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Volume 9 Issue 3

Jul.  1992

Article Contents

Spectral and Anisotropic Corrections for GMS Satellite Data


doi: 10.1007/BF02656939

  • Using the radiative transfer simulation, the sampling study about the spectral and anisotropic corrections for GMS satellite data is carried out. The conversion factor and the anisotropic reflectance factor in inversion process of broadband radiation fluxes have been obtained for various underlying surface scenes in clear sky and for the case of overcast sky. The results demonstrate that the consideration of spectral and anisotropic corrections is essential for the earth radiation budget research using satellite data. The mean conversion factors for GMS are between 2.54 and 5.30. The values of the conversion factor are different for various observation angles, especially in cases of ocean, vegeta-tion cover and wet soil surface. The error of retrieving broadband radiance without considering the difference of ob-servation geometry is about 5.5%-15% for ocean, 4.5%-10% for various land surfaces. The calculated anisotropic factors for ocean and cloud scenes are in good agreement with those estimated from Nimbus-7. For Land, desert and snow scenes, the calculated values in backward scattering direction are smaller than the measured.
  • [1] Myoung-Hwan AHN, Eun-Ha SOHN, Byong-Jun HWANG, 2003: A New Algorithm for Sea Fog/Stratus Detection Using GMS-5 IR Data, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 899-913.  doi: 10.1007/BF02915513
    [2] Yanni Qu, Mitchell D. Goldberg, Murty Divakarla, 2001: Ozone Profile Retrieval from Satellite Observation Using High Spectral Resolution Infrared Sounding Instrument, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 959-971.
    [3] WANG Han, SUN Xiaobing, SUN Bin, LIANG Tianquan, LI Cuili, and HONG Jin, 2014: Retrieval of Aerosol Optical Properties over a Vegetation Surface Using Multi-angular, Multi-spectral, and Polarized data, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 879-887.  doi: 10.1007/s00376-013-3100-5
    [4] Ling WANG, Xiuqing HU, Na XU, Lin CHEN, 2021: Water Vapor Retrievals from Near-infrared Channels of the Advanced Medium Resolution Spectral Imager Instrument onboard the Fengyun-3D Satellite, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1351-1366.  doi: 10.1007/s00376-020-0174-8
    [5] Peng ZHANG, Qifeng LU, Xiuqing HU, Songyan GU, Lei YANG, Min MIN, Lin CHEN, Na XU, Ling Sun, Wenguang BAI, Gang MA, Di XIAN, 2019: Latest Progress of the Chinese Meteorological Satellite Program and Core Data Processing Technologies, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1027-1045.  doi: 10.1007/s00376-019-8215-x
    [6] ZENG Heqing, JIA Gensuo, 2013: Impacts of Snow Cover on Vegetation Phenology in the Arctic from Satellite Data, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1421-1432.  doi: 10.1007/s00376-012-2173-x
    [7] Li Jun, Zhou Fengxian, Gao Qinghuai, 1991: Satellite Data Reduction Using Entropy-preserved Image Compression Technique, ADVANCES IN ATMOSPHERIC SCIENCES, 8, 237-242.  doi: 10.1007/BF02658097
    [8] Li Jun, Wang Luyi, Zhou Fengxian, 1993: Convective and Stratiform Cloud Rainfall Estimation from Geostationary Satellite Data, ADVANCES IN ATMOSPHERIC SCIENCES, 10, 475-480.  doi: 10.1007/BF02656972
    [9] Yaodeng CHEN, Jie SHEN, Shuiyong FAN, Deming MENG, Cheng WANG, 2020: Characteristics of Fengyun-4A Satellite Atmospheric Motion Vectors and Their Impacts on Data Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 1222-1238.  doi: 10.1007/s00376-020-0080-0
    [10] Fabien CARMINATI, Nigel ATKINSON, Brett CANDY, Qifeng LU, 2021: Insights into the Microwave Instruments Onboard the Fengyun 3D Satellite: Data Quality and Assimilation in the Met Office NWP System, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1379-1396.  doi: 10.1007/s00376-020-0010-1
    [11] Keyi CHEN, Niels BORMANN, Stephen ENGLISH, Jiang ZHU, 2018: Assimilation of Feng-Yun-3B Satellite Microwave Humidity Sounder Data over Land, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 268-275.  doi: 10.1007/s00376-017-7088-0
    [12] Jincheng WANG, Xingwei JIANG, Xueshun SHEN, Youguang ZHANG, Xiaomin WAN, Wei HAN, Dan WANG, 2023: Assimilation of Ocean Surface Wind Data by the HY-2B Satellite in GRAPES: Impacts on Analyses and Forecasts, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 44-61.  doi: 10.1007/s00376-022-1349-2
    [13] Li Jun, Zhou Fengxian, 1992: On Accurate Detection of Oceanic Features from Satellite IR Data Using ICSED Method, ADVANCES IN ATMOSPHERIC SCIENCES, 9, 373-382.  doi: 10.1007/BF02656948
    [14] Seung-Woo LEE, Dong-Kyou LEE, 2011: Improvement in Background Error Covariances Using Ensemble Forecasts for Assimilation of High-Resolution Satellite Data, ADVANCES IN ATMOSPHERIC SCIENCES, 28, 758-774.  doi: 10.1007/s00376-010-0145-6
    [15] Shengzhe CHEN, Jiping LIU, Yifan DING, Yuanyuan ZHANG, Xiao CHENG, Yongyun HU, 2021: Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 168-186.  doi: 10.1007/s00376-020-0213-5
    [16] Yong L. McHall, 1993: Group Velocity of Anisotropic Waves-Part I: Mathematical Expression, ADVANCES IN ATMOSPHERIC SCIENCES, 10, 393-406.  doi: 10.1007/BF02656964
    [17] Yong L. McHall, 1993: Group Velocity of Anisotropic Waves-Part II: Conservative Properties, ADVANCES IN ATMOSPHERIC SCIENCES, 10, 407-414.  doi: 10.1007/BF02656965
    [18] Li Jun, Zhou Fengxian, Wang Luyi, 1992: Automatic Classification and Compression of GMS Cloud Imagery in Heavy Rainfall Monitoring Application, ADVANCES IN ATMOSPHERIC SCIENCES, 9, 458-464.  doi: 10.1007/BF02677078
    [19] Kefeng ZHU, Ming XUE, Yujie PAN, Ming HU, Stanley G. BENJAMIN, Stephen S. WEYGANDT, Haidao LIN, 2019: The Impact of Satellite Radiance Data Assimilation within a Frequently Updated Regional Forecast System Using a GSI-based Ensemble Kalman Filter, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1308-1326.  doi: 10.1007/s00376-019-9011-3
    [20] Huaming ZHANG, Yijun ZHANG, Weitao LYU, Yang ZHANG, Qi QI, Yanfeng FAN, 2019: Analysis of the Spectral Characteristics of Triggered Lightning, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1265-1272.  doi: 10.1007/s00376-019-9006-0

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Manuscript History

Manuscript received: 10 July 1992
Manuscript revised: 10 July 1992
通讯作者: 陈斌, bchen63@163.com
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Spectral and Anisotropic Corrections for GMS Satellite Data

  • 1. Institute of Geophysics and Meteorology, University of Cologne, F. R. Germany

Abstract: Using the radiative transfer simulation, the sampling study about the spectral and anisotropic corrections for GMS satellite data is carried out. The conversion factor and the anisotropic reflectance factor in inversion process of broadband radiation fluxes have been obtained for various underlying surface scenes in clear sky and for the case of overcast sky. The results demonstrate that the consideration of spectral and anisotropic corrections is essential for the earth radiation budget research using satellite data. The mean conversion factors for GMS are between 2.54 and 5.30. The values of the conversion factor are different for various observation angles, especially in cases of ocean, vegeta-tion cover and wet soil surface. The error of retrieving broadband radiance without considering the difference of ob-servation geometry is about 5.5%-15% for ocean, 4.5%-10% for various land surfaces. The calculated anisotropic factors for ocean and cloud scenes are in good agreement with those estimated from Nimbus-7. For Land, desert and snow scenes, the calculated values in backward scattering direction are smaller than the measured.

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