检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:张莹[1,2] 陈良富[1] 陶金花[1] 苏林[1] 余超[1,2] 范萌[1,2]
机构地区:[1]遥感科学国家重点实验室,中国科学院遥感应用研究所,北京100101 [2]中国科学院研究生院,北京100049
出 处:《遥感学报》2012年第2期232-247,共16页NATIONAL REMOTE SENSING BULLETIN
基 金:国家高技术研究发展计划(863计划)(编号:2006AA06A303);中国科学院知识创新工程重大项目(编号:kzcx1-yw-06-01)~~
摘 要:基于欧洲中尺度天气预报中心(ECMWF)大气廓线库和RTTOV9.3辐射传输正向模式,探讨了大气CH4混合比浓度垂直廓线和柱总量的经验正交函数(EOF)反演方法,并利用地基傅里叶热红外光谱仪(FTS)观测数据和红外EOS-AQUA卫星的大气红外传感器(AIRS)实际观测资料进行反演实验和验证。并且与地基傅里叶热红外光谱仪(FTS)观测结果相比,300hPa以下EOF模型反演的CH4混合比均方根相对误差小于AIRS的CH4产品,CH4柱总量的相对误差也小于AIRS产品。与AIRS的CH4产品相比,EOF模型反演的CH4混合比廓线相关系数为0.97,均方根相对误差小于2.5%。验证结果表明EOF模型可以为物理反演提供很好的初始值,由于其稳定且运算更快捷,在业务化运行方面具有很大应用前景。This paper presents an improved Empirical Orthogonal Functions (EOF) model for estimating methane profiles from spaceborne hyperspectral infrared observations based on profile dataset from European Centre for Medium-Range Weather Forecasts (ECMWF) and radiative transfer model RTTOV9.3. The model was applied to Atmospheric Infrared Sounder (AIRS) observations, validated by ground-based Fourier Transform Spectrometer (FTS) observations and AIRS vS.0 CH4 products. Compared with FTS measurements, the Root Mean Square (RMS) relative error of CH4 mixing ratio of EOF retrieval was smaller than that of AIRS v5.0 CH4 product for data lower than 300 hPa, and the relative error of CH4 column amount of EOF retrieval was also smaller. Compared with AIRS v5.0 CH4 product, the coefficient of determination for CH4 profiles retrieved from EOF model was 0.9715, and the RMS relative errors were smaller than 2.5%. The validation results show that the EOF model could provide a good initial value for physical retrieval and is a promising operational approach due to high stability and efficiency.
关 键 词:经验正交函数 甲烷 AIRS 大气红外遥感 物理统计
分 类 号:P402[天文地球—大气物理学与大气环境] P407[天文地球—大气科学及气象学]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.40