A stochastic cloud model for cloud and ozone retrievals from UV measurements. (November 2016) - Efremenko, Dmitry S.; Schüssler, Olena; Doicu, Adrian; Loyola, Diego
Abstract: The new generation of satellite instruments provides measurements in and around the Oxygen A-band on a global basis and with a relatively high spatial resolution. These data are commonly used for the determination of cloud properties. A stochastic model and radiative transfer model, previously developed by the authors, is used as the forward model component in retrievals of cloud parameters and ozone total and partial columns. The cloud retrieval algorithm combines local and global optimization routines, and yields a retrieval accuracy of about 1% and a fast computational time. Retrieved parameters are the cloud optical thickness and the cloud-top height. It was found that the use of the independent pixel approximation instead of the stochastic cloud model leads to large errors in the retrieved cloud parameters, as well as, in the retrieved ozone height resolved partial columns. The latter can be reduced by using the stochastic cloud model to compute the optimal value of the regularization parameter in the framework of Tikhonov regularization. Abstract : Highlights: A stochastic radiative transfer model for retrieving clouds/ozone is designed. Errors of independent pixel approximation (IPA) for O3 total column are small. The error of IPA for ozone profile retrieval may become large. The use of stochastic model reduces the error of ozone profile retrieval.