Research Progress of Retrieving Atmosphere Humidity Profiles from AIRS Data
Received date: 2013-06-06
Revised date: 2013-07-02
Online published: 2013-08-10
With the breakthrough of the satellite remote sensing key technology, satellite spectral resolution has reached to the level of distinguish between each spectral line, the researchers begin to research atmosphere profile and various micro constituent inversion using huge number of channels at the same time. This paper make a comment of the advances in Atmospheric humidity profile inversion using AIRS data, Analyzed and discussed the research status of clear sky atmospheric profiles from four aspects: training data, information extraction and dimensionality reduction of channels, inversion algorithm and accuracy improvement of Inversion. CIMSS and brightness temperature simulated used SARTA are usually chose to retrieve water vapor profile using AIRS data. Summarized two kinds of methods to do information extraction and dimensionality reduction, the first is spectral information compression, compared with PCA found that ICA is more practical. The second is channel selection, that is keeping part of channel contained more atmospheric profile information to achieve dimensionality reduction. It is worth mentioning that we need to choose different channel combination under different regional climate types, underlying surface, season, and real-time weather condition. Introduces three kinds of inversion algorithm: eigenvector regression algorithms(ERA), the Newton method(NM), and aritificial neural network algorithms(ANN). Compare the three methods found that ERA is simple, but the precision is not ideal; NW has high precision but it is not suitable for business application due to its long computing time; ANN has high computing speed and its precision can meet the requirements, thus, ANN has excellent foreground. Analyzed several samples classification method and additional factors, and give some suggestions to improve inversion algorithm. Finally, provide a brief introduction of infrared cloudcleared and inversion atmospheric profile under cloud condition.
Key words: Hyper spectral; Retrieval; Humidity Profiles; AIRS
Liu Yang , Cai Bo , Ban Xianxiu , Yuan Jian , Geng Shujiang , Zhao Shuhui , Li Shuaibin . Research Progress of Retrieving Atmosphere Humidity Profiles from AIRS Data[J]. Advances in Earth Science, 2013 , 28(8) : 890 -896 . DOI: 10.11867/j.issn.1001-8166.2013.08.0890
[1]Huang Hunglung, Li Jun, Baggett K, et al. Evaluation of cloud-cleared radiances for numerical weather prediction and cloud contaminated sounding applications[C]∥Atmospheric and Evironmental Remote Sensing Data Processing and Utilization: Numerical Atmaspheric Prediction and Environment Monitoring. Procecdings of SPIE 5890.SanDiego, California, USA,2005: 38-45.
[2]Guan Li. The Application of Spaceborne Infrared Hyperspectral Data[M].Beijing:China Meteorological Press,2008:6-60.[官莉.星载红外高光谱资料的应用[M].北京:气象出版社,2008:6-60.]
[3]Strow L L, Hannon S E, Motteler H E.An overview of the AIRS radiative transfer model[J]. IEEE Transactions on Geoscience and Remote Sensing,2003,41:303-313.
[4]Hannon S E, Strow L L. SARTA: The Stand Alone AIRS Radiative Transfer Algorithm[EB/OL].[2013-02-03].http:∥asl.umbc.edu/pub/packages/sarta.html.
[5]Liu Yang, Guan Li. Study on the inversion of clear sky atmospheric humidity profiles with artificial neural network[J]. Meteorological Monthly, 2011,37(3):318-324.[刘旸,官莉.人工神经网络法反演晴空大气湿度廓线的研究[J].气象,2011,37(3):318-324.]
[6]Susskind J, Joiner J, Chahine M T. Determination of temperature and moisture profiles in a cloudy atmosphere using AIRS/AMSU[J].NATO ASI Series,1993,19:149-161.
[7]Guan L, Huang L H, Li J. A study on retrieving atmospheric profiles from EOS_AIRS Observations[J].Acta Meteorologia Sinica,2005,19(1):112-119.
[8]Yang Fusheng,Hong Bo. The Principle and Application of Independent Component Analysis[M]. Beijing: Tsinghua University Press,2006.[杨福生,洪波.独立分量分析的原理与应用[M].北京:清华大学出版社,2006.]
[9]Jiang Deming. Approach to High Spectral Resolution Infrared Remote Sensing of Atmospheric Temperature and Humidity Profiles[D]. Nanjing: Nanjing Univercity of Information and Science Technology, 2007:29-42.[蒋德明.高光谱分辨率红外遥感大气温湿度廓线反演方法研究[D].南京:南京信息工程大学,2007:29-42.]
[10] Zhang Jianwei, Wang Gen, Zhang Hua, et al. Experiment on hyper-spectral atmospheric infrared sounder channel selection based on the cumulative effect coefficient of principal component[J]. Transactions of Atmospheric Sciences, 2011,34(1):36-42.[张建伟,王根,张华,等.基于主成分累计影响系数法的高光谱大气红外探测器的通道选择试验[J].大气科学学报,2011,34(1):36-42.
[11]Florence R, Fourrie N, Ourrie D, et al. Channel selection methods for infrared atmospheric sounding interferometer radiances[J].Quarterly Journal of the Royal Meteorological Society,2002,128(581):1 011-1 027.
[12]Fourrie N, Thepaut J N. Validation of the NESDIS Near Real Time AIRS Channel Selection[Z].ECMWF Technical Memoranda European Center for Medium Range, 2002.
[13]Liu Hui, Dong Chaohua, Zhang Wenjian,et al. Retrieval of clear-air atmospheric temperature profiles using AIRS observations[J].Acta Meteorologica Sinica, 2008,66(4):513-519.[刘辉,董超华,张文建,等.AIRS晴空大气温度廓线反演试验[J].气象学报,2008,66(4):513-519.]
[14]Zhang Jianwei, Wang Gen, Zhang Hua, et al. Experiment on hyper-spectral atmospheric infrared sounder channel selection based on the cumulative effect coefficient of principal component[J]. Transactions of Atmospheric Sciences, 2011,34(1):36-42.[张建伟,王根,张华,等.基于主成分累计影响系数法的高光谱大气红外探测器的通道选择试验[J].大气科学学报,2011,34(1):36-42.]
[15]Zhang Shuiping. Hyperspectral atmospheric sounding information channel selection study[J]. Scientia Meteorologica Sinica, 2009,29(4):475-481.[张水平. AIRS资料反演大气温度廓线的通道选择研究[J].气象科学,2009,29(4):475-481.]
[16]Smith W L, Woolf H M. The use of eigenvectors of statistical covariance matrices for interpreting satellite sounding radiometer observations[J]. Journal of the Atmospheric Sciences,1976,33:1 127-1 140.
[17]Smith W L, Zhou D K, Harrison F W,et al. Hyperspectral remote sensing of atmospheric profiles from satellites and aircraft[C]∥Second SEPI International Asia-Pacific Symposium on Remote Sensing of the Atmosphere, Environment, and Space. Proceedings of SPIE. Sendai, Japan,2001:94-102.
[18]Guan Li. Retrieving atmospheric profiles from MODIS/AIRS observations I. Eigenvector regression algorithms[J].Journal of Nanjing Institute of Meteorology,2006,29(6):756-761.[官莉.利用AIRS卫星资料反演大气廓线I.特征向量统计反演法[J].南京气象学院学报,2006,29(6): 756-761.]
[19]Jiang Deming, Dong Chaohua, Lu Weisong. Preliminary study on the capacity of high spectral resolution infrared atmospheric sounding instrument using AIRS measurements[J].Journal of Remote Sensing,2006,10(4):586-592.[蒋德明,董超华,陆维松.利用AIRS观测资料进行红外高光谱大气探测能力试验的研究[J].遥感学报,2006,10(4):586-592.]
[20]Guan Li. The Application of Spaceborne Infrared Hyperspectral Data[M].Beijing:China Meteorological Press,2008:55-56.[官莉.星载红外高光谱资料的应用[M].北京:气象出版社,2008:55-56.]
[21]Li Jun, Zeng Qingcun. Infrared remote sensing of clear atmosphere and its inversion problem. Part I: Theoretical study[J].Scientia Atmospheric Sinica,1997,21(1):1-9.[李俊,曾庆存.晴空时大气红外遥感及其反演问题研究I.理论研究[J].大气科学,1997,21(1):1-9.]
[22]Li Jun, Zeng Qingcun. Infrared remote sensing of clear atmosphere and related inversion problem. Part II: Experimental study[J].Scientia Atmospheric Sinica,1997,21(2):214-222.[李俊,曾庆存.晴空时大气红外遥感及其反演问题研究II.反演试验研究[J].大气科学,1997,21(2):214-222.]
[23][JP3]Wang Xin,Deng Xiaobo,Zhang Shenglan. Retrieving atmospheric water vapor using artificial neural network method[C]∥The 29th Annual Meeting of China Meteorological Society, S6 Atmospheric Composition and Climate Change.Shenyang,2012.[王鑫,邓小波,张升兰.利用人工神经网络方法反演大气水汽[C]∥第29届中国气象学会年会,S6大气成分与天气气候变化.沈阳,2012.][JP]
[24]Guan Li. A Sutdy on Inrfared Hyperspecrtal Measurements and Its Applications on Cloud Detection,Cloud-Clearing and Atmospheric Sounding Profile[D]. Nanjing:Nanjing University of Information Science & Teehnology,2005:47-83.[官莉. 卫星红外超光谱资料及其在云检测、晴空订正和大气廓线反演方面的应用[D]. 南京:南京信息工程大学,2005:47-83.]
[25]Jiang Deming, Dong Chaohua,Cao Siqin. Impact assessment of assitional predictors to the retrieval of atmospheric profiles from infrared radiances[J]. Journal of Tropical Meteorology,2009,25(Suppl.):79-84.[蒋德明,董超华,曹思沁.附加影响因子对红外遥感资料反演大气温湿廓线的辅助作用[J].热带气象学报,2009,25(增刊):79-84.]
[26]Song Jinnuan.A Simulation Study on the Methods of Atmospheric Profiles Retrieval in Clear Sky with AIRS Observations[D]. Nanjing:Nanjing University of Information Science & Technology, 2007:50-51.[宋金暖.AIRS资料反演晴空大气廓线方法的模拟研究[D].南京:南京信息工程大学,2007:50-51.]
[27]Smith W L. An improved method for calculating tropospheric temperature and moisture from satellite radiometer measurements[J].Monthly Weather Review,1968,96:387-396.
[28]Guan Li, Huang H L, Baggett K, et al. Comparison of global AIRS/AMSU and AIRS/MODIS cloud-clearing performance[C]∥Atmospheric and Environmental Remote Sensing Data Processing and Utilization: Numerical Atmospherics Prediction and Environmental Monitoring: Proceedings of SPIE 5890. SanDiego Califoria, USA,2005:334-342.
[29]Guan Li, Huang Hunglung. Comparison of two infrared cloud-cleared approaches and their respective sounding retrieval products[J]. Journal of Nanjing Institute of Meteorology,2008,31(5):640-645.[官莉,Huang Hunglung.两种红外晴空辐射订正方法及其反演大气参数的比较[J]. 南京气象学院学报,2008,31(5):640-645.]
[30]Guan Li, Wang Zhenhui, Huang Hunglung. Simulation of atmospheric profile retrieval sensitivity to cloud from hyperspectral infrared data[J]. Scientia Meteorologica Sinica, 2009,29(3):312-316.[官莉,王振会,Huang Hunglung.红外高光谱资料模拟大气廓线反演对云的敏感性[J].气象科学,2009,29(3):312-316.]
[31]Guan Li, Huang Hunglung, Wang Zhenhui. Simulation of atmospheric profile retrieval from hyperspectral infrared data under cloudy condition[J].Journal of Remote Sensing, 2008,12(6):987-992.[官莉,Huang Hunglung,王振会.高光谱资料反演有云时大气温湿廓线的模拟研究[J].遥感学报,2008,12(6):987-992.]
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