Present study focuses on rainfall over Western Ghats (WG), a complex topographic region (elevation > 500 m) of India to evaluate and to better understand the satellite behavior in contrast with a flat region (FR) (elevation < 500 m) of central India from 1998 to 2016 using the combinatory data sets of TMPA and IMERG (satellite rainfall estimation). The categorical Intra Seasonal Oscillations (ISO) of Indian summer monsoon (ISM) namely, Madden Julian Oscillation (MJO) and Quasi Bi-Weekly Oscillation (QBWO) are tested in satellite and India Meteorological Department (IMD) gridded rainfall data sets to find out the satellite performance. As the accurate estimation of rainfall from satellites over higher elevation zones is challenging, here we propose a new perspective to select the rainfall products of satellite for better comparison with ground measurements. Considering the satellite’s best capability in detecting the cold clouds resulting from deep convection and its coupling with higher-level circulation, we show that the rainfall from satellites yield fruitful comparison with ground measurements when moist static stability, tropical easterly jet is above the climatological values.

In the present study, we analyse large‐scale connections to deadly heatwaves in India in spring. Deadly Indian heatwaves occur in the spring months of April and May, and are increasing in recent years. These events are associated with the amplification of planetary Rossby waves. This amplification is called quasi‐resonant amplification (QRA). An increase of amplitude or resonance occurs when stationary and moving waves coincide in their size. Previous studies stressed QRA's role in summer because persistent extreme weather events such as the 2003 European heatwave, the 2010 Pakistan flood, Russian heatwave, the 2011 Texas and Oklahoma heat waves, and drought occurred in summer. QRA seems to be related to the amplification of Arctic warming in winter and summer, but observations show that Arctic warming occurs in spring also. The novel aspect of our study is that we found strong evidence for QRA in the boreal spring, the season of Indian heatwaves. Amplified Arctic warming or Arctic amplification thought to be responsible for QRA occurs in spring also. Our results confirm that maximum surface temperatures in spring over India show predictability with high statistical significance, about 4 days ahead. Maximum surface temperatures can be used to predict heatwaves, as shown earlier by some authors.

The Indian summer monsoon (ISM) rainfall is often influenced by El Niño‐Southern Oscillation (ENSO) on the interannual time scale. Physical mechanisms that link the canonical El Niño and ISM rainfall have been well documented. Very few studies have discussed the pathways that link El Niño Modoki and ISM rainfall variations. In this study using long period (1901‐2014) reanalysis and observed rainfall data, it is found that rainfall anomalies are negative over the southern peninsular India and positive over the central parts of India during El Niño Modoki years. Detailed analysis suggests that the El Niño Modoki modulates ISM rainfall by inducing changes in the western north Pacific (WNP) low level circulation. The weak positive rainfall over the monsoon trough region is due to weak moisture convergence associated with the westward extension of WNP cyclonic circulation corroborated by lows and depressions. Anomalous WNP cyclonic circulation is induced by the central Pacific Sea Surface Temperature (SST) warming associated with the El Niño Modoki. Further, strong moisture divergence over south peninsular India caused negative rainfall anomalies during the El Niño Modoki years. Thus, WNP circulation plays a critical role in determining the ISM rainfall patterns during the El Niño Modoki years as evidenced by significant correlation between WNP circulation pattern and EMI. These regional rainfall patterns over the Indian subcontinent corresponding to El Niño Modoki are not well explained in previous studies. It is found that many Coupled Model Intercomparison Project Phase 5 (CMIP5) models displayed poor skill in representing the relation between ISM rainfall and El Niño Modoki events due to unrealistic simulation of SST and circulation patterns over the Indo‐Pacific region. This suggests that CMIP5 models tend to have a large diversity in representing the El Niño Modoki teleconnections to ISM rainfall.

India has experienced remarkable changes in temperature extremes in recent decades due to rapid global warming leading to extreme heat events with disastrous societal impacts. In response to continuing global warming, this study investigates summertime (March–June) heatwave characteristics over India in the present and future climate. During 1951–2020, India Meteorological Department observational data show rising trends in heatwave characteristics such as frequency, intensity, duration, and season length, mainly over India’s northwest, central, and south peninsular regions. Further, the present study explores the changes in future heatwave characteristics using the state-of-the-art statistically downscaled bias-corrected climate models data from Coupled Model Intercomparison Project Phase 6 (CMIP6) of the Shared Socioeconomic Pathway scenario. This study uses varying hazard thresholds, namely fixed (time-invariant historical climatological threshold) and decadal moving thresholds (time-varying future climatological threshold), to define heatwaves and examine the future changes in heatwave characteristics over India. Results show a significant increase in mean summertime heatwaves defined using fixed thresholds in terms of their frequency, duration, number, amplitude, cumulative magnitude, and season length in the near future (NF) (2025–2054) and the far future (FF) (2065–2094) compared to the baseline period (1985–2014) over much of India, with the most substantial increases seen in the FF. However, heatwaves defined using the decadal moving thresholds show no significant changes in their characteristics during the NF but a substantial change in the FF over many parts of India. This work is the first attempt to use bias-corrected CMIP6 models data to project heatwave characteristics utilising the concept of the varying hazard thresholds across India. Overall, this study provides a comprehensive assessment of climate change’s impact on Indian heatwaves, which can help in planning better adaptation and mitigation strategies.

Given the wide use of the multi-climate model mean (MMM) for impact assessment studies, this work examines the fidelity of Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating the features of Indian summer monsoons as well as the post-rainy seasons for assessing the possible impacts of climate change on post-rainy season sorghum crop yields across India. The MMM simulations captured the spatial patterns and annual cycles of rainfall and surface air temperatures. However, bias was observed in the precipitation amounts and daily rainfall intensity. The trends in the simulations of MMM for both precipitation and temperatures were less satisfactory than the observed climate means. The Crop Environment Resource Synthesis (CERES)-sorghum model was used to estimate the potential impacts of future climate change on post-rainy season sorghum yield values. On average, post-rainy season sorghum yields are projected to vary between −4% and +40% as well as +10% and +59% in the near future (2040–2069) for RCP 4.5 and RCP 8.5, respectively, and between +20% and +70% (RCP 4.5) as well as +38% and +89% (RCP 8.5) in the far future (2070–2099). Even though surface air temperatures are increasing in future climate change projections, the findings suggest that an increase in the post-rainy season sorghum yields was due to an increase in the rainfall amounts up to 23% and an increase in the atmospheric CO₂ levels by the end of the 21st century. The results suggest that the projected climate change during the post-rainy season over India is an opportunity for smallholders to capitalize on the increase in rainfall amounts and further increase sorghum yields with appropriate crop management strategies.