{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T00:09:15Z","timestamp":1775261355047,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,30]],"date-time":"2021-04-30T00:00:00Z","timestamp":1619740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2018YFC1507101"],"award-info":[{"award-number":["2018YFC1507101"]}]},{"name":"the National Key Research and Development Program of China","award":["2017YFA0603701"],"award-info":[{"award-number":["2017YFA0603701"]}]},{"name":"the National Natural Science Foundation of China","award":["42075189"],"award-info":[{"award-number":["42075189"]}]},{"name":"the National Natural Science Foundation of China","award":["41605042"],"award-info":[{"award-number":["41605042"]}]},{"name":"the National Natural Science Foundation of China","award":["41875094"],"award-info":[{"award-number":["41875094"]}]},{"name":"the Qinglan Project of Jiangsu Province of China","award":["\/"],"award-info":[{"award-number":["\/"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Assessing satellite-based precipitation product capacity for detecting precipitation and linear trends is fundamental for accurately knowing precipitation characteristics and changes, especially for regions with scarce and even no observations. In this study, we used daily gauge observations across the Huai River Basin (HRB) during 1983\u20132012 and four validation metrics to evaluate the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) capacity for detecting extreme precipitation and linear trends. The PERSIANN-CDR well captured climatologic characteristics of the precipitation amount- (PRCPTOT, R85p, R95p, and R99p), duration- (CDD and CWD), and frequency-based indices (R10mm, R20mm, and Rnnmm), followed by moderate performance for the intensity-based indices (Rx1day, R5xday, and SDII). Based on different validation metrics, the PERSIANN-CDR capacity to detect extreme precipitation varied spatially, and meanwhile the validation metric-based performance differed among these indices. Furthermore, evaluation of the PERSIANN-CDR linear trends indicated that this product had a much limited and even no capacity to represent extreme precipitation changes across the HRB. Briefly, this study provides a significant reference for PERSIANN-CDR developers to use to improve product accuracy from the perspective of extreme precipitation, and for potential users in the HRB.<\/jats:p>","DOI":"10.3390\/rs13091747","type":"journal-article","created":{"date-parts":[[2021,4,30]],"date-time":"2021-04-30T10:53:29Z","timestamp":1619780009000},"page":"1747","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Capacity of the PERSIANN-CDR Product in Detecting Extreme Precipitation over Huai River Basin, China"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7237-2722","authenticated-orcid":false,"given":"Shanlei","family":"Sun","sequence":"first","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters\/Key Laboratory of Meteorological Disaster, Ministry of Education\/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiazhi","family":"Wang","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters\/Key Laboratory of Meteorological Disaster, Ministry of Education\/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanrong","family":"Shi","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters\/Key Laboratory of Meteorological Disaster, Ministry of Education\/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongfan","family":"Chai","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters\/Key Laboratory of Meteorological Disaster, Ministry of Education\/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8613-0003","authenticated-orcid":false,"given":"Guojie","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,30]]},"reference":[{"key":"ref_1","unstructured":"Field, C.B., Barros, V.R., Dokken, D.J., Mach, K.J., Mastrandrea, M.D., Bilir, T.E., Chatterjee, M., Ebi, K.L., Estrada, Y.O., and Genova, R.C. (2014). Summary for policymakers. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group ii to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1038\/415514a","article-title":"Increasing risk of great floods in a changing climate","volume":"415","author":"Milly","year":"2002","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1835","DOI":"10.1007\/s11069-013-0772-1","article-title":"Lessons learned from protective measures associated with the 2010 Zhouqu debris flow disaster in China","volume":"69","author":"Wang","year":"2013","journal-title":"Nat. Hazards"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1038\/d41586-018-07447-1","article-title":"Why extreme rains are gaining strength as the climate warms","volume":"563","author":"Witze","year":"2018","journal-title":"Nature"},{"key":"ref_5","unstructured":"Amarnath, G., Yoshimoto, S., Goto, O., Fujihara, M., Smakhtin, V., Aggarwal, P.K., and Ravan, S. (2020, August 03). Global Trends in Water-Related Disasters Using Publicly Available Database for Hazard and Risk Assessment. Available online: https:\/\/cgspace.cgiar.org\/bitstream\/handle\/10568\/93032\/H048407.pdf."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1175\/MWR-D-13-00020.1","article-title":"Ensemble-based analysis of the May 2010 extreme rainfall in Tennessee and Kentucky","volume":"142","author":"Lynch","year":"2014","journal-title":"Mon. Weather Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1780","DOI":"10.1002\/qj.2082","article-title":"The role of upper-level dynamics and surface processes for the Pakistan flood of July 2010","volume":"139","author":"Martius","year":"2013","journal-title":"Q. J. Roy. Meteorol. Soc."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"\u00c1vila, \u00c1., Guerrero, F.C., Escobar, Y.C., and Justino, F. (2019). Recent Precipitation Trends and Floods in the Colombian Andes. Water, 11.","DOI":"10.3390\/w11020379"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1007\/s11069-016-2207-2","article-title":"Floods and associated socioeconomic damages in China over the last century","volume":"82","author":"Duan","year":"2016","journal-title":"Nat. Hazards"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"11775","DOI":"10.1029\/2001JD900066","article-title":"Scale issues in verification of precipitation forecasts","volume":"106","author":"Tustison","year":"2001","journal-title":"J. Geophysi. Res. Atmos."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4896","DOI":"10.1002\/joc.5131","article-title":"Evaluation of satellite rainfall climatology using CMORPH, PERSIANN-CDR, PERSIANN, TRMM, MSWEP over Iran","volume":"37","author":"Alijanian","year":"2017","journal-title":"Int. J. Climatol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2289","DOI":"10.1175\/1520-0477(1999)080<2289:TLOTWR>2.0.CO;2","article-title":"The limitations of the WSR-88D radar network for quantitative precipitation measurement over the Coastal Western United States","volume":"80","author":"Westrick","year":"1999","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"19691","DOI":"10.1029\/1999JD900123","article-title":"An evaluation of NEXRAD precipitation estimates in complex terrain","volume":"104","author":"Young","year":"1999","journal-title":"J. Geophysi. Res. Atmos."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"AghaKouchak, A., Behrangi, A., Sorooshian, S., Hsu, K., and Amitai, E. (2011). Evaluation of satellite-retrieved extreme precipitation rates across the central United States. J. Geophysi. Res. Atmos., 116.","DOI":"10.1029\/2010JD014741"},{"key":"ref_15","unstructured":"Huffman, G.J. (2020, January 01). README for Accessing Experimental Realtime TRMM Multi-Satellite Precipitation Analysis (Tmpart) Data Sets. NASA Tech. Doc, Available online: Ftp:\/\/mesoa.gsfc.nasa.gov\/pub\/trmmdocs\/rt\/3B4XRT_README.pdf."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1175\/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2","article-title":"CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution","volume":"5","author":"Joyce","year":"2014","journal-title":"J. Hydrometeorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1175\/JHM-D-15-0094.1","article-title":"Estimating uncertainties in high-resolution satellite precipitation products: Systematic or random error?","volume":"17","author":"Maggioni","year":"2016","journal-title":"J. Hydrometeorol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.1175\/2011BAMS3158.1","article-title":"Advanced concepts on remote sensing of precipitation at multiple scales","volume":"92","author":"Sorooshian","year":"2011","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1175\/JHM560.1","article-title":"The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-global, multi-year, combined-sensor precipitation at fine scales","volume":"8","author":"Huffman","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_20","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_21","doi-asserted-by":"crossref","unstructured":"Shen, Y., Xiong, A., Wang, Y., and Xie, P. (2010). Performance of high-resolution satellite precipitation products over China. J. Geophysi. Res. Atmos., 115.","DOI":"10.1029\/2009JD012097"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1504","DOI":"10.3390\/rs70201504","article-title":"Evaluation of six high-resolution satellite and ground-based precipitation products over Malaysia","volume":"7","author":"Tan","year":"2015","journal-title":"Remote Sens."},{"key":"ref_23","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_24","first-page":"1200","article-title":"The trend analysis and statistical distribution of extreme rainfall events in the Huaihe River Basin in the past 50 years","volume":"66","author":"She","year":"2011","journal-title":"Acta Geo. Sin."},{"key":"ref_25","first-page":"577","article-title":"Contrast analysis of meteorological and hydrological features of extremely heavy rainfall causing severe floods in Huai River Valley","volume":"27","author":"Bi","year":"2004","journal-title":"J. Nanjing Inst. Meteorol."},{"key":"ref_26","first-page":"1360","article-title":"Oscillation characteristics of summer precipitation in the Huaihe River valley and relevant climate background","volume":"39","author":"Wei","year":"2009","journal-title":"Sci. China Earth Sci."},{"key":"ref_27","first-page":"2","article-title":"The 2003 floods in Huai River Basin","volume":"5","author":"Zhang","year":"2003","journal-title":"Meteorol. Knowl."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1007\/s12040-016-0664-3","article-title":"Projection of extreme precipitation in the context of climate change in Huang-Huai-Hai region, China","volume":"125","author":"Yin","year":"2016","journal-title":"J. Earth Syst. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1387","DOI":"10.1175\/JHM-D-14-0174.1","article-title":"Evaluation of the PERSIANN-CDR daily rainfall estimates in capturing the behavior of extreme precipitation events over China","volume":"16","author":"Miao","year":"2015","journal-title":"J. Hydrometeorol."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Liu, J., Xu, Z., Bai, J., Peng, D., and Ren, M. (2018). Assessment and correction of the PERSIANN-CDR product in the Yarlung Zangbo River Basin, China. Remote Sens., 10.","DOI":"10.3390\/rs10122031"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Liu, J., Xia, J., She, D., Li, L., Wang, Q., and Zou, L. (2019). Evaluation of six satellite-based precipitation products and their ability for capturing characteristics of extreme precipitation events over a climate transition area in China. Remote Sens., 11.","DOI":"10.3390\/rs11121477"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.atmosres.2018.05.016","article-title":"Comparison of two long-term and high-resolution satellite precipitation datasets in Xinjiang, China","volume":"212","author":"Gao","year":"2018","journal-title":"Atmos. Res."},{"key":"ref_33","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":"2012","journal-title":"J. Hydrol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Sun, S., Shi, W., Zhou, S., Chai, R., Chen, H., Wang, G., Zhou, Y., and Shen, H. (2020). Capacity of satellite-based and reanalysis precipitation products in detecting long-term trends across Mainland China. Remote Sens., 12.","DOI":"10.3390\/rs12182902"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3311","DOI":"10.1007\/s00382-018-4080-z","article-title":"Evaluation of precipitation trends from high-resolution satellite precipitation products over Mainland China","volume":"51","author":"Chen","year":"2018","journal-title":"Clim. Dyn."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1175\/BAMS-D-13-00068.1","article-title":"PERSIANNCDR: Daily precipitation climate data record from multi-satellite observations for hydrological and climate studies","volume":"96","author":"Ashouri","year":"2015","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.jhydrol.2011.02.031","article-title":"Guidelines on validation procedures for meteorological data from automatic weather stations","volume":"402","year":"2011","journal-title":"J. Hydrol."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Gentilucci, M., Barbieri, M., Burt, P., and D\u2019Aprile, F. (2018). Preliminary data validation and reconstruction of temperature and precipitation in Central Italy. Geosciences, 8.","DOI":"10.20944\/preprints201806.0055.v1"},{"key":"ref_39","unstructured":"Zahumensk\u00fd, I. (2004). Guidelines on Quality Control Procedures for Data from Automatic Weather Stations, World Meteorological Organization."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1002\/joc.906","article-title":"Homogeneity of 20th century European daily temperature and precipitation series","volume":"23","author":"Wijngaard","year":"2003","journal-title":"Int. J. Climatol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.jaridenv.2013.05.013","article-title":"Evaluation of satellite-based precipitation estimation over Iran","volume":"97","author":"Nasrollahi","year":"2013","journal-title":"J. Arid. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Alexander, L.V., Zhang, X., Peterson, T.C., Caesar, J., Klein, T.A.M.G., Haylock, M., Collins, D., Trewin, B., Rahimzadeh, F., and Tgipour, A. (2006). Global observed changes in daily climate extremes of temperature and precipitation. J. Geophys. Res. Atmos., 111.","DOI":"10.1029\/2005JD006290"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1769","DOI":"10.1007\/s00382-015-2674-2","article-title":"Attribution of extreme temperature changes during 1951\u20132010","volume":"46","author":"Kim","year":"2016","journal-title":"Clim. Dyn."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1175\/BAMS-D-12-00109.1","article-title":"Global land-based datasets for monitoring climatic extremes","volume":"94","author":"Donat","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"6341","DOI":"10.1175\/JCLI-D-17-0853.1","article-title":"Detection of anthropogenic influence on fixed threshold indices of extreme temperature","volume":"31","author":"Yin","year":"2018","journal-title":"J. Clim."},{"key":"ref_46","first-page":"105299","article-title":"Recent intensification of extreme precipitation events in the La Plata Basin in Southern South America (1981\u20132018)","volume":"249","author":"Kayano","year":"2020","journal-title":"Atmos. Res."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Villarini, G., Mandapaka, P.V., Krajewski, W.F., and Moore, R.J. (2008). Rainfall and sampling uncertainties: A rain gauge perspective. J. Geophysi. Res. Atmos., 113.","DOI":"10.1029\/2007JD009214"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1016\/j.atmosres.2016.04.016","article-title":"Assessment of measurement errors and dynamic calibration methods for three different tipping bucket rain gauges","volume":"178","author":"Shedekar","year":"2016","journal-title":"Atmos. Res."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3863","DOI":"10.1029\/2017WR022421","article-title":"Quantifying and mitigating wind-Induced undercatch in rainfall measurements","volume":"54","author":"Pollock","year":"2018","journal-title":"Water Resour. Res."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Adam, J.C., and Lettenmaier, D.P. (2003). Adjustment of global gridded precipitation for systematic bias. J. Geophysi. Res. Atmos., 108.","DOI":"10.1029\/2002JD002499"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/j.advwatres.2018.10.027","article-title":"Influence of temporal data aggregation on trend estimation for intense rainfall","volume":"122","author":"Morbidelli","year":"2018","journal-title":"Adv. Water. Res."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1175\/1525-7541(2001)002<0122:ABCSRP>2.0.CO;2","article-title":"A bias-corrected Siberian regional precipitation climatology","volume":"2","author":"Yang","year":"2001","journal-title":"J. Hydrometeorol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1747\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:56:04Z","timestamp":1760162164000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1747"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,30]]},"references-count":52,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13091747"],"URL":"https:\/\/doi.org\/10.3390\/rs13091747","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,30]]}}}