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Aurélie Bouchard
,
Florence Rabier
,
Vincent Guidard
, and
Fatima Karbou

Abstract

The Concordiasi field experiment, which is taking place in Antarctica, involves the launching of radiosoundings and stratospheric balloons. One of the main goals of this campaign is the validation of the Infrared Atmospheric Sounding Interferometer (IASI) radiance assimilation. Prior to the campaign, it was necessary to improve satellite data assimilation at high latitudes. Two types of sensors, microwave and infrared, have been considered to help with this issue. A major problem associated with microwave satellite data is the calculation of the surface emissivity. An innovative approach, based on satellite observations, improves the surface emissivity modeling over land and sea ice within the constraints of the four-dimensional variational data assimilation (4D-VAR) system. With this new calculation of emissivity, it has been possible to include many more microwave observations during the assimilation. In this study, this method has been applied to high latitudes, after some adjustments have been made to assimilate additional Advanced Microwave Sounding Unit-A/B (AMSU-A/B) data over sea ice and snow. The use of additional data from IASI and the Atmospheric Infrared Sounder (AIRS) sensors over land and sea ice has also been tested. The use of the microwave and infrared data over this polar area has modified the dynamical and thermodynamical model fields such as the snow precipitation quantity. Additional data have been found to have a positive impact on the skill of a model specially tuned for Antarctica.

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Thomas Pangaud
,
Nadia Fourrie
,
Vincent Guidard
,
Mohamed Dahoui
, and
Florence Rabier

Abstract

An approach to make use of Atmospheric Infrared Sounder (AIRS) cloud-affected infrared radiances has been developed at Météo-France in the context of the global numerical weather prediction model. The method is based on (i) the detection and the characterization of clouds by the CO2-slicing algorithm and (ii) the identification of clear–cloudy channels using the ECMWF cloud-detection scheme. Once a hypothetical cloud-affected pixel is detected by the CO2-slicing scheme, the cloud-top pressure and the effective cloud fraction are provided to the radiative transfer model simultaneously with other atmospheric variables to simulate cloud-affected radiances. Furthermore, the ECMWF scheme flags each channel of the pixel as clear or cloudy. In the current configuration of the assimilation scheme, channels affected by clouds whose cloud-top pressure ranges between 600 and 950 hPa are assimilated over sea in addition to clear channels. Results of assimilation experiments are presented. On average, 3.5% of additional pixels are assimilated over the globe but additional assimilated channels are much more numerous for mid- to high latitudes (10% of additional assimilated channels on average). Encouraging results are found in the quality of the analyses: background departures of AIRS observations are reduced, especially for surface channels, which are globally 4 times smaller, and the analysis better fits some conventional and satellite data. Global forecasts are slightly improved for the geopotential field. These improvements are significant up to the 72-h forecast range. Predictability improvements have been obtained for a case study: a low pressure system that affected the southeastern part of Italy in September 2006. The trajectory, intensity, and the whole development of the cyclogenesis are better predicted, whatever the forecast range, for this case study.

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Bruna Barbosa Silveira
,
Nadia Fourrié
,
Vincent Guidard
,
Philippe Chambon
,
Jean-François Mahfouf
,
Pierre Brousseau
,
Patrick Moll
,
Thomas August
, and
Tim Hultberg

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.

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