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

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.