Articles | Volume 13, issue 10
https://doi.org/10.5194/gmd-13-4639-2020
https://doi.org/10.5194/gmd-13-4639-2020
Development and technical paper
 | 
30 Sep 2020
Development and technical paper |  | 30 Sep 2020

Image-processing-based atmospheric river tracking method version 1 (IPART-1)

Guangzhi Xu, Xiaohui Ma, Ping Chang, and Lin Wang

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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Guangzhi XU on behalf of the Authors (07 Aug 2020)  Author's response    Manuscript
ED: Publish as is (21 Aug 2020) by Paul Ullrich
AR by Guangzhi XU on behalf of the Authors (22 Aug 2020)  Author's response    Manuscript
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Short summary
We observed considerable limitations in existing atmospheric river (AR) detection methods and looked into other disciplines for inspirations of tackling the AR detection problem. A new method is derived from an image-processing technique and encodes the spatiotemporal-scale information of AR systems, which is a key physical ingredient of ARs that is more stable than the vapor flux intensities, making it more suitable for climate-scale studies when models often have different biases.