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Montgomery Flora
Montgomery Flora
PostDoctoral Research Associate
Adresă de e-mail confirmată pe noaa.gov - Pagina de pornire
Titlu
Citat de
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Sensitivity of idealized supercell simulations to horizontal grid spacing: Implications for Warn-on-Forecast
CK Potvin, ML Flora
Monthly Weather Review 143 (8), 2998-3024, 2015
812015
Object-based verification of short-term, storm-scale probabilistic mesocyclone guidance from an experimental Warn-on-Forecast system
ML Flora, PS Skinner, CK Potvin, AE Reinhart, TA Jones, N Yussouf, ...
Weather and Forecasting 34 (6), 1721-1739, 2019
452019
Using machine learning to generate storm-scale probabilistic guidance of severe weather hazards in the Warn-on-Forecast system
ML Flora, CK Potvin, PS Skinner, S Handler, A McGovern
Monthly Weather Review 149 (5), 1535-1557, 2021
442021
Sensitivity of supercell simulations to initial-condition resolution
CK Potvin, EM Murillo, ML Flora, DM Wheatley
Journal of the Atmospheric Sciences 74 (1), 5-26, 2017
392017
Postprocessing next-day ensemble probabilistic precipitation forecasts using random forests
ED Loken, AJ Clark, A McGovern, M Flora, K Knopfmeier
Weather and Forecasting 34 (6), 2017-2044, 2019
352019
Practical predictability of supercells: Exploring ensemble forecast sensitivity to initial condition spread
ML Flora, CK Potvin, LJ Wicker
Monthly Weather Review 146 (8), 2361-2379, 2018
302018
Assessing systematic impacts of PBL schemes on storm evolution in the NOAA Warn-on-Forecast System
CK Potvin, PS Skinner, KA Hoogewind, MC Coniglio, JA Gibbs, AJ Clark, ...
Monthly Weather Review 148 (6), 2567-2590, 2020
212020
Exploring the usefulness of downscaling free forecasts from the Warn-on-Forecast System
WJS Miller, CK Potvin, ML Flora, BT Gallo, LJ Wicker, TA Jones, ...
Weather and Forecasting 37 (2), 181-203, 2022
202022
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
Quantification of NSSL Warn-on-Forecast System accuracy by storm age using object-based verification
JE Guerra, PS Skinner, A Clark, M Flora, B Matilla, K Knopfmeier, ...
Weather and Forecasting 37 (11), 1973-1983, 2022
182022
A review of machine learning for convective weather
A McGovern, RJ Chase, M Flora, DJ Gagne, R Lagerquist, CK Potvin, ...
Artificial Intelligence for the Earth Systems 2 (3), e220077, 2023
122023
Comparing explanation methods for traditional machine learning models part 1: an overview of current methods and quantifying their disagreement
M Flora, C Potvin, A McGovern, S Handler
arXiv preprint arXiv:2211.08943, 2022
102022
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
A machine learning explainability tutorial for atmospheric sciences
ML Flora, CK Potvin, A McGovern, S Handler
Artificial Intelligence for the Earth Systems 3 (1), e230018, 2024
72024
Warn-on-forecast system: From vision to reality
PL Heinselman, PC Burke, LJ Wicker, AJ Clark, JS Kain, J Gao, ...
Weather and Forecasting 39 (1), 75-95, 2024
62024
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
An iterative storm segmentation and classification algorithm for convection-allowing models and gridded radar analyses
CK Potvin, BT Gallo, AE Reinhart, B Roberts, PS Skinner, RA Sobash, ...
Journal of Atmospheric and Oceanic Technology 39 (7), 999-1013, 2022
32022
Storm-scale ensemble-based severe weather guidance: Development of an object-based verification framework and applications of machine learning
M Flora
32020
Interpreting Warn-on-Forecast System Guidance, Part I: Review of Probabilistic Guidance Concepts, Product Design, and Best Practices
PS Skinner, KA Wilson, BC Matilla, B Roberts, N Yussouf, P Burke, ...
22023
Comparing explanation methods for traditional machine learning models Part 2: Quantifying model explainability faithfulness and improvements with dimensionality reduction
M Flora, C Potvin, A McGovern, S Handler
arXiv preprint arXiv:2211.10378, 2022
22022
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