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The European Centre for Medium-range Weather Forecasts (ECMWF) brightness will use temperatures from the Soil Moisture and Ocean Salinity mission to analyze root zone soil moisture through a variational data assimilation system. The first guess is obtained from numerical weather prediction (NWP) model fields, an auxiliary database, and a land surface microwave emission model. In this paper, we present the Community Microwave Emission Model and research the first-guess errors in L-band brightness temperatures. An error propagation study is performed on errors introduced through: 1) uncertainties in the parameterizations of the radiative transfer model; 2) auxiliary geophysical quantities for the radiative transfer computations; and 3) an imperfect NWP model. It is found that the vegetation and dielectric models introduce uncertainties with a difference of up to 25 K between models. However, the biggest error in brightness temperature is likely related to the use of an auxiliary vegetation database, which results in differences of --20 to +20 K in our simulations. These potential errors are in many regions higher than the variance in brightness temperatures related to an imperfect NWP model. Index Terms--Microwave radiometry, moisture, simulation.

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz H and V polarized brightness temperature observations from the scanning multichannel microwave radiometer (SMMR) over several test sites in Illinois. Results using only nighttime data are presented at this time due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a nonlinear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness, and that vegetation optical depth for H-polarization is the same as for V-polarization. Surface temperature is derived by a procedure using high frequency V-polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and may be applied to other wavelengths. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors. Index Terms--Microwave radiometry, remote sensing, soil moisture, vegetation.