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How well do multi-source ensemble rainfall products capture precipitation during monsoons in India?

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Abstract

This study evaluated the effectiveness of the Multi-Source Ensemble Rainfall Analysis (MERA) product in capturing precipitation patterns exclusively during the southwest monsoon season in India. MERA combines data from multiple satellite sources, including INSAT-3D, GPM-IMERG, and GSMaP, to generate high-resolution (4 km hourly) rainfall estimates. The methodology involves the bias correction of individual satellite products, weighted blending, and ensemble generation. The performance of MERA was assessed through spatial, temporal, and statistical comparisons with gauge observations and other satellite products for the 2020 monsoon season. The results showed that MERA captures spatial rainfall patterns well, especially in regions with complex topographies. It demonstrates improved accuracy in detecting light to moderate rainfall compared to individual satellite products. However, the performance declines for high-intensity rainfall events. Statistical evaluation shows that MERA exhibits lower errors and stronger correlation with gauge observations compared to other products across most regions. These findings underscore the potential of MERA for improving monsoon rainfall monitoring and prediction in India, while also highlighting the need for continued refinement. Hence, suggesting that MERA could be used to validate high-resolution operational numerical weather prediction (NWP) models, further emphasizing its potential applications in meteorological research and forecasting.

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Acknowledgements

This work was supported by the Ministry of Earth Sciences, Government of India, under the National Monsoon Mission (Phase II). The authors acknowledge the India Meteorological Department (IMD) for providing conventional and gridded observational datasets used for validation. Computational resources were provided by the Mihir High-Performance Computing facility at the National Centre for Medium Range Weather Forecasting (NCMRWF). The authors also acknowledge NASA for the GPM-IMERG data, JAXA for the GSMaP data, and ISRO for the INSAT-3D observations. The first author gratefully acknowledges Mr. O. P. Sreejith (IMD Pune) for providing IMD gauge observations and Dr. Luigi Renzullo for his valuable contributions to the MERA project under the Monsoon Mission Phase II.

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  1. National Centre for Medium Range Weather Forecasting (NCMRWF), Ministry of Earth Sciences (MoES), A-50, Sector-62, Noida, Uttar Pradesh, 201309, India

    K. Amarjyothi, D. Preveen Kumar, M. Venkatarami Reddy, Ashis. K. Mitra, M. N. Raghavendra Sreevathsa, M. Neha Rajput & V. S. Prasad

  2. TERI School of Advanced Studies, New Delhi, India

    Ashis. K. Mitra

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  1. K. Amarjyothi
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  2. D. Preveen Kumar
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Amarjyothi, K., Kumar, D.P., Reddy, M.V. et al. How well do multi-source ensemble rainfall products capture precipitation during monsoons in India?. Meteorol Atmos Phys 137, 49 (2025). https://doi.org/10.1007/s00703-025-01098-4

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