Abstract

The performance of the Aviation Run (AVN) of the National Meteorological Center's (NMC) Global Spectral Model (GSM) in predicting surface cyclones was examined during the autumn of 1990 through the winter of 1992, a period during which the resolution of the model was increased with the implementation of the triangular truncation 126 (T126) GSM, and the GSM analysis scheme was changed. The results indicate that the finer resolution T126 GSM produces stronger and deeper cyclones than the old T80 GSM. These results also revealed that the errors in AVN position forecasts of surface cyclones were smaller than those found in the NMC Nested Grid Model (NGM). The geographical distribution of the pressure errors were similar to those found in the NGM over eastern North America and the adjacent western Atlantic Ocean. Negative pressure errors, indicative of overdeepening of surface cyclones, dominated the mountainous regions of western North America. Positive pressure errors, indicative of underdeepening of surface cyclones, dominated most of the western Atlantic. The AVN tended to underpredict the 1000-500-mb thickness over surface cyclones, especially during the first 36 h of the forecast cycle. This cold bias decreased with forecast length and in the T80 version of the AVN became a warm bias at the later forecast periods during several months. The skill in the AVN, measured by examining the sign of the forecast and observed 12-h pressure changes, the number of nonobserved and nonforecast cyclones, and skill indices revealed that the AVN is superior to the NGM in predicting the development and life cycle of surface cyclones. The AVN is able to forecast the sign of the 12-h pressure change greater than 80% of the time for the first 36 h of the forecast cycle and 74% of the time at 72 h. The results indicate that the T126 AVN performs at a skill comparable to the skill of the 48 h NGM cyclone forecasts. These results imply that the T126 AVN forecasts are accurate enough to provide guidance for basic weather forecasts to three days as has been done for the two-day forecasts for the past 25–30 years.

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