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杜梦蛟, 邓浩, 文仁强, 等. 2023. 大气再分析资料在中国近海的风资源特征和适用性分析[J]. 气候与环境研究, 28(5): 483−494. doi: 10.3878/j.issn.1006-9585.2023.22050
引用本文: 杜梦蛟, 邓浩, 文仁强, 等. 2023. 大气再分析资料在中国近海的风资源特征和适用性分析[J]. 气候与环境研究, 28(5): 483−494. doi: 10.3878/j.issn.1006-9585.2023.22050
DU Mengjiao, DENG Hao, WEN Renqiang, et al. 2023. Wind Resource Characteristics and Applicability of Atmospheric Reanalysis Data in Offshore China [J]. Climatic and Environmental Research (in Chinese), 28 (5): 483−494. doi: 10.3878/j.issn.1006-9585.2023.22050
Citation: DU Mengjiao, DENG Hao, WEN Renqiang, et al. 2023. Wind Resource Characteristics and Applicability of Atmospheric Reanalysis Data in Offshore China [J]. Climatic and Environmental Research (in Chinese), 28 (5): 483−494. doi: 10.3878/j.issn.1006-9585.2023.22050

大气再分析资料在中国近海的风资源特征和适用性分析

Wind Resource Characteristics and Applicability of Atmospheric Reanalysis Data in Offshore China

  • 摘要: 基于ECMWF(European Centre for Medium-Range Weather Forecasts)ERA5(Reanalysis version 5)、CFSR(Climate Forecast System Reanalysis)、MERRA2(Modern-Era Retrospective analysis for Research and Applications version 2)3种再分析数据,13个海洋观测站和3个测风塔的观测数据,研究了中国近海风资源时空特征,并讨论了3种再分析数据在中国近海风资源评估中的适用性。结果表明,再分析数据在中国东海和南海的弱风频率比渤海、黄海高,且ERA5在所有海域小于6 m/s的弱风累积概率比CFSR(MERRA2)高39.0%(44.9%)、43.6%(47.5%)、60.7%(41.6%)和47.9%(38.2%)。ERA5、CFSR和MERRA2在中国近海的有效风时空间分布相似,量级都介于84%~95%;3种再分析平均风能密度自北向南呈“低高低”空间分布,其中台湾海峡是WPD大值中心(超过4000 W/m2)。风能稳定性方面,ERA5和CFSR的日变异呈“南弱北强”特征,而MERRA2日变异系数介于1.03~4。适用性分析表明,ERA5整体性能优于CFSR和MERRA2,但MERRA2在再现渤海、南海的风能日波动,CFSR在刻画黄海的有效风时、风能密度和东海、黄海的变异系数时具有一定优势。由此说明不同再分析数据对中国近海风资源不同指标的适用性各有优劣,应根据需要及数据条件,针对不同海域采用不同类的再分析数据开展风资源评估研究及工作。

     

    Abstract: In this study, the characteristics and applicability of wind resources in offshore China are analyzed using the reanalysis data of ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis version 5), CFSR (Climate Forecast System Reanalysis), and MERRA2 (Modern-Era Retrospective analysis for Research and Applications version 2) and the observation data of 13 ocean stations and three wind towers in offshore China. Results showed that the weak wind frequency of reanalysis data in the East China Sea and South China Sea is higher than that in the Bohai Sea and Yellow Sea. The cumulative probabilities of weak wind (<6 m/s) of ERA5 in all sea areas are 38.99% (44.95%), 43.63% (47.54%), 60.74% (41.63%), and 47.94% (38.19%), higher than that of CFSR (MERRA2). In all three reanalyses, the distributions of effective wind time (EW) in offshore China are similar (84%–95%). The value of mean wind energy density (WPD) showed the “low–high–low” spatial distribution from north to south; the Taiwan Strait had a high WPD value (>4000 W/m2). Regarding the stability of wind energy, the daily variation of ERA5 and CFSR is weak in the south and strong in the north, while the daily coefficient of variation (CV) of MERRA2 is between 1.03 and 4. The performance of ERA5 is better than that of CFSR and MERRA2. The MERRA2 reproduces the daily fluctuation of wind energy in the Bohai Sea and the South China Sea. Moreover, CFSR has certain advantages with respect to the EW and WPD of the Yellow Sea and the CV of the East China Sea and the Yellow Sea. According to the above-mentioned conclusions, the applicability of reanalysis data to different indicators of offshore China wind resources varies. Consequently, based on the requirements and data conditions, using different types of reanalysis data for different sea areas in wind resource assessment research and work.

     

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