Apport des observations satellitaires hyperspectrales infrarouges IASI au-dessus des continents dans le modèle météorologique à échelle convective AROME

Abstract : An essential component of the numerical weather forecast is the analysis of the atmosphere, the necessary step for the definition of the initial conditions of forecasts. This analysis uses in-situ data as well as satellite observations. The current high-spectral resolution advanced infrared sounder generation includes in particular IASI (Infrared Atmospheric Sounding Interferometer, developed by CNES / EUMETSAT) onboard polar orbiting Metop satellites. These sounders provide a large amount of information allowing to describe accurately surface parameters (such as land surface temperature ’LST’ and surface emissivity on a wide range of wavelengths). However, the forecast of continental surface temperature is not realistic enough to use the infrared information in the lower troposphere and close to the surface over continents because radiances sensitive to these regions are strongly affected by the variation of surface parameters (e.g. LST, surface emissivity and humidity) and cloud cover. This issue could produce a large difference between the observations and the simulations, also a bad cloud detection, which prompts the system to reject the observations and limits the use of these data. This PhD work aims to improve the analyses and the forecasts by increasing the assimilation of IASI observations over land in the convective-scale AROME model of Météo-France. The first part of study was focused on the identification of the appropriate IASI surface-sensitive channel for LST retrieval. By pursuing the approach developed by [Vincensini, 2013] to find surface temperature from a combination of channels, a new channel selection over land was build, to better analyse the lower layers of the atmosphere, in particular in term of temperature and humidity. LST was extracted from IASI radiances using radiative transfer equation inversion [Karbou et al., 2006], RTTOV model and a surface emissivity atlas developed by the Space Science and Engineering Center at University of Wisconsin. IASI channel 1194 was then selected to retrieve LST as a result of several comparisons with background and other IASI, SEVIRI and AVHRR LST retrievals. The retrieved LST from this channel was then used in RTTOV model to improve the simulation of IASI surface-sensitive infrared observations. The impact on the McNally & Watts cloud detection scheme has been evaluated with more clear channels inside clear pixel with LST retrieval. Data assimilation experiments using the retrieved LST and enhancing the IASI channel selection over land were carried out in the AROME-France model. Improvement of humidity analyses and forecasts will also be described.
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Niama Boukachaba. Apport des observations satellitaires hyperspectrales infrarouges IASI au-dessus des continents dans le modèle météorologique à échelle convective AROME. Météorologie. INP Toulouse, 2017. Français. ⟨tel-01719748⟩

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