The Indian subcontinent is one of the hotspots of deadly heat stress. Several attribution studies have shown increasing trends in heatwaves and its linkage with dry spells over South Asia. However, very few studies have investigated concurrent or successive (lagged d-day) occurrence of humid heat stress (high temperature compounded by humidity) and precipitation extremes within a short time window. Using gauge-based observation records of the last five decades, we have analyzed the concurrence of extreme wet bulb temperature, Tw and peak rain events in 9 urban locations of India, distributed over climatologically heterogeneous regions. We find a larger fraction of the population is exposed to a significant increase (more than 1% and up to 2.5%/decade) in mean and extreme Tw (around 1%/decade) in several sites than solely accounting dry-bulb temperature trends. This prompted us to analyze the compound hazard associated with storm events preceded by extreme Tw (assessed through ≥ 95 – 98.5th percentile exceedances and annual maxima series) up to a week of occurrence of the event. Considering synchronicity between two drivers (extreme Tw and peak rain), we demonstrate cities located across the western half of the country showed positive dependence, whereas those located over the eastern half show negative dependence. While negative correlation suggests the concurrence of dry and hot episodes, the positive correlation suggests robust amplification in precipitation extremes. This is confirmed by the large upper tail distributions of peak rain events during the core monsoon season (June – September) to locations showing positive dependence. Based on extreme Tw-precipitation sensitivity, we propose compound heat stress – rain-induced flood hazard model for densely populated areas. Understanding drivers of peak runoff responses would benefit risk management, insurance, and flash flood forecast, devising flood resilience under climate change.

The analysis of drought onset and their potential relationship to drought severity (deficit volume) are critical for providing timely information for agricultural operations, such as cultivation planning and crop productivity monitoring. A coupling between drought timing and deficit volume can be used as a proxy for drought-related damage estimation and associated risks. Despite its high importance, so far little attention was paid to determine the timing of drought and its linkage with deficit volume for hydrological droughts. This study utilizes quality-controlled streamflow observations from 1965 to 2018 to unveil regional patterns of hydrological drought onset, trends in event-specific deficit volume, and nonlinear relationships between onset timing and deficit volume across 97 rain-dominated catchments in Peninsular India (8-24o N, 72-87o E). Our results show a shift towards earlier hydrological drought onset in conjunction with a decrease in deficit volume during the Indian monsoon (June-September) season, which is contrasted by a delayed onset in the pre-monsoon (March-May) and post-monsoon (October-February) seasons. Further, approximately one-third of the catchments show a significant nonlinear dependency between drought deficit volume and onset time. We find environmental controls, such as soil organic carbon, vertical distance to channel network, and soil wetness are dominant factors in influencing droughts. Our analysis provides new insights into the causal chain and physical processes linking climatic and physiographic controls on streamflow drought mechanisms, which can support drought forecasting and climate impact assessment studies.

The cascade hazard, heat stress (preconditioned) and heavy rainfall (response) in close succession have become frequent in several areas of the globe, causing critical infrastructure failures. Although some regions of South Asia witness deadly humid heat stress, little is known about the linkage of humid heat stress (HHS; high temperature compounded by humidity) versus record rainfall and cascade hazard due to compound (same or lagged-day) occurrences of both extremes. We leverage ground-based meteorological records from 1970-2018 to analyze the risk of extreme precipitation preceded by heat stress over selected urban locations of India using a multivariate conditional-probability approach. We show that humid heat is likely to intensify the extreme rainfall, especially during the core monsoon (June-September) season. This phenomenon is associated with moisture convergence and large upper tail distributions of peak precipitation over several sites. Our insights to compound flood hazard would benefit (re)-insurance and flash flood forecast, devising adaptations.