Skip to Main content Skip to Navigation
Journal articles

Assessment of stochastic weather forecast of precipitation near European cities, based on analogs of circulation

Abstract : In this study, we assess the skill of a stochastic weather generator (SWG) to forecast precipitation in several cities in western Europe. The SWG is based on a random sampling of analogs of the geopotential height at 500 hPa (Z500). The SWG is evaluated for two reanalyses (NCEP and ERA5). We simulate 100-member ensemble forecasts on a daily time increment. We evaluate the performance of SWG with forecast skill scores and we compare it to ECMWF forecasts.

Results show significant positive skill score (continuous rank probability skill score and correlation) compared with persistence and climatology forecasts for lead times of 5 and 10 d for different areas in Europe. We find that the low predictability episodes of our model are related to specific weather regimes, depending on the European region. Comparing the SWG forecasts to ECMWF forecasts, we find that the SWG shows a good performance for 5 d. This performance varies from one region to another. This paper is a proof of concept for a stochastic regional ensemble precipitation forecast. Its parameters (e.g., region for analogs) must be tuned for each region in order to optimize its performance.

Document type :
Journal articles
Complete list of metadata

https://hal-insu.archives-ouvertes.fr/insu-03721923
Contributor : Nathalie POTHIER Connect in order to contact the contributor
Submitted on : Wednesday, July 13, 2022 - 2:02:00 PM
Last modification on : Friday, July 15, 2022 - 3:23:30 AM

File

gmd-15-4941-2022.pdf
Publisher files allowed on an open archive

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Meriem Krouma, Pascal Yiou, Céline Déandreis, Soulivanh Thao. Assessment of stochastic weather forecast of precipitation near European cities, based on analogs of circulation. Geoscientific Model Development, European Geosciences Union, 2022, 15, pp.4941-4958. ⟨10.5194/gmd-15-4941-2022⟩. ⟨insu-03721923⟩

Share

Metrics

Record views

0

Files downloads

0