Indian Summer Monsoon Rainfall Characteristics Derived From Multiple Gridded Precipitation Datasets: A Comparative Assessment

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.

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Publication Details

Journal
International Journal of Climatology
Published
2024-12-10
DOI
https://doi.org/10.1002/joc.8708
Citations
7
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
2.63
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article

Indian Summer Monsoon Rainfall Characteristics Derived From Multiple Gridded Precipitation Datasets: A Comparative Assessment

Priyank J. Sharma, Ramesh S. V. Teegavarapu, Sandipan Paul
7 citations
International Journal of Climatology
Precipitation Measurement and Analysis
2.63
article

Indian Summer Monsoon Rainfall Characteristics Derived From Multiple Gridded Precipitation Datasets: A Comparative Assessment

Priyank J. Sharma, Ramesh S. V. Teegavarapu, Sandipan Paul
article en
7 citations

Abstract

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.

International Journal of ClimatologyVol. 45(2)
Indian Institute of Technology Bombay (IN), Florida Atlantic University (US), Indian Institute of Technology Indore (IN)
Life below water
Openalex Percentile: Top 10%
Precipitation Measurement and Analysis
2.63
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