This Project Grant award of $500,000.00 from the National Science Foundation's Geosciences Program (CFDA 47.050) is funding the development of a transformative AI-based framework for generating high-fidelity, physically consistent, and uncertainty-calibrated geoscience data. The goal is to overcome limitations in observational infrastructure and computational cost to produce enhanced datasets that can improve decision-making for disaster preparedness, emergency response, and infrastructure...
This $798,840 federal Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) supports research to enhance forecasting capabilities for high-impact weather events like heat waves, cold snaps, wildfires, and heavy rainfall. The project aims to integrate physics-based atmospheric science with state-of-the-art machine learning techniques, generating stochastic models to better predict midlatitude weather patterns and extreme events. This research will contribute...
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 National Science Foundation (NSF) Integrative Activities (CFDA 47.083) Project Grant award of $290,165 to the University of Hawaii (UH) at Manoa will support a collaborative research project to improve subseasonal-to-seasonal (S2S) forecasting of extreme hydrometeorological events and their impacts in Hawaii. The project aims to deepen the understanding of intraseasonal climate variability in the central Pacific and develop an S2S forecast system for events like heavy rainfall, flooding,...
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 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 in the amount of $200,000 was issued on September 15, 2023 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA #47.070). The grant supports the development and deployment of a multi-hazard monitoring and detection system combining the University of Hawaii's climate mesonet infrastructure with Northwestern University's artificial intelligence-enhanced sensor platform. This system is being...
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 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant award of $290,285, effective July 1, 2025 through June 30, 2028, aims to develop an advanced cyberinfrastructure that integrates artificial intelligence (AI) with diverse space weather data to improve forecasting of extreme space weather events. The project will create a homogenized dataset of vector magnetograms, open-access computational tools, and machine learning models to process...
This National Science Foundation project grant of $199,984 supports the development of model enabled machine learning approaches to predict ecosystem regime shifts through the Biological Sciences program (CFDA 47.074). The University of Hawaii at Manoa will receive funding from January 15, 2023 through December 31, 2025 to co-develop numerical methods with stakeholders that combine theoretical ecosystem models with machine learning to forecast regime shifts in coral reefs, freshwater lakes...