AIR: Weather information for the smart economy

拟议的工作将推进集合天气预报统计后处理方面的学术研究。预计将在几个关键领域进行创新：预报问题和训练数据集的有效说明；自动选择预报员的可能性；统计模型之间选择的自动化；综合从特定决策问题的具体情况得出的质量标准；创建一个专家系统以确定多阶段决策值计算的基本节点结构；以及分析气象和预报及结果训练数据以具体说明每个决策节点的参数的自动算法。该项目的总体目标是开发和编码这些算法，并为该系统的商业化准备一个完整的技术转移计划。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。设想的方法将使完全概率预报的价值能够在科学的、数据驱动的方法中得到利用，以管理广泛的对天气敏感的部门，包括能源、保险、旅游、交通、航空、建筑和公共安全。

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.