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Validation of the Air Force Global Weather Center Relocatable Window Model Total Cloud Forecast
Validation of the Air Force Global Weather Center Relocatable Window Model Total Cloud Forecast Author:Edward C. Harris This is a AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING report procured by the Pentagon and made available for public release. It has been reproduced in the best form available to the Pentagon. It is not spiral-bound, but rather assembled with Velobinding in a soft, white linen cover. The Storming Media report number is A3... more »63323. The abstract provided by the Pentagon follows: Air Force Global Weather Center's (AFGWC) Relocatable Window Model (RWM) total cloud forecasts were validated using data for selected days in May, June, and July, 1996. Forecasts were generated twice daily (00 UTC and 12 UTC) to determine the RWM's ability to accurately forecast total cloud cover during the late spring and early summer. The RWM forecasts were post-processed using the Slingo cloud forecast algorithm and compared against AFGWC's operational real time nephanalysis (RTNEPH) cloud analysis model. As a minimal-skill baseline comparison to the RWM's total cloud forecast, the RTNEPH initial analysis hour was persisted and evaluated against the same RTNEPH analysis as the RWM forecasts. The results indicate RWM total cloud forecasts did not show improved skill, sharpness, accuracy or bias when compared against RTNEPH persistence through the 36-hour forecast period. The results also suggest the Slingo algorithm, as tested, is not appropriate for use in the RWM as an accurate total cloud forecast method for the late spring and early summer months. The RWM's total cloud forecast performance during the late spring and early summer over the North American Window should be improved in the short term by incorporating convective parameterization within the Slingo algorithm or replacing the Slingo algorithm with an alternative algorithm designed for more accurate and skillful total cloud forecasts.« less