Near-surface air temperature retrieval from Chinese Geostationary FengYun Meteorological Satellite (FY-2C) data

被引:5
|
作者
Guo, Zheng [1 ,2 ]
Chen, Yunhao [1 ]
Cheng, Miaomiao [3 ]
Jiang, Hong [3 ,4 ]
机构
[1] Beijing Normal Univ, Coll Resource Sci & Technol, Beijing 100875, Peoples R China
[2] Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China
[3] Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210093, Jiangsu, Peoples R China
[4] Zhejiang Agr & Forestry Univ, Zhejiang Prov Key Lab Carbon Cycling Forest Ecosy, Hangzhou 311300, Zhejiang, Peoples R China
关键词
SPLIT-WINDOW ALGORITHM; REMOTE-SENSING DATA; AVHRR DATA; LAND; PHOTOSYNTHESIS; EMISSIVITY; SPACE;
D O I
10.1080/01431161.2014.919674
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Spatially distributed near-surface air temperature data are a very important input parameter for several land-surface models. Such data are often lacking because there are few traditional meteorological stations. It is of great significance in both theoretical research and practical applications to retrieve air temperature data from remote-sensing observations. Based on the radiative transfer theory, this article addresses the estimate of near-surface air temperature from data from the first Chinese operational geostationary meteorological satellite, FengYun-2C (FY-2C), in two thermal infrared channels (IR1, 10.3-11.3 mu m and IR2, 11.5-12.5 mu m) and the MODIS atmospheric profile (MOD07) product, which provide profiles of water vapour and air temperature in different atmospheric layers. The algorithm involves only two essential parameters (transmittance and emissivity). Sensitivity analysis of the algorithm has been performed for evaluation of probable near-surface air temperature estimation error due to the possible errors in transmittance and emissivity. Results from the analysis indicate that the proposed algorithm is able to provide an accurate estimation of near-surface air temperature from FY-2C data. Results from the sensitivity analysis indicate that the average air temperature estimation error is less than 1.2 K for a possible transmittance error of 0.05 in both channels under an emissivity range 0.95-0.98. Assuming an error of 0.005 in ground emissivity for the two thermal channels, the average near-surface air temperature error is 0.6 K. Measured air temperature datasets have been used to validate the algorithm. All the validated data indicate that the estimate error is less than 3 K in more than 80% of the samples. The high accuracy for this dataset confirms the applicability of the proposed algorithm as an alternative method for accurate near-surface air temperature retrieval from FY-2C data.
引用
收藏
页码:3892 / 3914
页数:23
相关论文
共 50 条
  • [1] Generalized Split-Window algorithm for estimate of Land Surface Temperature from Chinese geostationary FengYun meteorological satellite (FY-2C) data
    Tang, Bohui
    Bi, Yuyun
    Li, Zhao-Liang
    Xia, Jun
    SENSORS, 2008, 8 (02) : 933 - 951
  • [2] Estimation of the Land Surface Temperature over the Tibetan Plateau by Using Chinese FY-2C Geostationary Satellite Data
    Hu, Yuanyuan
    Zhong, Lei
    Ma, Yaoming
    Zou, Mijun
    Xu, Kepiao
    Huang, Ziyu
    Feng, Lu
    SENSORS, 2018, 18 (02)
  • [3] Estimation and Validation of Land Surface Temperature Using Chinese Geostationary FengYun Meteorological Satellite (FY-2D) Data in an Arid Region
    Pan, Xin
    Liu, Suyi
    Yang, Zi
    Zhu, Xi
    Yang, Yingbao
    Xie, Wenying
    Yuan, Jie
    Wang, Zhanchuan
    Song, Hao
    IEEE ACCESS, 2023, 11 : 136033 - 136040
  • [4] Estimation of Near-Surface Air Temperature in Daxing’anling Mountains Forest Area based on Fengyun-4B Geostationary Meteorological Satellite Data
    Sun, Zhongqiu
    Ye, Xin
    Linye Kexue/Scientia Silvae Sinicae, 2024, 60 (12): : 27 - 34
  • [6] Automatic Tracking and Characterization of Cumulonimbus Clouds from FY-2C Geostationary Meteorological Satellite Images
    Liu, Yu
    Xi, Du-Gang
    Li, Zhao-Liang
    Shi, Chun-Xiang
    ADVANCES IN METEOROLOGY, 2014, 2014
  • [7] Deep Learning for Near-Surface Air Temperature Estimation From FengYun 4A Satellite Data
    Yang, Shanmin
    Ren, Qing
    Zhou, Ningfang
    Zhang, Yan
    Wu, Xi
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2024, 17 : 13108 - 13119
  • [8] Deep Learning for Near-Surface Air Temperature Estimation From FengYun 4A Satellite Data
    Yang, Shanmin
    Ren, Qing
    Zhou, Ningfang
    Zhang, Yan
    Wu, Xi
    SCIENTIFIC REPORTS, 2023, 13 (01): : 13108 - 13119
  • [9] Estimating net surface shortwave radiation from Chinese geostationary meteorological satellite FengYun-2D (FY-2D) data under clear sky
    Zhang, Xiaoyu
    Li, Lingling
    OPTICS EXPRESS, 2016, 24 (06): : A476 - A487
  • [10] Operational retrieval of Asian sand and dust storm from FY-2C geostationary meteorological satellite and its application to real time forecast in Asia
    Hu, X. Q.
    Lu, N. M.
    Niu, T.
    Zhang, P.
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2008, 8 (06) : 1649 - 1659