Global soil wetness project: forecast and assimilation experiments performed at Météo-France
Projet d'humidité globale du sol : expériences d'assimilation et de prévision réalisées à Météo-France
Douville, H. ; Bazile, E. ; Caille, P. ; Giard, D. ; Noilhan, J. ; Peirone, L. ; Taillefer, F.
Année de publication
1999
Global soil moisture data of high quality and resolution are not
available by direct observation, but are useful as boundary and initial
conditions in comprehensive climate models. In the framework of the
Global Soil Wetness Project (GSWP), the ISBA land-surface scheme of
Météo-France has been forced with meteorological observations and
analyses in order to study the feasibility of producing a global soil
wetness climatology at a 1°×1° horizontal resolution between January
1987 and December 1988. A control experiment and several sensitivity
tests have been performed, suggesting that soil moisture remains one of
the most difficult climatological parameters to model and that any
computed climatology must be considered with great caution. The
prescription of the soil depth is particularly critical, showing the
relevance of the absolute value of the soil water content and the
interest for land surface schemes to include a deep layer beyond the
rooting depth. Compared to a river flow climatology, the runoff
simulated over large river basins seems to be underestimated because of
deficiencies in both the ISBA scheme and the GSWP experiment design. In
order to obtain a more reliable climatology, a global reanalysis of soil
moisture has been attempted, using a sequential optimal interpolation
technique, in which soil moisture is corrected by iterative comparison
between simulated and observed near-surface air temperature and relative
humidity. Preliminary tests have been performed for July 1987, showing
the potential of this method in idealized conditions. In practice, many
uncertainties, either in the observations, the land surface properties
or the atmospheric forcing, are liable to jeopardize the quality of the
reanalysis, suggesting the need for more consistent data within the GSWP
framework. Some outlooks are presented for improving the robustness of
the assimilation technique, which lead to encouraging results.</div>
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