Climate change influences the changes in drought features. This study assesses the changes in severe drought characteristics over the Asian monsoon region responding to 1.5 and 2.0 °C of global average temperature increases above preindustrial levels. Based on the selected 5 global climate models, the drought characteristics are analyzed according to different regional climate zones using the standardized precipitation index. Under global warming, the severity and frequency of severe drought (i.e., SPI <−1.5) are modulated by the changes in seasonal and regional precipitation features regardless of the region. Due to the different regional change trends, global warming is likely to aggravate (or alleviate) severe drought in warm (or dry/cold) climate zones. For seasonal analysis, the ranges of changes in drought severity (and frequency) are −11.5%~6.1% (and −57.1%~23.2%) under 1.5 and 2.0 °C of warming compared to reference condition. The significant decreases in drought frequency are indicated in all climate zones due to the increasing precipitation tendency. In general, drought features under global warming closely tend to be affected by the changes in the amount of precipitation as well as the changes in dry spell length. As the warming enhanced, the spatial variation of drought severity will be increased across climate zones, which can lead to increased water stress over Asia. This study demonstrates that precipitation characteristic changes can explicitly modulate severe regional drought features.

Understanding the influence of global warming on regional hydroclimatic extremes is challenging. To reduce the potential risk of extremes under future climate states, assessing the change in extreme climate events is important, especially in Asia, due to spatial variability of climate and its seasonal variability. Here, the changes in hydroclimatic extremes are assessed over the Asian monsoon region under global mean temperature warming targets of 1.5 and 2.0 ^∘C above preindustrial levels based on representative concentration pathways (RCPs) 4.5 and 8.5. Analyses of the subregions classified using regional climate characteristics are performed based on the multimodel ensemble mean (MME) of five bias-corrected global climate models (GCMs). For runoff extremes, the hydrologic responses to 1.5 and 2.0 ^∘C global warming targets are simulated based on the variable infiltration capacity (VIC) model. Changes in temperature extremes show increasing warm extremes and decreasing cold extremes in all climate zones with strong robustness under global warming conditions. However, the hottest extreme temperatures occur more frequently in low-latitude regions with tropical climates. Changes in mean annual precipitation and mean annual runoff and low-runoff extremes represent the large spatial variations with weak robustness based on intermodel agreements. Global warming is expected to consistently intensify maximum extreme precipitation events (usually exceeding a 10 % increase in intensity under 2.0 ^∘C of warming) in all climate zones. The precipitation change patterns directly contribute to the spatial extent and magnitude of the high-runoff extremes. Regardless of regional climate characteristics and RCPs, this behavior is expected to be enhanced under the 2.0 ^∘C (compared with the 1.5 ^∘C) warming scenario and increase the likelihood of flood risk (up to 10 %). More importantly, an extra 0.5 ^∘C of global warming under two RCPs will amplify the change in hydroclimatic extremes on temperature, precipitation, and runoff with strong robustness, especially in cold (and polar) climate zones. The results of this study clearly show the consistent changes in regional hydroclimatic extremes related to temperature and high precipitation and suggest that hydroclimatic sensitivities can differ based on regional climate characteristics and type of extreme variables under warmer conditions over Asia.

It is challenging to estimate how the regional climate will be shifted under future global warming. To reduce the potential risk of regional climate shift under future climates, examining the change in climate features over Asia is important, as approximately 60% of the world's population resides there. In this study, climate shifts are assessed over the Asian monsoon region under global mean temperature warming targets from 1.5°C to 5.0°C above preindustrial (PI) levels based on different shared socioeconomic pathway (SSP) scenarios. Global warming impacts the individual climate variables, and consequently, it impacts the regional climate features across the Asian region. Temperature change patterns are more dominant contributors to the spatial extent and magnitude of climate shifts than precipitation change patterns. Changes in regional climates show different behaviors according to the degree of global warming rather than the type of SSP scenario. Climate shifts are intensified under a higher level of global warming that is above the PI levels. The largest climate shifts in this region are shown under global warming of 5.0°C based on the SSP5‐8.5 scenario, especially in current polar climate zones. Future change patterns in individual climate zone can differ. Regions with tropical climates and arid climates are likely to be expanded, whereas some regions with warm temperate climates, cold climates, and polar climates are likely to shrink under global warming conditions. Therefore, this study supports the necessity of mitigating greenhouse gas (GHG) emissions and establishing an adaptation plan for future global warming conditions.

This study assesses the potential changes in regional hydroclimates over South Korea in response to 1.5 and 2.0°C of global warming above preindustrial levels based on multimodel ensemble projections forced by a representative concentration pathway (RCP4.5) scenario. The meteorological inputs, which are derived from five global climate models after removing systematic bias using quantile mapping, are fed into a distributed hydrological model, the variable infiltration capacity model, to estimate the hydrologic responses to different levels of greenhouse gas concentrations in future periods. The changes in seasonal mean precipitation differ between monsoon and intermonsoon seasons. An increase in summer precipitation and a decrease in winter precipitation commonly occur under 1.5 and 2.0°C of global warming, resulting in intensified precipitation seasonality. However, changes in spring and fall precipitation show opposite change signals or relatively little robustness (as measured by model agreement) in response to different degrees of warming. Spatial and seasonal changes in precipitation are directly transferred to runoff patterns, increasing the disparity between wet and dry seasons. Global warming also leads to changes in the distributions of daily precipitation and streamflow, and the projected changes systematically involve an increase in high‐intensity precipitation and a decrease in relatively low‐intensity precipitation. This behaviour tends to be amplified under 2.0°C in comparison to 1.5°C of global warming, with potential implications for increased water stress under a much warmer climate. More importantly, under 2.0°C of global warming, the magnitude of extremes such as the annual maximum day flow in Korean basins is likely to be enhanced. This study demonstrates that changes in precipitation characteristics can explicitly modulate runoff and subsequently streamflow patterns, suggesting positive benefits of half a degree less warming in terms of the frequency and intensity of extreme streamflow.

Burundi is susceptible to future water-related disasters, but examining the influence of climate change on regional hydroclimatic features is challenging due to a lack of local data and adaptation planning. This study investigated the influence of climate change on hydroclimate-focused changes in the climatology of heavy precipitation (and streamflow) means and extremes based on the multi-model ensemble mean of earth system models in the sixth phase of the Coupled Model Intercomparison Project (CMIP). For runoff analysis, hydrologic responses to future climate conditions were simulated using the Soil and Water Assessment Tool (SWAT) model over the Ruvubu River basin, Burundi. Temperature increases by 5.6 °C, with strong robustness, under future climate conditions. The mean annual precipitation (and runoff) undergoes large seasonal variations, with weak robustness. Precipitation (and streamflow) changes between the wet and dry seasons differ in signal and magnitude. However, alterations in both the amount and frequency of precipitation reveal the intensification of the water cycle due to anthropogenic climate change. Thus, the highest variability in the maximum daily streamflow is shown in months of long wet seasons, especially in the far future (2085). Without considering the regional climate characteristics and shared socioeconomic pathway (SSP) scenarios, this behavior is expected to be enhanced in 2085 (compared with 2045) and increase the severity of extreme precipitation and flood risk. Climate change will cause alterations in the magnitude and seasonal distributions of extreme precipitation (and streamflow). These findings could be important for flood planning and mitigation measures to cope with climate change in Burundi.