Over the past few decades, South Asia (SA) has experienced an upsurge in the frequency of severe monsoonal compound drought and heatwave (CDHW) occurrences. Climate models that identify land‐atmosphere coupling as a major contributing factor for this exacerbation and anticipate an increase in the intensity and frequency of CDHW occurrences in future also represent this. For the first time, this study investigated the future evolution of monsoonal CDHW events based on new generations of the CMIP6 and population products by applying a multivariate framework. Specifically, this study explored the impacts of natural climate variability and future land‐atmosphere coupling on the monsoonal CDHW event risks and their bivariate return periods for two future time‐periods and emission scenarios across SA and its subregions. The odds of CDHW occurrences were then examined using a logistic regression model and its association with the natural and anthropogenic drivers was determined. The results indicate that the monsoonal CDHWs occurrence is anticipated to increase substantially during the late twenty‐first century (2056–2090). The 50‐year CDHW events might increase by two‐fold across most of SA by the mid‐21st century under the high emission scenario. We find that the co‐occurring dry and warm conditions rapidly strengthens with soil moisture and temperature coupling and are further exacerbated by land‐atmospheric feedback loops. Our findings show that persistent dry spells contribute significantly to heatwave events, emphasizing regional exposure to changing climates.

In recent decades, water scarcity is a significant constraint for socioeconomic development and threatens livelihood in an agriculture-based developing country like Pakistan. The water crisis in the country is projected to exacerbate in the coming years, especially in the southern parts. This dire situation calls for an investigation of major droughts, associated water scarcity, and changes in teleconnection patterns over Southern Pakistan. Moderate to low Southeastern monsoon (SEM) precipitation triggered the extreme drought episode (2017–2020) over Southern Pakistan and intensified the water scarcity. This study explored the severity of the respective drought event, underlying mechanisms, and changes in water scarcity over Southern Pakistan. To investigate the future changes (1980–2050) in water scarcity, coupling models (global hydrological models (GHMs)-global climate models (GCMs)) have been used to achieve the interannual performance of water availability and total water consumption. Besides, future scenarios used in this study are the combinations of SSPs and RCPs, including middle-of-the-road (SSP1-RCP4.5) and fossil-fueled development (SSP2-RCP8.5). The findings indicated a precipitation deficit of 45% during the 4-year (2017–2020), depicting the worst events in the past 50 years. South Pakistan observed the worst SEM droughts over the last 50 years, as 2000–2005 was the worst drought (precipitation deficit of 75%), followed by 2017–2020 with a 49% of precipitation deficit. Water scarcity was exacerbated by the extreme dry spells that developed over most of southern Pakistan between 2017 and 2020 as a result of moderate-to-exceptionally low SEM precipitation. Furthermore, this drought episode was accompanied by the cool phase in the Pacific and equatorial Indian Oceans. The future changes in water scarcity over the southern regions of Pakistan present a sharp increase under the SSP2-RCP8.5 scenario and are anticipated to be intensified in already stressed regions. This research is essential for environmentalists, and water resources managers, and provided crucial information to identify the hot spot areas in the target region so that water scarcity problems could be reduced in the future.

Using a succession of 24 h Weather Research and Forecasting model (WRF) simulations, we investigate the sensitivity to initial soil moisture of a short-range high-temperature weather event that occurred in late July 2003 in East China. The initial soil moisture (SMOIS) in the Noah land surface scheme is adjusted (relative to the control run, CTL) for four groups of simulations: DRY25 (−25%), DRY50 (−50%), WET25 (+25%) and WET50 (+50%). Ten 24 h integrations are performed in each group. We focus on 2 m surface air temperature (SAT) greater than 35 °C (the threshold of "high-temperature" events in China) at 06:00 UTC (roughly 14:00 LT in the study domain) to analyse the occurrence of the high-temperature event. The 10-day mean results show that the 06:00 UTC SAT (SAT06) is sensitive to the SMOIS change; specifically, SAT06 exhibits an apparent increase with the SMOIS decrease (e.g. compared with CTL, DRY25 generally results in a 1 °C SAT06 increase over the land surface of East China), areas with 35 °C or higher SAT06 are the most affected, and the simulations are more sensitive to the SMOIS decrease than to the SMOIS increase, which suggests that hot weather can be amplified under low soil moisture conditions. Regarding the mechanism underlying the extremely high SAT06, sensible heat flux has been shown to directly heat the lower atmosphere, and latent heat flux has been found to be more sensitive to the SMOIS change, resulting in an overall increase in surface net radiation due to the increased greenhouse effect (e.g. with the SMOIS increase from DRY25 to CTL, the 10-day mean net radiation increases by 5 W m⁻²). Additionally, due to the unique and dynamic nature of the western Pacific subtropical high, negative feedback occurs between the regional atmospheric circulation and the air temperature in the lower atmosphere while positive feedback occurs in the mid-troposphere. Using a method based on an analogous temperature relationship, a detailed analysis of the physical processes shows that for the SAT change, the SMOIS change affects diabatic processes (e.g. surface fluxes) more strongly than the adiabatic process of subsidence in the western Pacific subtropical high in the five groups of simulations. Interestingly, although diabatic processes dominate subsidence during the daytime and night-time separately, they do not necessarily dominate during the 24 h periods (e.g. they are dominant in the WET and CTL simulations only). Further, as the SMOIS decreases, the SAT06 increases, which is largely due to the reduced cooling effect of the diabatic processes, rather than the warming effect of subsidence. Unlike previous studies on heatwave events at climate timescales, this paper presents the sensitivity of simulated short-term hot weather to initial soil moisture and emphasises the importance of appropriate soil moisture initialization when simulating hot weather.

A heavy rainfall event occurring in the Yangtze‐Huaihe valley and south China during late June, 2003 was simulated to examine the effects of different land‐surface schemes on simulated precipitations using the Weather Research and Forecasting Model (WRF) Version 3.1 and National Centers for Environmental Prediction (NCEP) analysis data. The simulation was performed in the short‐range mode for 24‐h integrations. The results show that generally the simulated heavy rainfall event is sensitive to different land‐surface schemes, the scheme‐induced difference of threat score becomes larger as the forecast categories of rainfall gets higher within the relatively large study subarea, where the scheme‐induced relative differences of precipitation can amount up to 30% with an average of 7%, while the maximum values of daily precipitation differences can be as large as 100%~150%, and different schemes lead to simulated systematic differences in averaged sensible and latent heat fluxes that are characterized by regional distributions. Finally, the land‐surface schemes can substantially affect the simulated precipitations via two mechanisms, i.e., by affecting land surface evaporation, and by affecting low‐level atmospheric circulation and water vapor convergence, the schemes exert great influences, respectively, on the simulated rainfall over a relatively large area of the model domain (e.g., with an average difference of 7% and a maximum difference of ~30%), and on simulated heavy rainfalls within small areas including rainfall centers (e.g., up to differences within 100%~150%). All these suggest that different land surfaces affect heavy rainfall weather at different spatial scales and to different extents, and that improving the land‐surface schemes can lead to better simulation of the heavy‐rainfall weather with the WRF model.