Future Work and Challenges:
§Ensemble Kalman Filter will be implemented in LDAS to further compare the relative advantages of EnKF and EKF.
§Other land surface models (Catchment, CLM, NOAH, VIC) will be used with Kalman Filters for assimilating land
data products from satellite observations.
§The most efficient and reliable data assimilation algorithm and land surface model will be selected for operational procedures of AMSR-E land product validation.
§Soil moisture assimilation results will also be analyzed
with model output
of fluxes.
§How model error variance and observation error variance can
be known a priori?
§How to implement the assimilation algorithm to the global scale?
§How the spatial heteorogeneity of land surafce state variables can be considered or used in the data assimilation and/or validation?