SBIR Phase I: Consumer Centric Parametric Insurance

小型企业创新研究(SBIR)第一阶段项目的更广泛影响/商业潜力是将气候风险管理工具(包括参数保险)带到消费者休闲旅行、活动和户外娱乐市场。该项目量化与背景相关的天气事件的概率，并通过一套工具提供这些分析，以帮助规划天气变异性。该项目将首次使以前无法投保的天气和气候风险能够广泛投保。这个小型企业创新研究(SBIR)第一阶段项目将为历史天气和预报数据开发高性能数据服务和应用程序编程接口(API)，以支持高级机器学习数据分析前端和精算参数天气保险平台。该数据服务将获取全球40多年来以每小时和次每小时时间分辨率和不到10公里的空间尺度记录的结构化历史天气数据，以及以类似空间分辨率进行的多种基于集合的国家天气预报。这项数据服务将使前端每天能够处理数百万个特定位置的查询和分析请求。为了实现秒级或亚秒级访问时间的技术目标，开源和专有软件将需要与领先的云提供商提供的现有云服务(主要是缓存、流和扩展/负载平衡)结合使用。该奖项反映了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审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to bring climate risk management tools, including parametric insurance, to the consumer leisure travel, events, and outdoor recreation markets. This project quantifies the probability of contextually relevant weather events and presents these analytics through a suite of tools to help plan for weather variability. The project will make previously uninsurable weather and climate risks broadly insurable for the first time.This Small Business Innovation Research (SBIR) Phase I project will develop a high-performance data service and application programming interface (API) for historical weather and forecast data to power an advanced machine learning data analytics front-end and an actuarial parametric weather insurance platform. The data service will access over 40 years of structured historical weather data recorded at hourly and sub-hourly temporal resolution and at spatial scales of less than 10 km, globally, in addition to multiple ensemble-based National Weather Prediction forecasts at similar spatial resolutions. This data service will power a front end capable of millions of location-specific queries and analysis requests per day. In order to accomplish the technical objective of second or sub-second access times, the open-source and proprietary software will need to be used in conjunction with existing cloud services provided by the leading cloud providers, principally caching, streaming, and scaling / load balancing.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.