Summer Climate Prediction Over China Based On An Ensemble Canonical Correlation Method

Using geopotential height at 500 hPa, sea level pressure, surface air temperature and temperature at 850 hPa in winter over East Asia as predictors of summer air temperature over China. The 500hPa height field in the early winter, the surface air temperature of the Eurasian continent in spring and the SST in the tropical Pacific Ocean in winter are the predictors of summer precipitation in eastern China. The summer air temperature in China and the summer precipitation in eastern China are predicted respectively. Based on the these detrended datasets during the period 1951-2009,individual forecasting models are established separately by Bamett-Preisendorfer canonical correlation analysis (BP-CCA) , and the ensemble canonical correlation (ECC) prediction based on one-year-out cross validation is used to predict the summer temperature and precipitation over China during the same period. Independent sample tests are then performed to test the actual forecasting ability of each ECC model. Besides, through the prediction test by choosing typical year, the actual ability of the model to predict extreme climate was checked. The main conclusions are as follows.(1) Analyzing the CCA mode can figure out the source of the skill for each predictor in ECC prediction. Analyzing the BP-CCA mode shows that the spatial patterns of BP-CCA can in general reflect the remote correlation characteristics between predictor and predictand. The time series of CCA modes can reflect the synchronization of their time variations.(2) In the prediction of summer air temperature and precipitation in China, both the circulation field and the thermal field can provide prediction information. Since ECC prediction collected the skill of each predictor in different areas, its skill is higher and more stable than any individual BP-CCA prediction. For single factor BP-CCA prediction, in the study of summer air temperature prediction in China, the BP-CCA prediction model established by the East Asian surface temperature in the early winter has the best performance under the test of the three prediction evaluation parameters. While in the study of summer precipitation in eastern China,for the three predictors, there wasn't a single factor BP-CCA prediction model with the best performance in the test of the three prediction evaluation parameters, which also reflects the limitations of single factor prediction and the complexity of the forecast of summer precipitation in China.(3) The BP-CCA prediction model and the ECC prediction model were independently tested. The anomaly correlation coefficient of the ECC forecast model about summer air temperature in China is 0.31, the percentage of the same anomaly sign is 69.1% and the prediction score is 82.4, indicating that the model has a practical ability to predict summer temperature in China. For the summer precipitation prediction, The anomaly correlation coefficient of the ECC forecast model is 0.20, the percentage of the same anomaly sign is 64.5% and the prediction score is 77.5, indicating that the model has a practical ability to predict summer precipitation in eastern China as well. Through the prediction test by choosing the typical year, the summer temperature and precipitation prediction model established by ECC have a certain ability to predict extreme climate. In general, the prediction skill of temperature model established by ECC method is higher than that of precipitation.