Weather and Climate Superensemble Forecasts from Multimodels

首席研究员将进一步探索集合/超集合方法，使用一系列不同模式的预报实验进行数值天气预报。一个superenergy方法执行集合平均后，个别成员模型的偏差被删除，从而提高了预测的技能以上的个别模型的预测。PI将通过使用一套代理模型来扩展这种方法，该代理模型被称为合成超级组件，以解决季节性气候异常问题。将在飓风登陆、路径和强度以及暴雨预报和数值天气预报方面探索合成超强天气的各种变体。研究生将参与这项研究。

The principal investigator will further explore the ensemble/superensemble approach for numerical weather prediction using forecast experiments from a range of different models. A superensemble approach performs an ensemble average after the bias of the individual member models is removed, thereby increasing the skill of the prediction above that of individual model forecasts. The PI will extend this approach by using a suite of proxy models, which is called the synthetic superensemble component, to address the issue of seasonal climate anomalies. Variants of the synthetic superensemble will be explored with regard to hurricane landfall, track and intensity, as well as heavy rain forecasts and numerical weather prediction. Graduate students will participate in this research.