DIAGNOSING AN OPERATIONAL NUMERICAL-MODEL USING Q-VECTOR AND POTENTIAL VORTICITY CONCEPTS

A quasigeostrophic (QG) diagnostic model is used to evaluate the neste d grid model's (NGM) predictions for a December cyclone whose impact o n northeastern Colorado was underpredicted. Although the NGM predicted deepening of the associated 500-mb low, the model was 12 h slow in th e onset of deepening and moved the storm too far east too quickly. Syn thetic soundings, generated from 12-h predicted data initialized 24 h before cyclogenesis became apparent, were submitted to the same QG dia gnostic algorithms used to analyze verifying rawinsonde data. Comparis ons reveal that the NGM apparently 1) transported too much potential v orticity, westerly momentum, and cold air into the lower troposphere a long the axis of the jet stream; 2) moved the first of two short-wavel ength jet streaks too far northeastward and with too much strength; 3) failed to predict the strength of the following jet maximum; and 4) f ailed to develop an apparent tropopause fold. it is established that t hese errors were not caused by obvious discrepancies in the model's in itialization. Through inference, the errors could have been caused by rapid growth of subtle, undetected initialization errors or by the mod el's inadequate parameterization of some physical process-perhaps of t urbulent dissipation over mountainous terrain. Diagnosis of the model' s subsequent initialization (12 h after its first erroneous prediction ) indicates that the model did not have available crucial Mexican soun dings that might have prevented it from making a similar error in pred icting the position and strength of the then-intensifying cyclone. The diagnostic results could have alerted forecasters not only to the pre sence of the complex jet stream but also to the extent and intensity o f its associated tropopause fold. Furthermore, QG diagnostics can aler t forecasters to model errors that are not made obvious by conventiona l model comparisons.