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David Harrison
David Harrison
Cooperative Institute for Severe and High-Impact Weather Research and Operations, The University of
Adresă de e-mail confirmată pe ou.edu - Pagina de pornire
Titlu
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Development of a human–machine mix for forecasting severe convective events
CD Karstens, J Correia, DS LaDue, J Wolfe, TC Meyer, DR Harrison, ...
Weather and Forecasting 33 (3), 715-737, 2018
562018
A machine learning tutorial for operational meteorology. Part I: Traditional machine learning
RJ Chase, DR Harrison, A Burke, GM Lackmann, A McGovern
Weather and Forecasting 37 (8), 1509-1529, 2022
512022
A climatology of operational storm-based warnings: A geospatial analysis
DR Harrison, CD Karstens
Weather and Forecasting 32 (1), 47-60, 2017
302017
A machine learning tutorial for operational meteorology. Part II: Neural networks and deep learning
RJ Chase, DR Harrison, GM Lackmann, A McGovern
Weather and Forecasting 38 (8), 1271-1293, 2023
222023
A real-time, virtual spring forecasting experiment to advance severe weather prediction
AJ Clark, IL Jirak, BT Gallo, B Roberts, AR Dean, KH Knopfmeier, ...
Bulletin of the American Meteorological Society 102 (4), E814-E816, 2021
202021
Utilizing the high-resolution ensemble forecast system to produce calibrated probabilistic thunderstorm guidance
DR Harrison, MS Elliott, IL Jirak, PT Marsh
Weather and Forecasting 37 (7), 1103-1115, 2022
82022
The second real-time, virtual spring forecasting experiment to advance severe weather prediction
AJ Clark, IL Jirak, BT Gallo, KH Knopfmeier, B Roberts, M Krocak, J Vancil, ...
Bulletin of the American Meteorological Society 103 (4), E1114-E1116, 2022
82022
Correcting, improving, and verifying automated guidance in a new warning paradigm
D Harrison
62018
The third real-time, virtual spring forecasting experiment to advance severe weather prediction capabilities
AJ Clark, IL Jirak, BT Gallo, B Roberts, KH Knopfmeier, J Vancil, D Jahn, ...
Bulletin of the American Meteorological Society 104 (2), E456-E458, 2023
42023
Machine learning co-production in operational meteorology
D Harrison
42022
Storm Evader: using an iPad to teach kids about Meteorology and technology
A McGovern, A Balfour, M Beene, D Harrison
Bulletin of the American Meteorological Society 96 (3), 397-404, 2015
42015
Harnessing the Thunder: Civil Society's Care and Creativity in South Africa's COVID Storm
D Harrison
Porcupine Press, 2020
32020
Winter precipitation-type classification with a 1D convolutional neural network
DR Harrison, A McGovern, C Karstens, IL Jirak, PT Marsh
102nd American Meteorological Society Annual Meeting, 2022
22022
The first hybrid NOAA Hazardous Weather Testbed Spring Forecasting Experiment for advancing severe weather prediction
AJ Clark, IL Jirak, TA Supinie, KH Knopfmeier, J Vancil, D Jahn, ...
Bulletin of the American Meteorological Society 104 (12), E2305-E2307, 2023
12023
Machine Learning Tutorials for Operational Meteorology
RJ Chase, DR Harrison, A Burke, GM Lackmann, A McGovern
103rd AMS Annual Meeting, 2023
12023
Using machine learning techniques to predict near-term severe weather trends
D Harrison, C Karstens, A McGovern
98th American Meteorological Society Annual Meeting, 2018
12018
Activities and Preliminary Results from the 1st Hybrid NOAA/Hazardous Weather Testbed Spring Forecasting Experiment
AJ Clark, IL Jirak, TA Supinie, J Vancil, DE Jahn, KH Knopfmeier, Y Wang, ...
104th AMS Annual Meeting, 2024
2024
Developing Dry Thunderstorm Verification Tools to Improve Fire Weather Forecasting at NOAA’s Storm Prediction Center
P Lin, MS Elliott, DR Harrison, ES Bentley, IL Jirak, J Vancil, K Halbert, ...
104th AMS Annual Meeting, 2024
2024
An Overview of the 1st Hybrid NOAA Hazardous Weather Testbed Spring Forecasting Experiment in 2023
AJ Clark, IL Jirak, TA Supinie, J Vancil, DE Jahn, KH Knopfmeier, ...
32nd Conference on Weather Analysis and Forecasting (WAF)/28th Conference on …, 2023
2023
6A. 1 PREDICTING PROBABILISTIC LIGHTNING FLASH DENSITY FROM THE HREF CALIBRATED THUNDER GUIDANCE
DR Harrison, MS Elliott, IL Jirak, PT Marsh
2023
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