THE DOWNSCALING FORECASTING OF SEASONAL PRECIPITATION IN GUANGDONG BASED ON CLIMATE FORECAST SYSTEMS PRODUCTS

The Climate Forecast Systems （CFS） datasets provided by National Centers for Environmental Prediction （NCEP）, which cover the time from 1981 to 2008, can be used to forecast atmospheric circulation nine months ahead. Compared with the NCEP datasets, CFS datasets successfully simulate many major feat...

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Published inJournal of Tropical Meteorology Vol. 20; no. 2; pp. 143 - 153
Main Author 李春晖 林爱兰 谷德军 王婷 潘蔚娟 郑彬
Format Journal Article
LanguageEnglish
Published Guangzhou Guangzhou Institute of Tropical & Marine Meteorology 01.06.2014
Subjects
Climate change
Datasets
Forecasting
Methods
Oceanic analysis
Precipitation
Wind
East Asia
United States > US
China
South Asia
Online AccessGet full text
ISSN1006-8775

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Summary:The Climate Forecast Systems （CFS） datasets provided by National Centers for Environmental Prediction （NCEP）, which cover the time from 1981 to 2008, can be used to forecast atmospheric circulation nine months ahead. Compared with the NCEP datasets, CFS datasets successfully simulate many major features of the Asian monsoon circulation systems and exhibit reasonably high skill in simulating and predicting ENSO events. Based on the CFS forecasting results, a downscaling method of Optimal Subset Regression （OSR） and mean generational function model of multiple variables are used to forecast seasonal precipitation in Guangdong. After statistical analysis tests, sea level pressure, wind and geopotential height field are made predictors. Although the results are unstable in some individual seasons, both the OSR and multivariate mean generational function model can provide good forecasting as operational tests score more than sixty points. CFS datasets are available and updated in real time, as compared with the NCEP dataset. The downscaling forecast method based on the CFS datasets can predict three seasons of seasonal precipitation in Guangdong, enriching traditional statistical methods. However, its forecasting stability needs to be improved.
Bibliography:The Climate Forecast Systems （CFS） datasets provided by National Centers for Environmental Prediction （NCEP）, which cover the time from 1981 to 2008, can be used to forecast atmospheric circulation nine months ahead. Compared with the NCEP datasets, CFS datasets successfully simulate many major features of the Asian monsoon circulation systems and exhibit reasonably high skill in simulating and predicting ENSO events. Based on the CFS forecasting results, a downscaling method of Optimal Subset Regression （OSR） and mean generational function model of multiple variables are used to forecast seasonal precipitation in Guangdong. After statistical analysis tests, sea level pressure, wind and geopotential height field are made predictors. Although the results are unstable in some individual seasons, both the OSR and multivariate mean generational function model can provide good forecasting as operational tests score more than sixty points. CFS datasets are available and updated in real time, as compared with the NCEP dataset. The downscaling forecast method based on the CFS datasets can predict three seasons of seasonal precipitation in Guangdong, enriching traditional statistical methods. However, its forecasting stability needs to be improved.
CFS; Optimal Subset Regression; mean generational function; Guangdong; precipitation;downscaling
LI Chun-hui, LIN Ai-lan , GU De-jun WANG Ting PAN Wel-juan ZHEN Bin （1. Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510080 China; 2. Guangdong Climate and Agrometeorological Center, Guangzhou 510080 China）
44-1409/P
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ISSN:1006-8775