Abstract

AbstractThis study investigates the projected heatwaves for India using 0.25° × 0.25° summer mean temperature data from Coupled Model Intercomparison Project (CMIP) 5 and 6 simulations for 2016–2100. The heatwaves were delineated using count and density‐based indices. A new approach of using medians of past as threshold for computing projected variables was introduced to amplify the footprint of the warming signal on the heatwaves. Further, spatio‐climatic heterogeneity of India was accounted through optimizing climatic zones using the fuzzy c‐mean clustering technique. Temporal homogeneity, trend, intensification and attribution of the heatwave variables were computed and analysed. Additionally, the scenario uncertainty was partitioned from the internal climatic variability, and consequently the variables were modelled within a probabilistic framework. Within this probabilistic framework, a novel concept of intensification ratio was introduced to capture the cost of climate action/inaction on heatwaves in India. All the heatwave variables except heatwave count have breaks in homogeneity between 2045 and 2055 and show predominantly increasing trends. While heatwave count shows an intensification of 4–6 times over the past, with 70% of the intensification being attributable to climate change, for other variables, the figures are 35–30 times and 95%. The scenario uncertainty surpasses the internal climatic variability around 2050. The probabilistic framework yields normalized values of uncertainty mostly below 0.5, enhancing the applicability of the results. Finally, the intensification ratio shows that climate inaction will intensify the heatwaves for ~75% of India by ~50–100%. The intensification of heatwave density over its count and relative accentuation of heatwaves resulting from climate inaction are the major takeaways from this study.

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