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Jacob Radford
Jacob Radford
Data Visualization Researcher, CIRA
Verified email at noaa.gov
Title
Cited by
Cited by
Year
An evaluation of snowband predictability in the High-Resolution Rapid Refresh
JT Radford, GM Lackmann, MA Baxter
Weather and Forecasting 34 (5), 1477-1494, 2019
122019
Trust and trustworthy artificial intelligence: A research agenda for AI in the environmental sciences
A Bostrom, JL Demuth, CD Wirz, MG Cains, A Schumacher, ...
Risk Analysis 44 (6), 1498-1513, 2024
82024
An Iterative Approach toward Development of Ensemble Visualization Techniques for High-Impact Winter Weather Hazards: Part II: Product Evaluation
JT Radford, GM Lackmann, J Goodwin, J Correia Jr, K Harnos
Bulletin of the American Meteorological Society 104 (9), E1649–E1669, 2023
22023
Assessing variations in the predictive skill of ensemble snowband forecasts with object-oriented verification and self-organizing maps
JT Radford, GM Lackmann
Weather and Forecasting 38 (9), 1673-1693, 2023
22023
Verification of high-resolution banded snowfall forecasts
JT Radford
North Carolina State University, 2019
22019
NWS Forecaster Perceptions of New AI Guidance for Coastal Fog Prediction
CD Wirz, JL Demuth, M White, JT Radford, PE Tissot, MG Cains, ...
104th AMS Annual Meeting, 2024
12024
Evaluation of Tropical Cyclone Track and Intensity Forecasts from Purely ML-based Weather Prediction Models, Illustrated with FourCastNet
RT DeMaria, M DeMaria, G Chirokova, K Musgrave, JT Radford, ...
104th AMS Annual Meeting, 2024
12024
Evidential deep learning: Enhancing predictive uncertainty estimation for earth system science applications
JS Schreck, DJ Gagne II, C Becker, WE Chapman, K Elmore, G Gantos, ...
arXiv preprint arXiv:2309.13207, 2023
12023
Improving High-Resolution Ensemble Forecast (HREF) system mesoscale snowband forecasts with random forests
JT Radford, GM Lackmann
Weather and Forecasting 38 (9), 1695-1706, 2023
12023
Increasing the reproducibility and replicability of supervised AI/ML in the Earth systems science by leveraging social science methods
CD Wirz, C Sutter, JL Demuth, KJ Mayer, WE Chapman, MG Cains, ...
Earth and Space Science 11 (7), e2023EA003364, 2024
2024
Implicit Associations of AI and Trustworthiness Held by AI and Environmental Science Experts and the Public
A Bostrom, E Smith, S Campbell, J Demuth, C Wirz, M Cains, J Radford
OSF, 2024
2024
A Research Agenda for the Evaluation of AI-Based Weather Forecasting Models
I Ebert-Uphoff, JQ Stewart, JT Radford
EGU24, 2024
2024
Visualizing Data-Driven AI Models to Engage Operational Forecasters
JT Radford, I Ebert-Uphoff, JQ Stewart, RT DeMaria, T Wilson, JL Demuth, ...
104th AMS Annual Meeting, 2024
2024
Lessons Learned from Building Real-Time Machine Learning Testbeds for AI2ES
DJ Gagne, JK Williams, JQ Stewart, J Demuth, PE Tissot, A Kurbanovas, ...
104th AMS Annual Meeting, 2024
2024
Improving Generalizability of Road Condition Classification Models for Department of Transportation Camera Images
C Sutter, KJ Sulia, NP Bassill, CD Thorncroft, V Przybylo, CD Wirz, ...
104th AMS Annual Meeting, 2024
2024
Forecaster Perceptions of Trustworthiness, Explainability, and Interpretability in the Context of AI-Derived Guidance
MG Cains, CD Wirz, JL Demuth, A Bostrom, M White, JT Radford
104th AMS Annual Meeting, 2024
2024
Probability and Verification for High Impact Weather Events II
JT Radford, CP Kalb
104th AMS Annual Meeting, 2024
2024
From Data to Decision: AI at the Intersection of Meteorology, Climate, and Society
JT Radford, JK Williams
104th AMS Annual Meeting, 2024
2024
A Climatology of North American Heat Waves: Patterns and Processes
L Getker, GM Lackmann, JT Radford, WA Robinson
104th AMS Annual Meeting, 2024
2024
DESI-The Newest Decision Support Tool for Fast and Meaningful Interrogation of Ensemble-based Numerical Weather Data
T Wilson, JQ Stewart, R Howlett, JT Radford, C Kahler, K Anderson, ...
104th AMS Annual Meeting, 2024
2024
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