On the benefits of assimilating a denser set of geostationary clear-sky radiance
- ECMWF, Research department, Bonn, Germany
Within the framework of Destination Earth (https://digital-strategy.ec.europa.eu/en/policies/destination-earth) we are running global weather forecasts at the km-scale. A major goal is to improve forecasts of wind for renewable energy purposes, as well as precipitation in extreme weather events. Initialisation of the high-resolution forecasts requires analysis that can be constrained by high-resolution observations.
Our experiments use a relatively denser set of clear-sky radiances from geostationary satellites. In assimilating the clear-sky observations, we simultanously vary the spatial & temporal sampling. Short-range forecasts compared to independent humidity sensitive satellite instruments such as IASI and CrIS show significant improvements as well as all-sky instruments such as SSMIS. Comparing observation of wind measurements such as AEOLUS reveals a better agreement under certain conditions together with improvements in comparisons to conventional wind measurements.
Furthermore, we diagnose the effect on simulated satellite images for GOES and SEVIRI based on the study by Lopez & Matricardi (2022). Such a diagnostic tool allows for verification at the km-scale, as well as at very high temporal resolution down to 10 min. Comparing infrared, visible, water vapor observations with ifs simulated cloud fields we find better performance in the high-resolution simulations as briefly discussed by Lledo et al. (2022) using the fractional-skill score on clouds. In future experiments, we aim to compare forecasts at the km-scale based on assimilation experiments with higher temporal and spatial data density compared to the current operational setting of the IFS.
- L. Lledó, T. Haiden, J. Schröttle, and R. Forbes, Scale-dependent verification of precipitation and cloudiness at ECMWF.ECMWF Newsletter Number 174 (2022)
- P. Lopez and M. Matricardi, Validation of IFS+RTTOV/MFASIS0.64-μm reflectances against observations from GOES-16, GOES-17, MSG-4 and Himawari-8. ECMWF Technical Memoranda (2022)
How to cite: Schröttle, J., Lledó, L., Lupu, C., Burrows, C., and Holm, E.: On the benefits of assimilating a denser set of geostationary clear-sky radiance, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-82, https://doi.org/10.5194/ems2023-82, 2023.
