HR: 1144h
AN: A42C-08    [Abstracts]
TI: Use of satellite observation to evaluate cloud schemes
AU: * Chaboureau, J
EM: Jean-Pierre.Chaboureau@aero.obs-mip.fr
AF: University of Toulouse, Laboratoire d'Aerologie, OMP 14 avenue Belin, Toulouse, 31400, France
AB: Mesoscale models offer an ideal framework for performing detailed and explicit simulations of cloud. First these models are able to follow the time evolution of different moments of the cloud distributions in the context of real meteorological conditions. Second the gridmesh of a mesoscale model is of the same size than a satellite pixel facilitating a comparison without it being necessary to resort to additional assumptions on size. Here we adopt a model-to-satellite approach, in which satellite brightness temperature (BT) images are directly compared to BTs computed from predicted model fields. The approach is especially powerful in identifying discrepancies of cloud cover forecasts with BTs at 10.8 μm. The model-to-satellite approach associated with the BT difference (BTD) technique can also verify specific forecasts such as cirrus cover and convective overshoots. Recent applications of the approach to the MSG observations will be shown. In particular, the BTD technique leads us to improve the cloud scheme of the Meso-NH model by tuning a critical parameter in a cirrus parameterization. This improvement yields a better predicted diurnal cycle of upper- tropospheric humidity in the Tropics. The model-to-satellite approach is further combined with the calculation of meteorological scores for an objective and long-term evaluation of the model forecasts. These recent applications of the approach to the MSG observations and the Meso-NH forecasts will be shown in the context of AMMA, TROCCINOX, and COPS field campaigns over West Africa, Brazil, and Western Europe, respectively.
UR: http://mesonh.aero.obs- mip.fr/chaboureau/PUB
DE: 0321 Cloud/radiation interaction
DE: 3310 Clouds and cloud feedbacks
DE: 3315 Data assimilation
DE: 3333 Model calibration (1846)
DE: 3360 Remote sensing
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting