EFFICIENT METHODS TO ASSIMILATE REMOTELY-SENSED DATA-BASED ON INFORMATION-CONTENT

Two basic approaches have evolved to utilize measurements of radiance (i.e. thermal or scattered solar radiation) by satellite-borne instrum ents in data assimilation systems: radiances (raw or cloud-corrected) may be assimilated directly, or they may be pre-processed to retrieve geophysical parameters for subsequent assimilation. The retrieval proc ess is often ill-posed, and therefore requires the use of prior inform ation to constrain the solution. For example, temperature and humidity profiles retrieved using radiances from nadir-viewing infrared and mi crowave sounders often incorporate prior information in the form of cl imatology or forecasts. The use of prior information presents difficul ties when assimilating retrievals. Here we present methods to remove p rior information from retrievals in order to achieve a more consistent assimilation of the data. In addition, these methods can be used as a data compression device, which can reduce the amount of computation r equired by some analysis systems compared with radiance assimilation. The methods are implemented and compared in a one-dimensional assimila tion system using simulated data from current and future infrared-temp erature profiling instruments.