Hou Chengzhi, Xu Zhiwei, Karnauskas Kristopher B, Huang Danqing, Lu Huayu
School of Geography and Ocean Science, Nanjing University, Nanjing, China.
Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO, USA.
Nat Commun. 2025 Apr 22;16(1):3775. doi: 10.1038/s41467-025-59195-2.
The global capacity for wind power has grown rapidly in recent years, yet uncertainties in wind power density (WPD) assessments still hinder effective climate change mitigation efforts. One major challenge is the significant underestimation of WPD when using coarser temporal resolutions (∆t) of wind speed data. Here, we show that using daily ∆t results in an average underestimation of 35.6% in global onshore WPD compared to hourly ∆t. This discrepancy arises from the exponential decay of WPD with increasing ∆t, reflecting the intrinsic properties of wind speed distributions, particularly in regions with weaker winds. To address this, we propose a calibration method that introduces a correction coefficient to reduce biases and harmonize WPD estimates across temporal resolutions. Applying this method to future wind energy projections under the Shared Socioeconomic Pathway 585 scenario increases global onshore WPD estimates by 25% by 2100, compared to uncorrected daily data. These findings highlight the effectiveness of calibration in reducing uncertainties, enhancing WPD assessments, and facilitating robust policy action toward carbon neutrality.
近年来,全球风能发电能力迅速增长,但风能密度(WPD)评估中的不确定性仍然阻碍了有效的气候变化缓解努力。一个主要挑战是,在使用风速数据的较粗时间分辨率(∆t)时,WPD会被显著低估。在此,我们表明,与每小时的∆t相比,使用每日的∆t会导致全球陆上WPD平均低估35.6%。这种差异源于WPD随∆t增加而呈指数衰减,这反映了风速分布的内在特性,特别是在风力较弱的地区。为解决这一问题,我们提出了一种校准方法,引入一个校正系数以减少偏差,并使不同时间分辨率下的WPD估计值趋于一致。与未校正的每日数据相比,在共享社会经济路径585情景下,将这种方法应用于未来风能预测,到2100年全球陆上WPD估计值将增加25%。这些发现凸显了校准在减少不确定性、加强WPD评估以及推动实现碳中和的有力政策行动方面的有效性。