Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/6214
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dc.contributor.authorDubey, Saketen_US
dc.contributor.authorGupta, Harshiten_US
dc.contributor.authorGoyal, Manish Kumaren_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-21T10:45:54Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-21T10:45:54Z-
dc.date.issued2021-
dc.identifier.citationDubey, S., Gupta, H., Goyal, M. K., & Joshi, N. (2021). Evaluation of precipitation datasets available on google earth engine over india. International Journal of Climatology, 41(10), 4844-4863. doi:10.1002/joc.7102en_US
dc.identifier.issn0899-8418-
dc.identifier.otherEID(2-s2.0-85103419093)-
dc.identifier.urihttps://doi.org/10.1002/joc.7102-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/6214-
dc.description.abstractMonthly mean precipitation estimates of seven products (TerraClimate, TRMM, CHIRPS, PERSIANN-CDR, GPM-IMERG, ERA5 and CFSR) available on Google earth engine (GEE) are evaluated against gridded gauge-based precipitation product available from Indian Meteorological Department (IMD) for their skills and presence of systematic biases (during 2001–2018). All these products represent the climatological features reasonably well. Presence of systematic biases in these products is also observed from their evaluation. Biases across the periphery of the country are relatively on the higher side in comparison to the central regions. The magnitude of spatial variability is represented better for winter precipitation in comparison to summer precipitation. During both winter and summer, ensemble mean of various products outperforms individual products in terms of both RMSE and correlation. Performance of these products is also assessed across various Indian states, elevation bands and climate zones. The ability of these products to represent the seasonality was observed to be highest for the states with mid-ranged peaks (10–20 mm·day−1) which tend to decrease with both increasing and decreasing peaks. Ability of the precipitation products to resemble the annual cycle does not vary with the amount of precipitation, although individual disparity among the products exists. Additionally, an alternative approach for data evaluation using Multiple Triple Collocation (MTC) was performed for the period 2001–2015 using an additional dataset obtained from soil-moisture-based rainfall estimates (SM2RAIN). Results from MTC convey that ERA5 performs relatively poor in comparison to the other products for central India followed by CFSR. In brief, the comprehensive evaluation of precipitation products reported herein will act a valuable reference for the researchers as well as decision makers to select the optimal product for their intended application and will inform the users about the various uncertainties in the foundations and specification of these products. © 2021 Royal Meteorological Societyen_US
dc.language.isoenen_US
dc.publisherJohn Wiley and Sons Ltden_US
dc.sourceInternational Journal of Climatologyen_US
dc.subjectDecision makingen_US
dc.subjectEnginesen_US
dc.subjectRain gagesen_US
dc.subjectSoil moistureen_US
dc.subjectComprehensive evaluationen_US
dc.subjectDecision makersen_US
dc.subjectMean precipitationen_US
dc.subjectPrecipitation productsen_US
dc.subjectRainfall estimatesen_US
dc.subjectSpatial variabilityen_US
dc.subjectSummer precipitationen_US
dc.subjectWinter precipitationen_US
dc.subjectPetroleum reservoir evaluationen_US
dc.subjectclimate modelingen_US
dc.subjectcomparative studyen_US
dc.subjectdata seten_US
dc.subjectInterneten_US
dc.subjectprecipitation (climatology)en_US
dc.subjectregional climateen_US
dc.subjectIndiaen_US
dc.titleEvaluation of precipitation datasets available on Google earth engine over Indiaen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Civil Engineering

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