Sensitivity Investigation and Related Review of Some Factors Critical to Satellite Data Assimilation in the Land Surface Modeling Context Through LIS

Simulations conducted through the NASA GSFC (National Aeronautics and Space Administration, Goddard Space Flight Center) software framework LIS (Land Information System) with a few variations on the AFWA (Air Force Weather Agency; now the 557th Weather Squadron) AGRMET (Agricultural Meteorology) approach are compared and evaluated versus in situ measurements and sample remotely sensed soil moisture data. In particular, forcing precipitation data sets were changed and land surface model (LSM) layer thickness was modified toward addressing subtleties concerning satellite based data assimilation (DA) to do with retrieval depth and precipitation field characteristics. This exercise was conducted toward honing LSM and DA approaches. A review of the subtleties and considerations important to this context from the literature and recent experiences, as well results from statistical evaluations of factors that might influence our results from forcing to parameterization and resolution considerations, is presented and implications are discussed.