Improved weather and seasonal climate forecasts from multimodel superensemble
Improved weather and seasonal climate forecasts from multimodel superensemble
复制标题
DOI：
10.1126/science.285.5433.1548
复制
发表时间：
1999-09-03
期刊：
影响因子：
56.9
通讯作者：
Surendran, S
中科院分区：
文献类型：
--
作者：
Krishnamurti, TN;Kishtawal, CM;Surendran, S
提出了一种提高天气气候预报水平的方法。它被称为超光谱，它起源于对低阶谱模型的统计特性的研究。多元回归用于确定多模式预测和观测的系数。然后将这些系数用于超辐射技术。超级天气预报在多季节、中期天气和飓风预报方面优于所有模式的预报。此外，superenergies被证明有更高的技能，比预测的基础上合奏平均。
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.