Spatio-temporal analysis of the accuracy of tropical multisatellite precipitation analysis 3B42 precipitation data in mid-high latitudes of China
Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration sa...
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| description | Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS). This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998-2012. Comparative analysis at three timescales (daily, monthly and annual scale) indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%). Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these data are important for the rational application of TMPA methods in climatic and hydrological research. |
| doi_str_mv | 10.1371/journal.pone.0120026 |
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However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS). This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998-2012. Comparative analysis at three timescales (daily, monthly and annual scale) indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%). Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these data are important for the rational application of TMPA methods in climatic and hydrological research.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0120026</identifier><identifier>PMID: 25830776</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Accuracy ; Algorithms ; Annual precipitation ; Arid regions ; Arid zones ; Basins ; Calibration ; China ; Climate change ; Comparative analysis ; Data processing ; Estimates ; Humid areas ; Hydrologic cycle ; Hydrologic data ; Hydrologic research ; Hydrology ; Ice cover ; Laboratories ; Latitude ; Methods ; Precipitation ; Precipitation data ; Precipitation estimation ; Rain ; Rainfall ; Satellite data ; Satellites ; Seasons ; Spacecraft ; Spatial analysis ; Spatio-Temporal Analysis ; Studies ; Tropical Climate ; Tropical rainfall ; Tropical Rainfall Measuring Mission (TRMM) ; Weather forecasting ; Weather stations ; Winter</subject><ispartof>PloS one, 2015-04, Vol.10 (4), p.e0120026-e0120026</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Cai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Cai et al 2015 Cai et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-397c98c74fdac07395d820798f56372021c6b6046fe6aabdc32a314b3d35ec983</citedby><cites>FETCH-LOGICAL-c692t-397c98c74fdac07395d820798f56372021c6b6046fe6aabdc32a314b3d35ec983</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382316/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382316/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79569,79570</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25830776$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Cai, Yancong</creatorcontrib><creatorcontrib>Jin, Changjie</creatorcontrib><creatorcontrib>Wang, Anzhi</creatorcontrib><creatorcontrib>Guan, Dexin</creatorcontrib><creatorcontrib>Wu, Jiabing</creatorcontrib><creatorcontrib>Yuan, Fenghui</creatorcontrib><creatorcontrib>Xu, Leilei</creatorcontrib><title>Spatio-temporal analysis of the accuracy of tropical multisatellite precipitation analysis 3B42 precipitation data in mid-high latitudes of China</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. 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Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these data are important for the rational application of TMPA methods in climatic and hydrological research.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Annual precipitation</subject><subject>Arid regions</subject><subject>Arid zones</subject><subject>Basins</subject><subject>Calibration</subject><subject>China</subject><subject>Climate change</subject><subject>Comparative analysis</subject><subject>Data processing</subject><subject>Estimates</subject><subject>Humid areas</subject><subject>Hydrologic cycle</subject><subject>Hydrologic data</subject><subject>Hydrologic research</subject><subject>Hydrology</subject><subject>Ice cover</subject><subject>Laboratories</subject><subject>Latitude</subject><subject>Methods</subject><subject>Precipitation</subject><subject>Precipitation data</subject><subject>Precipitation 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analysis of the accuracy of tropical multisatellite precipitation analysis 3B42 precipitation data in mid-high latitudes of China</title><author>Cai, Yancong ; Jin, Changjie ; Wang, Anzhi ; Guan, Dexin ; Wu, Jiabing ; Yuan, Fenghui ; Xu, Leilei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-397c98c74fdac07395d820798f56372021c6b6046fe6aabdc32a314b3d35ec983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Annual precipitation</topic><topic>Arid regions</topic><topic>Arid zones</topic><topic>Basins</topic><topic>Calibration</topic><topic>China</topic><topic>Climate change</topic><topic>Comparative analysis</topic><topic>Data processing</topic><topic>Estimates</topic><topic>Humid areas</topic><topic>Hydrologic cycle</topic><topic>Hydrologic data</topic><topic>Hydrologic research</topic><topic>Hydrology</topic><topic>Ice 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one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cai, Yancong</au><au>Jin, Changjie</au><au>Wang, Anzhi</au><au>Guan, Dexin</au><au>Wu, Jiabing</au><au>Yuan, Fenghui</au><au>Xu, Leilei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatio-temporal analysis of the accuracy of tropical multisatellite precipitation analysis 3B42 precipitation data in mid-high latitudes of China</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2015-04-01</date><risdate>2015</risdate><volume>10</volume><issue>4</issue><spage>e0120026</spage><epage>e0120026</epage><pages>e0120026-e0120026</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS). This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998-2012. Comparative analysis at three timescales (daily, monthly and annual scale) indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%). Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these data are important for the rational application of TMPA methods in climatic and hydrological research.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>25830776</pmid><doi>10.1371/journal.pone.0120026</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Accuracy Algorithms Annual precipitation Arid regions Arid zones Basins Calibration China Climate change Comparative analysis Data processing Estimates Humid areas Hydrologic cycle Hydrologic data Hydrologic research Hydrology Ice cover Laboratories Latitude Methods Precipitation Precipitation data Precipitation estimation Rain Rainfall Satellite data Satellites Seasons Spacecraft Spatial analysis Spatio-Temporal Analysis Studies Tropical Climate Tropical rainfall Tropical Rainfall Measuring Mission (TRMM) Weather forecasting Weather stations Winter |
| title | Spatio-temporal analysis of the accuracy of tropical multisatellite precipitation analysis 3B42 precipitation data in mid-high latitudes of China |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-19T19%3A53%3A04IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Spatio-temporal%20analysis%20of%20the%20accuracy%20of%20tropical%20multisatellite%20precipitation%20analysis%203B42%20precipitation%20data%20in%20mid-high%20latitudes%20of%20China&rft.jtitle=PloS%20one&rft.au=Cai,%20Yancong&rft.date=2015-04-01&rft.volume=10&rft.issue=4&rft.spage=e0120026&rft.epage=e0120026&rft.pages=e0120026-e0120026&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0120026&rft_dat=%3Cgale_plos_%3EA423835526%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1668244699&rft_id=info:pmid/25830776&rft_galeid=A423835526&rft_doaj_id=oai_doaj_org_article_b400d15a7e7341e4b509fb43290541bd&rfr_iscdi=true |