Probabilistic Forecasting of Summer Wind Speed in China Using Multimodel Ensembles

Abstract Wind has a crucial impact on human socio‐economic activities as well as the safety of life and property. Bayesian Model Averaging (BMA) and Ensemble Model Output Statistics (EMOS), are utilized to enhance the probabilistic forecasting skills for 10 m wind speed during the summer in China. A...

Celý popis

Podrobná bibliografie

Hlavní autoři:	Luying Ji, Yan Ji, Xiefei Zhi, Qixiang Luo, Shoupeng Zhu
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	American Geophysical Union (AGU) 2025-04-01
Edice:	Earth and Space Science
Témata:	bayesian model averaging ensemble model output statistics probabilistic forecasts
On-line přístup:	https://doi.org/10.1029/2024EA003850
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!