Sequential assimilation of soil moisture from atmospheric low level parameters. Part II: Implementation within a mesoscale model
Assimilation séquentielle de l'humidité du sol à partir de paramètres atmosphériques de bas niveau en altitude. Part II: Implémentation dans un modèle de mésoéchelle
Bouttier, F. ; Mahfouf, J.-F. ; Noilhan, J.
Année de publication
1993
A sequential assimilation technique based upon optimum interpolation is <br>developed to initialize soil moisture in atmospheric models. Soil <br>moisture increments are linearly related to forecast errors of <br>near-surface atmospheric temperature and relative humidity. Part I has <br>shown that soil moisture can be estimated from surface characteristics <br>(vegetation coverage, soil texture). In this part, the behavior of the <br>method is examined within a three-dimensional mesoscale model. The model<br> includes a realistic land surface parameterization that relates soil <br>moisture to atmospheric variables. Results reveal that after 48-h <br>assimilations soil moisture has converged near reference values by <br>blending atmospheric quantities in the algorithm. The convergence rate <br>is almost independent of the first guess. Sensitivity studies show that <br>the observational errors modulate the efficiency of the process and that<br> results with an analytic formulation of the optimum coefficients are <br>close to those obtained with a Monte Carlo method. These conclusions are<br> of practical interest for an implementation in operational models.</div>
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