Retrieval Algorithms for Atmospheric Data Assimilation

We propose to develop algorithms which can be used to assimilate separate satellite data sets of important geophysical parameters into global, gridded data sets. The data assimilation program will be cast as a retrieval problem in which the true, instrument independent global distribution is retrieved from the combined satellite data set. This problem will be solved using the method of optimal estimation. The feasibility of the approach will be tested by applying the algorithm to synthetic data sets consisting of simulated ozone measurements from several instruments. The initial simulations will use a combination of solar occultation instruments in different orbits, to imitate the OOAM/POAM III data set. Errors in the resulting retrievals will be quantified and studied as a function of altitude, latitude and longitude. The software package developed to implement the algorithm will be highly modular and generic, allowing for the algorithms to be modified for application to more complicated data sets in future work.