Evaluating temporal wind changes in mesoscale numerical forecasts using an object-based method

This talk documents a novel method for evaluating numerical weather prediction models by comparing the characteristics of temporal changes in simulated and observed 10-m (AGL) wind. Temporal objects, or wind events, are defined at the observation locations and at each grid point in the model domain as vector wind changes over 2 h. Changes above the uppermost quartile of the distributions in the observations and simulations are arbitrarily classified as significant, though this threshold can easily be adjusted to suit the needs of a particular application. Some analysis and interpretation of the attributes of significant changes will be shown for a 1-year collection of 1-day simulations by the MM5 over southern New Mexico.

The presenter will demonstrate how the simulated temporal shifts at each location tend to organize into spatially coherent structures, even though the events at individual locations are identified independently from one another. Such continuity suggests that displaying them in the same manner as traditional forecast fields are displayed could be useful to forecasters and allow them to monitor real-time observations for indications of such features and to mentally adjust the forecasts based on documented systematic errors in the amplitude, direction, and timing of wind events. Several examples will be shown to highlight the general applicability of this technique to any NWP system and any prognostic quantity.