Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/15103
Title: Indian Summer Monsoon Rainfall Characteristics Derived From Multiple Gridded Precipitation Datasets: A Comparative Assessment
Authors: Sharma, Priyank
Keywords: frequency-based performance measures;gridded precipitation datasets;Indian summer monsoon rainfall (ISMR);performance assessment;rank score
Issue Date: 2024
Publisher: John Wiley and Sons Ltd
Citation: Paul, S., Sharma, P. J., & Teegavarapu, R. S. V. (2024a). Indian Summer Monsoon Rainfall Characteristics Derived From Multiple Gridded Precipitation Datasets: A Comparative Assessment. International Journal of Climatology. Scopus. https://doi.org/10.1002/joc.8708
Abstract: Precipitation, a crucial component of the Earth system processes, regulates the spatiotemporal cyclicity of water, energy, and carbon fluxes. Accurate precipitation datasets leverage the understanding of precipitation dynamics and are vital for hydro-climatological studies. South Asian monsoon is a complex, multi-scale interacting, synoptic, and ocean–land–atmosphere coupled system, contributing to significant spatial and temporal variability in summer monsoonal rainfall across India. This study evaluates four types of gridded (observational, satellite, reanalysis, and hybrid) precipitation products in their ability to replicate Indian Summer Monsoonal Rainfall (ISMR) characteristics using the India Meteorological Department (IMD) 0.25° gridded data as the baseline. A comparative assessment is performed in this study that uses several continuous and interval-based performance measures to evaluate the overall rainfall magnitude detectability and time-matched capturing of rainfall events. A new metric, rank score, is developed by aggregating multiple measures to find the best product. The analyses based on several performance measures indicate that MSWEP is the best dataset (rank one) that closely approximates the occurrence and magnitude of IMD-based rainfall events, while APHRODITE, CHIRPS, and IMDAA are ranked as the next best set of products. PGF is ranked the lowest among all products evaluated and is not recommended for applications. Nonetheless, APHRODITE suffers from strong negative biases, while the reanalysis (IMDAA, ERA5-Land, PGF) datasets show significant positive biases. Among the products evaluated, APHRODITE, ERA5-Land, and IMDAA have shown a limited ability to detect excess, normal, and deficit monsoon years, respectively. In general, the performance of satellite-based data products is superior to that of reanalysis datasets in accurately characterising the monsoon years. ERA5-Land is noted to be the best-performing dataset among the reanalysis products. The comprehensive comparative assessment carried out in this study benefits the selection and use of appropriate gridded precipitation products for hydroclimatic modelling, climate variability, and change studies. © 2024 Royal Meteorological Society.
URI: https://doi.org/10.1002/joc.8708
https://dspace.iiti.ac.in/handle/123456789/15103
ISSN: 0899-8418
Type of Material: Journal Article
Appears in Collections:Department of Civil Engineering

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