The Third Pole （TP） has diverse climate and frequent disasters and is a key area that affects global and Asian climate anomalies. The study of seasonal-interannual climate prediction in the TP area is of great scientific and guiding significance for improving regional forecasting skills and reducing the natural disaster impacts. Based on the hindcast data of BCC_CSM1.1m， we evaluated the prediction performance of 2m-air temperature （T2m） and snow depth over the TP by employing deterministic forecast verification methods and then analyzed the modulation of the Sea Surface Temperature Anomalies （SSTA）. The results indicate that BCC_CSM1.1m has useful prediction skills in the TP area for the seasonal-interannual 2m-air temperature and snow depth predictions. The prediction skill of summer T2m is generally higher than winter T2m and snow depth. The predictivity of BCC_CSM1.1m is generally weaker for a longer lead time， but there is a skill-recovery. Meanwhile， SSTA could modulate the seasonal-interannual climate prediction over the TP and ocean signals such as El Ni?o show their direct and indirect influences on the predictability.