From research to applications – examples of operational ensemble post-processing in France using machine learning - Archive ouverte HAL Access content directly
Journal Articles Nonlinear Processes in Geophysics Year : 2020

From research to applications – examples of operational ensemble post-processing in France using machine learning

(1, 2) , (1, 2)
1
2

Abstract

Abstract. Statistical post-processing of ensemble forecasts, from simple linear regressions to more sophisticated techniques, is now a well-known procedure for correcting biased and poorly dispersed ensemble weather predictions. However, practical applications in national weather services are still in their infancy compared to deterministic post-processing. This paper presents two different applications of ensemble post-processing using machine learning at an industrial scale. The first is a station-based post-processing of surface temperature and subsequent interpolation to a grid in a medium-resolution ensemble system. The second is a gridded post-processing of hourly rainfall amounts in a high-resolution ensemble prediction system. The techniques used rely on quantile regression forests (QRFs) and ensemble copula coupling (ECC), chosen for their robustness and simplicity of training regardless of the variable subject to calibration. Moreover, some variants of classical techniques used, such as QRF and ECC, were developed in order to adjust to operational constraints. A forecast anomaly-based QRF is used for temperature for a better prediction of cold and heat waves. A variant of ECC for hourly rainfall was built, accounting for more realistic longer rainfall accumulations. We show that both forecast quality and forecast value are improved compared to the raw ensemble. Finally, comments about model size and computation time are made.
Fichier principal
Vignette du fichier
npg-27-329-2020.pdf (21.91 Mo) Télécharger le fichier
Origin : Publisher files allowed on an open archive

Dates and versions

meteo-03544128 , version 1 (27-01-2022)

Licence

Attribution - CC BY 4.0

Identifiers

Cite

Maxime Taillardat, Olivier Mestre. From research to applications – examples of operational ensemble post-processing in France using machine learning. Nonlinear Processes in Geophysics, 2020, 27 (2), pp.329-347. ⟨10.5194/npg-27-329-2020⟩. ⟨meteo-03544128⟩
36 View
25 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More