In the development of the winter weather index, weighting based on daily accumulation of snowfall, and the occurrence of freezing rain was found to best correlate with maintenance costs. Early and late season snow and ice events were found to contribute less to the maintenance costs, probably a consequence of warmer surface and subsurface temperatures at that time, so that an adjustment based on date is used in the index. Mean winter temperatures, and winds were not found to significantly correlate with winter maintenance costs.
The index can be used to determine the relative severity of winters, or months within a given winter, and may be used to evaluate the performance of individual garages. At the present time, work is ongoing to compare a neural network-derived index with the one already developed. These results will also be presented at the conference.