Papers that cite Herbie

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This is a collection of papers that cite Herbie in peer-reviewed literature. If you see Herbie used in a paper, please tell everyone about it here!

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Santellanes and Melgar 2024

Santellanes, S. R. and Melgar, D.: Contemporary measurements of the background open ocean tsunami spectrum using the Deep-ocean Assessment and Reporting of Tsunami (DART) stations, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-1614, 2024.

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Baldwin et al. 2023

Baldwin, M. E., H. D. Reeves, and A. A. Rosenow, 2023: Evaluation of a Probabilistic Subfreezing Road Temperature Nowcast System Based on Machine Learning. Wea. Forecasting, 38, 2427–2440, https://doi.org/10.1175/WAF-D-23-0137.1.

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Gaudet et al. 2024

Gaudet, L. C., K. J. Sulia, R. D. Torn, and N. P. Bassill, 2024: Verification of the Global Forecast System, North American Mesoscale Forecast System, and High-Resolution Rapid Refresh Model Near-Surface Forecasts by Use of the New York State Mesonet. Wea. Forecasting, 39, 369–386, https://doi.org/10.1175/WAF-D-23-0094.1.

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Hennon et al. 2022

Hennon, C. C., A. Coleman, and A. Hill, 2022: Short-Term Weather Forecast Skill of Artificial Neural Networks. Wea. Forecasting, 37, 1941–1951, https://doi.org/10.1175/WAF-D-22-0009.1.

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Millstein et al. 2023

Millstein, D., S. Jeong, A. Ancell, R. Wiser, 2023: A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models. Sci Data 10, 883. https://doi.org/10.1038/s41597-023-02804-w.

[williamhobbs]

Two that are NOT PEER REVIEWED, but maybe still worth listing:

EPRI (Larson et al.) 2023

Guidance on Weather Datasets for Studies: Data Sources and Use Cases for Historical Datasets.
EPRI, Palo Alto, CA: 2023. 3002024375. Online: https://www.epri.com/research/products/000000003002024375

EPRI (Larson et al.) 2024

Guidance on Numerical Weather Prediction: Models and Data Sources. EPRI, Palo Alto,
CA: 2024. 3002027745. Online: https://www.epri.com/research/products/000000003002027745