Climate predictability on seasonal timescales over South America from the NMME models

This paper evaluates the predictability and skill of the models from the North American Multi-Model Ensemble project (NMME) in South America on seasonal timescales using analysis of variance (ANOVA). The results show that the temperature variance is dominated by the multi-model ensemble signal in the austral autumn and summer and by the inter-model biases in the austral spring and winter. The temperature predictability is higher at low latitudes, although moderate values are found in extratropical latitudes in the austral spring and summer. The predictability of precipitation is lower than that of temperature because noise dominates the variance. The highest levels of precipitation predictability are reached in tropical latitudes with large inter-seasonal variations. Southeastern South America and Patagonia present the highest predictability at midlatitudes. The NMME skill of temperature is better than that of precipitation, and it is better at low latitudes for both variables. At extratropical latitudes, the skill is moderate for temperature and low for precipitation, although precipitation reaches a local maximum in southeastern South America.

Automated summary

This paper evaluates the predictability and skill of the models from the NMME project in South America, and finds that temperature predictability is higher than precipitation predictability. The multi-model ensemble signal dominates temperature variance in autumn and summer, while inter-model biases dominate in spring and winter. The highest predictability of precipitation is found in tropical latitudes.