Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 2
Articles | Volume 14, issue 2
https://doi.org/10.5194/amt-14-785-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-785-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 2
Research article
 | 
02 Feb 2021
Research article |  | 02 Feb 2021

Smartphone pressure data: quality control and impact on atmospheric analysis

Rumeng Li, Qinghong Zhang, Juanzhen Sun, Yun Chen, Lili Ding, and Tian Wang

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Latest update: 13 Dec 2024
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Short summary
In this paper, we describe a bias-correction method based on machine learning without the need to obtain users' personal information and demonstrate that the method can effectively reduce the bias in smartphone pressure observations. The characteristics of this dataset are discussed, and the potential application of the bias-corrected data is illustrated by the fine-scale analysis of a hailstorm that occurred on 10 June 2016 in Beijing, China.
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