INNOVIM Awarded SBIR Grant for New Machine Learning Technique

INNOVIM Awarded SBIR Grant for New Machine Learning Technique

INNOVIM, LLC has been awarded a Small Business Innovation Research (SBIR) grant to develop a new Machine Learning technique for accurately forecasting extreme precipitation from Landfalling Atmospheric Rivers.

Atmospheric rivers transport large volumes of water vapor outside the tropics and when landfalling, produce large quantities of rain that replenish aquifers, contribute to beneficial increases in snowpack, yet can cause flooding and damage. Accurate forecasts of precipitation during landfalling atmospheric rivers are critical because they play a large role in water supply and flooding. However, the intensity, location, and duration of atmospheric rivers are poorly forecast in all currently operational numerical weather prediction models beyond forecast Day 7, resulting in a significant decision support services gap. We will employ machine learning techniques in developing a family of products that improve Earth system decision support models in general and the outlook for landfalling atmospheric rivers at 7-21 days in particular. Today’s numerical weather prediction models produce skillful forecasts accurately predicting atmospheric rivers one week in advance, with rapidly diminished skill in Week 2. There exists additional information in the observing systems’ datasets that are complementary to traditional weather forecasts and can significantly extends the accuracy and precision of the predictions—in terms of timing, location, intensity, and duration of landfalling atmospheric rivers—when these data are combined with deterministic or ensemble model predictions through the use of machine learning techniques.

According to NOAA, extreme weather cost $1.6 trillion between 1980 and 2018, while weather forecasts generate $35 billion in economic benefits to U.S. households annually. California alone suffers some $300 million a year in flood damage as a result of atmospheric river-derived precipitation. While it is difficult to precisely quantify the benefit to reservoir and emergency managers to be realized from even one additional day of skillful atmospheric river forecasts, it is significant—increased confidence in the forecasts would not only lead to increased lead time for more confident, earlier, and effective decision-making, but will drive strong commercial value.

This is another exciting opportunity for INNOVIM to use our data analytics capabilities to provide real-world solutions to issues impacting the safety and property of those in the U.S. and around the world. We are proud to be expanding these capabilities that complement the work our team has been performing at the Climate Prediction Center, NOAA, NASA and the most recent addition of the Kessel Run Data Science Services contract supporting the U.S. Air Force.