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Abstract
Three methods of objectively forecasting maximum temperature using multiple-stepwise screening are described and compared. The first method is the traditional “perfect prog” approach whereby a historical series of upper air predictors are screened against maximum temperature to establish a prediction equation. The second method employs a stratification of the historical data on the basis of mean sea level pressure gradient analogues prior to the regression step. A new prediction equation is required for each forecast. The third method is similar to the second except that random stratification is used instead of analogue stratification.
A comparison of the accuracy of the three methods when tested on independent data indicates that the best forecasts are obtained when analogue stratification is used. Application of the analogue stratification method to “model output statistics” forecasts and the statistical correction of prognoses is discussed.
Abstract
Three methods of objectively forecasting maximum temperature using multiple-stepwise screening are described and compared. The first method is the traditional “perfect prog” approach whereby a historical series of upper air predictors are screened against maximum temperature to establish a prediction equation. The second method employs a stratification of the historical data on the basis of mean sea level pressure gradient analogues prior to the regression step. A new prediction equation is required for each forecast. The third method is similar to the second except that random stratification is used instead of analogue stratification.
A comparison of the accuracy of the three methods when tested on independent data indicates that the best forecasts are obtained when analogue stratification is used. Application of the analogue stratification method to “model output statistics” forecasts and the statistical correction of prognoses is discussed.
Abstract
Model output statistics (MOS) forecasts of daily temperature maxima and minima are developed for seven Australian cities. The developmental data and method of derivation of the MOS equations are described and the equations briefly compared to those employed in the United States. The MOS equations are applied to four midseason months of independent data and the resulting forecasts are compared to the official forecasts. It is shown that the MOS forecasts of daily maxima are slightly worse than the official forecasts and are very poor compared to the official maximum forecasts at Sydney, Melbourne and Adelaide in midsummer. In contrast, the MOS minimum temperature forecasts appear to be more accurate than the official forecasts.
Abstract
Model output statistics (MOS) forecasts of daily temperature maxima and minima are developed for seven Australian cities. The developmental data and method of derivation of the MOS equations are described and the equations briefly compared to those employed in the United States. The MOS equations are applied to four midseason months of independent data and the resulting forecasts are compared to the official forecasts. It is shown that the MOS forecasts of daily maxima are slightly worse than the official forecasts and are very poor compared to the official maximum forecasts at Sydney, Melbourne and Adelaide in midsummer. In contrast, the MOS minimum temperature forecasts appear to be more accurate than the official forecasts.
Abstract
The Model output Statistics (MOS) technique has been used to produce forecasts of both the probability of precipitation and the rain amount for seven major Australian cities in subtropical and middle latitudes. Single station equations were generated using data from the current objective analysis, together with some surface observations for the same time, and a 24 h prognosis based on that analysis, to predict the rainfall in the 24 h beyond the prognosis validity time.
In order to increase the usefulness and acceptability of the MOS predictions, transformations were applied that reduced the biases of the final forecasts throughout the forecast ranges. The skid with which large rainfall totals were predicted was particularly enhanced in this manner the MOS forecasts showed much greater skill in the prediction of large totals than was achieved by either the operational or persistence forecasts, while predicting small totals with comparable proficiency.
The MOS probability forecasts were better able to predict rainfall occurrence than were the quantitative MOS forecasts, and additionally were superior in this regard to both subjective forecasts produced operationally and predictions based on persistence. The overall skill of the quantitative precipitation forecasts was further enhanced by using the probability estimates to provide a categorical prediction of rain occurrence such that a rain amount was only forecast if the predicted probability of precipitation exceeded 50%.
Routine issuance of the MOS guidance to the operational forecasters commenced in January 1984.
Abstract
The Model output Statistics (MOS) technique has been used to produce forecasts of both the probability of precipitation and the rain amount for seven major Australian cities in subtropical and middle latitudes. Single station equations were generated using data from the current objective analysis, together with some surface observations for the same time, and a 24 h prognosis based on that analysis, to predict the rainfall in the 24 h beyond the prognosis validity time.
In order to increase the usefulness and acceptability of the MOS predictions, transformations were applied that reduced the biases of the final forecasts throughout the forecast ranges. The skid with which large rainfall totals were predicted was particularly enhanced in this manner the MOS forecasts showed much greater skill in the prediction of large totals than was achieved by either the operational or persistence forecasts, while predicting small totals with comparable proficiency.
The MOS probability forecasts were better able to predict rainfall occurrence than were the quantitative MOS forecasts, and additionally were superior in this regard to both subjective forecasts produced operationally and predictions based on persistence. The overall skill of the quantitative precipitation forecasts was further enhanced by using the probability estimates to provide a categorical prediction of rain occurrence such that a rain amount was only forecast if the predicted probability of precipitation exceeded 50%.
Routine issuance of the MOS guidance to the operational forecasters commenced in January 1984.
