Project Grant 2530919
- This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $410,837 to Boston University to conduct collaborative research aimed at improving the performance of climate models used to simulate weather and climate. The research addresses two key shortcomings of current climate models: their computational intensity and lack of incorporation of observational data. The project will develop climate emulators that use machine learning to extract...
- Colorado State University was awarded a $795,202 Project Grant from the National Science Foundation Division of Atmospheric and Geospace Sciences. The award is part of the NSF's Geosciences program (CFDA 47.050) to strengthen understanding of the integrated Earth system through basic research in atmospheric, earth, and ocean sciences. Under the three-year award beginning September 1, 2021, Colorado State University will research the influence of climate change on temperature persistence. The...
- The National Science Foundation (NSF) awarded a $1,030,041 Project Grant under CFDA 47.050 Geosciences to Colorado State University (CSU) to conduct research on the pattern effect and its impact on radiative feedbacks in the Earth system. The project, titled "ANALYSES OF THE PATTERN EFFECT ON RADIATIVE FEEDBACKS: GAINING PHYSICAL INSIGHTS FROM STATISTICAL METHODS; TESTING THE ROLE OF LAND SURFACE TEMPERATURES -THE RESPONSE OF THE GLOBAL ATMOSPHERE/OCEAN SYSTEM TO RADIATIVE FORCING DEPENDS...
- 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 $252,059 Project Grant award from the National Science Foundation's Geosciences program (CFDA 47.050) aims to develop a machine learning-based "emulator" that can efficiently predict water isotope patterns in fully-coupled global climate models. The goal is to build a powerful tool that can enhance climate science, hydrology, and understanding of the Earth's past and future climate by leveraging water isotope data. The University Corporation for Atmospheric Research (UCAR),...
- 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 National Science Foundation (NSF) Division of Atmospheric and Geospace Sciences Project Grant award, under the Geosciences program (CFDA 47.050), provides $158,059 to Colorado State University from July 1, 2023 to June 30, 2026. The funding will support collaborative research to understand the impact of declining Arctic sea ice on summertime climate change, including the effects on atmospheric circulation patterns, heat waves, and extreme weather. The research approach includes analysis...
- This National Science Foundation (NSF) Geosciences Program (CFDA 47.050) Project Grant award of $319,907 to the University of Maryland, College Park aims to build a machine-learning-based "emulator" that can efficiently predict water isotope patterns in climate models. The three-year project, starting November 1, 2025, seeks to develop a smart shortcut to incorporate water isotopes, which act as natural recorders of climate history, into complex climate simulations. This...
- 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...
- 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...
The National Science Foundation (NSF) awarded a $783,920 project grant under its Geosciences Program (CFDA 47.050) to Colorado State University (CSU) for the project "COLLABORATIVE RESEARCH: CAIG: UNDERSTANDING RADIATIVE FEEDBACKS, OCEAN HEAT UPTAKE, AND ENERGY CONSERVATION TO IMPROVE ML-CLIMATE EMULATIONS." The project aims to develop climate emulators using machine learning to extract statistical relationships from observational data and physics-based climate simulations, with the goal of improving computational efficiency and utilization of observational data in climate modeling. The award period runs from January 1, 2026 to December 31, 2028. The project will evaluate the performance of multiple climate emulators in simulating the response of the climate system to regional temperature variations, addressing questions related to coupled climate dynamics and regional-to-global climate impacts.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $783.9k | 7/16/25 |