Construction and Application Verification of a High-Resolution Wind Resource Dataset in the Guangdong Sea Area Based on Three-Dimensional Barnes Assimilation
NIU Tao
HU Jianglin
ZHANG Hao
CHEN Wenchao
YI Kan
JIANG Yiliang
HUANG Congwu
WEN Renqiang
YUAN Chunhong
SONG Lili
Abstract：Aiming at the scarcity of offshore observations in the Guangdong sea area and the demand for high-precision,long-term data in wind power development,this study collected gradient wind data from 7 observation sites(comprising wind measurement towers and lidars)during 2012-2021.It developed a three-dimensional Barnes objective analysis method and a multi-source data fusion and assimilation technology,and constructed a high-resolution three-dimensional grid dataset(1 000 m horizontal resolution;10 m and 30 m vertical levels)and hourly wind field data at 20 reference points based on ERA5 reanalysis data.Error analysis shows that the correlation coefficient between the fused-assimilated wind speed and the observed wind speed are all≥0.82(with an average of 0.913),the average root mean square error(RMSE)is 1.20 m·s-1,and the wind speed error at heights above 30-40 m is≤1 m·s-1.The accuracy is significantly higher than that of ERA5 and power-law fitting.The average RMSE of wind direction is 20.2 °.The dataset clearly presents the spatiotemporal distribution characteristics of wind speed,such as increasing with the offshore distance and exhibiting annual dual peaks in winter and summer(winter>summer).It can also effectively depict the diurnal variation of wind fields,the passage of key weather systems(including typhoons),and climate system features such as monsoons and land-sea breezes.This dataset can provide reliable data support for wind farm planning,site selection,and wind energy resource assessment in the Guangdong sea area.
Keywords：multi-source observationsthree-dimensional Barnes fusion assimilationhigh-resolution wind field datasetwind profile power-law modelGuangdong sea areaerror analysis
Publication Date：2025-12-31
Online Publishing Date：2026-01-12(First online date of this platform, not the publication date of the document)
Pages：13( 745-757 )