All-sky satellite observations are difficult to assimilate for many reasons, not the least of which is that there are many uncertainties in the forward calculations. Furthermore, different frequencies are not uncorrelated from one another, and there are far less independent pieces of information than the number of channels. In such a situation, it is most advantageous to take a statistical approach. We have developed one such approach to find the maximally certain pieces of information based on both model simulations and empirical match-ups. We also use advanced deconvolution techniques to process the brightness temperatures before assimilating. We show that our end-to-end methodology for these observations has the potential to improving hurricane forecasting using the case of Hurricane Earl.
*email: jeffsteward@gmail.com
*Preference: Poster