{"title":"最优概率法在温度、水汽和臭氧剖面反演中的应用","authors":"S. Clough, R. Isaacs, R. Worsham, J. Moncet","doi":"10.1364/orsa.1990.tub2","DOIUrl":null,"url":null,"abstract":"A code has been developed to perform the retrieval of atmospheric state parameters using the method of nonlinear least squares in conjunction with a program to compute the forward problem (Isaacs, 1988). In the present study, FASCODE (Clough et al., 1986) has been utilized for the forward problem other algorithms including rapid algorithms may readily be accommodated. The method has been applied to retrievals of temperature profiles, surface temperature and pressure, water vapor profiles and other constituent distributions using both real and simulated data. The method is applicable to both sequential and simultaneous retrievals. Either of two approaches may be selected for performing retrievals: the method of ridge regression or the maximum likelihood method. Our implementation of the latter approach is similar to that discussed by Rodgers (1976, 1987) and more recently by Eyre (1989).","PeriodicalId":320202,"journal":{"name":"Optical Remote Sensing of the Atmosphere","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Application of the Optimal Probability Method to the Retrieval of Temperature, Water Vapor and Ozone Profiles\",\"authors\":\"S. Clough, R. Isaacs, R. Worsham, J. Moncet\",\"doi\":\"10.1364/orsa.1990.tub2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A code has been developed to perform the retrieval of atmospheric state parameters using the method of nonlinear least squares in conjunction with a program to compute the forward problem (Isaacs, 1988). In the present study, FASCODE (Clough et al., 1986) has been utilized for the forward problem other algorithms including rapid algorithms may readily be accommodated. The method has been applied to retrievals of temperature profiles, surface temperature and pressure, water vapor profiles and other constituent distributions using both real and simulated data. The method is applicable to both sequential and simultaneous retrievals. Either of two approaches may be selected for performing retrievals: the method of ridge regression or the maximum likelihood method. Our implementation of the latter approach is similar to that discussed by Rodgers (1976, 1987) and more recently by Eyre (1989).\",\"PeriodicalId\":320202,\"journal\":{\"name\":\"Optical Remote Sensing of the Atmosphere\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Optical Remote Sensing of the Atmosphere\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1364/orsa.1990.tub2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optical Remote Sensing of the Atmosphere","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/orsa.1990.tub2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
利用非线性最小二乘方法,结合计算正演问题的程序,开发了一种执行大气状态参数检索的代码(Isaacs, 1988)。在本研究中,FASCODE (Clough et al., 1986)被用于正演问题,其他算法包括快速算法可以很容易地适应。该方法已应用于实际和模拟数据的温度分布、地表温度和压力、水汽分布和其他成分分布的反演。该方法既适用于顺序检索,也适用于同时检索。可以选择两种方法中的任何一种进行检索:脊回归方法或最大似然方法。我们对后一种方法的实施类似于Rodgers(1977,1987)和Eyre(1989)所讨论的方法。
Application of the Optimal Probability Method to the Retrieval of Temperature, Water Vapor and Ozone Profiles
A code has been developed to perform the retrieval of atmospheric state parameters using the method of nonlinear least squares in conjunction with a program to compute the forward problem (Isaacs, 1988). In the present study, FASCODE (Clough et al., 1986) has been utilized for the forward problem other algorithms including rapid algorithms may readily be accommodated. The method has been applied to retrievals of temperature profiles, surface temperature and pressure, water vapor profiles and other constituent distributions using both real and simulated data. The method is applicable to both sequential and simultaneous retrievals. Either of two approaches may be selected for performing retrievals: the method of ridge regression or the maximum likelihood method. Our implementation of the latter approach is similar to that discussed by Rodgers (1976, 1987) and more recently by Eyre (1989).