Improving forecast skill by assimilation of quality‐controlled AIRS temperature retrievals under partially cloudy conditions

Abstract

The National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) on board the Aqua satellite is now recognized as an important contributor towards the improvement of weather forecasts. At this time only a small fraction of the total data produced by AIRS is being used by operational weather systems. In fact, in addition to effects of thinning and quality control, the only AIRS data assimilated are radiance observations of channels unaffected by clouds. Observations in mid‐lower tropospheric sounding AIRS channels are assimilated primarily under completely clear‐sky conditions, thus imposing a very severe limitation on the horizontal distribution of the AIRS‐derived information. In this work it is shown that the ability to derive accurate temperature profiles from AIRS observations in partially cloud‐contaminated areas can be utilized to further improve the impact of AIRS observations in a global model and forecasting system. The analyses produced by assimilating AIRS temperature profiles obtained under partial cloud cover result in a substantially colder representation of the northern hemisphere lower midtroposphere at higher latitudes. This temperature difference has a strong impact, through hydrostatic adjustment, in the midtropospheric geopotential heights, which causes a different representation of the polar vortex especially over northeastern Siberia and Alaska. The AIRS‐induced anomaly propagates through the model's dynamics producing improved 5‐day forecasts.