Total Seasonal Rainfall Research Articles

Understanding the Variations of the Length and the Seasonal Rainfall Anomalies of the Indian Summer Monsoon

AbstractThe canonical relationship between the length and the total seasonal rainfall anomalies of the Indian summer monsoon (ISM) is the association of the longer (shorter) season with wetter (drier) seasonal rainfall anomalies. This study shows that such canonical behavior is clearly associated with relatively strong ENSO SST anomalies in the eastern equatorial Pacific Ocean that appear in the boreal summer and fall seasons. The noncanonical relationship is caused by a longer (shorter) season associated with drier (wetter) ISM seasonal rainfall anomalies. A majority of these noncanonical seasons, with anomalously short season length but anomalously high seasonal mean rain, tend to occur under relatively weak La Niña forcing during the boreal summer season. Although the onset of such seasons occurs through canonical ENSO forcing of a large-scale meridional temperature gradient, the demise is dictated by the depletion of moist static energy from the underlying cooling of the upper ocean in the northern Indian Ocean. This is due to stronger meridional Ekman ocean heat transport forced by the stronger low-level atmospheric southwesterlies than those in the corresponding canonical wet ISM season.

Downscaling probabilistic seasonal climate forecasts for decision support in agriculture: A comparison of parametric and non-parametric approach

Abstract Seasonal climate forecasts (SCF) are produced operationally in tercile-probabilities of the most likely categories, e.g., below-, near- and above-normal rainfall. Inherently, these are difficult to translate into information useful for decision support in agriculture. For example, probabilistic SCF must first be downscaled to daily weather realizations to link with process-based crop models, a tedious process, especially for non-technical users. Here, we present two approaches for downscaling probabilistic seasonal climate forecasts – a parametric method, predictWTD, and a non-parametric method, FResampler1, and compare their performance. The predictWTD, which is based on a conditional stochastic weather generator, was found to be not very sensitive to types of rainfall information (amount, frequency or intensity) in constraining or conditioning the stochastic weather generator, but conditioning the stochastic weather generator on both rainfall frequency and rainfall intensity had distorted the distribution of the downscaled seasonal rainfall total. Both predictWTD and FResampler1 are sensitive to the length of climate data, especially for a wet SCF; climate data longer than 30 years was found suitable for reproducing the theoretical distribution of SCF. FResampler1 performed well as predictWTD in downscaling probabilistic SCF, however, it requires the generation of more realizations to ensure stable simulations of the seasonal rainfall total distributions.

Demonstrating Effect of Rainfall Characteristics on Wheat Yield: Case of Sinana District, South Eastern Ethiopia

Demonstrating Effects of Current and Projected Rainfall Characteristics on Wheat yield has been investigated in Sinana district for the period 1995-2016. Data on rainfall and crop yield for the period 1995-2016 were obtained from National Meteorological Agency and Sinana District Agricultural Offices, respectively. Following data quality checking, rainfall data (current and future), correlation and regression studies were analyzed using Statistical software like Instat V3.36 and SPSS V20. Downscaling the output of CSIRO-Mk3.6.0 GCM model (daily rainfall data) for RCP8.5 emission scenario using a web based software tool (Marksim GCM) for the period 2020-2049 were used to determine seasonal total rainfall and ascertain its impact on yield. This study used mean, coefficient of variation, correlation and regression analysis to ascertain the relation, cause and effect relationship between rainfall characteristics and wheat yields. The results indicated that the mean onset date of the main rainy season (JJAS) for Robe and Sinana station was June 30 and July 3. Furthermore, the results of Pearson Correlation Coefficients indicated that kiremt rainfall total (JJAS) had moderate positive relationship (r = 0.499) with wheat yield in the study area. It was also observed that nearly fifty percent of total variance of crop yield is explained jointly by kiremt rainfall total and rainy day (R2 value was 47.9%). The result of projected wheat yield indicated that there will be a slight decrease in wheat yield (qt/ha) after 2030 years due to the impact of expected weakening of kiremt rainfall total. Taking in to account the above findings, it could be suggested that the farmers’ community will be encouraged encouraged to utilize timely climate information issued from National Meteorological Agency of Ethiopia (NMA) and other centers for farm level decision to enhance their crop production.

Modelling cereal crops to assess future climate risk for family food self-sufficiency in southern Mali

Future climate change will have far reaching consequences for smallholder farmers in sub-Saharan Africa, the majority of whom depend on agriculture for their livelihoods. Here we assessed the farm-level impact of climate change on family food self-sufficiency and evaluated potential adaptation options of crop management. Using three years of experimental data on maize and millet from an area in southern Mali representing the Sudano-Sahelian zone of West Africa we calibrated and tested the Agricultural Production Systems sIMulator (APSIM) model. Changes in future rainfall, maximum and minimum temperature and their simulated effects on maize and millet yield were analysed for climate change predictions of five Global Circulation Models (GCMs) for the 4.5 Wm−2 and 8.5 Wm−2 radiative forcing scenario (rcp4.5 and rcp8.5). In southern Mali, annual maximum and minimum temperatures will increase by 2.9 °C and 3.3 °C by the mid-century (2040–2069) as compared with the baseline (1980–2009) under the rcp4.5 and rcp8.5 scenario respectively. Predicted changes in the total seasonal rainfall differed between the GCMs, but on average, seasonal rainfall was predicted not to change. By mid-century maize grain yields were predicted to decrease by 51% and 57% under current farmer's fertilizer practices in the rcp4.5 and rcp8.5 scenarios respectively. APSIM model predictions indicated that the use of mineral fertilizer at recommended rates cannot fully offset the impact of climate change but can buffer the losses in maize yield up to 46% and 51% of the baseline yield. Millet yield losses were predicted to be less severe under current farmer's fertilizer practices by mid-century i.e. 7% and 12% in the rcp4.5 and rcp8.5 scenario respectively. Use of mineral fertilizer on millet can offset the predicted yield losses resulting in yield increases under both emission scenarios. Under future climate and current cropping practices, food availability is expected to reduce for all farm types in southern Mali. However, large and medium-sized farms can still achieve food self–sufficiency if early planting and recommended rates of fertilizer are applied. Small farms, which are already food insecure, will experience a further decrease in food self-sufficiency, with adaptive measures of early planting and fertilizer use unable to help them achieve food self-sufficiency. By taking into account the diversity in farm households that is typical for the region, we illustrated that crop management strategies must be tailored to the capacity and resource endowment of local farmers. Our place-based findings can support decision making by extension and development agents and policy makers in the Sudano-Sahelian zone of West Africa. (Resume d'auteur)

Impacts of Some Climatic Variables on Productivity of Boro rice in South-Western Coastal Regions of Bangladesh

Climate change is the top most important issue in the modern world. Various aspects of Bangladesh are verily affected by climate change. An agro-climatic study was conducted in Khulna, Satkhira and Bagerhat district in Khulna division as well as the Southwestern coastal part of Bangladesh with last 30 (1981-2011) years of some climatic data of average temperature, maximum temperature, seasonal total rainfall, average humidity and sea level pressure to address the climatic variability and its impacts on Boro rice production in Southwestern coastal part of Bangladesh. The average temperature increased by 0.51°C in Boro season in this area. The sea level pressure was about stable here. The Boro rice production increased by 0.04 and 0.3 tha-1 in Khulna and Bagerhat district. However most of the time the production showed increasing trends except in 2007 and 2009 affected by two devastating natural calamities as “SIDR” and “AILA” occurred in these two year respectively.J. Environ. Sci. & Natural Resources, 9(1): 95-98 2016

Contribution of Monthly and Regional Rainfall to the Strength of Indian Summer Monsoon

Indian summer monsoon rainfall (ISMR; June–September) has both temporal and spatial variability causing floods and droughts in different seasons and locations, leading to a strong or weak monsoon. Here, the authors present the contribution of all-India monthly, seasonal, and regional rainfall to the ISMR, with an emphasis on the strong and weak monsoons. Here, regional rainfall is restricted to the seasonal rainfall over four regions defined by the India Meteorological Department (IMD) primarily for the purpose of forecasting regional rainfall: northwest India (NWI), northeast India (NEI), central India (CI), and south peninsula India (SPIN). In this study, two rainfall datasets provided by IMD are used: 1) all-India monthly and seasonal (June–September) rainfall series for the entire Indian subcontinent as well as seasonal rainfall series for the four homogeneous regions for the period 1901–2013 and 2) the latest daily gridded rainfall data for the period 1951–2014, which is used for assessment at the extent to which the four regions are appropriate for the intended purpose. Rainfall during July–August contributes the most to the total seasonal rainfall, regardless of whether it is a strong or weak monsoon. Although NEI has the maximum area-weighted rainfall, its contribution is the least toward determining a strong or weak monsoon. It is the rainfall in the remaining three regions (NWI, CI, and SPIN) that controls whether an ISMR is strong or weak. Compared to monthly rainfall, regional rainfall dominates the strong or weak rainfall periods.

Comparison of different statistical downscaling methods for climate change rainfall projections over the Lake Victoria basin considering CMIP3 and CMIP5

Abstract In this study, outputs of three statistical downscaling (SD) methods including the change factor (Delta), simplified (simQP) and advanced (wetQP) quantile-perturbation-based approaches were compared based on daily rainfall series at 9 meteorological stations in the Lake Victoria basin (LVB) in Eastern Africa. The comparison was made considering phase 5 and phase 3 of the Coupled Model Inter-comparison Project, i.e. CMIP5 and CMIP3 respectively. For the CMIP5 (CMIP3) at each station, there were a total of 7 (14) GCMs, 18 (20) daily historical (control) simulations over the period 1961–2000, and 35 (49) daily future projection series of the periods 2050s and 2090s. The ensemble mean of the GCMs' Bias in reproducing rainfall extremes for return periods in the range of 1 to 40 years for the CMIP5 (CMIP3) varied from −19.05% to 3.11% (−65.85% to −4.86%). For the high greenhouse gas scenario rcp8.5 (A2) of the CMIP5 (CMIP3), the ensemble mean of the projected changes over the LVB in the 10-year rainfall intensity quantile obtained from the Delta, simQP, wetQP SD goes up to 5.8, 10 and 22.4% (11.7, 15.9 and 43.6%) in the 2050s and 8, 11.4, and 25.4% (14.2, 23.3 and 40.6%) in the 2090s. Rainfall totals of the main wet (dry) season are generally projected to increase (decrease) in both the 2050s and 2090s. Because the outputs from the three SD methods captured well the pattern of monthly rainfall totals, the difference between the projected changes of seasonal or annual rainfall totals from the Delta, simQP and wetQP was shown to be insignificant. However, the differences in the results from the Delta, simQP and wetQP methods with respect to the projections of rainfall quantiles indicate that the choice of the SD method can be made on a case by case basis in line with the objectives of the climate change impact study, e.g. the Delta does not capture well the changes in rainfall extremes, whereas the wetQP is suitable for both rainfall extremes and rainfall totals at both seasonal and annual time scales. The findings of this study also show the need to consider evaluations of the inter-GCM differences in the LVB as a data scarce region in assessing the discernible impact of climate change on rainfall extremes and/totals for decision making related to water resources management and engineering.

Impacts of Some Climatic Variables on the Seasonal Productivity of Aman Rice at Dhaka Region, Central Part of Bangladesh

An agro-climatic study was conducted at Dhaka region of Bangladesh using 43 years (1970-2012) of climatic data (daily maximum temperature, seasonal total rainfall, daily average humidity, and daily sunshine hour) to observe the climatic variability and their impacts on the productivity of Aman rice. The average maximum temperature increased by 0.04°C in Aman season in Dhaka region. The average sunshine hours decreased by 0.05 in the season. The average humidity decreased by 0.14% in the season. The average seasonal rainfall increased slightly by 0.09 mm in the season. The Aman rice production increased by 0.03 t ha-1 in the region. The production year 2003 shows highest productivity due to less climatic devastation impact on the seasonal productivity of the rice. The climatic variables impact ( Savg > Havg > Tmax ) implies the seasonal productivity of Aman rice was mostly and inversely correlated with average sunshine (Savg) hour. However, most of the time the production showed increasing trend except some devastating natural calamities in the year of 1988 and 1998 which affected crop production seriously.J. Environ. Sci. & Natural Resources, 8(2): 7-10 2015

An empirical investigation of climate and land-use effects on water quantity and quality in two urbanising catchments in the southern United Kingdom

Using historical data of climate, land-use, hydrology and water quality from four catchments located in the south of England, this study identifies the impact of climate and land-use change on selected water quantity and water quality indicators. The study utilises a paired catchment approach, with two catchments that have experienced a high degree of urbanisation over the past five decades and two nearby, hydrologically similar, but undeveloped catchments. Multivariate regression models were used to assess the influence of rainfall and urbanisation on runoff (annual and seasonal), dissolved oxygen levels and temperature. Results indicate: (i) no trend in annual or seasonal rainfall totals, (ii) upward trend in runoff totals in the two urban catchments but not in the rural catchments, (iii) upward trend in dissolved oxygen and temperature in the urban catchments, but not in the rural catchments, and (iv) changes in temperature and dissolved oxygen in the urban catchments are not driven by climatic variables.

Interannual variability of rainfall characteristics over southwestern Madagascar

The interannual variability of daily frequency of rainfall [>1 mm/day] and heavy rainfall [>30 mm/day] is studied for the southwestern region of Madagascar, which is relatively arid compared to the rest of the island. Attention is focused on the summer rainy season from December to March at four stations (Morondava, Ranohira, Toliara and Taolagnaro), whose daily rainfall data covering the period 1970–2000 were obtained from the Madagascar Meteorological Service. El Nino Southern Oscillation (ENSO) was found to have a relatively strong correlation with wet day frequency at each station and, particularly, for Toliara in the extreme southwest. In terms of seasonal rainfall totals, most El Nino (La Nina) summers receive below (above) average amounts. An ENSO connection with heavy rainfall events was less clear. However, for heavy rainfall events, the associated atmospheric circulation displays a Southern Annular Mode-like pattern throughout the hemisphere. For ENSO years and the neutral seasons 1979/80, 1981/82 which had large anomalies in wet day frequency, regional atmospheric circulation patterns consisted of strong anomalies in low-level moisture convergence and uplift over and near southwestern Madagascar that made conditions correspondingly more or less favourable for rainfall. Dry (wet) summers in southern Madagascar were also associated with an equatorward (poleward) displacement of the ITCZ in the region.

Towards Climate-Smart Agricultural Approach: Prospect for Smallholder Farmers in Semi-Arid Regions

Towards Climate-Smart Agricultural Approach: Prospect for Smallholder Farmers in Semi-Arid Regions Lavhelesani Rodney Managa, Nolitha Nkobole-Mhlongo Abstract Climate change has become a major threat to human developmental sectors in recent times. Agriculture is particularly vulnerable sector because it is highly dependent on climate variables. General decrease in total seasonal rainfall, accompanied by more frequent in-season dry spells are pervasive to sub-Saharan Africa, and significantly impact on crop and livestock production, and hence hamper food security in the region. The hardest hit by climate change is the rural smallholder farmers in the drier areas, owing to adaptive capacity and limited resources. As to carter the adaption needs of smallholder farmers to climate change, climate-smart agricultural approach provides much needed potential. However, to efficiently achieve climate-smart agriculture, evidence-base, and location specific framework that unpack complexity and define precise implementation pathway is urgently needed. This paper therefore, reviewed prospect of present and future climates change implications to smallholder farmers in developing countries. Thereafter, it drew upon a variety of current adaptation strategies within concept of climate smart agriculture, and assess the required support to increase the adaptive capacity of smallholder farmers’ in semi-arid regions Full Text: PDF DOI: 10.15640/jaes.v4n2a5

Meteo-climatic analysis during the period 1984 – 2014 in Rome area (Central Italy)

In this paper rainfall trends and a seasonal distribution model of the period 1984-2014 for the urban area of Rome and surroundings are presented using the available data of 46 rain gauge stations. The average annual precipitation is 793 mm in the urban area and increases up to 945 mm in the surrounding hilly areas. The seasonal distribution of the isohyets is almost homogeneous, increasing from plain towards hilly areas. The scattered variability of annual rainfall does not allow the recognition of trends and cyclic tendencies, with the exception of seasonal variations. Nevertheless, the rainfall analysis highlights an increasing trend in winter and, to a lesser significant extent, in summer, while a decreasing tendency characterizes autumns and, definitely less spring periods. The annual rainfall time series analysis show significant changes for 28% out of the 46 stations considered, i.e.: descending to ascending trends or increasing of average values concomitant to the absence of significant trends. The plots of three-monthly (seasonal) total rainfall values show, for most of the rainfall stations, a winter season characterized by a negative to positive tendency inversion around 1993. According to the qualitative classification of the Seasonal Index (SI), the study area sectors fall between the classes “uniform but with a clear wet season” (SI=0.20-0.39) and “fairly seasonal with a minor dry season” (SI=0.40-0.59).The analysis of the rainfall was further developed by spatial elaboration of long-term trends derived from the data analysis of the Standard Precipitation Index (SPI), aggregated at annual, semiannual and quarterly scale.The analysis of the temperature data of 21 stations for the period 1984-2014 highlighted that, generally, isotherms follow the topographic elevations and the existence of an area, coinciding with the metropolitan area of Rome, characterized by temperatures greater than those of the surroundings.

A Bayesian Hidden Markov Model of Daily Precipitation over South and East Asia

Abstract A Bayesian hidden Markov model (HMM) for climate downscaling of multisite daily precipitation is presented. A generalized linear model (GLM) component allows exogenous variables to directly influence the distributional characteristics of precipitation at each site over time, while the Markovian transitions between discrete states represent seasonality and subseasonal weather variability. Model performance is evaluated for station networks of summer rainfall over the Punjab region in northern India and Pakistan and the upper Yangtze River basin in south-central China. The model captures seasonality and the marginal daily distributions well in both regions. Extremes are reproduced relatively well in the Punjab region, but underestimated for the Yangtze. In terms of interannual variability, the combined GLM–HMM with spatiotemporal averages of observed rainfall as a predictor is shown to exhibit skill (in terms of reduced RMSE) at the station level, particularly for the Punjab region. The skill is largest for dry-day counts, moderate for seasonal rainfall totals, and very small for the number of extreme wet days.

Prediction of inflows into Lake Kariba using a combination of physical and empirical models

ABSTRACTSeasonal climate forecasts are operationally produced at various climate prediction centres around the world. However, these forecasts may not necessarily be appropriately integrated into application models in order to help with decision‐making processes. This study investigates the use of a combination of physical and empirical models to predict seasonal inflows into Lake Kariba in southern Africa. Two predictions systems are considered. The first uses antecedent seasonal rainfall totals over the upper Zambezi catchment as predictor in a statistical model for estimating seasonal inflows into Lake Kariba. The second and more sophisticated method uses predicted low‐level atmospheric circulation of a coupled ocean–atmosphere general circulation model (CGCM) downscaled to the inflows. Forecast verification results are presented for five run‐on 3‐month seasons; from September to June over an independent hindcast period of 14 years (1995/1996 to 2008/2009). Verification is conducted using the relative operating characteristic (ROC) and the reliability diagram. In addition to the presented verification statistics, the hindcasts are also evaluated in terms of their economic value as a usefulness indicator of forecast quality for bureaucrats and to the general public. The models in general perform best during the austral mid‐summer season of DJF (seasonal onset of inflows) and the autumn season of MAM (main inflow season). Moreover, the prediction system that uses the output of the CGCM is superior to the simple statistical approach. An additional forecast of a recent flooding event (2010/2011), which lies outside of the 14‐year verification window, is presented to demonstrate the forecast system's operational capability further during a season of high inflows that caused societal and infrastructure problems over the region.

Propagation of Strong Rainfall Events from Southeastern South America to the Central Andes

Abstract Based on high-spatiotemporal-resolution data, the authors perform a climatological study of strong rainfall events propagating from southeastern South America to the eastern slopes of the central Andes during the monsoon season. These events account for up to 70% of total seasonal rainfall in these areas. They are of societal relevance because of associated natural hazards in the form of floods and landslides, and they form an intriguing climatic phenomenon, because they propagate against the direction of the low-level moisture flow from the tropics. The responsible synoptic mechanism is analyzed using suitable composites of the relevant atmospheric variables with high temporal resolution. The results suggest that the low-level inflow from the tropics, while important for maintaining sufficient moisture in the area of rainfall, does not initiate the formation of rainfall clusters. Instead, alternating low and high pressure anomalies in midlatitudes, which are associated with an eastward-moving Rossby wave train, in combination with the northwestern Argentinean low, create favorable pressure and wind conditions for frontogenesis and subsequent precipitation events propagating from southeastern South America toward the Bolivian Andes.

Interannual variability of seasonal rainfall over the Cape south coast of South Africa and synoptic type association

The link between interannual variability of seasonal rainfall over the Cape south coast of South Africa and different synoptic types as well as selected teleconnections is explored. Synoptic circulation over the region is classified into different synoptic types by employing a clustering technique, the self-organizing map (SOM), on daily circulation data for the 33-year period from 1979 to 2011. Daily rainfall data are used to investigate interannual variability of seasonal rainfall within the context of the identified synoptic types. The anomalous frequency of occurrence of the different synoptic types for wet and for dry seasons differs significantly within the SOM space, except for austral spring. The main rainfall-producing synoptic types are to a large extent consistent for wet and dry seasons. The main rainfall-producing synoptic types have a notable larger contribution to seasonal rainfall totals during wet seasons than during dry seasons, consistent with a higher frequency of occurrence of the main rainfall-producing synoptic types during wet seasons compared to dry seasons. Dry seasons are characterized by a smaller contribution to seasonal rainfall totals by all the different synoptic types, but with the largest negative anomalies associated with low frequencies of the main rainfall-producing synoptic types. The frequencies of occurrence of specific configurations of ridging high pressure systems, cut-off lows and tropical-temperate troughs associated with rainfall are positively linked to interannual variability of seasonal rainfall. It is also shown that the distribution of synoptic types within the SOM space is linked to the Southern Annular Mode and El Nino Southern Oscillation, implying some predictability of intraseasonal variability at the seasonal time scale.

The Impacts of California’s San Francisco Bay Area Gap on Precipitation Observed in the Sierra Nevada during HMT and CalWater

Abstract Atmospheric rivers (ARs) are narrow regions of enhanced water vapor transport, usually found on the warm-sector side of the polar cold front in many midlatitude storms formed primarily over the oceans. Nonbrightband (NBB) rain is a shallow orographic rainfall process driven by collision and coalescence that has been observed in some of these storms. NBB rain accounts for about one-third, on average, of the total winter season rainfall occurring at a coastal mountain site in Northern California. During the California Energy Commission’s CalWater project, nearly the same fraction of NBB rain was observed at a northern Sierra Nevada foothills site as compared to the coastal mountains, whereas less than half of the fractional amount of NBB rain was observed at a southern Sierra Nevada foothills site. Both Sierra Nevada sites often experience terrain-induced blocked flow, that is, Sierra barrier jet (SBJ) during landfalling winter storms. However, the northern Sierra Nevada site often is oriented geographically downwind of a gap in the coastal terrain near San Francisco during AR landfall. This gap allows maritime air in the AR to arrive at the northern site and enhance the collision–coalescence process in orographic feeder clouds as compared with the southern site. As a result, a greater amount and intensity of NBB rain and overall precipitation was produced at the northern site. This study uses a variety of observations collected in the coastal and Sierra Nevada ranges from the Hydrometeorology Testbed and CalWater field campaigns to document this behavior. A detailed case study provides additional context on the interaction between AR flow, the SBJ, and precipitation processes.

Assessing the skill of precipitation forecasts on seasonal time scales over East Africa from a Climate Forecast System model

It is becoming increasingly important to be able to verify the skill of precipitation forecasts, especially with the advent of high-resolution numerical weather prediction models. This study focused on assessing the skill of climate forecast system (CFS) model in predicting rainfall on seasonal time scales over East Africa region for the period January 1981 to December 2009. The rainfall seasons considered were March to May (MAM) and October to December (OND). The data used in the study included the observed seasonal rainfall totals from January 1981 to December 2009 and CFS model forecast data for the same period. The model had 15 Runs. The measure of skill employed was the categorical skill scores and included Heidke skill scores, bias, probability of detection and false alarm ratio. The results from the categorical skill scores confirmed relatively higher skills during OND season as compared to MAM. When compared with individual Runs, the mean of all the 15 Runs depicted relatively higher accuracy during OND season. Some individual Runs – 1, 7, 9 and 10 – also performed better during OND season. During MAM season, the mean of all the 15 Runs showed relatively lower accuracy in predicting rainfall. Some individual Runs – 5, 10, 12 and 14 – performed better than the mean of all the 15 Runs. The prediction of seasonal rainfall over East Africa region using CFS model depends on the season considered. During MAM, the prediction of seasonal rainfall is better as Runs are fewer, which showed relatively higher averaged skills; on the other hand, during OND the prediction of seasonal rainfall is better when using the mean of all the 15 Runs.

Spatial and temporal variability of rainfall in the Nile Basin

Abstract. Spatiotemporal variability in annual and seasonal rainfall totals were assessed at 37 locations of the Nile Basin in Africa using quantile perturbation method (QPM). To get insight into the spatial difference in rainfall statistics, the stations were grouped based on the pattern of the long-term mean (LTM) of monthly rainfall and that of temporal variability. To find the origin of the driving forces for the temporal variability in rainfall, correlation analyses were carried out using global monthly sea level pressure (SLP) and sea surface temperature (SST). Further investigations to support the obtained correlations were made using a total of 10 climate indices. It was possible to obtain three groups of stations; those within the equatorial region (A), Sudan and Ethiopia (B), and Egypt (C). For group A, annual rainfall was found to be below (above) the reference during the late 1940s to 1950s (1960s to mid-1980s). Conversely for groups B and C, the period from 1930s to late 1950s (1960s to 1980s) was characterized by anomalies being above (below) the reference. For group A, significant linkages were found to Niño 3, Niño 3.4, and the North Atlantic Ocean and Indian Ocean drivers. Correlations of annual rainfall of group A with Pacific Ocean-related climate indices were inconclusive. With respect to the main wet seasons, the June–September rainfall of group B has strong connection to the influence from the Indian Ocean. For the March–May (October–February) rainfall of group A (C), possible links to the Atlantic and Indian oceans were found.

Spatiotemporal characteristics and synchronization of extreme rainfall in South America with focus on the Andes Mountain range

The South American Andes are frequently exposed to intense rainfall events with varying moisture sources and precipitation-forming processes. In this study, we assess the spatiotemporal characteristics and geographical origins of rainfall over the South American continent. Using high-spatiotemporal resolution satellite data (TRMM 3B42 V7), we define four different types of rainfall events based on their (1) high magnitude, (2) long temporal extent, (3) large spatial extent, and (4) high magnitude, long temporal and large spatial extent combined. In a first step, we analyze the spatiotemporal characteristics of these events over the entire South American continent and integrate their impact for the main Andean hydrologic catchments. Our results indicate that events of type 1 make the overall highest contributions to total seasonal rainfall (up to $$50\,\%$$ ). However, each consecutive episode of the infrequent events of type 4 still accounts for up to $$20\,\%$$ of total seasonal rainfall in the subtropical Argentinean plains. In a second step, we employ complex network theory to unravel possibly non-linear and long-ranged climatic linkages for these four event types on the high-elevation Altiplano-Puna Plateau as well as in the main river catchments along the foothills of the Andes. Our results suggest that one to two particularly large squall lines per season, originating from northern Brazil, indirectly trigger large, long-lasting thunderstorms on the Altiplano Plateau. In general, we observe that extreme rainfall in the catchments north of approximately $$20^{\circ }$$ S typically originates from the Amazon Basin, while extreme rainfall at the eastern Andean foothills south of $$20^{\circ }$$ S and the Puna Plateau originates from southeastern South America.