Remotely sensed observations are inherently incomplete, and some method must be used to obtain a complete and global state of the atmosphere. Data assimilation is a method that combines an atmospheric model with observations in a dynamically and chemically coherent state of the atmosphere. The degree to which measurements contradicts model-predicted fields can also be an indicator of problems with the instrument, the measurement technique, the inversion, or of the model. The research presented here aims towards obtaining the chemical state of the atmosphere with an emphasis on global atmospheric pollution in the troposphere using observations from MOPITT.
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