{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T19:57:23Z","timestamp":1775851043135,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2023,7,7]],"date-time":"2023-07-07T00:00:00Z","timestamp":1688688000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monitoring water resources globally is crucial for forecasting future geo-hydro disasters across the Earth. In the present study, an attempt was made to assess the functional dimensionality of multi-satellite precipitation products, retrieved from CHIRPS, NASA POWER, ERA-5, and PERSIANN-CDR with respect to the gridded India Meteorological Department (IMD) precipitation dataset over a period of 30+ years (1990\u20132021) on monthly and yearly time scales at regional, sub regional, and pixel levels. The study findings showed that the performance of the PERSIANN-CDR dataset was significantly better in Central India, Northeast India, and Northwest India, whereas the NASA-POWER precipitation product performed better in Central India and South Peninsular of India. The other two precipitation products (CHIRPS and ERA-5) showed the intermediate performance over various sub regions of India. The CHIRPS and NASA POWER precipitation products underperformed from the mean value (3.05 mm\/day) of the IMD gridded precipitation product, while the other two products ERA-5 and PERSIANN-CDR are over performed across all India. In addition, PERSIANN-CDR performed better in Central India, Northeast India, Northwest India, and the South Peninsula, when the yearly mean rainfall was between 0 and 7 mm\/day, while ERA-5 performed better in Central India and the South Peninsula region for a yearly mean rainfall above 0\u20137 mm\/day. Moreover, a peculiar observation was made from the investigation that the respective datasets were able to characterize the precipitation amount during the monsoon in Western Ghats. However, those products needed a regular calibration with the gauge-based datasets in order to improve the future applications and predictions of upcoming hydro-disasters for longer time periods with the very dense rain gauge data. The present study findings are expected to offer a valuable contribution toward assisting in the selection of an appropriate and significant datasets for various studies at regional and zonal scales.<\/jats:p>","DOI":"10.3390\/rs15133443","type":"journal-article","created":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T00:47:35Z","timestamp":1688950055000},"page":"3443","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Performance Assessment of Global-EO-Based Precipitation Products against Gridded Rainfall from the Indian Meteorological Department"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5302-7184","authenticated-orcid":false,"given":"Nitesh","family":"Awasthi","sequence":"first","affiliation":[{"name":"Department of Earth & Planetary Sciences, University of Allahabad, Prayagraj 211002, Uttar Pradesh, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0529-5437","authenticated-orcid":false,"given":"Jayant Nath","family":"Tripathi","sequence":"additional","affiliation":[{"name":"Department of Earth & Planetary Sciences, University of Allahabad, Prayagraj 211002, Uttar Pradesh, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1442-1423","authenticated-orcid":false,"given":"George P.","family":"Petropoulos","sequence":"additional","affiliation":[{"name":"Department of Geography, Harokopio University of Athens, El. Venizelou St., 70, Kallithea, 17671 Athens, Greece"}]},{"given":"Dileep Kumar","family":"Gupta","sequence":"additional","affiliation":[{"name":"Department of Physics, Institute of Science, Banaras Hindu University, Varanasi 221005, Uttar Pradesh, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8834-2464","authenticated-orcid":false,"given":"Abhay Kumar","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Physics, Institute of Science, Banaras Hindu University, Varanasi 221005, Uttar Pradesh, India"}]},{"given":"Amar Kumar","family":"Kathwas","sequence":"additional","affiliation":[{"name":"Haryana Space Applications Centre, Hisar 125004, Haryana, India"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1175\/BAMS-D-14-00283.1","article-title":"So, how much of the Earth\u2019s surface is covered by rain gauges?","volume":"98","author":"Kidd","year":"2017","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1016\/j.gsf.2014.02.009","article-title":"Effect of climate change on seasonal monsoon in Asia and its impact on the variability of monsoon rainfall in Southeast Asia","volume":"6","author":"Loo","year":"2015","journal-title":"Geosci. Front."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1002\/joc.3735","article-title":"The variability of the Southeast Asian summer monsoon","volume":"34","author":"Misra","year":"2014","journal-title":"Int. J. Climatol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Dikshit, K.R., and Dikshit, J.K. (2014). North-East India: Land, People and Economy, Springer.","DOI":"10.1007\/978-94-007-7055-3"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"50-1","DOI":"10.1029\/2002GL015522","article-title":"Role of Asian and African orography in Indian summer monsoon","volume":"29","author":"Chakraborty","year":"2002","journal-title":"Geophys. Res. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"287","DOI":"10.5194\/esd-4-287-2013","article-title":"Consistent increase in Indian monsoon rainfall and its variability across CMIP-5 models","volume":"4","author":"Menon","year":"2013","journal-title":"Earth Syst. Dyn."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"8987","DOI":"10.1002\/2015JD023437","article-title":"Comprehensive evaluation of multisatellite precipitation estimates over India using gridded rainfall data","volume":"120","author":"Sunilkumar","year":"2015","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Chauhan, A.S., Singh, S., Maurya, R.K.S., Kisi, O., Rani, A., and Danodia, A. (2022). Spatio-temporal analysis of rainfall dynamics of 120 years (1901\u20132020) using innovative trend methodology: A case study of Haryana, India. Sustainability, 14.","DOI":"10.3390\/su14094888"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s12524-015-0465-1","article-title":"Assessment of Kalpana-1 rainfall product over Indian meteorological sub-divisions during the summer monsoon season","volume":"44","author":"Bushair","year":"2016","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"177","DOI":"10.54302\/mausam.v69i2.261","article-title":"Validation of INSAT-3D derived rainfall estimates (HE & IMSRA), GPM (IMERG) and GLDAS 2.1 model rainfall product with IMD gridded rainfall & NMSG data over IMD\u2019s meteorological sub-divisions during monsoon","volume":"69","author":"Singh","year":"2018","journal-title":"Mausam"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"317","DOI":"10.54302\/mausam.v61i3.835","article-title":"Evaluation of Indian summer monsoon rainfall features using TRMM and KALPANA-1 satellite derived precipitation and rain gauge observation","volume":"61","author":"Durai","year":"2010","journal-title":"Mausam"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1111\/1745-5871.12068","article-title":"Meteorological Sub-divisional Scale Rainfall Monitoring Using K alpana-1 VHRR Measurements","volume":"52","author":"Mahesh","year":"2014","journal-title":"Geogr. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1007\/s00704-011-0435-7","article-title":"Large-scale precipitation estimation using Kalpana-1 IR measurements and its validation using GPCP and GPCC data","volume":"106","author":"Prakash","year":"2011","journal-title":"Theor. Appl. Climatol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1175\/1520-0477(1997)078<0005:TGPCPG>2.0.CO;2","article-title":"The global precipitation climatology project (GPCP) combined precipitation dataset","volume":"78","author":"Huffman","year":"1997","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1175\/JHM560.1","article-title":"The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales","volume":"8","author":"Huffman","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Setti, S., Maheswaran, R., Sridhar, V., Barik, K.K., Merz, B., and Agarwal, A. (2020). Inter-comparison of gauge-based gridded data, reanalysis and satellite precipitation product with an emphasis on hydrological modeling. Atmosphere, 11.","DOI":"10.3390\/atmos11111252"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.jhydrol.2012.01.011","article-title":"Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios","volume":"424","author":"Kling","year":"2012","journal-title":"J. Hydrol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1175\/BAMS-D-14-00017.1","article-title":"Global view of real-time TRMM multisatellite precipitation analysis: Implications for its successor global precipitation measurement mission","volume":"96","author":"Yong","year":"2015","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1016\/j.jhydrol.2016.01.029","article-title":"A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region","volume":"556","author":"Prakash","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_20","unstructured":"Prakash, S., Mitra, A.K., Gairola, R.M., Norouzi, H., and Pai, D.S. (2018). Remote Sensing of Aerosols, Clouds, and Precipitation, Elsevier."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.advwatres.2015.11.008","article-title":"From TRMM to GPM: How well can heavy rainfall be detected from space?","volume":"88","author":"Prakash","year":"2016","journal-title":"Adv. Water Resour."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3097","DOI":"10.5194\/acp-19-3097-2019","article-title":"From ERA-Interim to ERA5: The considerable impact of ECMWF\u2019s next-generation reanalysis on Lagrangian transport simulations","volume":"19","author":"Hoffmann","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"150066","DOI":"10.1038\/sdata.2015.66","article-title":"The climate hazards infrared precipitation with stations\u2014A new environmental record for monitoring extremes","volume":"2","author":"Funk","year":"2015","journal-title":"Sci. Data"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Wiwoho, B.S., Astuti, I.S., Alfarizi, I.A.G., and Sucahyo, H.R. (2021). Validation of three daily satellite rainfall products in a humid tropic watershed, Brantas, Indonesia: Implications to land characteristics and hydrological modelling. Hydrology, 8.","DOI":"10.3390\/hydrology8040154"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Saicharan, V., and Rangaswamy, S.H. (2023). A Comparison and Ranking Study of Monthly Average Rainfall Datasets with IMD Gridded Data in India. Sustainability, 15.","DOI":"10.3390\/su15075758"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Dubey, R.K., Dubey, P.K., Chaurasia, R., Rao, C.S., and Abhilash, P.C. (2021). Impact of integrated agronomic practices on soil fertility and respiration on the Indo-Gangetic Plain of North India. Agronomy, 11.","DOI":"10.3390\/agronomy11020402"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"4844","DOI":"10.1002\/joc.7102","article-title":"Evaluation of precipitation datasets available on Google earth engine over India","volume":"41","author":"Dubey","year":"2021","journal-title":"Int. J. Climatol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1559","DOI":"10.1007\/s10967-021-08056-5","article-title":"Assessment of physicochemical and radon-attributable radiological parameters of drinking water samples of Pithoragarh district, Uttarakhand","volume":"330","author":"Singh","year":"2021","journal-title":"J. Radioanal. Nucl. Chem."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1007\/s00704-020-03308-y","article-title":"Future changes in precipitation extremes during northeast monsoon over south peninsular India","volume":"142","author":"Rao","year":"2020","journal-title":"Theor. Appl. Climatol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.aca.2005.06.056","article-title":"Chemometric analysis of groundwater quality data of alluvial aquifer of Gangetic plain, North India","volume":"550","author":"Singh","year":"2005","journal-title":"Anal. Chim. Acta"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1007\/s12524-010-0033-7","article-title":"Application of landscape ecology and remote sensing for assessment, monitoring and conservation of biodiversity","volume":"38","author":"Singh","year":"2010","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1177\/2321024913515127","article-title":"Agro-Economic Indicators\u2014A Comparative Study of North-Eastern States of India","volume":"2","author":"Nandy","year":"2014","journal-title":"J. Land Rural. Stud."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1144\/GSL.SP.1997.120.01.15","article-title":"Tertiary palaeosurfaces of the SW Deccan, Western India: Implications for passive margin uplift","volume":"120","author":"Widdowson","year":"1997","journal-title":"Geol. Soc. Lond. Spec. Publ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.54302\/mausam.v65i1.851","article-title":"Development of a new high spatial resolution (0.25 \u00d7 0.25) long period (1901\u20132010) daily gridded rainfall data set over India and its comparison with existing data sets over the region","volume":"65","author":"Pai","year":"2014","journal-title":"Mausam"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1175\/JHM-D-14-0024.1","article-title":"Comparison of TMPA-3B42 versions 6 and 7 precipitation products with gauge-based data over India for the southwest monsoon period","volume":"16","author":"Prakash","year":"2015","journal-title":"J. Hydrometeorol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1175\/BAMS-D-13-00068.1","article-title":"PERSIANN-CDR: Daily precipitation climate data record from multisatellite observations for hydrological and climate studies","volume":"96","author":"Ashouri","year":"2015","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.jhydrol.2009.08.003","article-title":"Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling","volume":"377","author":"Gupta","year":"2009","journal-title":"J. Hydrol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"4323","DOI":"10.5194\/hess-23-4323-2019","article-title":"Inherent benchmark or not? Comparing Nash\u2013Sutcliffe and Kling\u2013Gupta efficiency scores","volume":"23","author":"Knoben","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Rahman, S., Sengupta, D., and Ravichandran, M. (2009). Variability of Indian summer monsoon rainfall in daily data from gauge and satellite. J. Geophys. Res. Atmos., 114.","DOI":"10.1029\/2008JD011694"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"9761","DOI":"10.1038\/s41598-020-66363-5","article-title":"Quantification of node importance in rain gauge network: Influence of temporal resolution and rain gauge density","volume":"10","author":"Tiwari","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"7183","DOI":"10.1029\/2000JD900719","article-title":"Summarizing multiple aspects of model performance in a single diagram","volume":"106","author":"Taylor","year":"2001","journal-title":"J. Geophys. Res. Atmos."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/13\/3443\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:07:58Z","timestamp":1760126878000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/13\/3443"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,7]]},"references-count":42,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2023,7]]}},"alternative-id":["rs15133443"],"URL":"https:\/\/doi.org\/10.3390\/rs15133443","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,7]]}}}