall data, and hourly rainfall data obtained from Taipei weather station during 2004 to 2010. Results show that there is a strong correlation among R-factors estimated from different interval rainfall data. Moreover, the shorter time-interval rainfall data (e.g., 1-min) yields larger value of R-factor. The conversion factors of rainfall erosivity (ratio of values estimated from the resolution lower than 30-min rainfall data to those estimated from 60-min and hourly rainfall data, respectively) range from 1.85 to 1.40 (resp. from 1.89 to 1.02) for 60-min (resp. hourly) rainfall data as the time resolution increasing from 30-min to 1-min. This paper provides useful information on estimating R-factor when hourly rainfall data is only available.

A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall

Science.gov (United States)

Lombardo, F.; Volpi, E.; Koutsoyiannis, D.; Serinaldi, F.

2017-06-01

Generating fine-scale time series of intermittent rainfall that are fully consistent with any given coarse-scale totals is a key and open issue in many hydrological problems. We propose a stationary disaggregation method that simulates rainfall time series with given dependence structure, wet/dry probability, and marginal distribution at a target finer (lower-level) time scale, preserving full consistency with variables at a parent coarser (higher-level) time scale. We account for the intermittent character of rainfall at fine time scales by merging a discrete stochastic representation of intermittency and a continuous one of rainfall depths. This approach yields a unique and parsimonious mathematical framework providing general analytical formulations of mean, variance, and autocorrelation function (ACF) for a mixed-type stochastic process in terms of mean, variance, and ACFs of both continuous and discrete components, respectively. To achieve the full consistency between variables at finer and coarser time scales in terms of marginal distribution and coarse-scale totals, the generated lower-level series are adjusted according to a procedure that does not affect the stochastic structure implied by the original model. To assess model performance, we study rainfall process as intermittent with both independent and dependent occurrences, where dependence is quantified by the probability that two consecutive time intervals are dry. In either case, we provide analytical formulations of main statistics of our mixed-type disaggregation model and show their clear accordance with Monte Carlo simulations. An application to rainfall time series from real world is shown as a proof of concept.

Predicting rainfall erosivity by momentum and kinetic energy in Mediterranean environment

Science.gov (United States)

Carollo, Francesco G.; Ferro, Vito; Serio, Maria A.

2018-05-01

Rainfall erosivity is an index that describes the power of rainfall to cause soil erosion and it is used around the world for assessing and predicting soil loss on agricultural lands. Erosivity can be represented in terms of both rainfall momentum and kinetic energy, both calculated per unit time and area. Contrasting results on the representativeness of these two variables are available: some authors stated that momentum and kinetic energy are practically interchangeable in soil loss estimation while other found that kinetic energy is the most suitable expression of rainfall erosivity. The direct and continuous measurements of momentum and kinetic energy by a disdrometer allow also to establish a relationship with rainfall intensity at the study site. At first in this paper a comparison between the momentum-rainfall intensity relationships measured at Palermo and El Teularet by an optical disdrometer is presented. For a fixed rainfall intensity the measurements showed that the rainfall momentum values measured at the two experimental sites are not coincident. However both datasets presented a threshold value of rainfall intensity over which the rainfall momentum assumes a quasi-constant value. Then the reliability of a theoretically deduced relationship, linking momentum, rainfall intensity and median volume diameter, is positively verified using measured raindrop size distributions. An analysis to assess which variable, momentum or kinetic energy per unit area and time, is the best predictor of erosivity in Italy and Spain was also carried out. This investigation highlighted that the rainfall kinetic energy per unit area and time can be substituted by rainfall momentum as index for estimating the rainfall erosivity, and this result does not depend on the site where precipitation occurs. Finally, rainfall intensity measurements and soil loss data collected from the bare plots equipped at Sparacia experimental area were used to verify the reliability of some

The all-year rainfall region of South Africa: Satellite rainfall-estimate perspective

CSIR Research Space (South Africa)

Engelbrecht, CJ

2012-09-01

Full Text Available Climate predictability and variability studies over South Africa typically focus on the summer rainfall region and to a lesser extent on the winter rainfall region. The all-year rainfall region of South Africa, a narrow strip located along the Cape...

Temperature and rainfall interact to control carbon cycling in tropical forests.

Science.gov (United States)

Taylor, Philip G; Cleveland, Cory C; Wieder, William R; Sullivan, Benjamin W; Doughty, Christopher E; Dobrowski, Solomon Z; Townsend, Alan R

2017-06-01

Tropical forests dominate global terrestrial carbon (C) exchange, and recent droughts in the Amazon Basin have contributed to short-term declines in terrestrial carbon dioxide uptake and storage. However, the effects of longer-term climate variability on tropical forest carbon dynamics are still not well understood. We synthesised field data from more than 150 tropical forest sites to explore how climate regulates tropical forest aboveground net primary productivity (ANPP) and organic matter decomposition, and combined those data with two existing databases to explore climate - C relationships globally. While previous analyses have focused on the effects of either temperature or rainfall on ANPP, our results highlight the importance of interactions between temperature and rainfall on the C cycle. In cool forests (forests (> 20 °C) it consistently enhanced both ANPP and decomposition. At the global scale, our analysis showed an increase in ANPP with rainfall in relatively warm sites, inconsistent with declines in ANPP with rainfall reported previously. Overall, our results alter our understanding of climate - C cycle relationships, with high precipitation accelerating rates of C exchange with the atmosphere in the most productive biome on earth. © 2017 John Wiley & Sons Ltd/CNRS.

Large rainfall changes consistently projected over substantial areas of tropical land

Science.gov (United States)

Chadwick, Robin; Good, Peter; Martin, Gill; Rowell, David P.

2016-02-01

Many tropical countries are exceptionally vulnerable to changes in rainfall patterns, with floods or droughts often severely affecting human life and health, food and water supplies, ecosystems and infrastructure. There is widespread disagreement among climate model projections of how and where rainfall will change over tropical land at the regional scales relevant to impacts, with different models predicting the position of current tropical wet and dry regions to shift in different ways. Here we show that despite uncertainty in the location of future rainfall shifts, climate models consistently project that large rainfall changes will occur for a considerable proportion of tropical land over the twenty-first century. The area of semi-arid land affected by large changes under a higher emissions scenario is likely to be greater than during even the most extreme regional wet or dry periods of the twentieth century, such as the Sahel drought of the late 1960s to 1990s. Substantial changes are projected to occur by mid-century--earlier than previously expected--and to intensify in line with global temperature rise. Therefore, current climate projections contain quantitative, decision-relevant information on future regional rainfall changes, particularly with regard to climate change mitigation policy.

Simulation of rainfall-runoff for major flash flood events in Karachi

Science.gov (United States)

Zafar, Sumaira

2016-07-01

Metropolitan city Karachi has strategic importance for Pakistan. With the each passing decade the city is facing urban sprawl and rapid population growth. These rapid changes directly affecting the natural resources of city including its drainage pattern. Karachi has three major cities Malir River with the catchment area of 2252 sqkm and Lyari River has catchment area about 470.4 sqkm. These are non-perennial rivers and active only during storms. Change of natural surfaces into hard pavement causing an increase in rainfall-runoff response. Curve Number is increased which is now causing flash floods in the urban locality of Karachi. There is only one gauge installed on the upstream of the river but there no record for the discharge. Only one gauge located at the upstream is not sufficient for discharge measurements. To simulate the maximum discharge of Malir River rainfall (1985 to 2014) data were collected from Pakistan meteorological department. Major rainfall events use to simulate the rainfall runoff. Maximum rainfall-runoff response was recorded in during 1994, 2007 and 2013. This runoff causes damages and inundation in floodplain areas of Karachi. These flash flooding events not only damage the property but also cause losses of lives

Rainfall is a risk factor for sporadic cases of Legionella pneumophila pneumonia.

Directory of Open Access Journals (Sweden)

Carolina Garcia-Vidal

Full Text Available It is not known whether rainfall increases the risk of sporadic cases of Legionella pneumonia. We sought to test this hypothesis in a prospective observational cohort study of non-immunosuppressed adults hospitalized for community-acquired pneumonia (1995-2011. Cases with Legionella pneumonia were compared with those with non-Legionella pneumonia. Using daily rainfall data obtained from the regional meteorological service we examined patterns of rainfall over the days prior to admission in each study group. Of 4168 patients, 231 (5.5% had Legionella pneumonia. The diagnosis was based on one or more of the following: sputum (41 cases, antigenuria (206 and serology (98. Daily rainfall average was 0.556 liters/m(2 in the Legionella pneumonia group vs. 0.328 liters/m(2 for non-Legionella pneumonia cases (p = 0.04. A ROC curve was plotted to compare the incidence of Legionella pneumonia and the weighted median rainfall. The cut-off point was 0.42 (AUC 0.54. Patients who were admitted to hospital with a prior weighted median rainfall higher than 0.42 were more likely to have Legionella pneumonia (OR 1.35; 95% CI 1.02-1.78; p = .03. Spearman Rho correlations revealed a relationship between Legionella pneumonia and rainfall average during each two-week reporting period (0.14; p = 0.003. No relationship was found between rainfall average and non-Legionella pneumonia cases (-0.06; p = 0.24. As a conclusion, rainfall is a significant risk factor for sporadic Legionella pneumonia. Physicians should carefully consider Legionella pneumonia when selecting diagnostic tests and antimicrobial therapy for patients presenting with CAP after periods of rainfall.

Effect Of Seasonal Rainfall And Other Environmental Changes, On ...

African Journals Online (AJOL)

Background: The last study on snail population density in relation to rainfall pattern in Kigungu canoe landing and recreational sites on Lake Victoria shore was earlier carried out about fifteen years ago. This study also reviewed the influence of other environmental factors on the snails\\' infection rate. Objective: To reassess ...

Numerical Study on Interdecadal Modulations of ENSO-related Spring Rainfall over South China by the Pacific Decadal Oscillation

Science.gov (United States)

MAO, J.; WU, X.

2017-12-01

The spatio-temporal variations of eastern China spring rainfall are identified via empirical orthogonal function (EOF) analysis of rain-gauge (gridded) precipitation datasets for the period 1958-2013 (1920-2013). The interannual variations of the first two leading EOF modes are linked with the El Niño-Southern Oscillation (ENSO), with this linkage being modulated by the Pacific Decadal Oscillation (PDO). The EOF1 mode, characterized by predominant rainfall anomalies from the Yangtze River to North China (YNC), is more likely associated with out-of-phase PDO-ENSO events [i.e., El Niño during cold PDO (EN_CPDO) and La Niña during warm PDO (LN_WPDO)]. The sea surface temperature anomaly (SSTA) distributions of EN_CPDO (LN_WPDO) events induce a significant anomalous anticyclone (cyclone) over the western North Pacific stretching northwards to the Korean Peninsula and southern Japan, resulting in anomalous southwesterlies (northeasterlies) prevailing over eastern China and above-normal (below-normal) rainfall over YNC. In contrast, EOF2 exhibits a dipole pattern with predominantly positive rainfall anomalies over southern China along with negative anomalies over YNC, which is more likely connected to in-phase PDO-ENSO events [i.e., El Niño during warm PDO (EN_WPDO) and La Niña during cold PDO (LN_CPDO)]. EN_WPDO (LN_CPDO) events force a southwest-northeast oriented dipole-like circulation pattern leading to significant anomalous southwesterlies (northeasterlies) and above-normal (below-normal) rainfall over southern China. Numerical experiments with the CAM5 model forced by the SSTA patterns of EN_WPDO and EN_CPDO events reproduce reasonably well the corresponding anomalous atmospheric circulation patterns and spring rainfall modes over eastern China, validating the related mechanisms.

Application of flood-intensity-duration curve, rainfall-intensity-duration curve and time of concentration to analyze the pattern of storms and their corresponding floods for the natural flood events

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Kim, Nam Won; Shin, Mun-Ju; Lee, Jeong Eun

2016-04-01

The analysis of storm effects on floods is essential step for designing hydraulic structure and flood plain. There are previous studies for analyzing the relationship between the storm patterns and peak flow, flood volume and durations for various sizes of the catchments, but they are not enough to analyze the natural storm effects on flood responses quantitatively. This study suggests a novel method of quantitative analysis using unique factors extracted from the time series of storms and floods to investigate the relationship between natural storms and their corresponding flood responses. We used a distributed rainfall-runoff model of Grid based Rainfall-runoff Model (GRM) to generate the simulated flow and areal rainfall for 50 catchments in Republic of Korea size from 5.6 km2 to 1584.2 km2, which are including overlapped dependent catchments and non-overlapped independent catchments. The parameters of the GRM model were calibrated to get the good model performances of Nash-Sutcliffe efficiency. Then Flood-Intensity-Duration Curve (FIDC) and Rainfall-Intensity-Duration Curve (RIDC) were generated by Flood-Duration-Frequency and Intensity-Duration-Frequency methods respectively using the time series of hydrographs and hyetographs. Time of concentration developed for the Korea catchments was used as a consistent measure to extract the unique factors from the FIDC and RIDC over the different size of catchments. These unique factors for the storms and floods were analyzed against the different size of catchments to investigate the natural storm effects on floods. This method can be easily used to get the intuition of the natural storm effects with various patterns on flood responses. Acknowledgement This research was supported by a grant (11-TI-C06) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

Science.gov (United States)

Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

2017-12-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic

Indian summer monsoon rainfall variability during 2014 and 2015 and associated Indo-Pacific upper ocean temperature patterns

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Kakatkar, Rashmi; Gnanaseelan, C.; Chowdary, J. S.; Parekh, Anant; Deepa, J. S.

2018-02-01

In this study, factors responsible for the deficit Indian Summer Monsoon (ISM) rainfall in 2014 and 2015 and the ability of Indian Institute of Tropical Meteorology-Global Ocean Data Assimilation System (IITM-GODAS) in representing the oceanic features are examined. IITM-GODAS has been used to provide initial conditions for seasonal forecast in India during 2014 and 2015. The years 2014 and 2015 witnessed deficit ISM rainfall but were evolved from two entirely different preconditions over Pacific. This raises concern over the present understanding of the role of Pacific Ocean on ISM variability. Analysis reveals that the mechanisms associated with the rainfall deficit over the Indian Subcontinent are different in the two years. It is found that remote forcing in summer of 2015 due to El Niño is mostly responsible for the deficit monsoon rainfall through changes in Walker circulation and large-scale subsidence. In the case of the summer of 2014, both local circulation with anomalous anticyclone over central India and intrusion of mid-latitude dry winds from north have contributed for the deficit rainfall. In addition to the above, Tropical Indian Ocean (TIO) sea surface temperature (SST) and remote forcing from Pacific Ocean also modulated the ISM rainfall. It is observed that Pacific SST warming has extended westward in 2014, making it a basin scale warming unlike the strong El Niño year 2015. The eastern equatorial Indian Ocean is anomalously warmer than west in summer of 2014, and vice versa in 2015. These differences in SST in both tropical Pacific and TIO have considerable impact on ISM rainfall in 2014 and 2015. The study reveals that initializing coupled forecast models with proper upper ocean temperature over the Indo-Pacific is therefore essential for improved model forecast. It is important to note that the IITM-GODAS which assimilates only array for real-time geostrophic oceanography (ARGO) temperature and salinity profiles could capture most of the

Trend analysis and forecast of precipitation, reference evapotranspiration and rainfall deficit in the Blackland Prairie of eastern Mississippi

Science.gov (United States)

Trend analysis and estimation of monthly and annual precipitation, reference evapotranspiration (ETo) and rainfall deficit are essential for water resources management and cropping system design. Rainfall, ETo, and water deficit patterns and trends in eastern Mississippi USA for a 120-year period (1...

EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS

Directory of Open Access Journals (Sweden)

A. Cilek

2016-06-01

Full Text Available The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA, a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

A Decadal Historical Satellite Data and Rainfall Trend Analysis (2001–2016 for Flood Hazard Mapping in Sri Lanka

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Niranga Alahacoon

2018-03-01

Full Text Available Critical information on a flood-affected area is needed in a short time frame to initiate rapid response operations and develop long-term flood management strategies. This study combined rainfall trend analysis using Asian Precipitation—Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE gridded rainfall data with flood maps derived from Synthetic Aperture Radar (SAR and multispectral satellite to arrive at holistic spatio-temporal patterns of floods in Sri Lanka. Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR data were used to map flood extents for emergency relief operations while eight-day Moderate Resolution Imaging Spectroradiometer (MODIS surface reflectance data for the time period from 2001 to 2016 were used to map long term flood-affected areas. The inundation maps produced for rapid response were published within three hours upon the availability of satellite imagery in web platforms, with the aim of supporting a wide range of stakeholders in emergency response and flood relief operations. The aggregated time series of flood extents mapped using MODIS data were used to develop a flood occurrence map (2001–2016 for Sri Lanka. Flood hotpots identified using both optical and synthetic aperture average of 325 km2 for the years 2006–2015 and exceptional flooding in 2016 with inundation extent of approximately 1400 km2. The time series rainfall data explains increasing trend in the extreme rainfall indices with similar observation derived from satellite imagery. The results demonstrate the feasibility of using multi-sensor flood mapping approaches, which will aid Disaster Management Center (DMC and other multi-lateral agencies involved in managing rapid response operations and preparing mitigation measures.

Rainfall interception and spatial variability of throughfall in spruce stand

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Dohnal Michal

2014-12-01

Full Text Available The interception was recognized as an important part of the catchment water balance in temperate climate. The mountainous forest ecosystem at experimental headwater catchment Liz has been subject of long-term monitoring. Unique dataset in terms of time resolution serves to determine canopy storage capacity and free throughfall. Spatial variability of throughfall was studied using one weighing and five tipping bucket rain gauges. The basic characteristics of forest affecting interception process were determined for the Norway spruce stand at the experimental area - the leaf area index was 5.66 - 6.00 m2 m-2, the basal area was 55.7 m2 ha-1, and the crown closure above individual rain gauges was between 19 and 95%. The total interception loss in both growing seasons analyzed was 34.5%. The mean value of the interception capacity determined was about 2 mm. Throughfall exhibited high variability from place to place and it was strongly affected by character of rainfall. On the other hand, spatial pattern of throughfall in average showed low variability.

Simulated sensitivity of African terrestrial ecosystem photosynthesis to rainfall frequency, intensity, and rainy season length

Science.gov (United States)

Guan, Kaiyu; Good, Stephen P.; Caylor, Kelly K.; Medvigy, David; Pan, Ming; Wood, Eric F.; Sato, Hisashi; Biasutti, Michela; Chen, Min; Ahlström, Anders; Xu, Xiangtao

2018-02-01

There is growing evidence of ongoing changes in the statistics of intra-seasonal rainfall variability over large parts of the world. Changes in annual total rainfall may arise from shifts, either singly or in a combination, of distinctive intra-seasonal characteristics -i.e. rainfall frequency, rainfall intensity, and rainfall seasonality. Understanding how various ecosystems respond to the changes in intra-seasonal rainfall characteristics is critical for predictions of future biome shifts and ecosystem services under climate change, especially for arid and semi-arid ecosystems. Here, we use an advanced dynamic vegetation model (SEIB-DGVM) coupled with a stochastic rainfall/weather simulator to answer the following question: how does the productivity of ecosystems respond to a given percentage change in the total seasonal rainfall that is realized by varying only one of the three rainfall characteristics (rainfall frequency, intensity, and rainy season length)? We conducted ensemble simulations for continental Africa for a realistic range of changes (-20% ~ +20%) in total rainfall amount. We find that the simulated ecosystem productivity (measured by gross primary production, GPP) shows distinctive responses to the intra-seasonal rainfall characteristics. Specifically, increase in rainfall frequency can lead to 28% more GPP increase than the same percentage increase in rainfall intensity; in tropical woodlands, GPP sensitivity to changes in rainy season length is ~4 times larger than to the same percentage changes in rainfall frequency or intensity. In contrast, shifts in the simulated biome distribution are much less sensitive to intra-seasonal rainfall characteristics than they are to total rainfall amount. Our results reveal three major distinctive productivity responses to seasonal rainfall variability—‘chronic water stress’, ‘acute water stress’ and ‘minimum water stress’ - which are respectively associated with three broad spatial patterns of

Identification of homogeneous regions for rainfall regional frequency analysis considering typhoon event in South Korea

Science.gov (United States)

Heo, J. H.; Ahn, H.; Kjeldsen, T. R.

2017-12-01

South Korea is prone to large, and often disastrous, rainfall events caused by a mixture of monsoon and typhoon rainfall phenomena. However, traditionally, regional frequency analysis models did not consider this mixture of phenomena when fitting probability distributions, potentially underestimating the risk posed by the more extreme typhoon events. Using long-term observed records of extreme rainfall from 56 sites combined with detailed information on the timing and spatial impact of past typhoons from the Korea Meteorological Administration (KMA), this study developed and tested a new mixture model for frequency analysis of two different phenomena; events occurring regularly every year (monsoon) and events only occurring in some years (typhoon). The available annual maximum 24 hour rainfall data were divided into two sub-samples corresponding to years where the annual maximum is from either (1) a typhoon event, or (2) a non-typhoon event. Then, three-parameter GEV distribution was fitted to each sub-sample along with a weighting parameter characterizing the proportion of historical events associated with typhoon events. Spatial patterns of model parameters were analyzed and showed that typhoon events are less commonly associated with annual maximum rainfall in the North-West part of the country (Seoul area), and more prevalent in the southern and eastern parts of the country, leading to the formation of two distinct typhoon regions: (1) North-West; and (2) Southern and Eastern. Using a leave-one-out procedure, a new regional frequency model was tested and compared to a more traditional index flood method. The results showed that the impact of typhoon on design events might previously have been underestimated in the Seoul area. This suggests that the use of the mixture model should be preferred where the typhoon phenomena is less frequent, and thus can have a significant effect on the rainfall-frequency curve. This research was supported by a grant(2017-MPSS31

Distributed modelling of shallow landslides triggered by intense rainfall

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G. B. Crosta

2003-01-01

Full Text Available Hazard assessment of shallow landslides represents an important aspect of land management in mountainous areas. Among all the methods proposed in the literature, physically based methods are the only ones that explicitly includes the dynamic factors that control landslide triggering (rainfall pattern, land-use. For this reason, they allow forecasting both the temporal and the spatial distribution of shallow landslides. Physically based methods for shallow landslides are based on the coupling of the infinite slope stability analysis with hydrological models. Three different grid-based distributed hydrological models are presented in this paper: a steady state model, a transient "piston-flow" wetting front model, and a transient diffusive model. A comparative test of these models was performed to simulate landslide occurred during a rainfall event (27–28 June 1997 that triggered hundreds of shallow landslides within Lecco province (central Southern Alps, Italy. In order to test the potential for a completely distributed model for rainfall-triggered landslides, radar detected rainfall intensity has been used. A new procedure for quantitative evaluation of distributed model performance is presented and used in this paper. The diffusive model results in the best model for the simulation of shallow landslide triggering after a rainfall event like the one that we have analysed. Finally, radar data available for the June 1997 event permitted greatly improving the simulation. In particular, radar data allowed to explain the non-uniform distribution of landslides within the study area.

Chemical and biological relationships relevant to the effect of acid rainfall on the soil-plant system

Science.gov (United States)

Marvin Nyborg

1976-01-01

This paper deals with problems of measuring acidity in rainfall and the interpretation of these measurements in terms of effects on the soil-plant system. Theoretical relationships of the carbon-dioxide-bicarbonate equalibria and its effect on rainfall acidity measurements are given. The relationship of a cation-anion balance model of acidity in rainfall to plant...

On the nature of rainfall in dry climate: Space-time patterns of convective rain cells over the Dead Sea region and their relations with synoptic state and flash flood generation

Science.gov (United States)

Belachsen, Idit; Marra, Francesco; Peleg, Nadav; Morin, Efrat

2017-04-01

Space-time patterns of rainfall are important climatic characteristics that influence runoff generation and flash flood magnitude. Their derivation requires high-resolution measurements to adequately represent the rainfall distribution, and is best provided by remote sensing tools. This need is further emphasized in dry climate regions, where rainfall is scarce and, often, local and highly variable. Our research is focused on understanding the nature of rainfall events in the dry Dead Sea region (Eastern Mediterranean) by identifying and characterizing the spatial structure and the dynamics of convective storm cores (known as rain cells). To do so, we take advantage of 25 years of corrected and gauge-adjusted weather radar data. A statistical analysis of convective rain-cells spatial and temporal characteristics was performed with respect to synoptic pattern, geographical location, and flash flood generation. Rain cells were extracted from radar data using a cell segmentation method and a tracking algorithm and were divided into rain events. A total of 10,500 rain cells, 2650 cell tracks and 424 rain events were elicited. Rain cell properties, such as mean areal and maximal rain intensity, area, life span, direction and speed, were derived. Rain events were clustered, according to several ERA-Interim atmospheric parameters, and associated with three main synoptic patterns: Cyprus Low, Low to the East of the study region and Active Red Sea Trough. The first two originate from the Mediterranean Sea, while the third is an extension of the African monsoon. On average, the convective rain cells in the region are 90 km2 in size, moving from West to East in 13 ms-1 and living 18 minutes. Several significant differences between rain cells of the various synoptic types were observed. In particular, Active Red Sea Trough rain cells are characterized by higher rain intensities and lower speeds, suggesting a higher flooding potential for small catchments. The north

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

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G. T. Ayehu

2018-04-01

Full Text Available Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor ground observations or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3 and the African Rainfall Climatology (ARC 2 products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD  =  0.99, 1.00 and measure of volumetric rainfall (VHI  =  1.00, 1.00, the highest correlation coefficients (r =  0.81, 0.88, better bias values (0.96, 0.96, and the lowest RMSE (28.45 mm dekad−1, 59.03 mm month−1 than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale, although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance

Long-term monitoring of Dzanga Bai forest elephants: forest clearing use patterns.

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Turkalo, Andrea K; Wrege, Peter H; Wittemyer, George

2013-01-01

Individual identification of the relatively cryptic forest elephant (Loxodonta cyclotis) at forest clearings currently provides the highest quality monitoring data on this ecologically important but increasingly threatened species. Here we present baseline data from the first 20 years of an individually based study of this species, conducted at the Dzanga Clearing, Central African Republic. A total of 3,128 elephants were identified over the 20-year study (1,244 adults; 675 females, 569 males). It took approximately four years for the majority of elephants visiting the clearing to be identified, but new elephants entered the clearing every year of the study. The study population was relatively stable, varying from 1,668 to 1,864 individuals (including juveniles and infants), with increasingly fewer males than females over time. The age-class distribution for females remained qualitatively unchanged between 1995 and 2010, while the proportion of adult males decreased from 20% to 10%, likely reflecting increased mortality. Visitation patterns by individuals were highly variable, with some elephants visiting monthly while others were ephemeral users with visits separated by multiple years. The number of individuals in the clearing at any time varied between 40 and 100 individuals, and there was little evidence of a seasonal pattern in this variation. The number of elephants entering the clearing together (defined here as a social group) averaged 1.49 (range 1-12) for males and 2.67 (range 1-14) for females. This collation of 20 years of intensive forest elephant monitoring provides the first detailed, long term look at the ecology of bai visitation for this species, offering insight to the ecological significance and motivation for bai use, social behavior, and threats to forest elephants. We discuss likely drivers (rainfall, compression, illegal killing, etc.) influencing bai visitation rates. This study provides the baseline for future demographic and behavioral

Deforestation and rainfall recycling in Brazil: Is decreased forest cover connectivity associated with decreased rainfall connectivity?

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Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2017-12-01

In the Brazilian rainforest-savanna transition zone, deforestation has the potential to significantly affect rainfall by disrupting rainfall recycling, the process by which regional evapotranspiration contributes to regional rainfall. Understanding rainfall recycling in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching, agriculture, hydropower generation, and drinking water management. Simulations in previous studies suggest complex, scale-dependent interactions between forest cover connectivity and rainfall. For example, the size and distribution of deforested patches has been found to affect rainfall quantity and spatial distribution. Here we take an empirical approach, using the spatial connectivity of rainfall as an indicator of rainfall recycling, to ask: as forest cover connectivity decreased from 1981 - 2015, how did the spatial connectivity of rainfall change in the Brazilian rainforest-savanna transition zone? We use satellite forest cover and rainfall data covering this period of intensive forest cover loss in the region (forest cover from the Hansen Global Forest Change dataset; rainfall from the Climate Hazards Infrared Precipitation with Stations dataset). Rainfall spatial connectivity is quantified using transfer entropy, a metric from information theory, and summarized using network statistics. Networks of connectivity are quantified for paired deforested and non-deforested regions before deforestation (1981-1995) and during/after deforestation (2001-2015). Analyses reveal a decline in spatial connectivity networks of rainfall following deforestation.

Effect of rainfall on the reliability of an infinite slope

OpenAIRE

Yuan, J.; Papaioannou, I.; Mok, C. M.; Straub, D.

2014-01-01

Rainfall is one of the most common factors triggering landslides, since infiltration of water into the soil has a significant impact on pore water pressure buildup that affects slope stability. In this study, the influence of the wetting front development on the reliability of an infinite slope is analyzed. The failure condition of the slope is expressed in terms of the factor of safety. Rainfall infiltration is simulated by a time-dependent model, based on the Green and Ampt assumptions. The...

Statistical downscaling of rainfall: a non-stationary and multi-resolution approach

Science.gov (United States)

Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir

2016-05-01

A novel downscaling technique is proposed in this study whereby the original rainfall and reanalysis variables are first decomposed by wavelet transforms and rainfall is modelled using the semi-parametric additive model formulation of Generalized Additive Model in Location, Scale and Shape (GAMLSS). The flexibility of the GAMLSS model makes it feasible as a framework for non-stationary modelling. Decomposition of a rainfall series into different components is useful to separate the scale-dependent properties of the rainfall as this varies both temporally and spatially. The study was conducted at the Onkaparinga river catchment in South Australia. The model was calibrated over the period 1960 to 1990 and validated over the period 1991 to 2010. The model reproduced the monthly variability and statistics of the observed rainfall well with Nash-Sutcliffe efficiency (NSE) values of 0.66 and 0.65 for the calibration and validation periods, respectively. It also reproduced well the seasonal rainfall over the calibration (NSE = 0.37) and validation (NSE = 0.69) periods for all seasons. The proposed model was better than the tradition modelling approach (application of GAMLSS to the original rainfall series without decomposition) at reproducing the time-frequency properties of the observed rainfall, and yet it still preserved the statistics produced by the traditional modelling approach. When downscaling models were developed with general circulation model (GCM) historical output datasets, the proposed wavelet-based downscaling model outperformed the traditional downscaling model in terms of reproducing monthly rainfall for both the calibration and validation periods.

Rainfall erosivity in the Fukushima Prefecture: implications for radiocesium mobilization and migration

Science.gov (United States)

Laceby, J. Patrick; Chartin, Caroline; Degan, Francesca; Onda, Yuichi; Evrard, Olivier; Cerdan, Olivier; Ayrault, Sophie

2015-04-01

The Fukushima Dai-ichi nuclear power plant (FDNPP) accident in March 2011 led to the fallout of predominantly radiocesium (137Cs and 134Cs) on soils of the Fukushima Prefecture. This radiocesium was primarily fixated to fine soil particles. Subsequently, rainfall and snow melt run-off events result in significant quantities of radiocesium being eroded and transported throughout the coastal catchments and ultimately exported to the Pacific Ocean. Erosion models, such as the Universal Soil Loss Equation (USLE), relate rainfall directly to soil erosion in that an increase in rainfall one month will directly result in a proportional increase in sediment generation. Understanding the rainfall regime of the region is therefore fundamental to modelling and predicting long-term radiocesium export. Here, we analyze rainfall data for ~40 stations within a 100 km radius of the FDNPP. First we present general information on the rainfall regime in the region based on monthly and annual rainfall totals. Second we present general information on rainfall erosivity, the R-factor of the USLE equation and its relationship to the general rainfall data. Third we examine rainfall trends over the last 100 years at several of the rainfall stations to understand temporal trends and whether ~20 years of data is sufficient to calculate the R-factor for USLE models. Fourth we present monthly R-factor maps for the Fukushima coastal catchments impacted by the FDNPP accident. The variability of the rainfall in the region, particularly during the typhoon season, is likely resulting in a similar variability in the transfer and migration of radiocesium throughout the coastal catchments of the Fukushima Prefecture. Characterizing the region's rainfall variability is fundamental to modelling sediment and the concomitant radiocesium migration and transfer throughout these catchments and ultimately to the Pacific Ocean.

Tea shoot production in relation to rainfall, solar radiation, and temperature in Pagilaran tea estate, Batang

International Nuclear Information System (INIS)

Yudono, P.

2000-01-01

Tea shoot production pattern in PT Pagilaran tea estate, Batang, is studied in relation to rainfall, solar radiation, and temperature. Pagilaran tea estate is located at 700-1,500 m above the sea level, with temperature of 15-30 deg. C and rainfall ranging from 4,500 mm to 7,000 mm per year. However, the area is also characterized by two up to three dry months for every three years. Monthly data of rainfall, solar radiation, and temperature were collected and were related to tea shoot production using correlation and regression analysis. The results indicated that there was no significant different pattern of tea shoot production form the three estate units (Kayulandak, Pagilaran, and Andongsili). Monthly shoots production increases during October up to December, and then goes down in January up to February. It fluctuated at a lesser degree in the upper units (Kayulandak and Andongsili) which might be attributed to better soil moisture available in the area. They are right below a forests area which understandably serves as rainfall catchment area and maintains soil moisture of the area below in a better condition. Weak to moderate correlation was obtained when monthly tea shoot production was correlated to amount of rainfall (r = -0.3771), days of rainfall (r = -0.3512), maximum temperature (r = -0.3502), minimum temperature (r = -0.2786), and solar radiation (r=0.6607) of the same month. On regressing monthly tea shoot production to those variables, rainfall and duration of solar radiation turned out to be the two significant factors through the following equation y = 759.5616-0.1802 xi-1 + 0.1057 xi-2 + 0.5239 zi-1 (R at the power of 2 = 0.3398), where y = tea shoots production, x=amount of monthly rainfall, z=duration of solar radiation, and i refer to month [in

Modeling rainfall-runoff process using soft computing techniques

Science.gov (United States)

Kisi, Ozgur; Shiri, Jalal; Tombul, Mustafa

2013-02-01

Rainfall-runoff process was modeled for a small catchment in Turkey, using 4 years (1987-1991) of measurements of independent variables of rainfall and runoff values. The models used in the study were Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP) which are Artificial Intelligence (AI) approaches. The applied models were trained and tested using various combinations of the independent variables. The goodness of fit for the model was evaluated in terms of the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and scatter index (SI). A comparison was also made between these models and traditional Multi Linear Regression (MLR) model. The study provides evidence that GEP (with RMSE=17.82 l/s, MAE=6.61 l/s, CE=0.72 and R2=0.978) is capable of modeling rainfall-runoff process and is a viable alternative to other applied artificial intelligence and MLR time-series methods.

Rainfall Intensity and Frequency Explain Production Basis Risk in Cumulative Rain Index Insurance

Science.gov (United States)

Muneepeerakul, Chitsomanus P.; Muneepeerakul, Rachata; Huffaker, Ray G.

2017-12-01

With minimal moral hazard and adverse selection, weather index insurance promises financial resilience to farmers struck by harsh weather conditions through swift compensation at affordable premium. Despite these advantages, the very nature of indexing gives rise to production basis risk as the selected weather indexes do not sufficiently correspond to actual damages. To address this problem, we develop a stochastic yield model, built upon a stochastic soil moisture model driven by marked Poisson rainfall. Our analysis shows that even under similar temperature and rainfall amount yields can differ significantly; this was empirically supported by a 2-year field experiment in which rain-fed maize was grown under very similar total rainfall. Here, the year with more intense, less-frequent rainfall produces a better yield—a rare counter evidence to most climate change projections. Through a stochastic yield model, we demonstrate the crucial roles of rainfall intensity and frequency in determining the yield. Importantly, the model allows us to compute rainfall pattern-related basis risk inherent in cumulative rain index insurance. The model results and a case study herein clearly show that total rainfall is a poor indicator of yield, imposing unnecessary production basis risk on farmers and false-positive payouts on insurers. Incorporating rainfall intensity and frequency in the design of rain index insurance can offer farmers better protection, while maintaining the attractive features of the weather index insurance and thus fulfilling its promise of financial resilience.

Spatio-temporal modelling of rainfall in the Murray-Darling Basin

Science.gov (United States)

Nowak, Gen; Welsh, A. H.; O'Neill, T. J.; Feng, Lingbing

2018-02-01

The Murray-Darling Basin (MDB) is a large geographical region in southeastern Australia that contains many rivers and creeks, including Australia's three longest rivers, the Murray, the Murrumbidgee and the Darling. Understanding rainfall patterns in the MDB is very important due to the significant impact major events such as droughts and floods have on agricultural and resource productivity. We propose a model for modelling a set of monthly rainfall data obtained from stations in the MDB and for producing predictions in both the spatial and temporal dimensions. The model is a hierarchical spatio-temporal model fitted to geographical data that utilises both deterministic and data-derived components. Specifically, rainfall data at a given location are modelled as a linear combination of these deterministic and data-derived components. A key advantage of the model is that it is fitted in a step-by-step fashion, enabling appropriate empirical choices to be made at each step.

Climate-change driven increase in high intensity rainfall events: Analysis of development in the last decades and towards an extrapolation of future progression

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Müller, Eva; Pfister, Angela; Gerd, Büger; Maik, Heistermann; Bronstert, Axel

2015-04-01

Hydrological extreme events can be triggered by rainfall on different spatiotemporal scales: river floods are typically caused by event durations of between hours and days, while urban flash floods as well as soil erosion or contaminant transport rather result from storms events of very short duration (minutes). Still, the analysis of climate change impacts on rainfall-induced extreme events is usually carried out using daily precipitation data at best. Trend analyses of extreme rainfall at sub-daily or even sub-hourly time scales are rare. In this contribution two lines of research are combined: first, we analyse sub-hourly rainfall data for several decades in three European regions.Second, we investigate the scaling behaviour of heavy short-term precipitation with temperature, i.e. the dependence of high intensity rainfall on the atmospheric temperature at that particular time and location. The trend analysis of high-resolution rainfall data shows for the first time that the frequency of short and intensive storm events in the temperate lowland regions in Germany has increased by up to 0.5 events per year over the last decades. I.e. this trend suggests that the occurrence of these types of storms have multiplied over only a few decades. Parallel to the changes in the rainfall regime, increases in the annual and seasonal average temperature and changes in the occurrence of circulation patterns responsible for the generation of high-intensity storms have been found. The analysis of temporally highly resolved rainfall records from three European regions further indicates that extreme precipitation events are more intense with warmer temperatures during the rainfall event. These observations follow partly the Clausius-Clapeyron relation. Based on this relation one may derive a general rule of maximum rainfall intensity associated to the event temperature, roughly following the Clausius-Clapeyron (CC) relation. This rule might be used for scenarios of future maximum

Stochastic bias-correction of daily rainfall scenarios for hydrological applications

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I. Portoghese

2011-09-01

Full Text Available The accuracy of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes. In fact, the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows and groundwater recharge.

In this study, a comparison between statistical properties of rainfall observations and model control simulations from a Regional Climate Model (RCM was performed through a robust and meaningful representation of the precipitation process. The output of the adopted RCM was analysed and re-scaled exploiting the structure of a stochastic model of the point rainfall process. In particular, the stochastic model is able to adequately reproduce the rainfall intermittency at the synoptic scale, which is one of the crucial aspects for the Mediterranean environments. Possible alteration in the local rainfall regime was investigated by means of the historical daily time-series from a dense rain-gauge network, which were also used for the analysis of the RCM bias in terms of dry and wet periods and storm intensity. The result is a stochastic scheme for bias-correction at the RCM-cell scale, which produces a realistic representation of the daily rainfall intermittency and precipitation depths, though a residual bias in the storm intensity of longer storm events persists.

Downscaling of rainfall in Peru using Generalised Linear Models

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Bergin, E.; Buytaert, W.; Onof, C.; Wheater, H.

2012-04-01

The assessment of water resources in the Peruvian Andes is particularly important because the Peruvian economy relies heavily on agriculture. Much of the agricultural land is situated near to the coast and relies on large quantities of water for irrigation. The simulation of synthetic rainfall series is thus important to evaluate the reliability of water supplies for current and future scenarios of climate change. In addition to water resources concerns, there is also a need to understand extreme heavy rainfall events, as there was significant flooding in Machu Picchu in 2010. The region exhibits a reduction of rainfall in 1983, associated with El Nino Southern Oscillation (SOI). NCEP Reanalysis 1 data was used to provide weather variable data. Correlations were calculated for several weather variables using raingauge data in the Andes. These were used to evaluate teleconnections and provide suggested covariates for the downscaling model. External covariates used in the model include sea level pressure and sea surface temperature over the region of the Humboldt Current. Relative humidity and temperature data over the region are also included. The SOI teleconnection is also used. Covariates are standardised using observations for 1960-1990. The GlimClim downscaling model was used to fit a stochastic daily rainfall model to 13 sites in the Peruvian Andes. Results indicate that the model is able to reproduce rainfall statistics well, despite the large area used. Although the correlation between individual rain gauges is generally quite low, all sites are affected by similar weather patterns. This is an assumption of the GlimClim downscaling model. Climate change scenarios are considered using several GCM outputs for the A1B scenario. GCM data was corrected for bias using 1960-1990 outputs from the 20C3M scenario. Rainfall statistics for current and future scenarios are compared. The region shows an overall decrease in mean rainfall but with an increase in variance.

Comparison and Evolution of Extreme Rainfall-Induced Landslides in Taiwan

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Chunhung WU

2017-11-01

Full Text Available This study analyzed the characteristics of, and locations prone to, extreme rainfall-induced landslides in three watersheds in Taiwan, as well as the long-term evolution of landslides in the Laonong River watershed (LRW, based on multiannual landslide inventories during 2003–2014. Extreme rainfall-induced landslides were centralized beside sinuous or meandering reaches, especially those with large sediment deposition. Landslide-prone strata during extreme rainfall events were sandstone and siltstone. Large-scale landslides were likely to occur when the maximum 6-h accumulated rainfall exceeded 420 mm. All of the large-scale landslides induced by short-duration and high-intensity rainfall developed from historical small-scale landslides beside the sinuous or meandering reaches or in the source area of rivers. However, most of the large-scale landslides induced by long-duration and high-intensity rainfall were new but were still located beside sinuous or meandering reaches or near the source. The frequency density of landslides under long-duration and high-intensity rainfall was larger by one order than those under short-duration rainfall, and the β values in the landslide frequency density-area analysis ranged from 1.22 to 1.348. The number of downslope landslides was three times larger than those of midslope and upslope landslides. The extreme rainfall-induced landslides occurred in the erosion gullies upstream of the watersheds, whereas those beside rivers were downstream. Analysis of the long-term evolution of landslides in the LRW showed that the geological setting, sinuousness of reaches, and sediment yield volume determined their location and evolution. Small-scale landslides constituted 71.9–96.2% of the total cases from 2003 to 2014, and were more easily induced after Typhoon Morakot (2009. The frequency density of landslides after Morakot was greater by one order than before, with 61% to 68% of total landslides located in the

Changing On Diurnal Cycle Of Rainfall In Northern Coastal Of West Java

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Yulihastin, E.; Hadi, T. W.; Ningsih, N. S.

2017-12-01

The floods event in the north of Java was largely due to persistent of rainfall that occurred in the morning which indicated of deviation of diurnal pattern of rainfall. The shift of the phase of diurnal rainfall cycle using TRMM satellite hourly data of 3B41RT on the rainy period of 2000-2016 exhibits over land from Late Afternoon-Early Midnight (LA-EM) to morning. The peak of the cycle changes from diurnal to semidiurnal with a peak occurring in LA-EM and morning. Location of rainfall which usually occurs in the oceans shifted into near coastal area. The classification of diurnal rainfall cycles based on composite analysis shows four types: Normal (N) Type (45.6%) with one peak rainfall occurring in the afternoon until night, Diurnal (D) Type (26%) with one peak and phase opposite to normal type, Semidiurnal (SD) Type (6.5 %) with two peaks and the main peak occurring in the afternoon until night, Third Diurnal (TD) Type (21.7%) with three peaks and the main peak occurs in the morning. The classification was confirmed using the objective method of Empirical Mode Decomposition (EMD) and obtained three IMFs representing three diurnal cycle modes of Type TD (67.8%) with the main rain peak taking place in the afternoon, Type D with rain peak occurring in the early hours (18.9%), and SD type (9.9%) with the first peak occurred in the afternoon. For D Type, the results also prove that the diurnal cycle with significant deviations in amplitude occurred in February 2002, 2004, 2008, 2014, wich is the maximum rainfall occurs in the EM. It also seems that in those years, rainfall intensity is concentrated on the northern coast of West Java while in the Java Sea rainfall was minimum.

Analysis and Modeling of Time-Correlated Characteristics of Rainfall-Runoff Similarity in the Upstream Red River Basin

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Xiuli Sang

2012-01-01

Full Text Available We constructed a similarity model (based on Euclidean distance between rainfall and runoff to study time-correlated characteristics of rainfall-runoff similar patterns in the upstream Red River Basin and presented a detailed evaluation of the time correlation of rainfall-runoff similarity. The rainfall-runoff similarity was used to determine the optimum similarity. The results showed that a time-correlated model was found to be capable of predicting the rainfall-runoff similarity in the upstream Red River Basin in a satisfactory way. Both noised and denoised time series by thresholding the wavelet coefficients were applied to verify the accuracy of model. And the corresponding optimum similar sets obtained as the equation solution conditions showed an interesting and stable trend. On the whole, the annual mean similarity presented a gradually rising trend, for quantitatively estimating comprehensive influence of climate change and of human activities on rainfall-runoff similarity.

Daily rainfall forecasting for one year in a single run using Singular Spectrum Analysis

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Unnikrishnan, Poornima; Jothiprakash, V.

2018-06-01

Effective modelling and prediction of smaller time step rainfall is reported to be very difficult owing to its highly erratic nature. Accurate forecast of daily rainfall for longer duration (multi time step) may be exceptionally helpful in the efficient planning and management of water resources systems. Identification of inherent patterns in a rainfall time series is also important for an effective water resources planning and management system. In the present study, Singular Spectrum Analysis (SSA) is utilized to forecast the daily rainfall time series pertaining to Koyna watershed in Maharashtra, India, for 365 days after extracting various components of the rainfall time series such as trend, periodic component, noise and cyclic component. In order to forecast the time series for longer time step (365 days-one window length), the signal and noise components of the time series are forecasted separately and then added together. The results of the study show that the method of SSA could extract the various components of the time series effectively and could also forecast the daily rainfall time series for longer duration such as one year in a single run with reasonable accuracy.

Regionalization of the Modified Bartlett-Lewis Rectangular Pulse Stochastic Rainfall Model

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Dongkyun Kim

2013-01-01

Full Text Available Parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP stochastic rainfall simulation model were regionalized across the contiguous United States. Three thousand four hundred forty-four National Climate Data Center (NCDC rain gauges were used to obtain spatial and seasonal patterns of the model parameters. The MBLRP model was calibrated to minimize the discrepancy between the precipitation depth statistics between the observed and MBLRP-generated precipitation time series. These statistics included the mean, variance, probability of zero rainfall and autocorrelation at 1-, 3-, 12- and 24-hour accumulation intervals. The Ordinary Kriging interpolation technique was used to generate maps of the six MBLRP model parameters for each of the 12 months of the year. All parameters had clear to discernible regional tendencies; except for one related to rain cell duration distribution. Parameter seasonality was not obvious and it was more apparent in some locations than in others, depending on the seasonality of the rainfall statistics. Cross-validation was used to assess the validity of the parameter maps. The results indicate that the suggested maps reproduce well the observed rainfall statistics for different accumulation intervals, except for the lag-1 autocorrelation coefficient. The boundaries of the expected residual, with 95% confidence, between the observed rainfall statistics and the simulated rainfall statistics based on the map parameters were approximately ±0.064 mm hr-1, ±1.63 mm2 hr-2, ±0.16, and ±0.030 for the mean, variance, lag-1 autocorrelation and probability of zero rainfall at hourly accumulation levels, respectively. The estimated parameter values were also used to estimate the storm and rain cell characteristics.

Astronomically forced western African (21°N-20°S) rainfall variations during the Last Interglacial

Science.gov (United States)

Govin, Aline; Varma, Vidya; Prange, Matthias

2013-04-01

the decrease in June-July-August (JJA) insolation. Although modern JJA rainfall is very limited at 5-10°S, the contribution of JJA precipitation to the annual rainfall amount is enhanced during the LIG. Finally, the data indicate very limited rainfall changes at 20°S during the LIG. The model shows east-west contrasting rainfall patterns in Southern Africa (similarly to what is observed during the Holocene), which lead to negligible rainfall variations when averaged over the core catchment area. To conclude, long-term changes in western African precipitation respond to insolation variations during the LIG, except during its early part when persistent melting of northern ice sheets delayed the intensification of the NW African monsoon.

On the relative role of fire and rainfall in determining vegetation patterns in tropical savannas: a simulation study

Science.gov (United States)

Spessa, Allan; Fisher, Rosie

2010-05-01

LPJ-GUESS vegetation model. Recently, SPIFTIRE has been coupled to the Ecosystem Demography (ED) model, which simulates global vegetation dynamics as part of the new land surface scheme JULES (Joint UK Environment Simulator) within the QUEST Earth System Model (http://www.quest-esm.ac.uk/). This study forms part of on-going work to further improve and test the ability of JULES to accurately simulate the terrestrial carbon cycle and land-atmosphere exchanges under different climates. Using the JULES (ED-SPITFIRE) model driven by observed climate (1901-2002), and focusing on large-scale rainfall gradients in the tropical savannas of west Africa, the Northern Territory (Australia) and central-southern Brazil, this study assesses: i) simulated versus observed vegetation dynamics and distributions, and ii) the relative importance of fire versus rainfall in determining vegetation patterns. A sensitivity analysis approach was used.

Understanding Survival And Abundance Of Overwintering Warblers: Does Rainfall Matter?

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Katie M. Dugger; John G Faaborg; Wayne J. Arendt; Keith A. Hobson

2004-01-01

We investigated relationships between warbler abundance and survival rates measured on a Puerto Rican wintering site and rainfall patterns measured on the wintering site and in regions where these warblers breed, as estimated using stable-isotope analysis (δD) of feathers collected from wintering birds. We banded birds using constant-effort mist netting...

Analysis of rainfall preceding debris flows on the Smědavská hora Mt., Jizerské hory Mts., Czech Republic

Czech Academy of Sciences Publication Activity Database

Smolíková, J.; Blahůt, Jan; Vilímek, V.

2016-01-01

Roč. 13, č. 4 (2016), s. 683-696 ISSN 1612-510X Institutional support: RVO:67985891 Keywords : debris flow * rainfall pattern * rainfall thresholds * Jizerské hory Mts. * Czech Republic Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 3.657, year: 2016

Seasonality in cholera dynamics : a rainfall-driven model explains the wide range of patterns of an infectious disease in endemic areas

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Baracchini, Theo; Pascual, Mercedes; King, Aaron A.; Bouma, Menno J.; Bertuzzo, Enrico; Rinaldo, Andrea

2015-04-01

An explanation for the spatial variability of seasonal cholera patterns has remained an unresolved problem in tropical medicine te{pascual_2002}. Previous studies addressing the role of climate drivers in disease dynamics have focused on interannual variability and modelled seasonality as given te{king_nature}. Explanations for seasonality have relied on complex environmental interactions that vary with spatial location (involving regional hydrological models te{bertuzzo_2012}, river discharge, sea surface temperature, and plankton blooms). Thus, no simple and unified theory based on local climate variables has been formulated te{emch_2008}, leaving our understanding of seasonal variations of cholera outbreaks in different regions of the world incomplete. Through the analysis of a unique historical dataset containing 50 years of monthly meteorological, demographic and epidemiological records, we propose a mechanistic, SIR-based stochastic model for the population dynamics of cholera driven by local rainfall and temperature that is able to capture the full range of seasonal patterns in this large estuarine region, which encompasses the variety of patterns worldwide. Parameter inference was implemented via new statistical methods that allow the computation of maximum-likelihood estimates for partially observed Markov processes through sequential Monte-Carlo te{ionides_2011}. Such a model may provide a unprecedented opportunity to gain insights on the conditions and factors responsible for endemicity around the globe, and therefore, to also revise our understanding of the ecology of Vibrio cholerae. Results indicate that the hydrological regime is a decisive driver determining the seasonal dynamics of cholera. It was found that rainfall and longer water residence times tend to buffer the propagation of the disease in wet regions due to a dilution effect, while also enhancing cholera incidence in dry regions. This indicates that overall water levels matter and appear

Roles of tropical SST patterns during two types of ENSO in modulating wintertime rainfall over southern China

Science.gov (United States)

Xu, Kang; Huang, Qing-Lan; Tam, Chi-Yung; Wang, Weiqiang; Chen, Sheng; Zhu, Congwen

2018-03-01

The impacts of the eastern-Pacific (EP) and central-Pacific (CP) El Niño-Southern Oscillation (ENSO) on the southern China wintertime rainfall (SCWR) have been investigated. Results show that wintertime rainfall over most stations in southern China is enhanced (suppressed) during the EP (CP) El Niño, which are attributed to different atmospheric responses in the western North Pacific (WNP) and South China Sea (SCS) during two types of ENSO. When EP El Niño occurs, an anomalous low-level anticyclone is present over WNP/the Philippines region, resulting in stronger-than-normal southwesterlies over SCS. Such a wind branch acts to suppress East Asian winter monsoon (EAWM) and enhance moisture supply, implying surplus SCWR. During CP El Niño, however, anomalous sinking and low-level anticyclonic flow are found to cover a broad region in SCS. These circulation features are associated with moisture divergence over the northern part of SCS and suppressed SCWR. General circulation model experiments have also been conducted to study influence of various tropical sea surface temperature (SST) patterns on the EAWM atmospheric circulation. For EP El Niño, formation of anomalous low-level WNP anticyclone is jointly attributed to positive/negative SST anomalies (SSTA) over the central-to-eastern/ western equatorial Pacific. However, both positive and negative CP Niño-related-SSTA, located respectively over the central Pacific and WNP/SCS, offset each other and contribute a weak but broad-scale anticyclone centered at SCS. These results suggest that, besides the vital role of SST warming, SST cooling over SCS/WNP during two types of El Niño should be considered carefully for understanding the El Niño-EAWM relationship.

Eddy-induced salinity pattern in the North Pacific

Science.gov (United States)

Abe, H.; Ebuchi, N.; Ueno, H.; Ishiyama, H.; Matsumura, Y.

2017-12-01

This research examines spatio-temporal behavior of sea surface salinity (SSS) after intense rainfall events using observed data from Aquarius. Aquarius SSS in the North Pacific reveals one notable event in which SSS is locally freshened by intense rainfall. Although SSS pattern shortly after the rainfall reflects atmospheric pattern, its final form reflects ocean dynamic structure; an anticyclonic eddy. Since this anticyclonic eddy was located at SSS front created by precipitation, this eddy stirs the water in a clockwise direction. This eddy stirring was visible for several months. It is expected horizontal transport by mesoscale eddies would play significant role in determining upper ocean salinity structure.

The Soil Moisture Dependence of TRMM Microwave Imager Rainfall Estimates

Science.gov (United States)

Seyyedi, H.; Anagnostou, E. N.

2011-12-01

This study presents an in-depth analysis of the dependence of overland rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) on the soil moisture conditions at the land surface. TMI retrievals are verified against rainfall fields derived from a high resolution rain-gauge network (MESONET) covering Oklahoma. Soil moisture (SOM) patterns are extracted based on recorded data from 2000-2007 with 30 minutes temporal resolution. The area is divided into wet and dry regions based on normalized SOM (Nsom) values. Statistical comparison between two groups is conducted based on recorded ground station measurements and the corresponding passive microwave retrievals from TMI overpasses at the respective MESONET station location and time. The zero order error statistics show that the Probability of Detection (POD) for the wet regions (higher Nsom values) is higher than the dry regions. The Falls Alarm Ratio (FAR) and volumetric FAR is lower for the wet regions. The volumetric missed rain for the wet region is lower than dry region. Analysis of the MESONET-to-TMI ratio values shows that TMI tends to overestimate for surface rainfall intensities less than 12 (mm/h), however the magnitude of the overestimation over the wet regions is lower than the dry regions.

Applying Spatially Distributed Rainfall to a Hydrological Model in a Tropical Watershed, Manoa Watershed, in Hawaii

Science.gov (United States)

Huang, Y. F.; Tsang, Y. P.

2017-12-01

Rainfall in Hawaii is characterized with high spatial and temporal variability. In the south side of Oahu, the Manoa watershed, with an area of 11 km2, has the annual maximum rainfall of 3900mm and the minimum rainfall of 1000 mm. Despite this high spatial heterogeneity, the rain gage network seems insufficiently capture this pattern. When simulating stream flow and predicting floods with hydrological models in Hawaii, the model performance is often unsatisfactory because of inadequate representation of rainfall data. Longman et al. (in prep.) have developed the spatially distributed daily rainfall across the Hawaiian Islands by applying ordinary kriging, yet these data have not been applied to hydrological models. In this study, we used the Soil and Water Assessment Tool (SWAT) model to assess the streamflow simulation by applying spatially-distributed rainfall in the Manoa watershed. We first used point daily-rainfall at Lyon Arboretum from National Center of Environmental Information (NCEI) as the uniform rainfall input. Secondly, we summarized sub-watershed mean rainfall from the daily spatial-statistical rainfall. Both rainfall data are available from 1999 to 2014. The SWAT was set up for five-year warm-up, nine-year calibration, and two-year validation. The model parameters were calibrated and validated with four U.S. Geological Survey stream gages. We compared the calibrated watershed parameters, characteristics, and assess the streamflow hydrographs from these two rainfall inputs. The differences and improvement of using spatially distributed rainfall input in SWAT were discussed. In addition to improving the model by the representation of rainfall, this study helped us having a better understanding of the watershed hydrological response in Hawaii.

Responses of diatom communities to hydrological processes during rainfall events

Science.gov (United States)

Wu, Naicheng; Faber, Claas; Ulrich, Uta; Fohrer, Nicola

2015-04-01

The importance of diatoms as a tracer of hydrological processes has been recently recognized (Pfister et al. 2009, Pfister et al. 2011, Tauro et al. 2013). However, diatom variations in a short-term scale (e.g., sub-daily) during rainfall events have not been well documented yet. In this study, rainfall event-based diatom samples were taken at the outlet of the Kielstau catchment (50 km2), a lowland catchment in northern Germany. A total of nine rainfall events were caught from May 2013 to April 2014. Non-metric multidimensional scaling (NMDS) revealed that diatom communities of different events were well separated along NMDS axis I and II, indicating a remarkable temporal variation. By correlating water level (a proxy of discharge) and different diatom indices, close relationships were found. For example, species richness, biovolume (μm3), Shannon diversity and moisture index01 (%, classified according to van Dam et al. 1994) were positively related with water level at the beginning phase of the rainfall (i.e. increasing limb of discharge peak). However, in contrast, during the recession limb of the discharge peak, diatom indices showed distinct responses to water level declines in different rainfall events. These preliminary results indicate that diatom indices are highly related to hydrological processes. The next steps will include finding out the possible mechanisms of the above phenomena, and exploring the contributions of abiotic variables (e.g., hydrologic indices, nutrients) to diatom community patterns. Based on this and ongoing studies (Wu et al. unpublished data), we will incorporate diatom data into End Member Mixing Analysis (EMMA) and select the tracer set that is best suited for separation of different runoff components in our study catchment. Keywords: Diatoms, Rainfall event, Non-metric multidimensional scaling, Hydrological process, Indices References: Pfister L, McDonnell JJ, Wrede S, Hlúbiková D, Matgen P, Fenicia F, Ector L, Hoffmann L

Comparative Study of Monsoon Rainfall Variability over India and the Odisha State

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K C Gouda

2017-10-01

Full Text Available Indian summer monsoon (ISM plays an important role in the weather and climate system over India. The rainfall during monsoon season controls many sectors from agriculture, food, energy, and water, to the management of disasters. Being a coastal province on the eastern side of India, Odisha is one of the most important states affected by the monsoon rainfall and associated hydro-meteorological systems. The variability of monsoon rainfall is highly unpredictable at multiple scales both in space and time. In this study, the monsoon variability over the state of Odisha is studied using the daily gridded rainfall data from India Meteorological Department (IMD. A comparative analysis of the behaviour of monsoon rainfall at a larger scale (India, regional scale (Odisha, and sub-regional scale (zones of Odisha is carried out in terms of the seasonal cycle of monsoon rainfall and its interannual variability. It is seen that there is no synchronization in the seasonal monsoon category (normal/excess/deficit when analysed over large (India and regional (Odisha scales. The impact of El Niño, La Niña, and the Indian Ocean Dipole (IOD on the monsoon rainfall at both scales (large scale and regional scale is analysed and compared. The results show that the impact is much more for rainfall over India, but it has no such relation with the rainfall over Odisha. It is also observed that there is a positive (negative relation of the IOD with the seasonal monsoon rainfall variability over Odisha (India. The correlation between the IAV of monsoon rainfall between the large scale and regional scale was found to be 0.46 with a phase synchronization of 63%. IAV on a sub-regional scale is also presented.

Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

DEFF Research Database (Denmark)

Thorndahl, Søren; Korup Andersen, Aske; Larsen, Anders Badsberg

2017-01-01

Continuous and long rainfall series are a necessity in rural and urban hydrology for analysis and design purposes. Local historical point rainfall series often cover several decades, which makes it possible to estimate rainfall means at different timescales, and to assess return periods of extreme...... includes climate changes projected to a specific future period. This paper presents a framework for resampling of historical point rainfall series in order to generate synthetic rainfall series, which has the same statistical properties as an original series. Using a number of key target predictions...... for the future climate, such as winter and summer precipitation, and representation of extreme events, the resampled historical series are projected to represent rainfall properties in a future climate. Climate-projected rainfall series are simulated by brute force randomization of model parameters, which leads...

Soil Moisture and Turgidity of Selected Robusta Coffee Clones on Alluvial Plain with Seasonal Rainfall Pattern

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Rudy Erwiyono

2005-08-01

Full Text Available Observation on the seasonal variations of hydrological condition and turgidity of selected Robusta coffee clones has been carried out in Kaliwining Experimental Station, Indonesian Coffee and Cocoa Research Institute in Jember. The aim was to evaluate the effect of hydrological variation on the coffee plants and the degree of soil moisture effect on plant performance. Experimental site overlays on alluvial plain, + 45 m a.s.l., 8o 15’ South with D rainfall type. Observation was conducted by survey method at the experimental plots of organic fertilizer and nitogen treatments on selected Robusta coffee clones derived from rooted cuttings, i.e. BP 436, BP 42, BP 936 and BP 358. Observation was only conducted at the experimental blocks of organic matter trials of 20 l/tree/year at nitrogen (Urea application of locally recommanded rate during the subsequent years of 1999 to 2001. Parameters observed included plant turgidity and soil moisture content of three different depths, i.e. 0—20, 20—40 and 40—60 cm and the weather. Observation was carried out in five replicates designed as blocks of barn manure treatment and N-fertilizer of recommended rate as basal fertilizer. The results showed that meteorological condition and soil moisture of experimental site through the years have seasonal patterns following the seasonal pattern of rainfall. Compared to other meteorological characteristics, relative humidity dominantly determined evaporation and plant turgidity. Plant turgi-dity was not only determined by soil moisture condition, but also atmospheric demand. When relative humidity (RH was relatively high, plant turgidity was relatively stable although soil moisture of surface layers was very low, and the reversal when soil moisture content was high plant turgidity was controlled by atmospheric demand (relative humidity. With a 3—4 dry month period, relative turgidity of the coffee plants was relatively stable above 82%, except when soil

Rainfall Downscaling Conditional on Upper-air Atmospheric Predictors: Improved Assessment of Rainfall Statistics in a Changing Climate

Science.gov (United States)

Langousis, Andreas; Mamalakis, Antonis; Deidda, Roberto; Marrocu, Marino

2015-04-01

To improve the level skill of Global Climate Models (GCMs) and Regional Climate Models (RCMs) in reproducing the statistics of rainfall at a basin level and at hydrologically relevant temporal scales (e.g. daily), two types of statistical approaches have been suggested. One is the statistical correction of climate model rainfall outputs using historical series of precipitation. The other is the use of stochastic models of rainfall to conditionally simulate precipitation series, based on large-scale atmospheric predictors produced by climate models (e.g. geopotential height, relative vorticity, divergence, mean sea level pressure). The latter approach, usually referred to as statistical rainfall downscaling, aims at reproducing the statistical character of rainfall, while accounting for the effects of large-scale atmospheric circulation (and, therefore, climate forcing) on rainfall statistics. While promising, statistical rainfall downscaling has not attracted much attention in recent years, since the suggested approaches involved complex (i.e. subjective or computationally intense) identification procedures of the local weather, in addition to demonstrating limited success in reproducing several statistical features of rainfall, such as seasonal variations, the distributions of dry and wet spell lengths, the distribution of the mean rainfall intensity inside wet periods, and the distribution of rainfall extremes. In an effort to remedy those shortcomings, Langousis and Kaleris (2014) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables, which accurately reproduces the statistical character of rainfall at multiple time-scales. Here, we study the relative performance of: a) quantile-quantile (Q-Q) correction of climate model rainfall products, and b) the statistical downscaling scheme of Langousis and Kaleris (2014), in reproducing the statistical structure of rainfall, as well as rainfall extremes, at a

Erosividade e características hidrológicas das chuvas de Rio Grande (RS Erosivity and hydrological characteristics of rainfalls in Rio Grande (RS, Brazil

Directory of Open Access Journals (Sweden)

Marcos Gabriel Peñalva Bazzano

2010-02-01

coefficient were not significant. Regarding the total rainfalls studied, it was found that 32.6 % of the rainfalls and 99.3 % of the rain volume were erosive. From the total number of erosive rainfalls, 45.6 % had an advanced hydrologic pattern, 25.6 % an intermediary and 28.7 % a delayed pattern, while for the total volume of erosive rainfalls, 47.8 % had an advanced hydrologic pattern, 28.0 % an intermediary and 24.2 % a delayed pattern. In terms of annual erosivity, 49.1 % corresponded to rainfalls with an advanced, 28.9 % an intermediary and 22.1 % to a delayed pattern. The method of extreme distribution type I was adequate to obtain intensity-duration-frequency curves. Rainfall return periods can be calculated by the equations using the values of the parameters found, or by the graphs of intensity-duration-frequency.

Karst Aquifer in Qatar and its bearing on Natural Rainfall Recharge

Science.gov (United States)

Baalousha, Husam; Ackerer, Philippe

2017-04-01

Qatar is an arid country with little rainfall and high evaporation. Surface water is non-existent so aquifer is the only source of natural water. The annual long-term averages of rainfall and evaporation are 80 mm and more than 2000 mm, respectively. Despite the low rainfall and high evaporation, natural recharge from rainfall occurs at an average of approximately 50 million m3 per year. Rainfall recharge in Qatar takes in land depressions that occur all over the country. These depressions are a result of land collapse due to sinkholes and cavity in the limestone formation. In the northern part of the country, karst features occur as a result of dissolution of limestone, which leads to land depressions. Results of this study shows groundwater recharge occurs in land depression areas, especially in the northern part of the country, where surface runoff accumulates in these land depressions and recharges the aquifer. This paper was made possible by NPRP grant # [NPRP 9-030-1-008] from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the author[s]."

Climatological studies on precipitation features and large-scale atmospheric fields on the heavy rainfall days in the eastern part of Japan from the Baiu to midsummer season

Science.gov (United States)

Matsumoto, Kengo; Kato, Kuranoshin; Otani, Kazuo

2017-04-01

In East Asia the significant subtropical frontal zone called the Meiyu (in China) / Baiu (in Japan) appears in early summer (just before the midsummer) and the huge rainfall is brought due to the frequent appearance of the "heavy rainfall days" (referred to as HRDs hereafter) mainly in that western part. On the other hand, large-scale fields around the front in eastern Japan is rather different from that in western Japan but the total precipitation in the eastern Japan is still considerable compared to that in the other midlatitude regions. Thus, it is also interesting to examine how the rainfall characteristics and large-scale atmospheric fields on HRDs (with more than 50 mm/day) in the eastern Japan in the mature stage of the Baiu season (16 June 15 July), together with those in midsummer (1 31 August). Based on such scientific background, further analyses were performed in this study mainly with the daily and the hourly precipitation data and the NCEP/NCAR re-analysis date from 1971 to 2010, succeeding to our previous results (e.g., EGU2015). As reported at EGU2014 and 2015, about half of HRDs at Tokyo (eastern Japan) were related to the typhoon even in the Baiu season. Interestingly, half of HRDs were characterized by the large contribution of moderate rain less than 10 mm/h. While, the precipitation on HRDs at Tokyo in midsummer was mainly brought by the intense rainfall with more than 10 mm/h, in association with the typhoons. In the present study, we examined the composite meridional structure of the rainfall area along 140E. In the pattern only associated with a typhoons in the Baiu season (Pattern A), the heavy rainfall area (more than 50 mm/day) with large contribution of the intense rain (stronger than 10 mm/h) showed rather wide meridional extension. The area was characterized by the duration of the intermittent enhancement of the rainfall. In the pattern associated with a typhoon and a front (Pattern B), while the contribution ratio of the rainfall

Rainfall over the African continent from the 19th through the 21st century

Science.gov (United States)

Nicholson, Sharon E.; Funk, Chris; Fink, Andreas H.

2018-06-01

Most of the African continent is semi-arid and hence prone to extreme variations in rainfall from year to year. The extreme droughts that have plagued the Sahel and eastern Africa are particularly well known. This article uses a markedly expanded and updated rainfall data set to examine rainfall variability in 13 sectors that cover most of the continent. Annual rainfall is presented for each sector; the March-to-May and October-November seasons are also examined for equatorial sectors. In each case, the article includes the longest and most comprehensive precipitation gauge series ever published. All time series cover at least a century and most cover roughly one and one-half centuries or more. Although towards the end of the 20th century there was a widespread trend towards more arid conditions, few significant trends are evident over the entire period of record. The largest were downward trends in the Sahel and western sectors of North Africa. In those regions, an abrupt reduction in rainfall occurred around 1968, but a synchronous change occurred many other parts of Africa. A recovery did occur in the Sahel, but to varying degrees across the east-west expanse of the region. Noteworthy is that the west-to-east rainfall gradient across the region appears to have weakened in recent decades. For the continent as a whole, another change began in the 1980s decade, with more arid conditions persisting at the continental scale until early in the twenty-first century. No other such period of dry conditions occurred within the roughly one and one-half centuries evaluated here. A notable change also occurred at the seasonal level. During the period 1980 to 1998 rainfall during March-to-May was well below the long-term mean throughout most of the area from 20° N to 35° S. At the same time rainfall was above the long-term mean in most of eastern sectors within this latitude span, indicating a change in the seasonality of rainfall of a large part of Africa.

Remote sensing entropy to assess the sustainability of rainfall in tropical catchment

Science.gov (United States)

Mahmud, M. R.; Reba, M. N. M.; Wei, J. S.; Razak, N. H. Abdul

2018-02-01

This study demonstrated the utility of entropy computation using the satellite precipitation remote sensing data to assess the sustainability of rainfall in tropical catchments. There were two major issues need to be anticipated in monitoring the tropical catchments; first is the frequent monitoring of the rainfall and second is the appropriate indicator that sensitive to rainfall pattern changes or disorder. For the first issue, the use of satellite remote sensing precipitation data is suggested. Meanwhile for the second issue, the utilization of entropy concept in interpreting the disorder of temporal rainfall can be used to assess the sustain ability had been successfully adopted in some studies. Therefore, we hypothesized that the use of satellite precipitation as main data to compute entropy can be a novel tool in anticipating the above-mentioned conflict earlier. The remote sensing entropy results and in-situ river level showed good agreement indicating its reliability. 72% of the catchment has moderate to good rainfall supply during normal or non-drought condition. However, our result showed that the catchments were highly sensitive to drought especially in the west coast and southern part of the Peninsular Malaysia. High resiliency was identified in the east coast. We summarized that the proposed entropy-quantity scheme was a useful tool for cost-effective, quick, and operational sustainability assessment This study demonstrated the utility of entropy computation using the satellite precipitation remote sensing data to assess the sustainability of rainfall in tropical catchments.

Rainfall prediction with backpropagation method

Science.gov (United States)

Wahyuni, E. G.; Fauzan, L. M. F.; Abriyani, F.; Muchlis, N. F.; Ulfa, M.

2018-03-01

Rainfall is an important factor in many fields, such as aviation and agriculture. Although it has been assisted by technology but the accuracy can not reach 100% and there is still the possibility of error. Though current rainfall prediction information is needed in various fields, such as agriculture and aviation fields. In the field of agriculture, to obtain abundant and quality yields, farmers are very dependent on weather conditions, especially rainfall. Rainfall is one of the factors that affect the safety of aircraft. To overcome the problems above, then it’s required a system that can accurately predict rainfall. In predicting rainfall, artificial neural network modeling is applied in this research. The method used in modeling this artificial neural network is backpropagation method. Backpropagation methods can result in better performance in repetitive exercises. This means that the weight of the ANN interconnection can approach the weight it should be. Another advantage of this method is the ability in the learning process adaptively and multilayer owned on this method there is a process of weight changes so as to minimize error (fault tolerance). Therefore, this method can guarantee good system resilience and consistently work well. The network is designed using 4 input variables, namely air temperature, air humidity, wind speed, and sunshine duration and 3 output variables ie low rainfall, medium rainfall, and high rainfall. Based on the research that has been done, the network can be used properly, as evidenced by the results of the prediction of the system precipitation is the same as the results of manual calculations.

Rainfall and runoff water quality of the Pang and Lambourn, tributaries of the River Thames, south-eastern England

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C. Neal

2004-01-01

Full Text Available The water quality of rainfall and runoff is described for two catchments of two tributaries of the River Thames, the Pang and Lambourn. Rainfall chemistry is variable and concentrations of most determinands decrease with increasing volume of catch probably due to 'wash out' processes. Two rainfall sites have been monitored, one for each catchment. The rainfall site on the Lambourn shows higher chemical concentrations than the one for the Pang which probably reflects higher amounts of local inputs from agricultural activity. Rainfall quality data at a long-term rainfall site on the Pang (UK National Air Quality Archive shows chemistries similar to that for the Lambourn site, but with some clear differences. Rainfall chemistries show considerable variation on an event-to-event basis. Average water quality concentrations and flow-weighted concentrations as well as fluxes vary across the sites, typically by about 30%. Stream chemistry is much less variable due to the main source of water coming from aquifer sources of high storage. The relationship between rainfall and runoff chemistry at the catchment outlet is described in terms of the relative proportions of atmospheric and within-catchment sources. Remarkably, in view of the quantity of agricultural and sewage inputs to the streams, the catchments appear to be retaining both P and N. Keywords: water quality, nitrate, ammonium, phosphorus, ammonia, nitrogen dioxide, pH, alkalinity, nutrients, trace metals, rainfall, river, Pang, Lambourn, LOCAR

Radar rainfall image repair techniques

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Stephen M. Wesson

2004-01-01

Full Text Available There are various quality problems associated with radar rainfall data viewed in images that include ground clutter, beam blocking and anomalous propagation, to name a few. To obtain the best rainfall estimate possible, techniques for removing ground clutter (non-meteorological echoes that influence radar data quality on 2-D radar rainfall image data sets are presented here. These techniques concentrate on repairing the images in both a computationally fast and accurate manner, and are nearest neighbour techniques of two sub-types: Individual Target and Border Tracing. The contaminated data is estimated through Kriging, considered the optimal technique for the spatial interpolation of Gaussian data, where the 'screening effect' that occurs with the Kriging weighting distribution around target points is exploited to ensure computational efficiency. Matrix rank reduction techniques in combination with Singular Value Decomposition (SVD are also suggested for finding an efficient solution to the Kriging Equations which can cope with near singular systems. Rainfall estimation at ground level from radar rainfall volume scan data is of interest and importance in earth bound applications such as hydrology and agriculture. As an extension of the above, Ordinary Kriging is applied to three-dimensional radar rainfall data to estimate rainfall rate at ground level. Keywords: ground clutter, data infilling, Ordinary Kriging, nearest neighbours, Singular Value Decomposition, border tracing, computation time, ground level rainfall estimation

Forecasting and Analysis of Monthly Rainfalls in Ardabil Province by Arima, Autoregrressive, and Winters Models

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B. Salahi

2017-01-01

for climatologists to better explain and predict phenomena besides statistical models and pay more attention to general circulation models (GCM under different climate conditions. Conclusion: Results of rainfall investigation by order 2 Autoregrressive, Winters, and Arima models showed a descending trend in monthly rainfalls in the coming years across the study location. The results of modeling and analysis of monthly rainfalls in Ardabil synoptic station showed that among these models, Arima was better than the other two because it enjoyed the lowest MAPE and the highest R2. AIC, RMSE and MAD scales of different patterns were calculated and finally, SARIMA(1,1,1(2,0,112 pattern having the lowest AIC, RMSE and MAD was selected as the most appropriate pattern for monthly rainfall forecasting in Ardabil synoptic station.

Climate change and predicting soil loss from rainfall

Science.gov (United States)

Kinnell, Peter

2017-04-01

Conceptually, rainfall has a certain capacity to cause soil loss from an eroding area while soil surfaces have a certain resistance to being eroded by rainfall. The terms "rainfall erosivity' and "soil erodibility" are frequently used to encapsulate the concept and in the Revised Universal Soil Loss Equation (RUSLE), the most widely used soil loss prediction equation in the world, average annual values of the R "erosivity" factor and the K "erodibility" factor provide a basis for accounting for variation in rainfall erosion associated with geographic variations of climate and soils. In many applications of RUSLE, R and K are considered to be independent but in reality they are not. In RUSLE2, provision has been made to take account of the fact that K values determined using soil physical factors have to be adjusted for variations in climate because runoff is not directly included as a factor in determining R. Also, the USLE event erosivity index EI30 is better related to accounting for event sediment concentration than event soil loss. While the USLE-M, a modification of the USLE which includes runoff as a factor in determining the event erosivity index provides better estimates of event soil loss when event runoff is known, runoff prediction provides a challenge to modelling event soil loss as climate changes

Use of a large-scale rainfall simulator reveals novel insights into stemflow generation

Science.gov (United States)

Levia, D. F., Jr.; Iida, S. I.; Nanko, K.; Sun, X.; Shinohara, Y.; Sakai, N.

2017-12-01

Detailed knowledge of stemflow generation and its effects on both hydrological and biogoechemical cycling is important to achieve a holistic understanding of forest ecosystems. Field studies and a smaller set of experiments performed under laboratory conditions have increased our process-based knowledge of stemflow production. Building upon these earlier works, a large-scale rainfall simulator was employed to deepen our understanding of stemflow generation processes. The use of the large-scale rainfall simulator provides a unique opportunity to examine a range of rainfall intensities under constant conditions that are difficult under natural conditions due to the variable nature of rainfall intensities in the field. Stemflow generation and production was examined for three species- Cryptomeria japonica D. Don (Japanese cedar), Chamaecyparis obtusa (Siebold & Zucc.) Endl. (Japanese cypress), Zelkova serrata Thunb. (Japanese zelkova)- under both leafed and leafless conditions at several different rainfall intensities (15, 20, 30, 40, 50, and 100 mm h-1) using a large-scale rainfall simulator in National Research Institute for Earth Science and Disaster Resilience (Tsukuba, Japan). Stemflow production and rates and funneling ratios were examined in relation to both rainfall intensity and canopy structure. Preliminary results indicate a dynamic and complex response of the funneling ratios of individual trees to different rainfall intensities among the species examined. This is partly the result of different canopy structures, hydrophobicity of vegetative surfaces, and differential wet-up processes across species and rainfall intensities. This presentation delves into these differences and attempts to distill them into generalizable patterns, which can advance our theories of stemflow generation processes and ultimately permit better stewardship of forest resources. ________________ Funding note: This research was supported by JSPS Invitation Fellowship for Research in

The response of ungulates to rainfall along the riverbeds of the Southern Kalahari

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M. G. L Mills

1984-12-01

Full Text Available The responses of springbok Antidorcas marsupialis, gemsbok Oryx gazella, blue wildebeest Connochaetes taurinus and red hartebeest Alcelaphus buselaphus to rainfall along the riverbeds of the southern Kalahari are analysed. Springbok reacted most rapidly to rainfall along the riverbeds and, by browsing in dry times, maintained a fairly stable presence throughout the year, although the actual number present in any one year was dependent on annual rainfall. Gemsbok responded more slowly to rainfall and reached their highest numbers in years of high rainfall when the grasses were tall and mature, after which they rapidly departed from the riverbeds. Red hartebeest also reached their highest numbers during the rainy season, but departed slightly more slowly than gemsbok. In dry years, they too, failed to come into the riverbeds. Blue wildebeest in the vicinity of the riverbeds tended to be more sedentary than the other species. The presence of potable artificial water appeared to be more important for wildebeest than for the other species and, although rainfall was undoubtedly an important factor in regulating their numbers along the riverbeds, they depended to a greater extent on breeding success and mortality factors, than on emigration and immigration. The overall seasonal pattern of ungulate abundance along the riverbeds in the southern Kalahari was one of wet season concentrations and dry season dispersion.

Rainfall, El Niño, and reproduction of red-cockaded woodpeckers

Science.gov (United States)

Richard N. Conner; Daniel Saenz; Richard R. Schaefer; James R. McCormick; D. Craig Rudolph; D. Brent Burt

2005-01-01

This study examines the relationship between Red-cockaded Woodpecker (Picoides borealis Vieillot) reproduction and rainfall during May when group members are provisioning nestlings with food. Patterns of variation over a 4-year period of approximately 30 woodpecker groups suggested that the mean number of hatchling deaths was positively related to...

A space-time hybrid hourly rainfall model for derived flood frequency analysis

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U. Haberlandt

2008-12-01

Full Text Available For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series.

First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in

Rainfall erosivity map for Ghana

International Nuclear Information System (INIS)

Oduro Afriyie, K.

1995-10-01

Monthly rainfall data, spanning over a period of more than thirty years, were used to compute rainfall erosivity indices for various stations in Ghana, using the Fournier index, c, defined as p 2 /P, where p is the rainfall amount in the wettest month and P is the annual rainfall amount. Values of the rainfall erosivity indices ranged from 24.5 mm at Sunyani in the mid-portion of Ghana to 180.9 mm at Axim in the south western coastal portion. The indices were used to construct a rainfall erosivity map for the country. The map revealed that Ghana may be broadly divided into five major erosion risk zones. The middle sector of Ghana is generally in the low erosion risk zone; the northern sector is in the moderate to severe erosion risk zone, while the coastal sector is in the severe to extreme severe erosion risk zone. (author). 11 refs, 1 fig., 1 tab

Historical analysis of interannual rainfall variability and trends in southeastern Brazil based on observational and remotely sensed data

Science.gov (United States)

Vásquez P., Isela L.; de Araujo, Lígia Maria Nascimento; Molion, Luiz Carlos Baldicero; de Araujo Abdalad, Mariana; Moreira, Daniel Medeiros; Sanchez, Arturo; Barbosa, Humberto Alves; Rotunno Filho, Otto Corrêa

2018-02-01

The Brazilian Southeast is considered a humid region. It is also prone to landslides and floods, a result of significant increases in rainfall during spring and summer caused by the South Atlantic Convergence Zone (SACZ). Recently, however, the region has faced a striking rainfall shortage, raising serious concerns regarding water availability. The present work endeavored to explain the meteorological drought that has led to hydrological imbalance and water scarcity in the region. Hodrick-Prescott smoothing and wavelet transform techniques were applied to long-term hydrologic and sea surface temperature (SST)—based climate indices monthly time series data in an attempt to detect cycles and trends that could help explain rainfall patterns and define a framework for improving the predictability of extreme events in the region. Historical observational hydrologic datasets available include monthly precipitation amounts gauged since 1888 and 1940 and stream flow measured since the 1930s. The spatial representativeness of rain gauges was tested against gridded rainfall satellite estimates from 2000 to 2015. The analyses revealed variability in four time scale domains—infra-annual, interannual, quasi-decadal and inter-decadal or multi-decadal. The strongest oscillations periods revealed were: for precipitation—8 months, 2, 8 and 32 years; for Pacific SST in the Niño-3.4 region—6 months, 2, 8 and 35.6 years, for North Atlantic SST variability—6 months, 2, 8 and 32 years and for Pacific Decadal Oscillation (PDO) index—6.19 months, 2.04, 8.35 and 27.31 years. Other periodicities less prominent but still statistically significant were also highlighted.

Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

KAUST Repository

Srinivas, C. V.

2015-09-11

This study examines the ability of the Advanced Research WRF (ARW) regional model to simulate Indian summer monsoon (ISM) rainfall climatology in different climate zones during the monsoon onset phase in the decade 2000–2009. The initial and boundary conditions for ARW are provided from the NCEP/NCAR Reanalysis Project (NNRP) global reanalysis. Seasonal onset-phase rainfall is compared with corresponding values from 0.25° IMD (India Meteorological Department) rainfall and NNRP precipitation data over seven climate zones (perhumid, humid, dry/moist, subhumid, dry/moist, semiarid and arid) of India to see whether dynamical downscaling using a regional model yields advantages over just using large-scale model predictions. Results show that the model could simulate the onset phase in terms of progression and distribution of rainfall in most zones (except over the northeast) with good correlations and low error metrics. The observed mean onset dates and their variability over different zones are well reproduced by the regional model over most climate zones. It has been found that the ARW performed similarly to the reanalysis in most zones and improves the onset time by 1 to 3 days in zones 4 and 7, in which the NNRP shows a delayed onset compared to the actual IMD onset times. The variations in the onset-phase rainfall during the below-normal onset (June negative) and above-normal onset (June positive) phases are well simulated. The slight underestimation of onset-phase rainfall in the northeast zone could be due to failure in resolving the wide extent of topographic variations and the associated multiscale interactions in that zone. Spatial comparisons showed improvement of pentad rainfall in both space and quantity in ARW simulations over NNRP data, as evident from a wider eastward distribution of pentad rainfall over the Western Ghats, central and eastern India, as in IMD observations. While NNRP under-represented the high pentad rainfall over northeast, east and

Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

Directory of Open Access Journals (Sweden)

C. V. Srinivas

2015-09-01

Full Text Available This study examines the ability of the Advanced Research WRF (ARW regional model to simulate Indian summer monsoon (ISM rainfall climatology in different climate zones during the monsoon onset phase in the decade 2000–2009. The initial and boundary conditions for ARW are provided from the NCEP/NCAR Reanalysis Project (NNRP global reanalysis. Seasonal onset-phase rainfall is compared with corresponding values from 0.25° IMD (India Meteorological Department rainfall and NNRP precipitation data over seven climate zones (perhumid, humid, dry/moist, subhumid, dry/moist, semiarid and arid of India to see whether dynamical downscaling using a regional model yields advantages over just using large-scale model predictions. Results show that the model could simulate the onset phase in terms of progression and distribution of rainfall in most zones (except over the northeast with good correlations and low error metrics. The observed mean onset dates and their variability over different zones are well reproduced by the regional model over most climate zones. It has been found that the ARW performed similarly to the reanalysis in most zones and improves the onset time by 1 to 3 days in zones 4 and 7, in which the NNRP shows a delayed onset compared to the actual IMD onset times. The variations in the onset-phase rainfall during the below-normal onset (June negative and above-normal onset (June positive phases are well simulated. The slight underestimation of onset-phase rainfall in the northeast zone could be due to failure in resolving the wide extent of topographic variations and the associated multiscale interactions in that zone. Spatial comparisons showed improvement of pentad rainfall in both space and quantity in ARW simulations over NNRP data, as evident from a wider eastward distribution of pentad rainfall over the Western Ghats, central and eastern India, as in IMD observations. While NNRP under-represented the high pentad rainfall over

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

Science.gov (United States)

Pall, Pardeep; Patricola, Christina; Wehner, Michael; Stone, Dáithí; Paciorek, Christopher; Collins, William

2015-04-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods across the South Platte River basin impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling an 'event that was' for September 2013 and comparing it to a modelled 'event that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'event that was' simulations with the regional Weather Research and Forecasting (WRF) model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'event that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. Our model results suggests that, given an insignificant change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the probability of heavy rainfall occurring over the South Platte River basin in September 2013.

Rainfall Reliability Evaluation for Stability of Municipal Solid Waste Landfills on Slope

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Fu-Kuo Huang

2013-01-01

Full Text Available A method to assess the reliability for the stability of municipal solid waste (MSW landfills on slope due to rainfall infiltration is proposed. Parameter studies are first done to explore the influence of factors on the stability of MSW. These factors include rainfall intensity, duration, pattern, and the engineering properties of MSW. Then 100 different combinations of parameters are generated and associated stability analyses of MSW on slope are performed assuming that each parameter is uniform distributed around its reason ranges. In the following, the performance of the stability of MSW is interpreted by the artificial neural network (ANN trained and verified based on the aforementioned 100 analysis results. The reliability for the stability of MSW landfills on slope is then evaluated and explored for different rainfall parameters by the ANN model with first-order reliability method (FORM and Monte Carlo simulation (MCS.

Spatial dependence of extreme rainfall

Science.gov (United States)

Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri

2017-05-01

This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

Rainfall erosivity in Europe.

Science.gov (United States)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Klik, Andreas; Rousseva, Svetla; Tadić, Melita Perčec; Michaelides, Silas; Hrabalíková, Michaela; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Beguería, Santiago; Alewell, Christine

2015-04-01

Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60 min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30 min using linear regression functions. Precipitation time series ranged from a minimum of 5 years to a maximum of 40 years. The average time series per precipitation station is around 17.1 years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1 km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722 MJ mm ha(-1) h(-1) yr(-1), with the highest values (>1000 MJ mm ha(-1) h(-1) yr(-1)) in the Mediterranean and alpine regions and the lowest (<500 MJ mm ha(-1) h(-1) yr(-1)) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods

Long-term changes in soil erosion due to forest fires. A rainfall simulation approach in Eastern Spain

Science.gov (United States)

Cerdà, Artemi; Keesstra, Saskia; Pereira, Paulo; Matrix-Solera, Jorge; Giménez-Morera, Antonio; Úbeda, Xavier; Francos, Marcos; Alcañiz, Meritxell; Jordán, Antonio

2016-04-01

-437. DOI: 10.1071/WF05044 Cerdà, A., Jurgensen, M.F., Bodi, M.B. 2009. Effects of ants on water and soil losses from organically-managed citrus orchards in eastern Spain. Biologia, 64 (3), 527-531. DOI: 10.2478/s11756-009-0114-7 Dlapa P., Bodí M.B., Mataix-Solera J., Cerdà A., Doerr S.H. 2015. Organic matter and wettability characteristics of wildfire ash from Mediterranean conifer forests. Catena, 135, 369-376. DOI: 10.1016/j.catena.2014.06.018 Dlapa, P., Bodí, M.B., Mataix-Solera, J., Cerdà, A., Doerr, S.H. 2013. FT-IR spectroscopy reveals that ash water repellency is highly dependent on ash chemical composition. Catena, 108, 35-43. DOI: 10.1016/j.catena.2012.02.011 Gessesse B., Bewket W., Bräuning A. 2015. Model-Based Characterization and Monitoring of Runoff and Soil Erosion in Response to Land Use/land Cover Changes in the Modjo Watershed, Ethiopia. (2015) Land Degradation and Development, 26 (7), 711-724.. DOI: 10. 1002/ldr. 2276 Hedo J., Lucas-Borja M. E., Wic C., Andrés-Abellán M., De Las Heras J. 2015. Soil microbiological properties and enzymatic activities of long-term post-fire recovery in dry and semiarid Aleppo pine (Pinus halepensis M.) forest stands. Solid Earth, 6 (1), 243-252. DOI: 10. 5194/se-6-243-2015 Hedo de Santiago, J., Lucas-Borja, M.E., Wic-Baena, C., Andrés-Abellán, M., de las Heras, J. 2015. Effects of thinning and induced drought on microbiological soil properties and plant species diversity at dry and semiarid locations. Land Degradation and Development, DOI: 10.1002/ldr.2361 Iserloh, T., Ries, B.J., Cerdà, A., Echeverría, M.T., Fister, W., Geißler, C., Kuhn, N.J., León, F.J., Peters, P., Schindewolf, M., Schmidt, J., Scholten, T., Seeger, M. 2013. Comparative measurements with seven rainfall s simulators on uniform bare fallow land. Zeitschrift fur Geomorphologie, 57 (1 SUPPL. 1), 1-10. DOI: 10.1127/0372-8854/2012/S-00085 Jordán-López, A., Martínez-Zavala, L., Bellinfante, N. 2009. Impact of different parts of unpaved forest

Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

Science.gov (United States)

Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

2018-04-01

The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

Analysis and modelling of spatio-temporal properties of daily rainfall over the Danube basin

Science.gov (United States)

Serinaldi, F.; Kilsby, C. G.

2012-04-01

Central and Eastern Europe are prone to severe floods due to heavy rainfall that cause societal and economic damages, ranging from agriculture to water resources, from the insurance/reinsurance sector to the energy industry. To improve the flood risk analysis, a better characterisation and modelling of the rainfall patterns over this area, which involves the Danube river watershed, is strategically important. In this study, we analyse the spatio-temporal properties of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe through different lagged and non-lagged indices of associations that quantify both the overall dependence and extreme dependence of pairwise observations. We also show that these measures are linked to each other and can be written in a unique and coherent notation within the copula framework. Moreover, the lagged version of these measures allows exploring some important spatio-temporal properties of the rainfall fields. The exploratory analysis is complemented by the preliminary results of a spatio-temporal rainfall simulation performed via a compound model based upon the Generalized Additive Models for Location, Scale and Shape (GAMLSS) and meta-elliptical multivariate distributions.

Building rainfall thresholds for large-scales landslides by extracting occurrence time of landslides from seismic records

Science.gov (United States)

Yen, Hsin-Yi; Lin, Guan-Wei

2017-04-01

Understanding the rainfall condition which triggers mass moment on hillslope is the key to forecast rainfall-induced slope hazards, and the exact time of landslide occurrence is one of the basic information for rainfall statistics. In the study, we focused on large-scale landslides (LSLs) with disturbed area larger than 10 ha and conducted a string of studies including the recognition of landslide-induced ground motions and the analyses of different terms of rainfall thresholds. More than 10 heavy typhoons during the periods of 2005-2014 in Taiwan induced more than hundreds of LSLs and provided the opportunity to characterize the rainfall conditions which trigger LSLs. A total of 101 landslide-induced seismic signals were identified from the records of Taiwan seismic network. These signals exposed the occurrence time of landslide to assess rainfall conditions. Rainfall analyses showed that LSLs occurred when cumulative rainfall exceeded 500 mm. The results of rainfall-threshold analyses revealed that it is difficult to distinct LSLs from small-scale landslides (SSLs) by the I-D and R-D methods, but the I-R method can achieve the discrimination. Besides, an enhanced three-factor threshold considering deep water content was proposed as the rainfall threshold for LSLs.

Analysis of the sensitivity to rainfall spatio-temporal variability of an operational urban rainfall-runoff model in a multifractal framework

Science.gov (United States)

Gires, A.; Tchiguirinskaia, I.; Schertzer, D. J.; Lovejoy, S.

2011-12-01

-band radar data is used. This analysis highlights the interest of implementing X-band radars in urban areas. Indeed such radars provide the rainfall data at a hectometric resolution that would enable a better nowcasting and management of storm water. The multifractal properties of the simulated hydrographs were analysed with the help of simulated rainfall fields of resolution 111 m x 111 m x 1 min, lasting 4 hours, and corresponding to a 5 year return period event. On the whole, the discharge exhibits a good scaling behaviour over the range 4 h - 5 min. Both UM parameters tend to be greater for the discharge than for the rainfall. The notion of maximum probable singularity was used to clarify the consequences on the assessment of extremes. It appears that the urban drainage network basically reproduces the extremes, or only slightly damps them, at least in terms of multifractal statistics. The results were obtained with the financial support from the EU FP7 SMARTesT Project and the Chair "Hydrology for Resilient Cities" (sponsored by Veolia) of Ecole des Ponts ParisTech.

The influence of El Niño-Southern Oscillation on boreal winter rainfall over Peninsular Malaysia

Science.gov (United States)

Richard, Sandra; Walsh, Kevin J. E.

2017-09-01

Multi-scale interactions between El Niño-Southern Oscillation and the Boreal Winter Monsoon contribute to rainfall variations over Malaysia. Understanding the physical mechanisms that control these spatial variations in local rainfall is crucial for improving weather and climate prediction and related risk management. Analysis using station observations and European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim) reanalysis reveals a significant decrease in rainfall during El Niño (EL) and corresponding increase during La Niña particularly north of 2°N over Peninsular Malaysia (PM). It is noted that the southern tip of PM shows a small increase in rainfall during El Niño although not significant. Analysis of the diurnal cycle of rainfall and winds indicates that there are no significant changes in morning and evening rainfall over PM that could explain the north-south disparity. Thus, we suggest that the key factor which might explain the north-south rainfall disparity is the moisture flux convergence (MFC). During the December to January (DJF) period of EL years, except for the southern tip of PM, significant negative MFC causes drying as well as suppression of uplift over most areas. In addition, lower specific humidity combined with moisture flux divergence results in less moisture over PM. Thus, over the areas north of 2°N, less rainfall (less heavy rain days) with smaller diurnal rainfall amplitude explains the negative rainfall anomaly observed during DJF of EL. The same MFC argument might explain the dipolar pattern over other areas such as Borneo if further analysis is performed.

Along the Rainfall-Runoff Chain: From Scaling of Greatest Point Rainfall to Global Change Attribution

Science.gov (United States)

Fraedrich, K.

2014-12-01

Processes along the continental rainfall-runoff chain cover a wide range of time and space scales which are presented here combining observations (ranging from minutes to decades) and minimalist concepts. (i) Rainfall, which can be simulated by a censored first-order autoregressive process (vertical moisture fluxes), exhibits 1/f-spectra if presented as binary events (tropics), while extrema world wide increase with duration according to Jennings' scaling law. (ii) Runoff volatility (Yangtze) shows data collapse which, linked to an intra-annual 1/f-spectrum, is represented by a single function not unlike physical systems at criticality and the short and long return times of extremes are Weibull-distributed. Atmospheric and soil moisture variabilities are also discussed. (iii) Soil moisture (in a bucket), whose variability is interpreted by a biased coinflip Ansatz for rainfall events, adds an equation of state to energy and water flux balances comprising Budyko's frame work for quasi-stationary watershed analysis. Eco-hydrologic state space presentations in terms of surface flux ratios of energy excess (loss by sensible heat over supply by net radiation) versus water excess (loss by discharge over gain by precipitation) allow attributions of state change to external (or climate) and internal (or anthropogenic) causes. Including the vegetation-greenness index (NDVI) as an active tracer extends the eco-hydrologic state space analysis to supplement the common geographical presentations. Two examples demonstrate the approach combining ERA and MODIS data sets: (a) global geobotanic classification by combining first and second moments of the dryness ratio (net radiation over precipitation) and (b) regional attributions (Tibetan Plateau) of vegetation changes.

Rainfall Characteristic on the Slopes of Mount Merapi Region (Empirical Formula, Duration, Distribution, And Critical Line Woro River

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Pudak Juni Laksana

2015-05-01

Full Text Available Debris flow on the slopes of Mount Merapi area became a serious natural disasters because it has great destructive force and velocity. Rainfall with a certain intensity and duration is one component triggering debris flow. Rainfall has variability of the temporal and spatial characteristics influenced by various factors, such as topography and climate. Dharma (2012 suggested to define the characteristics of the intensity of rainfall using rainfall data with a shorter duration with statistical tests to establish the best empirical IDF formula.  This research was using of 30 minutes rainfall data for short duration (<3 hours and a spreadsheet software representing duration and distribution of the rainfall. The most appropriate rainfall intensity formula was done by the empirical IDF formula, i.e. Sherman, Kimijima, Hasper and Mononobe. Rainfall intensity analysis applied Frequency Analysis Software (based on Microsoft Excel. Debris flow occurrence was analyzed using MLIT for method A to establish standard rainfall index.  Sherman formula performed the best fit to the IDF characteristics of rainfall in the region of the slopes of Mount Merapi. Rainfall distribution pattern showed high intensity rainfall in the first hour and then decreased in the next hour which means distribution for the duration of 3 hours, 12%, 28%, 25%, 16%, 12%, and 7%, respectively with an interval of 30 minutes. Based on critical line, 5 mm of standard rainfall index was gained in the case of warning (R1 and 28 mm in the case of evacuation (R2.

Prediction of Rainfall-Induced Landslides

Science.gov (United States)

Nadim, F.; Sandersen, F.

2009-12-01

-mum intensity of rain within a short period of time (1-3 hours) during a storm is most critical for triggering of debris flows. Therefore empirical methods developed for prediction of initiation of debris flows include both long-duration and short-duration rain-fall. More recent research has focused on the spatial distribution of unstable areas and on better spatial resolution of the occurrence of landslide-triggering precipitation events. Spatial distribution can be assessed by analyzing the stability conditions for shallow landslides if reasonable estimates of strength parameters are available. In general, two different approaches may be adopted for the assessment of threshold values for rainfall-induced landslides: empirical methods that are based on past observations and statistical analyses, and numerical analyses that are based on geo-mechanical modelling. The former approach together with very short-term weather forecasting (now-casting) are commonly used in the design of early warning systems for debris flows.

Rainfall trends in the Brazilian Amazon Basin in the past eight decades

Science.gov (United States)

Satyamurty, Prakki; de Castro, Aline Anderson; Tota, Julio; da Silva Gularte, Lucia Eliane; Manzi, Antonio Ocimar

2010-01-01

Rainfall series at 18 stations along the major rivers of the Brazilian Amazon Basin, having data since 1920s or 1930s, are analyzed to verify if there are appreciable long-term trends. Annual, rainy-season, and dry-season rainfalls are individually analyzed for each station and for the region as a whole. Some stations showed positive trends and some negative trends. The trends in the annual rainfall are significant at only six stations, five of which reporting increasing trends (Barcelos, Belem, Manaus, Rio Branco, and Soure stations) and just one (Itaituba station) reporting decreasing trend. The climatological values of rainfall before and after 1970 show significant differences at six stations (Barcelos, Belem, Benjamin Constant, Iaurete, Itaituba, and Soure). The region as a whole shows an insignificant and weak downward trend; therefore, we cannot affirm that the rainfall in the Brazilian Amazon basin is experiencing a significant change, except at a few individual stations. Subregions with upward and downward trends are interspersed in space from the far eastern Amazon to western Amazon. Most of the seasonal trends follow the annual trends, thus, indicating a certain consistency in the datasets and analysis.

An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa

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Margaret Wambui Kimani

2017-05-01

Full Text Available Accurate and consistent rainfall observations are vital for climatological studies in support of better agricultural and water management decision-making and planning. In East Africa, accurate rainfall estimation with an adequate spatial distribution is limited due to sparse rain gauge networks. Satellite rainfall products can potentially play a role in increasing the spatial coverage of rainfall estimates; however, their performance needs to be understood across space–time scales and factors relating to their errors. This study assesses the performance of seven satellite products: Tropical Applications of Meteorology using Satellite and ground-based observations (TAMSAT, African Rainfall Climatology And Time series (TARCAT, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS, Tropical Rainfall Measuring Mission (TRMM-3B43, Climate Prediction Centre (CPC Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR, CPC Merged Analysis of Precipitation (CMAP, and Global Precipitation Climatology Project (GPCP, using locally developed gridded (0.05° rainfall data for 15 years (1998–2012 over East Africa. The products’ assessments were done at monthly and yearly timescales and were remapped to the gridded rain gauge data spatial scale during the March to May (MAM and October to December (OND rainy seasons. A grid-based statistical comparison between the two datasets was used, but only pixel values located at the rainfall stations were considered for validation. Additionally, the impact of topography on the performance of the products was assessed by analyzing the pixels in areas of highest negative bias. All the products could substantially replicate rainfall patterns, but their differences are mainly based on retrieving high rainfall amounts, especially of localized orographic types. The products exhibited systematic errors, which

Influence of Changing Rainfall Patterns on the Yield of Rambutan (Nephelium lappaceum L. and Selection of Genotypes in Known Drought-tolerant Fruit Species for Climate Change Adaptation

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Pablito M. Magdalita

2015-06-01

Full Text Available In fruit crop production, rainfall, water stress, temperature, and wind are key variables for success, and the present changes in rainfall patterns could affect the flowering and yield of the rambutan (Nephelium lappaceum L. Other fruit species like macopa (Syzygium samarangense, siniguelas (Spondias purpurea, and native santol or cotton fruit (Sandoricum koetjape remain productive despite extreme climatic changes. This study assessed the influence of rainfall on rambutan yield and evaluated and selected tree genotypes of known drought-tolerant fruit species. Rambutan yield in a selected farm in Calauan, Laguna, Philippines, dropped remarkably from 152.2 kg/tree in 2008 to 8.6 kg/tree in 2009. This reduction could be attributed to the high rainfall in April 2009 at 334.4 mm, and possibly other environmental factors like temperature, relative humidity, solar radiation, and strong wind. Furthermore, wet months in 2009 also inhibited the flowering of rambutan. However, a low yield obtained in 2010 at 45.5 kg/tree could be partly attributed to the very low rainfall in May 2010 at only 9.1 mm. On the other hand, in relation to changing climate, selection of tree genotypes for use as varieties in known drought- and flood-tolerant fruit species based on important fruit qualities like sweetness, juiciness, and high edible portion was done. Among 103 macopa genotypes, Mc-13, 43, and 91 were selected and the best (i.e. , Mc-13 had sweet (7.15 °Brix and crispy fruits weighing 49.44 g, creamy white (RHCC 155 A, and had high edible portion (EP, 93.22%. Among 114 siniguelas genotypes, Sg-41, 42 and 105 were selected and the best selection (i.e., Sg-41, had sweet (12.50 °Brix and juicy fruit weighing 20.42 g, ruby red (RHCC 59 A, and had high EP (83.27%. Among 101 native santol genotypes, Sn-47, 59, and 74 were selected and the best selection (i.e. , Sn-59 had relatively sweet (5.56 °Brix and juicy fruits weighing 51.96 g, maize yellow (RHCC 21 B, and had

Climate change impact assessment on urban rainfall extremes and urban drainage: Methods and shortcomings

DEFF Research Database (Denmark)

Willems, P.; Arnbjerg-Nielsen, Karsten; Olsson, J.

2012-01-01

Cities are becoming increasingly vulnerable to flooding because of rapid urbanization, installation of complex infrastructure, and changes in the precipitation patterns caused by anthropogenic climate change. The present paper provides a critical review of the current state-of-the-art methods...... for assessing the impacts of climate change on precipitation at the urban catchment scale. Downscaling of results from global circulation models or regional climate models to urban catchment scales are needed because these models are not able to describe accurately the rainfall process at suitable high temporal...... and spatial resolution for urban drainage studies. The downscaled rainfall results are however highly uncertain, depending on the models and downscaling methods considered. This uncertainty becomes more challenging for rainfall extremes since the properties of these extremes do not automatically reflect those...

Accuracy of CHIRPS Satellite-Rainfall Products over Mainland China

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Lei Bai

2018-02-01

Full Text Available Precipitation is the main component of global water cycle. At present, satellite quantitative precipitation estimates (QPEs are widely applied in the scientific community. However, the evaluations of satellite QPEs have some limitations in terms of the deficiency in observation, evaluation methodology, the selection of time windows for evaluation and short periods for evaluation. The objective of this work is to make some improvements by evaluating the spatio-temporal pattern of the long-terms Climate Hazard Group InfraRed Precipitation Satellite’s (CHIRPS’s QPEs over mainland China. In this study, we compared the daily precipitation estimates from CHIRPS with 2480 rain gauges across China and gridded observation using several statistical metrics in the long-term period of 1981–2014. The results show that there is significant difference between point evaluation and grid evaluation for CHIRPS. CHIRPS has better performance for a large amount of precipitation than it does for arid and semi-arid land. The change in good performance zones has strong relationship with monsoon’s movement. Therefore, CHIRPS performs better in river basins of southern China and exhibits poor performance in river basins in northwestern and northern China. Moreover, CHIRPS exhibits better in warm season than in Winter, owing to its limited ability to detect snowfall. Nevertheless, CHIRPS is moderately sensitive to the precipitation from typhoon weather systems. The limitations for CHIRPS result from the Tropical Rainfall Measuring Mission (TRMM 3B42 estimates’ accuracy and valid spatial coverage.

Soil losses from typic cambisols and red latosol as related to three erosive rainfall patterns Perdas de solo em cambissolo e latossolo vermelho, em relação a três padrões de chuvas erosivas

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Regimeire Freitas Aquino

2013-02-01

Full Text Available Rainfall erosivity is one of the main factors related to water erosion in the tropics. This work focused on relating soil loss from a typic dystrophic Tb Haplic Cambisol (CXbd and a typic dystrophic Red Latosol (LVdf to different patterns of natural erosive rainfall. The experimental plots of approximately 26 m² (3 x 8.67 m consisted of a CXbd area with a 0.15 m m-1 slope and a LVdf area with 0.12 m m-1 slope, both delimited by galvanized plates. Drainpipes were installed at the lower part of these plots to collect runoff, interconnected with a Geib or multislot divisor. To calculate erosivity (EI30, rainfall data, recorded continuously at a weather station in Lavras, were used. The data of erosive rainfall events were measured (10 mm precipitation intervals, accuracy 0.2 mm, 24 h period, 20 min intervals, characterized as rainfall events with more than 10 mm precipitation, maximum intensity > 24 mm h-1 within 15 min, or kinetic energy > 3.6 MJ, which were used in this study to calculate the rainfall erosivity parameter, were classified according to the moment of peak precipitation intensity in advanced, intermediate and delayed patterns. Among the 139 erosive rainfall events with CXbd soil loss, 60 % were attributed to the advanced pattern, with a loss of 415.9 Mg ha-1, and total losses of 776.0 Mg ha-1. As for the LVdf, of the 93 erosive rainfall events with soil loss, 58 % were listed in the advanced pattern, with 37.8 Mg ha-1 soil loss and 50.9 Mg ha-1 of total soil loss. The greatest soil losses were observed in the advanced rain pattern, especially for the CXbd. From the Cambisol, the soil loss per rainfall event was greatest for the advanced pattern, being influenced by the low soil permeability.A erosividade da chuva é um dos principais fatores relacionados à erosão hídrica para as condições tropicais. Este trabalho teve como objetivo relacionar as perdas de solo em Cambissolo Háplico Tb distrófico típico (CXbd e Latossolo

Past, present and future variations of extreme rainfall in Denmark

DEFF Research Database (Denmark)

Gregersen, Ida Bülow

of non-stationary extreme rainfall behaviour, in Denmark as well as worldwide. To provide recommendations on future design intensities it is necessary to explore and understand patterns of temporal variation in urban design rainfall and identify potential drivers behind past, present and future changes...... to the natural variability, the expected impacts of climate change and their interplay. A large part of the uncertainty is inherent and cannot be reduced. On top of this come the many unknown features in the climate system. The irrational behaviour of mankind contributes to the uncertainty, as it both affects...... the greenhouse gas emissions, and the requirements to cities of the future. Simple case studies based on different decision making frameworks show that the uncertainty of the future is not a hindrance for adaptation....

Evolution of extreme rainfall in France with a changing climate

International Nuclear Information System (INIS)

Soubeyroux, Jean-Michel; Veysseire, Jean-Michel; Gouget, Viviane; Neppel, Luc; Tramblay, Yves; Carreau, Julie

2015-01-01

This paper focuses a synthesis of the works led within the framework of the French project ANR/Extraflo on the evolution of the daily (and infra daily) extreme rainfall in France. An important dataset of more than 900 series was used. It was shown that a majority of series presented a not significant upward trend in particular in Mediterranean area, in relation with various recent exceptional extreme events. An interesting way to characterize this evolution consists in identifying climatic co-variables associated to heavy rainfall events (weather patterns, average temperatures, flow of humidity) and in taking into account them with a non stationary POT model. The application of this method with climatic projections under scenario A2 from IPCC could lead to a possible increase on extreme precipitation quantiles on the horizon 2070. (authors)

Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

Science.gov (United States)

Kang, Suchul; Im, Eun-Soon; Eltahir, Elfatih A. B.

2018-03-01

In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

Energy Technology Data Exchange (ETDEWEB)

Pattanaik, D.R. [India Meteorological Department (IMD), New Delhi (India); Kumar, Arun [Climate Prediction Center, National Centre for Environmental Prediction (NCEP)/NWS/NOAA, Camp Springs, MD (United States)

2010-03-15

The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction's (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS's hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50 E-110 E and 10 S-35 N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon

Prediction of rainfall-induced shallow landslides at national scale in Italy

Science.gov (United States)

Montrasio, Lorella; Valentino, Roberto; Rossi, Lauro; Rudari, Roberto; Terrone, Andrea

2013-04-01

devoted to the discussion of the input data, which have been collected through a Geographic Information System (GIS) platform. Results of the slope-stability analysis on national scale, over a two year time interval (2011 - 2012), are finally presented. The results predicted by the SLIP model are analyzed in terms of safety factor (Fs) maps, corresponding to some particular rainfall events. The paper shows the comparison between observed landslide localizations and model predictions. Notwithstanding an improvement in terms of accuracy is needed, the application of the model on the study area guarantees a good agreement between the instability condition and the expected date and localization of the selected events. The obtained results suggest that the output of the SLIP model could be used to define different levels of "dynamic" susceptibility. If coupled with a model of forecast rainfall, SLIP could be the basis for the development of an early-warning alert system against the phenomena of interest, especially if adopted as a local scale tool, in the framework of an alert system at a wider scale.

Tropical Rainfall Measuring Mission (TRMM) and the Future of Rainfall Estimation from Space

Science.gov (United States)

Kakar, Ramesh; Adler, Robert; Smith, Eric; Starr, David OC. (Technical Monitor)

2001-01-01

Tropical rainfall is important in the hydrological cycle and to the lives and welfare of humans. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. Recognizing the importance of rain in the tropics, NASA for the U.S.A. and NASDA for Japan have partnered in the design, construction and flight of a satellite mission to measure tropical rainfall and calculate the associated latent heat release. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms and applications of these results to areas such as Data Assimilation and model initialization. TRMM has reduced the uncertainty of climatological rainfall in tropics by over a factor of two, therefore establishing a standard for comparison with previous data sets and climatologies. It has documented the diurnal variation of precipitation over the oceans, showing a distinct early morning peak and this satellite mission has shown the utility of precipitation information for the improvement of numerical weather forecasts and climate modeling. This paper discusses some promising applications using TRMM data and introduces a measurement concept being discussed by NASA/NASDA and ESA for the future of rainfall estimation from space.

Multi-catchment rainfall-runoff simulation for extreme flood estimation

Science.gov (United States)

Paquet, Emmanuel

2017-04-01

rainfall of each event is distributed through the different sub-catchments using the spatial patterns calculated in the SPAZM precipitation reanalysis (Gottardi et al., 2012) for comparable situations of the 1948-2005 period. Corresponding runoffs are calculated with the hydrological models and aggregated to compute the discharge at the outlet of the main catchment. A complete distribution of flood discharges is finally computed. This method is illustrated with the example of the Durance at Serre-Ponçon catchment (south of French Alps, 3600 km2) which has been divided in four sub-catchements. The proposed approach is compared with the "classical" SCHADEX approach applied on the whole catchment. References: Garçon, R. (1996). Prévision opérationnelle des apports de la Durance à Serre-Ponçon à l'aide du modèle MORDOR. Bilan de l'année 1994-1995. La Houille Blanche, (5), 71-76. Gottardi, F., Obled, C., Gailhard, J., & Paquet, E. (2012). Statistical reanalysis of precipitation fields based on ground network data and weather patterns: Application over French mountains. Journal of Hydrology, 432, 154-167. Paquet, E., Garavaglia, F., Garçon, R., & Gailhard, J. (2013). The SCHADEX method: A semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology, 495, 23-37.

Peak-summer East Asian rainfall predictability and prediction part II: extratropical East Asia

Science.gov (United States)

Yim, So-Young; Wang, Bin; Xing, Wen

2016-07-01

The part II of the present study focuses on northern East Asia (NEA: 26°N-50°N, 100°-140°E), exploring the source and limit of the predictability of the peak summer (July-August) rainfall. Prediction of NEA peak summer rainfall is extremely challenging because of the exposure of the NEA to midlatitude influence. By examining four coupled climate models' multi-model ensemble (MME) hindcast during 1979-2010, we found that the domain-averaged MME temporal correlation coefficient (TCC) skill is only 0.13. It is unclear whether the dynamical models' poor skills are due to limited predictability of the peak-summer NEA rainfall. In the present study we attempted to address this issue by applying predictable mode analysis method using 35-year observations (1979-2013). Four empirical orthogonal modes of variability and associated major potential sources of variability are identified: (a) an equatorial western Pacific (EWP)-NEA teleconnection driven by EWP sea surface temperature (SST) anomalies, (b) a western Pacific subtropical high and Indo-Pacific dipole SST feedback mode, (c) a central Pacific-El Nino-Southern Oscillation mode, and (d) a Eurasian wave train pattern. Physically meaningful predictors for each principal component (PC) were selected based on analysis of the lead-lag correlations with the persistent and tendency fields of SST and sea-level pressure from March to June. A suite of physical-empirical (P-E) models is established to predict the four leading PCs. The peak summer rainfall anomaly pattern is then objectively predicted by using the predicted PCs and the corresponding observed spatial patterns. A 35-year cross-validated hindcast over the NEA yields a domain-averaged TCC skill of 0.36, which is significantly higher than the MME dynamical hindcast (0.13). The estimated maximum potential attainable TCC skill averaged over the entire domain is around 0.61, suggesting that the current dynamical prediction models may have large rooms to improve

Mexico's summer rainfall patterns: an analysis of regional modes and changes in their teleconnectivity

Energy Technology Data Exchange (ETDEWEB)

Englehart, P.J.; Douglas, A.V. [Department of Atmospheric and Environmental Sciencies, Creighton University, Omaha, N.E. (United States)

2002-07-01

This study explores the interanual variability in Mexico's warm season rainfall. It is based on historical rainfall data (1927-1997) from a grid of 130 long-term stations. The grid provides reasonable spatial coverage over most of the country. Using Principal Component Analysis, this study delimits five relatively large sub-areas of the country. Within each of these regions, monthly station rainfall exhibits high levels of spatial coherence. The regional structures are distinct and physically plausible with respect to the climatology of Mexico. The regional time series are expressed as departures from normal. In most of these series the intra seasonal, that is, month to month, persistence is minimal; in fact, only a few of the series display significant tendencies toward nonrandom serial behavior. This study evaluates the tele connectivity between the regional rainfall series and several different indices of large-scale ocean and atmosphere variability. These indices include an El Nino-Southern Oscillation index, indices that describe the strength and position of the subtropical anticyclone belt, as well as local SSTs in the Eastern Pacific and the Gulf of Mexico. All of the tele connections analyses consider the quasi-decadal mode of variability that is commonly referred to as the Pacific Decadal Oscillations (PDO). The study results generally agree with the findings of other researchers to the extent that they indicate differential tele connectivity as a function of PDO phase. However, unlike other studies, we see no compelling evidence for non-linear behavior in the tele connections within PDO phase. Instead, the more prominent feature of the tele connections is simply that they tend to be both more spatially extensive and stronger in the positive PDO phase. [Spanish] Este estudio explora la variabilidad interanual de la lluvia de verano en Mexico. Se basa en el analisis de datos historicos de la lluvia de 130 estaciones con un periodo largo de observacion

Linking landscape structure and rainfall runoff behaviour in a thermodynamic optimality context

Science.gov (United States)

Zehe, Erwin; Ehret, Uwe; Blume, Theresa; Kleidon, Axel; Scherer, Ulrike; Westhoff, Martijn

2015-04-01

gradients, and thus a faster relaxation back towards local thermodynamic equilibrium. Thermodynamic optimality principles allow for a priory optimization of the resistance field at a given gradient, not in the sense how they exactly look like but in the sense how they function with respect to export and dissipation of free energy associated with rainfall runoff processes. Based on this framework we explored the possibility of independent predictions of rainfall runoff, in the sense that the a-priory optimum model structures should match independent observations. We found that spatially organized patterns of soils and macropores observed in two distinctly different landscapes are in close accordance with thermodynamic optima expressed either by minimized relaxation times towards local thermodynamic equilibrium in cohesive soils or as steady state in the potential energy of soil water in non-cohesive soils. Predicted rainfall runoff based on the two optimized model structures was in both catchments in acceptable accordance with independent discharge observations. However, the nature of these optima suggests there might be two distinctly different thermodynamically optimal regimes of rainfall runoff behaviour. In the capillary- or c--regime, free energy dynamics of soil water is dominated by changes in its capillary binding energy, which is the case for cohesive soils. Soil wetting during rainfall in the c-regime implies pushing the system back towards LTE, especially after long dry spells. Dead ended macropores (roots, worm burrows which end in the soil matrix) act as dissipative wetting structures by enlarging water flows against steep gradients in soil water potential after long dry spells. This implies accelerated depletion of these gradients and faster relaxation back towards LTE during rainfall runoff. In the c-regime several optimum macropore densities with respect to maximization of net reduction of free energy exist. This is because the governing equation is a second

Rainfall prediction of Cimanuk watershed regions with canonical correlation analysis (CCA)

Science.gov (United States)

Rustiana, Shailla; Nurani Ruchjana, Budi; Setiawan Abdullah, Atje; Hermawan, Eddy; Berliana Sipayung, Sinta; Gede Nyoman Mindra Jaya, I.; Krismianto

2017-10-01

Rainfall prediction in Indonesia is very influential on various development sectors, such as agriculture, fisheries, water resources, industry, and other sectors. The inaccurate predictions can lead to negative effects. Cimanuk watershed is one of the main pillar of water resources in West Java. This watersheds divided into three parts, which is a headwater of Cimanuk sub-watershed, Middle of Cimanuk sub-watershed and downstream of Cimanuk sub- watershed. The flow of this watershed will flow through the Jatigede reservoir and will supply water to the north-coast area in the next few years. So, the reliable model of rainfall prediction is very needed in this watershed. Rainfall prediction conducted with Canonical Correlation Analysis (CCA) method using Climate Predictability Tool (CPT) software. The prediction is every 3months on 2016 (after January) based on Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data over West Java. Predictors used in CPT were the monthly data index of Nino3.4, Dipole Mode (DMI), and Monsoon Index (AUSMI-ISMI-WNPMI-WYMI) with initial condition January. The initial condition is chosen by the last data update. While, the predictant were monthly rainfall data CHIRPS region of West Java. The results of prediction rainfall showed by skill map from Pearson Correlation. High correlation of skill map are on MAM (Mar-Apr-May), AMJ (Apr-May-Jun), and JJA (Jun-Jul-Aug) which means the model is reliable to forecast rainfall distribution over Cimanuk watersheds region (over West Java) on those seasons. CCA score over those season prediction mostly over 0.7. The accuracy of the model CPT also indicated by the Relative Operating Characteristic (ROC) curve of the results of Pearson correlation 3 representative point of sub-watershed (Sumedang, Majalengka, and Cirebon), were mostly located in the top line of non-skill, and evidenced by the same of rainfall patterns between observation and forecast. So, the model of CPT with CCA method

On the influence of simulated SST warming on rainfall projections in the Indo-Pacific domain: an AGCM study

Science.gov (United States)

Zhang, Huqiang; Zhao, Y.; Moise, A.; Ye, H.; Colman, R.; Roff, G.; Zhao, M.

2018-02-01

Significant uncertainty exists in regional climate change projections, particularly for rainfall and other hydro-climate variables. In this study, we conduct a series of Atmospheric General Circulation Model (AGCM) experiments with different future sea surface temperature (SST) warming simulated by a range of coupled climate models. They allow us to assess the extent to which uncertainty from current coupled climate model rainfall projections can be attributed to their simulated SST warming. Nine CMIP5 model-simulated global SST warming anomalies have been super-imposed onto the current SSTs simulated by the Australian climate model ACCESS1.3. The ACCESS1.3 SST-forced experiments closely reproduce rainfall means and interannual variations as in its own fully coupled experiments. Although different global SST warming intensities explain well the inter-model difference in global mean precipitation changes, at regional scales the SST influence vary significantly. SST warming explains about 20-25% of the patterns of precipitation changes in each of the four/five models in its rainfall projections over the oceans in the Indo-Pacific domain, but there are also a couple of models in which different SST warming explains little of their precipitation pattern changes. The influence is weaker again for rainfall changes over land. Roughly similar levels of contribution can be attributed to different atmospheric responses to SST warming in these models. The weak SST influence in our study could be due to the experimental setup applied: superimposing different SST warming anomalies onto the same SSTs simulated for current climate by ACCESS1.3 rather than directly using model-simulated past and future SSTs. Similar modelling and analysis from other modelling groups with more carefully designed experiments are needed to tease out uncertainties caused by different SST warming patterns, different SST mean biases and different model physical/dynamical responses to the same underlying

Climate teleconnections and recent patterns of human and animal disease outbreaks.

Directory of Open Access Journals (Sweden)

Assaf Anyamba

2012-01-01

Full Text Available Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya.We derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004-2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3-4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found

Monsoon Rainfall and Landslides in Nepal

Science.gov (United States)

Dahal, R. K.; Hasegawa, S.; Bhandary, N. P.; Yatabe, R.

2009-12-01

A large number of human settlements on the Nepal Himalayas are situated either on old landslide mass or on landslide-prone areas. As a result, a great number of people are affected by large- and small-scale landslides all over the Himalayas especially during monsoon periods. In Nepal, only in the half monsoon period (June 10 to August 15), 70, 50 and 68 people were killed from landslides in 2007, 2008 and 2009, respectively. In this context, this paper highlights monsoon rainfall and their implications in the Nepal Himalaya. In Nepal, monsoon is major source of rainfall in summer and approximately 80% of the annual total rainfall occurs from June to September. The measured values of mean annual precipitation in Nepal range from a low of approximately 250 mm at area north of the Himalaya to many areas exceeding 6,000 mm. The mean annual rainfall varying between 1500 mm and 2500 mm predominate over most of the country. In Nepal, the daily distribution of precipitation during rainy season is also uneven. Sometime 10% of the total annual precipitation can occur in a single day. Similarly, 50% total annual rainfall also can occur within 10 days of monsoon. This type of uneven distribution plays an important role in triggering many landslides in Nepal. When spatial distribution of landslides was evaluated from record of more than 650 landslides, it is found that more landslides events were concentrated at central Nepal in the area of high mean annual rainfall. When monsoon rainfall and landslide relationship was taken into consideration, it was noticed that a considerable number of landslides were triggered in the Himalaya by continuous rainfall of 3 to 90 days. It has been noticed that continuous rainfall of few days (5 days or 7 days or 10 days) are usually responsible for landsliding in the Nepal Himalaya. Monsoon rains usually fall with interruptions of 2-3 days and are generally characterized by low intensity and long duration. Thus, there is a strong role of

Relationships between southeastern Australian rainfall and sea surface temperatures examined using a climate model

Science.gov (United States)

Watterson, I. G.

2010-05-01

Rainfall in southeastern Australia has declined in recent years, particularly during austral autumn over the state of Victoria. A recent study suggests that sea surface temperature (SST) variations in both the Indonesian Throughflow (ITF) region and in a meridional dipole in the central Indian Ocean have influenced Victorian late autumn rainfall since 1950. However, it remains unclear to what extent SSTs in these and other regions force such a teleconnection. Analysis of a 1080 year simulation by the climate model CSIRO Mk3.5 shows that the model Victorian rainfall is correlated rather realistically with SSTs but that part of the above relationships is due to the model ENSO. Furthermore, the remote patterns of pressure, rainfall, and land temperature greatly diminish when the data are lagged by 1 month, suggesting that the true forcing by the persisting SSTs is weak. In a series of simulations of the atmospheric Mk3.5 with idealized SST anomalies, raised SSTs to the east of Indonesia lower the simulated Australian rainfall, while those to the west raise it. A positive ITF anomaly lowers pressure over Australia, but with little effect on Victorian rainfall. The meridional dipole and SSTs to the west and southeast of Australia have little direct effect on southeastern Australia in the model. The results suggest that tropical SSTs predominate as an influence on Victorian rainfall. However, the SST indices appear to explain only a fraction of the observed trend, which in the case of decadal means remains within the range of unforced variability simulated by Mk3.5.

[Rainfall and soil moisture redistribution induced by xerophytic shrubs in an arid desert ecosystem].

Science.gov (United States)

Wang, Zheng Ning; Wang, Xin Ping; Liu, Bo

2016-03-01

Rainfall partitioning by desert shrub canopy modifies the redistribution of incident rainfall under the canopy, and may affect the distribution pattern of soil moisture around the plant. This study examined the distribution of rainfall and the response of soil moisture beneath the canopy of two dominant desert shrubs, Caragana korshinskii and Artemisia ordosica, in the revegetation area at the southeastern edge of the Tengger Desert. The results showed that throughfall and stemflow ave-ragely occupied 74.4%, 11.3% and 61.8%, 5.5% of the gross precipitation for C. korshinskii and A. ordosica, respectively. The mean coefficients of variation (CV) of throughfall were 0.25 and 0.30, respectively. C. korshinski were more efficient than A. ordosica on stemflow generation. The depth of soil wetting front around the stem area was greater than other areas under shrub canopy for C. korshinski, and it was only significantly greater under bigger rain events for A. ordosica. The shrub canopy could cause the unevenness of soil wetting front under the canopy in consequence of rainfall redistribution induced by xerophytic shrub.

Predicting watershed acidification under alternate rainfall conditions

International Nuclear Information System (INIS)

Huntington, T.G.

1996-01-01

The effect of alternate rainfall scenarios on acidification of a forested watershed subjected to chronic acidic deposition was assessed using the model of acidification of groundwater in catchments (MAGIC). The model was calibrated at the Panola Mountain Research Watershed, near Atlanta, Georgia, USA using measured soil properties, wet and dry deposition, and modeled hydrologic routing. Model forecast simulations were evaluated to compare alternate temporal averaging of rainfall inputs and variations in rainfall amount and seasonal distribution. Soil water alkalinity was predicted to decrease to substantially lower concentrations under lower rainfall compared with current or higher rainfall conditions. Soil water alkalinity was also predicted to decrease to lower levels when the majority of rainfall occurred during the growing season compared with other rainfall distributions. Changes in rainfall distribution that result in decreases in net soil water flux will temporarily delay acidification. Ultimately, however, decreased soilwater flux will result in larger increases in soil-adsorbed sulfur and soil-water sulfate concentrations and decreases in alkalinity when compared to higher water flux conditions. Potential climate change resulting in significant changes in rainfall amounts, seasonal distributions of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading. 29 refs., 7 figs., 4 tabs

Application of seasonal rainfall forecasts and satellite rainfall observations to crop yield forecasting for Africa

Science.gov (United States)

Greatrex, H. L.; Grimes, D. I. F.; Wheeler, T. R.

2009-04-01

Rain-fed agriculture is of utmost importance in sub-Saharan Africa; the FAO estimates that over 90% of food consumed in the region is grown in rain-fed farming systems. As the climate in sub-Saharan Africa has a high interannual variability, this dependence on rainfall can leave communities extremely vulnerable to food shortages, especially when coupled with a lack of crop management options. The ability to make a regional forecast of crop yield on a timescale of months would be of enormous benefit; it would enable both governmental and non-governmental organisations to be alerted in advance to crop failure and could facilitate national and regional economic planning. Such a system would also enable individual communities to make more informed crop management decisions, increasing their resilience to climate variability and change. It should be noted that the majority of crops in the region are rainfall limited, therefore the ability to create a seasonal crop forecast depends on the ability to forecast rainfall at a monthly or seasonal timescale and to temporally downscale this to a daily time-series of rainfall. The aim of this project is to develop a regional-scale seasonal forecast for sub-Saharan crops, utilising the General Large Area Model for annual crops (GLAM). GLAM would initially be driven using both dynamical and statistical seasonal rainfall forecasts to provide an initial estimate of crop yield. The system would then be continuously updated throughout the season by replacing the seasonal rainfall forecast with daily weather observations. TAMSAT satellite rainfall estimates are used rather than rain-gauge data due to the scarcity of ground based observations. An important feature of the system is the use of the geo-statistical method of sequential simulation to create an ensemble of daily weather inputs from both the statistical seasonal rainfall forecasts and the satellite rainfall estimates. This allows a range of possible yield outputs to be

Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

Science.gov (United States)

van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

2015-05-01

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nonstationarities in Catchment Response According to Basin and Rainfall Characteristics: Application to Korean Watershed

Science.gov (United States)

Kwon, Hyun-Han; Kim, Jin-Guk; Jung, Il-Won

2015-04-01

It must be acknowledged that application of rainfall-runoff models to simulate rainfall-runoff processes are successful in gauged watershed. However, there still remain some issues that will need to be further discussed. In particular, the quantitive representation of nonstationarity issue in basin response (e.g. concentration time, storage coefficient and roughness) along with ungauged watershed needs to be studied. In this regard, this study aims to investigate nonstationarity in basin response so as to potentially provide useful information in simulating runoff processes in ungauged watershed. For this purpose, HEC-1 rainfall-runoff model was mainly utilized. In addition, this study combined HEC-1 model with Bayesian statistical model to estimate uncertainty of the parameters which is called Bayesian HEC-1 (BHEC-1). The proposed rainfall-runofall model is applied to various catchments along with various rainfall patterns to understand nonstationarities in catchment response. Further discussion about the nonstationarity in catchment response and possible regionalization of the parameters for ungauged watershed are discussed. KEYWORDS: Nonstationary, Catchment response, Uncertainty, Bayesian Acknowledgement This research was supported by a Grant (13SCIPA01) from Smart Civil Infrastructure Research Program funded by the Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and the Korea Agency for Infrastructure Technology Advancement (KAIA).

Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

Science.gov (United States)

Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

2016-10-01

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches

Assessing vegetation structure and ANPP dynamics in a grassland-shrubland Chihuahuan ecotone using NDVI-rainfall relationships

Science.gov (United States)

Moreno-de las Heras, M.; Diaz-Sierra, R.; Turnbull, L.; Wainwright, J.

2015-01-01

Climate change and the widespread alteration of natural habitats are major drivers of vegetation change in drylands. A classic case of vegetation change is the shrub-encroachment process that has been taking place over the last 150 years in the Chihuahuan Desert, where large areas of grasslands dominated by perennial grass species (black grama, Bouteloua eriopoda, and blue grama, B. gracilis) have transitioned to shrublands dominated by woody species (creosotebush, Larrea tridentata, and mesquite, Prosopis glandulosa), accompanied by accelerated water and wind erosion. Multiple mechanisms drive the shrub-encroachment process, including exogenous triggering factors such as precipitation variations and land-use change, and endogenous amplifying mechanisms brought about by soil erosion-vegetation feedbacks. In this study, simulations of plant biomass dynamics with a simple modelling framework indicate that herbaceous (grasses and forbs) and shrub vegetation in drylands have different responses to antecedent precipitation due to functional differences in plant growth and water-use patterns, and therefore shrub encroachment may be reflected in the analysis of landscape-scale vegetation-rainfall relationships. We analyze the structure and dynamics of vegetation at an 18 km2 grassland-shrubland ecotone in the northern edge of the Chihuahuan Desert (McKenzie Flats, Sevilleta National Wildlife Refuge, NM, USA) by investigating the relationship between decade-scale (2000-2013) records of medium-resolution remote sensing of vegetation greenness (MODIS NDVI) and precipitation. Spatial evaluation of NDVI-rainfall relationship at the studied ecotone indicates that herbaceous vegetation shows quick growth pulses associated with short-term (previous 2 months) precipitation, while shrubs show a slow response to medium-term (previous 5 months) precipitation. We use these relationships to (a) classify landscape types as a function of the spatial distribution of dominant vegetation

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

Science.gov (United States)

Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

2017-04-01

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this

An Advanced Method to Apply Multiple Rainfall Thresholds for Urban Flood Warnings

Directory of Open Access Journals (Sweden)

Jiun-Huei Jang

2015-11-01

Full Text Available Issuing warning information to the public when rainfall exceeds given thresholds is a simple and widely-used method to minimize flood risk; however, this method lacks sophistication when compared with hydrodynamic simulation. In this study, an advanced methodology is proposed to improve the warning effectiveness of the rainfall threshold method for urban areas through deterministic-stochastic modeling, without sacrificing simplicity and efficiency. With regards to flooding mechanisms, rainfall thresholds of different durations are divided into two groups accounting for flooding caused by drainage overload and disastrous runoff, which help in grading the warning level in terms of emergency and severity when the two are observed together. A flood warning is then classified into four levels distinguished by green, yellow, orange, and red lights in ascending order of priority that indicate the required measures, from standby, flood defense, evacuation to rescue, respectively. The proposed methodology is tested according to 22 historical events in the last 10 years for 252 urbanized townships in Taiwan. The results show satisfactory accuracy in predicting the occurrence and timing of flooding, with a logical warning time series for taking progressive measures. For systems with multiple rainfall thresholds already in place, the methodology can be used to ensure better application of rainfall thresholds in urban flood warnings.

Underwater Acoustic Measurements to Estimate Wind and Rainfall in the Mediterranean Sea

Directory of Open Access Journals (Sweden)

Sara Pensieri

2015-01-01

Full Text Available Oceanic ambient noise measurements can be analyzed to obtain qualitative and quantitative information about wind and rainfall phenomena over the ocean filling the existing gap of reliable meteorological observations at sea. The Ligurian Sea Acoustic Experiment was designed to collect long-term synergistic observations from a passive acoustic recorder and surface sensors (i.e., buoy mounted rain gauge and anemometer and weather radar to support error analysis of rainfall rate and wind speed quantification techniques developed in past studies. The study period included combination of high and low wind and rainfall episodes and two storm events that caused two floods in the vicinity of La Spezia and in the city of Genoa in 2011. The availability of high resolution in situ meteorological data allows improving data processing technique to detect and especially to provide effective estimates of wind and rainfall at sea. Results show a very good correspondence between estimates provided by passive acoustic recorder algorithm and in situ observations for both rainfall and wind phenomena and demonstrate the potential of using measurements provided by passive acoustic instruments in open sea for early warning of approaching coastal storms, which for the Mediterranean coastal areas constitutes one of the main causes of recurrent floods.

Impact analysis of satellite rainfall products on flow simulations in the Magdalena River Basin, Colombia

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Amr Elgamal

2017-02-01

Full Text Available The Magdalena River is the most important river in Colombia in terms of economic activities and is home to about 77% of the country’s population. The river faces water resources allocation challenges, which require reliable hydrological assessments. However, hydrological analysis and model simulations are hampered by insufficient and uncertain knowledge of the actual rainfall fields. In this research the reliability of groundbased measurements, different satellite products of rainfall and their combinations are tested for their impact on the discharge simulations of the Magdalena River. Two different satellite rainfall products from the Tropical Rainfall Measuring Mission (TRMM, have been compared and merged with the ground-based measurements and their impact on the Magdalena river flows quantified using the Representative Elementary Watershed (REW distributed hydrological model.

Stochastic modelling of daily rainfall sequences

NARCIS (Netherlands)

Buishand, T.A.

1977-01-01

Rainfall series of different climatic regions were analysed with the aim of generating daily rainfall sequences. A survey of the data is given in I, 1. When analysing daily rainfall sequences one must be aware of the following points:
a. Seasonality. Because of seasonal variation

Characterization of Future Caribbean Rainfall and Temperature Extremes across Rainfall Zones

Directory of Open Access Journals (Sweden)

Natalie Melissa McLean

2015-01-01

Full Text Available End-of-century changes in Caribbean climate extremes are derived from the Providing Regional Climate for Impact Studies (PRECIS regional climate model (RCM under the A2 and B2 emission scenarios across five rainfall zones. Trends in rainfall, maximum temperature, and minimum temperature extremes from the RCM are validated against meteorological stations over 1979–1989. The model displays greater skill at representing trends in consecutive wet days (CWD and extreme rainfall (R95P than consecutive dry days (CDD, wet days (R10, and maximum 5-day precipitation (RX5. Trends in warm nights, cool days, and warm days were generally well reproduced. Projections for 2071–2099 relative to 1961–1989 are obtained from the ECHAM5 driven RCM. Northern and eastern zones are projected to experience more intense rainfall under A2 and B2. There is less consensus across scenarios with respect to changes in the dry and wet spell lengths. However, there is indication that a drying trend may be manifest over zone 5 (Trinidad and northern Guyana. Changes in the extreme temperature indices generally suggest a warmer Caribbean towards the end of century across both scenarios with the strongest changes over zone 4 (eastern Caribbean.

Investigation of Rainfall-Runoff Processes and Soil Moisture Dynamics in Grassland Plots under Simulated Rainfall Conditions

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Nana Zhao

2014-09-01

Full Text Available The characteristics of rainfall-runoff are important aspects of hydrological processes. In this study, rainfall-runoff processes and soil moisture dynamics at different soil depths and slope positions of grassland with two different row spacings (5 cm and 10 cm, respectively, referred to as R5 and R10 were analyzed, by means of a solution of rainfall simulation experiments. Bare land was also considered as a comparison. The results showed that the mechanism of runoff generation was mainly excess infiltration overland flow. The surface runoff amount of R5 plot was greater than that of R10, while the interflow amount of R10 was larger than that of R5 plot, although the differences of the subsurface runoff processes between plots R5 and R10 were little. The effects of rainfall intensity on the surface runoff were significant, but not obvious on the interflow and recession curve, which can be described as a simple exponential equation, with a fitting degree of up to 0.854–0.996. The response of soil moisture to rainfall and evapotranspiration was mainly in the 0–20 cm layer, and the response at the 40 cm layer to rainfall was slower and generally occurred after the rainfall stopped. The upper slope generally responded fastest to rainfall, and the foot of the slope was the slowest. The results presented here could provide insights into understanding the surface and subsurface runoff processes and soil moisture dynamics for grasslands in semi-arid regions.

Rainfall Stochastic models

Science.gov (United States)

Campo, M. A.; Lopez, J. J.; Rebole, J. P.

2012-04-01

This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series

Linking Vital Rates of Landbirds on a Tropical Island to Rainfall and Vegetation Greenness.

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James F Saracco

Full Text Available Remote tropical oceanic islands are of high conservation priority, and they are exemplified by range-restricted species with small global populations. Spatial and temporal patterns in rainfall and plant productivity may be important in driving dynamics of these species. Yet, little is known about environmental influences on population dynamics for most islands and species. Here we leveraged avian capture-recapture, rainfall, and remote-sensed habitat data (enhanced vegetation index [EVI] to assess relationships between rainfall, vegetation greenness, and demographic rates (productivity, adult apparent survival of three native bird species on Saipan, Northern Mariana Islands: rufous fantail (Rhipidura rufifrons, bridled white-eye (Zosterops conspicillatus, and golden white-eye (Cleptornis marchei. Rainfall was positively related to vegetation greenness at all but the highest rainfall levels. Temporal variation in greenness affected the productivity of each bird species in unique ways. Predicted productivity of rufous fantail was highest when dry and wet season greenness values were high relative to site-specific 5-year seasonal mean values (i.e., relative greenness; while the white-eye species had highest predicted productivity when relative greenness contrasted between wet and dry seasons. Survival of rufous fantail and bridled white eye was positively related to relative dry-season greenness and negatively related to relative wet-season greenness. Bridled white-eye survival also showed evidence of a positive response to overall greenness. Our results highlight the potentially important role of rainfall regimes in affecting population dynamics of species on oceanic tropical islands. Understanding linkages between rainfall, vegetation, and animal population dynamics will be critical for developing effective conservation strategies in this and other regions where the seasonal timing, extent, and variability of rainfall is expected to change in the

Rainy Day: A Remote Sensing-Driven Extreme Rainfall Simulation Approach for Hazard Assessment

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Wright, Daniel; Yatheendradas, Soni; Peters-Lidard, Christa; Kirschbaum, Dalia; Ayalew, Tibebu; Mantilla, Ricardo; Krajewski, Witold

2015-04-01

Progress on the assessment of rainfall-driven hazards such as floods and landslides has been hampered by the challenge of characterizing the frequency, intensity, and structure of extreme rainfall at the watershed or hillslope scale. Conventional approaches rely on simplifying assumptions and are strongly dependent on the location, the availability of long-term rain gage measurements, and the subjectivity of the analyst. Regional and global-scale rainfall remote sensing products provide an alternative, but are limited by relatively short (~15-year) observational records. To overcome this, we have coupled these remote sensing products with a space-time resampling framework known as stochastic storm transposition (SST). SST "lengthens" the rainfall record by resampling from a catalog of observed storms from a user-defined region, effectively recreating the regional extreme rainfall hydroclimate. This coupling has been codified in Rainy Day, a Python-based platform for quickly generating large numbers of probabilistic extreme rainfall "scenarios" at any point on the globe. Rainy Day is readily compatible with any gridded rainfall dataset. The user can optionally incorporate regional rain gage or weather radar measurements for bias correction using the Precipitation Uncertainties for Satellite Hydrology (PUSH) framework. Results from Rainy Day using the CMORPH satellite precipitation product are compared with local observations in two examples. The first example is peak discharge estimation in a medium-sized (~4000 square km) watershed in the central United States performed using CUENCAS, a parsimonious physically-based distributed hydrologic model. The second example is rainfall frequency analysis for Saint Lucia, a small volcanic island in the eastern Caribbean that is prone to landslides and flash floods. The distinct rainfall hydroclimates of the two example sites illustrate the flexibility of the approach and its usefulness for hazard analysis in data-poor regions.

Forecasting Global Rainfall for Points Using ECMWF's Global Ensemble and Its Applications in Flood Forecasting

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Pillosu, F. M.; Hewson, T.; Mazzetti, C.

2017-12-01

Prediction of local extreme rainfall has historically been the remit of nowcasting and high resolution limited area modelling, which represent only limited areas, may not be spatially accurate, give reasonable results only for limited lead times (based statistical post-processing software ("ecPoint-Rainfall, ecPR", operational in 2017) that uses ECMWF Ensemble (ENS) output to deliver global probabilistic rainfall forecasts for points up to day 10. Firstly, ecPR applies a new notion of "remote calibration", which 1) allows us to replicate a multi-centennial training period using only one year of data, and 2) provides forecasts for anywhere in the world. Secondly, the software applies an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals, and of where biases in the model can be improved upon. A long-term verification has shown that the post-processed rainfall has better reliability and resolution at every lead time if compared with ENS, and for large totals, ecPR outputs have the same skill at day 5 that the raw ENS has at day 1 (ROC area metric). ecPR could be used as input for hydrological models if its probabilistic output is modified accordingly to the inputs requirements for hydrological models. Indeed, ecPR does not provide information on where the highest total is likely to occur inside the gridbox, nor on the spatial distribution of rainfall values nearby. "Scenario forecasts" could be a solution. They are derived from locating the rainfall peak in sensitive positions (e.g. urban areas), and then redistributing the remaining quantities in the gridbox modifying traditional spatial correlation characterization methodologies (e.g. variogram analysis) in order to take account, for instance, of the type of rainfall forecast (stratiform, convective). Such an approach could be a turning point in the field of medium-range global real-time riverine flood forecasts. This presentation will

Monitoring Multitemporal Soil Moisture, Rainfall, and ET in Lake Manatee Watershed, South Florida under Global Changes

Science.gov (United States)

Chang, N.

2009-12-01

Ni-Bin Chang1, Ammarin Daranpob 1, and Y. Jeffrey Yang2 1Civil, Environmental, and Construction Engineering Department, University of Central Florida, Orlando FL, USA 2Water Supply and Water Resources Division, National Risk Management Research Laboratory, U.S. EPA, Cincinnati, Ohio, USA ASBTRACT: Global climate change and its related impacts on water supply are universally recognized. The Atlantic Multidecadal Oscillation (AMO), which is based on long term changes in the temperature of the surface of the North Atlantic Ocean, is a source of changes in river flow patterns in Florida. The AMO has a multi-decadal frequency. Under its impact, several distinct types of river patterns were identified within Florida, including a Southern River Pattern (SRP), a Northern River Pattern (NRP), a Bimodal River Pattern (BRP), etc. (Kelley and Gore, 2008). Some SRPs are present in the South Florida Water Management District (SFWMD). Changes in river flows occur because significant sea surface temperature (SST) changes affect continental rainfall patterns. It had been observed that, between AMO warm (i.e., from 1939 to 1968) and cold phases (i.e., from 1969 to 1993), the average daily inflow to Lake Okeechobee varies by 40% in the transition from the warm to cold phases in South Florida. The Manatee County is located in the Southern Water Use Caution Area (SWUCA) due to the depletion of the Upper Floridian Aquifer and its entire western portion of the County is designated as part of the Most Impacted Area (MIA) within the Eastern Tampa Bay Water Use Caution Area relative to the SWUCA. Major source of Manatee County’s water is an 332 Km2 (82,000-acre) watershed (i.e., Lake Manatee Watershed) that drains into the man-made Lake Manatee Reservoir. The lake has a total volume of 0.21 billion m3 (7.5 billion gallons) and will cover 7.3 Km2 (1,800 acres) when full. The proper use of remote sensing images and sensor network technologies can provide information on both spatial and

Analyses of the temporal and spatial structures of heavy rainfall from a catalog of high-resolution radar rainfall fields

DEFF Research Database (Denmark)

Thorndahl, Søren; Smith, James A.; Baeck, Mary Lynn

2014-01-01

that relate to size, structure and evolution of heavy rainfall. Extreme rainfall is also linked with severe weather (tornados, large hail and damaging wind). The diurnal cycle of rainfall for heavy rain days is characterized by an early peak in the largest rainfall rates, an afternoon-evening peak in rain...

Technical Report Series on Global Modeling and Data Assimilation. Volume 12; Comparison of Satellite Global Rainfall Algorithms

Science.gov (United States)

Suarez, Max J. (Editor); Chang, Alfred T. C.; Chiu, Long S.

1997-01-01

Seventeen months of rainfall data (August 1987-December 1988) from nine satellite rainfall algorithms (Adler, Chang, Kummerow, Prabhakara, Huffman, Spencer, Susskind, and Wu) were analyzed to examine the uncertainty of satellite-derived rainfall estimates. The variability among algorithms, measured as the standard deviation computed from the ensemble of algorithms, shows regions of high algorithm variability tend to coincide with regions of high rain rates. Histograms of pattern correlation (PC) between algorithms suggest a bimodal distribution, with separation at a PC-value of about 0.85. Applying this threshold as a criteria for similarity, our analyses show that algorithms using the same sensor or satellite input tend to be similar, suggesting the dominance of sampling errors in these satellite estimates.

Urban rainfall estimation employing commercial microwave links

Science.gov (United States)

Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko; ten Veldhuis, Marie-claire

2015-04-01

Urban areas often lack rainfall information. To increase the number of rainfall observations in cities, microwave links from operational cellular telecommunication networks may be employed. Although this new potential source of rainfall information has been shown to be promising, its quality needs to be demonstrated more extensively. In the Rain Sense kickstart project of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS), sensors and citizens are preparing Amsterdam for future weather. Part of this project is rainfall estimation using new measurement techniques. Innovative sensing techniques will be utilized such as rainfall estimation from microwave links, umbrellas for weather sensing, low-cost sensors at lamp posts and in drainage pipes for water level observation. These will be combined with information provided by citizens in an active way through smartphone apps and in a passive way through social media posts (Twitter, Flickr etc.). Sensor information will be integrated, visualized and made accessible to citizens to help raise citizen awareness of urban water management challenges and promote resilience by providing information on how citizens can contribute in addressing these. Moreover, citizens and businesses can benefit from reliable weather information in planning their social and commercial activities. In the end city-wide high-resolution rainfall maps will be derived, blending rainfall information from microwave links and weather radars. This information will be used for urban water management. This presentation focuses on rainfall estimation from commercial microwave links. Received signal levels from tens of microwave links within the Amsterdam region (roughly 1 million inhabitants) in the Netherlands are utilized to estimate rainfall with high spatial and temporal resolution. Rainfall maps will be presented and compared to a gauge-adjusted radar rainfall data set. Rainfall time series from gauge(s), radars and links will be compared.

A framework of integrated hydrological and hydrodynamic models using synthetic rainfall for flash flood hazard mapping of ungauged catchments in tropical zones

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W. Lohpaisankrit

2016-05-01

Full Text Available Flash flood hazard maps provide a scientific support to mitigate flash flood risk. The present study develops a practical framework with the help of integrated hydrological and hydrodynamic modelling in order to estimate the potential flash floods. We selected a small pilot catchment which has already suffered from flash floods in the past. This catchment is located in the Nan River basin, northern Thailand. Reliable meteorological and hydrometric data are missing in the catchment. Consequently, the entire upper basin of the main river was modelled with the help of the hydrological modelling system PANTA RHEI. In this basin, three monitoring stations are located along the main river. PANTA RHEI was calibrated and validated with the extreme flood events in June 2011 and July 2008, respectively. The results show a good agreement with the observed discharge data. In order to create potential flash flood scenarios, synthetic rainfall series were derived from temporal rainfall patterns based on the radar-rainfall observation and different rainfall depths from regional rainfall frequency analysis. The temporal rainfall patterns were characterized by catchment-averaged rainfall series selected from 13 rainstorms in 2008 and 2011 within the region. For regional rainfall frequency analysis, the well-known L-moments approach and related criteria were used to examine extremely climatic homogeneity of the region. According to the L-moments approach, Generalized Pareto distribution was recognized as the regional frequency distribution. The synthetic rainfall series were fed into the PANTA RHEI model. The simulated results from PANTA RHEI were provided to a 2-D hydrodynamic model (MEADFLOW, and various simulations were performed. Results from the integrated modelling framework are used in the ongoing study to regionalize and map the spatial distribution of flash flood hazards with four levels of flood severities. As an overall outcome, the presented framework

Stochastic characterization of regional circulation patterns for climate model diagnosis and estimation of local precipitation

International Nuclear Information System (INIS)

Zorita, E.; Hughes, J.P.

1993-01-01

Two statistical approaches for linking large-scale atmospheric circulation patterns and daily local rainfall are described and applied to several GCM (general circulation model) climate simulations. The ultimate objective is to simulate local precipitation associated with alternative climates. The index stations are located near the West and East North American coasts. The first method is based on CART analysis (Classification and Regression trees). It finds the classification of observed daily SLR (sea level pressure) fields in weather types that are most strongly associated with the presence/absence of rainfall in a set of index stations. The best results were obtained for winter rainfall for the West Coast, where a set of physically reasonable weather types could be identified, whereas for the East Coast the rainfall process seemed to be spatially less coherent. The GCM simulations were validated against observations in terms of probability of occurrence and survival time of these weather states. Some discrepancies werefound but there was no systematic bias, indicating that this behavior depends on the particular dynamics of each model. This classification method was then used for the generation of daily rainfall time series from the daily SLP fields from historical observation and from the GCM simulations. Whereas the mean rainfall and probability distributions were rather well replicated, the simulated dry periods were in all cases shorter than in the rainfall observations. The second rainfall generator is based on the analog method and uses information on the evolution of the SLP field in several previous days. It was found to perform reasonably well, although some downward bias in the simulated rainfall persistence was still present. Rainfall changes in a 2xCO 2 climate were investigated by applying both methods to the output of a greenhouse-gas experiment. The simulated precipitation changes were small. (orig.)

Variations of Sea Surface Temperature, Wind Stress, and Rainfall over the Tropical Atlantic and South America.

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Nobre, Paulo; Srukla, J.

1996-10-01

Empirical orthogonal functions (E0Fs) and composite analyses are used to investigate the development of sea surface temperature (SST) anomaly patterns over the tropical Atlantic. The evolution of large-scale rainfall anomaly patterns over the equatorial Atlantic and South America are also investigated. 71e EOF analyses revealed that a pattern of anomalous SST and wind stress asymmetric relative to the equator is the dominant mode of interannual and longer variability over the tropical Atlantic. The most important findings of this study are as follows.Atmospheric circulation anomalies precede the development of basinwide anomalous SST patterns over the tropical Atlantic. Anomalous SST originate off the African coast simultaneously with atmospheric circulation anomalies and expand westward afterward. The time lag between wind stress relaxation (strengthening) and maximum SST warming (cooling) is about two months.Anomalous atmospheric circulation patterns over northern tropical Atlantic are phase locked to the seasonal cycle. Composite fields of SLP and wind stress over northern tropical Atlantic can be distinguished from random only within a few months preceding the March-May (MAM) season. Observational evidence is presented to show that the El Niño-Southern Oscillation phenomenon in the Pacific influences atmospheric circulation and SST anomalies over northern tropical Atlantic through atmospheric teleconnection patterns into higher latitudes of the Northern Hemisphere.The well-known droughts over northeastern Brazil (Nordeste) are a local manifestation of a much larger-scale rainfall anomaly pattern encompassing the whole equatorial Atlantic and Amazon region. Negative rainfall anomalies to the south of the equator during MAM, which is the rainy season for the Nordeste region, are related to an early withdrawal of the intertropical convergence zone toward the warm SST anomalies over the northern tropical Atlantic. Also, it is shown that precipitation anomalies

Tropical influence on Euro-Asian autumn rainfall variability

Energy Technology Data Exchange (ETDEWEB)

Mariotti, A. [University of Maryland, College Park, MD (United States); ENEA, Rome (Italy); Ballabrera-Poy, J. [University of Maryland, ESSIC, College Park, MD (United States); Zeng, N. [University of Maryland, ESSIC, College Park, MD (United States); University of Maryland, Department of Meteorology,, College Park, MD (United States)

2005-04-01

The connection between autumn rainfall variability in the Euro-Asian domain and tropical climate is documented using state-of-the-art global observational datasets and re-analyses. Results suggest a robust statistical relationship between the El Nino Southern Oscillation (ENSO) and autumn rainfall in parts of southwest Europe, northern Africa and southwest Asia. The correlation between area-mean anomalies over this region (P{sub ea}) and the NINO3.4 index is 0.68, stationary over the last 50 years. Global ENSO-like tropical climate anomalies are observed in conjunction with P{sub ea} anomalies confirming the relationship found with the NINO3.4 index. Overall, the connection with Indo-Pacific variability is stronger than that with the eastern Pacific.While rainfall anomalies in southwest Europe and southwest Asia appear to largely co-vary as one pattern under the influence of ENSO, our results suggest that different mechanisms may be contributing to the observed anomalies. In the North Atlantic/European region, it is speculated that while a PNA-like mode maybe the prevailing teleconnection mechanism for high P{sub ea}, for low P{sub ea} tropical Atlantic ENSO related SST anomalies may be playing a more relevant role forcing northeastward propagating Rossby waves. Over southwest Asia, a more direct connection to the Indo-Pacific region is suggested by the upper air anomaly observed over southern Asia, possibly the Rossby wave response to enhanced heating in the Indian Ocean. (orig.)

Flowering phenology in the arid winter rainfall region of southern Africa

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M. Struck

1994-10-01

Full Text Available The impact of physical factors on the flowering phenology of a succulent karroid community in the winter rainfall region of the northwestern Cape, South Africa, based upon a three year study on permanent plots, is examined, (in the permanent plots, flowering of the shrubby species extended over a period of 4 to 4'/i> months each year, while blooming ot the therophytes peaked m the first half of the flowering season. Species composition and numbers of individuals in the therophytes and geophytes offering flowers varied greatly according to the pattern and amount of seasonal precipitation. Despite these variations a consistent flowering sequence between the years was observed. Possible relations between the flowering phenology and the climatic variables are discussed in detail. The present data suggest that the onset of flowering is determined indirectly by the first drop in temperature in autumn, indicating the beginning of the rainy season and presumably the start of the growing period, and/or by the increase of temperatures in the beginning of spring. The pattern and amount of rainfall within a given season mainly influenced the duration of anthesis and the number of flowers produced.

Erosividade e padrões hidrológicos de precipitação no Agreste Central pernambucano Erosivity and rainfall hydrological patterns in the Pernambuco Central 'Agreste'

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Thais E. M. dos Santos

2012-08-01

Full Text Available A principal forma de erosão nas condições brasileiras é a causada pela energia cinética do impacto das gotas de chuva sobre a superfície do solo, desencadeando o processo de erosão hídrica. Desenvolveu-se o presente trabalho com o objetivo de avaliar o índice de erosividade (EI30 e caracterizar o padrão hidrológico das chuvas do Agreste Central pernambucano, considerando-se uma série de 29 anos de dados, ficando patente que o primeiro semestre do ano é caracterizado pela ocorrência de chuvas de elevado potencial erosivo. O valor do fator "R" da equação universal de perda de solo para a região estudada é de 2.779,79 MJ mm ha-1 h-1. O padrão de chuva de maior ocorrência é o avançado, seguido do intermediário e atrasado, com 46,57; 36,38 e 17,19% dos totais de chuvas erosivas analisados, respectivamente. Não foram encontradas correlações significativas entre erosividade, coeficiente de chuva e precipitação.The main form of erosion in Brazilian conditions is caused by the kinetic energy of the impact of raindrops on the soil surface, triggering the erosion process. The present study was conducted with the aim to evaluate the erosivity index (EI30, as well as to characterize the hydrological pattern of rainfall in the Pernambuco Central 'Agreste', considering a series of 29 years of data. It was found that the first half of the year is characterized by rain with high erosive potential. The value of the factor "R" in the Universal equation of soil loss for the studied region is 2,779.79 MJ mm ha-1 h-1. The rain pattern of higher occurrence is the advanced, followed by intermediate and delayed, with 46.57; 36.38 and 17.19% of total erosive rainfall analyzed, respectively. There were no significant correlations between erosivity, rainfall coefficient and precipitation.

Recent trends in rainfall and temperature over North West India during 1871-2016

Science.gov (United States)

Saxena, Rani; Mathur, Prasoon

2018-03-01

Rainfall and temperature are the most important environmental factors influencing crop growth, development, and yield. The northwestern (NW) part of India is one of the main regions of food grain production of the country. It comprises of six meteorological subdivisions (Haryana, Punjab, West Rajasthan, East Rajasthan, Gujarat and Saurashtra, Kutch and Diu). In this study, attempts were made to study variability and trends in rainfall and temperature during 30-year climate normal periods (CN) and 10-year decadal excess or deficit rainfall frequency during the historical period from 1871 to 2016. The Mann-Kendall and Spearman's rank correlation (Spearman's rho) tests were used to determine significance of trends. Least square linear fitting method was adopted to find out the slopes of the trend lines. The long-term mean annual rainfall over North West India is 587.7 mm (standard deviation of 153.0 mm and coefficient of variation 26.0). There was increasing trend in minimum and maximum temperatures during post monsoon season in entire study period and current climate normal period (1991-2016) due to which the sowing of rabi season crops may be delayed and there may be germination problem too. There was a non-significant decreasing trend in rainfall during monsoon season and an increasing trend in rainfall during post monsoon over North West India during entire study period. During current CN5 (1991-2016), all the subdivision (except the Saurashtra region) showed a decreasing trend in rainfall during monsoon season which is a matter of concern for kharif crops and those rabi crops which are grown as rainfed on conserved soil moisture. The decadal annual and seasonal frequencies of excess and deficit years results revealed that the annual total deficit rainfall years (24) exceeded total excess rainfall years (22) in North West India during the entire study period. While during the current decadal period (2011 to 2016), single year was the excess year and 2 years were

Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

Science.gov (United States)

Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

2016-12-01

Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

Dry/Wet Conditions Monitoring Based on TRMM Rainfall Data and Its Reliability Validation over Poyang Lake Basin, China

Directory of Open Access Journals (Sweden)

Xianghu Li

2013-11-01

Full Text Available Local dry/wet conditions are of great concern in regional water resource and floods/droughts disaster risk management. Satellite-based precipitation products have greatly improved their accuracy and applicability and are expected to offer an alternative to ground rain gauges data. This paper investigated the capability of Tropical Rainfall Measuring Mission (TRMM rainfall data for monitoring the temporal and spatial variation of dry/wet conditions in Poyang Lake basin during 1998–2010, and validated its reliability with rain gauges data from 14 national meteorological stations in the basin. The results show that: (1 the daily TRMM rainfall data does not describe the occurrence and contribution rates of precipitation accurately, but monthly TRMM data have a good linear relationship with rain gauges rainfall data; (2 both the Z index and Standardized Precipitation Index (SPI based on monthly TRMM rainfall data oscillate around zero and show a consistent interannual variability as compared with rain gauges data; (3 the spatial pattern of moisture status, either in dry months or wet months, based on both the Z index and SPI using TRMM data, agree with the observed rainfall. In conclusion, the monthly TRMM rainfall data can be used for monitoring the variation and spatial distribution of dry/wet conditions in Poyang Lake basin.

Variability of rainfall over small areas

Science.gov (United States)

Runnels, R. C.

1983-01-01

A preliminary investigation was made to determine estimates of the number of raingauges needed in order to measure the variability of rainfall in time and space over small areas (approximately 40 sq miles). The literature on rainfall variability was examined and the types of empirical relationships used to relate rainfall variations to meteorological and catchment-area characteristics were considered. Relations between the coefficient of variation and areal-mean rainfall and area have been used by several investigators. These parameters seemed reasonable ones to use in any future study of rainfall variations. From a knowledge of an appropriate coefficient of variation (determined by the above-mentioned relations) the number rain gauges needed for the precise determination of areal-mean rainfall may be calculated by statistical estimation theory. The number gauges needed to measure the coefficient of variation over a 40 sq miles area, with varying degrees of error, was found to range from 264 (10% error, mean precipitation = 0.1 in) to about 2 (100% error, mean precipitation = 0.1 in).

Analysis of rainfall infiltration law in unsaturated soil slope.

Science.gov (United States)

Zhang, Gui-rong; Qian, Ya-jun; Wang, Zhang-chun; Zhao, Bo

2014-01-01

In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering the characteristics of slope and rainfall, the key factors affecting rainfall infiltration of slope, including hydraulic properties, water storage capacity (θs - θr), soil types, rainfall intensities, and antecedent and subsequent infiltration rates on unsaturated soil slope, are discussed by using theory analysis and numerical simulation technology. Based on critical factors changing, this paper presents three calculation models of rainfall infiltrability for unsaturated slope, including (1) infiltration model considering rainfall intensity; (2) effective rainfall model considering antecedent rainfall; (3) infiltration model considering comprehensive factors. Based on the technology of system response, the relationship of rainfall and infiltration is described, and the prototype of regression model of rainfall infiltration is given, in order to determine the amount of rain penetration during a rain process.

Patterns of species richness and abundance among cactus communities receiving different rainfall levels in the semiarid region of Brazil

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Paulo Sérgio Monteiro Ferreira

Full Text Available ABSTRACT This study examines the variation in cacti species richness and abundance among sites with different average rainfall and soil types. We assessed a total of 3,660 individuals of six species of Cactaceae: Cereus jamacaru, Melocactus zehntneri, Pilosocereus gounellei, Pilosocereus pachycladus, Tacinga inamoena, and Tacinga palmadora. The greatest species richness and abundance of cacti were at locations with low rainfall and more clayey soils. The species studied differed in multidimensional representation, with some species being more positively related to soils with a higher proportion of fine particles (M. zehntneri and P. gounellei, while others were negatively related to soils with a higher proportion of coarser particles (T. inamoena or positively related to areas with higher rainfall and vegetation cover (C. jamacaru and P. pachycladus. The differential responses of the species of Cactaceae studied in relation to the gradients analyzed demonstrates the need for more research into the relationship between cacti and environmental variables in semiarid ecosystems with high environmental heterogeneity.

EVALUATION OF RAINFALL-RUNOFF EROSIVITY FACTOR FOR CAMERON HIGHLAND, PAHANG, MALAYSIA

Directory of Open Access Journals (Sweden)

Abdulkadir Taofeeq Sholagberu

2016-07-01

Full Text Available Rainfall-runoff is the active agent of soil erosion which often resulted in land degradation and water quality deterioration. Its aggressiveness to induce erosion is usually termed as rainfall erosivity index or factor (R. R-factor is one of the factors to be parameterized in the evaluation of soil loss using the Universal Soil Loss Equation and its reversed versions (USLE/RUSLE. The computation of accurate R-factor for a particular watershed requires high temporal resolution rainfall (pluviograph data with less than 30-minutes intensities for at least 20 yrs, which is available only in a few regions of the world. As a result, various simplified models have been proposed by researchers to evaluate R-factor using readily available daily, monthly or annual precipitation data. This study is thus aimed at estimating R-factor and to establish an approximate relationship between R-factor and rainfall for subsequent usage in the estimation of soil loss in Cameron highlands watershed. The results of the analysis showed that the least and peak (critical R-factors occurred in the months of January and April with 660.82 and 2399.18 MJ mm ha-1 h-1year-1 respectively. Also, it was observed that erosivity power starts to increase from the month of January through April before started falling in the month of July. The monthly and annual peaks (critical periods may be attributed to increased rainfall amount due to climate change which in turn resulted to increased aggressiveness of rains to cause erosion in the study area. The correlation coefficient of 0.985 showed that there was a strong relationship rainfall and R-factor.

Effect of monthly areal rainfall uncertainty on streamflow simulation

Science.gov (United States)

Ndiritu, J. G.; Mkhize, N.

2017-08-01

Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic

Probabilistic clustering of rainfall condition for landslide triggering

Science.gov (United States)

Rossi, Mauro; Luciani, Silvia; Cesare Mondini, Alessandro; Kirschbaum, Dalia; Valigi, Daniela; Guzzetti, Fausto

2013-04-01

Landslides are widespread natural and man made phenomena. They are triggered by earthquakes, rapid snow melting, human activities, but mostly by typhoons and intense or prolonged rainfall precipitations. In Italy mostly they are triggered by intense precipitation. The prediction of landslide triggered by rainfall precipitations over large areas is commonly based on the exploitation of empirical models. Empirical landslide rainfall thresholds are used to identify rainfall conditions for the possible landslide initiation. It's common practice to define rainfall thresholds by assuming a power law lower boundary in the rainfall intensity-duration or cumulative rainfall-duration space above which landslide can occur. The boundary is defined considering rainfall conditions associated to landslide phenomena using heuristic approaches, and doesn't consider rainfall events not causing landslides. Here we present a new fully automatic method to identify the probability of landslide occurrence associated to rainfall conditions characterized by measures of intensity or cumulative rainfall and rainfall duration. The method splits the rainfall events of the past in two groups: a group of events causing landslides and its complementary, then estimate their probabilistic distributions. Next, the probabilistic membership of the new event to one of the two clusters is estimated. The method doesn't assume a priori any threshold model, but simple exploits the real empirical distribution of rainfall events. The approach was applied in the Umbria region, Central Italy, where a catalogue of landslide timing, were obtained through the search of chronicles, blogs and other source of information in the period 2002-2012. The approach was tested using rain gauge measures and satellite rainfall estimates (NASA TRMM-v6), allowing in both cases the identification of the rainfall condition triggering landslides in the region. Compared to the other existing threshold definition methods, the prosed