| description abstract | An objective classification model was developed that can automatically predict synoptic weather types in southern California. Stepwise discriminant analysis was used to match the National Meteorological Center's Limited-area Fine Mesh (LFM) Model Output Statistics to subjectively classified weather types or patterns. The five classified weather types range from hot, dry, windy Santa Ana days to cool, rainy, cloudy days caused by a synoptic low. Discriminant function equations were developed for predicting each weather type 12 and 24 h in advance by screening 80 potential predictors consisting of forecasts at 500, 700 and 850 mb from the LFM model. Model output at nine grid points was used because that information adequately describes the meteorological patterns over southern California. Using independent LFM model forecasts valid 12 and 24 h in advance, the objective classification model predicted the probability of the days being in each of the five weather types, then the type with the highest probability was selected. Eighty-eight of 107 24 h periods (days) centered 12 h in advance (81%) were correctly predicted. Of 99 independent days centered 24 h in advance, 71 (72%) were correctly predicted. Hourly means and standard deviations of surface temperature and dew points at eight research sites in the San Bernardino Mountains computed by month for the five weather types had distinct diurnal variations corresponding with weather types. Summarizing hourly temperatures in August at the eight sites by weather type reduced their standard deviation by almost one-half. Measurements of mean daily maximum ozone at a San Bernardino Mountain crest site, where chronic ozone injury to ponderosa pine has occurred, showed significant differences between the weather types. The mean surface wind, temperature and dew-point patterns at 2100 GMT over southern California for type 1 (Santa Ana) days show strong offshore winds, high temperatures and very low dew points, whereas type 5 (synoptic low) days show strong onshore winds, low temperatures and high dew points. | |
