Precipitation Extremes over India in a Coupled Land–Atmosphere Regional Climate Model: Influence of the Land Surface Model and Domain Extent

Author:

Mishra Alok Kumar12,Dinesh Anand Singh3,Kumari Amita4,Pandey Lokesh Kumar3

Affiliation:

1. K Banerjee Centre of Atmospheric and Ocean Studies, University of Allahabad, Prayagraj 211002, India

2. Volcani Institute, Agricultural Research Organization, Rishon LeZion 7505101, Israel

3. Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Bhopal, Bhopal 462066, India

4. The Fredy & Nadine Herrmann Institute of Earth Sciences, Hebrew University Jerusalem, The Edmond J. Safra Campus—Givat Ram, Jerusalem 9190401, Israel

Abstract

The frequency and intensity of extreme precipitation events are on the rise worldwide. Despite extensive efforts, regional climate models still show significant biases for extreme precipitation events, often due to factors like improper physics, the choice of land surface model, and spatial domain. Thus, this study uses a Coupled Land–Atmosphere Regional Climate Model version 4.7 (RegCM4.7) to explore how the choice of land surface models (LSMs) and domain extent affects the simulation of extreme precipitation over India. In this regard, a total of four sensitivity experiments have been carried out using two LSMs (CLM4.5 and BATS) over each of the two domains (one over the bigger South Asia CORDEX domain and another for the smaller domain over the Indian region). The main objective is to provide a holistic idea for obtaining an optimum model domain and LSMs for precipitation extremes over India. The model performance is demonstrated for extreme precipitation and associated processes. The result shows the systematic discrepancy in simulating extreme precipitation with a strong inter-simulation spread, indicating the strong sensitivity of extreme precipitation on the LSMs as well as the model domain. The BATS configuration shows a significant overestimation of consecutive wet days and very low precipitation, partially associated with a deficiency in convection. By contrast, the considerable underestimation of intense precipitation can be attributed to the presence of frequent, light drizzle, which hinders the accumulation of moisture in the atmosphere to a sufficient degree to prevent extreme rainfall. Despite significant improvement, the best-configured model (CLM with Indian domain) still indicates substantial bias for extreme precipitation. This deficiency in the model could potentially be mitigated by enhancing both horizontal and vertical resolutions. Nevertheless, further research is needed to explore other physics parameterizations and dynamic mechanisms to address this issue.

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

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