气象2026，Vol.52Issue(8)：999-1007,9.DOI:10.7519/j.issn.1000-0526.2026.010602
多因子耦合的近地层风廓线指数修正算法
Multi-Factor Coupled Correction Algorithm for the Near-Surface Wind Profile Exponent
摘要
Abstract
Using wind-measuring lidar wind profiler data and the wind profile exponent(WPE)method,we calculate the WPE within the 50-500 m height range under different surface wind conditions in this study.Then the results are validated using data from 50 meteorological stations with observation heights excee-ding 40 m.The results indicate that the WPE retrieved from wind-measuring lidar has the problem of sys-tematic overestimation,with the error magnitude closely related to the building density and height charac-teristics of the observation area.To address this issue,building density and building average height pa-rameters on a 100 m×100 m grid are introduced to develop a multi-factor-driven dynamic correction algo-rithm for the WPE,which overcomes the limitation of traditional methods that rely solely on a single roughness parameter.After correction,91.7％of the wind force calculation errors are confined within the range of 1 level,with 50.1％showing zero error.On this basis,a three-dimensional high-level wind field reconstruction model tailored for urban complex building environments is further developed.This model has a horizontal resolution of 100 m and vertical coverage from 50 to 500 m,enabling real-time monitoring every 5 min and forecast outputs up to 168 h.The model can provide a low-cost,high-precision wind disaster prevention and control technology pathway for urban high-level operations,having business application po-tential and engineering value.关键词
激光测风雷达/风廓线指数/百米级网格建筑物密度/百米级网格建筑物平均高度/近地层高空风监测预报/风灾防控Key words
wind-measuring lidar/wind profile exponent/building density on a 100 m×100 m grid/aver-age height of buildings on a 100 m×100 m grid/near-surface high-level wind field monitoring and forecasting/wind disaster prevention分类
天文与地球科学引用本文复制引用
王婷,张锦城,胡琳..多因子耦合的近地层风廓线指数修正算法[J].气象,2026,52(8):999-1007,9.基金项目
广东省气象联合基金项目(2024A1515510011)和粤港澳大湾区气象科技协同攻关项目(GHMA2024Y05)共同资助 （2024A1515510011）
