{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1363670321012803840.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.1155/2016/4126393"}},{"identifier":{"@type":"URI","@value":"http://downloads.hindawi.com/journals/amete/2016/4126393.pdf"}},{"identifier":{"@type":"URI","@value":"http://downloads.hindawi.com/journals/amete/2016/4126393.xml"}}],"dc:title":[{"@value":"An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data"}],"description":[{"type":"abstract","notation":[{"@value":"<jats:p>Precipitable water vapor (PWV) is one of the most variable components of the atmosphere in both space and time. In this study, a passive microwave-based retrieval algorithm for PWV over land without land surface temperature (LST) data was developed. To build the algorithm, two assumptions exist: (1) land surface emissivities (LSE) at two adjacent frequencies are equal and (2) there are simple parameterizations that relate transmittance, atmospheric effective radiating temperature, and PWV. Error analyses were performed using radiosonde sounding observations from Zhangye, China, and CE318 measurements of Dalanzadgad (43°34′37′′N, 104°25′8′′E) and Singapore (1°17′52′′N, 103°46′48′′E) sites from Aerosol Robotic Network (AERONET), respectively. In Zhangye, the algorithm had a Root Mean Square Error (RMSE) of 4.39 mm and a bias of 0.36 mm on cloud-free days, while on cloudy days there was an RMSE of 4.84 mm and a bias of 0.52 mm because of the effect of liquid water in clouds. The validations in Dalanzadgad and Singapore sites showed that the retrieval algorithm had an RMSE of 4.73 mm and a bias of 0.84 mm and the bigger errors appeared when the water vapor was very dry or very moist.</jats:p>"}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1383670321012803844","@type":"Researcher","foaf:name":[{"@value":"Fang-Cheng Zhou"}],"jpcoar:affiliationName":[{"@value":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"@value":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"@id":"https://cir.nii.ac.jp/crid/1383670321012803843","@type":"Researcher","foaf:name":[{"@value":"Xiaoning Song"}],"jpcoar:affiliationName":[{"@value":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"@id":"https://cir.nii.ac.jp/crid/1383670321012803842","@type":"Researcher","foaf:name":[{"@value":"Pei Leng"}],"jpcoar:affiliationName":[{"@value":"Key Laboratory of Agri-Informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}]},{"@id":"https://cir.nii.ac.jp/crid/1383670321012803840","@type":"Researcher","foaf:name":[{"@value":"Hua Wu"}],"jpcoar:affiliationName":[{"@value":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"@value":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}]},{"@id":"https://cir.nii.ac.jp/crid/1383670321012803841","@type":"Researcher","foaf:name":[{"@value":"Bo-Hui Tang"}],"jpcoar:affiliationName":[{"@value":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"@value":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}]}],"publication":{"publicationIdentifier":[{"@type":"PISSN","@value":"16879309"},{"@type":"EISSN","@value":"16879317"}],"prism:publicationName":[{"@value":"Advances in Meteorology"}],"dc:publisher":[{"@value":"Wiley"}],"prism:publicationDate":"2016","prism:volume":"2016","prism:startingPage":"1","prism:endingPage":"11"},"reviewed":"false","dc:rights":["http://creativecommons.org/licenses/by/4.0/"],"url":[{"@id":"http://downloads.hindawi.com/journals/amete/2016/4126393.pdf"},{"@id":"http://downloads.hindawi.com/journals/amete/2016/4126393.xml"}],"createdAt":"2016-02-03","modifiedAt":"2017-06-24","relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1390015443654955648","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"en","@value":"A Study on Analysis Setting Optimization of Ship-Based GNSS Measurements for Maritime Precipitable Water Vapor Monitoring"},{"@language":"ja","@value":"海上可降水量観測のための船舶搭載GNSS解析設定の最適化に関する研究"}]},{"@id":"https://cir.nii.ac.jp/crid/2050025942122902272","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Comparison of shipborne GNSS-derived precipitable water vapor with radiosonde in the western North Pacific and in the seas adjacent to Japan"}]}],"dataSourceIdentifier":[{"@type":"CROSSREF","@value":"10.1155/2016/4126393"},{"@type":"CROSSREF","@value":"10.1186/s40623-017-0740-1_references_DOI_JURqOlClXCHZWy5nA8TmWZOQmrb"},{"@type":"CROSSREF","@value":"10.2151/jmsj.2023-020_references_DOI_JURqOlClXCHZWy5nA8TmWZOQmrb"}]}