Articles | Volume 19, issue 21
https://doi.org/10.5194/gmd-19-10651-2026
https://doi.org/10.5194/gmd-19-10651-2026
Methods for assessment of models
 | 
10 Nov 2026
Methods for assessment of models |  | 10 Nov 2026

Evaluating extreme precipitation forecasts: a threshold-weighted, spatial verification approach for comparing an AI weather prediction model against a high-resolution NWP model

Nicholas Loveday and Tracy Hertneky

Cited articles

Abdi, D., Jankov, I., Madden, P., Vargas, V., Smith, T. A., Frolov, S., Flora, M., and Potvin, C.: HRRRCast: a data-driven emulator for regional weather forecasting at convection allowing scales, arXiv [preprint], arXiv:2507.05658, 2025. a
Adamov, S., Oskarsson, J., Denby, L., Landelius, T., Hintz, K., Christiansen, S., Schicker, I., Osuna, C., Lindsten, F., Fuhrer, O., and Schemm, S.: Building Machine Learning Limited Area Models: Kilometer-Scale Weather Forecasting in Realistic Settings, arXiv [preprint], arXiv:2504.09340, 2025. a
Allen, S.: Weighted scoringRules: Emphasizing Particular Outcomes When Evaluating Probabilistic Forecasts, J. Stat. Softw., 110, https://doi.org/10.18637/jss.v110.i08, 2024. a
Allen, S., Ginsbourger, D., and Ziegel, J.: Evaluating Forecasts for High-Impact Events Using Transformed Kernel Scores, SIAM/ASA Journal on Uncertainty Quantification, 11, 906–940, https://doi.org/10.1137/22m1532184, 2023. a, b, c, d
Ayer, M., Brunk, H. D., Ewing, G. M., Reid, W. T., and Silverman, E.: An Empirical Distribution Function for Sampling with Incomplete Information, Ann. Math. Stat., 26, 641–647, https://doi.org/10.1214/aoms/1177728423, 1955. a
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Short summary
This study introduces a verification method that accounts for differences in grid resolution when evaluating extreme event forecasts. We apply it to an artificial intelligence-based weather prediction model and a high-resolution numerical weather prediction model. Results show that, when assessed on equivalent neighborhood scales, the high resolution numerical weather prediction model only outperforms the AI system for short lead times in predicting extreme precipitation.
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