Articles | Volume 13, issue 10
https://doi.org/10.5194/gmd-13-4639-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-4639-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Image-processing-based atmospheric river tracking method version 1 (IPART-1)
Guangzhi Xu
CORRESPONDING AUTHOR
Key Laboratory of Physical Oceanography, Institute for Advanced Ocean Studies,
Ocean University of China and Qingdao National Laboratory for Marine
Science and Technology, Qingdao, China
Xiaohui Ma
Key Laboratory of Physical Oceanography, Institute for Advanced Ocean Studies,
Ocean University of China and Qingdao National Laboratory for Marine
Science and Technology, Qingdao, China
The International Laboratory for
High-Resolution Earth System Prediction, Texas A&M University, College
Station, TX, USA
Ping Chang
Department of Oceanography and Department of Atmospheric Sciences,
Texas A&M University, College Station,
TX, USA
The International Laboratory for
High-Resolution Earth System Prediction, Texas A&M University, College
Station, TX, USA
Center for Monsoon System Research, Institute of Atmospheric
Physics, Chinese Academy of Sciences, Beijing, China
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Cited
23 citations as recorded by crossref.
- Objective identification of tropical cyclone‐induced remote moisture transport using digraphs S. Xiao et al. 10.1002/qj.4612
- Response of lacustrine glacier dynamics to atmospheric forcing in the Cordillera Darwin L. Langhamer et al. 10.1017/jog.2024.14
- Atmospheric river, a term encompassing different meteorological patterns L. Gimeno et al. 10.1002/wat2.1558
- A cluster analysis of cold-season atmospheric river tracks over the North Atlantic and their linkages to extreme precipitation and winds C. Li et al. 10.1007/s00382-022-06297-y
- Scalable Feature Extraction and Tracking (SCAFET): a general framework for feature extraction from large climate data sets A. Nellikkattil et al. 10.5194/gmd-17-301-2024
- Linkage between anomalies of pre-summer thawing of frozen soil over the Tibetan Plateau and summer precipitation in East Asia Y. Li et al. 10.1088/1748-9326/ac2f1c
- IPART: A Python Package for Image-Processing based Atmospheric River Tracking G. Xu et al. 10.21105/joss.02407
- Atmospheric rivers and associated extreme rainfall over Morocco A. Khouakhi et al. 10.1002/joc.7676
- A regionally refined quarter-degree global atmospheric rivers database based on ERA5 B. Guan & D. Waliser 10.1038/s41597-024-03258-4
- Changes in Moisture Sources of Atmospheric Rivers Landfalling the Iberian Peninsula With WRF‐FLEXPART J. Fernández‐Alvarez et al. 10.1029/2022JD037612
- The Role of Atmospheric Rivers in Antarctic Sea Ice Variations K. Liang et al. 10.1029/2022GL102588
- Extreme atmospheric rivers in a warming climate S. Wang et al. 10.1038/s41467-023-38980-x
- Response of the upper ocean to northeast Pacific atmospheric rivers under climate change C. Shields et al. 10.1038/s43247-024-01774-0
- Association Between Extreme Atmospheric Anomalies Over Antarctic Sea Ice, Southern Ocean Polar Cyclones and Atmospheric Rivers E. Hepworth et al. 10.1029/2021JD036121
- High‐Tide Floods and Storm Surges During Atmospheric Rivers on the US West Coast C. Piecuch et al. 10.1029/2021GL096820
- Improving the Understanding of Atmospheric River Water Vapor Transport Using a Three‐Dimensional Straightened Composite Analysis G. Xu et al. 10.1029/2021JD036159
- The increasing influence of atmospheric moisture transport on hydrometeorological extremes in the Euromediterranean region with global warming L. Gimeno-Sotelo et al. 10.1038/s43247-024-01787-9
- Leading Modes of Wintertime North Pacific Atmospheric Rivers and Their Drivers G. Xu et al. 10.1029/2022JD037719
- Increased amplitude of atmospheric rivers and associated extreme precipitation in ultra-high-resolution greenhouse warming simulations A. Nellikkattil et al. 10.1038/s43247-023-00963-7
- A Comparison between the Kuroshio Extension and Pineapple Express Atmospheric Rivers Affecting the West Coast of North America S. Wang et al. 10.1175/JCLI-D-21-0554.1
- A glacial lake outburst floods hazard assessment in the Patagonian Andes combining inventory data and case-studies B. Colavitto et al. 10.1016/j.scitotenv.2023.169703
- Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1 A. Mahesh et al. 10.5194/gmd-17-3533-2024
- SAR-UNet: A Model of Atmospheric River Recognition Network Based on Spatial Attention Mechanism 月. 罗 10.12677/CSA.2023.134081
22 citations as recorded by crossref.
- Objective identification of tropical cyclone‐induced remote moisture transport using digraphs S. Xiao et al. 10.1002/qj.4612
- Response of lacustrine glacier dynamics to atmospheric forcing in the Cordillera Darwin L. Langhamer et al. 10.1017/jog.2024.14
- Atmospheric river, a term encompassing different meteorological patterns L. Gimeno et al. 10.1002/wat2.1558
- A cluster analysis of cold-season atmospheric river tracks over the North Atlantic and their linkages to extreme precipitation and winds C. Li et al. 10.1007/s00382-022-06297-y
- Scalable Feature Extraction and Tracking (SCAFET): a general framework for feature extraction from large climate data sets A. Nellikkattil et al. 10.5194/gmd-17-301-2024
- Linkage between anomalies of pre-summer thawing of frozen soil over the Tibetan Plateau and summer precipitation in East Asia Y. Li et al. 10.1088/1748-9326/ac2f1c
- IPART: A Python Package for Image-Processing based Atmospheric River Tracking G. Xu et al. 10.21105/joss.02407
- Atmospheric rivers and associated extreme rainfall over Morocco A. Khouakhi et al. 10.1002/joc.7676
- A regionally refined quarter-degree global atmospheric rivers database based on ERA5 B. Guan & D. Waliser 10.1038/s41597-024-03258-4
- Changes in Moisture Sources of Atmospheric Rivers Landfalling the Iberian Peninsula With WRF‐FLEXPART J. Fernández‐Alvarez et al. 10.1029/2022JD037612
- The Role of Atmospheric Rivers in Antarctic Sea Ice Variations K. Liang et al. 10.1029/2022GL102588
- Extreme atmospheric rivers in a warming climate S. Wang et al. 10.1038/s41467-023-38980-x
- Response of the upper ocean to northeast Pacific atmospheric rivers under climate change C. Shields et al. 10.1038/s43247-024-01774-0
- Association Between Extreme Atmospheric Anomalies Over Antarctic Sea Ice, Southern Ocean Polar Cyclones and Atmospheric Rivers E. Hepworth et al. 10.1029/2021JD036121
- High‐Tide Floods and Storm Surges During Atmospheric Rivers on the US West Coast C. Piecuch et al. 10.1029/2021GL096820
- Improving the Understanding of Atmospheric River Water Vapor Transport Using a Three‐Dimensional Straightened Composite Analysis G. Xu et al. 10.1029/2021JD036159
- The increasing influence of atmospheric moisture transport on hydrometeorological extremes in the Euromediterranean region with global warming L. Gimeno-Sotelo et al. 10.1038/s43247-024-01787-9
- Leading Modes of Wintertime North Pacific Atmospheric Rivers and Their Drivers G. Xu et al. 10.1029/2022JD037719
- Increased amplitude of atmospheric rivers and associated extreme precipitation in ultra-high-resolution greenhouse warming simulations A. Nellikkattil et al. 10.1038/s43247-023-00963-7
- A Comparison between the Kuroshio Extension and Pineapple Express Atmospheric Rivers Affecting the West Coast of North America S. Wang et al. 10.1175/JCLI-D-21-0554.1
- A glacial lake outburst floods hazard assessment in the Patagonian Andes combining inventory data and case-studies B. Colavitto et al. 10.1016/j.scitotenv.2023.169703
- Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1 A. Mahesh et al. 10.5194/gmd-17-3533-2024
1 citations as recorded by crossref.
Latest update: 16 Nov 2024
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.
We observed considerable limitations in existing atmospheric river (AR) detection methods and...