Articles | Volume 31, issue 2
https://doi.org/10.5194/npg-31-247-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.Evaluation of forecasts by a global data-driven weather model with and without probabilistic post-processing at Norwegian stations
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Subject: Time series, machine learning, networks, stochastic processes, extreme events | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere | Techniques: Big data and artificial intelligence
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Downscaling of surface wind forecasts using convolutional neural networks
Data-driven methods to estimate the committor function in conceptual ocean models
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2023Cited articles
Ben-Bouallegue, Z., Clare, M. C. A., Magnusson, L., Gascon, E., Maier-Gerber, M., Janousek, M., Rodwell, M., Pinault, F., Dramsch, J. S., Lang, S. T. K., Raoult, B., Rabier, F., Chevallier, M., Sandu, I., Dueben, P., Chantry, M., and Pappenberger, F.: The rise of data-driven weather forecasting, arXiv [preprint], https://doi.org/10.48550/arXiv.2307.10128, 2023. a, b, c
Benjamini, Y. and Hochberg, Y.: Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing, J. Roy. Stat. Soc. B, 57, 289–300, 1995. a
Bi, K., Xie, L., Zhang, H., Chen, X., Gu, X., and Tao, Q.: Accurate medium-range global weather forecasting with 3D neural networks, Nature, 619, 533–538, https://doi.org/10.1038/s41586-023-06185-3, 2023. a, b, c
Bremnes, J. B.: Ensemble Postprocessing Using Quantile Function Regression Based on Neural Networks and Bernstein Polynomials, Mon. Weather Rev., 148, 403–414, https://doi.org/10.1175/MWR-D-19-0227.1, 2020. a, b, c