Affiliation:
1. a CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
2. b EUMETSAT, Darmstadt, Germany
Abstract
Abstract
The main objective of the study is to evaluate the feasibility and benefits of assimilating satellite temperature and humidity soundings (aka Level 2 or L2 profiles), instead of radiances, from the EUMETSAT Advanced Retransmission Service (EARS) into the AROME-France data assimilation system. The satellite soundings are operational forecast-independent retrievals that used the infrared sounder IASI in synergy with its companion microwave instruments AMSU-A and MHS on board the MetOp platforms. In this assimilation study, L2 profiles are used as pseudoradiosondes, discarding vertical error correlations and the instrument vertical sensitivity in the observation operator due to the lack of available averaging kernels. Three assimilation experiments were performed, the baseline (including all satellite radiances except those from IASI, AMSU-A, and MHS sounders), the control (with observations from the baseline plus IASI, AMSU-A, and MHS radiances), and the L2 experiment (with observations from the baseline and L2 temperature and humidity profiles). The assimilation runs cover the periods of the winter 2017 and summer 2018. The forecast skills of the three experiments are gauged against independent analyses and observations. Despite that the vertical observation operator is not accounted for in this study, it is found that L2 profile assimilation does not have a negative impact on 1-h temperature and humidity forecasts, especially in the midtroposphere. Their impacts are comparable in magnitude to the radiance ones in the operational AROME framework, except in terms of temperature and wind fields during winter where the impact is more negative than positive. These findings encourage further investigations.
Funder
European Organization for the Exploitation of Meteorological Satellites
Publisher
American Meteorological Society
Reference23 articles.
1. Deterministic and fuzzy verification methods for a hierarchy of numerical models;Amodei, M.,2009
2. Adaptive bias correction for satellite data in a numerical weather prediction system;Auligné, T.,2007
3. Improvement of the forecast of convective activity from the AROME-France system;Brousseau, P.,2016
4. Impacts of targeted AERI and Doppler lidar wind retrievals on short-term forecasts of the initiation and early evolution of thunderstorms;Coniglio, M. C.,2019
5. The Arpege project at Meteo France;Courtier, P.,1991