摘要
文章利用广西壮族自治区北海国家气候观象台的风廓线雷达和L波段探空雷达2022年的探空数据,建立了以风廓线雷达测风数据为自变量、L波段探空雷达测风数据为因变量的线性回归模型。研究结果显示,通过建立线性回归模型,L波段探空雷达和风廓线雷达测风数据的相关系数得到了提高,标准差有效降低。线性回归模型能够提升L波段探空雷达和风廓线雷达测风数据的一致性,为更好地实现L波段探空雷达和风廓线雷达测风数据的融合和同化应用提供基础。
The article uses the wind profile radar and L-band sounding radar data from the Beihai National Climate Observatory in Guangxi Zhuang Autonomous Region in 2022 to establish a linear regression model with wind profile radar data as the independent variable and L-band sounding radar data as the dependent variable.The research results show that by establishing a linear regression model,the correlation coefficient between wind measurement data from L-band sounding radar and wind profile radar has been improved,and the standard deviation has been effectively reduced.The linear regression model can improve the consistency of wind measurement data from L-band sounding radar and wind profile radar,providing a foundation for better integration and assimilation of wind measurement data from L-band sounding radar and wind profile radar.
作者
韩宇龙
尹海燕
Han Yulong;Yin Haiyan(Guangxi Zhuang Autonomous Region Meteorological Technology Equipment Center,Nanning 530022;Beihai Meteorological Bureau,Beihai 536000)
出处
《气象水文海洋仪器》
2024年第6期9-12,共4页
Meteorological,Hydrological and Marine Instruments
基金
广西气象科研计划项目“北海国家气候观象台风廓线雷达与L波段探空雷达测风数据一致性研究”(桂气科2023M06)资助。
