Prediction of Intermonth Modes of Winter Air Temperature over China

Abstract

Abstract The features and causes of the leading intermonth modes of winter surface air temperature anomalies (SATA) over China are investigated, and associated prediction models are developed. The first three intermonth modes of winter SATA over China are obtained by extended empirical orthogonal function (i.e., EEOF1–3) analysis. The results show that EEOF1 represents consistent variations in the whole winter, with a variance contribution of 32.3%, whereas EEOF2 and EEOF3 show spatiotemporally inconsistent changes, and their variance contributions are 16.9% and 12.5%, respectively. EEOF2 has out-of-phase variations between December and January–February, and EEOF3 exhibits a temporal warm–cold alternating pattern, with spatially reversing changes over northwestern and southern China. However, the Climate Forecast System, version 2 (CFSv2) presents a limited prediction skill for winter SATA over China and their intermonth modes. Further investigations indicate that the September sea ice over the Barents–Laptev Seas, the November snow cover over western Europe and East Asia, and the November northern Atlantic sea surface temperature can be, respectively, adopted to develop prediction schemes for the consistent mode (EEOF1 scheme) and two inconsistent modes (EEOF2 and EEOF3 schemes) based on specific mechanisms. These schemes show effective performances in predicting both individual modes and the reconstruction field of SATA over China. The temporal correlation coefficients (TCCs) between cross-validation results and observations are 0.48, 0.51, and 0.31 for the EEOF1–3 modes, respectively (the 90% confidence level is 0.27). For the reconstruction field, the TCCs are 0.40, 0.27, and 0.45 in December, January, and February, respectively, which are much higher than those of the CFSv2 outputs (0.23, −0.16, and −0.09).