Discriminate Analysis for Dust Storm Prediction in the Gobi and Steppe Regions in Mongolia

A discriminate analysis method for probability forecast of dust storms in Mongolia has been developed. The prediction method uses data recorded at 23 meteorological stations in the Gobi and steppe regions of Mongolia, including surface air pressure and geo-potential height at the 500-hPa level on grid points, and weather maps from 1975 to 1990. Weather elements such as air temperature, pressure, geo-potential height etc, which influence the formation of dust storms, are prepared as predictors. To select the most informative/important predictors (variables), we used a mean correlation matrix of variables together with the Mahalonobis distance, and correlation coefficients between dust storms and predictors with an orthogonalization for removing correlated predictors. The most informative predictors for dust storm prediction are intensities of surface cyclones and migratory anticyclones, passage of cold fronts, the horizontal gradients of the surface air pressure in the cold frontal zone, cyclonic circulations from the ground surface up to the 500-hPa level, the geo-potential height at 500-hPa level and its temporal changes. Selected predictors are used in discriminate analysis for formulating dust storm prediction equations. Sandstorm data have been classified into three classes, viz., strong, moderate and weak dust storms, depending on their intensities, durations and areas covered. Predictions of the probabilities of dust storm occurrence use the prediction equations for each class. The prediction is made from 12 hours to 36 hours. Verification of the probability forecasts of dust storms is also shown. The accuracy of forecasts is 72.2–79.9% with the data used for developing equations (dependent variables), in contrast to 67.1–72.0% with unrelated data for deriving equations (independent variables).