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Development and validation of observing‐system simulation experiments at NASA's Global Modeling and Assimilation Office
Author(s) -
Errico Ronald M.,
Yang Runhua,
Privé Nikki C.,
Tai KingSheng,
Todling Ricardo,
Sienkiewicz Meta E.,
Guo Jing
Publication year - 2012
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.2027
Subject(s) - data assimilation , meteorology , representativeness heuristic , environmental science , troposphere , numerical weather prediction , range (aeronautics) , computer science , statistics , mathematics , aerospace engineering , engineering , physics
Initial design and validation of baseline Observing System Simulation Experiments (OSSEs) at NASA's Global Modeling and Assimilation Office (GMAO) are described. The OSSEs mimic the procedures used to analyze global observations for specifying states of the atmosphere. As simulations, however, OSSEs are not only confined to already existing observations and they provide a perfect description of the true state being analyzed. These two properties of the simulations can be exploited to improve both existing and envisioned observing systems and the algorithms to analyze them. Preliminary to any applications, however, the OSSE framework must be adequately validated. 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. These observations include simulated errors of both instruments and representativeness. Since the statistics of analysis and forecast errors are partially determined by these observational errors, their appropriate modelling can be crucial for validating the realism of the OSSE. That validation is performed by comparing the statistics of the results of assimilating these simulated observations for one summer month compared with the corresponding statistics obtained from assimilating real observations during the same time of year. The assimilation system is the three‐dimensional variational analysis (GSI) scheme used at both the National Centers for Environmental Prediction and GMAO. 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 is validated remarkably well, even with some simplifications currently employed. In order to obtain this degree of success, it was necessary to employ horizontally correlated observation errors for both atmospheric motion vectors and some satellite observed radiances. The simulated observations with added observation errors appear suitable for some initial OSSE applications.