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《Journal of Arid Meteorology》 2015-06
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Application of Partial Least Square Regression on Precipitation Prediction During the Flood Season in Liaoning Province

ZHAO Zhongjun;LIU Shanliang;YOU Daming;WANG Xuezhong;HU Banghui;CHENG Yifan;Troop Unit 92493 of PLA;Troop Unit 61741 of PLA;Institute of Meteorology and Oceanography,PLAUST;College of Atmospheric Science,Lanzhou University;  
Based on the monthly mean temperature and precipitation at 160 weather stations in China during 1951- 2011,74 circulation indexes from National Climate Center and the monthly SST from NCEP / NCAR,combined with mean generating function( MGF),the prediction models of precipitation during the flood season in 5 stations of Liaoning Province were respectively established by using the partial least square regression( PLSR). And the effects predicted by PLS model on precipitation were tested. The result showed that the periodic factor of the prediction founded by MGF could weaken the correlation of the predictors in the statistic model to some extent. The root mean square error( RMSE) of mean precipitation during the flood season in Liaoning Province predicted by PLSR model considering the periodicity from 2002 to 2011 was reduced by 10. 0 mm. The effect predicted by PLSR model on precipitation during the flood season was much more efficient in comparison with that predicted by step wise regression( SWR) model owing to better resolve about the multi- correlation problem. The mean prediction skill score of precipitation during the flood season in 5 stations from2002 to 2011 was 72. 6%,which improved by 10. 3% than that of SWR model.
【Fund】: 公益性行业(气象)专项(GYHY201306047 GYHY201206004)资助
【CateGory Index】: P426.6;P457.6
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