Initialized Seasonal Prediction with the NCAR Models in the North American Multimodel Ensemble (NMME) Weather and Forecasting

This study investigates the seasonal prediction capabilities of three models, all developed by the National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) and implemented by the University of Miami, within the North American Multimodel Ensemble (NMME) framework. All three models, Community Climate System Model, version 3 (CCSM3), CCSM4, and Community Earth System Model, version 1 (CESM1), are initialized using the Climate Forecast System Reanalysis (CFSR) and have a common period of 1991–2018. The models’ performance in predicting key climate variables including surface temperature, precipitation, and El Niño–Southern Oscillation (ENSO) teleconnections is assessed. The models’ prediction skill is assessed using the sign test, a robust nonparametric method for comparing forecast errors. CCSM4 succeeded CCSM3 in 2014, bringing a much more accurate representation of global temperature trends and improved prediction of precipitation extremes and 2-m temperature over land. CESM1, introduced in 2023, shows further improvement relative to CCSM4 in the prediction of sea surface temperature in the tropical Pacific and precipitation extremes over land. The improvement in precipitation prediction skill is encouraging, as this field has seen little improvement over the life of the NMME. The modeled similarity to observed ENSO teleconnection patterns of 2-m temperature is somewhat less in CESM1 than in CCSM4, although precipitation teleconnection patterns are similar. CCSM4 and CESM1 show stronger surface temperature trends in the tropical Pacific and Southern Ocean than observed trends over the same period, a common problem for current state-of-the-art climate models with implications for prediction and for climate projections. Grant no. NA18OAR4310275