Direct Assimilation of ABI Infrared Radiances in NWP Models

Abstract

GOES-R satellite was successfully launched on November 19, 2016 with an Advanced Baseline Imager (ABI) on board. ABI is a new imager and provides more advanced capabilities for weather applications through more channels and higher temporal and spatial resolutions than the earlier GOES imagers. In this study, impacts from assimilating ABI brightness temperatures in NWP models on quantitative precipitation forecasts (QPFs) are presented and compared with those from assimilating GOES-13/-15 imager data. Cloudy and precipitation-affected brightness temperatures are removed in assimilation through using an infrared (IR) cloud algorithm in quality control. This quality control can be applied for ABI data both at day and at night. Assimilation of the ten ABI IR channels improves the 24-h forecast accuracy of both temperature and specific humidity fields when compared with radiosonde observations. It is also shown that the assimilation of ABI IR channels produces positive impacts on QPFs. The impacts of ABI data assimilation on QPFs are slightly larger than those from assimilation of GOES-13 and -15 imager observations.

Keywords

• Data assimilation
• geostationary satellite
• quantitative precipitation forecast (QPF)