Abstract
Independent test results of four different weather forecast models [climatological, persistence, analogue, and regional mesoscale weather simulation (MM5) model] have been compared for four past winters (winter 2003–2004 to winter 2006–2007) for qualitative weather (snow day/no snow day) and quantitative categorical snowfall prediction at six different areas in northwest Himalaya (NW-Himalaya) in India. Weather forecast guidance provided by the MM5 model at 10 km resolution was taken for the study. Test results of MM5 and the analogue model were compared for a limited number of days (with irregular gaps) due to lack of availability of MM5 weather forecast guidance for complete winter periods. Forecasts based on the persistence, climatological, and analogue models were compared for day 1 predictions only. Performance of the analogue model for qualitative weather prediction was found to be comparable to that of the MM5 model for day 1 prediction. However, for day 2 and day 3, performance of the MM5 model was found to be marginally better than that of the analogue model. Marginal difference in overall accuracy of the analogue and MM5 models was found for quantitative categorical snowfall prediction for day 3. The quantitative categorical snowfall forecast error of the MM5 model was found to be greater than that for the analogue model for all three days. Comparative study of the performance of the climatological, persistence, and analogue models showed that the analogue model performs better than the persistence and climatological models for day 1 predictions. The results of this study suggest that the analogue model shows some capability for weather prediction and, along with the MM5 model, could be a useful tool for weather forecasters. Comparative study of the performance of the MM5 model at high resolution (about 2–3 km) and the analogue model for complete winter period may provide some interesting and fruitful results.
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