Large-scale dynamics have greater role than thermodynamics in driving precipitation extremes over India
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Large‑scale dynamics have greater role than thermodynamics in driving precipitation extremes over India Naveen Sudharsan1 · Subhankar Karmakar1,2,3 · Hayley J. Fowler4 · Vittal Hari5 Received: 22 January 2020 / Accepted: 29 July 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The changing characteristics of precipitation extremes under global warming have recently received tremendous attention, yet the mechanisms are still insufficiently understood. The present study attempts to understand these processes over India by separating the ‘dynamic’ and ‘thermodynamic’ components of precipitation extremes using a suite of observed and reanalysis datasets. The former is mainly due to changes in atmospheric motion, while the latter is driven mainly by the changes associated with atmospheric moisture content. Limited studies have attributed dynamic and thermodynamic contributions to precipitation extremes, and their primary focus has been on the horizontal atmospheric motion component of the water budget. Our study, on the other hand, implements the decomposition of vertical atmospheric motion, based on the framework proposed by Oueslati et al. (Sci Rep 9: 2859, 2019), which has often been overlooked, especially for India. With the focus on two major and recent extreme events in the Kerala and Uttarakhand regions of India, we show that the vertical atmospheric motion has a more significant contribution to the events than the horizontal atmospheric motion. Further, decomposition of the vertical atmospheric motion shows that the dynamic component overwhelms the thermodynamic component’s contribution to these extreme events, which is found to be negligible. Using a threshold method to define extreme rainfall, we further extended our work to all India, and the results were consistent with those of the two considered events. Finally, we evaluate the contributions from the recently made available CMIP6 climate models, and the results are interestingly in alignment with the observations. The outcomes of this study will play a critical role in the proper prediction of rainfall extremes, whose value to climate adaptation can hardly be overemphasised.
1 Introduction
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00382-020-05410-3) contains supplementary material, which is available to authorized users. * Vittal Hari [email protected] 1
Environmental Science and Engineering Department, Indian Institute of Technology Bombay, Mumbai 400076, India
2
Interdisciplinary Program in Climate Studies, Indian Institute of Technology Bombay, Mumbai 400076, India
3
Centre for Urban Science and Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India
4
School of Engineering, Newcastle University, Newcastle‑upon‑Tyne, UK
5
Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research, UFZ, Leipzig, Germany
Human-induced climate change is evident, and currently poses a great concern to society, primarily due t
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