Diagnosing an operational numerical model using Q-vector and potential vorticity concepts

Abstract

A quasigeostrophic (QG) diagnostic model is used to evaluate the nested grid model's (NGM) predictions for a December cyclone whose impact on northeastern Colorado was underpredicted. Synthetic soundings, generated from 12-h predicted data initialized 24 h before cyclogenesis became apparent, were submitted to the same QG diagnostic algorithms used to analyze verifying rawinsonde data. Comparisons reveal that the NGM apparently 1) transported too much potential vorticity, westerly momentum, and cold air into the lower troposphere along the axis of the jet stream; 2) moved the first of two short-wavelength jet streaks too far northeastward and with too much strength; 3) failed to predict the strength of the following jet maximum; and 4) failed to develop an apparent tropopause fold. It is established that these errors were not caused by obvious discrepancies in the model's initialization. Diagnosis of the model's subsequent initialization (12 h after its first erroneous prediction) indicates that the model did not have available crucial Mexican soundings that might have prevented it from making a similar error in predicting the position and strength of the then-intensifying cyclone. -from Authors