Estimation of Atmospheric Boundary Layer Turbulence Parameters over the South China Sea Based on Multi-Source Data

Understanding optical turbulence within the atmospheric boundary layer (ABL) is essential for refining atmospheric motion analyses, enhancing numerical weather prediction models, and improving light propagation assessments. This study develops an optical turbulence model for the boundary layer over the South China Sea (SCS) by integrating multiple observational and reanalysis datasets, including ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF), radiosonde observations, coherent Doppler wind lidar (CDWL), and ultrasonic anemometer (CSAT3) measurements. Utilizing Monin–Obukhov Similarity Theory (MOST) as the theoretical foundation, the model’s performance is evaluated by comparing its outputs with the observed diurnal cycle of near-surface optical turbulence. Error analysis indicates a root mean square error (RMSE) of less than 1 and a correlation coefficient exceeding 0.6, validating the model’s predictive capability. Moreover, this study demonstrates the feasibility of employing ERA5-derived temperature and pressure profiles as alternative inputs for optical turbulence modeling while leveraging CDWL’s high-resolution observational capacity for all-weather turbulence characterization. A comprehensive statistical analysis of the atmospheric refractive index structure constant (Cn2) from November 2019 to September 2020 highlights its critical implications for optoelectronic system optimization and astronomical observatory site selection in the SCS region.

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Publication Details

Journal
Remote Sensing
Published
2025-06-02
DOI
https://doi.org/10.3390/rs17111929
Citations
3
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
3.32

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article

Estimation of Atmospheric Boundary Layer Turbulence Parameters over the South China Sea Based on Multi-Source Data

Kaixuan Yang, Ningquan Weng, Shiyong Shao, Shengcheng Cui et al.
3 citations
Remote Sensing
Atmospheric aerosols and clouds
3.32
article

Estimation of Atmospheric Boundary Layer Turbulence Parameters over the South China Sea Based on Multi-Source Data

Kaixuan Yang, Ningquan Weng, Shiyong Shao, Shengcheng Cui, Tao Luo, Hanjiu Zhang, Ying Liu, Xuebing Li, Liming Zhu
article en
3 citations

Abstract

Understanding optical turbulence within the atmospheric boundary layer (ABL) is essential for refining atmospheric motion analyses, enhancing numerical weather prediction models, and improving light propagation assessments. This study develops an optical turbulence model for the boundary layer over the South China Sea (SCS) by integrating multiple observational and reanalysis datasets, including ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF), radiosonde observations, coherent Doppler wind lidar (CDWL), and ultrasonic anemometer (CSAT3) measurements. Utilizing Monin–Obukhov Similarity Theory (MOST) as the theoretical foundation, the model’s performance is evaluated by comparing its outputs with the observed diurnal cycle of near-surface optical turbulence. Error analysis indicates a root mean square error (RMSE) of less than 1 and a correlation coefficient exceeding 0.6, validating the model’s predictive capability. Moreover, this study demonstrates the feasibility of employing ERA5-derived temperature and pressure profiles as alternative inputs for optical turbulence modeling while leveraging CDWL’s high-resolution observational capacity for all-weather turbulence characterization. A comprehensive statistical analysis of the atmospheric refractive index structure constant (Cn2) from November 2019 to September 2020 highlights its critical implications for optoelectronic system optimization and astronomical observatory site selection in the SCS region.

Remote SensingVol. 17(11)
University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Anhui Institute of Optics and Fine Mechanics (CN)
Natural Science Foundation for Distinguished Young Scholars of Anhui Province, National Natural Science Foundation of China, Chinese Academy of Sciences
Life below water
Openalex Percentile: Top 8%
Atmospheric aerosols and clouds
3.32
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