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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/amt-2020-167
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2020-167
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 22 Jun 2020

Submitted as: research article | 22 Jun 2020

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This preprint is currently under review for the journal AMT.

A novel Mie lidar gradient cluster analysis method of nocturnal boundary layer detection during air pollution episodes

Yingchao Zhang, Su Chen, Siying Chen, He Chen, and Pan Guo Yingchao Zhang et al.
  • School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China

Abstract. The observation of the nocturnal boundary layer height (NBLH) plays an important role in air pollution and monitoring. Through 39 days heavily polluted observation experiment over Beijing (China) and exhaustive evaluation of gradient method (GM), wavelet covariance transform method (WCT) and cubic roots gradient method (CRGM), a novel algorithm based on cluster analysis of gradient method (CA-GM) of lidar signal is developed to capture the multilayer structure and achieve stability in the nighttime. The CA-GM highlights its performance in comparison with radiosonde data, the best correlation (0.85), the weakest root mean square error (203 m), and the improved 25 % correlation coefficient by the GM. In comparison with long-term experiments with other algorithms, a reasonable parameter selection can distinguish layers with different properties, such as the cloud layer, elevated aerosol layers, and random noise. Consequently, the CA-GM can automatically deal with the uncertainty of the multiple structures and obtain a stable NBLH with a high time resolution, which expected to contribute to air pollution monitoring and climatologies, as well as model verification.

Yingchao Zhang et al.

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Yingchao Zhang et al.

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Short summary
Air pollution has an important impact on human health, climatic patterns, and the ecological environment. The complexity of the nocturnal boundary layer (NBL) and a companion with the strong physio-chemical effect, which induce a worse polluted episode. Therefore, we present a new approach named cluster analysis of gradient method (CA-GM) to overcome the multi-layer structure and remove the fluctuation of NBLH with raw data resolution.
Air pollution has an important impact on human health, climatic patterns, and the ecological...
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