Seasonal Prediction of Summer Temperature over Northeast China Using a Year-to-Year Incremental Approach

We present a model for predicting summertime surface air temperature in Northeast China (NESSAT) using a year-to-year incremental approach. The predicted value for each year's increase or decrease of NESSAT is added to the observed value within a particular year to yield the net forecast NESSAT. The seasonal forecast model for the year-to-year increments of NESSAT is constructed based on data from 1975 2007. Five predictors are used: an index for sea ice cover over the East Siberian Sea, an index for central Pacific tropical sea surface temperature, two high latitude circulation indices, as well as a North American pressure index. All predictors are available by no later than March, which allows for compilation of a seasonal forecast with a two-month lead time. The prediction model accurately captures the interannual variations of NESSAT during 1977-2007 with a correlation coefficient between the predicted and observed NESSAT of 0.87 (accounting for 76% of total variance) and a mean absolute error (MAE) of 0.3 degrees C. A cross-validation test during 1977-2008 demonstrates that the model has good predictive skill, with MAE of 0.4 degrees C and a correlation coefficient between the predicted and observed NESSAT of 0.76.