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 article
| 
12 Nov 2025
Data description article |
| 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
Related authors
No articles found.
Yi Liu, Yunhan Yang, Haijin Dai, Jun Zhao, and Qiang Li
EGUsphere, https://doi.org/10.5194/egusphere-2026-153, https://doi.org/10.5194/egusphere-2026-153, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
The East Greenland Current (EGC) typically flows equatorward at high speeds. In autumn, a branch of EGC strengthened, reaching an intensity comparable to that of the main current. Sea ice expands as temperatures drop, while ocean waves continue to propagate toward the ice zone and dissipate at the ice edge via wave–ice interactions, transferring energy to the sea ice and ocean. This mechanism accounts for strengthening of the EGC branch and enhances eddy activity through barotropic instability.
Pingyi Dong, Xingwen Jiang, Xingbing Zhao, Yuanchang Dong, Jiafeng Zheng, Chun Hu, Guolu Gao, Lei Liu, Shulei Li, and Lingbing Bu
Atmos. Meas. Tech., 19, 1407–1419, https://doi.org/10.5194/amt-19-1407-2026, https://doi.org/10.5194/amt-19-1407-2026, 2026
Short summary
Short summary
A method is developed and validated for retrieving vertical profiles of the raindrop size distributions (DSD) parameters from a single-frequency Ka-band radar in this study. Some unique characteristics of the vertical profiles of DSD parameters in the eastern Tibetan Plateau are found. The empirical relationships for quantitative precipitation estimates and attenuation correction in the eastern Tibetan Plateau with Ka-band radar are derived.
Qiaomin Pei, Chuanfeng Zhao, Xing Yan, Xingchuan Yang, Annan Chen, and Xin Wan
EGUsphere, https://doi.org/10.5194/egusphere-2026-689, https://doi.org/10.5194/egusphere-2026-689, 2026
Short summary
Short summary
Using satellite observations from 2012 to 2024, we assessed global patterns of forest fire activity and smoke and examined how elevation influences these patterns. Fire occurrence has increased slightly and mainly produces fine particles. Fires are most frequent at low elevations, while smoke is greater at mid-elevations due to lifting and terrain transport. These findings show that topography strongly shapes fire impacts and improves wildfire risk and climate assessment.
Linying Ma, Jun Wang, Zishan Wang, Qian Zhang, Ran Yan, Zhi Huang, Yabin Ye, Hao Zheng, Shuyue Xiao, Xiaokang Zhang, Zhenhai Li, Hongzhang Wang, Tao Wei, Haijin Dai, Meirong Wang, and Xiuying Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2026-142, https://doi.org/10.5194/egusphere-2026-142, 2026
Short summary
Short summary
From April to June 2024, the North China Plain experienced an extreme dry-hot event. Satellite data showed rapid crop growth in April but record-low levels in June under combined heat and drought stress. Consistent with vegetation signals, Yield statistics and field observations confirmed higher winter wheat yields but lower summer maize yields. Growth was enhanced by warming and carryover in April, dominated by carryover in May, and strongly limited by high vapor pressure deficit in June.
Jinfeng Ding, Yuan Shang, Yulong Shan, Jingkai Ma, Jin Ye, Xichuan Liu, Lei Liu, and Xiaoqiao Wang
The Cryosphere, 20, 629–646, https://doi.org/10.5194/tc-20-629-2026, https://doi.org/10.5194/tc-20-629-2026, 2026
Short summary
Short summary
This study employed the numerical model to simulate an intense blowing snow event near Zhongshan Station, East Antarctica, from 15–17 July 2022. While primarily driven by a mid-latitude cyclone, the event’s evolution was strongly modulated by complex local topography, which influenced airflow and enhanced snow transport. Terrain-induced uplift intensified snowfall and prolonged blizzard conditions, underscoring the importance of high-resolution modeling for Antarctic weather research.
Chengyan Liu, Zhaomin Wang, Dake Chen, Xianxian Han, Hengling Leng, Xi Liang, Liangjun Yan, Xiang Li, Craig Stevens, Andrew Hogg, Kazuya Kusahara, Kaihe Yamazaki, Kay Ohshima, Meng Zhou, Xiao Cheng, Dongxiao Wang, Changming Dong, Jiping Liu, Qinghua Yang, Xichen Li, Ruibo Lei, Minghu Ding, Zhaoru Zhang, Dujuan Kang, Di Qi, Tongya Liu, Jihai Dong, Lu An, Ru Chen, Tong Zhang, Xiaoming Hu, Bo Han, Haibo Bi, Qi Shu, Longjiang Mu, Shiming Xu, Hu Yang, Hailong Liu, Tingfeng Dou, Zhixuan Feng, Lei Zheng, Xueyuan Tang, Guitao Shi, Yongqing Cai, Bingrui Li, Yang Wu, Xia Lin, Wenjin Sun, Yu Liu, Kai Yu, Yu Zhang, Weizeng Shao, Xiaoyu Wang, Shaojun Zheng, Chengyi Yuan, Chunxia Zhou, Jian Liu, Yang Liu, Yue Xia, Xiaoyu Pan, Jiabao Zeng, Kechen Liu, Jiahao Fan, Chen Cheng, and Qi Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-6487, https://doi.org/10.5194/egusphere-2025-6487, 2026
Short summary
Short summary
We developed a high-resolution computer model to simulate how the ocean, sea ice, and ice shelves interact around Antarctica. This helps us understand their critical role in global climate and sea-level rise. Our model successfully captures essential features like major currents and seasonal ice changes. Despite some remaining biases, it provides a useful tool for predicting future changes in this vital and rapidly evolving region.
Guokun Lyu, Longjiang Mu, Armin Koehl, Ruibo Lei, Xi Liang, and Chuanyu Liu
Geosci. Model Dev., 18, 9451–9468, https://doi.org/10.5194/gmd-18-9451-2025, https://doi.org/10.5194/gmd-18-9451-2025, 2025
Short summary
Short summary
In the sea ice-ocean models, errors in the parameters and missing spatiotemporal variations contribute to the deviations between the simulations and the observations. We extended an adjoint method to optimize spatiotemporally varying parameters together with the atmosphere forcing and the initial conditions using satellite and in-situ observations. Seasonally, this scheme demonstrates a more prominent advantage in mid-autumn and show great potential for accurately reproducing the Arctic changes.
Qiaomin Pei, Chuanfeng Zhao, Yikun Yang, Annan Chen, Zhiyuan Cong, Xin Wan, Haotian Zhang, and Guangming Wu
Atmos. Chem. Phys., 25, 10443–10456, https://doi.org/10.5194/acp-25-10443-2025, https://doi.org/10.5194/acp-25-10443-2025, 2025
Short summary
Short summary
This study investigates the impact of smoke on atmospheric warming over the Himalayas and Tibetan Plateau (HTP) using MODIS fire data, ground-based and satellite aerosol observations, and model simulations. It finds that smoke aerosols, predominantly concentrated between 6 and 8 km in the mid-troposphere over southern HTP, likely alter regional atmospheric stability by modifying the vertical temperature profile, as indicated by a reduced lapse rate.
Jingye Ren, Songjian Zou, Honghao Xu, Guiquan Liu, Zhe Wang, Anran Zhang, Chuanfeng Zhao, Min Hu, Dongjie Shang, Lizi Tang, Ru-Jin Huang, Yele Sun, and Fang Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1483, https://doi.org/10.5194/egusphere-2025-1483, 2025
Preprint archived
Short summary
Short summary
In this study, a new framework of cloud condensation nuclei (CCN) prediction in polluted region has been developed and it achieves well prediction of hourly-to-yearly scale across North China Plain. The study reveals a significant long-term decreasing trend of CCN concentration at typical supersaturations due to a rapid reduction in aerosol concentrations from 2014 to 2018. This improvement of our new model would be helpful to aerosols climate effect assessment in models.
Jiayi Shi, Xichuan Liu, Lei Liu, Liying Liu, and Peng Wang
Atmos. Meas. Tech., 18, 2261–2278, https://doi.org/10.5194/amt-18-2261-2025, https://doi.org/10.5194/amt-18-2261-2025, 2025
Short summary
Short summary
The Three-Dimensional Precipitation Particle Imager (3D-PPI) was introduced as a new instrument to measure the three-dimensional shape, size, and falling velocity of precipitation particles. Field experiments of the 3D-PPI were conducted in Tulihe, China, during the winter of 2023 to 2024. More than 880 000 snowflakes in a typical snowfall case lasting 13 h were recorded. It shows potential applications in atmospheric science, polar research, and other fields.
Fu Zhao, Xi Liang, Zhongxiang Tian, Ming Li, Na Liu, and Chengyan Liu
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
Short summary
Short summary
In this work, we introduce a newly developed Antarctic sea ice forecasting system, namely the Southern Ocean Ice Prediction System (SOIPS). The system is based on a regional sea ice‒ocean‒ice shelf coupled model and can assimilate sea ice concentration observations. By assessing the system's performance in sea ice forecasts, we find that the system can provide reliable Antarctic sea ice forecasts for the next 7 d and has the potential to guide ship navigation in the Antarctic sea ice zone.
Hongfei Hao, Kaicun Wang, Chuanfeng Zhao, Guocan Wu, and Jing Li
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
Short summary
Short summary
In this study, we employed a machine learning technique to derive daily aerosol optical depth from hourly visibility observations collected at more than 5000 airports worldwide from 1959 to 2021 combined with reanalysis meteorological parameters.
Wei Huang, Lei Liu, Bin Yang, Shuai Hu, Wanying Yang, Zhenfeng Li, Wantong Li, and Xiaofan Yang
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
Short summary
Short summary
To improve the retrieval speed of the AERI optimal estimation (AERIoe) method, a fast-retrieval algorithm named Fast AERIoe is proposed on the basis of the findings that the change in Jacobians during the retrieval process had little effect on the performance of AERIoe. The results of the experiment show that the retrieved profiles from Fast AERIoe are comparable to those of AERIoe and that the retrieval speed is significantly improved, with the average retrieval time reduced by 59 %.
Bin Mu, Xiaodan Luo, Shijin Yuan, and Xi Liang
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
Short summary
Short summary
To improve the long-term forecast skill for sea ice extent (SIE), we introduce IceTFT, which directly predicts 12 months of averaged Arctic SIE. The results show that IceTFT has higher forecasting skill. We conducted a sensitivity analysis of the variables in the IceTFT model. These sensitivities can help researchers study the mechanisms of sea ice development, and they also provide useful references for the selection of variables in data assimilation or the input of deep learning models.
Hao Fan, Xingchuan Yang, Chuanfeng Zhao, Yikun Yang, and Zhenyao Shen
Atmos. Chem. Phys., 23, 7781–7798, https://doi.org/10.5194/acp-23-7781-2023, https://doi.org/10.5194/acp-23-7781-2023, 2023
Short summary
Short summary
Using 20-year multi-source data, this study shows pronounced regional and seasonal variations in fire activities and emissions. Seasonal variability of fires is larger with increasing latitude. The increase in temperature in the Northern Hemisphere's middle- and high-latitude forest regions was primarily responsible for the increase in fires and emissions, while the changes in fire occurrence in tropical regions were more influenced by the decrease in precipitation and relative humidity.
Ming Li, Husi Letu, Hiroshi Ishimoto, Shulei Li, Lei Liu, Takashi Y. Nakajima, Dabin Ji, Huazhe Shang, and Chong Shi
Atmos. Meas. Tech., 16, 331–353, https://doi.org/10.5194/amt-16-331-2023, https://doi.org/10.5194/amt-16-331-2023, 2023
Short summary
Short summary
Influenced by the representativeness of ice crystal scattering models, the existing terahertz ice cloud remote sensing inversion algorithms still have significant uncertainties. We developed an ice cloud remote sensing retrieval algorithm of the ice water path and particle size from aircraft-based terahertz radiation measurements based on the Voronoi model. Validation revealed that the Voronoi model performs better than the sphere and hexagonal column models.
Yufang Ye, Yanbing Luo, Yan Sun, Mohammed Shokr, Signe Aaboe, Fanny Girard-Ardhuin, Fengming Hui, Xiao Cheng, and Zhuoqi Chen
The Cryosphere, 17, 279–308, https://doi.org/10.5194/tc-17-279-2023, https://doi.org/10.5194/tc-17-279-2023, 2023
Short summary
Short summary
Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. This study gives a systematic inter-comparison and evaluation of eight SITY products. Main results include differences in SITY products being significant, with average Arctic multiyear ice extent up to 1.8×106 km2; Ku-band scatterometer SITY products generally performing better; and factors such as satellite inputs, classification methods, training datasets and post-processing highly impacting their performance.
Qi Liang, Wanxin Xiao, Ian Howat, Xiao Cheng, Fengming Hui, Zhuoqi Chen, Mi Jiang, and Lei Zheng
The Cryosphere, 16, 2671–2681, https://doi.org/10.5194/tc-16-2671-2022, https://doi.org/10.5194/tc-16-2671-2022, 2022
Short summary
Short summary
Using multi-temporal ArcticDEM and ICESat-2 altimetry data, we document changes in surface elevation of a subglacial lake basin from 2012 to 2021. The long-term measurements show that the subglacial lake was recharged by surface meltwater and that a rapid drainage event in late August 2019 induced an abrupt ice velocity change. Multiple factors regulate the episodic filling and drainage of the lake. Our study also reveals ~ 64 % of the surface meltwater successfully descended to the bed.
Yu Liang, Haibo Bi, Haijun Huang, Ruibo Lei, Xi Liang, Bin Cheng, and Yunhe Wang
The Cryosphere, 16, 1107–1123, https://doi.org/10.5194/tc-16-1107-2022, https://doi.org/10.5194/tc-16-1107-2022, 2022
Short summary
Short summary
A record minimum July sea ice extent, since 1979, was observed in 2020. Our results reveal that an anomalously high advection of energy and water vapor prevailed during spring (April to June) 2020 over regions with noticeable sea ice retreat. The large-scale atmospheric circulation and cyclones act in concert to trigger the exceptionally warm and moist flow. The convergence of the transport changed the atmospheric characteristics and the surface energy budget, thus causing a severe sea ice melt.
Lixing Shen, Chuanfeng Zhao, Xingchuan Yang, Yikun Yang, and Ping Zhou
Atmos. Chem. Phys., 22, 419–439, https://doi.org/10.5194/acp-22-419-2022, https://doi.org/10.5194/acp-22-419-2022, 2022
Short summary
Short summary
Using multi-year data, this study reveals the slump of sea land breeze (SLB) at Brisbane during mega fires and investigates the impact of fire-induced aerosols on SLB. Different aerosols have different impacts on sea wind (SW) and land wind (LW). Aerosols cause the decrease of SW, partially offset by the warming effect of black carbon (BC). The large-scale cooling effect of aerosols on sea surface temperature (SST) and the burst of BC contribute to the slump of LW.
Yue Sun and Chuanfeng Zhao
Atmos. Chem. Phys., 21, 16555–16574, https://doi.org/10.5194/acp-21-16555-2021, https://doi.org/10.5194/acp-21-16555-2021, 2021
Short summary
Short summary
Using high-resolution multi-year warm season data, the influence of aerosol on precipitation time over the North China Plain (NCP), Yangtze River Delta (YRD), and Pearl River Delta (PRD) is investigated. Aerosol amount and type have significant influence on precipitation time: precipitation start time is advanced by 3 h in the NCP, delayed 2 h in the PRD, and negligibly changed in the YRD. Aerosol impact on precipitation is also influenced by precipitation type and meteorological conditions.
Tianmeng Chen, Zhanqing Li, Ralph A. Kahn, Chuanfeng Zhao, Daniel Rosenfeld, Jianping Guo, Wenchao Han, and Dandan Chen
Atmos. Chem. Phys., 21, 6199–6220, https://doi.org/10.5194/acp-21-6199-2021, https://doi.org/10.5194/acp-21-6199-2021, 2021
Short summary
Short summary
A convective cloud identification process is developed using geostationary satellite data from Himawari-8.
Convective cloud fraction is generally larger before noon and smaller in the afternoon under polluted conditions, but megacities and complex topography can influence the pattern.
A robust relationship between convective cloud and aerosol loading is found. This pattern varies with terrain height and is modulated by varying thermodynamic, dynamical, and humidity conditions during the day.
Cited articles
Andersson, A., Fennig, K., Klepp, C., Bakan, S., Graßl, H., and Schulz, J.: The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data – HOAPS-3, Earth Syst. Sci. Data, 2, 215–234, https://doi.org/10.5194/essd-2-215-2010, 2010.
Belmonte Rivas, M. and Stoffelen, A.: Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT, Ocean Sci., 15, 831–852, https://doi.org/10.5194/os-15-831-2019, 2019.
Businger, S. and Reed, R. J.: Cyclogenesis in cold air masses, Wea. Forecasting, 4, 133–156, https://doi.org/10.1175/1520-0434(1989)004<0133:cicam>2.0.co;2, 1989.
Bromwich, D. H.: Mesoscale cyclogenesis over the southwestern ross sea linked to strong katabatic winds, Mon. Wea. Rev., 119, 1736–1753, https://doi.org/10.1175/1520-0493(1991)119<1736:MCOTSR>2.0.CO;2, 1991.
Bland, J. M. and Altman, D. G.: Measuring agreement in method comparison studies, Stat. Methods Med. Res., 8, 135–60, https://doi.org/10.1177/096228029900800204, 1999.
Blechschmidt, A.-M.: A 2-year climatology of polar low events over the Nordic Seas from satellite remote sensing, Geophys. Res. Lett., 35, L09815, https://doi.org/10.1029/2008GL033706, 2008.
Clancy, R., Bitz, C. M., Blanchard-Wrigglesworth, E., McGraw, M. C., and Cavallo, S. M.: A cyclone-centered perspective on the drivers of asymmetric patterns in the atmosphere and sea ice during Arctic cyclones, J. Clim., 1–47, https://doi.org/10.1175/JCLI-D-21-0093.1, 2022.
Claud, C., Duchiron, B., and Terray, P.: Associations between large-scale atmospheric circulation and polar low developments over the north atlantic during winter, J. Geophys. Res., 112, D1201, https://doi.org/10.1029/2006JD008251, 2007.
Condron, A. and Renfrew, I. A.: The impact of polar mesoscale storms on northeast atlantic ocean circulation, Nat. Geosci., 6, 34–37, https://doi.org/10.1038/ngeo1661, 2013.
Condron, A., Bigg, G. R., and Renfrew, I. A.: Polar Mesoscale Cyclones in the Northeast Atlantic: Comparing Climatologies from ERA-40 and Satellite Imagery, Mon. Weather Rev., 134, 1518–1533, https://doi.org/10.1175/MWR3136.1, 2006.
Copernicus Marine Service: Global Ocean Hourly Reprocessed Sea Surface Wind and Stress from Scatterometer and Model (WIND_GLO_PHY_L4_MY_012_006), Copernicus Marine Service Information [data set], https://doi.org/10.48670/moi-00185, 2024.
Day, J. J., Holland, M. M., and Hodges, K. I.: Seasonal differences in the response of Arctic cyclones to climate change in CESM1, Clim. Dynam., 50, 3885–3903, https://doi.org/10.1007/s00382-017-3767-x, 2018.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., Van De Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. -J., Park, B. -K., Peubey, C., De Rosnay, P., Tavolato, C., Thépaut, J. -N., and Vitart, F.: The ERA-interim reanalysis: Configureuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Fang, R.: A repository of Python code and sample files related to the IMPMCT dataset, Zenodo [code], https://doi.org/10.5281/zenodo.17498230, 2025a.
Fang, R.: validation dataset for yolov8-obb-posecyclone-detect-model, Zenodo [data set], https://doi.org/10.5281/zenodo.15119534, 2025b.
Fang, R. and Ding, J.: IMPMCT: A Dataset of Integrated Multi-source Polar Mesoscale Cyclone Tracks, Zenodo [data set], https://doi.org/10.5281/zenodo.17142448, 2025.
Forbes, G. S. and Lottes, W. D.: Classification of mesoscale vortices in polar airstreams and the influence of the large-scale environment on their evolutions, Tellus A, 37A, 132–155, https://doi.org/10.1111/j.1600-0870.1985.tb00276.x, 1985.
Furevik, B. R., Schyberg, H., Noer, G., Tveter, F., and Röhrs, J.: ASAR and ASCAT in polar low situations, Journal of Atmospheric and Oceanic Technology, 32, 783–792, https://doi.org/10.1175/JTECH-D-14-00154.1, 2015.
Graham, R. M., Hudson, S. R., and Maturilli, M.: Improved performance of ERA5 in arctic gateway relative to four global atmospheric reanalyses, Geophys. Res. Lett., 46, 6138–6147, https://doi.org/10.1029/2019gl082781, 2019.
Golubkin, P., Smirnova, J., and Bobylev, L.: Satellite-Derived Spatio-Temporal Distribution and Parameters of North Atlantic Polar Lows for 2015–2017, Atmosphere, 12, 224, https://doi.org/10.3390/atmos12020224, 2021.
Gurvich, I., Pichugin, M., and Baranyuk, A.: Satellite multi-sensor data analysis of unusually strong polar lows over the chukchi and beaufort seas in october 2017, Remote Sensing, 15, 120, https://doi.org/10.3390/rs15010120, 2022.
Haakenstad, H., Breivik, Ø., Furevik, B. R., Reistad, M., Bohlinger, P., and Aarnes, O. J.: NORA3: A nonhydrostatic high-resolution hindcast of the north sea, the norwegian sea, and the barents sea, J. Appl. Meteorol. Clim., 60, 1443–1464, https://doi.org/10.1175/JAMC-D-21-0029.1, 2021.
Han, Y. and Ullrich, P. A. The system for classification of low-pressure systems (SyCLoPS): An all-in-one objective framework for large-scale data sets, J. Geophys. Res.-Atmos., 130, e2024JD041287, https://doi.org/10.1029/2024JD041287, 2025.
Harold, J. M., Bigg, G. R., and Turner, J.: Mesocyclone activity over the north-east atlantic. Part 1: Vortex distribution and variability, Int. J. Climatol., 19, 1187–1204, https://doi.org/10.1002/(SICI)1097-0088(199909)19:11<1187::AID-JOC419>3.0.CO;2-Q, 1999.
Harrold, T. W. and Browning, K. A.: The polar low as a baroclinic disturbance, Q. J. Roy. Meteor. Soc., 95, 710–723, https://doi.org/10.1002/qj.49709540605, 1969.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., De Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Jocher, G., Chaurasia, A., and Qiu, J.: Ultralytics YOLO (Version 8.0.0), GitHub [code], https://github.com/ultralytics/ultralytics (last access: 11 November 2024), 2023.
Kalluri, S., Cao, C., Heidinger, A., Ignatov, A., Key, J., and Smith, T.: The advanced very high resolution radiometer: Contributing to earth observations for over 40 years, Bulletin of the American Meteorological Society, 102, E351–E366, https://doi.org/10.1175/BAMS-D-20-0088.1, 2021.
King, G. P., Portabella, M., Lin, W., and Stoffelen, A.: Correlating extremes in wind divergence with extremes in rain over the tropical atlantic, Remote Sensing, 14, 1147, https://doi.org/10.3390/rs14051147, 2022.
Laffineur, T., Claud, C., Chaboureau, J.-P., and Noer, G.: Polar lows over the nordic seas: Improved representation in ERA-interim compared to ERA-40 and the impact on downscaled simulations, Mon. Weather Rev., 142, 2271–2289, https://doi.org/10.1175/MWR-D-13-00171.1, 2014.
Mallet, P., Claud, C., Cassou, C., Noer, G., and Kodera, K.: Polar lows over the nordic and labrador seas: Synoptic circulation patterns and associations with north atlantic-europe wintertime weather regimes, J. Geophys. Res.-Atmos., 118, 2455–2472, https://doi.org/10.1002/jgrd.50246, 2013.
Meyer, M., Polkova, I., Modali, K. R., Schaffer, L., Baehr, J., Olbrich, S., and Rautenhaus, M.: Interactive 3-D visual analysis of ERA5 data: improving diagnostic indices for marine cold air outbreaks and polar lows, Weather Clim. Dynam., 2, 867–891, https://doi.org/10.5194/wcd-2-867-2021, 2021.
Michel, C., Terpstra, A., and Spengler, T.: Polar Mesoscale Cyclone Climatology for the Nordic Seas Based on ERA-Interim, J. Clim., 31, 2511–2532, https://doi.org/10.1175/JCLI-D-16-0890.1, 2018.
Moreno-Ibáñez, M., Laprise, R., and Gachon, P.: Recent advances in polar low research: current knowledge, challenges and future perspectives, Tellus: Series A, 73, 1–31, https://doi.org/10.1080/16000870.2021.1890412, 2021.
Moreno-Ibáñez, M., Laprise, R., and Gachon, P.: Assessment of simulations of a polar low with the canadian regional climate model, PLoS ONE, 18, e0292250, https://doi.org/10.1371/journal.pone.0292250, 2023.
Noer, G., Saetra, Ø., Lien, T., and Gusdal, Y.: A climatological study of polar lows in the Nordic Seas, Q. J. Roy. Meteor. Soc., 137, 1762–1772, https://doi.org/10.1002/qj.846, 2011.
Orimolade, A. P., Furevik, B. R., Noer, G., Gudmestad, O. T., and Samelson, R. M.: Waves in polar lows, J. Geophys. Res.-Oceans, 121, 6470–6481, https://doi.org/10.1002/2016JC012086, 2016.
Parkinson, C. L. and Comiso, J. C.: On the 2012 record low Arctic sea ice cover: Combined impact of preconditioning and an August storm, Geophys. Res. Lett., 40, 1356–1361, https://doi.org/10.1002/grl.50349, 2013.
Pezza, A., Sadler, K., Uotila, P., Vihma, T., Mesquita, M. D. S., and Reid, P.: Southern hemisphere strong polar mesoscale cyclones in high-resolution datasets, Clim. Dynam., 47, 1647–1660, https://doi.org/10.1007/s00382-015-2925-2, 2016.
Rasmussen, E.: An investigation of a polar low with a spiral cloud structure, J. Atmos. Sci., 38, 1785–1792, https://doi.org/10.1175/1520-0469(1981)038<1785:aioapl>2.0.co;2, 1981.
Rasmussen, E. A. and Turner, J. (Eds.): Polar Lows: Mesoscale Weather Systems in the Polar Regions, Cambridge University Press, Cambridge, UK, New York, 612 pp., ISBN 978-0-521-62430-5, 2003.
Redmon, J., Divvala, S., Girshick, R., and Farhadi, A.: You only look once: Unified, real-time object detection, arXiv [preprint], https://doi.org/10.48550/arXiv.1506.02640, 2016.
Rojo, M., Claud, C., Mallet, P.-E., Noer, G., Carleton, A. M., and Vicomte, M.: Polar low tracks over the Nordic Seas: a 14-winter climatic analysis, Tellus A, 67, 24660, https://doi.org/10.3402/tellusa.v67.24660, 2015.
Rojo, M., Claud, C., Noer, G., and Carleton, A. M.: In Situ Measurements of Surface Winds, Waves, and Sea State in Polar Lows Over the North Atlantic, J. Geophys. Res.-Atmos., 124, 700–718, https://doi.org/10.1029/2017JD028079, 2019.
Shimizu, S. and Uyeda, H.: Algorithm for the identification and tracking of convective cells based on constant and adaptive threshold methods using a new cell-merging and -splitting scheme, J. Meteorol. Soc. Jpn., 90, 869–889, https://doi.org/10.2151/jmsj.2012-602, 2012.
Smirnova, J. and Golubkin, P.: Comparing polar lows in atmospheric reanalyses: Arctic system reanalysis versus ERA-interim, Mon. Weather Rev., 145, 2375–2383, https://doi.org/10.1175/MWR-D-16-0333.1, 2017.
Smirnova, J. E., Golubkin, P. A., Bobylev, L. P., Zabolotskikh, E. V., and Chapron, B.: Polar low climatology over the Nordic and Barents seas based on satellite passive microwave data, Geophys. Res. Lett., 42, 5603–5609, https://doi.org/10.1002/2015GL063865, 2015.
Stoll, P. J.: A global climatology of polar lows investigated for local differences and wind-shear environments, Weather Clim. Dynam., 3, 483–504, https://doi.org/10.5194/wcd-3-483-2022, 2022.
Stoll, P. J., Graversen, R. G., Noer, G., and Hodges, K.: An objective global climatology of polar lows based on reanalysis data, Q. J. Roy. Meteor. Soc., 144, 2099–2117, https://doi.org/10.1002/qj.3309, 2018.
Stoll, P. J., Valkonen, T. M., Graversen, R. G., and Noer, G.: A well-observed polar low analysed with a regional and a global weather-prediction model, Q. J. Roy. Meteor. Soc., 146, 1740–1767, https://doi.org/10.1002/qj.3764, 2020.
Stoll, P. J., Spengler, T., Terpstra, A., and Graversen, R. G.: Polar lows – moist-baroclinic cyclones developing in four different vertical wind shear environments, Polar lows, Weather Clim. Dyn., 2, 19 –36, https://doi.org/10.5194/wcd-2-19-2021, 2021.
Smedsrud, L. H., Muilwijk, M., Brakstad, A., Madonna, E., Lauvset, S. K., Spensberger, C., Born, A., Eldevik, T., Drange, H., Jeansson, E., Li, C., Olsen, A., Skagseth, Ø., Slater, D. A., Straneo, F., Våge, K., and Årthun, M.: Nordic seas heat loss, atlantic inflow, and arctic sea ice cover over the last century, Rev. Geophys., 60, e2020RG000725, https://doi.org/10.1029/2020RG000725, 2022.
Terpstra, A., Michel, C., and Spengler, T.: Forward and Reverse Shear Environments during Polar Low Genesis over the Northeast Atlantic, Mon. Weather Rev., 144, 1341–1354, https://doi.org/10.1175/MWR-D-15-0314.1, 2016.
Verezemskaya, P., Tilinina, N., Gulev, S., Renfrew, I. A., and Lazzara, M.: Southern ocean mesocyclones and polar lows from manually tracked satellite mosaics, Geophys. Res. Lett., 44, 7985–7993, https://doi.org/10.1002/2017GL074053, 2017.
Wang, C., Graham, R. M., Wang, K., Gerland, S., and Granskog, M. A.: Comparison of ERA5 and ERA-Interim near-surface air temperature, snowfall and precipitation over Arctic sea ice: effects on sea ice thermodynamics and evolution, The Cryosphere, 13, 1661–1679, https://doi.org/10.5194/tc-13-1661-2019, 2019.
Watanabe, S. I., Niino, H., and Yanase, W.: Climatology of Polar Mesocyclones over the Sea of Japan Using a New Objective Tracking Method, Mon. Weather Rev., 144, 2503–2515, https://doi.org/10.1175/MWR-D-15-0349.1, 2016.
Wilhelmsen, K.: Climatological study of gale-producing polar lows near norway, Tellus A, 37A, 451–459, https://doi.org/10.1111/j.1600-0870.1985.tb00443.x, 1985.
Yan, Z., Wang, Z., Peng, M., and Ge, X.: Polar Low Motion and Track Characteristics over the North Atlantic, J. Clim., 36, 4559–4569, https://doi.org/10.1175/JCLI-D-22-0547.1, 2023.
Yanase, W., Niino, H., Watanabe, S. I., Hodges, K., Zahn, M., Spengler, T., and Gurvich, I. A.: Climatology of polar lows over the sea of japan using the JRA-55 reanalysis, J. Clim., 29, 419–437, https://doi.org/10.1175/JCLI-D-15-0291.1, 2016.
Yao, L., Lu, J., Xia, X., Jing, W., and Liu, Y.: Evaluation of the ERA5 sea surface temperature around the pacific and the atlantic, IEEE Access, 9, 12067–12073, https://doi.org/10.1109/ACCESS.2021.3051642, 2021.
Zappa, G., Shaffrey, L., and Hodges, K.: Can Polar Lows be Objectively Identified and Tracked in the ECMWF Operational Analysis and the ERA-Interim Reanalysis?, Mon. Weather Rev., 142, 2596–2608, https://doi.org/10.1175/MWR-D-14-00064.1, 2014.
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...
Altmetrics
Final-revised paper
Preprint