Weather Forecasting and Verification
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Weather Forecasting and Verification is becoming ever more computer intensive. Numerical weather prediction systems become more accurate and detailed with each increase in computer power. Likewise the statistical methods for tailoring their forecasts have progressed from linear regression to include many facets of artificial inelegance. Thus, the role of humans in forecasting is becoming more diverse. Actual forecasters must keep ahead of advancing technology, learning to evaluate the performance of new computer products and combine their guidance to produce the most useful forecasts possible. Numerical model developers must achieve greater understanding of the atmosphere, particularly those processes happening on scales too small to be resolved in their models. And statistical meteorologists must strive to apply the latest techniques in artificial intelligence to extract the maximum information possible from numerical forecasts and forecast verifications.
Forecast Tools | Selected Publications
| Site | Region | Application |
| BUFKIT Data Site | United States | Thunderstorms and lake-effect snow |
| The Map Wall | Global | Guide to forecasting resources on the Web |
Schroeder, A.J., D.R. Stauffer, N.L. Seaman, A. Deng, A.M. Gibbs, G.K. Hunter, and G.S. Young, 2006: An automated high-resolution, rapidly relocatable meteorological nowcasting and prediction system. Mon. Wea. Rev., 134, 1237-1265. --- Abstract
Watkins, R.R., and G. S. Young, 2006: A synoptic climatology for those heavy snowfall events spanning the East Coast megalopolis: Insights from Northeast Snowstorms. Nat. Wea. Dig., 30, 45-48. --- Abstract
Sousounis, P.J., G. Mann, G.S. Young, B. Hoggatt, W. Bandini, R. Wagenmaker, 2000: Forecasting during the Lake-ICE/SNOWBANDS Field Experiment. Weather and Forecasting, 14, 955-975. --- Abstract
Young, G.S., and L. Kristensen, 1992: Boundary layer gusts for aircraft operations. Boundary-Layer Meteor., 59, 231-242. --- Abstract
Alexander, G.D., and G.S. Young, 1990: The use of quantitative surface cyclone characteristics to determine systematic departures from mean nested grid model forecast errors. National Weather Digest, 15, 6-12. --- Abstract
Vislocky, R.L., and G.S. Young, 1989: The use of perfect prog forecasts to improve model output statistics forecasts of precipitation probability. Weather and Forecasting, 4, 202-209. --- Abstract
Vislocky, R.L., and G.S. Young, 1988: Improving your weather forecasts
through a better knowledge of skill scores. National Weather Digest,
13, 15-17. --- Abstract