The China Multi-Model Ensemble Prediction System (CMME), developed by the Beijing Climate Centre, is an extensible climate prediction system that integrates forecast data from multiple domestic and international mainstream climate models. The system consists of four subsystems that provide monthly-seasonal, sub-seasonal, climate phenomena prediction and prediction verification.

The monthly and seasonal prediction subsystem includes 9 domestic and international models with an atmospheric horizontal resolution of 1°x1° and oceanic horizontal resolution of 1°x1°. It provides deterministic and probabilistic prediction products for basic climate elements such as temperature, precipitation, and sea surface temperature on a monthly and rolling seasonal basis for the next 6 months.

The sub-seasonal prediction subsystem consists of three models with a horizontal resolution of 1.5°x1.5°, capable of providing forecasts for the next 15-60 days or 3-12 "hou". It offers rolling forecast products for basic climatic elements at 5 days intervals, every half a month, and at monthly scales.

The climate phenomena prediction subsystem provides monitoring and forecast products for major climate phenomena such as ENSO, IOD (Indian Ocean Dipole), the Western Pacific Subtropical High, and MJO (Madden-Julian Oscillation) based on the monthly, seasonal and sub-seasonal multi-model ensemble data. The prediction products cover the next 6 months for oceanic and atmospheric circulation phenomena and the next 40 days for MJO.

The prediction verification subsystem offers comprehensive historical and real-time verification products for climate factors and climate phenomena prediction. For monthly and seasonal predictions, the system employs methods such as temporal correlation coefficient (TCC), root mean square error (RMSE), and mean square skill score (MSSS) to verify the accuracy of the predictions. Similarly, for sub-seasonal predictions, techniques such as temporal correlation coefficient (TCC), anomaly correlation coefficient (ACC), and mean square skill score (MSSS) are primarily utilizedto ensure the reliability of the predictions.

The CMME version 1.0 was officially operationalized in 2020, and was upgraded to the CMME version 2.0 in 2023, which has enabled real-time release of related products.Its main goal is to provide objective information for operational forecasts, comprehensive technical support for meteorological disaster prediction, and disaster prevention and reduction decision-making.