Articles | Volume 17, issue 7
https://doi.org/10.5194/essd-17-3243-2025
© 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-17-3243-2025
© 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
| 
04 Jul 2025
Data description article |
| 04 Jul 2025
| 04 Jul 2025
A global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology based on deep-learning methods
Yuanyuan Wu
Nanjing-Helsinki Institute in Atmospheric and Earth System Sciences, Nanjing University, Nanjing, 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences & Institute for Climate and Global Change Research, Nanjing, 210023, China
Nanjing-Helsinki Institute in Atmospheric and Earth System Sciences, Nanjing University, Nanjing, 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences & Institute for Climate and Global Change Research, Nanjing, 210023, China
Yu Zhang
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences & Institute for Climate and Global Change Research, Nanjing, 210023, China
Kang-En Huang
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Boyang Zheng
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Yichuan Wang
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Yanyun Li
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Quan Wang
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Chen Zhou
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Yuan Liang
TianJi Weather Science and Technology Company, Beijing, 100000, China
Jianning Sun
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Minghuai Wang
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences & Institute for Climate and Global Change Research, Nanjing, 210023, China
Daniel Rosenfeld
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
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Geosci. Model Dev., 19, 10551–10569, https://doi.org/10.5194/gmd-19-10551-2026, https://doi.org/10.5194/gmd-19-10551-2026, 2026
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We developed a new global ocean model to understand how mercury moves and changes in seawater. The model closely matches observed mercury patterns, providing confidence in its results. It will serve as the ocean part of a fully coupled Earth system mercury model (CESM2-Hg) with air, land, and river processes, improving predictions of future mercury pollution and guiding strategies to protect marine life and human health.
Jinpeng Lu, Sijia Lou, Wuke Wang, Jiankai Zhang, Ke Ding, Xin Huang, Yiquan Jiang, Tengyu Liu, Yawen Liu, Qingyan Xie, Lian Xue, Zilin Wang, Chen Zhou, Anbao Zhu, and Aijun Ding
EGUsphere, https://doi.org/10.5194/egusphere-2026-5104, https://doi.org/10.5194/egusphere-2026-5104, 2026
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The 2022 Hunga Tonga eruption injected sulfur gases and massive water vapor into the stratosphere. With observations and simulations, we assessed effects on the tropical quasi-biennial oscillation (QBO). Pollutants lingered over a year; the water-rich eruption notably altered QBO winds. Cooling from excess vapor and particles, concentrated south of 15° N, reshaped upper circulation and drove downward wind anomalies modulating the QBO, with April–October 2022 cooling causing more wind shifts.
Wenxin Zhang, Man Yue, Xinyue Shao, Xinyi Dong, and Minghuai Wang
Atmos. Chem. Phys., 26, 11967–11989, https://doi.org/10.5194/acp-26-11967-2026, https://doi.org/10.5194/acp-26-11967-2026, 2026
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Isoprene-derived secondary organic aerosol (ISOA) remains poorly represented in models, creating uncertainty in its changes and drivers. An improved model better matches observations and shows that low-NOx formation dominates. Overall ISOA changed little from 2000 to 2019 because opposite regional trends offset each other: increases in Southwest China were driven by stronger isoprene emissions, while decreases in Shaanxi–Gansu–Ningxia were driven by changes in anthropogenic emissions.
Boyang Zheng, Yannian Zhu, Yang Cao, Kang-En Huang, Jihu Liu, Yichuan Wang, Jun Shi, Yicheng Wei, Daniel Rosenfeld, Chen Zhou, and Minghuai Wang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-360, https://doi.org/10.5194/essd-2026-360, 2026
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We created a global dataset of clear‑sky energy at the top of the atmosphere over the ocean that matches real satellite overpass times. Knowing how much energy the Earth reflects and emits under cloud‑free conditions helps assess how clouds influence climate. We trained a model with satellite measurements and atmospheric data to estimate clear‑sky energy fluxes at observation times. This dataset can support studies of atmospheric processes and improve comparisons between models and observations.
Guangxin Ai, Shuaiqi Tang, Hailong Wang, Fan Mei, and Minghuai Wang
Atmos. Chem. Phys., 26, 7967–7984, https://doi.org/10.5194/acp-26-7967-2026, https://doi.org/10.5194/acp-26-7967-2026, 2026
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Tiny aerosol particles help form cloud droplets and can affect rainfall and climate, but their behavior is hard to predict. We used aircraft measurements over the ocean near the Azores and over the central United States to compare clean and polluted air. We found that particle size and chemical makeup together control how easily clouds form, and organic-rich particles often reduce droplet formation. These results can improve how weather and climate models represent clouds.
Xinyue Shao, Yaman Liu, Xinyi Dong, Minghuai Wang, Ruochong Xu, Joel A. Thornton, Duseong S. Jo, Man Yue, Wenxiang Shen, Manish Shrivastava, Stephen R. Arnold, and Ken S. Carslaw
Atmos. Chem. Phys., 26, 6427–6448, https://doi.org/10.5194/acp-26-6427-2026, https://doi.org/10.5194/acp-26-6427-2026, 2026
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Highly Oxygenated Organic Molecules (HOMs) are key precursors of secondary organic aerosols (SOA). Incorporating the HOMs chemical mechanism into a global climate model allows for a reasonable reproduction of observed HOM characteristics. HOM-SOA constitutes a significant fraction of global SOA, and its distribution and formation pathways exhibit strong sensitivity to uncertainties in autoxidation processes and peroxy radical branching ratios.
Xinyue Shao, Minghuai Wang, Xinyi Dong, Yaman Liu, Stephen R. Arnold, Leighton A. Regayre, Duseong S. Jo, Wenxiang Shen, Hao Wang, Man Yue, Jingyi Wang, Wenxin Zhang, and Ken S. Carslaw
Atmos. Chem. Phys., 26, 4439–4451, https://doi.org/10.5194/acp-26-4439-2026, https://doi.org/10.5194/acp-26-4439-2026, 2026
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This study uses a global chemistry–climate model to investigate how new particle formation (NPF) from highly oxygenated organic molecules (HOMs) contributes to cloud condensation nuclei (CCN) in both preindustrial and present-day environments and its impact on aerosol indirect radiative forcing. The findings highlight the crucial role of biogenic emissions in climate change, providing new insights for carbon-neutral scenarios and enhancing our understanding of aerosol–cloud interactions.
Mei Chong, Shengkai Wang, Xi Chen, Yuan Liang, Bing Pu, Shian-Jiann Lin, Zhi Liang, and Yimin Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-628, https://doi.org/10.5194/essd-2025-628, 2026
Preprint under review for ESSD
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The wind speed needed to lift dust from surfaces governs the highest uncertainty in emission models, making it the root cause of dust forecasting errors. We developed iDust-ut, a global threshold dataset by fusing ground observations, satellite data, and reanalysis products. Tests with the iDust model show doubled severe dust storm prediction accuracy. The dataset works directly in any model with built-in adaptation for wind biases, substantially improving operational dust forecasting worldwide.
Calvin Coulbury, Ivy Tan, David Turner, and Chen Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2025-6553, https://doi.org/10.5194/egusphere-2025-6553, 2026
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Observations of low-level, single-layer clouds above the North Slope of Alaska, within the Arctic circle, are used to assess how cloud properties have changed from 2004 to 2023. Evidence is provided for a cooling influence of cloud property changes on Arctic amplified warming. Local temperature changes result in clouds becoming more opaque, driven by changes in cloud liquid water content. This work represents an avenue for the evaluation and improvement of model representations of Arctic clouds.
Qingmin Wang, Yincheng Liu, Lujun Zhang, and Chen Zhou
Atmos. Chem. Phys., 25, 6741–6755, https://doi.org/10.5194/acp-25-6741-2025, https://doi.org/10.5194/acp-25-6741-2025, 2025
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Our research explores how SST (sea surface temperature) changes in non-polar regions impact the polar energy budget. Through idealized SST experiments, we found that warming in tropical and mid-latitude oceans raises polar temperatures through enhanced atmospheric energy transport, leading to surface warming and top-of-atmosphere cooling in polar areas. This study highlights the distinct impacts of tropical Pacific and Indian Ocean SST changes on Arctic and Antarctic climates.
Hanzheng Zhu, Yaman Liu, Man Yue, Shihui Feng, Pingqing Fu, Kan Huang, Xinyi Dong, and Minghuai Wang
Atmos. Chem. Phys., 25, 5175–5197, https://doi.org/10.5194/acp-25-5175-2025, https://doi.org/10.5194/acp-25-5175-2025, 2025
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Dust-soluble iron deposition from East Asia plays an important role in the marine ecology of the Northwest Pacific. Using the developed model, our findings highlight a dual trend: a decrease in the overall deposition of soluble iron from dust but an increase in the solubility of the iron itself due to the enhanced atmospheric processing. The study underscores the critical roles of both dust emission and atmospheric processing in soluble iron deposition and marine ecology.
Wenxin Zhang, Yaman Liu, Man Yue, Xinyi Dong, Kan Huang, and Minghuai Wang
Atmos. Chem. Phys., 25, 3857–3872, https://doi.org/10.5194/acp-25-3857-2025, https://doi.org/10.5194/acp-25-3857-2025, 2025
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Understanding long-term organic aerosol (OA) trends and their driving factors is important for air quality management. Our modeling revealed that OA in China increased by 5.6 % from 1990 to 2019, primarily due to a 32.3 % increase in secondary organic aerosols (SOAs) and an 8.1 % decrease in primary organic aerosols (POAs), both largely driven by changes in anthropogenic emissions. Biogenic SOA increased due to warming but showed little response to changes in anthropogenic nitrogen oxide emissions.
Chris J. Wright, Joel A. Thornton, Lyatt Jaeglé, Yang Cao, Yannian Zhu, Jihu Liu, Randall Jones II, Robert Holzworth, Daniel Rosenfeld, Robert Wood, Peter Blossey, and Daehyun Kim
Atmos. Chem. Phys., 25, 2937–2946, https://doi.org/10.5194/acp-25-2937-2025, https://doi.org/10.5194/acp-25-2937-2025, 2025
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Aerosol particles influence clouds, which exert a large forcing on solar radiation and freshwater. To better understand the mechanisms by which aerosol influences thunderstorms, we look at the two busiest shipping lanes in the world, where recent regulations have reduced sulfur emissions by nearly an order of magnitude. We find that the reduction in emissions has been accompanied by a dramatic decrease in both lightning and the number of droplets in clouds over the shipping lanes.
Zhe Song, Shaocai Yu, Pengfei Li, Ningning Yao, Lang Chen, Yuhai Sun, Boqiong Jiang, and Daniel Rosenfeld
Atmos. Chem. Phys., 25, 2473–2494, https://doi.org/10.5194/acp-25-2473-2025, https://doi.org/10.5194/acp-25-2473-2025, 2025
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Our results with injected sea salt aerosols for five open oceans show that sea salt aerosols with low injection amounts dominate shortwave radiation, mainly through indirect effects. As indirect aerosol effects saturate with increasing injection rates, direct effects exceed indirect effects. This implies that marine cloud brightening is best implemented in areas with extensive cloud cover, while aerosol direct scattering effects remain dominant when clouds are scarce.
He Huang, Quan Wang, Chao Liu, and Chen Zhou
Atmos. Meas. Tech., 17, 7129–7141, https://doi.org/10.5194/amt-17-7129-2024, https://doi.org/10.5194/amt-17-7129-2024, 2024
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This study introduces a cloud property retrieval method which integrates traditional radiative transfer simulations with a machine learning method. Retrievals from a machine learning algorithm are used to provide a priori states, and a radiative transfer model is used to create lookup tables for later iteration processes. The new method combines the advantages of traditional and machine learning algorithms, and it is applicable to both daytime and nighttime conditions.
Xinyue Shao, Minghuai Wang, Xinyi Dong, Yaman Liu, Wenxiang Shen, Stephen R. Arnold, Leighton A. Regayre, Meinrat O. Andreae, Mira L. Pöhlker, Duseong S. Jo, Man Yue, and Ken S. Carslaw
Atmos. Chem. Phys., 24, 11365–11389, https://doi.org/10.5194/acp-24-11365-2024, https://doi.org/10.5194/acp-24-11365-2024, 2024
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Highly oxygenated organic molecules (HOMs) play an important role in atmospheric new particle formation (NPF). By semi-explicitly coupling the chemical mechanism of HOMs and a comprehensive nucleation scheme in a global climate model, the updated model shows better agreement with measurements of nucleation rate, growth rate, and NPF event frequency. Our results reveal that HOM-driven NPF leads to a considerable increase in particle and cloud condensation nuclei burden globally.
Renmin Yuan, Hongsheng Zhang, Jiajia Hua, Hao Liu, Peizhe Wu, Xingyu Zhu, and Jianning Sun
Atmos. Meas. Tech., 17, 2089–2102, https://doi.org/10.5194/amt-17-2089-2024, https://doi.org/10.5194/amt-17-2089-2024, 2024
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Previously, a new method for atmospheric aerosol flux was proposed, and a large-aperture scintillometer was developed for experimental measurements, but the method was consistently not validated. In this paper, eddy correlation experiments for aerosol vertical transport fluxes were conducted to verify the reliability of the previous large-aperture scintillometer method. The experimental results also show that urban green land is a sink area for aerosol particles.
Yawen Liu, Yun Qian, Philip J. Rasch, Kai Zhang, Lai-yung Ruby Leung, Yuhang Wang, Minghuai Wang, Hailong Wang, Xin Huang, and Xiu-Qun Yang
Atmos. Chem. Phys., 24, 3115–3128, https://doi.org/10.5194/acp-24-3115-2024, https://doi.org/10.5194/acp-24-3115-2024, 2024
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Fire management has long been a challenge. Here we report that spring-peak fire activity over southern Mexico and Central America (SMCA) has a distinct quasi-biennial signal by measuring multiple fire metrics. This signal is initially driven by quasi-biennial variability in precipitation and is further amplified by positive feedback of fire–precipitation interaction at short timescales. This work highlights the importance of fire–climate interactions in shaping fires on an interannual scale.
He Huang, Quan Wang, Chao Liu, and Chen Zhou
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-36, https://doi.org/10.5194/amt-2024-36, 2024
Preprint withdrawn
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This study introduces a cloud property retrieval method which integrates traditional radiative transfer simulations with a machine-learning method. Retrievals from a machine learning algorithm are used to provide initial guesses, and a radiative transfer model is used to create radiance lookup tables for later iteration processes. The new method combines the advantages of traditional and machine learning algorithms, and is applicable both daytime and nighttime conditions.
Yuchen Wang, Xvli Guo, Yajie Huo, Mengying Li, Yuqing Pan, Shaocai Yu, Alexander Baklanov, Daniel Rosenfeld, John H. Seinfeld, and Pengfei Li
Atmos. Chem. Phys., 23, 5233–5249, https://doi.org/10.5194/acp-23-5233-2023, https://doi.org/10.5194/acp-23-5233-2023, 2023
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Substantial advances have been made in recent years toward detecting and quantifying methane super-emitters from space. However, such advances have rarely been expanded to measure the global methane pledge because large-scale swaths and high-resolution sampling have not been coordinated. Here we present a versatile spaceborne architecture that can juggle planet-scale and plant-level methane retrievals, challenge official emission reports, and remain relevant for stereoscopic measurements.
Paolo Dandini, Céline Cornet, Renaud Binet, Laetitia Fenouil, Vadim Holodovsky, Yoav Y. Schechner, Didier Ricard, and Daniel Rosenfeld
Atmos. Meas. Tech., 15, 6221–6242, https://doi.org/10.5194/amt-15-6221-2022, https://doi.org/10.5194/amt-15-6221-2022, 2022
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3D cloud envelope and development velocity are retrieved from realistic simulations of multi-view
CLOUD (C3IEL) images. Cloud development velocity is derived by finding matching features
between acquisitions separated by 20 s. The tie points are then mapped from image to space via 3D
reconstruction of the cloud envelope obtained from 2 simultaneous images. The retrieved cloud
topography as well as the velocities are in good agreement with the estimates obtained from the
physical models.
Mengying Li, Shaocai Yu, Xue Chen, Zhen Li, Yibo Zhang, Zhe Song, Weiping Liu, Pengfei Li, Xiaoye Zhang, Meigen Zhang, Yele Sun, Zirui Liu, Caiping Sun, Jingkun Jiang, Shuxiao Wang, Benjamin N. Murphy, Kiran Alapaty, Rohit Mathur, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 22, 11845–11866, https://doi.org/10.5194/acp-22-11845-2022, https://doi.org/10.5194/acp-22-11845-2022, 2022
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This study constructed an emission inventory of condensable particulate matter (CPM) in China with a focus on organic aerosols (OAs), based on collected CPM emission information. The results show that OA emissions are enhanced twofold for the years 2014 and 2017 after the inclusion of CPM in the new inventory. Sensitivity cases demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to primary, secondary, and total OA concentrations.
Feiyue Mao, Ruixing Shi, Daniel Rosenfeld, Zengxin Pan, Lin Zang, Yannian Zhu, and Xin Lu
Atmos. Chem. Phys., 22, 10589–10602, https://doi.org/10.5194/acp-22-10589-2022, https://doi.org/10.5194/acp-22-10589-2022, 2022
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Previous studies generally ignored the faint aerosols undetected by the CALIPSO layer detection algorithm because they are too optically thin. Here, we retrieved the faint aerosol extinction based on instantaneous CALIPSO observations with the constraint of SAGE data. The correlation and normalized root-mean-square error of the retrievals with independent SAGE data are 0.66 and 100.6 %, respectively. The minimum retrieved extinction at night can be extended to 10-4 km-1 with 125 % uncertainty.
Kai Zhang, Wentao Zhang, Hui Wan, Philip J. Rasch, Steven J. Ghan, Richard C. Easter, Xiangjun Shi, Yong Wang, Hailong Wang, Po-Lun Ma, Shixuan Zhang, Jian Sun, Susannah M. Burrows, Manish Shrivastava, Balwinder Singh, Yun Qian, Xiaohong Liu, Jean-Christophe Golaz, Qi Tang, Xue Zheng, Shaocheng Xie, Wuyin Lin, Yan Feng, Minghuai Wang, Jin-Ho Yoon, and L. Ruby Leung
Atmos. Chem. Phys., 22, 9129–9160, https://doi.org/10.5194/acp-22-9129-2022, https://doi.org/10.5194/acp-22-9129-2022, 2022
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Here we analyze the effective aerosol forcing simulated by E3SM version 1 using both century-long free-running and short nudged simulations. The aerosol forcing in E3SMv1 is relatively large compared to other models, mainly due to the large indirect aerosol effect. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 have a strong correlation. The aerosol forcing estimates in E3SMv1 are sensitive to the parameterization changes in both liquid and ice cloud processes.
Sagar P. Parajuli, Georgiy L. Stenchikov, Alexander Ukhov, Suleiman Mostamandi, Paul A. Kucera, Duncan Axisa, William I. Gustafson Jr., and Yannian Zhu
Atmos. Chem. Phys., 22, 8659–8682, https://doi.org/10.5194/acp-22-8659-2022, https://doi.org/10.5194/acp-22-8659-2022, 2022
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Rainfall affects the distribution of surface- and groundwater resources, which are constantly declining over the Middle East and North Africa (MENA) due to overexploitation. Here, we explored the effects of dust on rainfall using WRF-Chem model simulations. Although dust is considered a nuisance from an air quality perspective, our results highlight the positive fundamental role of dust particles in modulating rainfall formation and distribution, which has implications for cloud seeding.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
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Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Ramon Campos Braga, Barbara Ervens, Daniel Rosenfeld, Meinrat O. Andreae, Jan-David Förster, Daniel Fütterer, Lianet Hernández Pardo, Bruna A. Holanda, Tina Jurkat-Witschas, Ovid O. Krüger, Oliver Lauer, Luiz A. T. Machado, Christopher Pöhlker, Daniel Sauer, Christiane Voigt, Adrian Walser, Manfred Wendisch, Ulrich Pöschl, and Mira L. Pöhlker
Atmos. Chem. Phys., 21, 17513–17528, https://doi.org/10.5194/acp-21-17513-2021, https://doi.org/10.5194/acp-21-17513-2021, 2021
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Interactions of aerosol particles with clouds represent a large uncertainty in estimates of climate change. Properties of aerosol particles control their ability to act as cloud condensation nuclei. Using aerosol measurements in the Amazon, we performed model studies to compare predicted and measured cloud droplet number concentrations at cloud bases. Our results confirm previous estimates of particle hygroscopicity in this region.
Linhui Jiang, Yan Xia, Lu Wang, Xue Chen, Jianjie Ye, Tangyan Hou, Liqiang Wang, Yibo Zhang, Mengying Li, Zhen Li, Zhe Song, Yaping Jiang, Weiping Liu, Pengfei Li, Daniel Rosenfeld, John H. Seinfeld, and Shaocai Yu
Atmos. Chem. Phys., 21, 16985–17002, https://doi.org/10.5194/acp-21-16985-2021, https://doi.org/10.5194/acp-21-16985-2021, 2021
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This paper establishes a bottom-up approach to reveal a unique pattern of urban on-road vehicle emissions at a spatial resolution 1–3 orders of magnitude higher than current inventories. The results show that the hourly average on-road vehicle emissions of CO, NOx, HC, and PM2.5 are 74 kg, 40 kg, 8 kg, and 2 kg, respectively. Integrating our traffic-monitoring-based approach with urban measurements, we could address major data gaps between urban air pollutant emissions and concentrations.
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Short summary
Based on a deep-learning method, we established a global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology. This aims to promote a comprehensive understanding of cloud dynamics and cloud–climate feedback. Closed mesoscale cellular convection (MCC) clouds occur more frequently at night, while suppressed cumulus clouds exhibit remarkable decreases. Solid stratus and MCC cloud types show clear seasonal variations.
Based on a deep-learning method, we established a global classification dataset of daytime and...
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