Abstract

AbstractSatellite radiances make up the vast majority of observations that are assimilated routinely at the Met Office and at other major numerical weather prediction (NWP) centres. Improvements in the use of these data have led to significant improvements in NWP forecast skill over the last 30 years. Since the advent of hyperspectral sensors, capable of measuring infrared radiance emerging from the atmosphere over thousands of channels, data providers and NWP centres have been facing the challenges of distributing, monitoring, and assimilating a considerable wealth of data. Forthcoming hyperspectral sensors such as the Infrared Atmospheric Sounding Interferometer New Generation (IASI‐NG) on MetOp Second Generation (Metop‐SG) and the Meteosat Third Generation Infrared Sounder (MTG‐IRS) will increase the amount of data to be considered for assimilation even further. It has been shown that Transformed Retrievals (TRs) generated from a spectrum of radiances can represent most of the information content of the radiances in a significantly reduced set of TR components. In this article we show for the first time, to our knowledge, that by assimilating TRs in an operational data assimilation system it is possible to achieve forecast skill gains similar to those when the same radiances used to generate the TRs are assimilated directly. These results pave the way to exploiting an order‐of‐magnitude larger number of channels from hyperspectral sounders for operational NWP.

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