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Thomas E. Rosmond


The Navy Operational Global Atmospheric Prediction System (NOGAPS) has proven itself to be competitive with any of the large forecast models run by the large operational forecast centers around the world. The navy depends on NOGAPS for an astonishingly wide range of applications, from ballistic winds in the stratosphere to air-sea fluxes to drive ocean general circulation models. Users of these applications will benefit from a better understanding of how a system such as NOGAPS is developed, what physical assumptions and compromises have been made, and what they can reasonably expect in the future as the system continues to evolve.

The discussions will be equally relevant for users of products from other large forecast centers, e.g., National Meteorological Center, European Centre for Medium-Range Weather Forecasts. There is little difference in the scientific basis of the models and the development methodologies used for their development. However, the operational priorities of each center and their computer hardware and software environments often dictate what compromises are made and how model-based research is conducted. In this paper, NOGAPS will serve as the basis for discussing these issues and the art of numerical weather prediction model development.

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Chi–Sann Liou, Jen–Her Chen, Chuen–Teyr Terng, Feng–Ju Wang, Chin–Tzu Fong, Thomas E. Rosmond, Hong–Chi Kuo, Chih–Hui Shiao, and Ming–Dean Cheng


The global forecast system (GFS), which started its operation in 1988 at the Central Weather Bureau in Taiwan, has been upgraded to incorporate better numerical methods and more complete parameterization schemes. The second-generation GFS uses multivariate optimum interpolation analysis and incremental nonlinear normal-mode initialization to initialize the forecast model. The forecast model is a global primitive equation model with a resolution of 18 sigma levels in the vertical and 79 waves of triangular truncation in the horizontal. The forecast model includes a 1.5-order eddy mixing parameterization, a gravity wave drag parameterization, a shallow convection parameterization, a relaxed version of Arakawa–Schubert cumulus parameterization, grid-scale condensation calculation, and longwave and shortwave radiative transfer calculations with consideration of fractional clouds. The performance of the second-generation GFS is significantly better than the first-generation GFS. For two 3-month periods in winter 1995/96 and summer 1996, the second-generation GFS provided forecasters with 5-day forecasts where the averaged 500-mb height anomaly correlation coefficients for the Northern Hemisphere were greater than 0.6.

Observational data available to the GFS are much less than those at other numerical weather prediction centers, especially in the Tropics and Southern Hemisphere. The GRID messages of 5° resolution, ECMWF 24-h forecast 500-mb height and 850- and 200-mb wind fields available once a day on the Global Telecommunications System are used as supplemental observations to increase the data coverage for the GFS data assimilation. The supplemental data improve the GFS performance both in the analysis and forecast.

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