Evaluation of rainfall datasets from CHIRPS and WorldClim in Meghalaya, India

Limited ground-based rainfall information has posed significant obstacles to hydrological, agricultural and related studies in Meghalaya, India.In this study, rainfall products were validated against ground-based rain gauge data from the India Meteorological Department, over three seasons.Both qualitative categorical metrics -probability of detection, false alarm rate, critical success index and frequency bias index, as well as quantitative statistical measures including Pearson correlation coefficient (r), Nash-Sutcliffe efficiency, relative bias, RMSE-observations standard deviation ratio, were computed to evaluate rainfall from CHIRPS and WorldClim.The quantitative statistics showed that the total rainfall estimated by CHIRPS provided better estimates than WorldClim during pre-monsoon (February-May) and post-monsoon (October-January).Neither dataset could provide good estimates of rainfall during the monsoon season (June-September).From this study, we found that CHIRPS is a reliable alternate source of rainfall data for Meghalaya with a limited rain gauge network.

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Journal
Current Science
Published
2025-08-08
DOI
https://doi.org/10.18520/cs/v129/i3/232-239
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
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article

Evaluation of rainfall datasets from CHIRPS and WorldClim in Meghalaya, India

Ranjit Kumar Das, Pratibha T. Das, S. P. Aggarwal, Dimpul Sonowal
Current Science
Precipitation Measurement and Analysis
article

Evaluation of rainfall datasets from CHIRPS and WorldClim in Meghalaya, India

Ranjit Kumar Das, Pratibha T. Das, S. P. Aggarwal, Dimpul Sonowal
article en

Abstract

Limited ground-based rainfall information has posed significant obstacles to hydrological, agricultural and related studies in Meghalaya, India.In this study, rainfall products were validated against ground-based rain gauge data from the India Meteorological Department, over three seasons.Both qualitative categorical metrics -probability of detection, false alarm rate, critical success index and frequency bias index, as well as quantitative statistical measures including Pearson correlation coefficient (r), Nash-Sutcliffe efficiency, relative bias, RMSE-observations standard deviation ratio, were computed to evaluate rainfall from CHIRPS and WorldClim.The quantitative statistics showed that the total rainfall estimated by CHIRPS provided better estimates than WorldClim during pre-monsoon (February-May) and post-monsoon (October-January).Neither dataset could provide good estimates of rainfall during the monsoon season (June-September).From this study, we found that CHIRPS is a reliable alternate source of rainfall data for Meghalaya with a limited rain gauge network.

Current ScienceVol. 129(3)
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Evaluation of rainfall datasets from CHIRPS and WorldClim in Meghalaya, India — Ranjit Kumar Das, Pratibha T. Das, et al. · Current Science (2025) | TGRS Research Map | TGRS