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Improved Weather and Seasonal Climate Forecasts from Multimodel Superensemble

机译:多模式超级集合改善了天气和季节性气候预报

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摘要

A method for improving weather and climate forecast skill has been developed. It is called a superensemble, and it arose from a study of the statistical properties of a low-order spectral model. Multiple regression was used to determine coefficients from multimodel forecasts and observations. The coefficients were then used in the superensemble technique. The superensemble was shown to outperform all model forecasts for multiseasonal, medium-range weather and hurricane forecasts. In addition, the superensemble was shown to have higher skill than forecasts based solely on ensemble averaging.
机译:已经开发了一种用于提高天气和气候预报技能的方法。它被称为超级集合,它源于对低阶光谱模型的统计特性的研究。多元回归被用来确定来自多模型预测和观察的系数。然后将这些系数用于超级合奏技术。结果表明,该超级集合优于所有模型的多季节,中程天气和飓风预报。另外,超级合奏被证明比仅基于合奏平均的预测具有更高的技能。

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