Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/15105
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dc.contributor.authorSharma, Priyanken_US
dc.date.accessioned2024-12-24T05:20:04Z-
dc.date.available2024-12-24T05:20:04Z-
dc.date.issued2025-
dc.identifier.citationPaul, S., Sharma, P. J., & Teegavarapu, R. S. V. (2025). Rain event detection and magnitude estimation during Indian summer monsoon: Comprehensive assessment of gridded precipitation datasets across hydroclimatically diverse regions. Atmospheric Research. Scopus. https://doi.org/10.1016/j.atmosres.2024.107761en_US
dc.identifier.issn0169-8095-
dc.identifier.otherEID(2-s2.0-85208940638)-
dc.identifier.urihttps://doi.org/10.1016/j.atmosres.2024.107761-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/15105-
dc.description.abstractAccurate precipitation estimates are quintessential for hydrologic modeling and climate studies. Different gridded precipitation products are available in any region, and selecting the best one is essential for hydroclimatic modeling and analysis. In the current study, observation- (APHRODITE), reanalysis- (IMDAA, ERA5-Land, PGF), satellite-based (IMERG, CHIRPS, PERSIANN-CDR), and hybrid (MSWEP) gridded precipitation products with different spatial and temporal resolutions are evaluated using several continuous, categorical, graphical, and interval-based performance measures towards detecting Indian Summer Monsoon Rainfall (ISMR) events and estimating their magnitudes for the subcontinent of India, considering IMD gauge-based gridded data as reference product. We confine our analysis to the monsoon season (i.e., June to September), the principal rainy season in the Indian sub-continent. The dearth of data and limited rain gauge-based observations from non-uniform sparse monitoring networks across India necessitated grid-to-grid comparative evaluations instead of point-to-grid assessments. We propose a new ranking framework to determine the suitability of precipitation datasets for twenty-seven hydroclimatic regions comprising homogeneous rainfall zones, Köppen-Geiger climate zones, and major river basins. Results from the comprehensive evaluation suggest that (1) APHRODITE, MSWEP, and ERA5-Land best approximate precipitation event occurrences across India, (2) MSWEP and ERA5-Land are most suitable (highest rank) alternatives at the regional level, while APHRODITE is found to be next suitable dataset owing to its persistent dry bias, (3) CHIRPS and IMERG have reasonably lower rank score across India, (4) close agreement of examined datasets is noted over semi-arid and sub-humid regions (e.g., peninsular and central India), whereas ERA5-Land, IMDAA, and APHRODITE fail to detect and reproduce the intensity of the events along the west coast and northeastern India, (5) PGF and PERSIANN-CDR are the least situated datasets. Moreover, the present study provides a unique and innovative perspective to characterise the precipitation over a vast topographic, ecologic, and climatic gradient region like India. © 2024en_US
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.sourceAtmospheric Researchen_US
dc.subjectAPHRODITEen_US
dc.subjectERA5-landen_US
dc.subjectFrequency-based performance measuresen_US
dc.subjectIndian Summer Monsoon Rainfall (ISMR)en_US
dc.subjectMSWEPen_US
dc.subjectRankingen_US
dc.titleRain event detection and magnitude estimation during Indian summer monsoon: Comprehensive assessment of gridded precipitation datasets across hydroclimatically diverse regionsen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Civil Engineering

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