A statistical prediction method for an East Asian winter monsoon index reflecting winter temperature changes over the Chinese mainland
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Abstract
Using the monthly temperature data from 160 stations of China, the National Centers for Environmental Prediction (NCEP) reanalysis data, the NOAA-Cooperative Institute for Research in Environmental Sciences(CIRES) 20th Reanalysis data, etc,. and the statistical analysis methods, the abilities to reflect the pattern of the consistent variability in winter temperatures over the mainland of eastern China are assessed for a variety of East Asian winter monsoon(EAWM) indices, respectivcly. The precursors affecting the EAWM intensity and associated influencing processes are investigated. According to these precursors, a prediction model is established to predict the FAWM index. The research results show that among these indices, the FAWM index defined by Zhu in 2008 can reflect well anomalous winter temperatures in most parts of eastern China during the two periods before 1981 and after 1981;the previous autumn(September-October) sea surface temperature(SST) in the mid-latitude North Pacific region to the west of the North American continent (35°-50°N, 145°-130° W), the previous autumn sea ice concentration over the Kara Sea region of the Arctic Uccan(75°-82°N, 65°-85° E), and the previous autumn high-level (300-200 hPa) air temperature over the mid-latitude region of the East Asia (30°-50°N, 80°-140°E) have a good persistence with anomalous signals persisting from the previous autumn to winter, and therefore may affect the strength of the EAWM; based on these three preceding factors, a statistical prediction model for the EAWM is established. The evaluation results show that the model has a strong predictive ability, and can be used to predict the EAWM intensity and its corresponding winter temperatures over eastern China.
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