| 利用卫星红外高光谱资料反演大气甲烷浓度垂直廓线 |
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| 引用本文： | 张莹,陈良富,陶金花,苏林,余超,范萌.利用卫星红外高光谱资料反演大气甲烷浓度垂直廓线[J].遥感学报,2012,16(2):232-247. |
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| 作者姓名： | 张莹 陈良富 陶金花 苏林 余超 范萌 |
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| 作者单位： | 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; 中国科学院研究生院, 北京 100049;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;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;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;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; 中国科学院研究生院, 北京 100049;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; 中国科学院研究生院, 北京 100049 |
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| 基金项目： | 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) |
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| 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EOSAQUA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。
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| 关 键 词： | 经验正交函数 甲烷 AIRS 大气红外遥感 物理统计 |
| 收稿时间： | 2011/2/27 0:00:00 |
| 修稿时间： | 2011/5/23 0:00:00 |
Retrieval of methane profiles from spaceborne hyperspectralinfrared observations |
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| ZHANG Ying,CHEN Liangfu,TAO Jinhu,SU Lin,YU Chao and FAN Meng.Retrieval of methane profiles from spaceborne hyperspectralinfrared observations[J].Journal of Remote Sensing,2012,16(2):232-247. |
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| Authors: | ZHANG Ying CHEN Liangfu TAO Jinhu SU Lin YU Chao and FAN Meng |
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| Institution: | State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of ChineseAcademy of Sciences and Beijing Normal University, Beijing 100101, China; Graduate University of Chinese Academy of Sciences, Beijing 100049, China;State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of ChineseAcademy of Sciences and Beijing Normal University, Beijing 100101, China;State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of ChineseAcademy of Sciences and Beijing Normal University, Beijing 100101, China;State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of ChineseAcademy of Sciences and Beijing Normal University, Beijing 100101, China;State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of ChineseAcademy of Sciences and Beijing Normal University, Beijing 100101, China; Graduate University of Chinese Academy of Sciences, Beijing 100049, China;State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of ChineseAcademy of Sciences and Beijing Normal University, Beijing 100101, China; Graduate University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | This paper presents an improved Empirical Orthogonal Functions (EOF) model for estimating methane profilesfrom spaceborne hyperspectral infrared observations based on profile dataset from European Centre for Medium-RangeWeather Forecasts (ECMWF) and radiative transfer model RTTOV9.3. The model was applied to Atmospheric InfraredSounder (AIRS) observations, validated by ground-based Fourier Transform Spectrometer (FTS) observations and AIRS v5.0 CH4 products. Compared with FTS measurements, the Root Mean Square (RMS) relative error of CH4 mixing ratio of EOFretrieval was smaller than that of AIRS v5.0 CH4 product for data lower than 300 hPa, and the relative error of CH4 columnamount of EOF retrieval was also smaller. Compared with AIRS v5.0 CH4 product, the coefficient of determination for CH4profiles retrieved from EOF model was 0.9715, and the RMS relative errors were smaller than 2.5%. The validation resultsshow that the EOF model could provide a good initial value for physical retrieval and is a promising operational approach dueto high stability and efficiency. |
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| Keywords: | EOF methane AIRS atmospheric infrared remote sensing physical regression |
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