Project Grant 2026025

This federal Project Grant award of $443,674 from the National Science Foundation's Geosciences Program (CFDA 47.050) will support research to develop advanced artificial intelligence (AI) models for predicting the initiation and evolution of thunderstorms. The project aims to enable significant breakthroughs in understanding convection initiation dynamics and improving the predictability of hazardous weather events like heavy rainfall, strong winds, hail, and tornadoes. Key objectives...

This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) Project Grant award in the amount of $274,912 provides funding to Salient Predictions Inc., a for-profit small business, to develop a machine learning model that can forecast extreme heat or cold events up to one month in advance. The goal is to create a predictive model that combines weather forecasting technologies with machine learning to deliver more accurate sub-seasonal temperature forecasts,...

This Project Grant award of $529,722.00 from the National Science Foundation's Geosciences Program (CFDA 47.050) will support research to develop advanced artificial intelligence models to predict the formation and evolution of thunderstorms. The project aims to create a prognostic, diagnostic, and generative deep learning nowcasting tool for convection initiation that can quantify the predictability and uncertainty of these predictions. The research will also seek to discover the physical and...

Prescient Weather LTD received a $398,208 Project Grant award from the National Oceanic and Atmospheric Administration under the Small Business Innovation Research Program to enhance subseasonal and seasonal forecasts. The two-year award running from February 2021 to January 2023 will support Prescient Weather's efforts to develop improved forecasting tools and models to better serve business and industry needs. The Small Business Innovation Research Program seeks to stimulate technological...

The National Science Foundation awarded a $275,000 Small Business Innovation Research Phase I Project Grant to Applied Research Team Inc. of Denver, Colorado under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084). The grant will support the development of machine learning algorithms to improve snowpack depth and water content retrieval from C-band and X-band radar data. Accurate snowpack information is critical for water management in the Western U.S., but current retrieval...

This Project Grant award from the National Science Foundation (NSF) Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support the development of machine learning methods for estimating the risk of adverse weather and climate events, such as rapid changes in solar power generation and flooding. The University of Hawaii at Manoa, as the prime contractor, will apply advances in generative artificial intelligence...

This federal Project Grant award of $1,298,986 from the National Oceanic and Atmospheric Administration (NOAA) Small Business Innovation Research (SBIR) Program supports the development of a high-impact innovation called XTREMECAST. XTREMECAST integrates global ensemble weather forecasts with an AI-driven post-processing model to provide skillful probabilistic forecasts of compound extreme weather events at extended lead times. The proposed solution aims to improve electric utility companies'...

This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program provides $449,321 to the University of California, Santa Cruz (UCSC) to develop AI-based atmospheric emulators that can reliably model climate change and extreme weather events. The project aims to create physically-consistent and numerically stable deep learning models to simulate atmospheric dynamics at a fraction of the computational cost of...

Iseechange Inc. received a $304,018 Small Business Innovation Research (SBIR) Phase I Project Grant from the National Science Foundation's (NSF) Directorate for Technology, Innovation, and Partnerships (CFDA 47.084) awarded on July 15, 2026, with completion targeted for December 31, 2026. The project delivers a deep learning framework and associated artificial intelligence (AI) computer vision technology that automatically converts unstructured smartphone photographs and videos of flood events...

This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) Project Grant, awarded on February 15, 2024 for $275,000.00, supports the development of a weather forecasting and climate prediction tool for subseasonal forecasting, extreme weather events, and long-term climatological changes. The project aims to establish the feasibility of utilizing physics-informed machine learning to create probabilistic models of crucial climatological parameters and extreme...