Abstract

A physical retrieval algorithm for the simultaneous retrieval of atmospheric temperature, water vapor and cloud liquid water as well as surface skin temperature and emissivity from microwave sounders has been developed by Moncet and Isaacs (1994, 1992). The algorithm uses a nonlinear inversion method similar to the one described by Rodgers (1976) for the inversion of the measured brightness temperatures. The primary background information is from climatology. As shown by Moncet and Isaacs (1992), climatology provides the desired inter-correlation between the various elements of the state vector. This information is used to effectively reduce the number of degree of freedom in the problem, and therefore reduce the dependence of the solution on the first-guess. Information from other sources, such as forecast models, is integrated by optimally combining it with the primary background information. Emissivity is treated by retrieving one emissivity value per channel. The degree of correlation between the emissivities in the different channels is specified through the first-guess error covariance matrix. This method offers more flexibility than the one proposed by Eyre (1990) and makes it possible to apply the algorithm to combinations of sensors with mixed viewing geometries and polarizations such as the DMSP microwave sensor suite. Cloud liquid water is treated in the same way as Eyre (1990).

© 1995 Optical Society of America