Projected near-surface wind speed and wind energy over Central Asia using dynamical downscaling with bias-corrected global climate models

Wind energy development in Central Asia can help alleviate drought and fragile ecosystems. Nevertheless, current studies mainly used the global climate models (GCMs) to project wind speed and energy. The simulated biases in GCMs remain prominent, which induce a large uncertainty in the projected res...

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Detalles Bibliográficos
Autores: Zha, Jinlin, Chuan, Ting, Qiu, Yuan, Wu, Jian, Zhao, Deming, Fan, Wenxuan, Lyu, Yan-Jun, Jiang, Hui-Ping, Deng, Kaiqiang, Andrés-Martín, M., Azorín-Molina, César, Chen, Deliang
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/373927
Acceso en línea:http://hdl.handle.net/10261/373927
Access Level:acceso abierto
Palabra clave:Near-surface wind speed
Wind power density
Dynamical downscaling
Central Asia
WRF
Descripción
Sumario:Wind energy development in Central Asia can help alleviate drought and fragile ecosystems. Nevertheless, current studies mainly used the global climate models (GCMs) to project wind speed and energy. The simulated biases in GCMs remain prominent, which induce a large uncertainty in the projected results. To reduce the uncertainties of projected near-surface wind speed (NSW) and better serve the wind energy development in Central Asia, the Weather Research and Forecasting (WRF) model with bias-corrected GCMs was employed. Compared with the outputs of GCMs, dynamical downscaling acquired using the WRF model can better capture the high- and low-value centres of NSWS, especially those of Central Asia's mountains. Meanwhile, the simulated NSWS bias was also reduced. For future changes in wind speed and wind energy, under the Representative Concentration Pathway 4.5 (RCP4.5) scenario, NSWS during 2031–2050 is projected to decrease compared with that in 1986–2005. The magnitude of NSWS reduction during 2031–2050 will reach 0.1 m s−1, and the maximum reduction is projected to occur over the central and western regions (>0.2 m s−1). Furthermore, future wind power density (WPD) can reveal nonstationarity and strong volatility, although a downward trend is expected during 2031–2050. In addition, the higher frequency of wind speeds at the turbine hub height exceeding 3.0 m s−1 can render the plain regions more suitable for wind energy development than the mountains from 2031 to 2050. This study can serve as a guide in gaining insights into future changes in wind energy across Central Asia and provide a scientific basis for decision makers in the formulation of policies for addressing climate change.