The Joint Technology Transfer Initiative (JTTI), works closely with the National Weather Service to accelerate the transition of matured weather research to NWS operations to improve forecasting for the benefit of the American public. This year’s competition focused on improving model development in collaboration with the UFS community to improve forecasts, finding innovative methodologies to understand the needs and challenges of underserved communities with respect to the communication of National Weather Service products and services related to extreme weather and water events, and developing innovative scientific and technological solutions to improve forecasts, products, services, and Decision Support Services (DSS) for extreme weather and water events in collaboration with NOAA Testbeds and Proving Grounds.
The award total* for the 15 selected projects equals $9.6 M in cooperative agreements and each project will be funded for 2-3 years beginning September 1, 2022.
*Award totals are distributed over the life of the projects and conditional on appropriations
Projects Selected
Project Title | PI’s & Co-PI’s | Affiliations |
---|---|---|
Advanced Coupling Evaluation Metrics in METplus for UFS Land Surface Models | Scott Miller (PI), Andrew Newman | University at Albany-SUNY, National Center for Atmospheric Research (NCAR) |
Multi-institution Collaborative Proposal: Integration of a Fully Functional Atmospheric UFS-HASFS into JEDI with Weakly Coupled Ocean Data Assimilation Capability | Altug Aksoy (PI), Xuguang Wang, Jonathan Poterjoy | Cooperative Institute for Marine and Atmospheric Studies (CIMAS)/ University of Miami, University of Oklahoma, University of Maryland |
Transitioning Weather-Aware Rapid Refresh Emission Modeling Capability to Support National Air Quality Forecast Capability Operations | Bok Baek (PI) | George Mason University |
Probabilistic Prediction of Thunderstorm Hazards using the NOAA Warn-on-Forecast System and Machine Learning | Montgomery Flora (PI) | University of Oklahoma |
Effectively Communicating Uncertainty in Tropical Cyclone Intensity Forecasts | Daniel Halperin (PI), Deanna Sellnow | Embry-Riddle Aeronautical University, University of Central Florida |
A Weather-Ready Nation Para Todos: Evaluating Current Practices in Communicating Hazardous Weather Risks to Spanish Speakers | Justin Reedy (PI) | University of Oklahoma |
Advancing the Lake-Coupling Techniques for the Unified Forecast System (UFS) | Christiane Jablonowski (PI) | Cooperative Institute for Great Lakes Research (CIGLR)/ University of Michigan |
Implementation of a Unified Workflow for the Unified Forecast System (UFS) Short Range Weather Application | Christina Holt (PI) | Cooperative Institute for Research in Environmental Sciences (CIRES)/ University of Colorado |
Creation and evaluation of a CONUS-wide gridded analysis-of-record for ice accumulation | Heather Reeves (PI) | Cooperative Institute for Severe and High-Impact Weather Research and Operations (CIWRO) University of Oklahoma |
A Scale-Aware Three-Dimensional Sub-Grid Scale Turbulent Mixing Parameterization for the Hurricane Analysis and Forecast System | Ping Zhu (PI), Jun Zhang | Florida International University, Cooperative Institute for Marine and Atmospheric Studies (CIMAS)/ University of Miami |
Deep Learning Hybrid Dynamical-statistical model for US Precipitation Subseasonal Forecasting | Hyemi Kim (PI) | Stony Brook University |
Implementation of an Ensemble Sensitivity Tool to Better Assess Uncertainty in Mid-Latitude Extreme Weather Forecasts | Brian Colle (PI), William Lamberson | Stony Brook University, Cooperative Institute for Research in Environmental Sciences (CIRES)/ University of Colorado |
Expanding Audiences, Removing Barriers, Promoting Action: Addressing the diverse needs of audiences for flood forecast information | Rachel Hogan Carr (PI) | Nurture Nature Center, Inc. |
Advancement of background ensemble covariance at the air-sea interface toward the UFS HAFS fully coupled data assimilation | Xuguang Wang (PI), Jun Zhang | University of Oklahoma, Cooperative Institute for Marine and Atmospheric Studies (CIMAS)/ University of Miami |
A Wind-Wave-Current Data Assimilation Scheme for the 3D-Real Time Mesoscale Analysis | Malaquías Peña (PI) | University of Connecticut |