Soil model parameter estimation with ensemble data assimilation

A parameter estimation problem in context of ensemble data assimilation is addressed. In an example using a one-point soil temperature model, the parameters corresponding to the emissivity and to the effective depth between the surface and the lowest atmospheric model level are estimated together with the initial conditions for temperature. The nonlinear synthetic observations representing various fluxes are assimilated using the Maximum Likelihood Ensemble Filter (MLEF). The results indicate a benefit of simultaneous assimilation of initial conditions and parameters. The estimated uncertainties are in general agreement with actual uncertainties. Copyright (C) 2009 Royal Meteorological Society