{"title":"Bayesian fusion of TRMM passive and active measurements","authors":"Ziad S. Haddad, S. Durden, Eastwood Im","doi":"10.1109/IGARSS.1997.608999","DOIUrl":null,"url":null,"abstract":"A Bayesian method was adopted to combine the instantaneous measurements of the Tropical Rainfall Measuring Mission's (TRMM) radar and radiometer. The method makes multiple estimates of the rain-rate profile using the radar reflectivities assuming various plausible values for the drop size distribution (DSD) shape parameters, then selects those parameter values which produce estimates that are most consistent with the passive observations. The resulting estimates are expressed directly in terms of the DSD parameters, thus allowing one to calculate any rain-related quantity, such as rain rate profile, precipitating liquid water profile, etc. The Bayesian approach also allows one to calculate the \"error bar\" associated with each estimate.","PeriodicalId":64877,"journal":{"name":"遥感信息","volume":"9 1","pages":"1642-1644 vol.4"},"PeriodicalIF":0.0000,"publicationDate":"1997-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"遥感信息","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.1109/IGARSS.1997.608999","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A Bayesian method was adopted to combine the instantaneous measurements of the Tropical Rainfall Measuring Mission's (TRMM) radar and radiometer. The method makes multiple estimates of the rain-rate profile using the radar reflectivities assuming various plausible values for the drop size distribution (DSD) shape parameters, then selects those parameter values which produce estimates that are most consistent with the passive observations. The resulting estimates are expressed directly in terms of the DSD parameters, thus allowing one to calculate any rain-related quantity, such as rain rate profile, precipitating liquid water profile, etc. The Bayesian approach also allows one to calculate the "error bar" associated with each estimate.
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Remote Sensing Information is a bimonthly academic journal supervised by the Ministry of Natural Resources of the People's Republic of China and sponsored by China Academy of Surveying and Mapping Science. Since its inception in 1986, it has been one of the authoritative journals in the field of remote sensing in China.In 2014, it was recognised as one of the first batch of national academic journals, and was awarded the honours of Core Journals of China Science Citation Database, Chinese Core Journals, and Core Journals of Science and Technology of China. The journal won the Excellence Award (First Prize) of the National Excellent Surveying, Mapping and Geographic Information Journal Award in 2011 and 2017 respectively.
Remote Sensing Information is dedicated to reporting the cutting-edge theoretical and applied results of remote sensing science and technology, promoting academic exchanges at home and abroad, and promoting the application of remote sensing science and technology and industrial development. The journal adheres to the principles of openness, fairness and professionalism, abides by the anonymous review system of peer experts, and has good social credibility. The main columns include Review, Theoretical Research, Innovative Applications, Special Reports, International News, Famous Experts' Forum, Geographic National Condition Monitoring, etc., covering various fields such as surveying and mapping, forestry, agriculture, geology, meteorology, ocean, environment, national defence and so on.
Remote Sensing Information aims to provide a high-level academic exchange platform for experts and scholars in the field of remote sensing at home and abroad, to enhance academic influence, and to play a role in promoting and supporting the protection of natural resources, green technology innovation, and the construction of ecological civilisation.
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