The Dichotomy of Wet and Dry Trends Over India by Aerosol Indirect Effects in CMIP5 Models

Journal Article · 13 August 2023 · Earth's Future

DOI: https://doi.org/10.1029/2022EF003266 · OSTI ID:1995030

Rai, Pradeep Kumar ^[1]; Sarangi, Chandan  ^[1]; Arun, N.  ^[1]; Kuiry, S. N.  ^[1]; Leung, L. Ruby  ^[2]

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1. Department of Civil Engineering Indian Institute of Technology Madras Chennai India
2. Pacific Northwest National Laboratory Richland WA USA

Abstract Aerosol‐cloud interactions, also known as aerosol indirect effect (AIE), substantially impact rainfall frequency and intensity. Here, we analyze NEX‐GDDP, a multimodel ensemble of high‐resolution (0.25°) historical simulations and future projections statistically downscaled from 21 CMIP5 models, to quantify the importance of AIE on extreme climate indices, specifically consecutive dry days (CDD), consecutive wet days (CWD), and simple daily intensity index (SDII). The 21 NEX‐GDDP CMIP5 models are classified into models with reliable (REM) and unreliable (UREM) monsoon climate simulated over India based on their simulations of the climate indices. The REM group is further decomposed based on whether the models represent only the direct (REM _ADE ) or the direct and indirect (REM _ALL ) aerosol effects. Compared to REM _ADE , including all aerosol effects significantly improves the model skills in simulating the observed historical trends of all three climate indices over India. Specifically, AIE enhances dry days and reduces wet days in India in the historical period, consistent with the observed changes. However, by the middle and end of the 21st century, there is a relative decrease in dry days and an increase in wet days and precipitation intensity. Moreover, the REM _ALL simulated future CWD and CDD changes are mostly opposite to those in REM _ADE , indicating the substantial role of AIE in the future projection of dry and wet climates. These findings underscore the crucial role of AIE in future projections of the Indian hydroclimate and motivate efforts to accurately represent AIE in climate models.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Grant/Contract Number: AC05-76RL01830
• OSTI ID: 1995030
• Report Number(s): PNNL-SA-192622; e2022EF003266
• Journal Information: Earth's Future, Journal Name: Earth's Future Journal Issue: 8 Vol. 11; ISSN 2328-4277
• Publisher: American Geophysical Union (AGU)Copyright Statement
• Country of Publication: United States
• Language: English