Assimilation of radiance observations from geostationary satellites: third year report

TitleAssimilation of radiance observations from geostationary satellites: third year report
Publication TypeReport
Date Published2020
Series/CollectionEUMETSAT/ECMWF Fellowship Programme Research Report
Document Number52
TypeReport
AuthorBurrows, C
Report Number52
Abstract

The assimilation of radiance data from Meteosat-8 and Meteosat-11 continues to be of value to the ECMWF system, along with other satellites in the geostationary ring. In particular, forecast sensitivity to observation impact (FSOI) results indicate that these observations are among the most beneficial infrared water vapour observations when normalised to produce the impact per observation, with the two Meteosat satellites giving the largest impact per observation in this category. Meteosat radiance observations with high zenith angles are now being exploited operationally in the ECMWF system, and we would encourage other data providers to disseminate observations with similarly large zenith angles.
In preparation for the assimilation of GOES-17 radiances, an investigation has taken place into the known instrument issue whereby at certain times of day close to the equinoxes the detector overheats. This is seen prominently in the first guess departure statistics, and the times at which the observations are degraded has been fed back to NOAA and may influence quality control decisions.
With the prospect of high temporal frequency data from both FCI and IRS on the MTG series of satellites, it is important to ensure that the assimilation system is prepared for receipt of these data. Although most clear sky radiance (CSR) products are provided hourly, the unofficial GOES-16 CSRs are provided every 10 minutes, each scan representing the full disk. This is a new opportunity, as observations have not been assimilated this frequently in global NWP. In order to extract the high temporal frequency
information of the humidity field that will lead to improved wind tracing, the assimilation system has required modification to remove a level of time discretisation which would otherwise have prevented these observations being assimilated optimally. The results presented here indicate that increasing the temporal frequency of assimilated GOES-16 CSRs to one full disk every 20 minutes can improve shortrange forecast skill in the ECMWF system. When observations are assimilated every 10 minutes, the short- range forecasts are degraded, but this can be mitigated by inflating the observation errors on
account of the neglect of temporal error correlations.
ECMWF is actively preparing for the launch of MTG-IRS, which will be the first geostationary hyperspectral instrument covering Europe, and will be a step change in the remote sensing of this region. A new opportunity for this preparation has been the provision of observation data from the GIIRS instrument onboard the Chinese satellite FY-4A. Although this instrument has a lower specification than IRS, a great deal can be learned from these data in anticipation of IRS. As presented here, initially, the spectral calibration of GIIRS was unsatisfactory, but in collaboration with SSEC and CMA, the required shift was
ascertained, using both ECMWF simulations and (at SSEC) co-located IASI and CrIS observations. A significantly improved spectral calibration has been implemented in the latest processing version of the GIIRS ground segment. Deficiencies have been discovered in the unofficial GIIRS RTTOV coefficients which we have used until recently, and it is shown that the official RTTOV coefficients look much better regarding consistency across the zenith angle range. Finally, some initial assimilation experiments have
been performed using GIIRS data in the global assimilation system. The assimilation setup for GIIRS is deliberately basic for these initial experiments, and plans to augment various aspects of this have been described. Although the experiments have not run for a long time, encouraging signals are being seen in the verification of short-range forecasts against independent observations.

URLhttps://www.ecmwf.int/node/19483
DOI10.21957/spbzz81e3
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