首页|基于风廓线雷达的大气扩散条件参数研究

基于风廓线雷达的大气扩散条件参数研究

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利用河北省13套风廓线雷达资料,基于大气动力学原理和动力条件反演算法,计算出垂直风切变、散度、涡度和边界层通风量等参数产品.通过与探空资料计算结果对比,以及与近地面浓度联合分析,对4种参数算法进行检验,结果表明,反演产品的变化趋势和特征表现较为合理.以2022年11月9-11日河北境内一次区域PM2.5(空气动力学直径小于等于2.5μm的颗粒物)污染过程为例,4种产品的具体分析结果表明:在污染积累过程中3 km以下垂直风切变从对角线到右下角依次减小,右下角数值多小于5 m/(s·km);涡度、散度数值基本都在20×10-5s-1以下,950 hPa等压面以下多小于15×10-5s-1,静稳形势明显;边界层通风量数值小于3000 m2/s.在污染物消散前垂直风切变整层数值升至10 m/(s·km)以上,2~3 km高度与0~1 km之间10 m/(s·km)以上风切变大值区对污染消散敏感性最强;850 hPa高空涡度、散度数值首先增大到30×10-5s-1以上,当20×10-5s-1以上涡度和散度区域扩展到边界层以内时,近地面PM2.5浓度迅速下降;边界层通风量数值升至4000 m2/s时,污染物浓度达标,沿着冷空气传输路径,下游站点数值增大滞后,多站点联合分析可用于下游站点的污染消散预报.
Research on Atmospheric Diffusion Condition Parameters Based on Wind Profile Radar
To harness the benefits derived from the high spatial and temporal resolution of vertically continuous wind profile radar observations and exploit its capacity for monitoring atmospheric diffusion conditions during pollution events,this paper calculates parameters such as vertical wind shear,divergence,vorticity,and boundary layer ventilation by utilising 13 sets of wind profile radar data in Hebei Province.The computations are based on the principles of atmospheric dynamics and the dynamic conditions inversion algorithm.By comparing the results with sounding data and analysing them in conjunction with near-surface PM2.5 concentration,the four parameter algorithms are examined.The results show that the variations and characteristics of the inversion products are reasonably represented,effectively reflecting the evolution of atmospheric pollution conditions.However,due to disparities in resolution and detection methods among different observational datasets,substantial discrepancies exist in the results derived from various datasets.Therefore,it is imperative to maintain data consistency when conducting analyses.Taking the regional PM2.5 pollution event in Hebei from 9 to 11 November 2022 as an example,through multi-site joint application,the evolution characteristics of the four products in this process indicate the following:during the pollution accumulation process,vertical wind shear below 3 km decreased from the diagonal to the lower right corner,with most values below 5 m/(s·km).Vorticity and divergence values were mostly within 20 × 10-5 s-1,and less than 15 × 10-5 s-1for distances below the 950 hPa isobaric surface,indicating a stable meteorological situation.Boundary layer ventilation was less than 3000 m2/s.Before the pollutant dispersal,vertical wind shear increased to above 10 m/(s.km)throughout the entire layer.The region with wind shear greater than 10 m/(s.km)between 2-3 km height and 0-1 km above the ground showed the strongest sensitivity to pollutant dispersion.Vorticity and divergence above the 850 hPa isobaric surface first increased to above 30 × 10-5 s-1,and when vorticity and divergence above 20 × 10-5 s-1 extended within the boundary layer,the near-surface PM2.5 concentration rapidly decreased.When boundary layer ventilation reached 4000 m2/s,pollutant concentrations met the standards.The values at downstream stations increased significantly with a noticeable delay along the cold air transmission path,thus multi-station joint analysis could be used for pollution dispersion forecasts at downstream sites.By comparing with the data of airborne sounding and near-surface wind field,the wind profile data had obvious advantages of high temporal and spatial resolution.However,these parameters exclusively responded to atmospheric dynamic conditions and did not account for the evolving principles governing the weather system.The application was most effective when used in conjunction with the prevailing circulation patterns and the diagnostic analysis of the weather system.

wind profile radarvertical wind shearvorticitydivergenceboundary layer ventilation

赵娜、杨雨灵、焦亚音、张智、赵玉广

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河北省气象与生态环境重点实验室,石家庄 050021

中国气象局雄安大气边界层重点开放实验室,雄安新区 071800

河北省气象灾害防御和环境气象中心,石家庄 050021

中国气象局邢台大气环境野外科学试验基地,邢台 054000

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风廓线雷达 垂直风切变 涡度 散度 边界层通风量

国家重点专项河北省气象局科研项目

2016YFC020330222ky03

2024

气象科技
中国气象科学研究院 北京市气象局 中国气象局大气探测技术中心 国家卫星气象中心 国家气象信息中心

气象科技

CSTPCD
影响因子:1.154
ISSN:1671-6345
年,卷(期):2024.52(4)
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