Abstract: Use of data assimilation techniques such as optimal interpolation or the Kaiman filter in global chemistry transport models (CTM) is becoming more common. However, owing to high computational requirements, it is often difficult to apply these techniques to multidimensional models containing extensive photochemical schemes. We present a sequential assimilation approach developed for use with general global chemistry transport models. It allows fast assimilation and mapping of satellite observations and provides estimates of analysis errors. The ...
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Topics: 
Meteorology
Atmospheric sciences