Project Grant NA20OAR0210073

This $428,965 Cooperative Agreement awarded by the National Oceanic and Atmospheric Administration (NOAA) under the Weather and Air Quality Research program (CFDA 11.459) aims to develop and test a method for improving subseasonal-to-seasonal (S2S) precipitation outlooks for the contiguous United States. The project, led by Utah State University, will apply a new weather regime-Gaussian mixture model (WR-GMM) framework to NOAA's Climate Prediction Center's dynamical forecast outputs to produce...

This three-year, $405,234 Project Grant from the National Oceanic and Atmospheric Administration will fund research at the University of Colorado Boulder to develop initialization strategies for the Unified Forecast System coupled atmosphere-ocean numerical forecast model. The goal is to improve probabilistic skill scores for subseasonal-to-seasonal forecasts of 2-8 weeks by ensuring initial ensemble perturbations project onto oscillating eigenfunctions of the Koopman and Perron-Frobenius...

This federal Cooperative Agreement award, provided by the National Oceanic and Atmospheric Administration (NOAA) under the Weather and Air Quality Research program (CFDA 11.459), aims to improve real-time U.S. week 3-4 precipitation forecasts through the application of machine learning and explainable artificial intelligence (XAI) techniques. The $254,646 project, which runs from February 1, 2025 to January 31, 2027, is a collaboration between the Climate Prediction Center (CPC) and Colorado...

This federal Project Grant award for $1,495,400 from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) supports the "ACCELNET Implementation Phase 1: International Network of Networks (S2S-ACCELNET) for Accelerating Subseasonal-to-Seasonal Forecast Applications and Services" initiative. The key objectives are to: 1) identify research opportunities and challenges in subseasonal-to-seasonal (S2S) forecast applications and services (FAS), 2)...

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 Project Grant award from the National Oceanic and Atmospheric Administration (NOAA) under the Climate and Atmospheric Research program (CFDA 11.431) provides $239,986 to the University of Wisconsin-Madison to advance the understanding of climate prediction models and improve seasonal to decadal climate forecasting. The project aims to explore how increased horizontal model resolution can enhance predictive skill for sea surface temperatures in the tropical Pacific and related impacts on...

This federal Project Grant award from the National Oceanic and Atmospheric Administration (NOAA) Small Business Innovation Research (SBIR) Program (CFDA 11.021) provides $3,249,675 to Salient Predictions Inc. to develop technology for improved subseasonal to seasonal (S2S) water availability forecasts. The goal is to combine Salient's machine learning-based S2S weather forecasting capabilities with the Variable Infiltration Capacity (VIC) hydrological model to generate more accurate soil...

This three-year, $563,324 National Science Foundation project grant funds research by Atmospheric & Environmental Research Inc. on observing and modeling the spatiotemporal variability of the seasonal cycle in sea level. The awardee will analyze satellite and in situ data, as well as output from global ocean models, to examine the seasonal cycle in sea level over global oceans and coastal regions. Specific objectives include analyzing the seasonal cycle's mean and year-to-year variability...

This Cooperative Agreement, awarded by the Department of Commerce National Oceanic and Atmospheric Administration (NOAA) under the Climate and Atmospheric Research program (CFDA 11.431), provides $487,987 to Atmospheric & Environmental Research Inc. to analyze emerging global ocean model simulations in order to improve seasonal to annual (S2A) forecasts of coastal sea level variability. The key objectives are to quantify resolution-related enhancements in the ability to forecast both...

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,...