Ooce Note Series on Global Modeling and Data Assimilation Eecient Methods to Assimilate Satellite Retrievals Based on Information Content

Two basic approaches have evolved to utilize radiance measurements (i.e., thermal radiation or scattered solar radiation) from satellite-borne instruments in data assimilation systems. The radiances (raw or cloud-corrected) may be assimilated directly or alternatively they may be pre-processed to retrieve geophysical parameters that are then assimilated. The retrieval process is often ill-posed and therefore requires the use of prior information. For example, temperature and humidity pro le retrievals using radiance measurements from nadir-viewing infrared and microwave sounders often incorporate prior information in the form of climatology or forecasts. The error characteristics of the prior information and its e ect on retrieval errors are in general di cult to model and account for in data assimilation systems. We present several methods to modify retrievals such that the prior information is removed and the errors can be de ned in a manner consistent with assumptions made in the analysis system. These methods also have the property of compressing the information content of remote radiance measurements, thereby reducing the amount of computation required by a statistical analysis system. This compression of radiance data will become increasingly important in the future as data from high-spectral-resolution instruments become available. The methods are implemented and compared in a one-dimensional assimilation system using simulated data from current and future infrared temperature pro ling instruments. On-line versions of this document are available from ftp://dao.gsfc.nasa.gov/pub/office_notes/on9606.ps.Z (postscript) ii