9.4 Development and Validation of Observing System Simulation Experiments at the NASA Global Modeling and Assimilation Office

Wednesday, 9 January 2013: 2:15 PM
Room 9C (Austin Convention Center)
Ronald M. Errico, NASA, Greenbelt, MD; and R. Yang, N. Prive, K. S. Tai, R. Todling, M. Sienkiewicz, and J. Guo

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 states of the atmosphere. 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 and 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 a weather forecast model. These observations include simulated errors of both instruments and representativeness. Since statistics of analysis and forecast errors are partially determined by these observational errors, their appropriate modeling can be crucial for validating the realism of the OSSE. That validation is performed by comparing statistics of the results of assimilating these simulated observations for one summer month compared with corresponding statistics obtained from assimilating real observations during the same time of year. The assimilation system is the one employed at the GMAO which shares the same 3–dimensional variational analysis (GSI) scheme used at the National Centers for Environmental Prediction. Here, only statistics concerning observation innovations or analysis increments 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 satellite observed radiances. The simulated observations with added observation errors are suitable for some initial OSSE applications. Validation results will be described for observation innovations, analysis increments, analysis quality, and 5 day forecast skill.

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