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The Mediterranean region is one of the most responsive areas to climate change and was identified as a major “hot-spot” based on global climate change analyses. This study provides insight into local climate changes in the Mediterranean region under the scope of the InTheMED project, which is part of the PRIMA programme. Precipitation and temperature were analyzed in an historical period and until the end of this century for five pilot sites, located between the two shores of the Mediterranean region. We used an ensemble of 17 Regional Climate Models, developed in the framework of the EURO-CORDEX initiative, under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Over the historical period, the temperature presents upward trends, which are statistically significant for some sites, while precipitation does not show significant tendencies. These trends will be maintained in the future as predicted by the climate models projections: all models indicate a progressive and robust warming in all study areas and moderate change in total annual precipitation, but some seasonal variations are identified. Future changes in droughts events over the Mediterranean region were studied considering the maximum duration of the heat waves, their peak temperature, and the number of consecutive dry days. All pilot sites are expected to increase the maximum duration of heat waves and their peak temperature. Furthermore, the maximum number of consecutive dry days is expected to increase for most of the study areas.

We examine the impact of +1.5 °C and +2 °C global warming levels above pre-industrial levels on consecutive dry days (CDD) and consecutive wet days (CWD), two key indicators for extreme precipitation and seasonal drought. This is done using climate projections from a multi-model ensemble of 25 regional climate model (RCM) simulations. The RCMs take boundary conditions from ten global climate models (GCMs) under the RCP8.5 scenario. We define CDD as the maximum number of consecutive days with rainfall amount less than 1 mm and CWD as the maximum number of consecutive days with rainfall amount more than 1 mm. The differences in model representations of the change in CDD and CWD, at 1.5 °C and 2 °C global warming, and based on the control period 1971−2000 are reported. The models agree on a noticeable response to both 1.5 °C and 2 °C warming for each index. Enhanced warming results in a reduction in mean rainfall across the region. More than 80% of ensemble members agree that CDD will increase over the Guinea Coast, in tandem with a projected decrease in CWD at both 1.5 °C and 2 °C global warming levels. These projected changes may influence already fragile ecosystems and agriculture in the region, both of which are strongly affected by mean rainfall and the length of wet and dry periods.

Droughts represent one of the most significant natural hazards, with widespread implications for agriculture, ecosystems, and human livelihoods, particularly in regions like southern Portugal. In recent decades, severe drought events have become increasingly frequent and intense. Considering the potential impacts of droughts, particularly concerning water and river basin management—a critical factor in southern Portugal—the main motivation for this study was the creation of a short-term forecast alert system for drought severity. This study aims to assess the effectiveness of the random forest (RF) model in forecasting drought severity, using consecutive dry days (CDD) as a drought indicator. Daily precipitation data from 17 meteorological stations across southern Portugal were used to classify drought severity into three categories (classes A, B, and C). The RF models were applied to predict the likelihood of each drought severity class, using historical data to forecast future drought conditions. The model's performance results indicate that the RF model performs well in predicting moderate to severe drought classes, with particularly strong accuracy during the peak dry season in July and August. However, the model exhibited challenges in forecasting extreme drought classes, especially during the transitional months of June and September, likely due to the variability in precipitation patterns during these periods. The findings demonstrate the utility of the RF model as a reliable tool for early drought warning and water resource management in southern Portugal. Furthermore, the methodology presented in this study can be adapted to other regions, making it a versatile approach to addressing drought-related challenges worldwide.

As a mountainous country, Nepal is most susceptible to precipitation extremes and related hazards, including severe floods, landslides and droughts that cause huge losses of life and property, impact the Himalayan environment, and hinder the socioeconomic development of the country. Given that the countrywide assessment of such extremes is still lacking, we present a comprehensive picture of prevailing precipitation extremes observed across Nepal. First, we present the spatial distribution of daily extreme precipitation indices as defined by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) from 210 stations over the period of 1981–2010. Then, we analyze the temporal changes in the computed extremes from 76 stations, featuring long-term continuous records for the period of 1970–2012, by applying a non-parametric Mann−Kendall test to identify the existence of a trend and Sen’s slope method to calculate the true magnitude of this trend. Further, the local trends in precipitation extremes have been tested for their field significance over the distinct physio-geographical regions of Nepal, such as the lowlands, middle mountains and hills and high mountains in the west (WL, WM and WH, respectively), and likewise, in central (CL, CM and CH) and eastern (EL, EM and EH) Nepal. Our results suggest that the spatial patterns of high-intensity precipitation extremes are quite different to that of annual or monsoonal precipitation. Lowlands (Terai and Siwaliks) that feature relatively low precipitation and less wet days (rainy days) are exposed to high-intensity precipitation extremes. Our trend analysis suggests that the pre-monsoonal precipitation is significantly increasing over the lowlands and CH, while monsoonal precipitation is increasing in WM and CH and decreasing in CM, CL and EL. On the other hand, post-monsoonal precipitation is significantly decreasing across all of Nepal while winter precipitation is decreasing only over the WM region. Both high-intensity precipitation extremes and annual precipitation trends feature east−west contrast, suggesting significant increase over the WM and CH region but decrease over the EM and CM regions. Further, a significant positive trend in the number of consecutive dry days but significant negative trend in the number of wet (rainy) days are observed over the whole of Nepal, implying the prolongation of the dry spell across the country. Overall, the intensification of different precipitation indices over distinct parts of the country indicates region-specific risks of floods, landslides and droughts. The presented findings, in combination with population and environmental pressures, can support in devising the adequate region-specific adaptation strategies for different sectors and in improving the livelihood of the rural communities in Nepal.

This study analyzes the interannual relationship between preceding winter Aleutian low (AL) and spring extreme consecutive dry days (extreme-CDDs) in the Yangtze-Huai River region (YHR) during 1979–2019. The results show that, independent from the El Niño-Southern Oscillation variability, a weakened AL in February is accompanied by more spring extreme-CDDs in YHR. Additionally, such a relationship shows a remarkable decadal enhancement after the late-1990s, in which the changes in the Bering Sea ice (BSI) and stratospheric polar vortex (SPV) play bridging roles. On the one hand, the weakened AL could lead to decreased BSI in spring during the whole period by inducing anomalous warm-moist air transport and the resultant radiation effect. After the late-1990s, the decreased BSI could cause a stronger anomalous high over Lake Baikal in spring by exciting an eastward propagated atmospheric wave train, favoring downward motions and more extreme-CDDs in YHR. On the other hand, after the late-1990s, the weakened AL could induce an intensified SPV persisting from late February to early spring by inhibiting the upward propagation of planetary wave. The SPV signal could in turn propagate downward to the troposphere, also contributing to anomalous high over Lake Baikal in spring and more extreme-CDDs in YHR. In contrast, the stratosphere-troposphere interaction associated with anomalous AL is weak before the late-1990s. Through the above-mentioned physical processes, the February AL could have a significantly lagged impact on spring extreme-CDDs in YHR after the late-1990s, consequently providing valuable prediction source for the variability of spring extreme-CDDs in YHR.

There is an ongoing debate on the relationship between accelerated warming in the Arctic and extreme weather patterns in mid-latitudes. As extreme weather events have dramatic socioeconomic costs, it is important to investigate the possibility of the increased risk of such events in mid-latitudes. We investigated changes in the frequency of extreme weather events in Eastern Europe and Western to Central Asia (30–60 ∘ N, 20–75 ∘ E) in the post-Arctic amplification (2002–2022) compared to the pre-Arctic amplification (1979–1999) period. We analyzed the daily detrended near-surface temperature and precipitation of the ERA5 data. There is no robust evidence for the contribution of Arctic amplification to changes in extreme precipitation in Eastern Europe and Western to Central Asia. Most regions of the study area have experienced a decrease in annual precipitation in the post-Arctic amplification period. We also identified an increase in consecutive dry days in most parts of Central Asia by approximately 16 days per year, which could be attributed to a warmer climate because dry areas generally become drier in a warmer climate. Greater warming of the Earth in the more recent period has been associated with a significant increase in both warm days and nights and a significant decrease in cold days and nights over Eastern Europe and Western to Central Asia. Depending on the season, we identified both intensification and weakening of the upper tropospheric jet stream in the post-Arctic amplification period. The jet stream is intensified from the eastern Black Sea toward northern Kazakhstan and southeastern Russia in spring. In contrast, it has significantly weakened in the northern Mediterranean Sea and western Kazakhstan in summer and the Caspian Sea and Caucasus in autumn. Our results have important implications for a better understanding of the potential impact of rapid Arctic warming on extreme weather events in mid-latitudes.

The study analysed the changes in the rainfall, extreme indices and their future projections over Rajasthan state based on observed gridded datasets (1976–2005) and simulated climate models. The climate projections from two global circulation models (HadCM3 and GFCM21) are used in statistical downscaling tool LARS-WG5 (Long Ashton Research Station-Weather Generator) to generate future precipitation. Further, the changes in precipitation pattern are investigated for the baseline period and the future periods based on seven extreme precipitation indices. Three future periods are used for the analysis i.e., early century period 2011–2040 (2025s), a mid-century period of 2041–2070 (2055s) and a late-century period of 2071–2100 (2085s). The study area is classified in three regions based on elevation range i.e., region 1 (< 250 m), region 2 (251–350 m) and region 3 (350–1700 m). Based on results, it is observed that there is a possible decrease in monsoon precipitation at many grid points for all the three future periods. The maximum decrease in rainfall (−142 mm) is observed in Banswara for the period 2041–2070, while the maximum increase (37 mm) is found in Alwar along with Churu 1 and Ganganagar during the period 2071–2100. Consecutive dry days (CDD) is predicted to increase in the west and south-west direction, while it shows decrease values in eastern and central part of the study area with the maximum value in Ajmer district. The pattern in PRCPTOT revealed maximum negative change (− 90 mm) in southern parts, and maximum positive change in the northern regions (62.2 mm) in Churu 1. Further, R20 and RX5day are projected to decrease in all three regions in future with several magnitudes. For RX1day, a maximum positive change is observed in eastern parts (Jhalawar, Sawai Madhopur) and negative changes in the southern part of the study area. In case of R95p index, both positive and negative changes are observed. Similarly, the SDII indicates a positive change in 2011–2040 and negative changes for the remaining two future periods. Finally, SDII shows maximum positive changes in the south and southeastern regions (Jhalawar, Chittaurgarh) and positive changes in various parts with spatial and temporal changes. The results will help water resources planner to understand the change pattern in various precipitation indices in water scarce state of India.

This study compares the physical processes responsible for the heavy and light rain variations from the perspective of spring precipitation over Southern China. The results indicate that, heavy rain variation has a closer connection with the western North Pacific anticyclone. Intensified western North Pacific anticyclone and associated warm and humid air transport, coupled with intensified East Asian subtropical jet, favor significant moisture convergence and enhanced convective feedback over the key region, which causes increased heavy rain rather than light rain over there. In comparison, light rain variation shows a close relationship with the anomalous low over Lake Balkhash, which causes lower-tropospheric cyclone over the key region. On the one hand, anomalous cyclone favors lower-tropospheric cooling; concurred with cyclone-induced increased moisture, the lower-tropospheric relative humidity increases over there. On the other hand, the lower-tropospheric cooling center shifts northward with height and causes enhanced atmospheric baroclinity over there. Such atmospheric conditions are conducive to the occurrence of low cloud and more light rain. In addition, intensified East Asian subtropical jet associated with Lake Balkhash anomalous low also provides favorable dynamic lifting condition. Moreover, heavy and light rain variations are more related to El Niño-Southern Oscillation and North Atlantic horseshoe sea surface temperature in preceding winter, respectively. In addition, heavy rain shows a closer relationship with total precipitation amount variation, whereas light rain is more related to extreme consecutive dry days variation.

The duration of dry periods is closely related to drought conditions and is used to evaluate the degree of drought. In this article, using the rotated empirical orthogonal function (REOF) and K‐medoids clustering methods and considering the spatial continuity, 500 stations in China are divided into 10 clusters to analyze the variation characteristics of consecutive dry days (CDDs) with different durations in spring. In Clusters 1–5 over the middle and lower reaches of the Yangtze River, South China, North China, and eastern and western Southwest China, the contribution percentage of short‐duration CDDs to total dry days decreases, while that of medium‐ and/or long‐duration CDDs increases, which leads to an increase in the total dry days and the duration of CDDs. In Clusters 6–8, the total dry days decrease, which are mainly contributed by the decreases in medium‐duration CDDs (for Cluster 6 over southern Northeast China) or long‐duration CDDs (for Clusters 7–8 over northern Northeast China and southern Xinjiang). The total dry days change little in Clusters 9–10 over eastern Northwest China and northern Xinjiang, which is attributed to the offset among the changes in the three‐type duration CDDs. In Clusters 6–10, the duration of CDDs shortens overall. The decadal changes of spring dry days in China exhibit remarkable regional differences. The total day days and three‐type duration CDDs in some clusters (1, 4, and 8) all have significant decadal changes, but they have not in Cluster 7. And the decadal change times also exhibit regional differences. The investigation of different‐duration CDDs in this study provides more information on droughts at different time scales in China. Schematic diagram of the variations in total dry days and short‐, medium‐, and long‐duration CDDs in 10 clusters of China. Different (black) marks in China indicate the stations (central station) of each cluster. The (solid) arrows of ↑ and ↓ denote the (significant) increasing and decreasing trends, and the arrow of → represents almost no change. The values in the brackets denote the years when the significant decadal change occurs, and the marks of +/− indicate the increase/decrease decadal change.

Climate change presents recurring challenges in understanding extreme weather events, particularly the persistence of dry and wet periods. West Java is among the region's most vulnerable to such rainfall variability. This study analyses the relationship between consecutive dry days (CDD) and consecutive wet days (CWD). It estimates joint return periods (JRP) using a copula-based approach to assess the spatial characteristics of climate extremes in West Java. Marginal distributions were fitted for each indicator, followed by copula modelling using the Inference Function for Margins method and model selection based on the Akaike's information criterion (AIC). The inverse Gaussian (ING) distribution was most suitable for CDD, while the generalised extreme value (GEV) distribution best represented CWD. We found that the Gaussian and Frank copulas best captured the overall dependence structure between CDD and CWD. JRP analysis showed that simultaneous extremes (AND scheme) were significantly rarer than single-variable extremes (OR scheme). These findings provide valuable input for identifying high-risk areas and developing more locally adaptive climate risk mitigation strategies.