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The spatio-temporal characteristic of rainfall in the Beles Basin of Ethiopia is poorly understood, mainly due to lack of data. With recent advances in remote sensing, satellite derived rainfall products have become alternative sources of rainfall data for such poorly gauged areas. The objectives of this study were: (i) to evaluate a multi-source rainfall product (Climate Hazards Group Infrared Precipitation with Stations: CHIRPS) for the Beles Basin using gauge measurements and (ii) to assess the spatial and temporal variability of rainfall across the basin using validated CHIRPS data for the period 1981–2017. Categorical and continuous validation statistics were used to evaluate the performance, and time-space variability of rainfall was analyzed using GIS operations and statistical methods. Results showed a slight overestimation of rainfall occurrence by CHIRPS for the lowland region and underestimation for the highland region. CHIRPS underestimated the proportion of light daily rainfall events and overestimated the proportion of high intensity daily rainfall events. CHIRPS rainfall amount estimates were better in highland regions than in lowland regions, and became more accurate as the duration of the integration time increases from days to months. The annual spatio-temporal analysis result using CHIRPS revealed: a mean annual rainfall of the basin is 1490 mm (1050–2090 mm), a 50 mm increase of mean annual rainfall per 100 m elevation rise, periodical and persistent drought occurrence every 8 to 10 years, a significant increasing trend of rainfall (~5 mm year−1), high rainfall variability observed at the lowland and drier parts of the basin and high coefficient of variation of monthly rainfall in March and April (revealing occurrence of bimodal rainfall characteristics). This study shows that the performance of CHIRPS product can vary spatially within a small basin level, and CHIRPS can help for better decision making in poorly gauged areas by giving an option to understand the space-time variability of rainfall characteristics.

This study provides the first assessment of CMIP5 model performances in simulating southern Africa (SA) rainfall variability in austral summer (Nov–Feb), and its teleconnections with large-scale climate variability at different timescales. Observed SA rainfall varies at three major timescales: interannual (2–8 years), quasi-decadal (8–13 years; QDV) and interdecadal (15–28 years; IDV). These rainfall fluctuations are, respectively, associated with El Niño Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO), interacting with climate anomalies in the South Atlantic and South Indian Ocean. CMIP5 models produce their own variability, but perform better in simulating interannual rainfall variability, while QDV and IDV are largely underestimated. These limitations can be partly explained by spatial shifts in core regions of SA rainfall variability in the models. Most models reproduce the impact of La Niña on rainfall at the interannual scale in SA, in spite of limitations in the representation of ENSO. Realistic links between negative IPO are found in some models at the QDV scale, but very poor performances are found at the IDV scale. Strong limitations, i.e. loss or reversal of these teleconnections, are also noted in some simulations. Such model errors, however, do not systematically impact the skill of simulated rainfall variability. This is because biased SST variability in the South Atlantic and South Indian Oceans strongly impact model skills by modulating the impact of Pacific modes of variability. Using probabilistic multi-scale clustering, model uncertainties in SST variability are primarily driven by differences from one model to another, or comparable models (sharing similar physics), at the global scale. At the regional scale, i.e. SA rainfall variability and associated teleconnections, while differences in model physics remain a large source of uncertainty, the contribution of internal climate variability is increasing. This is particularly true at the QDV and IDV scales, where the individual simulations from the same model tend to differentiate, and the sampling error increase.

Recent variability in West African monsoon rainfall (WAMR) has been shown to be influenced by multiple ocean–atmosphere modes, including the El Niño Southern Oscillation, Atlantic Multidecadal Oscillation and the Interdecadal Pacific Oscillation. How these modes will change in response to long term forcing is less well understood. Here we use four transient simulations driven by changes in orbital forcing and greenhouse gas concentrations over the past 6000 years to examine the relationship between West African monsoon rainfall multiscale variability and changes in the modes associated with this variability. All four models show a near linear decline in monsoon rainfall over the past 6000 years in response to the gradual weakening of the interhemispheric gradient in sea surface temperatures. The only indices that show a long-term trend are those associated with the strengthening of the El Niño Southern Oscillation from the mid-Holocene onwards. At the interannual-to-decadal timescale, WAMR variability is largely influenced by Pacific–Atlantic – Mediterranean Sea teleconnections in all simulations; the exact configurations are model sensitive. The WAMR interannual-to-decadal variability depicts marked multi-centennial oscillations, with La Niña/negative Pacific Decadal Oscillation and a weakening and/or poleward shift of subtropical high-pressure systems over the Atlantic favoring wet WAMR anomalies. The WAMR interannual-to-decadal variability also depicts an overall decreasing trend throughout the Holocene that is consistent among the simulations. This decreasing trend relates to changes in the North Atlantic and Gulf of Guinea Sea Surface Temperature variability.

Climate change has a significant impact on the Ganga–Brahmaputra (GB) basin, the major food belt of India, which frequently experiences flooding and varied incidences of drought. The current study examines the changing trend of rainfall and temperature in the GB basin over a period of 30 years to identify areas at risk with an emphasis on the Paris Agreement’s mandate to keep increasing temperatures below 2 °C. The maximum temperature anomaly in the middle Ganga plains recorded an increase of more than 1.5 °C year −1 in 1999, 2005, and 2009. Some extreme events were observed in the Brahmaputra basin during 1999, 2009, and 2010, where a prominent temperature increase of 1.5 °C year −1 was observed. The minimum temperature revealed an increasing trend for the G-B basin with an anomalous increase of 0.04 to 0.06 °C year −1 . The rainfall variability across the Ganga basin shows a rising tendency over the lower Ganga region while the Brahmaputra basin showed a downward trend. To identify the statistical relation between the Global climatic oscillations and regional climate, Standardized Precipitation Index (SPI) and Niño 3.4 were used. The wet and dry period estimation shows a rise in flood conditions in the Ganga basin whereas, in the Brahmaputra basin, an increase in drought frequency was observed. The correlation based on Niño 3.4 and SPI3 presents a negative relation for the monsoon season in the G-B basin revealing a situation of drought occurrence (SPI3 below 0) with increased Nino 3.4 values (El Niño above + 0.4C).

The interannual variability in Indian summer monsoon rainfall (ISMR) results from numerous multi-scale interrelated phenomena. Using reconstructed rainfall data from 1813–2020 for 20 river basins in India, the research reveals substantial decline in the Ganga, Brahmaputra, Cauvery, Brahmani, Pallar & Ponniyar ranging 6.6–19.7%, and notable increase of 7.9% in Surma in past two decades compared to last century. Despite significant regional disparities, a modest increase of 1.3% in ISMR is observed over 101 years, indicating long-term stability. Spectral analysis highlights dominance of short-term fluctuations (75%) in interannual variability. The evolving relationships between rainfall and global climatic indices are underscored. The Southern Oscillation Index (SOI), Arctic Oscillation (AO), Niño3.4 and Pacific Decadal Oscillation (PDO) are most influential indices across basins, mostly show stronger relationship in June and September compared to July and August. Over time, AO and SOI maintained significant positive relationship and Niño3.4 inverse relationship with ISMR while, the AO-ISMR link weakened post-1980s indicating shift in traditional teleconnections with climate change. Northern and eastern basins, exhibit strong correlations with the warming over eastern and central Afro-Asian highlands, while southern basins influenced by equatorial climate dynamics. The findings emphasize the need for region-specific model predictions and localized adaptive water management strategies.

El Niño influence on the Euro‐Mediterranean Rainfall (EMedR) has changed along the 20th century, and the reasons for this lack of stationarity, which represents an important issue in the climate change context, are still unclear. Here, the causes of this changing relationship are studied at interannual timescales. To this aim the EMedR is analyzed using observations from 1900 to 2008. Results confirm the lack of stationarity, showing how the teleconnections with El Niño appear modulated by multidecadal oscillations of the anomalous Sea Surface Temperature (SST) over the Atlantic and Pacific basins. The study presents statistically significant evidences about how the Atlantic Multidecadal Oscillation (AMO) seems to modulate El Niño teleconnection for late winter‐spring, while modulation in fall could be controlled by the Pacific Decadal Oscillation (PDO). The results of this study have important implications in seasonal and decadal predictability, but they also represent a step forward in the understanding of the role of changes in the ocean mean state on the interannual teleconnections. Key Points EMedR as a result of internal variability or forced by El‐Nino Non stationary relationship between the Euro‐Mediterranean rainfall and El Nino El Nino impact depends on the sign of AMO (late‐winter and spring) or PDO (fall)

The lower number of rainfall events resulting in drier environment over the years is a crucial phenomenon attracting the concern of all around the world. The impact of rainfall deficiencies will lead to issues of water resources availability, both for the agricultural sector and also for health and human development. Therefore, this study on rainfall variability in terms of the dry spells (DS) and the drought characteristics of the regions is necessary to get a better understanding of the DS. In this study, the data period is from 1988–2017, and the intricacies of the DS and extreme DS occurrences, and spatial distribution for drought characteristics were analysed. In addition, this study was confined to the 30-year period rainfall data, which were then analysed using the Rainfall Variability Index (RVI) with two timeframes, initially, the 30-year long-term period and subsequently over six arbitrarily chosen 5-year sub-periods. The findings showed that the Northern Region and Central Region located in Peninsular Malaysia, and the regions that lie between Sabah and Sarawak had more DS occurrences in view of the higher number of DS exhibited during the study period. The next part of this study involves the spatial analysis for drought frequency (DF) and mean drought duration (MDD) over the 13 regions (4 in West Malaysia and 9 in East Malaysia) throughout Malaysia. It showed that the DF was significant for both the annual and monthly RVI, and for the MDD being significant for the monthly RVI over the 30-year period. For the six 5-year sub-periods, the spatial differences varied for both DF and MDD, are based on annual RVI.

The national economy and food security of many sub-Saharan countries relies on rain-fed agriculture, hence the impact of rainfall variability is highly significant. The intent of this study is to characterize rainfall variability and trend in Awash River Basin for agricultural water management using standard rainfall statistical descriptors. Long-term climate data of 12 stations were analyzed. Onset and cessation dates, length of growing period (LGP) and probability of dry spell occurrences were analysed using INSTAT Plus software. The Mann–Kendall test and the Sen's slope method were used to assess the statistical significance of the trend. The results show high variability of rainfall (38–73%), LGP (30–38 days) and high probability of dry spell occurrence (up to 100%) during the Belg season (the short rainy season from March to May) compared with the Kiremt season (the main rainy season from June to September) in all stations. Belg season showed a non-significant decline trend in most of the stations, whereas the Kiremt season indicated the contrary. The finding also revealed that supplementary irrigation is vital, especially in the Belg season to cover up to 40% of the crop water requirement deficit.

Satellite-derived rainfall estimates and the ERA-Interim reanalysis are used to better understand cold air surge/precipitation interactions and to identify the implications for rainfall variability in the Sahel and tropical Africa on synoptic to seasonal timescales. At the synoptic timescale, cold air surges are associated with cold conditions over the eastern Sahara throughout the year due to the eastward passage of surface low pressure systems over the Mediterranean and the subsequent ridging over northern Africa. Rainfall decreases over central and eastern Africa approximately 4–5 days after the cold air first arrives in northeastern Africa. These precipitation anomalies persist for 4 or more days. At the seasonal timescale, a significant relationship between eastern Saharan low-level temperatures and rainfall in the Sahel and tropical Africa is identified, with colder conditions associated with reduced convection on the northern flank of the primary convergence zone, and vice versa. During boreal winter, the anomalous rainfall occurs over tropical Africa (0°N–8°N). During the summer, rainfall anomalies associated with cold air surges occur over the Sahel (10°N–16°N). These relationships are mediated by anomalous anticyclonic flow over northwestern Africa and western Europe. The analysis shows that cold air surges are significantly associated with summertime cooling over the Sahara, but less so during the winter.

Landslides often cause deaths and severe economic losses. In general, forests play an important role in reducing landslide probability because of the stabilizing effect of the tree roots. Although fruit groves consist of trees, which are similar to forests, practical land management, such as the frequent trampling of fields by laborers and compression of the terrain, may cause such land to become prone to landslides compared with forests. Fruit groves are widely distributed in hilly regions, but few studies have examined their role in landslide initiation. This study aims at filling this gap evaluating the predisposing and triggering conditions for rainfall-triggering landslides in part of Uwajima City, Japan. A large number of landslides occurred due to a heavy rainfall event in July 2018, where citrus groves occupied about 50% of the study area. In this study, we combined geodata with a regression model to assess the landslide hazard of fruit groves in hilly regions. We developed maps for five conditioning factors: slope gradient, slope aspect, normalized difference vegetation index (NDVI), land use, and geology. Based on these five maps and a landslide inventory map, we found that the landslide area density in citrus groves was larger than in forests for the categories of slope gradient, slope aspect, NDVI, and geology. Ten logistic regression models along with different rainfall indices (i.e., 1-h, 3-h, 12-h, 24-h maximum rainfall and total rainfall) and different land use (forests or citrus groves) in addition to the other four conditioning factors were produced. The result revealed that “citrus grove” was a significant factor with a positive coefficient for all models, whereas “forest” was a negative coefficient. These results suggest that citrus groves have a higher probability of landslide initiation than forests in this study area. Similar studies targeting different sites with various types of fruit groves and several rainfall events are crucial to generalize the analysis of landslide hazard in fruit groves.