Predictability of Low-Level Winds by Mesoscale Meteorological Models

Abstract

Abstract This study describes the verification of model-based, low-level wind forecasts for the area of the Salt Lake valley and surrounding mountains during the 2002 Salt Lake City, Utah, Winter Olympics. Standard verification statistics (such as bias and mean absolute error) for wind direction and speed were compared for four models: the Eta, Rapid Update Cycle (RUC-2), and Global Forecast System of the National Centers for Environmental Prediction, and the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). Even though these models had horizontal grid increments that ranged over almost two orders of magnitude, the highest-resolution MM5 with a 1.33-km grid increment exhibited a forecast performance similar to that of the other models in terms of grid-average, conventional verification metrics. This is in spite of the fact that the MM5 is the only model capable of reasonably representing the complex terrain of the Salt Lake City region that exerts a strong influence on the local circulation patterns. The purpose of this study is to investigate why the standard verification measures did not better discriminate among the models and to describe alternative measures that might better represent the ability of high-horizontal-resolution models to forecast locally forced mesogamma-scale circulations. The spatial variability of the strength of the diurnal forcing was quantified by spectrally transforming the time series of wind-component data for each observation location. The amount of spectral power in the band with approximately a diurnal period varied greatly from place to place, as did the amount of power in the bands with periods longer (superdiurnal) and shorter (subdiurnal) than the diurnal. It is reasonable that the superdiurnal power is largely in the synoptic-scale motions, and thus can be reasonably predicted by all the models. In contrast, the subdiurnal power is mainly in nondiurnally forced small-scale fluctuations that are generally unpredictable with any horizontal resolution because they are unobserved in three dimensions by the observation network. A strong positive relationship is demonstrated between the strength of the local forcing at each observation location, as measured by the spectral power in the diurnal band of the wind component time series, and forecast skill, as reflected by an alternative verification metric, a measure of anomaly correlation. However, the mean-absolute error showed no relationship to the power in the diurnal band. Two other measures of comparison among the low-level wind forecasts, the direction climatology and the spatial variance, showed a positive correlation between forecast quality and horizontal resolution.