Proceedings of the 2023 9th International Conference on Advances in Energy Resources and Environment Engineering (ICAESEE 2023)

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Comparisons of Initial condition perturbation methods for regional ensemble wind speed forecasts in Gansu, China

Authors
Zifen Han1, *, Diangang Hu1, Jianmei Zhang2, Qingquan Lv2
1State Grid Gansu Electric Power Company, Lanzhou, China
2State Grid Gansu Electric Power Company, Electric Power Research Institute, Lanzhou, China
*Corresponding author. Email: wujiexia0102@163.com
Corresponding Author
Zifen Han
Available Online 14 May 2024.
DOI
10.2991/978-94-6463-415-0_21How to use a DOI?
Keywords
ensemble; dynamical downscaling; BGM; blending
Abstract

The study examined three methods for developing a regional ensemble prediction system (EPS) to forecast wind speeds: dynamical downscaling, breeding of growth modes (BGM), and blending. We used the Weather Research and Forecasting (WRF) model to downscale the ensemble forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) over Gansu province, China. One-month tests between October 1st and October 31st, 2020, were conducted to assess the performance of the three methods.

The results show that the blending method combines the high-resolution WRF BGM ensemble’s small-scale features and the global ensemble’s large-scale features, making it superior to the other two methods. Moreover, the performance difference is mainly observed in forecast and becomes less significant as the forecast time increases.

Additionally, we proposed an alternative method for generating scaling factors to eliminate the dependency on observation data, as the BGM method requires such data for generating scaling factors.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 9th International Conference on Advances in Energy Resources and Environment Engineering (ICAESEE 2023)
Series
Atlantis Highlights in Engineering
Publication Date
14 May 2024
ISBN
978-94-6463-415-0
ISSN
2589-4943
DOI
10.2991/978-94-6463-415-0_21How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Zifen Han
AU  - Diangang Hu
AU  - Jianmei Zhang
AU  - Qingquan Lv
PY  - 2024
DA  - 2024/05/14
TI  - Comparisons of Initial condition perturbation methods for regional ensemble wind speed forecasts in Gansu, China
BT  - Proceedings of the 2023 9th International Conference on Advances in Energy Resources and Environment Engineering (ICAESEE 2023)
PB  - Atlantis Press
SP  - 192
EP  - 203
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-415-0_21
DO  - 10.2991/978-94-6463-415-0_21
ID  - Han2024
ER  -