Articles | Volume 17, issue 11
https://doi.org/10.5194/essd-17-6049-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-6049-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
12 Nov 2025
Data description paper |
| 12 Nov 2025
| 12 Nov 2025
IMPMCT: a dataset of Integrated Multi-source Polar Mesoscale Cyclone Tracks in the Nordic Seas
Runzhuo Fang
College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China
Key Laboratory of High Impact Weather (special), China Meteorological Administration, Changsha, China
Jinfeng Ding
CORRESPONDING AUTHOR
College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China
Key Laboratory of High Impact Weather (special), China Meteorological Administration, Changsha, China
Wenjuan Gao
College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China
Key Laboratory of High Impact Weather (special), China Meteorological Administration, Changsha, China
Key Laboratory of Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Ministry of Natural Resources, Beijing, China
Zhuoqi Chen
School of Geospatial Engineering and Science, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai, China
Chuanfeng Zhao
Department of Atmospheric and Oceanic Sciences, School of Physics, and China Meteorological Administration Tornado Key Laboratory, Peking University, Beijing, China
Haijin Dai
College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China
Key Laboratory of High Impact Weather (special), China Meteorological Administration, Changsha, China
College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China
Key Laboratory of High Impact Weather (special), China Meteorological Administration, Changsha, China
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Geosci. Model Dev., 17, 6867–6886, https://doi.org/10.5194/gmd-17-6867-2024, https://doi.org/10.5194/gmd-17-6867-2024, 2024
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Earth Syst. Sci. Data, 16, 3233–3260, https://doi.org/10.5194/essd-16-3233-2024, https://doi.org/10.5194/essd-16-3233-2024, 2024
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Atmos. Meas. Tech., 16, 4101–4114, https://doi.org/10.5194/amt-16-4101-2023, https://doi.org/10.5194/amt-16-4101-2023, 2023
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Geosci. Model Dev., 16, 4677–4697, https://doi.org/10.5194/gmd-16-4677-2023, https://doi.org/10.5194/gmd-16-4677-2023, 2023
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Tianmeng Chen, Zhanqing Li, Ralph A. Kahn, Chuanfeng Zhao, Daniel Rosenfeld, Jianping Guo, Wenchao Han, and Dandan Chen
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A convective cloud identification process is developed using geostationary satellite data from Himawari-8.
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Yikun Yang, Chuanfeng Zhao, Quan Wang, Zhiyuan Cong, Xingchuan Yang, and Hao Fan
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Xingchuan Yang, Chuanfeng Zhao, Yikun Yang, and Hao Fan
Atmos. Chem. Phys., 21, 3803–3825, https://doi.org/10.5194/acp-21-3803-2021, https://doi.org/10.5194/acp-21-3803-2021, 2021
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Xingchuan Yang, Chuanfeng Zhao, Yikun Yang, Xing Yan, and Hao Fan
Atmos. Chem. Phys., 21, 3833–3853, https://doi.org/10.5194/acp-21-3833-2021, https://doi.org/10.5194/acp-21-3833-2021, 2021
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Using long-term multi-source data, this study shows significant impacts of fire events on aerosol properties over Australia. The contribution of carbonaceous aerosols to the total was 26 % of the annual average but larger (30–43 %) in September–December; smoke and dust are the two dominant aerosol types at different heights in southeastern Australia for the 2019 fire case. These findings are helpful for understanding aerosol climate effects and improving climate modeling in Australia in future.
Shihe Ren, Xi Liang, Qizhen Sun, Hao Yu, L. Bruno Tremblay, Bo Lin, Xiaoping Mai, Fu Zhao, Ming Li, Na Liu, Zhikun Chen, and Yunfei Zhang
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Zhanshan Ma, Chuanfeng Zhao, Jiandong Gong, Jin Zhang, Zhe Li, Jian Sun, Yongzhu Liu, Jiong Chen, and Qingu Jiang
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Short summary
Integrated Multi-source Polar Mesoscale Cyclone Tracks (IMPMCT) is a dataset containing a 24-year record (2001–2024) of polar storms in the Nordic Seas. These storms, called Polar Mesoscale Cyclones (PMCs), sometimes cause extreme winds and waves, threatening marine operations. IMPMCT combines remote sensing measurements and reanalysis data to construct a comprehensive PMCs archive. It includes 1110 PMCs tracks, 16 001 cloud patterns, and 4472 wind records, providing fundamental data for advancing our understanding of their development mechanisms.
Integrated Multi-source Polar Mesoscale Cyclone Tracks (IMPMCT) is a dataset containing a...
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