Spatiotemporal Variability Of Rainfall Research Articles

Spatio-temporal variability of precipitation from 1980 to 2021 within the Oum Er Rbia hydraulic basin (Morocco)

Abstract The aim of this work is to assess the spatio-temporal variability of the mean annual rainfall during the last four decades within the Oum Er Rbia hydraulic basin. The used database in this study consists with a series of rainfall data at different time scale. These data were subjected to statistical and cartographic analysis. The obtained results show that, during the period of 1980-2021, interannual variability marked the evolution of annual rainfall averages. Furthermore, this variability is characterized by alternating sequences of dry and wet seasons. From the hydrological year of 2015, a general decreasing trend of rainfall has clearly marked and observed. Rainfall patterns in the Oum Er Rbia basin are also characterized by spatial variability. Interannual averages vary considerably from one catchment to another. The upstream part of the basin receives the most amount of rainfall. By contrast, the middle of the basin is the driest. The recent drop in precipitation has had a negative impact on the basin’s territory, most notably on water resources and agriculture.

Spatiotemporal variability and trends of intra-seasonal rainfall and temperature in the drought-prone districts of Northwestern Ethiopia

Agriculture in Ethiopia is highly dictated by spatial patterns and temporal distributions of climate variables. The analysis of these climate variables is crucial for understanding the impacts on agricultural productivity. This study aimed to analyze spatiotemporal variability and trends of intra-seasonal rainfall and temperature using site-specific daily data from the Ethiopian Meteorology Institute (1992–2021). Standardized methods explore variability, while Mann–Kendall tests identify trends, using the Modified version for data with autocorrelation. Inverse Distance Weighted interpolation was employed for spatial analysis of rainfall, length of growing season, and temperature. The findings identified that Kiremt dominated the mono-modal rainfall pattern, contributing 72%-86% of total annual rainfall. The study found that the season typically begins early on June 13 in Adiszemen, and July 6 in Arbgebiya and ends between October 6 and October 26. The duration of the season varied across locations, averaging 95 days at Ebenat and 148 days at Adiszemen. The seasonal rainfall anomaly index shows identical patterns between ENSO episodes and seasonal rainfall. These findings inform decision-making and adaptation strategies for ENSO-driven rainfall variability. Temperatures showed predictable seasonal patterns, but have significantly increased over time, with maximum and minimum temperatures rising 0.014 °C to 0.421 °C and 0.027 °C to 0.485 °C per year respectively. This warming trend is negatively impacting water, crops, and livestock, requiring adaptation measures to build regional resilience. This study underscores the critical impact of climate variability on agriculture in the study area. The findings reveal shifts in rainfall patterns and temperature trends, providing essential insights for adapting agricultural practices.

Rainfall Sensitivity to Microphysics and Planetary Boundary Layer Parameterizations in Convection-Permitting Simulations over Northwestern South America

Convection-permitting modeling allows us to understand mechanisms that influence rainfall in specific regions. However, microphysics parameterization (MP) and planetary boundary layer (PBL) schemes remain an important source of uncertainty, affecting rainfall intensity, occurrence, duration, and propagation. Here, we study the sensitivity of rainfall to three MP [Weather Research and Forecasting (WRF) Single-Moment 6-class (WSM6), Thompson, and Morrison] and two PBL [the Yonsei University (YSU) and Mellor–Yamada Nakanishi Niino (MYNN)] schemes with a convection-permitting resolution (4 km) over northwestern South America (NWSA). Simulations were performed by using the WRF model and the results were evaluated against soundings, rain gauges, and satellite data, considering the spatio-temporal variability of rainfall over diverse regions prone to deep convection in NWSA. MP and PBL schemes largely influenced simulated rainfall, with better results for the less computationally expensive WSM6 MP and YSU PBL schemes. Regarding rain gauges and satellite estimates, simulations with Morrison MP overestimated rainfall, especially westward of the Andes, whereas the MYNN PBL underestimated precipitation in the Amazon–Savannas flatlands. We found that the uncertainty in the rainfall representation is highly dependent on the region, with a higher influence of MP in the Colombian Pacific and PBL in the Amazon–Savannas flatlands. When analyzing rainfall-related processes, the selection of both MP and PBL parameterizations exerted a large influence on the simulated lower tropospheric moisture flux and moisture convergence. PBL schemes significantly influenced the downward shortwave radiation, with MYNN simulating a greater amount of low clouds, which decreased the radiation income. Furthermore, latent heat fluxes were greater for YSU, favoring moist convection and rainfall. MP schemes had a marked impact on vertical velocity. Specifically, Morrison MP showed stronger convection and higher precipitation rates, which is associated with a greater latent heat release due to solid-phase hydrometeor formation. This study provides insights into assessing physical parameterizations in numerical models and suggests key processes for rainfall representation in NWSA.

Spatiotemporal variability of rainfall and drought characterization in Kaduna, Nigeria

Rainfall variability and drought events can affect food security globally. This study aimed to assess the spatial and temporal trends and variability of rainfall in Kaduna State, Nigeria. Gridded rainfall data were obtained from the Climate Research Unit (CRU_TS 4.07) (1952–2022) for Birnin Gwari, Kaduna, Kafanchan and Zaria towns. The rainfall data were subjected to the Anderson‒Darling normality test and found to be normally distributed. The data were analysed using the coefficient of variation (CV), rainfall anomaly index (RAI) and precipitation concentration index (PCI). The trend was assessed using the Mann‒Kendall trend test, and finally, meteorological drought was computed using the standardized precipitation index (SPI). The results revealed that all four locations had low to moderate variability, with CVs < 15%. The rainfall anomaly index revealed that 1983 was the driest year for Birnin Gwari, Kaduna and Kafanchan, with RAI values of − 4.863, − 4.474 and − 4.316, respectively, while in Zaria, the driest year was 1974, with a RAI value of − 4.065. The PCI showed that there was a high concentration of rainfall in Birnin Gwari, Kaduna, and Kafanchan. However, Zaria experienced 41 years of high concentrations and 30 years of very high concentrations of precipitation. The Mann‒Kendall trend test revealed that all four locations experienced a significant downward trend in rainfall within the study period. The Z statistics for Birnin Gwari, Kaduna, Kafanchan and Zaria were − 1.112, − 0.357, − 0.556 and − 0.764, respectively, all indicating decreasing rainfall amounts. Finally, the SPI Birnin Gwari and Kaduna experienced 18 months of severe drought, with maximum intensities of − 2.671 and − 3.111, respectively. Kafanchan experienced 25 months of drought with a maximum intensity of − 2.643, while Zaria experienced 30 months of drought with a maximum intensity of − 3.069. These severe droughts occurred from the 1970s to the 1990s. The study concluded that rainfall concentrations were mostly high and very high, and severe, catastrophic drought events occurred in the 1970s and 1980s.

Validating the Skills of Satellite Rainfall Products and Spatiotemporal Rainfall Variability Analysis over Omo River Basin in Ethiopia

Recently created long-term and regionally dispersed satellite-based rainfall estimates have emerged as crucial sources of rainfall data to assess rainfall&amp;apos;s spatial and temporal variability, particularly for data-scarce locations. &amp;lt;i&amp;gt;Objective (the general)&amp;lt;/i&amp;gt;: The purpose of this paper is to assess the skills of nine selected satellite rainfall estimates i.e., (ARC 2.0, TRMM 3B42, CHIRPS v. 2.0, TAMSAT 3.1, CMORPH v. 1.0 adj., PERSIANN CDR and DNRT, and MSWEP v. 2.2) and understand Spatio-temporal variability of rainfall over the Omo River basin using the best performing product. &amp;lt;i&amp;gt;Method&amp;lt;/i&amp;gt;: The validation analysis was done by using a point-to-grid-based comparison test at different temporal accumulations. MSWEP was selected as the best product to analyze the long-term trend and variability of rainfall over the Omo-River basin from 1990-2017. The coefficients of variation (CV) and the standardization rainfall anomalies index (SRAI) were used to examine rainfall variability, while the Mann-Kendall (MK) and Sen slope estimators were used to examine the trend and magnitude of rainfall patterns. &amp;lt;i&amp;gt;Results&amp;lt;/i&amp;gt;: The overall statistical, categorical, and volumetric validation index results show that the MSWEP is the best performing rainfall product followed by CHRIPS, 3B42, and TAMSAT according to their order of appearance than the remaining products (i.e., ARC, RFE, PER CDR, PER DNRT, and CMORPH). The CV result with the relatively highest monthly variability (CV &amp;gt; 30%) was observed in some southern, northern, southeastern, and central parts of the study area. In general, the overall annual CV shows almost no variation in the entire basin except in the lower part because of the region&amp;apos;s prevalent topographic variances, which ranged from 3455 to 352 m.a.s.l. In addition, the highest seasonal positive and negative anomalies are observed in each season in the entire basin. These abnormalities can result in significant floods and droughts that unquestionably influence the basin and its resources. &amp;lt;i&amp;gt;Conclusion&amp;lt;/i&amp;gt;: In general, the basin has an increasing trend in the southern portions and a declining trend in the central to northern tip parts of the basin, as can be observed from the annual average MK trend tests. The basin has experienced a greeter variation but is not significant except in some parts of the basin.

Spatiotemporal variability and trends in rainfall and temperature extremes using ERA5 reanalysis and CORDEX–Africa model in Southern Ethiopia

Rainfall and temperature are characterized by spatial and temporal variability in Ethiopia. However, less attention was given for the analysis of climate variability using advanced techniques and multiple sets of data. This study was conducted to examine spatiotemporal variability and trends in rainfall and temperature extremes in Ghibe III Dam watershed. Observational, ERA5, and regional simulation model data sets were used. The coefficient of variation (CV) and precipitation concentration index (PCI) were employed. The trends in rainfall and temperature extremes were examined using the modified Mann-Kendall test and the Sen Slope estimator in R-ClimDex in R 4.2.2 software. The warmest days exhibited temperature from 24.6°C to 40°C in Bele, 28.2°C to 35.43°C in Wolaita Sodo, 33.6 °C–44 °C in Areka, 31.64 °C–36.8 °C in Gesuba, and 29.19 °C–36.15 °C in Gena Bosa. The warmest nights showed temperature ranging from 14 °C to 18.74 °C in Bele and Gena Bosa, respectively. Annual warm days (TX90p) ranges from 11.34 to 57.1 days, with higher heating in the southern parts. The cool days (TX10p) range from 2.79 to 8.41, while the cool nights (TN10p) range from 0.04 to 8.26 days. The areal average temperature maximum and minimum range between 26.37 °C and 13.81 °C, respectively, with mean precipitation of 1446.92 mm.The rainfall extremes indices showed increasing and decreasing trends. The extreme temperature indices showed an overall warming trend. Based on ERA estimates, the rainfall in winter showed higher variability (CV = 72.4%–99.3 %) than the annual rainfall (CV = 33%–79.8 %). PCI showed a moderately (12 %) to very erratic (19.4 %) rainfall distribution. The climate model estimate showed high variability (CV = 20.65 %) in Climate Limited Area Modeling Community (CCLM) under representative concentration paths (RCP) 4.5 and 8.5 and extremely high variability (CV = 93.49 %) in the Regional Atmospheric Climate Model (RACMO) under RCP 4.5. Policymakers should design appropriate adaptation strategies applicable to farmers.

The trends and spatiotemporal variability of temperature and rainfall in Hulbarag district, Silte Zone, Ethiopia

Ethiopia gets its agricultural water primarily from rainfall. This study was intended to investigate current climate variability and trends across space and time. Daily gridded temperature and rainfall data from 1993 to 2022 in the Hulbarag district, Silte Zone of Ethiopia was obtained from the Ethiopian National Metrological Institute and the Climate Hazard Group Infrared Precipitation with Station. The trends and variability of temperature and rainfall were analyzed using the Mann-Kendall trend test, Sen's slope, coefficient of variation, precipitation concentration index, and rainfall anomaly index. The results indicated that annual, spring, and summer rainfall revealed statistically significant decreasing trends at Hulbarag and Sankura stations, with the magnitude of −13.4, −11.6, and −10.6 mm per year and −6.8, −3.6 and −10.9 mm per year respectively. Conversely, autumn and winter season rainfall showed statistically significant increasing trends at Hulbarag and Sankura stations, with the magnitude of 5.1 and 5.5mm per year and 3.4 and 1.84mm per year consecutively. Between 43 % and 47 % of the observation periods had negative anomalies. The average yearly temperature, average yearly minimum temperature, and average yearly maximum temperatures at Sankura and Fonko stations all displayed statistically significant increasing trends, with a magnitude of 0.091 °C, 0.009 °C and 0.051 °C per year and 0.03 °C,0.01 °C and 0.0022 °C per year successively. It is advisable to develop a farming system that is climate-resilient by improving the adaptive capacity of wheat and maize-growing farmers by expanding the availability of early maturing seeds, changing crop calendars, and enhancing proactive and credible climate information services.

East Asian monsoon and westerly jet driven changes in climate and surface conditions in the NE drylands of China since the Late Pleistocene

The East Asian summer monsoon (EASM) is a major component of the global climate yet, the causes for the past spatiotemporal variability of EASM rainfall, its interactions and impacts remain unresolved. Here we use the Sr–Nd isotopes and rare earth elements composition of dust in a peat record from northeast (NE) China to investigate the relationship between aeolian dust, the East Asian monsoon and Westerly Jet (WJ) over East Asia since the Late Pleistocene (14 cal ka BP). The NE drylands of China dominate the dust fraction (Hunshandake, Horqin; 44–88%) with a contribution from the deserts of NW China (Badain Jaran, Tengger, Taklamakan; 10–44%), suggesting an influence of the WJ. Dust deposition varied during the Holocene, displaying a minimum between 8.0 and 6.0 cal ka BP and two peaks at 5.8–3.8 and 1.7–0.3 cal ka BP. Changes in dust flux are opposite to the East Asian winter monsoon intensity profile, suggesting a limited influence of the winter monsoon. The EASM appears to have played a more significant role in the dust cycle, with increasing dust fluxes corresponding with lower EASM precipitation. Variations in dust flux from NE drylands display shifts reflecting changes in EASM precipitations and dune activity along the EASM margin, where the dust originates from. To account for the influence of the WJ, we propose that the meridional position and intensity of the WJ also affected dust emission in the drylands’ region. A more northward position of the WJ allows the EASM front further north, generating more precipitations over the NE drylands, reducing the extent of arid areas, and resulting in less dust emission from dune activity, while the opposite occurs with a strong, more southerly WJ. Anthropogenic activities are likely to have had an increasing impact on the dust cycle over the late Holocene. Nevertheless, the presence of inconsistencies in records, coupled with a simultaneous decline in climatic conditions (mainly precipitations) during the same timeframe, hinders the precise assessment of the influence of human activities on dust emissions in the region.

Spatiotemporal trends and variability of rainfall across agro-ecologies in East Guji Zone, Southeast Ethiopia

Distribution and trends of rainfall reveal spatial and temporal variability that have a paramount effect on the life and livelihood of small-holder farmers. This study aimed to analyze spatial variability and temporal trends of rainfall distribution across the three Agro-Ecological Zones (AEZs) of East Guji. Time series gridded daily rainfall data (1990–2020) were collected from the Ethiopian Meteorological Institution. Different descriptive statistics, trend tests: Man Kendal and Sen’s slope estimator, Inverse Distance Weighted Index and Precipitation Concentration Index (PCI) was used in the study. The finding demonstrated that altitude and rainfall decrease as one advances from the western (highland) to the eastern (lowland) direction in the study area where the highest rainfall was recorded in Solemo (highland) and the least in Negele (lowland).The study showed that as altitude increases annual rainfall also increases and rainfall variability decreases. Similarly the mean length of the growing season declines as one advance from the highlands to the lowlands. The PCI of the lowlands, midlands, and highlands AEZs was 19%, 17%, and 12% respectively. The PCI showed that those highlands had moderately concentrated rainfall but both lowlands, and midlands, had an irregular distribution of rainfall. The Coefficient of Variation (CV) indicated that highland areas had moderate variability in rainfall in all seasons except winter. In contrast, the low and midlands had shown high variability of rainfall (&gt;30%) in all seasons. From a seasonal perspective, both CV and PCI revealed that the winter season showed more variability than others. Moreover, a significant increasing trend of annual rainfall was observed in the highlands AEZs (Bore 15.3mm/year and Solemo14.6mm/year), lowland AEZs (Chembe 10.9mm/year, Dawa 8mm/year and Bitata 7.8mm/year) as well as midland AEZs (Kercha 14.5mm/year) at a significant level of 5%. Therefore, strategies should be designed to use additional water resources for irrigation; and provide short-cycle grown and drought-resistant crops in the rest of the midlands and lowlands AEZs.

Impacts of the Grand Ethiopian Renaissance Dam on the Nile River’s downstream reservoirs

The Nile River Basin’s (NRB’s) water resources are vulnerable to hydrologic alteration projects. Construction of the Grand Ethiopian Renaissance Dam (GERD), a hydroelectric power project on the Blue Nile, is expected to improve living standards in Ethiopia and contribute to the country's sustainable development. However, the effects of the GERD on water resources of downstream countries (Sudan and Egypt) have been a source of concern. In this study, eight types of remote sensing data and products were used to assess the impacts of the GERD reservoir’s filling process on Ethiopia’s, Sudan’s, and Egypt’s surface water resources. Specifically, spatiotemporal variability in surface area, volume, rainfall, and water storage for five reservoirs located in Ethiopia (GERD), Sudan (Roseires and Merowe), and Egypt (Lake Nasser and Toshka) for the period 2013–2022 were examined. Results indicate that (1) the GERD reservoir’s three filling phases started in July 2020, July 2021, and August 2022, respectively, (2) at the onset of these three phases, the GERD reservoir covered an area (volume) of 110 ± 7 km2 (1.87 ± 0.07 km3), 233 ± 31 km2 (4.30 ± 0.48 km3), and 544 ± 126 km2 (11.79 ± 2.18 km3), respectively, (3) a reduction in the GERD reservoir’s area (24–49 %) observed at the end of the first two fillings is attributed to enhanced infiltration and evaporation rates at the GERD site, (4) no significant changes were observed in the Roseires and Merowe reservoir’s surface areas, although both Nasser and Toshka reservoirs saw a slight increase in surface area during the investigated period, (5) the observed increase in water storage over the five reservoirs is attributed mainly to increased rainfall rates (6–10 %) and heavy flooding during the GERD filling period, and (6) if the GERD filling continues at the similar rates for an additional four years during drought periods, Egypt's Nile water allocation might be reduced by 35.47 ± 2.29 % (16.57 ± 1.07 km3), which could translate into an agricultural land loss of 33.14 ± 1.81 % each year. This study emphasizes the critical need for Ethiopia, Sudan, and Egypt to work together to effectively and equitably manage the water resources of the NRB.

Remote sensing-based spatio-temporal rainfall variability analysis: the case of Addis Ababa City, Ethiopia

Remote sensing-based spatio-temporal rainfall variability analysis: the case of Addis Ababa City, Ethiopia

Comprehensive analysis of spatiotemporal variability of rainfall-based extremes and their implications on agriculture in the Upper Ganga Command Area.

The agricultural sector in India primarily relieson monsoon rains, making it necessary for agricultural water managers to study variations in water availability by analyzing rainfall patterns. This information is critical for deciding cropping patterns and irrigation approaches, managing water resources, and improving crop water productivity. The long-term spatiotemporal variability over the command area, India Meteorological Department (IMD) based selection of thresholds for extremes indices, and thorough analysis of the consequences of extreme on agriculture make the study unique. These aspects collectively enhance the perception of the climate-agriculture relationship, which is essential for promoting agriculture resilience under changing rainfall patterns. This type of research is very limited in the literature. Therefore, the present study focuses on comprehensively analyzing the spatiotemporal variability of rainfall and extreme precipitation indices and their implications on agriculture. The study is carried out in the UpperGanga Command Area (UGCA), India's oldest irrigation canal system, by using long-term (1901-2021) high-resolution (0.25 × 0.25°) daily rainfall gridded data obtained from IMD, Pune. Eight different extreme rainfall indices are used to assess spatiotemporal variations. The Mann-Whitney-Pettitt test identified 1970 as a significant change point. Rainfall trends and extreme indices for pre- and post-1970 periods were examined using the non-parametric modified Mann-Kendall test. The results show significant increases in rainfall trends for the annual, monsoon, and kharif seasons from 1901 to 1970, but significant decreases were observed during 1971-2021. This difference resulted in a noticeable decrease in average precipitation in the latter period, approximately 62mm less than in 1901-1970. Similarly, extreme precipitation indices, including the number of rainy days (NxRainy), consecutive dry days (CWD), simple daily intensity index (SDII), and total precipitation (PRCPTOT), exhibited increasing trends in 1901-1970, but they showed significant decreasing trends in 1971-2021. In addition, there is a strong positive correlation between these indices and total precipitation. The study also found that geographical factors influence these trends, with all indices, except SDII, strongly correlated with latitude and elevation, but not with longitude. The implications of these negative rainfall and extreme rainfall trends were further analyzed, and the results indicate a significant impact on the cropping patterns in the study area. The present research findings will be beneficial for regional water resource managers and policymakers in better understanding the existing trends in rainfall distribution over the UGCA.

Spatio-Temporal Variability of Rainfall and Temperature and Their Effects on Pasture Variability over East Africa: Implication on the Cattle Grazing Areas

Spatio-Temporal Variability of Rainfall and Temperature and Their Effects on Pasture Variability over East Africa: Implication on the Cattle Grazing Areas

A gender-responsive breeding approach to the intensification of sesame (Sesamum indicum L.) production in the Maradi region of Niger.

Climatic variability and a decrease in soil fertility have had a detrimental effect on the productivity of the main rainfed crops in Niger (millet, sorghum, and cowpea) and led to a deterioration of the nutritional status and income of the country's farmers. The spatio-temporal variability in rainfall has led rural populations to diversify their farms by integrating sesame (Sesamum indicum L.) into their cropping systems because of its low water and fertilizer requirements. Sesame is increasingly becoming a significant source of income for farmers, and it contributes to their food and nutritional security. To boost the production of sesame and facilitate its rapid adoption, our breeding program focused on participatory breeding and varietal selection with the inclusion of gender-specific preferences, from the variety design to the evaluation of new lines on farms. This case study shows that, although women have more experience in sesame cultivation than men, they have less access to production factors such as land. This limited access is especially problematic, as recent trends in land tenure mean that the poorest are no longer able to exploit large areas of cultivable land. It also evidenced that the varietal preferences of sesame growers as well as the mastery of production techniques are a function of the livelihoods and the investment capacity of actors in the value chain. Our study found that men mainly prefer production traits, whereas women have fewer trait preferences, and their preferences tend to be related to marketing and processing. This finding highlights the contrasting roles and responsibilities between men and women in the sesame value chain. Therefore, the inclusion of complementary traits preferred by women and men, provided that they are not negatively correlated with a variety profile, will help meet the full range of needs across the value chain. We recommend the inclusion of gender research in setting breeding goals prior to variety design.

Future Change in Urban Flooding Using New Convection‐Permitting Climate Projections

AbstractRainfall intensity in the United Kingdom is projected to increase under climate change with significant implications for rainfall‐driven (combined pluvial and fluvial) flooding. In the UK, the current recommended best practice for estimating changes in pluvial flood hazard under climate change involves applying a simple percentage uplift to spatially uniform catchment rainfall, despite the known importance of the spatial and temporal characteristics of rainfall in the generation of pluvial floods. The UKCP Local Convective Permitting Model (CPM) has for the first time provided the capacity to assess changes in flood hazard using hourly, 2.2 km CPM precipitation data that varies in space and time. Here, we use an event set of ∼13,500 precipitation events across the three UKCP Local epochs (1981–2000, 2021–2040, and 2061–2080) to simulate rainfall‐driven flooding using the LISFLOOD‐FP hydrodynamic model at 20 m resolution over a 750 km2 area of Bristol and Bath, UK. We find that both the event set and uplift approaches indicate an increase in flood hazard under near‐term (2021–2040) and future (2061–2080) climate change. However, the event set produces markedly higher estimates of flood hazard when compared to the uplift approach, ranging from 19% to 49% higher depending on the return period. This suggests including the full spatiotemporal rainfall variability and its future change in rainfall‐driven flood modeling is critical for future flood risk assessment.

Spatiotemporal Variability of Rainfall and Surface Salinity in the Eastern Pacific Fresh Pool: A Joint In Situ and Satellite Analysis During the SPURS‐2 Field Campaign

AbstractWe perform a statistical characterization of the 2016–2017 SPURS‐2 field campaign in situ data and coincident satellite data spanning 8°–12°N, 120°–130°W to quantify the spatial and temporal scales of variability of rain and near‐surface salinity in the Eastern Pacific Fresh Pool. Observations of rain rate and near‐surface to surface salinity are obtained from ships, moorings, autonomous platforms, and satellite remote sensing: Integrated Multi‐satellitE Retrievals for GPM (IMERG); and Soil Moisture Active Passive (NASA SMAP L3 V5). The integral length and time scales of rain and near‐surface salinity vary seasonally. In the rainy season (August–October) when the Intertropical Convergence Zone (ITCZ) migrates over the SPURS‐2 study site, the integral time scales of rain were about 30–60 min and those of near‐surface salinity were closer to that of the rain, 1–2 days, indicating forcing by rain. Meanwhile, the zonal integral length scale of in situ near‐surface salinity was twice as large as the meridional scale (50 vs. 20 km), consistent with the ITCZ's zonally‐propagating and ‐organized rain features. The magnitude and seasonal variation of the sea surface salinity integral time scale were not captured by SMAP since the rainy ITCZ‐period scales were smaller than SMAP resolution (70 km, 8‐day running mean). In the dry season (February–May), the in situ rain integral time scale reduced to less than 30 min while that of the near‐surface salinity increased to 1–5 days, the ocean mesoscale. IMERG overestimated the rain integral time scale by a factor of two to ten in both seasons.

Spatiotemporal rainfall variability and its relationship to flash flood risk in Northeastern Sylhet Haor of Bangladesh

Abstract The variability and distribution of rainfall are uniquely significant for climatic risk prediction. This study aims to assess spatiotemporal rainfall variability and flash flood intensity events in the Sylhet haor region of Bangladesh by analyzing rainfall data from April for the period 1995–2022. For this, we used both Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data and Bangladesh Meteorological Department (BMD) daily rainfall data. Rainfall patterns were studied using zonal statistics in ArcGIS and graphical illustration. The results revealed that the rainfall pattern was erratic and showed a range of spatiotemporal variability. If the average rainfall exceeds 250 mm in Meghalaya and Assam and 400 mm in Sylhet, severe flash floods may occur in the Sylhet haor region. An increase in pre-monsoon rainfall and its shift from May to April may increase the intensity of flash floods and consequently damage the rice crop. This finding might help flood management agencies to develop flood management strategies, prepare flood contingency plans, provide real-time and advanced warnings to strengthen flood warning and forecasting systems, and schedule seasonal agricultural activities.

Spatiotemporal climate and vegetation trends, and their relationship: A case of Genale Dawa basin, Ethiopia

Understanding the variability of climate and vegetation, and their relationship in space and time are crucial for agricultural planning, flood risk assessment, and drought monitoring. However, most studies depend on scarce and unevenly distributed climate station datasets in most basins of Ethiopia like the Genale Dawa basin. Detailed climate and vegetation variabilities and their relationship have not well studied in the Genale Dawa basin, which is often affected by recurrent drought. Satellite remote sensing-derived high spatial resolution climate and vegetation data can provide detailed information on climate variability and vegetation changes. This study assessed spatiotemporal variability of temperature, rainfall, and vegetation greenness and their relationship in the Genale Dawa basin. For this study, temperature (minimum and maximum), rainfall data (4 × 4 km) and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data (250 × 250 m) were used. Statistical indices like the Mann Kendall (MK) trend test, Coefficient of Variation (CV), Standard Anomaly Index (SAI), Precipitations Concentration Index (PCI), and Pearson correlation techniques were used to examine the trends and variabilities. The result generally indicated increasing trends in rainfall during the dry (“Bega”) season, and maximum and minimum temperatures during Kiremt (Wet season) and annual seasons. Moreover, high rainfall variability in the Dry and Kiremt seasons and low variability of temperature at all timescales were observed in the basin. In addition, anomalies in temperatures (minimum and maximum) and rainfall were observed in the basin during all the timescales. The result further showed a strong correlation of NDVI with rainfall at annual (r = 0.58), dry season (r = 0.9), and the short rainy season (r = 0.7) while weakly correlated at Kiremt (r = 0.31) seasons in the Genale Dawa basin. The result generally showed spatial and temporal variability of climate and vegetation greenness in the Genale Dawa basin, which negatively affects agricultural production, water resource availability, and vegetation growth. Therefore, appropriate management strategies should be implemented to minimize the negative effects.

Spatiotemporal Variability and Trends in Rainfall and Temperature in South Ethiopia: Implications for Climate Change Adaptations in Rural Communities

Climate change is an environmental challenge for rural communities that rely heavily on rainwater-based agriculture. The main goal of this study is to investigate spatiotemporal variability and trends in rainfall and temperature in southern Ethiopia. Extreme temperature and rainfall indices were computed using the ClimPACT2 software. The detection and quantification of trends in rainfall and temperature extremes were analyzed using a nonparametric modified Mann–Kendall (MMK) test and Sen’s slope estimator. Results indicated that the mean annual rainfall has a declining trend at Boditi School and Mayokote stations with a statistically significant amount at magnitudes of 0.02 mm and 0.04 mm, respectively. The highest average monthly rainfall in the catchment was observed in the months of April, May, June, July, and August up to maximum rainfall of 117.50 mm, 177.43 mm, and 228.84 mm in Bilate Tena, Boditi, and Mayakote stations, respectively. On a seasonal scale, rainfall in Bilate Tena station was highly variable in all months, ranging from 49.54% to 126.92%, and three seasons except spring which showed moderate variation at 40.65%. In addition, the three locations over the catchment exhibited varied drought signs such as severe (1.28 &lt; SRA &lt; 1.65) and extreme drought (SRA &gt; 1.65). The temperature indices, on the other hand, exhibited a warming trend over the catchment which was observed through an increased annual number of warm days (TX90p) and warm nights (TN90p) ranges from 0.274 to 6.03 and 0.274 to 3.16, respectively. The annual maximum value of the daily maximum temperature (TXx) ranges from 30.10 to 33.76°C in the three agroecological zones and showed low, medium, and high values in Dega, Woyna Dega, and Kola agroecologies, while the annual maximum value of the daily minimum temperature (TNx) ranged between 17 and 17.44°C at Dega and Kola, respectively. Therefore, based on trends in rainfall variability and persistent temperature rise, appropriate adaptation strategies should be adopted.

Spatiotemporal Variability of Rainfall as an Evidence of Changing Climate over the Nigerian Niger Delta

This study assesses the spatial and temporal variability of rainfall over the Niger Delta area (Benin, Calabar, Port Harcourt and Uyo) in Nigeria between 1990 and 2020. The daily rainfall data used for this study were obtained through secondary source from NASA’s POWER (Prediction of Worldwide Energy Resources). Coefficient of variation, standardized anomaly index (SAI), precipitation concentration index (PCI) and seasonality index (SI) were used to evaluate rainfall variability and seasonality. The results of temporal analysis of annual rainfall indicated that Benin had the highest annual rainfall amount in 2000 and lowest in 1999 while Calabar and Port Harcourt had their highest rainfall amount in 2007 with the lowest occurring in 1991 and 2014 respectively. Uyo had the highest in 2000 and lowest in 2014. SAI also witnessed the presence of interannual variability of rainfall with negative and positive anomalies in 59.46% and 40.54% of the analyzed years, respectively. PCI and SI results implied that the Niger Delta area had strong irregular rainfall distribution. The results confirm the meteorological sensitivity to locations and provide support for the implementation of station and regional meteorological hazards prevention and to support the mitigation of hazards and improve the management practices of environment system in Niger Delta area.