Models participating in the North American Multi Model Ensemble project were calibrated and combined to produce reliable precipitation probabilistic forecast over South America. Ensemble Regression method (EREG) was chosen as it is computationally affordable and uses all the information from the ensemble. Two different approaches based on EREG were applied to combine forecasts while different ways to weight the relative contribution of each model to the ensemble were used. All the consolidated forecast obtained were confronted against the simple multi-model ensemble. This work assessed the performance of the predictions initialized in November to forecast the austral summer (December–January–February) for the period 1982–2010 using different probabilistic measures. Results show that the consolidated forecasts produce more skillful forecast than the simple multi-model ensemble, although no major differences were found between the combination and weighting approaches considered. The regions that presented better results are well-known to be impacted by El Niño Southern Oscillation.

参与北美多模型集合项目的模型经过校准和组合，以产生可靠的南美洲降水概率预报。选择集成回归方法 (EREG) 是因为它在计算上负担得起并且使用来自集成的所有信息。两种不同的基于 EREG 的方法被应用于组合预测，同时使用不同的方法来衡量每个模型对集合的相对贡献。所有获得的综合预测都面临着简单的多模式集合。这项工作评估了在 11 月初始化的预测性能，以使用不同的概率度量来预测 1982 年至 2010 年期间的南方夏季（12 月至 1 月至 2 月）。结果表明，合并预测比简单的多模式集合产生更熟练的预测，尽管在所考虑的组合方法和加权方法之间没有发现重大差异。众所周知，表现出更好结果的地区受到厄尔尼诺南方涛动的影响。