ISSN 1006-9895

CN 11-1768/O4

+Advanced Search 中文版
Analysis of FY-4A AGRI Radiance Data Bias Characteristics and a Correction Experiment
Author:
Affiliation:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
    Abstract:

    As the latest generation of geostationary meteorological satellites in our country, a significant development has been made for Fengyun-4A (FY-4A). Compared with the previous generation (Fengyun-2), FY-4A has better observation accuracy and a shorter scanning time. Taking full advantage of the advanced geosynchronous radiation imager (AGRI) data, the level of weather and meteorological disasters forecasting in countries along the “The Belt and Road Initiatives” will be effectively improved. The interface for the FY-4A AGRI data assimilation is complemented in Weather Research and Forecasting Data Assimilation (WRFDA) v3.9.1 model before investigating the bias characteristics based on RTTOV v11.3 model and GFS analysis. Bias-correction experiments of FY-4A AGRI data in infrared Channels 8–14 were further conducted. The results show that: (1) Channels 8–10 and 14 have warm biases. There are cold biases in Channels 11–13. The biases and standard deviation of the water vapor Channels 9 and 10 are small. The characteristics of the biases show obvious differences between land and ocean in Channels 11–14. Land’s biases are more complex than the ocean’s. For these channels, observations on land can be eliminated in quality control. (2) The slope of the linear regression equation between bias and satellite zenith angle is less than 0.035. There is no obvious dependence of biases on the satellite zenith angle. (3) The bias in Channels 8 and 11–14 show more obvious dependence on the scene temperature than those in Channels 9 and 10. (4) The variational bias correction tested during 1800 UTC on May 13–15, 2018 shows that the systematic bias was effectively corrected.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:November 12,2018
  • Revised:
  • Adopted:
  • Online: July 28,2020
  • Published: