Project Grant 2425899
- 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,...
- 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...
- 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 $328,081 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) will support research at Columbia University to understand the drivers of the extreme marine heatwaves that occurred globally in 2023. The project will use observational data, climate models, and artificial intelligence to investigate the roles of surface heat, clouds, and ocean currents in causing these marine heatwaves, which...
- The National Science Foundation (NSF) awarded a $497,419 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Colorado State University (CSU). The grant, titled "CAIG: Toward a Deeper Understanding of Cloud Processes and Future Storm Modes Using AI," aims to develop novel algorithms that leverage artificial intelligence (AI) and advanced mathematics to gain a deeper understanding of cloud formation and hazardous weather patterns in the...
- The National Science Foundation (NSF) awarded a $660,984 Project Grant under the Geosciences program (CFDA 47.050) to Brown University. The grant, titled "CAIG: Navigating the Climate Science Deluge: Training Language Models to Assist in Comprehensive Assessments," aims to develop an artificial intelligence (AI) climate science chatbot assistant to help researchers more efficiently review and summarize the growing body of climate research literature. The project will create new methods...
- 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 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...
- The National Science Foundation (NSF) awarded a $300,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Massachusetts (UMass) to investigate distributed machine learning for climate modeling and weather forecasting. Through this EAGER (EArly-concept Grants for Exploratory Research) award, UMass will leverage existing testbeds, including the CASA radar network, to support the development of a National Discovery Cloud for Climate...
- This $322,555 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program supports research to develop statistical and machine learning methods for studying the dynamics of weather and climate extremes. The three-year project, with a completion date of July 31, 2025, will focus on three key areas: climate model validation, changepoint estimation for extremes, and integration of multi-model climate ensembles. The research aims to enhance...
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 high-impact, low-probability climate phenomena. The award will fund research to develop AI Dynamic Galerkin Approximation (AI-DGA) and AI-based Rare Event Sampling (AI-RES) approaches to extract long return periods from short-duration emulations and generate more rare event data to enhance the emulator training process. This interdisciplinary effort aims to deliver transformational advances that can significantly improve the usefulness of AI emulators across climate science and geoscience domains.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $225.4k | 8/29/24 |