SUMMARY AMSU-A and -B measurements are still not extensively used over land surfaces for atmospheric applications. Recent studies have shown that it should now be possible to take advantage of the information content of these instruments provided land emissivity and skin temperature estimates are improved. This paper reports on comparisons between three land-surface schemes using the Météo-France four-dimensional variational (4D-Var) assimilation system. Firstly, a monthly mean estimated land emissivity atlas using AMSU data is used. A second land-surface scheme based on direct emissivity calculations is developed to obtain dynamically emissivity values. The third approach is based on the first one with the addition of a dynamic skin temperature estimation based on one AMSU-A or AMSU-B window channel. The land-surface schemes described above have been implemented within the 4D-Var system and their results have been compared with those of the operational surface scheme (which uses emissivity models). All land schemes have been evaluated by examining the performances of the observation operator for sounding channels prior to the assimilation. With dynamically varying emissivities and/or skin temperatures or with averaged emissivities, the simulations are clearly improved compared with the operational model and many more data pass the quality-control check.

International audienceTo improve the assimilation of Advanced Microwave Sounding Unit-A and -B (AMSU-A and -B) observations over land, three methods, based either on an estimation of the land emissivity or the land skin temperature directly from satellite observations, have been developed. Some feasibility studies have been performed in the Me´te´o-France assimilation system in order to choose the most appropriate method for the system. This study reports on three 2-month assimilation and forecast experiments that use different methods to estimate AMSU-A and -B land emissivities together with the operational run as a control experiment. The experiments and the control have been subjected to several comparisons. The performance of the observation operator for simulating window channel brightness temperatures has been studied. The study shows considerable improvements in the statistics of the window channels' first-guess departures (bias, standard deviation). The correlations between the observations and the model's simulations have also been improved, especially over snow-covered areas. The performances of the assimilation system, in terms of cost function change, have been examined: the cost function is generally improved during the screening and remains stable during the minimization. Moreover, comparisons have been made in terms of impacts on both analyses and forecasts

The first active humidity profiling system in space is being developed by the European Space Agency (ESA) in the horizon of 2010. Data quality in terms of vertical resolution, accuracy, low bias, and vertical extent is expected to be unsurpassed. There are pressing needs for high-quality water vapor observations to fulfill societal and scientific requirements in environmental understanding and operational weather prediction. At one level, these needs arise from requirements for more reliable information about the earth's climate system (Houghton et al. 1996(Houghton et al. ,2001) and closely related needs for improved weather forecasts (Weckwerth et al. 1999;Koch et al. 1997;Bell and Hammon 1989 (GEWEX 1998a,b; WCRP 2000).Data obtained from ground-based and airborne differential absorption lidars (DIALs) have proven the ability of the DIAL technique to meet these needs in terms of good vertical resolution, high precision, and low bias (Browell and Ismail 1995;Wulfmeyer and Bosenberg 1998;Ehret et al. 1999; Bruneau et al. 2001a,b). We argue that a spaceborne DIAL in the 2008-12 time frame would be a major advance, by achieving global coverage together with the high quality offered from the active remote sensing technique (Browell et al. 1998 The objective of this paper is not to report on technical solutions, but rather to show that the WALES mission will be of substantial benefit to both NWP and climate research. It is well recognized that water vapor effects dominate the earth's climate. Water vapor's radiative properties make it the most important greenhouse gas, and it plays a direct role in other major atmospheric processes including the formation of clouds and precipitation, surface and chemical processes, and dynamics (see Fig. 1). Microphysical processes involving atmospheric aerosol and leading to the formation and development of cloud and precipitation are strongly dependent on the water vapor distribution. Atmospheric water vapor has both direct and indirect effects on the radiation budget of the atmosphere (Elliot and Gaffen 1995). Climate sensitivity to increasing C02 is primarily dependent on water vapor feedback mechanisms taking place in the middle and upper troposphere (Sinha and Harries 1995). Furthermore, atmospheric dynamics at all space scales is strongly dependent on the variability of the atmospheric humidity field. The water vapor distribution is determined by the hydrological cycle. Water vapor is much less well mixed than other greenhouse gases because of its strong links with temperature and because of the interactions between clouds, convection, and atmospheric transport, especially in the upper troposphere and lower stratosphere. Because of these characteristics, water vapor has high variability in space and time. Together with its large dynamic range, this variability represents a major challenge for its observation.The main terrestrial sources of humidity data are currently land and ship synoptic reports, buoy data, and radiosonde soundings. Space-based humidity estimates are typi...