{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T02:51:40Z","timestamp":1774925500668,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T00:00:00Z","timestamp":1671753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["41931180"],"award-info":[{"award-number":["41931180"]}]},{"name":"National Natural Science Foundation of China","award":["51979263"],"award-info":[{"award-number":["51979263"]}]},{"name":"National Natural Science Foundation of China","award":["41901076"],"award-info":[{"award-number":["41901076"]}]},{"name":"National Natural Science Foundation of China","award":["41701019"],"award-info":[{"award-number":["41701019"]}]},{"name":"National Natural Science Foundation of China","award":["No.KYCX22_1210"],"award-info":[{"award-number":["No.KYCX22_1210"]}]},{"name":"the Jiangsu Province Postgraduate Research and Practice Innovation Program","award":["41931180"],"award-info":[{"award-number":["41931180"]}]},{"name":"the Jiangsu Province Postgraduate Research and Practice Innovation Program","award":["51979263"],"award-info":[{"award-number":["51979263"]}]},{"name":"the Jiangsu Province Postgraduate Research and Practice Innovation Program","award":["41901076"],"award-info":[{"award-number":["41901076"]}]},{"name":"the Jiangsu Province Postgraduate Research and Practice Innovation Program","award":["41701019"],"award-info":[{"award-number":["41701019"]}]},{"name":"the Jiangsu Province Postgraduate Research and Practice Innovation Program","award":["No.KYCX22_1210"],"award-info":[{"award-number":["No.KYCX22_1210"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remotely sensed precipitation estimates (RSPEs) play an essential role in monitoring drought, especially in ungauged or sparsely gauged areas. In this study, we evaluated the ability of three popular long-term RSPEs (PERSIANN, CHIRPS, and MSWEP) in capturing the meteorological drought variations over the 10 first-level water resource basins of China, based on the standardized precipitation index (SPI). Drought events were identified by run theory, and the drought characteristics (i.e., duration, severity, and intensity) were also evaluated and compared with a gridded in situ observational precipitation dataset (CMA). The results showed that the three RSPEs could generally capture the spatial patterns and trends of the CMA and showed better performance in the wetter basins. MSWEP had the best performance for the categorical skill of POD, followed by CHIRPS and PERSIANN for the four timescales. SPI6 was the optimal timescale for identifying meteorological drought events. There were large skill divergences in the 10 first-level basins for capturing the drought characteristics. CHIRPS can efficiently reproduce the spatial distribution of drought characteristics, with similar metrics of MDS, MDI, and MDP, followed by MSWEP and PERSIANN. Overall, no single product always outperformed the other products in capturing drought characteristics, underscoring the necessity of multiproduct ensemble applications. Our study\u2019s findings may provide useful information for drought monitoring in areas with complex terrain and sparse rain-gauge networks.<\/jats:p>","DOI":"10.3390\/rs15010086","type":"journal-article","created":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T07:31:56Z","timestamp":1672126316000},"page":"86","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Evaluation of Three Long-Term Remotely Sensed Precipitation Estimates for Meteorological Drought Monitoring over China"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0154-386X","authenticated-orcid":false,"given":"Yanzhong","family":"Li","sequence":"first","affiliation":[{"name":"School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources, Nanjing 210044, China"}]},{"given":"Jiacheng","family":"Zhuang","sequence":"additional","affiliation":[{"name":"School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9711-7069","authenticated-orcid":false,"given":"Peng","family":"Bai","sequence":"additional","affiliation":[{"name":"Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Wenjun","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0245-8413","authenticated-orcid":false,"given":"Lin","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Geography Science, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"given":"Manjie","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources, Nanjing 210044, China"}]},{"given":"Yincong","family":"Xing","sequence":"additional","affiliation":[{"name":"School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources, Nanjing 210044, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1038\/nature11575","article-title":"Little change in global drought over the past 60 years","volume":"491","author":"Sheffield","year":"2012","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2754","DOI":"10.1038\/s41467-021-22314-w","article-title":"Evidence of anthropogenic impacts on global drought frequency, duration, and intensity","volume":"2021","author":"Chiang","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1038\/nclimate3280","article-title":"Amplification of wildfire area burnt by hydrological drought in the humid tropics","volume":"7","author":"Taufik","year":"2017","journal-title":"Nat. Clim. Change"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4249","DOI":"10.1038\/s41467-018-06525-2","article-title":"Diverging importance of drought stress for maize and winter wheat in Europe","volume":"9","author":"Webber","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1490","DOI":"10.1038\/s41559-021-01551-8","article-title":"Exacerbated drought impacts on global ecosystems due to structural overshoot","volume":"5","author":"Zhang","year":"2021","journal-title":"Nat. Ecol. Evol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"128097","DOI":"10.1016\/j.jhydrol.2022.128097","article-title":"Modified drought severity index: Model improvement and its application in drought monitoring in China","volume":"612","author":"Sun","year":"2022","journal-title":"J. Hydrol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1080\/02626667.2021.1934473","article-title":"Critical drought intensity-duration-frequency curves based on total probability theorem-coupled frequency analysis","volume":"66","author":"Aksoy","year":"2021","journal-title":"Hydrol. Sci. J."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1175\/1520-0477-78.5.847","article-title":"Meteorological drought-Policy Statement","volume":"78","author":"Society","year":"1997","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1139\/a11-013","article-title":"A review of drought indices","volume":"19","author":"Zargar","year":"2011","journal-title":"Environ. Rev."},{"key":"ref_10","unstructured":"Palmer, W.C. (1965). Meteorological Drought."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1175\/1520-0477-83.8.1167","article-title":"The Quantification of Drought: An Evaluation of Drought Indices","volume":"83","author":"Keyantash","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_12","unstructured":"McKee, T.B., Doesken, N.J., and Kleist, J. (1993, January 17\u201322). The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology, Anaheim, CA, USA."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"10600","DOI":"10.1073\/pnas.1802129115","article-title":"Drought losses in China might double between the 1.5 \u00b0C and 2.0 \u00b0C warming","volume":"115","author":"Su","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1007\/s10584-021-03021-3","article-title":"A tree-ring-based drought reconstruction from 1466 to 2013 CE for the Aksu area, western China","volume":"165","author":"Wang","year":"2021","journal-title":"Clim. Change"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1111\/j.1752-1688.1998.tb05964.x","article-title":"Comparing the palmer drought index and the standardized precipitation index 1","volume":"34","author":"Guttman","year":"1998","journal-title":"J. Am. Water Resour. Assoc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4027","DOI":"10.1002\/joc.4267","article-title":"Candidate Distributions for Climatological Drought Indices (SPI and SPEI)","volume":"35","author":"Stagge","year":"2015","journal-title":"Int. J. Climatol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1002\/joc.4740","article-title":"A revised drought index based on precipitation and pan evaporation","volume":"37","author":"Li","year":"2017","journal-title":"Int. J. Climatol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"726","DOI":"10.1016\/j.jhydrol.2018.06.053","article-title":"Impacts of reservoir operations on multi-scale correlations between hydrological drought and meteorological drought","volume":"563","author":"Wu","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_19","unstructured":"Svoboda, M., Hayes, M., and Wood, D.A. (2022, October 01). Standardized precipitation Index User Guide. Available online: https:\/\/www.droughtmanagement.info\/literature\/WMO_standardized_precipitation_index_user_guide_en_2012.pdf."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2471","DOI":"10.1007\/s00477-017-1437-5","article-title":"Multi-models for SPI drought forecasting in the north of Haihe River Basin, China","volume":"31","author":"Zhang","year":"2017","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1061\/(ASCE)HE.1943-5584.0000619","article-title":"Climatological Drought Analyses and Projection Using SPI and PDSI: Case Study of the Arkansas Red River Basin","volume":"18","author":"Liu","year":"2013","journal-title":"J. Hydrol. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"105687","DOI":"10.1016\/j.atmosres.2021.105687","article-title":"Assessment of drought in SPI series using continuous wavelet analysis for Gediz Basin, Turkey","volume":"260","author":"Yerdelen","year":"2021","journal-title":"Atmos. Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"956","DOI":"10.2166\/wcc.2019.036","article-title":"Drought and climate change assessment using Standardized Precipitation Index (SPI) for Sarawak River Basin","volume":"11","author":"Bong","year":"2019","journal-title":"J. Water Clim. Change"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1016\/j.jhydrol.2013.10.052","article-title":"Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models","volume":"508","author":"Belayneh","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"127923","DOI":"10.1016\/j.jhydrol.2022.127923","article-title":"Drought evolution in the NW Iberian Peninsula over a 60 year period (1960\u20132020)","volume":"610","author":"Lorenzo","year":"2022","journal-title":"J. Hydrol."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Santos, J.F., Pulido-Calvo, I., and Portela, M.M. (2010). Spatial and temporal variability of droughts in Portugal. Water Resour. Res., 46.","DOI":"10.1029\/2009WR008071"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Guo, H., Li, M., Nzabarinda, V., Bao, A., Meng, X., Zhu, L., and De Maeyer, P. (2022). Assessment of Three Long-Term Satellite-Based Precipitation Estimates against Ground Observations for Drought Characterization in Northwestern China. Remote Sens., 14.","DOI":"10.3390\/rs14040828"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.jhydrol.2010.07.012","article-title":"A review of drought concepts","volume":"391","author":"Mishra","year":"2010","journal-title":"J. Hydrol."},{"key":"ref_29","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_30","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_31","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1175\/BAMS-D-17-0138.1","article-title":"MSWEP V2 global 3-hourly 0.1\u00b0 precipitation: Methodology and quantitative assessment","volume":"100","author":"Beck","year":"2019","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Bai, P., and Liu, X. (2018). Evaluation of Five Satellite-Based Precipitation Products in Two Gauge-Scarce Basins on the Tibetan Plateau. Remote Sens., 10.","DOI":"10.3390\/rs10081316"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"169","DOI":"10.5194\/hess-21-169-2017","article-title":"Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau","volume":"21","author":"Liu","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1002\/2017RG000574","article-title":"A review of global precipitation data sets: Data sources, estimation, and intercomparisons","volume":"56","author":"Sun","year":"2018","journal-title":"Rev. Geophys."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Mei, Y., Nikolopoulos, E.I., Anagnostou, E.N., Zoccatelli, D., and Borga, M. (2016). Error Analysis of Satellite Precipitation-Driven Modeling of Flood Events in Complex Alpine Terrain. Remote Sens., 8.","DOI":"10.3390\/rs8040293"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"5801","DOI":"10.5194\/hess-22-5801-2018","article-title":"The PERSIANN family of global satellite precipitation data: A review and evaluation of products","volume":"22","author":"Nguyen","year":"2018","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1007\/s11069-018-3196-0","article-title":"Evaluation of CHIRPS and its application for drought monitoring over the Haihe River Basin, China","volume":"92","author":"Gao","year":"2018","journal-title":"Nat. Hazards"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"124189","DOI":"10.1016\/j.jhydrol.2019.124189","article-title":"Evaluation of remotely sensed precipitation estimates using PERSIANN-CDR and MSWEP for spatio-temporal drought assessment over Iran","volume":"579","author":"Alijanian","year":"2019","journal-title":"J. Hydrol."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Guo, H., Bao, A., Liu, T., Ndayisaba, F., He, D., Kurban, A., and De Maeyer, P. (2017). Meteorological Drought Analysis in the Lower Mekong Basin Using Satellite-Based Long-Term CHIRPS Product. Sustainability, 9.","DOI":"10.3390\/su9060901"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1080\/10095020.2022.2054731","article-title":"Evaluating the accuracy of two satellite-based Quantitative Precipitation Estimation products and their application for meteorological drought monitoring over the Lake Victoria Basin, East Africa","volume":"25","author":"Das","year":"2022","journal-title":"Geo-Spatial Inf. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"105380","DOI":"10.1016\/j.atmosres.2020.105380","article-title":"Monitoring meteorological drought in a semiarid region using two long-term satellite-estimated rainfall datasets: A case study of the Piranhas River basin, northeastern Brazil","volume":"250","author":"Brito","year":"2021","journal-title":"Atmos. Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"268","DOI":"10.15446\/dyna.v86n211.80530","article-title":"Evaluation of reanalysis data in the study of meteorological and hydrological droughts in the Magdalena-Cauca river basin, Colombia","volume":"86","year":"2019","journal-title":"DYNA"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1006\/jare.1996.0099","article-title":"Climate change, drought and desertification","volume":"34","year":"1996","journal-title":"J. Arid. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1002\/joc.4341","article-title":"Validation and comparison of a new gauge-based precipitation analysis over mainland China","volume":"36","author":"Shen","year":"2016","journal-title":"Int. J. Climatol."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Guo, H., Chen, S., Bao, A., Hu, J., Yang, B., and Stepanian, P.M. (2016). Comprehensive Evaluation of High-Resolution Satellite-Based Precipitation Products over China. Atmosphere, 7.","DOI":"10.3390\/atmos7010006"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1016\/j.jhydrol.2017.11.050","article-title":"Comprehensive evaluation of Ensemble Multi-Satellite Precipitation Dataset using the Dynamic Bayesian Model Averaging scheme over the Tibetan plateau","volume":"556","author":"Ma","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"127228","DOI":"10.1016\/j.jhydrol.2021.127228","article-title":"A framework for assessing compound drought events from a drought propagation perspective","volume":"604","author":"Wu","year":"2022","journal-title":"J. Hydrol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"535","DOI":"10.5194\/hess-10-535-2006","article-title":"A global evaluation of streamflow drought characteristics","volume":"10","author":"Fleig","year":"2006","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.crte.2010.01.004","article-title":"Precipitation retrieval from space: An overview","volume":"342","author":"Prigent","year":"2010","journal-title":"Comptes Rendus Geosci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.jhydrol.2013.07.023","article-title":"Multi-scale evaluation of high-resolution multi-sensor blended global precipitation products over the Yangtze River","volume":"500","author":"Li","year":"2013","journal-title":"J. Hydrol."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Zhang, Y., and Li, Z. (2020). Uncertainty Analysis of Standardized Precipitation Index Due to the Effects of Probability Distributions and Parameter Errors. Front. Earth Sci., 8.","DOI":"10.3389\/feart.2020.00076"},{"key":"ref_52","first-page":"2581","article-title":"Multi-model Subseasonal Precipitation Forecasts over the Contiguous United States: Skill Assessment and Statistical Postprocessing","volume":"22","author":"Li","year":"2021","journal-title":"J. Hydrometeorol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"127718","DOI":"10.1016\/j.jhydrol.2022.127718","article-title":"Spatiotemporal estimation of 6-hour high-resolution precipitation across China based on Himawari-8 using a stacking ensemble machine learning model","volume":"609","author":"Zhou","year":"2022","journal-title":"J. Hydrol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1038\/529142a","article-title":"Trouble in Tibet: Rapid changes in Tibetan grasslands are threatening Asia\u2019s main water supply and the livelihood of nomads","volume":"529","author":"Qiu","year":"2016","journal-title":"Nature"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/1\/86\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:49:46Z","timestamp":1760147386000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/1\/86"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,23]]},"references-count":54,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["rs15010086"],"URL":"https:\/\/doi.org\/10.3390\/rs15010086","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,23]]}}}