The South Asian summer monsoon is a complex coupled human-natural system that poses unique challenges for understanding its evolution alongside increasing anthropogenic activities. Rapid and substantial changes in land-use, landmanagement and industrial activities over the subcontinent, and warming in the Indian Ocean, have influenced the South Asian summer monsoon. These might continue to be significant drivers in the near-term along with rising global greenhouse gas emissions. Deciphering the region's vulnerability to climate change requires an understanding of how these anthropogenic activities, acting on a range of spatial scales, have shaped the monsoon spatially and temporally. This review summarizes historical changes in monsoon rainfall characteristics, associated mechanisms, and the role of anthropogenic forcings, focusing on subseasonal variability and extreme events. Several studies have found intensified subseasonal extremes across parts of India and an increase in spatial variability of rainfall despite an overall weakening of seasonal rainfall in the monsoon core. However, understanding these changes remains challenging because of uncertainties in observations and climate models. The mechanisms and relative influences of various anthropogenic activities, particularly on subseasonal extremes, remain relatively underexplored. Large biases in the representation of relevant processes in global climate models limit the ability to attribute historical changes and make reliable projections. Nevertheless, recent advances in modeling these processes using higher-resolution modeling frameworks provide new tools to investigate the Indian summer monsoon's response to various anthropogenic forcings. There is an urgent need to understand how these forcings interact to shape climate variability and change in this vulnerable region. This article is categorized under:Paleoclimates and Current Trends > Earth System Behavioranthropogenic forcings, climate change attribution, extreme events, South Asian monsoon, subseasonal variability | INTRODUCTIONSouth Asia is one of the world's most densely populated regions, with a large fraction of people dependent on monsoonrelated activities for their livelihood. The summer monsoon season is the prime agricultural season for most of South Asia and the yields of the major cereal crops are highly sensitive to seasonal temperature and precipitation variability (DeFries et al., 2016). Recent studies have also highlighted the substantial impacts that subseasonal precipitation variability has on crop yields

The difference in land surface temperature (LST) between an urban region and its nearby non–urban region, known as surface urban heat island intensity (SUHII), is usually positive as reported in earlier studies. India has experienced unprecedented urbanization over recent decades with an urban population of 380 million. Here, we present the first study of the diurnal and seasonal characteristics of SUHII in India. We found negative SUHII over a majority of urban areas during daytime in pre-monsoon summer (MAM), contrary to the expected impacts of urbanization. This unexpected pattern is associated with low vegetation in non-urban regions during dry pre-monsoon summers, leading to reduced evapotranspiration (ET). During pre-monsoon summer nights, a positive SUHII occurs when urban impacts are prominent. Winter daytime SUHII becomes positive in Indo-Gangetic plain. We attribute such diurnal and seasonal behaviour of SUHII to the same of the differences in ET between urban and non-urban regions. Higher LST in non-urban regions during pre-monsoon summer days results in intensified heatwaves compared to heatwaves in cities, in contrast to presumptions made in the literature. These observations highlight the need for re-evaluation of SUHII in India for climate adaptation, heat stress mitigation, and analysis of urban micro-climates.

India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.

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The intensification of precipitation extremes in a warming world has been reported on a global scale and is traditionally explained with the Clausius-Clapeyron (C-C) relation. The relationship is observed to be valid in mid-latitudes; however, the debate persists in tropical monsoon regions, with the extremes of the Indian Summer Monsoon Rainfall (ISMR) being a prime example. Here, we present a comprehensive study on the dependence of ISMR extremes on both the 2 m surface air temperature over India and on the sea surface temperature over the tropical Indian Ocean. Remarkably, the ISMR extremes exhibit no significant association with temperature at either spatial scale: neither aggregated over the entire India/Tropical Indian Ocean area nor at the grid levels. We find that the theoretical C-C relation overestimates the positive changes in precipitation extremes, which is also reflected in the Coupled Model Intercomparison Project 5 (CMIP5) simulations. We emphasize that the changing patterns of extremes over the Indian subcontinent need a scientific re-evaluation, which is possible due to availability of the unique long-term in-situ data. This can aid bias correction of model projections of extremes whose value for climate adaptation can hardly be overemphasized, especially for the developing tropical countries.