Project Grant 2520791
- This $225,351 Project Grant award, funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will support the development of AI emulator tools for improving the estimation of statistics for rare and extreme climate events, such as heat waves and cold spells. The project, led by New York University (NYU), will focus on creating novel methods to leverage AI techniques to better model and predict the impacts of these...
- This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $353,178 to the University of Florida to develop a transformative AI-based framework for generating high-fidelity, physically consistent, and uncertainty-calibrated geoscience data. The research aims to overcome limitations in observational infrastructure and computational cost to produce high-resolution geoscience data essential for understanding and predicting extreme weather events....
- This Project Grant award of $199,316.00 from the National Science Foundation's (NSF) Geosciences Program (CFDA 47.050) aims to advance the understanding of how extreme weather events, such as heavy rainfall and flooding, may change in response to future climate scenarios. The project, titled "EMBRACE-AGS-SEED: Harnessing the Power of Machine Learning to Generate Ensembles of Regional Climate Projections," will evaluate whether artificial intelligence and machine learning can provide...
- This Project Grant award of $798,840 from the National Science Foundation's Geosciences Program (CFDA 47.050) supports research at the University of California, Los Angeles (UCLA) to develop deep learning-based stochastic models for improving forecasts of high-impact weather events such as heat waves, cold snaps, wildfires, and heavy rainfall. The project aims to integrate physics-based atmospheric science with advanced machine learning techniques to enhance the ability to predict these...
- 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...
- 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 $399,162 Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) aims to develop interpretable, stable, and mass-conserving artificial intelligence (AI) models to improve the computational speed and efficiency of geoscientific models, such as those used for air pollution and climate research. The project will create simpler "surrogate" machine learning models for key components like atmospheric chemistry and wildfire plume rise, allowing for...
- This Project Grant award for $1,250,000, funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will support the development of a novel Artificial Intelligence (AI)-assisted decision support system called PCEXPLORER (Physical & Citizen Sensing Exploration Tool). The project, led by George Mason University (GMU), aims to address challenges in emergency shelter planning and evacuation strategies for severe weather events...
- This $284,443 Project Grant award was provided by the National Science Foundation (NSF) through its Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) to the University of Chicago. The project, titled "COLLABORATIVE RESEARCH: CAIG: DEVELOPING AI EMULATOR TOOLS FOR EXTREME EVENTS WITH APPLICATION TO HEAT WAVES AND COLD SNAPS", aims to develop advanced mathematical tools and AI emulation techniques to improve the estimation of rare climate events,...
- The National Science Foundation awarded a $500,000 Project Grant from the Geosciences program (CFDA 47.050) to the University of Maryland, College Park. The grant will fund a collaborative research project titled "CAIG: Reliable Generative Downscaling for Geoscience Data" from October 1, 2025 to September 30, 2028. The project aims to develop a transformative AI-based framework for generating high-fidelity, physically consistent, and uncertainty-calibrated geoscience data. This will...
This Project Grant award of $250,000 from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports the development of advanced AI-driven tools to help communities across the U.S. better understand and mitigate environmental risks from extreme weather events. The project aims to build an AI model that integrates diverse datasets, including spatial, hazard, and socioeconomic data, to analyze regional environmental risks and community resilience. The research utilizes deep learning, ensemble models, and explainable AI methods to capture the complex dynamics of environmental threats and community preparedness. The tools developed will be made publicly available to assist researchers, planners, and local communities in developing adaptation strategies for extreme weather events. Additionally, the project includes mentoring and training for students to prepare them for careers in AI and policy-relevant research. No sub-awards are planned under this grant, which has an award date of September 1, 2025 and a scheduled completion date of August 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $250.0k | 8/25/25 |