The authors use numerical model integral products in a third level forecast of synthetically multi-level analog forecast technology.This is one of the strongest points of this study,which also includes the re-ducing m...The authors use numerical model integral products in a third level forecast of synthetically multi-level analog forecast technology.This is one of the strongest points of this study,which also includes the re-ducing mean vacant-forecast rate method,which pos-sesses many advantages with regard to filtering the analog term.Moreover,the similitude degree between samples is assessed using a combination of meteorological elements,which works better than that described using a single element in earlier analog forecast studies.Based on these techniques,the authors apply the model output,air sounding,surface observation and weather map data from 1990 to 2002 to perform an analog experiment of the quasi-stationary front rainstorm.The most important re-sults are as follows:(1) The forecast successful index is 0.36,and was improved after the forecast model was re-vised.(2) The forecast precise rate (0.59) and the lost-forecast rate (0.33) are also better than those of other methods.(3) Based on the model output data,the syn-thetically multilevel analog forecast technology can pro-duce more accurate forecasts of a quasi-stationary front rainstorm.(4) Optimal analog elements reveal that trig-gering mechanisms are located in the lower troposphere while upper level systems are more important in main-taining the phase of the rainstorm.These variables should be first taken into account in operational forecasts of the quasi-stationary front rainstorm.(5) In addition,experi-ments reveal that the position of the key zone is mainly decided by the position of the system causing the heavy rainfall.展开更多
An analog forecast method designed for monthly and seasonal outlooks is applied to the Arctic. The analog selection process uses pattern matches based on agreement with historical data to identify past years with simi...An analog forecast method designed for monthly and seasonal outlooks is applied to the Arctic. The analog selection process uses pattern matches based on agreement with historical data to identify past years with similar distributions of sea level pressure, upper-air geopotential height, surface and upper-air temperatures, precipitation, and sea surface temperatures. The evolution of the atmosphere in the analog years is then the basis of a prediction for the target year. Users can choose the predictor domain, the predictand domain, the variable to be predicted, and the number of antecedent months on which the analog selection is based. We provide an example of a monthly forecast generated by the analog forecast tool. In comparisons with operational dynamical model forecasts over the period 2012-2019, the analog system underperforms the dynamical models in middle latitudes but generally outperforms the dynamical models in monthly forecasts of surface air temperatures in the Arctic. The improvement over the dynamical models is especially apparent in the late summer and early autumn (August-October).展开更多
基金financially supported by the National Basic Research Program of China (Grant No. 2009CB421 401)
文摘The authors use numerical model integral products in a third level forecast of synthetically multi-level analog forecast technology.This is one of the strongest points of this study,which also includes the re-ducing mean vacant-forecast rate method,which pos-sesses many advantages with regard to filtering the analog term.Moreover,the similitude degree between samples is assessed using a combination of meteorological elements,which works better than that described using a single element in earlier analog forecast studies.Based on these techniques,the authors apply the model output,air sounding,surface observation and weather map data from 1990 to 2002 to perform an analog experiment of the quasi-stationary front rainstorm.The most important re-sults are as follows:(1) The forecast successful index is 0.36,and was improved after the forecast model was re-vised.(2) The forecast precise rate (0.59) and the lost-forecast rate (0.33) are also better than those of other methods.(3) Based on the model output data,the syn-thetically multilevel analog forecast technology can pro-duce more accurate forecasts of a quasi-stationary front rainstorm.(4) Optimal analog elements reveal that trig-gering mechanisms are located in the lower troposphere while upper level systems are more important in main-taining the phase of the rainstorm.These variables should be first taken into account in operational forecasts of the quasi-stationary front rainstorm.(5) In addition,experi-ments reveal that the position of the key zone is mainly decided by the position of the system causing the heavy rainfall.
文摘An analog forecast method designed for monthly and seasonal outlooks is applied to the Arctic. The analog selection process uses pattern matches based on agreement with historical data to identify past years with similar distributions of sea level pressure, upper-air geopotential height, surface and upper-air temperatures, precipitation, and sea surface temperatures. The evolution of the atmosphere in the analog years is then the basis of a prediction for the target year. Users can choose the predictor domain, the predictand domain, the variable to be predicted, and the number of antecedent months on which the analog selection is based. We provide an example of a monthly forecast generated by the analog forecast tool. In comparisons with operational dynamical model forecasts over the period 2012-2019, the analog system underperforms the dynamical models in middle latitudes but generally outperforms the dynamical models in monthly forecasts of surface air temperatures in the Arctic. The improvement over the dynamical models is especially apparent in the late summer and early autumn (August-October).
