Impacts of Assimilating FY-4A AGRI Clear-Sky Water Vapor Radiance on Short-Range Weather Prediction during Indian Summer Monsoon

ABSTRACT

This study aims to assess the impacts of assimilating the clear-sky radiances from the Advanced Geosynchronous Radiation Imager (AGRI) onboard the Fengyun-4A (FY-4A) satellite on 72-h forecasts. First, we compare the water vapour (WV) brightness temperature (T_B) in July 2018 from the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) analyses and Weather Research and Forecasting (WRF) forecasts with the clear-sky AGRI WV channel observations. The results suggest that the NCEP GDAS analyses are more consistent with the AGRI observations than the WRF forecasts, and the AGRI observations can be utilized to improve the initial conditions of the WRF model by data assimilation, especially in water vapour and surface temperature. After the preliminary verification, two identical cycling assimilation experiments are performed with and without the AGRI WV T_B assimilation for a month. The results reveal that the WRF forecasts with AGRI T_B assimilation are closer to satellite observations than the first guess in both WV channels. The validation with WV channel data of the Microwave Humidity Sounder (MHS) and SAPHIR sensors indicates that after the AGRI data assimilation, the errors are smaller than in the control experiment (without AGRI assimilation). The assimilation of the T_B observed by AGRI WV channels shows a remarkable positive impact on moisture forecasts at middle and upper levels. Comparison of the T_B from the WRF forecasts with the MHS observations suggests that the AGRI WV channel assimilation can improve the predictions. Overall, assimilating AGRI WV observations can positively influence the WRF analyses and forecasts.

KEYWORDS:

• AGRI
• Water vapour
• Assimilation, WRF model
• WRF model

Acknowledgements

The authors acknowledge the WRF model and its assimilation system and NCAR’s Research Data Archive for NCEP GDAS analysis, conventional observations, satellite winds and satellite radiance. The authors also acknowledge the National Satellite Meteorological Center China Meteorological Administration (http://www.nsmc.org.cn/) for Fengyun-4A satellite AGRI data. The Fengyun-4A satellite AGRI raw radiance and cloud mask product were collected from the National Satellite Meteorological Center, China Meteorological Administration (http://satellite.nsmc.org.cn/PortalSite/Data/DataView.aspx?SatelliteType=1&SatelliteCode=FY4A). This work was supported by the Shanghai Sailing Program (Grant No. 21YF1456800). The authors are also thankful to anonymous reviewers for their constructive suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Highlights of the manuscript

Assess the assimilation impact of clear-sky radiances from the AGRI onboard FY-4A satellite on Indian summer monsoon period.

Validations with independent microwave sensors exhibit a positive impact of AGRI WV radiance to improve analyses and forecasts.

Cycling assimilation experiments presented a remarkable positive impact on moisture and rainfall forecasts.

Open research

The WRF model and its assimilation system are available from https://github.com/wrf-model/. The NCEP GDAS analysis is available from https://rda.ucar.edu/datasets/ds083.3/. The conventional observations, satellite winds in PrepBUFR format are available from https://rda.ucar.edu/datasets/ds337.0/. The GPS RO measurements and satellite radiance are available from https://rda.ucar.edu/datasets/ds735.0/. The WRF model output and scripts are available from https://doi.org/10.5281/zenodo.7319456.