AIR: Weather information for the smart economy

拟议的工作将推进集合天气预报的统计后处理的奖学金。创新承诺在几个关键领域：预测问题和训练数据集的有效规范，预测器选择自动化的可能性，统计模型之间选择的自动化，从给定决策问题的细节导出的质量规范的集成，定义多周期决策值计算的基础节点结构的专家系统的创建，以及用于分析气象和预测以及结果训练数据以指定每个决策节点的参数的自动算法。 整个项目的目标是开发和编码这些算法，并为系统的商业化准备一个完整的技术转让计划，拟议的工作将为天气预报直接输入自动决策系统的广泛应用奠定基础。所设想的方法将使完全概率预测的价值能够在科学的、数据驱动的方法中得到利用，以在能源、保险、旅游、交通、航空、建筑和公共安全等广泛的天气敏感部门进行风险管理。

The proposed work will advance scholarship on the statistical post-processing of ensemble weather forecasts. Innovations are promised in several key areas: efficient specification of the forecast problem and training dataset, the possibility of automating predictor selection, the automation of the choice between statistical models, the integration of quality norms derived from the particulars of a given decision problem, the creation of an expert system to define the underlying node structure of the multi-period decision value calculation, and an automated algorithm for analyzing the meteorological and predict and outcome training data to specify the parameters of each decision node. The overall project goal is to develop and code these algorithms, and to prepare a full technology transfer plan for the commercialization of the system.The proposed work will lay the basis for a wide range of applications in which weather forecasts are fed directly into automated decision systems. The approach envisioned will allow the value of fully probabilistic forecasts to be exploited in scientific, data-driven approaches to risk management across a wide array of weather-sensitive sectors, including energy, insurance, tourism, transportation, aviation, construction, and public safety.