The future observing system of the global atmosphere which has been contemplated for the Global Atmospheric Research Program (GARP) is a combination of various observing subsystems including satellites, constant-level balloons, automatic ocean buoys, etc., as well as conventional upper-air and surface networks. All observing subsystems are neither perfect nor ideal. Numerical experiments (with global circulation models) are needed to evaluate the subsystems in terms of the accuracy, density, and frequency of observations. They are called Observing Systems Simulation Experiments (OSSE).

The purpose of this report is to describe the present activities in OSSE. Most useful up-to-date information was obtained from the oral presentation of papers at the International Symposium on Four-Dimensional Data Assimilation, Princeton, N. J., 19–22 April 1971.

Since a global circulation model is used as an integrator and analyzer of observed data in three-dimensional space and time taken from various observing subsystems, the question of error growth of the prediction model in relation to the accuracy of observation is discussed as the predictability experiment.

Another important property of the model atmosphere is the ability to adjust the model's variables for forced prescription of incomplete observed data. This adjustment property is used to assimilate observed data in four dimensions. The method of direct substitution is used to determine the basic data requirements for observation of wind, temperature, and surface pressure.

Various methods of four-dimensional data assimilation are reviewed for the purpose of optimum design for OSSE. Finally, questions concerning the reference level information are reviewed and results of some numerical experiments conducted at the National Center for Atmospheric Research are presented.

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Footnotes

1 This report is prepared at the request of the National Science Foundation for the Federal Committee for Meteorological Services and Supporting Research.

2 The National Center for Atmospheric Research is sponsored by the National Science Foundation.