International audienceThe Concordiasi project is making innovative observations of the atmosphere above Antarctica. The most important goals of the Concordiasi are as follows: 1. To enhance the accuracy of weather prediction and climate records in Antarctica through the assimilation of in situ and satellite data, with an emphasis on data provided by hyperspectral infrared sounders. The focus is on clouds, precipitation, and the mass budget of the ice sheets. The improvements in dynamical model analyses and forecasts will be used in chemical-transport models that describe the links between the polar vortex dynamics and ozone depletion, and to advance the understanding of the Earth system by examining the interactions between Antarctica and lower latitudes. 2. To improve our understanding of microphysical and dynamical processes controlling the polar ozone, by providing the first quasi-Lagrangian observations of stratospheric ozone and particles, in addition to an improved characterization of the 3D polar vortex dynamics. Techniques for assimilating these Lagrangian observations are being developed. A major Concordiasi component is a field experiment during the austral springs of 2008-10. The field activities in 2010 are based on a constellation of up to 18 long-duration stratospheric super-pressure balloons (SPBs) deployed from the McMurdo station. Six of these balloons will carry GPS receivers and in situ instruments measuring temperature, pressure, ozone, and particles. Twelve of the balloons will release drop-sondes on demand for measuring atmospheric parameters. Lastly, radiosounding measurements are collected at various sites, including the Concordia station

This work is in direct line with the Concordiasi international project. It aims to better constrain atmospheric analyses by improving the assimilation of low-level Advanced Microwave Sounding Unit (AMSU)-A and AMSU-B microwave observations over Antarctica. So far, a very small amount of available AMSU observations is effectively assimilated over Antarctica. To assimilate more observations, different issues have to be dealt with. In this work, the surface emissivity issue over Antarctica is examined. In a first step, a thorough review of the use of a specular assumption to calculate emissivity from AMSU-A measurements has been undertaken. The effect of five different assumptions about the surface on retrieved AMSU emissivities has then been evaluated using a one-year database: specular, Lambertian, and three intermediate assumptions. Simulations of brightness temperatures at AMSU sounding frequencies have been produced using a radiative transfer model. The emissivities obtained using the five assumptions have been found very useful in improving these simulations. The most successful schemes are found to be the Lambertian scheme during the winter season and a specular or an intermediate scheme (50% specular, 50% Lambertian) during Antarctica's short summer.

[1] The aim of this work is to estimate the land surface temperature from satellite observations in order to improve the assimilation of surface-sensitive infrared observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). To date, only a few SEVIRI observations are assimilated over land in limited area models; this is due to the still inappropriate description of the land surface in these systems (in both emissivity and surface temperature). In this paper, we demonstrate that the use of land emissivity climatologies at infrared wavelengths together with land surface temperature (LST) retrievals improve the assimilation of SEVIRI radiances against this operational configuration. Emissivity climatologies from the EUMETSAT Land Surface Analysis-Satellite Application Facilities (Land-SAF) were used, and LSTs were retrieved using one SEVIRI window channel and the radiative transfer equation. Retrieved LSTs were evaluated against independent observations/products. Some differences, due to instrumental specifications, were found when comparing SEVIRI and MODIS LSTs, but a good agreement was found between retrieved LSTs and the Land-SAF surface temperature product. The comparison of SEVIRI LSTs and LST analyses from ALADIN/France have pointed out warm (cold) biases during daytime (nighttime), which may be explained by an overall underestimation of the diurnal cycle by the model. The emissivity atlas combined with different LST retrievals were used to simulate SEVIRI radiances using the RTTOV radiative transfer model. A comparison was made between SEVIRI radiance simulations and observations. A significant improvement of the forward model statistics was noticed as well as an increase in the amount of data that could be potentially assimilated in ALADIN/France, compared to the operational setup. These developments were then tested in a context of data assimilation, thus enabling the use of more SEVIRI data over land. Two assimilation experiments were run over a 3 month period during summer 2009, one of which is representative of the operational model while the other differs by the assimilation of more SEVIRI data over land through a better representation of the emissivity and surface temperature. We show that the forecast impact is generally neutral to positive. In particular, SEVIRI data point to positive impact over southern Europe. SEVIRI data are also shown to improve the quality of analyses, particularly those of total column water vapor, and this is substantiated through comparisons with independent GPS measurements.Citation: Guedj, S., F. Karbou, and F. Rabier (2011), Land surface temperature estimation to improve the assimilation of SEVIRI radiances over land,