成印河,彭上博,赵彬彬,等. 两种数据在海洋大气折射环境中的应用评估[J]. 电波科学学报,2023,38(3):491-501. DOI: 10.12265/j.cjors.2022169
      引用本文: 成印河,彭上博,赵彬彬,等. 两种数据在海洋大气折射环境中的应用评估[J]. 电波科学学报,2023,38(3):491-501. DOI: 10.12265/j.cjors.2022169
      CHENG Y H, PENG S B, ZHAO B B, et al. Estimation of two reanalysis datasets on the application to atmospheric refractive environment over the global Sea[J]. Chinese journal of radio science,2023,38(3):491-501. (in Chinese). DOI: 10.12265/j.cjors.2022169
      Citation: CHENG Y H, PENG S B, ZHAO B B, et al. Estimation of two reanalysis datasets on the application to atmospheric refractive environment over the global Sea[J]. Chinese journal of radio science,2023,38(3):491-501. (in Chinese). DOI: 10.12265/j.cjors.2022169

      两种数据在海洋大气折射环境中的应用评估

      Estimation of two reanalysis datasets on the application to atmospheric refractive environment over the global Sea

      • 摘要: 海上大气折射率是影响电波传播的重要因子,是构建电波环境数据库的重要元素. 而再分析数据是其重要的数据源,因此本文利用典型海域的GPS探空数据从两个方面开展了欧洲中期天气预报中心ERA-I(ERA-interim)和美国国家环境预报中心FNL (FiNal)再分析数据在大气折射环境的应用评估,包括直接应用和作为初始场开展数值模拟. 结果表明:在靠近大洋的“开阔”海域,FNL再分析数据对大气折射率环境的适应性更好,其中在北极、南极海域,FNL数据计算的修正大气折射率的均方根误差(root mean square error, RMSE)分别为4.7和2.8 M单位;而在相对封闭的海域,ERA-I再分析数据刻画的大气折射更准确. 大气波导识别方面,ERA-I再分析数据能识别大部分波导,而FNL再分析数据只能识别小部分波导尤其是海上波导,在波导高发的中东地区,二者正确率分别为58.1%和45.4%. 在数值模拟中,两种不同数据初始场对模拟大气折射率的影响不大,各站点计算修正大气折射率的RMSE均小于1 M单位. 研究结果可对不同海域大气折射环境应用提供指导.

         

        Abstract: Atmospheric refractivity over the sea is one of important factors which affects the electromagnetic wave propagation, and is also a basic element which comprises dataset of electromagnetic environment. Since reanalysis data is an indispensable data source to study the atmospheric refractivity, comparative analysis of two kinds of reanalysis datasets, including ERA-I data and reanalysis data (FNL) provided by European Centre for Medium-Range Weather Forecasts (ECMWF) and US National Centers for Environmental Prediction (NCEP) respectively, are performed to analyze the atmospheric refractive environment based on the GPS sounding data in the direct application and numerical simulation as the initial field. The results show that the FNL dataset is better in the open sea facing the ocean, and the root mean square errors of the modified atmospheric refractivity from the FNL data are 4.7 and 2.8 M units in the Arctic and Antarctic respectively.However, in continental or marginal sea, ERA-I reanalysis data depict atmospheric refractive index more accurate and ERA-I data can identify most ducting cases against FNL data especially in the sea. For instance in the Middle East where ducting events are highly prevalent, the correct rates of ducting identified by ERA-I and FNL reanalysis data are 58.1% and 45.4%. On the numerical simulations, the results produced by WRF model with two datasets as initial fields have almost the same errors, and the overall root mean square errors of the modified atmospheric refractivity at each station are less than 1 M units. This results provide a reference for the application of atmospheric refractive environment in different sea areas.

         

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