SBIR Phase II: Sub-Decadal Weather and Climate Forecast System to Mitigate Risk for Energy and Natural Resource Applications

SBIR 第二阶段：次十年天气和气候预报系统，以减轻能源和自然资源应用的风险

• 批准号: 2233387
• 负责人: Benjamin Toms
• 金额: $ 100万
• 依托单位: INTERSPHERE, INC.
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2233387&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Sub; Decadal

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is in potentially reducing the detrimental impacts of weather and climate on the United States energy and insurance markets. To help the American economy prepare further in advance for impactful weather and climate events, this project will develop a forecast system that can translate climate forecasts into likelihoods of impactful weather events. This information will be used to inform the energy and insurance markets of financial risk, particularly within the renewable energy sector where weather and climate control the amount of energy produced. Renewable energy is produced locally within the United States, which means this project will improve the nation’s energy security by informing when and where renewable energy will be most available. Conservative estimates of the technology’s potential include a $2.5 million per year benefit to the renewable energy industry, with a similar multi-million dollar impact to the more general parametric insurance market.This project will enhance a climate forecast system developed during the company's NSF SBIR Phase I award that issues climate forecasts up to a decade into the future. The enhancements include increased forecast accuracy through automated machine learning model parameter tuning, forecast post-processing, and the translation of the climate forecasts into realistic weather patterns. The technology uses machine learning to identify patterns in the land, atmosphere, and ocean that help determine how the climate system will evolve on timescales of one month to one decade. These climate forecasts will then be translated into realistic possibilities of future weather patterns on daily timescales. These daily weather patterns can then be used to inform renewable energy power production forecasts and extreme weather event risk for numerous industries, including the energy sector and the general insurance industry. A key technical benefit to the proposed forecast system is its high computational scalability, which enables the rapid creation of climate forecasts that are typically produced using supercomputers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该小企业创新研究 (SBIR) 第二阶段项目的更广泛/商业影响可能会减少天气和气候对美国能源和保险市场的影响，帮助美国经济提前为影响天气和气候的影响做好准备。该项目将开发一个预测系统，可以将气候预测转化为影响性天气事件的可能性，该信息将用于向能源和保险市场通报金融风险，特别是在天气和气候控制风险的可再生能源领域。产生的可再生能源是保守估计，该技术的潜力包括每年为可再生能源行业带来 250 万美元的收益，这意味着该项目将通过告知可再生能源何时何地最容易获得来改善国家的能源安全。该项目将增强该公司在 NSF SBIR 第一阶段奖项期间开发的气候预测系统，该系统可发布未来十年的气候预测。增强功能包括通过提高预测准确性。自动化机器该技术利用机器学习来识别陆地、大气和海洋的模式，帮助确定气候系统在时间尺度上的演变。然后，这些气候预测将转化为每日时间尺度上未来天气模式的现实可能性，然后可以利用这些每日天气模式为众多行业提供可再生能源电力生产预测和极端天气事件风险。能源行业和一般保险行业是一个关键。所提出的预报系统的技术优势在于其高计算可扩展性，这使得能够快速创建通常使用超级计算机生成的气候预报。该奖项是 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响进行评估，被认为值得支持审查标准。