A channel selection for the assimilation of CrIS and HIRAS instruments at full spectral resolution

Abstract

A new channel selection is proposed for the processing of observations at full spectral resolution (FSR) from the Cross-track Infrared Sounder (CrIS) and Hyperspectral Infrared Atmospheric Sounder (HIRAS) instruments in the Met Office global numerical weather prediction (NWP) system. The new selection has been derived in order to minimise the error in NWP analysis and has been compared to an existing selection developed at the National Oceanic and Atmospheric Administration (NOAA). Both selections have been tested in the Met Office global NWP system to investigate the use of FSR CrIS compared with the current normal spectral resolution (NSR) set-up employed in operations. Improvements are obtained for most forecast variables up to 7-day lead times, with change in root-mean-square error (RMSE) ranging from 0.13 to 0.54%, although degradation of tropical temperatures are noted for the NOAA selection. The background fit to observations from independent sounders improves by up to 0.8% with the new selection, outperforming the NOAA selection which results in degradations across most instruments. The assimilation of HIRAS observations does not however benefit the system.

Impact of Channel Selection with Different Bandwidths on Retrieval at 50–60 GHz

“…In the first iteration, the computation of the analysis error covariance matrix also depends on the given background error covariance matrix. In this paper, the background error covariance is based on the statistical results of global samples [17].…”

Assimilation of FY-3D and FY-3E Hyperspectral Infrared Atmospheric Sounding Observation and Its Impact on Numerical Weather Prediction during Spring Season over the Continental United States

“…Among the payloads onboard the FY-3 series platforms, it is the microwave temperature sounding data, i.e., MWTS-1, -2, -3 and MWHS-2 that is widely used [12][13][14][15][16][17]. Recently, operational NWP centers started paying attention to the hyperspectral infrared sounding observations gathered by the Hyperspectral Infrared Atmospheric Sounder (HIRAS) onboard FY-3D [18,19]. The results reveal that most forecast variables up to a 7-day lead time can obtain improvements from HIRAS observation assimilation, with a 0.1 to 0.5% root-mean-square error (RMSE) deduction.…”

“…attention to the hyperspectral infrared sounding observations gathered by the Hyperspectral Infrared Atmospheric Sounder (HIRAS) onboard FY-3D [18,19]. The results reveal that most forecast variables up to a 7-day lead time can obtain improvements from HIRAS observation assimilation, with a 0.1 to 0.5% root-mean-square error (RMSE) deduction.…”