Homogeneity criteria from AVHRR information within IASI pixels in a numerical weather prediction context

Imane Farouk,Nadia Fourrié,Vincent Guidard

doi:10.5194/amt-12-3001-2019

Abstract

Abstract. This article focuses on the selection of satellite infrared IASI (Infrared Atmospheric Sounding Interferometer) observations in the global numerical weather prediction (NWP) system ARPEGE (Action de Recherche Petite Echelle Grande Echelle). The observation simulation is performed with the sophisticated radiative transfer model RTTOV-CLD, which takes into account the cloud scattering and the multilayer clouds from atmospheric profiles and cloud microphysical profiles (liquid water content, ice content and cloud fraction). The aim of this work is to select homogeneous scenes by using the information of the collocated Advanced Very High Resolution Radiometer (AVHRR) pixels inside each IASI field of view and to retain the most favourable cases for the assimilation of IASI infrared radiances. Two methods to select homogeneous scenes using homogeneity criteria already proposed in the literature were adapted: the criteria derived from Martinet et al. (2013) for cloudy sky selection in the French mesoscale model AROME (Applications of Research to Operations at MEsoscale) and the criteria from Eresmaa (2014) for clear-sky selection in the global model IFS (Integrated Forecasting System). A comparison between these methods reveals considerable differences, in both the method to compute the criteria and the statistical results. From this comparison a revised method representing a kind of compromise between the different tested methods is proposed and it uses the two infrared AVHRR channels to define the homogeneity criteria in the brightness temperature space. This revised method has a positive impact on the observation minus the simulation statistics, while retaining 36 % of observations for the assimilation. It was then tested in the NWP system ARPEGE for the clear-sky assimilation. These criteria were added to the current data selection based on the McNally and Watts (2003) cloud detection scheme. It appears that the impact on analyses and forecasts is rather neutral.

Highlights

Satellite observations are currently the dominant source of information for numerical weather prediction (NWP) systems
In the Météo-France global model ARPEGE (Action de Recherche Petite Echelle Grande Echelle, Courtier et al, 1991), 70 % of used observations come from infrared hyperspectral sounders, of which IASI (Infrared Atmospheric Sounding Interferometer; Cayla, 2001) fills a large part
We found that 12 % are clear homogeneous observations, 51 % are cloudy homogeneous observations and 37 % of IASI observations are made of different SEVIRI cloud types

Summary

Introduction

Satellite observations are currently the dominant source of information for numerical weather prediction (NWP) systems Their assimilation together with in situ observations give the atmosphere analysis, which is a necessary step in the definition of the initial conditions of the forecast. In the Météo-France global model ARPEGE (Action de Recherche Petite Echelle Grande Echelle, Courtier et al, 1991), 70 % of used observations come from infrared hyperspectral sounders, of which IASI (Infrared Atmospheric Sounding Interferometer; Cayla, 2001) fills a large part. This sounder provides information about the atmospheric temperature and humidity, and through its window channels information about the land surface parameters in clear-sky and cloudy parameters can be obtained.

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Conclusion