The International Soil Moisture Network: serving Earth system science for over a decade
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Engineering topics
Publications and source records attributed to Gruber, Alexander.
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The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model.
Climate Data Records (CDR) that blend multiple satellite products are invaluable for climate studies, trend analysis and risk assessments. Knowledge of any inhomogeneities in the CDR is therefore critical for making correct inferences. This work proposes a methodology to identify the spatiotemporal extent of the inhomogeneities in a 36-year, global multisatellite soil moisture CDR as the result of changing observing systems. Inhomogeneities are detected at up to 24 percent of the tested pixels with spatial extent varying with satellite changeover times. Nevertheless, the contiguous periods without inhomogeneities at changeover times are generally longer than 10 years. Although the inhomogeneities have measurable impact on the derived trends, these trends are similar to those observed in ground data and land surface reanalysis, with an average error less than 0.003 cubic meters per cubic meter per year. These results strengthen the basis of using the product for long-term studies and demonstrate the necessity of homogeneity testing of multisatellite CDRs in general.