Articles | Volume 18, issue 2
https://doi.org/10.5194/essd-18-1287-2026
© Author(s) 2026. 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-18-1287-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
19 Feb 2026
Data description article |
| 19 Feb 2026
| 19 Feb 2026
FYAI: a Fengyun satellite-based dataset for atmospheric ice water path
Yifan Yang
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
State Key Laboratory of Earth System Numerical Modeling and Application, University of Chinese Academy of Sciences, Beijing 100049, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
State Key Laboratory of Earth System Numerical Modeling and Application, University of Chinese Academy of Sciences, Beijing 100049, China
Gaojie Xu
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
State Key Laboratory of Earth System Numerical Modeling and Application, University of Chinese Academy of Sciences, Beijing 100049, China
Rui Zhou
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
State Key Laboratory of Earth System Numerical Modeling and Application, University of Chinese Academy of Sciences, Beijing 100049, China
Bo Li
Innovation Center for Fengyun Meteorological Satellite (FYSIC), Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China
Letu Husi
State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Wenyu Wang
Key Laboratory of Microwave Remote Sensing, National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China
Cunde Xiao
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Beijing Normal University, Beijing 100875, China
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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
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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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.
Qixiang Sun, Husi Letu, Yongqian Wang, Peng Zhang, Hong Liang, Chong Shi, Shuai Yin, Jiancheng Shi, and Dabin Ji
Earth Syst. Sci. Data, 18, 371–395, https://doi.org/10.5194/essd-18-371-2026, https://doi.org/10.5194/essd-18-371-2026, 2026
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The Tibetan Plateau plays a vital role in Asia’s water cycle, but tracking water vapor in this mountainous region is difficult, especially under cloudy conditions. We developed a new satellite-based method to generate hourly water vapor data at 0.02-degree resolution from 2016 to 2022, now available at https://doi.org/10.11888/Atmos.tpdc.301518, which improves accuracy and reveals fine-scale moisture transport critical for understanding rainfall and extreme weather.
Yutong Wang, Huazhe Shang, Chenqian Tang, Jian Xu, Tianyang Ji, Wenwu Wang, Lesi Wei, Yonghui Lei, Jiancheng Shi, and Husi Letu
Atmos. Chem. Phys., 25, 16167–16187, https://doi.org/10.5194/acp-25-16167-2025, https://doi.org/10.5194/acp-25-16167-2025, 2025
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By analyzing global CloudSat data, we identified that most liquid cloud profiles have triangle-shaped or steadily decreasing structures, and we developed a new method using pattern recognition, fitting techniques, and machine learning to accurately estimate these profiles. This research advances our understanding of cloud life cycle and improves the ability to characterize cloud profiles, which is crucial for enhancing weather forecast and climate change research.
Tong Zhang, Wei Yang, Yuzhe Wang, Chuanxi Zhao, Qingyun Long, and Cunde Xiao
The Cryosphere, 19, 4487–4498, https://doi.org/10.5194/tc-19-4487-2025, https://doi.org/10.5194/tc-19-4487-2025, 2025
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This study investigates the 2018 Sedongpu glacier detachment in Southeastern Tibet using a two-dimensional ice flow model that includes an ice stiffness and basal slip positive feedback mechanism. The model simulates rapid transitions in glacier flow, triggering detachment when ice stress exceeds yield strength. The results, including ice speed and duration, align with observations, demonstrating the potential for early warning of similar hazards in the region.
Zhengyan Zhang, Yan-An Liu, Xinjian Ma, Zhenglong Li, Pengbo Xu, Juan Zhang, Min Min, Di Di, Bo Li, and Jun Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-419, https://doi.org/10.5194/essd-2025-419, 2025
Revised manuscript under review for ESSD
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We developed a high-resolution wind dataset for the Yangtze River Delta at 1-kilometer resolution and hourly intervals during summer from 2021 to 2023. By combining advanced modeling with real-world observations, it captures fine-scale wind patterns near the surface, especially in urban and mountainous areas. This dataset supports improved weather forecasts, air quality studies, and planning for wind energy and aviation in rapidly developing regions.
Xinran Xia, Min Min, Jun Li, Yiming Zhao, Ling Gao, and Bo Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-2928, https://doi.org/10.5194/egusphere-2025-2928, 2025
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New ML method fuses GEO hyperspectral & imager data to improve nighttime cloud retrievals. Achieves ~10 % better accuracy (CER:9.73μm, COT:6.09 errors), especially for thin clouds. Maintains day-night continuity, aids weather/climate monitoring.
Ziming Wang, Husi Letu, Huazhe Shang, and Luca Bugliaro
Atmos. Chem. Phys., 24, 7559–7574, https://doi.org/10.5194/acp-24-7559-2024, https://doi.org/10.5194/acp-24-7559-2024, 2024
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The supercooled liquid fraction (SLF) in mixed-phase clouds is retrieved for the first time using passive geostationary satellite observations based on differences in liquid droplet and ice particle radiative properties. The retrieved results are comparable to global distributions observed by active instruments, and the feasibility of the retrieval method to analyze the observed trends of the SLF has been validated.
Tong Zhang, William Colgan, Agnes Wansing, Anja Løkkegaard, Gunter Leguy, William H. Lipscomb, and Cunde Xiao
The Cryosphere, 18, 387–402, https://doi.org/10.5194/tc-18-387-2024, https://doi.org/10.5194/tc-18-387-2024, 2024
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The geothermal heat flux determines how much heat enters from beneath the ice sheet, and thus impacts the temperature and the flow of the ice sheet. In this study we investigate how much geothermal heat flux impacts the initialization of the Greenland ice sheet. We use the Community Ice Sheet Model with two different initialization methods. We find a non-trivial influence of the choice of heat flow boundary conditions on the ice sheet initializations for further designs of ice sheet modeling.
Wenyu Wang, Jian Xu, and Zhenzhan Wang
Atmos. Meas. Tech., 16, 4137–4153, https://doi.org/10.5194/amt-16-4137-2023, https://doi.org/10.5194/amt-16-4137-2023, 2023
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This article presents a study for feasibility analysis of atmospheric wind measurement using a terahertz (THz) passive limb radiometer with high spectral resolution. The simulations show that line-of-sight wind from 40 to 120 km can be obtained better than 10 m s−1 (at most altitudes it is better than 5 m s−1) using the O3, O2, H2O, and OI bands. This study will provide reference for future payload design.
Elizabeth R. Thomas, Diana O. Vladimirova, Dieter R. Tetzner, B. Daniel Emanuelsson, Nathan Chellman, Daniel A. Dixon, Hugues Goosse, Mackenzie M. Grieman, Amy C. F. King, Michael Sigl, Danielle G. Udy, Tessa R. Vance, Dominic A. Winski, V. Holly L. Winton, Nancy A. N. Bertler, Akira Hori, Chavarukonam M. Laluraj, Joseph R. McConnell, Yuko Motizuki, Kazuya Takahashi, Hideaki Motoyama, Yoichi Nakai, Franciéle Schwanck, Jefferson Cardia Simões, Filipe Gaudie Ley Lindau, Mirko Severi, Rita Traversi, Sarah Wauthy, Cunde Xiao, Jiao Yang, Ellen Mosely-Thompson, Tamara V. Khodzher, Ludmila P. Golobokova, and Alexey A. Ekaykin
Earth Syst. Sci. Data, 15, 2517–2532, https://doi.org/10.5194/essd-15-2517-2023, https://doi.org/10.5194/essd-15-2517-2023, 2023
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The concentration of sodium and sulfate measured in Antarctic ice cores is related to changes in both sea ice and winds. Here we have compiled a database of sodium and sulfate records from 105 ice core sites in Antarctica. The records span all, or part, of the past 2000 years. The records will improve our understanding of how winds and sea ice have changed in the past and how they have influenced the climate of Antarctica over the past 2000 years.
Huazhe Shang, Souichiro Hioki, Guillaume Penide, Céline Cornet, Husi Letu, and Jérôme Riedi
Atmos. Chem. Phys., 23, 2729–2746, https://doi.org/10.5194/acp-23-2729-2023, https://doi.org/10.5194/acp-23-2729-2023, 2023
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We find that cloud profiles can be divided into four prominent patterns, and the frequency of these four patterns is related to intensities of cloud-top entrainment and precipitation. Based on these analyses, we further propose a cloud profile parameterization scheme allowing us to represent these patterns. Our results shed light on how to facilitate the representation of cloud profiles and how to link them to cloud entrainment or precipitating status in future remote-sensing applications.
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
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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.
Zhiheng Du, Jiao Yang, Lei Wang, Ninglian Wang, Anders Svensson, Zhen Zhang, Xiangyu Ma, Yaping Liu, Shimeng Wang, Jianzhong Xu, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5349–5365, https://doi.org/10.5194/essd-14-5349-2022, https://doi.org/10.5194/essd-14-5349-2022, 2022
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A dataset of the radiogenic strontium and neodymium isotopic compositions from the three poles (the third pole, the Arctic, and Antarctica) were integrated to obtain new findings. The dataset enables us to map the standardized locations in the three poles, while the use of sorting criteria related to the sample type permits us to trace the dust sources and sinks. The purpose of this dataset is to try to determine the variable transport pathways of dust at three poles.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
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The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
Wenyu Wang, Zhenzhan Wang, Qiurui He, and Lanjie Zhang
Atmos. Meas. Tech., 15, 6489–6506, https://doi.org/10.5194/amt-15-6489-2022, https://doi.org/10.5194/amt-15-6489-2022, 2022
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This paper uses a neural network approach to retrieve the ice water path from FY-3B/MWHS polarimetric measurements, focusing on its unique 150 GHz quasi-polarized channels. The Level 2 product of CloudSat is used as the reference value for the neural network. The results show that the polarization information is helpful for the retrieval in scenes with thicker cloud ice, and the 150 GHz channels give a significant improvement compared to using only 183 GHz channels.
Ming Li, Husi Letu, Yiran Peng, Hiroshi Ishimoto, Yanluan Lin, Takashi Y. Nakajima, Anthony J. Baran, Zengyuan Guo, Yonghui Lei, and Jiancheng Shi
Atmos. Chem. Phys., 22, 4809–4825, https://doi.org/10.5194/acp-22-4809-2022, https://doi.org/10.5194/acp-22-4809-2022, 2022
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To build on the previous investigations of the Voronoi model in the remote sensing retrievals of ice cloud products, this paper developed an ice cloud parameterization scheme based on the single-scattering properties of the Voronoi model and evaluate it through simulations with the Community Integrated Earth System Model (CIESM). Compared with four representative ice cloud schemes, results show that the Voronoi model has good capabilities of ice cloud modeling in the climate model.
Pradeep Khatri, Tadahiro Hayasaka, Hitoshi Irie, Husi Letu, Takashi Y. Nakajima, Hiroshi Ishimoto, and Tamio Takamura
Atmos. Meas. Tech., 15, 1967–1982, https://doi.org/10.5194/amt-15-1967-2022, https://doi.org/10.5194/amt-15-1967-2022, 2022
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Cloud properties observed by the Second-generation Global Imager (SGLI) onboard the Global Change Observation Mission – Climate (GCOM-C) satellite are evaluated using surface observation data. The study finds that SGLI-observed cloud properties are qualitative enough, although water cloud properties are suggested to be more qualitative, and both water and ice cloud properties can reproduce surface irradiance quite satisfactorily. Thus, SGLI cloud products are very useful for different studies.
Minghu Ding, Tong Zhang, Diyi Yang, Ian Allison, Tingfeng Dou, and Cunde Xiao
The Cryosphere, 15, 4201–4206, https://doi.org/10.5194/tc-15-4201-2021, https://doi.org/10.5194/tc-15-4201-2021, 2021
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Measurement of snow heat conductivity is essential to establish the energy balance between the atmosphere and firn, but it is still not clear in Antarctica. Here, we used data from three automatic weather stations located in different types of climate and evaluated nine schemes that were used to calculate the effective heat diffusivity of snow. The best solution was proposed. However, no conductivity–density relationship was optimal at all sites, and the performance of each varied with depth.
Yetang Wang, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Shugui Hou, and Cunde Xiao
Earth Syst. Sci. Data, 13, 3057–3074, https://doi.org/10.5194/essd-13-3057-2021, https://doi.org/10.5194/essd-13-3057-2021, 2021
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Accurate observation of surface mass balance (SMB) under climate change is essential for the reliable present and future assessment of Antarctic contribution to global sea level. This study presents a new quality-controlled dataset of Antarctic SMB observations at different temporal resolutions and is the first ice-sheet-scale compilation of multiple types of measurements. The dataset can be widely applied to climate model validation, remote sensing retrievals, and data assimilation.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Qiang Wang, Shifeng Pan, Jie Su, Xiaojun Yuan, Minghu Ding, Feng Zhang, Kai Xue, Peter A. Bieniek, and Hajo Eicken
The Cryosphere, 15, 883–895, https://doi.org/10.5194/tc-15-883-2021, https://doi.org/10.5194/tc-15-883-2021, 2021
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Rain-on-snow (ROS) events can accelerate the surface ablation of sea ice, greatly influencing the ice–albedo feedback. We found that spring ROS events have shifted to earlier dates over the Arctic Ocean in recent decades, which is correlated with sea ice melt onset in the Pacific sector and most Eurasian marginal seas. There has been a clear transition from solid to liquid precipitation, leading to a reduction in spring snow depth on sea ice by more than −0.5 cm per decade since the 1980s.
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Short summary
We developed "FYAI" (Fengyun Satellite-Based Dataset for Atmospheric Ice Water Path), a fifteen-year dataset (2010–2024) derived from Chinese Fengyun satellites. Using artificial intelligence, we mapped global atmospheric ice. This continuous record fills critical gaps in observation. It provides scientists with a vital tool to improve weather forecasts and better understand how atmospheric ice interacts with the global climate system.
We developed "FYAI" (Fengyun Satellite-Based Dataset for Atmospheric Ice Water Path), a...
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