Impact of assimilation of Atmospheric InfraRed Sounder (AIRS) radiances and retrievals in the WRF 3D‐Var assimilation system

Abstract

This study compares the performance of the advanced research version of the Weather Research and Forecasting (WRF) model in response to the assimilation of AIRS radiances and retrievals. The WRF model and its three‐dimensional variational (3D‐Var) data assimilation system is used to assimilate AIRS measurements (radiances and retrievals) and the impacts of these measurements are evaluated on the analysis and 24‐h forecasts over the Indian region for the entire month of July 2010. A rigorous validation is produced against HIRS and Kalpana VHRR radiances, NCEP analysis, and TRMM observed precipitation. Results show that the assimilation of AIRS measurements has a significant impact on WRF analysis and short range forecasts. The radiances simulated using WRF analyzed and forecast fields, assimilated with AIRS measurements, match significantly closer to HIRS and Kalpana VHRR radiances, relative to simulations without AIRS measurements (the control run). Assimilation of AIRS measurements leads to improvement of moisture, temperature, winds and rainfall forecast with respect to control run. This study indicates that assimilation of radiances and bias‐adjusted retrievals perform equally well when NCEP analysis is used for the verification, and it is found that analysis and forecasts resulting from assimilated AIRS radiances and bias‐adjusted retrievals are of better quality compared to those obtained by assimilating retrievals without bias‐adjustment.