ABSTRACT
Satellite data sets offer many advantages to conventional in-situ ground-based observations. Traditional in-situ ground observations have limitations for input, validation, and assimilation in models. Point data is difficult to interpret over spatial domain of models that range from 1/8 1/8 for the high resolution Land Surface Data Assimilation Schemes (LDAS) to 2 2.5 in the case of Global Climate Models. Satellite data provides continuous spatial coverage and repeat temporal coverage. The spatial and temporal coverages are dependent on the orbit and swath of the satellite, and the resolution of the sensor. The use of satellite data sets is extremely important in the context of the EOS satellites that provide data sets on a wide number of atmospheric and land surface variables. The EOS Terra satellite has been launched in December 1999 and the EOS Aqua has been launched in May 2002. Furthermore, there are a variety of satellites such as those launched by Japan (ADEOS II), Europe (ENVISAT), and India (INSAT) that will also have global coverage using different sensors but sense similar/same variables at different overpass times. Together, these satellites carry new and enhanced sensors that will provide high-resolution data sets that will be made available to the scientific community through the Goddard Data Active Archival Center (DAAC). Figure 1.1 depicts the physical variables that can be sensed by multiple satellite remote sensors.
