Validation of version one of the OSSEs at the GMAO

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Thursday, 27 January 2011: 9:30 AM
Validation of version one of the OSSEs at the GMAO
2B (Washington State Convention Center)
Ronald M. Errico, NASA, Greenbelt, MD; and R. Yang, M. E. Sienkiewicz, R. Todling, and H. C. Liu

Initial design and validation of baseline Observing System Simulation Experiments (OSSEs) at NASA's Global Modeling and Assimilation Office are described. The OSSEs mimic the procedures used to analyze global observations for specifying the state of the atmosphere at any time. As simulations, however, OSSEs are not confined to only already existing observations and they provide a perfect description of the true state being analyzed. These two properties of simulations can be exploited to improve both existing and envisioned observing systems the algorithms to analyze them.

This first version of the simulated observations is drawn from a 13-month simulation of nature produced by the European Center for Medium--Range Weather Forecasts using its weather forecast model. These observations include simulated errors of both instruments and representativeness. Validation is performed by comparing statistics of the results of assimilating these for one winter month compared with corresponding statistics obtained from assimilating real observations during an equivalent period. The assimilation system is the one employed at the GMAO which shares the same 3-dimensional variational analysis scheme used at the National Centers for Environmental Prediction. Here, only statistics concerning observation innovations or analysis increments, primarily within the troposphere, are considered for the validation.

In terms of the examined statistics, the OSSE validates remarkably well, even with some simplifications employed in this first version. Interestingly, in order to obtain this degree of success, it was found necessary to employ horizontally correlated observation errors for both atmospheric motion vectors (e.g., cloud-track winds) and radiances. The simulated observations with added observation errors are suitable for some initial OSSE applications.