Abstract: The Model initial error, Temporal Correlation Coefficient, and Anomaly Correlation Coefficient are investigated by using the hindcasts from the six climate modes, including BCC_CSM1.1m, ECMWF_SYSTEM5, NCEP_CFSv2, FGOALS_f, FGOALS_s2, PCCSM4. The result shows that FGOALS_s2 and ECMWF_SYSTEM5 have the maximum initial error among six models, and FGOALS_f has the minimum error. The southwestern part of evaluated area has the smaller initial error compared with other parts. For the temperature forecast in eastern Sichuan Basin, ECMWF_SYSTEM5 has the highest sensitivity to terrain changes in Southwest China, and the root mean squares of the analytical field are small. The maximum (minimum) ACCs of the ECMWF_SYSTEM5 prediction decreases (increase) over time, especially from 2016 to 2018, which may be related to the upgrading of the European Center mode. The ACCs of ECMWF _ SYSTEM5 model ( southwest and east regions ) and BCC _ CSM1.1m model ( northwest region ) are higher. The ACCs of BCC_CSM1.1m, NCEP_CFSv2, and ECMWF_SYSTEM5 are little. The reasons for this difference still need to be further analyzed. From the perspective of the horizontal distribution of the TCCs predicted by six climate model for the temperature of southwest China in one month lead, the forecast effect of each model for the eastern part is better than that of the west. Due to its particularity, the climate models have poor treatment effects. PCCSM4 has higher TCCs on the plateau area, but its forecast effect is still poor for the transitional area, with large terrain undulations, between the basin and the plateau. Judging from the regional average TCCs in 1~6 months lead, FGOALS_f has the worst forecasting effect, and it shows a single-peak change trend with the increase of the lead months, and the other models show a multi-peak change trend. It can be seen from the trend of TCCs changes with the forecast time of 1~3 months, for each model, the area with a higher (low) TCCs of one-month forecast time, its value decreases (increases) with the increases of forecast time.