Version 1
: Received: 13 February 2023 / Approved: 14 February 2023 / Online: 14 February 2023 (09:36:21 CET)
How to cite:
Han, Z.; Hu, D.; Lv, Q.; Zhong, A. X. Comparisons of Initial Condition Perturbation Methods for Regional Ensemble Forecasts of Wind Speed in Gansu of China. Preprints2023, 2023020243. https://doi.org/10.20944/preprints202302.0243.v1
Han, Z.; Hu, D.; Lv, Q.; Zhong, A. X. Comparisons of Initial Condition Perturbation Methods for Regional Ensemble Forecasts of Wind Speed in Gansu of China. Preprints 2023, 2023020243. https://doi.org/10.20944/preprints202302.0243.v1
Han, Z.; Hu, D.; Lv, Q.; Zhong, A. X. Comparisons of Initial Condition Perturbation Methods for Regional Ensemble Forecasts of Wind Speed in Gansu of China. Preprints2023, 2023020243. https://doi.org/10.20944/preprints202302.0243.v1
APA Style
Han, Z., Hu, D., Lv, Q., & Zhong, A. X. (2023). Comparisons of Initial Condition Perturbation Methods for Regional Ensemble Forecasts of Wind Speed in Gansu of China. Preprints. https://doi.org/10.20944/preprints202302.0243.v1
Chicago/Turabian Style
Han, Z., Qingquan Lv and And Xiaohui Zhong. 2023 "Comparisons of Initial Condition Perturbation Methods for Regional Ensemble Forecasts of Wind Speed in Gansu of China" Preprints. https://doi.org/10.20944/preprints202302.0243.v1
Abstract
This work compared the performance of three methods for constructing a regional ensemble prediction system (EPS) for wind speed forecasts: dynamical downscaling, breeding of growth modes (BGM), and blending method. The Weather Research and Forecasting (WRF) model was used to downscale the European Centre for Medium-range Weather Forecast (ECMWF) EPS. In addition, as the BGM method needs observation data for generating scaling factors, an alternative method for generating scaling factors was proposed to eliminate dependence on observation data. One-month tests between October 1st and October 30th, 2020, were implemented to evaluate the performance of three methods in the Gansu province of China. The results demonstrate that the blending method outperforms the other two methods. Furthermore, the difference in performance is evident mainly in early forecast lead time and becomes negligible as forecast time increases.
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
