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Volume 23 Issue 2

Mar.  2006

Article Contents
Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2006 >  23(2): 224-234

Estimating the Retrievability of Temperature Profiles from Satellite Infrared Measurements

  • 1.

    College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000,College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000,National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081,Cold and Arid Regions Environment and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000


doi: 10.1007/s00376-006-0224-x

  • A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generalized linear inverse theory and empirical orthogonal function analysis. Utilizing the NCEP global temperature reanalysis data in January and July from 1999 to 2003, the retrievabilities obtained with the Atmospheric Infrared Sounder (AIRS) and the High Resolution Infrared Radiation Sounder/3 (HIRS/3) sounding channel data are derived respectively for each standard pressure level on a global scale. As an incidental result of this study, the optimum truncation number in the method of generalized linear inverse is deduced too. The results show that the retrievabilities of temperature obtained with the two datasets are similar in spatial distribution and seasonal change characteristics. As for the vertical distribution, the retrievabilities are low in the upper and lower atmosphere, and high between 400 hPa and 850 hPa. For the geographical distribution, the retrievabilities are low in the low-latitude oceanic regions and in some regions in Antarctica, and relatively high in mid-high latitudes and continental regions. Compared with the HIRS/3 data, the retrievability obtained with the AIRS data can be improved by an amount between 0.15 and 0.40.
  • [1] YAO Zhigang, CHEN Hongbin, LIN Longfu, 2005: Retrieving Atmospheric Temperature Profiles from AMSU-A Data with Neural Networks, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 606-616.  doi: 10.1007/BF02918492
    [2] Bohua Huang, James L. Kinter III, Paul S. Schopf, 2002: Ocean Data Assimilation Using Intermittent Analyses and Continuous Model Error Correction, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 965-992.  doi: 10.1007/s00376-002-0059-z
    [3] Li Jun, Zhou Fengxian, Zeng Qingcun, 1994: Simultaneous Non-linear Retrieval of Atmospheric Temperature and Absorbing Constituent Profiles from Satellite Infrared Sounder Radiances, ADVANCES IN ATMOSPHERIC SCIENCES, 11, 128-138.  doi: 10.1007/BF02666541
    [4] Peipei YU, Chunxiang SHI, Ling YANG, Shuai SHAN, 2020: A New Temperature Channel Selection Method Based on Singular Spectrum Analysis for Retrieving Atmospheric Temperature Profiles from FY-4A/GIIRS, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 735-750.  doi: 10.1007/s00376-020-9249-9
    [5] Peng ZHANG, Jun YANG, Jinsong WANG, Xinwen YU, 2021: Preface to the Special Issue on Fengyun Meteorological Satellites: Data, Application and Assessment, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1265-1266.  doi: 10.1007/s00376-021-1002-5
    [6] ZHANG Jie, Zhenglong LI, Jun LI, Jinglong LI, 2014: Ensemble Retrieval of Atmospheric Temperature Profiles from AIRS, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 559-569.  doi: 10.1007/s00376-013-3094-z
    [7] Liu Changsheng, 1988: REMOTE SENSING OF TEMPERATURE PROFILES IN THE BOUNDARY LAYER, ADVANCES IN ATMOSPHERIC SCIENCES, 5, 67-74.  doi: 10.1007/BF02657346
    [8] Chao Jiping, Ji Zhengang, 1985: ON THE INFLUENCES OF LARGE-SCALE INHOMOGENEITY OF SEA TEMPERATURE UPON THE OCEANIC WAVES IN THE TROPICAL REGIONS——PART I : LINEAR THEORETICAL ANALYSIS, ADVANCES IN ATMOSPHERIC SCIENCES, 2, 295-306.  doi: 10.1007/BF02677245
    [9] Baofeng JIAO, Lingkun RAN, Na LI, Ren CAI, Tao QU, Yushu ZHOU, 2023: Comparative Analysis of the Generalized Omega Equation and Generalized Vertical Motion Equation, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 856-873.  doi: 10.1007/s00376-022-1435-5
    [10] ZHANG Lei, QIU Chongjian, HUANG Jianping, 2008: A Three-Dimensional Satellite Retrieval Method for Atmospheric Temperature and Moisture Profiles, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 897-904.  doi: 10.1007/s00376-008-0897-4
    [11] Lin Wantao, Ji Zhongzhen, Wang Bin, 2002: A Comparative Analysis of Computational Stability for Linear and Non-Linear Evolution Equations, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 699-704.  doi: 10.1007/s00376-002-0009-9
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    [13] ZHENG Jing, Jun LI, Timothy J. SCHMIT, Jinlong LI, Zhiquan LIU, 2015: The Impact of AIRS Atmospheric Temperature and Moisture Profiles on Hurricane Forecasts: Ike (2008) and Irene (2011), ADVANCES IN ATMOSPHERIC SCIENCES, 32, 319-335.  doi: 10.1007/s00376-014-3162-z
    [14] Qiumeng XUE, Li GUAN, Xiaoning SHI, 2022: One-Dimensional Variational Retrieval of Temperature and Humidity Profiles from the FY4A GIIRS, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 471-486.  doi: 10.1007/s00376-021-1032-z
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    [20] Xiaolei ZOU, Xiaoxu TIAN, 2019: Striping Noise Analysis and Mitigation for Microwave Temperature Sounder-2 Observations, ADVANCES IN ATMOSPHERIC SCIENCES, , 711-720.  doi: 10.1007/s00376-019-9009-x
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    • Manuscript History

    Manuscript received: 10 March 2006
    Manuscript revised: 10 March 2006
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    Estimating the Retrievability of Temperature Profiles from Satellite Infrared Measurements

    • 1. College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000,College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000,National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081,Cold and Arid Regions Environment and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000
    • Manuscript received: 2006-03-10
    • Manuscript revised: 2006-03-10

    Abstract: A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generalized linear inverse theory and empirical orthogonal function analysis. Utilizing the NCEP global temperature reanalysis data in January and July from 1999 to 2003, the retrievabilities obtained with the Atmospheric Infrared Sounder (AIRS) and the High Resolution Infrared Radiation Sounder/3 (HIRS/3) sounding channel data are derived respectively for each standard pressure level on a global scale. As an incidental result of this study, the optimum truncation number in the method of generalized linear inverse is deduced too. The results show that the retrievabilities of temperature obtained with the two datasets are similar in spatial distribution and seasonal change characteristics. As for the vertical distribution, the retrievabilities are low in the upper and lower atmosphere, and high between 400 hPa and 850 hPa. For the geographical distribution, the retrievabilities are low in the low-latitude oceanic regions and in some regions in Antarctica, and relatively high in mid-high latitudes and continental regions. Compared with the HIRS/3 data, the retrievability obtained with the AIRS data can be improved by an amount between 0.15 and 0.40.

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