Relative impact of polar-orbiting and geostationary satellite radiances in the Aladin/France numerical weather prediction system

被引:58
作者
Montmerle, Thibaut [1 ]
Rabier, Florence [1 ]
Fischer, Claude [1 ]
机构
[1] Meteo France CNRM, F-31057 Toulouse, France
关键词
3D-Var; SEVIRI; ATOVS; radiance assimilation;
D O I
10.1002/qj.34
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
For its short-range forecasts over Western Europe, Meteo-France runs the limited-area model ALADIN operationally with four daily analyses obtained with a 3D-Var data assimilation system. This system includes, among other observation types, radiances from AMSU-A, AMSU-B, HIRS and SEVIRI radiometers. SEVIRI is on board the geostationary platform Meteosat-8 and provides continuous observations in space and in time over the region of interest at several wavelengths, while the others, which are on board polar-orbiting satellites, have poorer temporal and horizontal resolutions but a better spectral resolution than SEVIRI. Observing System Experiments (OSEs) have been performed with the operational 3D-Var to assess the impact of such satellite data on analyses and on forecasts. DFS (Degrees of Freedom for Signal) have been computed and have shown the complementarity between WV channels from the different radiometers. In the operational version of the 3D-Var, DFS values show that analyses are strongly controlled by SEVIRI data in the mid to high troposphere. This is consistent with the large number of assimilated SEVIRI radiances. HIRS and AMSU-B WV data would provide more information if SEVIRI data were not assimilated and if ATOVS data were used with a higher density. However, using ATOVS data with a higher horizontal resolution makes the analyses more dependent on these data, and it does not appear to be beneficial in this particular context, probably because of a non-optimal bias correction. In that case however, the individual impact of each pixel decreases because of the horizontal correlation lengths of the structure functions. Forecast scores and predicted precipitation patterns display the positive impact of SEVIRI data. Copyright (C) 2007 Royal Meteorological Society.
引用
收藏
页码:655 / 671
页数:17
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