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 paper
| 
04 Jul 2025
Data description paper |
| 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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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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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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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
EGUsphere, https://doi.org/10.5194/egusphere-2025-1526, https://doi.org/10.5194/egusphere-2025-1526, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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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.
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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
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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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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
EGUsphere, https://doi.org/10.5194/egusphere-2024-4135, https://doi.org/10.5194/egusphere-2024-4135, 2025
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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 (PI) and present-day (PD) 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 understanding of aerosol-cloud interactions.
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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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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Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-36, https://doi.org/10.5194/amt-2024-36, 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 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.
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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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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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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
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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.
Ramon Campos Braga, Daniel Rosenfeld, Ovid O. Krüger, Barbara Ervens, Bruna A. Holanda, Manfred Wendisch, Trismono Krisna, Ulrich Pöschl, Meinrat O. Andreae, Christiane Voigt, and Mira L. Pöhlker
Atmos. Chem. Phys., 21, 14079–14088, https://doi.org/10.5194/acp-21-14079-2021, https://doi.org/10.5194/acp-21-14079-2021, 2021
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Quantifying the precipitation within clouds is crucial for our understanding of the Earth's hydrological cycle. Using in situ measurements of cloud and rain properties over the Amazon Basin and Atlantic Ocean, we show here a linear relationship between the effective radius (re) and precipitation water content near the tops of convective clouds for different pollution states and temperature levels. Our results emphasize the role of re to determine both initiation and amount of precipitation.
Xin Lu, Feiyue Mao, Daniel Rosenfeld, Yannian Zhu, Zengxin Pan, and Wei Gong
Atmos. Chem. Phys., 21, 11979–12003, https://doi.org/10.5194/acp-21-11979-2021, https://doi.org/10.5194/acp-21-11979-2021, 2021
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In this paper, a novel method for retrieving cloud base height and geometric thickness is developed and applied to produce a global climatology of boundary layer clouds with a high accuracy. The retrieval is based on the 333 m resolution low-level cloud distribution as obtained from the CALIPSO lidar data. The main part of the study describes the variability of cloud vertical geometrical properties in space, season, and time of the day. Resultant new insights are presented.
Yaman Liu, Xinyi Dong, Minghuai Wang, Louisa K. Emmons, Yawen Liu, Yuan Liang, Xiao Li, and Manish Shrivastava
Atmos. Chem. Phys., 21, 8003–8021, https://doi.org/10.5194/acp-21-8003-2021, https://doi.org/10.5194/acp-21-8003-2021, 2021
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Secondary organic aerosol (SOA) is considered one of the most important uncertainties in climate modeling. We evaluate SOA performance in the Community Earth System Model version 2.1 (CESM2.1) configured with the Community Atmosphere Model version 6 with chemistry (CAM6-Chem) through a long-term simulation (1988–2019) with observations in the United States, which indicates monoterpene-formed SOA contributes most to the overestimation of SOA at the surface and underestimation in the upper air.
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
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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.
Yuwei Zhang, Jiwen Fan, Zhanqing Li, and Daniel Rosenfeld
Atmos. Chem. Phys., 21, 2363–2381, https://doi.org/10.5194/acp-21-2363-2021, https://doi.org/10.5194/acp-21-2363-2021, 2021
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Impacts of anthropogenic aerosols on deep convective clouds (DCCs) and precipitation are examined using both the Morrison bulk and spectral bin microphysics (SBM) schemes. With the SBM scheme, anthropogenic aerosols notably invigorate convective intensity and precipitation, causing better agreement between the simulated DCCs and observations; this effect is absent with the Morrison scheme, mainly due to limitations of the saturation adjustment approach for droplet condensation and evaporation.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
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Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Liqiang Wang, Shaocai Yu, Pengfei Li, Xue Chen, Zhen Li, Yibo Zhang, Mengying Li, Khalid Mehmood, Weiping Liu, Tianfeng Chai, Yannian Zhu, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 20, 14787–14800, https://doi.org/10.5194/acp-20-14787-2020, https://doi.org/10.5194/acp-20-14787-2020, 2020
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The Chinese government has made major strides in curbing anthropogenic emissions. In this study, we constrain a state-of-the-art CTM by a reliable data assimilation method with extensive chemical and meteorological observations. This comprehensive technical design provides a crucial advance in isolating the influences of emission changes and meteorological perturbations over the Yangtze River Delta (YRD) from 2016 to 2019, thus establishing the first map of the PM2.5 mitigation across the YRD.
Jiwen Fan, Yuwei Zhang, Zhanqing Li, Jiaxi Hu, and Daniel Rosenfeld
Atmos. Chem. Phys., 20, 14163–14182, https://doi.org/10.5194/acp-20-14163-2020, https://doi.org/10.5194/acp-20-14163-2020, 2020
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We investigate the urbanization-induced land and aerosol impacts on convective clouds and precipitation over Houston. We find that Houston urbanization notably enhances storm intensity and precipitation, with the anthropogenic aerosol effect more significant. Urban land effect strengthens sea-breeze circulation, leading to a faster development of warm cloud into mixed-phase cloud and earlier rain. The anthropogenic aerosol effect accelerates the development of storms into deep convection.
Yi Zeng, Minghuai Wang, Chun Zhao, Siyu Chen, Zhoukun Liu, Xin Huang, and Yang Gao
Geosci. Model Dev., 13, 2125–2147, https://doi.org/10.5194/gmd-13-2125-2020, https://doi.org/10.5194/gmd-13-2125-2020, 2020
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Dust aerosol can impact many processes of the Earth system, but large uncertainties still remain in dust simulations. In this study, we investigated dust simulation sensitivity to two dust emission schemes and three dry deposition schemes using WRF-Chem. An optimal combination of dry deposition scheme and dust emission scheme has been identified to best simulate the dust storm in comparison with observation. Our results highlight the importance of dry deposition schemes for dust simulation.
Khalid Mehmood, Yujie Wu, Liqiang Wang, Shaocai Yu, Pengfei Li, Xue Chen, Zhen Li, Yibo Zhang, Mengying Li, Weiping Liu, Yuesi Wang, Zirui Liu, Yannian Zhu, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 20, 2419–2443, https://doi.org/10.5194/acp-20-2419-2020, https://doi.org/10.5194/acp-20-2419-2020, 2020
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We selected June 2014 as our study period, which exhibited a complete evolution process of open biomass burning (OBB) dominated by open crop straw burning (OCSB) over central and eastern China (CEC). We established a constraining method that integrates ground-based PM2.5 measurements with the two-way coupled WRF-CMAQ model to derive optimal OBB emissions. It was found that these emissions could allow the model to reproduce meteorological and chemical fields over CEC during the study period.
Pascal Polonik, Christoph Knote, Tobias Zinner, Florian Ewald, Tobias Kölling, Bernhard Mayer, Meinrat O. Andreae, Tina Jurkat-Witschas, Thomas Klimach, Christoph Mahnke, Sergej Molleker, Christopher Pöhlker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, Christiane Voigt, Ralf Weigel, and Manfred Wendisch
Atmos. Chem. Phys., 20, 1591–1605, https://doi.org/10.5194/acp-20-1591-2020, https://doi.org/10.5194/acp-20-1591-2020, 2020
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A realistic representation of cloud–aerosol interactions is central to accurate climate projections. Here we combine observations collected during the ACRIDICON-CHUVA campaign with chemistry-transport simulations to evaluate the model’s ability to represent the indirect effects of biomass burning aerosol on cloud microphysics. We find an upper limit for the model sensitivity on cloud condensation nuclei concentrations well below the levels reached during the burning season in the Amazon Basin.
Edward Gryspeerdt, Johannes Mülmenstädt, Andrew Gettelman, Florent F. Malavelle, Hugh Morrison, David Neubauer, Daniel G. Partridge, Philip Stier, Toshihiko Takemura, Hailong Wang, Minghuai Wang, and Kai Zhang
Atmos. Chem. Phys., 20, 613–623, https://doi.org/10.5194/acp-20-613-2020, https://doi.org/10.5194/acp-20-613-2020, 2020
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Aerosol radiative forcing is a key uncertainty in our understanding of the human forcing of the climate, with much of this uncertainty coming from aerosol impacts on clouds. Observation-based estimates of the radiative forcing are typically smaller than those from global models, but it is not clear if they are more reliable. This work shows how the forcing components in global climate models can be identified, highlighting similarities between the two methods and areas for future investigation.
Aijun Ding, Xin Huang, Wei Nie, Xuguang Chi, Zheng Xu, Longfei Zheng, Zhengning Xu, Yuning Xie, Ximeng Qi, Yicheng Shen, Peng Sun, Jiaping Wang, Lei Wang, Jianning Sun, Xiu-Qun Yang, Wei Qin, Xiangzhi Zhang, Wei Cheng, Weijing Liu, Liangbao Pan, and Congbin Fu
Atmos. Chem. Phys., 19, 11791–11801, https://doi.org/10.5194/acp-19-11791-2019, https://doi.org/10.5194/acp-19-11791-2019, 2019
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Based on continuous measurement at the SORPES statin in Nanjing, eastern China, we report the trend of PM2.5 and relevant chemical species there during 2011–2018. We found significant reduction of PM2.5 in both winter and early summer due to emission reduction of fossil-fuel combustion and open biomass burning, respectively. Reduction of fossil-fuel combustions contributed to 76 % of the wintertime PM2.5 decrease, with the remaining 24 % being caused by the change of meteorology.
Qiuji Ding, Jianning Sun, Xin Huang, Aijun Ding, Jun Zou, Xiuqun Yang, and Congbin Fu
Atmos. Chem. Phys., 19, 7759–7774, https://doi.org/10.5194/acp-19-7759-2019, https://doi.org/10.5194/acp-19-7759-2019, 2019
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Aerosol plays an important role in advection–radiation fog formation in eastern China though stabilizing atmospheric stratification and enhancing onshore flow. For the fog–haze episode in December 2013, the effect of aerosol–radiation interaction overwhelmed that of aerosol–cloud interaction. Light-absorbing aerosol like black carbon was more crucial than scattering aerosols. This paper highlights the importance of interaction among aerosol, regional circulation and boundary layer.
Ann M. Fridlind, Marcus van Lier-Walqui, Scott Collis, Scott E. Giangrande, Robert C. Jackson, Xiaowen Li, Toshihisa Matsui, Richard Orville, Mark H. Picel, Daniel Rosenfeld, Alexander Ryzhkov, Richard Weitz, and Pengfei Zhang
Atmos. Meas. Tech., 12, 2979–3000, https://doi.org/10.5194/amt-12-2979-2019, https://doi.org/10.5194/amt-12-2979-2019, 2019
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Weather radars are offering improved capabilities to investigate storm physics, which remain poorly understood. We investigate enhanced use of such data near Houston, Texas, where pollution sources often provide a convenient contrast between polluted and clean air. We conclude that Houston is a favorable location to conduct a future field campaign during June through September because isolated storms are common and tend to last an hour, allowing frequent observations of a full life cycle.
Zhibo Zhang, Hua Song, Po-Lun Ma, Vincent E. Larson, Minghuai Wang, Xiquan Dong, and Jianwu Wang
Atmos. Chem. Phys., 19, 1077–1096, https://doi.org/10.5194/acp-19-1077-2019, https://doi.org/10.5194/acp-19-1077-2019, 2019
Ge Zhang, Yang Gao, Wenju Cai, L. Ruby Leung, Shuxiao Wang, Bin Zhao, Minghuai Wang, Huayao Shan, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 19, 565–576, https://doi.org/10.5194/acp-19-565-2019, https://doi.org/10.5194/acp-19-565-2019, 2019
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Based on observed data, this study reveals a distinct seesaw feature of abnormally high and low PM2.5 concentrations in December 2015 and January 2016 over North China. The mechanism of the seesaw pattern was found to be linked to a super El Niño and the Arctic Oscillation (AO). During the mature phase of El Niño in December 2015, the weakened East Asian winter monsoon favors strong haze formation; however, the circulation pattern was reversed in the next month due to the phase change of the AO.
Zhen Peng, Lili Lei, Zhiquan Liu, Jianning Sun, Aijun Ding, Junmei Ban, Dan Chen, Xingxia Kou, and Kekuan Chu
Atmos. Chem. Phys., 18, 17387–17404, https://doi.org/10.5194/acp-18-17387-2018, https://doi.org/10.5194/acp-18-17387-2018, 2018
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An EnKF system was developed to simultaneously assimilate multiple surface measurements, including PM10, PM2.5, SO2, NO2, O3, and CO, via the joint adjustment of ICs and source emissions. Large improvements were achieved in the first 24 h forecast for PM2.5, PM10, SO2, and CO during an extreme haze episode that occurred in early October 2014 over the North China Plain, but no improvements were achieved for NO2 and O3.
Jianping Guo, Huan Liu, Zhanqing Li, Daniel Rosenfeld, Mengjiao Jiang, Weixin Xu, Jonathan H. Jiang, Jing He, Dandan Chen, Min Min, and Panmao Zhai
Atmos. Chem. Phys., 18, 13329–13343, https://doi.org/10.5194/acp-18-13329-2018, https://doi.org/10.5194/acp-18-13329-2018, 2018
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Objective analysis has been used to discriminate between the local- and synoptic-scale precipitations based on wind and pressure fields at 500 hPa. Aerosol is found to be linked with changes in the vertical structure of precipitation, depending on precipitation regimes. There has been some success in separating aerosol and meteorological influences on precipitation.
Hua Song, Zhibo Zhang, Po-Lun Ma, Steven Ghan, and Minghuai Wang
Geosci. Model Dev., 11, 3147–3158, https://doi.org/10.5194/gmd-11-3147-2018, https://doi.org/10.5194/gmd-11-3147-2018, 2018
Luiz A. T. Machado, Alan J. P. Calheiros, Thiago Biscaro, Scott Giangrande, Maria A. F. Silva Dias, Micael A. Cecchini, Rachel Albrecht, Meinrat O. Andreae, Wagner F. Araujo, Paulo Artaxo, Stephan Borrmann, Ramon Braga, Casey Burleyson, Cristiano W. Eichholz, Jiwen Fan, Zhe Feng, Gilberto F. Fisch, Michael P. Jensen, Scot T. Martin, Ulrich Pöschl, Christopher Pöhlker, Mira L. Pöhlker, Jean-François Ribaud, Daniel Rosenfeld, Jaci M. B. Saraiva, Courtney Schumacher, Ryan Thalman, David Walter, and Manfred Wendisch
Atmos. Chem. Phys., 18, 6461–6482, https://doi.org/10.5194/acp-18-6461-2018, https://doi.org/10.5194/acp-18-6461-2018, 2018
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This overview discuss the main precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin. It presents a review of the knowledge acquired about cloud processes and rainfall formation in Amazonas. In addition, this study provides a characterization of the seasonal variation and rainfall sensitivities to topography, surface cover, and aerosol concentration. Airplane measurements were evaluated to characterize and contrast cloud microphysical properties.
Heming Bai, Cheng Gong, Minghuai Wang, Zhibo Zhang, and Tristan L'Ecuyer
Atmos. Chem. Phys., 18, 1763–1783, https://doi.org/10.5194/acp-18-1763-2018, https://doi.org/10.5194/acp-18-1763-2018, 2018
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Precipitation susceptibility to aerosol perturbation plays a key role in understanding aerosol–cloud interactions and for constraining aerosol indirect effects. Here, multisensor aerosol and cloud products from A-Train satellites are analyzed to estimate precipitation susceptibility. Compared to precipitation intensity susceptibility, precipitation frequency susceptibility demonstrates relatively robust features across different retrieval products.
Bingliang Zhuang, Tijian Wang, Jane Liu, Huizheng Che, Yong Han, Yu Fu, Shu Li, Min Xie, Mengmeng Li, Pulong Chen, Huimin Chen, Xiu-qun Yang, and Jianning Sun
Atmos. Chem. Phys., 18, 1419–1436, https://doi.org/10.5194/acp-18-1419-2018, https://doi.org/10.5194/acp-18-1419-2018, 2018
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Aerosols have a significant influence on climate changes. Their uncertainties could be substantially reduced if observation data were used. The properties and the DRF of fractionated aerosols in the western Yangtze River Delta are investigated based on measurements. Results reveal the characteristics of the optical properties and DRFs of different types of fractionated aerosols, which can be further used to improve aerosol modelling performance in the eastern regions of China.
Meinrat O. Andreae, Armin Afchine, Rachel Albrecht, Bruna Amorim Holanda, Paulo Artaxo, Henrique M. J. Barbosa, Stephan Borrmann, Micael A. Cecchini, Anja Costa, Maximilian Dollner, Daniel Fütterer, Emma Järvinen, Tina Jurkat, Thomas Klimach, Tobias Konemann, Christoph Knote, Martina Krämer, Trismono Krisna, Luiz A. T. Machado, Stephan Mertes, Andreas Minikin, Christopher Pöhlker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, Daniel Sauer, Hans Schlager, Martin Schnaiter, Johannes Schneider, Christiane Schulz, Antonio Spanu, Vinicius B. Sperling, Christiane Voigt, Adrian Walser, Jian Wang, Bernadett Weinzierl, Manfred Wendisch, and Helmut Ziereis
Atmos. Chem. Phys., 18, 921–961, https://doi.org/10.5194/acp-18-921-2018, https://doi.org/10.5194/acp-18-921-2018, 2018
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We made airborne measurements of aerosol particle concentrations and properties over the Amazon Basin. We found extremely high concentrations of very small particles in the region between 8 and 14 km altitude all across the basin, which had been recently formed by gas-to-particle conversion at these altitudes. This makes the upper troposphere a very important source region of atmospheric particles with significant implications for the Earth's climate system.
Micael A. Cecchini, Luiz A. T. Machado, Manfred Wendisch, Anja Costa, Martina Krämer, Meinrat O. Andreae, Armin Afchine, Rachel I. Albrecht, Paulo Artaxo, Stephan Borrmann, Daniel Fütterer, Thomas Klimach, Christoph Mahnke, Scot T. Martin, Andreas Minikin, Sergej Molleker, Lianet H. Pardo, Christopher Pöhlker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, and Bernadett Weinzierl
Atmos. Chem. Phys., 17, 14727–14746, https://doi.org/10.5194/acp-17-14727-2017, https://doi.org/10.5194/acp-17-14727-2017, 2017
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This study introduces and explores the concept of gamma phase space. This space is able to represent all possible variations in the cloud droplet size distributions (DSDs). The methodology was applied to recent in situ aircraft measurements over the Amazon. It is shown that the phase space is able to represent several processes occurring in the clouds in a simple manner. The consequences for cloud studies, modeling, and the representation of the transition from warm to mixed phase are discussed.
Ramon Campos Braga, Daniel Rosenfeld, Ralf Weigel, Tina Jurkat, Meinrat O. Andreae, Manfred Wendisch, Ulrich Pöschl, Christiane Voigt, Christoph Mahnke, Stephan Borrmann, Rachel I. Albrecht, Sergej Molleker, Daniel A. Vila, Luiz A. T. Machado, and Lucas Grulich
Atmos. Chem. Phys., 17, 14433–14456, https://doi.org/10.5194/acp-17-14433-2017, https://doi.org/10.5194/acp-17-14433-2017, 2017
Caiwang Zheng, Chuanfeng Zhao, Yannian Zhu, Yang Wang, Xiaoqin Shi, Xiaolin Wu, Tianmeng Chen, Fang Wu, and Yanmei Qiu
Atmos. Chem. Phys., 17, 13473–13489, https://doi.org/10.5194/acp-17-13473-2017, https://doi.org/10.5194/acp-17-13473-2017, 2017
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This study analyzes influential factors including the aerosol type, relative humidity (RH), atmospheric boundary layer height (BLH), wind speed and direction, and aerosol vertical structure to the AOD–PM2.5 relationship. It shows that the ratio of PM2.5 to AOD, η, varies a lot with aerosol type. η is smaller for scattering-dominant (coarse mode) than for absorbing-dominant (fine mode) aerosol. The higher the RH (BLH), the larger (smaller) the η. η also decreases with the surface wind speed.
Micael A. Cecchini, Luiz A. T. Machado, Meinrat O. Andreae, Scot T. Martin, Rachel I. Albrecht, Paulo Artaxo, Henrique M. J. Barbosa, Stephan Borrmann, Daniel Fütterer, Tina Jurkat, Christoph Mahnke, Andreas Minikin, Sergej Molleker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, Christiane Voigt, Bernadett Weinzierl, and Manfred Wendisch
Atmos. Chem. Phys., 17, 10037–10050, https://doi.org/10.5194/acp-17-10037-2017, https://doi.org/10.5194/acp-17-10037-2017, 2017
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We study the effects of aerosol particles and updraft speed on the warm phase of Amazonian clouds. We expand the sensitivity analysis usually found in the literature by concomitantly considering cloud evolution and the effects on droplet size distribution (DSD) shape. The quantitative results show that particle concentration is the primary driver for the vertical profiles of effective diameter and droplet concentration in the warm phase of Amazonian convective clouds.
Kevin J. Sanchez, Gregory C. Roberts, Radiance Calmer, Keri Nicoll, Eyal Hashimshoni, Daniel Rosenfeld, Jurgita Ovadnevaite, Jana Preissler, Darius Ceburnis, Colin O'Dowd, and Lynn M. Russell
Atmos. Chem. Phys., 17, 9797–9814, https://doi.org/10.5194/acp-17-9797-2017, https://doi.org/10.5194/acp-17-9797-2017, 2017
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Unmanned aerial vehicles are equipped with meteorological sensors to measure cloud properties. The measurements are used to calculate the amount of solar radiation reflected by the clouds and compared to simulation results. The uncertainties related to radiative forcing in the simulations are from the lack of mixing in the boundary layer and mixing of dry air into the cloud top. Conservative variables are used to calculate the amount of air mixed into cloud top to minimize these uncertainties.
Evelyn Jäkel, Manfred Wendisch, Trismono C. Krisna, Florian Ewald, Tobias Kölling, Tina Jurkat, Christiane Voigt, Micael A. Cecchini, Luiz A. T. Machado, Armin Afchine, Anja Costa, Martina Krämer, Meinrat O. Andreae, Ulrich Pöschl, Daniel Rosenfeld, and Tianle Yuan
Atmos. Chem. Phys., 17, 9049–9066, https://doi.org/10.5194/acp-17-9049-2017, https://doi.org/10.5194/acp-17-9049-2017, 2017
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Vertical profiles of the cloud particle phase state in tropical deep convective clouds (DCCs) were investigated using airborne imaging spectrometer measurements during the ACRIDICON-CHUVA campaign, which was conducted over the Brazilian rainforest in September 2014. A phase discrimination retrieval was applied to observations of clouds formed in different aerosol conditions. The profiles were compared to in situ and satellite measurements.
Ramon Campos Braga, Daniel Rosenfeld, Ralf Weigel, Tina Jurkat, Meinrat O. Andreae, Manfred Wendisch, Mira L. Pöhlker, Thomas Klimach, Ulrich Pöschl, Christopher Pöhlker, Christiane Voigt, Christoph Mahnke, Stephan Borrmann, Rachel I. Albrecht, Sergej Molleker, Daniel A. Vila, Luiz A. T. Machado, and Paulo Artaxo
Atmos. Chem. Phys., 17, 7365–7386, https://doi.org/10.5194/acp-17-7365-2017, https://doi.org/10.5194/acp-17-7365-2017, 2017
Xueqian Wang, Weidong Guo, Bo Qiu, Ye Liu, Jianning Sun, and Aijun Ding
Atmos. Chem. Phys., 17, 4989–4996, https://doi.org/10.5194/acp-17-4989-2017, https://doi.org/10.5194/acp-17-4989-2017, 2017
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Land use or cover change is a fundamental anthropogenic forcing for climate change. Based on field observations, we quantified the contributions of different factors to surface temperature change and deepened the understanding of its mechanisms. We found evaporative cooling plays the most important role in the temperature change, while radiative forcing, which is traditionally emphasized, is not significant. This study provided firsthand evidence to verify the model results in IPCC AR5.
Jiwen Fan, L. Ruby Leung, Daniel Rosenfeld, and Paul J. DeMott
Atmos. Chem. Phys., 17, 1017–1035, https://doi.org/10.5194/acp-17-1017-2017, https://doi.org/10.5194/acp-17-1017-2017, 2017
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How orographic mixed-phase clouds respond to changes in cloud condensation nuclei (CCN) and ice nucleating particles (INPs) is highly uncertain. We conducted this study to improve understanding of these processes. We found a new mechanism through which CCN can invigorate orographic mixed-phase clouds and drastically intensify snow precipitation when CCN concentrations are high. Our findings have very important implications for orographic precipitation in polluted regions.
Cheng Zhou, Joyce E. Penner, Guangxing Lin, Xiaohong Liu, and Minghuai Wang
Atmos. Chem. Phys., 16, 12411–12424, https://doi.org/10.5194/acp-16-12411-2016, https://doi.org/10.5194/acp-16-12411-2016, 2016
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We examined the different ice nucleation parameterization factors that affect the simulated ice number concentrations in cirrus clouds in the upper troposphere using the CAM5 model. We examined the effect from three different updraft velocities (from low to high), two different water vapour accommodation coefficients (α = 0.1 or 1), the effect of including vapour deposition onto pre-existing ice particles during ice nucleation, and the effect of including SOA as heterogeneous ice nuclei.
Xin Huang, Aijun Ding, Lixia Liu, Qiang Liu, Ke Ding, Xiaorui Niu, Wei Nie, Zheng Xu, Xuguang Chi, Minghuai Wang, Jianning Sun, Weidong Guo, and Congbin Fu
Atmos. Chem. Phys., 16, 10063–10082, https://doi.org/10.5194/acp-16-10063-2016, https://doi.org/10.5194/acp-16-10063-2016, 2016
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We conducted a comprehensive modelling work to understand the impact of biomass burning on synoptic weather during agricultural burning season in East China. We demonstrated that the numerical model with fire emission, chemical processes, and aerosol–meteorology online coupled could reproduce the change of air temperature and precipitation induced by air pollution during this event. This study highlights the importance of including human activities in numerical-model-based weather forecast.
Weidong Guo, Xueqian Wang, Jianning Sun, Aijun Ding, and Jun Zou
Atmos. Chem. Phys., 16, 9875–9890, https://doi.org/10.5194/acp-16-9875-2016, https://doi.org/10.5194/acp-16-9875-2016, 2016
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Basic characteristics of land–atmosphere interactions at four neighboring sites with different underlying surfaces in southern China, a typical monsoon region, are analyzed systematically. Despite the same climate background, the differences in land surface characteristics like albedo and aerodynamic roughness length due to land use/cover change exert distinct influences on the surface radiative budget and energy allocation and result in differences of near-surface micrometeorological elements.
Renmin Yuan, Tao Luo, Jianning Sun, Hao Liu, Yunfei Fu, and Zhien Wang
Atmos. Meas. Tech., 9, 1925–1937, https://doi.org/10.5194/amt-9-1925-2016, https://doi.org/10.5194/amt-9-1925-2016, 2016
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Atmospheric aerosol has a great influence on the natural environment. Despite consistent research efforts, there are still uncertainties in our understanding of its effects due to poor knowledge of aerosol vertical transport. In this paper, a new method for measuring atmospheric aerosol mass vertical transport flux is developed based on the similarity theory, the theory of light propagation, and the observations and studies of the atmospheric equivalent refractive index.
Shipeng Zhang, Minghuai Wang, Steven J. Ghan, Aijun Ding, Hailong Wang, Kai Zhang, David Neubauer, Ulrike Lohmann, Sylvaine Ferrachat, Toshihiko Takeamura, Andrew Gettelman, Hugh Morrison, Yunha Lee, Drew T. Shindell, Daniel G. Partridge, Philip Stier, Zak Kipling, and Congbin Fu
Atmos. Chem. Phys., 16, 2765–2783, https://doi.org/10.5194/acp-16-2765-2016, https://doi.org/10.5194/acp-16-2765-2016, 2016
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The variation of aerosol indirect effects (AIE) in several climate models is investigated across different dynamical regimes. Regimes with strong large-scale ascent are shown to be as important as stratocumulus regimes in studying AIE. AIE over regions with high monthly large-scale surface precipitation rate contributes the most to the total aerosol indirect forcing. These results point to the need to reduce the uncertainty in AIE in different dynamical regimes.
Xin Huang, Luxi Zhou, Aijun Ding, Ximeng Qi, Wei Nie, Minghuai Wang, Xuguang Chi, Tuukka Petäjä, Veli-Matti Kerminen, Pontus Roldin, Anton Rusanen, Markku Kulmala, and Michael Boy
Atmos. Chem. Phys., 16, 2477–2492, https://doi.org/10.5194/acp-16-2477-2016, https://doi.org/10.5194/acp-16-2477-2016, 2016
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By combining a regional model and a box model, this study simulates new particle formation in Nanjing, China, when the air masses were affected by anthropogenic activities, biogenic emissions, or mixed ocean and continental sources. The simulations reveal that biogenic organic compounds play a vital role in growth of newly formed clusters. This novel combination of two models makes it possible to accomplish new particle formation simulation without direct measurements of all chemical species.
K. Thayer-Calder, A. Gettelman, C. Craig, S. Goldhaber, P. A. Bogenschutz, C.-C. Chen, H. Morrison, J. Höft, E. Raut, B. M. Griffin, J. K. Weber, V. E. Larson, M. C. Wyant, M. Wang, Z. Guo, and S. J. Ghan
Geosci. Model Dev., 8, 3801–3821, https://doi.org/10.5194/gmd-8-3801-2015, https://doi.org/10.5194/gmd-8-3801-2015, 2015
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This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that is implemented in CAM v5.3. We show mean climate and tropical variability results from global simulations. The model has a degradation in precipitation skill but improvements in shortwave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. We also show estimation of computational expense and sensitivity to number of subcolumns.
X. M. Qi, A. J. Ding, W. Nie, T. Petäjä, V.-M. Kerminen, E. Herrmann, Y. N. Xie, L. F. Zheng, H. Manninen, P. Aalto, J. N. Sun, Z. N. Xu, X. G. Chi, X. Huang, M. Boy, A. Virkkula, X.-Q. Yang, C. B. Fu, and M. Kulmala
Atmos. Chem. Phys., 15, 12445–12464, https://doi.org/10.5194/acp-15-12445-2015, https://doi.org/10.5194/acp-15-12445-2015, 2015
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We report 2 years of measurements of submicron particles at the SORPES station and provide a comprehensive understanding of main factors controlling temporal variation of the aerosol size distribution and NPF in eastern China. The number concentrations of total particles at Nanjing were comparable to other Chinese megacities but the frequency of NPF was much higher. Year-to-year differences of meteorological conditions could significantly influence the seasonal cycle of NPF and growth.
R. Yuan, T. Luo, J. Sun, Z. Zeng, C. Ge, and Y. Fu
Atmos. Chem. Phys., 15, 2521–2531, https://doi.org/10.5194/acp-15-2521-2015, https://doi.org/10.5194/acp-15-2521-2015, 2015
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This study developed a theoretical framework to analyse the contribution of absorption to scintillation, which can be used to derive the imaginary part of the ARISP in the urban atmospheric boundary layer from scintillation measurements. In this study, a simple expression for the imaginary part of the ARISP is obtained, which can be conveniently used to determine the imaginary part of the ARISP from LAS measurements. The experimental results showed good agreement with the presented theory.
W. Nie, A. J. Ding, Y. N. Xie, Z. Xu, H. Mao, V.-M. Kerminen, L. F. Zheng, X. M. Qi, X. Huang, X.-Q. Yang, J. N. Sun, E. Herrmann, T. Petäjä, M. Kulmala, and C. B. Fu
Atmos. Chem. Phys., 15, 1147–1159, https://doi.org/10.5194/acp-15-1147-2015, https://doi.org/10.5194/acp-15-1147-2015, 2015
R. L. Storer, B. M. Griffin, J. Höft, J. K. Weber, E. Raut, V. E. Larson, M. Wang, and P. J. Rasch
Geosci. Model Dev., 8, 1–19, https://doi.org/10.5194/gmd-8-1-2015, https://doi.org/10.5194/gmd-8-1-2015, 2015
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Representing clouds in climate models is a challenging problem. It is particularly difficult to represent deep convective clouds and, historically, deep convective parameterization is separate from the representation of other cloud types. Here we use a single-column cloud model to simulate three deep convective cases, and two shallow cloud cases. The results look reasonable, demonstrating that it may be possible to use one parameterization within a climate model for all cloud types.
D. Rosenfeld, G. Liu, X. Yu, Y. Zhu, J. Dai, X. Xu, and Z. Yue
Atmos. Chem. Phys., 14, 2479–2496, https://doi.org/10.5194/acp-14-2479-2014, https://doi.org/10.5194/acp-14-2479-2014, 2014
H. Wang, R. C. Easter, P. J. Rasch, M. Wang, X. Liu, S. J. Ghan, Y. Qian, J.-H. Yoon, P.-L. Ma, and V. Vinoj
Geosci. Model Dev., 6, 765–782, https://doi.org/10.5194/gmd-6-765-2013, https://doi.org/10.5194/gmd-6-765-2013, 2013
K. Zhang, X. Liu, M. Wang, J. M. Comstock, D. L. Mitchell, S. Mishra, and G. G. Mace
Atmos. Chem. Phys., 13, 4963–4982, https://doi.org/10.5194/acp-13-4963-2013, https://doi.org/10.5194/acp-13-4963-2013, 2013
Related subject area
Domain: ESSD – Atmosphere | Subject: Atmospheric chemistry and physics
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Large synthesis of in situ field measurements of the size distribution of mineral dust aerosols across their life cycles
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GHOST: a globally harmonised dataset of surface atmospheric composition measurements
Changes in air pollutant emissions in China during two clean-air action periods derived from the newly developed Inversed Emission Inventory for Chinese Air Quality (CAQIEI)
Version 1 NOAA-20/OMPS Nadir Mapper total column SO2 product: continuation of NASA long-term global data record
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Multiwavelength aerosol lidars at the Maïdo supersite, Réunion Island, France: instrument description, data processing chain, and quality assessment
PM2.5 concentrations based on near-surface visibility in the Northern Hemisphere from 1959 to 2022
MAP-IO: an atmospheric and marine observatory program on board Marion Dufresne over the Southern Ocean
Retrieving ground-level PM2.5 concentrations in China (2013–2021) with a numerical-model-informed testbed to mitigate sample-imbalance-induced biases
Reconstructing long-term (1980–2022) daily ground particulate matter concentrations in India (LongPMInd)
Visibility-derived aerosol optical depth over global land from 1959 to 2021
Characterizing clouds with the CCClim dataset, a machine learning cloud class climatology
A Level 3 monthly gridded ice cloud dataset derived from 12 years of CALIOP measurements
IPB-MSA&SO4: a daily 0.25° resolution dataset of in situ-produced biogenic methanesulfonic acid and sulfate over the North Atlantic during 1998–2022 based on machine learning
Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence
The Total Carbon Column Observing Network's GGG2020 data version
Global anthropogenic emissions (CAMS-GLOB-ANT) for the Copernicus Atmosphere Monitoring Service simulations of air quality forecasts and reanalyses
Deep Convective Microphysics Experiment (DCMEX) coordinated aircraft and ground observations: microphysics, aerosol, and dynamics during cumulonimbus development
High-resolution physicochemical dataset of atmospheric aerosols over the Tibetan Plateau and its surroundings
Introduction to the NJIAS Himawari-8/9 Cloud Feature Dataset for climate and typhoon research
The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020
PalVol v1: a proxy-based semi-stochastic ensemble reconstruction of volcanic stratospheric sulfur injection for the last glacial cycle (140 000–50 BP)
Ground- and ship-based microwave radiometer measurements during EUREC4A
Shortwave and longwave components of the surface radiation budget measured at the Thule High Arctic Atmospheric Observatory, Northern Greenland
Cloud condensation nuclei concentrations derived from the CAMS reanalysis
A merged continental planetary boundary layer height dataset based on high-resolution radiosonde measurements, ERA5 reanalysis, and GLDAS
12 years of continuous atmospheric O2, CO2 and APO data from Weybourne Atmospheric Observatory in the United Kingdom
CLAAS-3: the third edition of the CM SAF cloud data record based on SEVIRI observations
Peiyuan Jiao, Chengzhi Xing, Yikai Li, Xiangguang Ji, Wei Tan, Qihua Li, Haoran Liu, and Cheng Liu
Earth Syst. Sci. Data, 17, 3167–3187, https://doi.org/10.5194/essd-17-3167-2025, https://doi.org/10.5194/essd-17-3167-2025, 2025
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Vertical profile observations are key to understanding regional air pollution but remain scarce due to existing limits. This study presents a high-time-resolution (ca. 15 min) dataset of aerosol, nitrogen dioxide, and formaldehyde vertical profiles from 32 sites in China (2019–2023) using passive remote sensing. It documents vertical distribution, seasonal variations, and diurnal patterns, revealing long-term trends. Data are available at Zenodo under https://doi.org/10.5281/zenodo.15211604.
Juan A. Añel, Juan-Carlos Antuña-Marrero, Antonio Cid Samamed, Celia Pérez-Souto, Laura de la Torre, Maria Antonia Valente, Yuri Brugnara, Alfonso Saiz-Lopez, and Luis Gimeno
Earth Syst. Sci. Data, 17, 2437–2446, https://doi.org/10.5194/essd-17-2437-2025, https://doi.org/10.5194/essd-17-2437-2025, 2025
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Ozone (discovered in 1837) was first measured in 1847 using paper strips that reacted with ozone, providing an indication of its concentration based on colour changes. Here, we present the data, covering over 60 years of daily observations conducted along the eastern Atlantic coast, spanning from the tropics to the northern extratropics.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Rajesh Kumar, Piyush Bhardwaj, Cenlin He, Jennifer Boehnert, Forrest Lacey, Stefano Alessandrini, Kevin Sampson, Matthew Casali, Scott Swerdlin, Olga Wilhelmi, Gabriele G. Pfister, Benjamin Gaubert, and Helen Worden
Earth Syst. Sci. Data, 17, 1807–1834, https://doi.org/10.5194/essd-17-1807-2025, https://doi.org/10.5194/essd-17-1807-2025, 2025
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We have created a 14-year hourly air quality dataset at 12 km resolution by combining satellite observations of atmospheric composition with air quality models over the contiguous United States (CONUS). The dataset has been found to reproduce key observed features of air quality over the CONUS. To enable easy visualization and interpretation of county-level air quality measures and trends by stakeholders, an ArcGIS air quality dashboard has also been developed.
Alexandra M. Catena, Mackenzie L. Smith, Lee T. Murray, Eric M. Leibensperger, Jie Zhang, Margaret J. Schwab, and James J. Schwab
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-135, https://doi.org/10.5194/essd-2025-135, 2025
Revised manuscript accepted for ESSD
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Methane and carbon dioxide emission rates were calculated for facilities across several sectors in New York State using aerial observations. Of the sampled facilities, landfills dominated the methane emission rates while combustion facilities had the highest carbon dioxide emission rates, followed by landfills. The self-reported EPA inventory is mostly underestimating landfill methane emissions apart from a few facilities with comparable numbers.
Giulio Bongiovanni, Michael Matiu, Alice Crespi, Anna Napoli, Bruno Majone, and Dino Zardi
Earth Syst. Sci. Data, 17, 1367–1391, https://doi.org/10.5194/essd-17-1367-2025, https://doi.org/10.5194/essd-17-1367-2025, 2025
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EEAR-Clim is a new and unprecedented observational dataset gathering in situ daily measurements of air temperature and precipitation from a network of about 9000 weather stations covering the European Alps. Data collected, including time series from recordings up to 2020 and time series significantly enhancing data coverage at high elevations, were tested for quality and homogeneity. The dataset aims to serve as a powerful tool for better understanding climate change over the European Alpine region.
André Ehrlich, Susanne Crewell, Andreas Herber, Marcus Klingebiel, Christof Lüpkes, Mario Mech, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Matthias Buschmann, Hans-Christian Clemen, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Andreas Giez, Sarah Grawe, Christophe Gourbeyre, Jörg Hartmann, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsófia Jurányi, Benjamin Kirbus, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Christian Mallaun, Johanna Mayer, Stephan Mertes, Guillaume Mioche, Manuel Moser, Hanno Müller, Veronika Pörtge, Nils Risse, Greg Roberts, Sophie Rosenburg, Johannes Röttenbacher, Michael Schäfer, Jonas Schaefer, Andreas Schäfler, Imke Schirmacher, Johannes Schneider, Sabrina Schnitt, Frank Stratmann, Christian Tatzelt, Christiane Voigt, Andreas Walbröl, Anna Weber, Bruno Wetzel, Martin Wirth, and Manfred Wendisch
Earth Syst. Sci. Data, 17, 1295–1328, https://doi.org/10.5194/essd-17-1295-2025, https://doi.org/10.5194/essd-17-1295-2025, 2025
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This paper provides an overview of the HALO–(AC)3 aircraft campaign data sets, the campaign-specific instrument operation, data processing, and data quality. The data set comprises in situ and remote sensing observations from three research aircraft: HALO, Polar 5, and Polar 6. All data are published in the PANGAEA database by instrument-separated data subsets. It is highlighted how the scientific analysis of the HALO–(AC)3 data benefits from the coordinated operation of three aircraft.
Janusz W. Krzyścin, Agnieszka Czerwińska, Bonawentura Rajewska-Więch, Janusz Jarosławski, Piotr S. Sobolewski, and Izabela Pawlak
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-622, https://doi.org/10.5194/essd-2024-622, 2025
Revised manuscript accepted for ESSD
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Time series (1976−2023) of biologically effective (for skin redness, vitamin D3 production and psoriasis healing) daily radiant exposure (RE) at Belsk from standard erythemal biometers are examined. Comparisons of the measured data for cloudless days with values from a radiation transfer model provide a basis for data homogenization. Averaged results from different versions of the recalculated data give the 1976−2004 trend of about 6 % per 10 years in annual RE for all biological effects.
Simo Tukiainen, Tuomas Siipola, Niko Leskinen, and Ewan O'Connor
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-605, https://doi.org/10.5194/essd-2024-605, 2025
Revised manuscript accepted for ESSD
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Measurement campaigns are crucial for advancing the understanding of complex cloud–aerosol interactions in the atmosphere. Ground-based remote sensing measurements were conducted in Kenttärova, Finland, during the PaCE 2022 campaign. These measurements were processed using the Cloudnet methodology, and the data are available through the ACTRIS Cloudnet data portal.
Yugo Kanaya, Roberto Sommariva, Alfonso Saiz-Lopez, Andrea Mazzeo, Theodore K. Koenig, Kaori Kawana, James E. Johnson, Aurélie Colomb, Pierre Tulet, Suzie Molloy, Ian E. Galbally, Rainer Volkamer, Anoop Mahajan, John W. Halfacre, Paul B. Shepson, Julia Schmale, Hélène Angot, Byron Blomquist, Matthew D. Shupe, Detlev Helmig, Junsu Gil, Meehye Lee, Sean C. Coburn, Ivan Ortega, Gao Chen, James Lee, Kenneth C. Aikin, David D. Parrish, John S. Holloway, Thomas B. Ryerson, Ilana B. Pollack, Eric J. Williams, Brian M. Lerner, Andrew J. Weinheimer, Teresa Campos, Frank M. Flocke, J. Ryan Spackman, Ilann Bourgeois, Jeff Peischl, Chelsea R. Thompson, Ralf M. Staebler, Amir A. Aliabadi, Wanmin Gong, Roeland Van Malderen, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Juan Carlos Gómez Martin, Masatomo Fujiwara, Katie Read, Matthew Rowlinson, Keiichi Sato, Junichi Kurokawa, Yoko Iwamoto, Fumikazu Taketani, Hisahiro Takashima, Monica Navarro Comas, Marios Panagi, and Martin G. Schultz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-566, https://doi.org/10.5194/essd-2024-566, 2025
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The first comprehensive dataset of tropospheric ozone over oceans/polar regions is presented, including 77 ship/buoy and 48 aircraft campaign observations (1977–2022, 0–5000 m altitude), supplemented by ozonesonde and surface data. Air masses isolated from land for 72+ hours are systematically selected as essentially oceanic. Among the 11 global regions, they show daytime decreases of 10–16% in the tropics, while near-zero depletions are rare, unlike in the Arctic, implying different mechanisms.
Isolde Glissenaar, Klaas Folkert Boersma, Isidora Anglou, Pieter Rijsdijk, Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Michel Van Roozendael, and Henk Eskes
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-616, https://doi.org/10.5194/essd-2024-616, 2025
Revised manuscript accepted for ESSD
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We developed a new global dataset of nitrogen dioxide (NO2) levels in the lower atmosphere, using data from TROPOMI for 2018–2021. This dataset offers improved accuracy and detail compared to earlier versions, meeting high international standards for climate data. By refining how measurement errors are calculated and reduced over time and space, we provide clearer insights into pollution patterns. This work supports better air quality monitoring and informs actions to address pollution globally.
Laura Köhler, Julia Windmiller, Dariusz Baranowski, Michał Brennek, Michał Ciuryło, Lennéa Hayo, Daniel Kȩpski, Stefan Kinne, Beata Latos, Bertrand Lobo, Tobias Marke, Timo Nischik, Daria Paul, Piet Stammes, Artur Szkop, and Olaf Tuinder
Earth Syst. Sci. Data, 17, 633–659, https://doi.org/10.5194/essd-17-633-2025, https://doi.org/10.5194/essd-17-633-2025, 2025
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We present atmospheric and oceanic data from the Atlantic References and Convection ship campaign with the Maria S. Merian from Mindelo to Punta Arenas observed with the integrated ship sensors; humidity and temperature profiler; ceilometer; aerosol instruments (Calitoo, Microtops, and DustTrak); radiosondes; uncrewed aircraft vehicles; and conductivity, temperature, and depth scans. The data include three complete profiles of the Intertropical Convergence Zone and a storm in the South Atlantic.
Emmanouil Proestakis, Vassilis Amiridis, Carlos Pérez García-Pando, Svetlana Tsyro, Jan Griesfeller, Antonis Gkikas, Thanasis Georgiou, María Gonçalves Ageitos, Jeronimo Escribano, Stelios Myriokefalitakis, Elisa Bergas Masso, Enza Di Tomaso, Sara Basart, Jan-Berend W. Stuut, and Angela Benedetti
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-43, https://doi.org/10.5194/essd-2025-43, 2025
Revised manuscript accepted for ESSD
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Quantification of dust deposition into the broader Atlantic Ocean is provided, with the estimates established on the basis of Earth Observations. The dataset is considered unique with respect to a range of applications, including compensating for spatiotemporal gaps of sediment-trap measurements, assessments of model simulations, shedding light into physical processes related to the dust cycle, and to better understand dust biogeochemical impacts on oceanic ecosystems, on weather, and climate.
Jürgen Gratzl, David Brus, Konstantinos Doulgeris, Alexander Böhmländer, Ottmar Möhler, and Hinrich Grothe
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-543, https://doi.org/10.5194/essd-2024-543, 2025
Revised manuscript accepted for ESSD
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Near-real time monitoring of airborne biological particles like fungal spores or pollen grains is of great interest for two main reasons: To improve atmospheric allergen forecasts and deepen the understanding of how bioaerosols influence cloud formation. Here, we measured fluorescent bioaerosols in the Finnish sub-Arctic with high time resolution. A data set that might improve our understanding of biosphere-cloud interactions and the dynamics of bioaerosols in the atmosphere.
Xiaoran Guo, Jianping Guo, Deli Meng, Yuping Sun, Zhen Zhang, Hui Xu, Liping Zeng, Juan Chen, Ning Li, and Tianmeng Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-589, https://doi.org/10.5194/essd-2024-589, 2025
Revised manuscript accepted for ESSD
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Optimal atmospheric dynamic condition is essential for convective storms. This study generates a dataset of high-resolution divergence and vorticity profiles using the measurements of radar wind profiler mesonet in Beijing. The negative divergence and positive vorticity are present in advance of rainfall events. This suggests that this dataset can help improve our understanding of prestorm environment and has the potential to be applied to weather forecasting.
Yueming Dong, Jing Li, Zhenyu Zhang, Chongzhao Zhang, and Qiurui Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-583, https://doi.org/10.5194/essd-2024-583, 2025
Revised manuscript accepted for ESSD
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This study develops two merged global land aerosol single scattering albedo (SSA) datasets by combining AERONET ground observations and two satellite datasets using an Ensemble Kalman Filter data synergy method. The merged datasets exhibit significantly improved accuracy compared to the original satellite data. These results can provide more reliable estimates of aerosol scattering and absorption properties, essential for improving climate modeling and assessing aerosol climate effects.
Israel Silber, Jennifer M. Comstock, Michael R. Kieburtz, and Lynn M. Russell
Earth Syst. Sci. Data, 17, 29–42, https://doi.org/10.5194/essd-17-29-2025, https://doi.org/10.5194/essd-17-29-2025, 2025
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We present ARMTRAJ, a set of multipurpose trajectory datasets, which augments cloud, aerosol, and boundary layer studies utilizing the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility data. ARMTRAJ data include ensemble run statistics that enhance consistency and serve as uncertainty metrics for air mass coordinates and state variables. ARMTRAJ will soon become a near real-time product that will accompany past, ongoing, and future ARM deployments.
Cheng Chen, Xuefeng Lei, Zhenhai Liu, Haorang Gu, Oleg Dubovik, Pavel Litvinov, David Fuertes, Yujia Cao, Haixiao Yu, Guangfeng Xiang, Binghuan Meng, Zhenwei Qiu, Xiaobing Sun, Jin Hong, and Zhengqiang Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-483, https://doi.org/10.5194/essd-2024-483, 2024
Revised manuscript accepted for ESSD
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POSP on board GF-5(02) satellite is the first space-borne UV-VIS-NIR-SWIR multi-spectral cross-track scanning polarimeter. Due to wide spectral range and polarimetric capabilities, POSP measurements provide rich information for aerosol and surface characterization. We present the aerosol/surface products generated from POSP first 18 months of operation using GRASP/Models, including spectral AOD, AODF, AODC, and AE, SSA, scale height, full surface BRDF, BPDF, black-/white-sky albedos, NDVI.
Fan Mei, Jennifer M. Comstock, Mikhail S. Pekour, Jerome D. Fast, Krista L. Gaustad, Beat Schmid, Shuaiqi Tang, Damao Zhang, John E. Shilling, Jason M. Tomlinson, Adam C. Varble, Jian Wang, L. Ruby Leung, Lawrence Kleinman, Scot Martin, Sebastien C. Biraud, Brian D. Ermold, and Kenneth W. Burk
Earth Syst. Sci. Data, 16, 5429–5448, https://doi.org/10.5194/essd-16-5429-2024, https://doi.org/10.5194/essd-16-5429-2024, 2024
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Our study explores a comprehensive dataset from airborne field studies (2013–2018) conducted using the US Department of Energy's Gulfstream 1 (G-1). The 236 flights span diverse regions, including the Arctic, US Southern Great Plains, US West Coast, eastern North Atlantic, Amazon Basin in Brazil, and Sierras de Córdoba range in Argentina. This dataset provides unique insights into atmospheric dynamics, aerosols, and clouds and makes data available in a more accessible format.
Viktoria F. Sofieva, Alexei Rozanov, Monika Szelag, John P. Burrows, Christian Retscher, Robert Damadeo, Doug Degenstein, Landon A. Rieger, and Adam Bourassa
Earth Syst. Sci. Data, 16, 5227–5241, https://doi.org/10.5194/essd-16-5227-2024, https://doi.org/10.5194/essd-16-5227-2024, 2024
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Climate-related studies need information about the distribution of stratospheric aerosols, which influence the energy balance of the Earth’s atmosphere. In this work, we present a merged dataset of vertically resolved stratospheric aerosol extinction coefficients, which is derived from data of six limb and occultation satellite instruments. The created aerosol climate record covers the period from October 1984 to December 2023. It can be used in various climate-related studies.
Hasna Chebaicheb, Joel F. de Brito, Tanguy Amodeo, Florian Couvidat, Jean-Eudes Petit, Emmanuel Tison, Gregory Abbou, Alexia Baudic, Mélodie Chatain, Benjamin Chazeau, Nicolas Marchand, Raphaële Falhun, Florie Francony, Cyril Ratier, Didier Grenier, Romain Vidaud, Shouwen Zhang, Gregory Gille, Laurent Meunier, Caroline Marchand, Véronique Riffault, and Olivier Favez
Earth Syst. Sci. Data, 16, 5089–5109, https://doi.org/10.5194/essd-16-5089-2024, https://doi.org/10.5194/essd-16-5089-2024, 2024
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Long-term (2015–2021) quasi-continuous measurements have been obtained at 13 French urban sites using online mass spectrometry, to acquire the comprehensive chemical composition of submicron particulate matter. The results show their spatial and temporal differences and confirm the predominance of organics in France (40–60 %). These measurements can be used for many future studies, such as trend and epidemiological analyses, or comparisons with chemical transport models.
Paola Formenti and Claudia Di Biagio
Earth Syst. Sci. Data, 16, 4995–5007, https://doi.org/10.5194/essd-16-4995-2024, https://doi.org/10.5194/essd-16-4995-2024, 2024
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Particles from deserts and semi-vegetated areas (mineral dust) are important for Earth's climate and human health, notably depending on their size. In this paper we collect and make a synthesis of a body of these observations since 1972 in order to provide researchers modeling Earth's climate and developing satellite observations from space with a simple way of confronting their results and understanding their validity.
Yichen Jiang, Su Shi, Xinyue Li, Chang Xu, Haidong Kan, Bo Hu, and Xia Meng
Earth Syst. Sci. Data, 16, 4655–4672, https://doi.org/10.5194/essd-16-4655-2024, https://doi.org/10.5194/essd-16-4655-2024, 2024
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Limited ultraviolet (UV) measurements hindered further investigation of its health effects. This study used a machine learning algorithm to predict UV radiation with a daily and 10 km resolution of high accuracy in mainland China in 2005–2020. Then, uneven spatial distribution and population exposure risks as well as increased temporal trend of UV radiation were found in China. The long-term and high-quality UV dataset could further facilitate health-related research in the future.
Dene Bowdalo, Sara Basart, Marc Guevara, Oriol Jorba, Carlos Pérez García-Pando, Monica Jaimes Palomera, Olivia Rivera Hernandez, Melissa Puchalski, David Gay, Jörg Klausen, Sergio Moreno, Stoyka Netcheva, and Oksana Tarasova
Earth Syst. Sci. Data, 16, 4417–4495, https://doi.org/10.5194/essd-16-4417-2024, https://doi.org/10.5194/essd-16-4417-2024, 2024
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GHOST (Globally Harmonised Observations in Space and Time) represents one of the biggest collections of harmonised measurements of atmospheric composition at the surface. In total, 7 275 148 646 measurements from 1970 to 2023, from 227 different components, and from 38 reporting networks are compiled, parsed, and standardised. Components processed include gaseous species, total and speciated particulate matter, and aerosol optical properties.
Lei Kong, Xiao Tang, Zifa Wang, Jiang Zhu, Jianjun Li, Huangjian Wu, Qizhong Wu, Huansheng Chen, Lili Zhu, Wei Wang, Bing Liu, Qian Wang, Duohong Chen, Yuepeng Pan, Jie Li, Lin Wu, and Gregory R. Carmichael
Earth Syst. Sci. Data, 16, 4351–4387, https://doi.org/10.5194/essd-16-4351-2024, https://doi.org/10.5194/essd-16-4351-2024, 2024
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A new long-term inversed emission inventory for Chinese air quality (CAQIEI) is developed in this study, which contains constrained monthly emissions of NOx, SO2, CO, PM2.5, PM10, and NMVOCs in China from 2013 to 2020 with a horizontal resolution of 15 km. Emissions of different air pollutants and their changes during 2013–2020 were investigated and compared with previous emission inventories, which sheds new light on the complex variations of air pollutant emissions in China.
Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, Chris McLinden, Debora Griffin, Peter J. T. Leonard, Simon Carn, Colin Seftor, and Alexander Vasilkov
Earth Syst. Sci. Data, 16, 4291–4309, https://doi.org/10.5194/essd-16-4291-2024, https://doi.org/10.5194/essd-16-4291-2024, 2024
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Sulfur dioxide (SO2), a poisonous gas from human activities and volcanoes, causes air pollution, acid rain, and changes to climate and the ozone layer. Satellites have been used to monitor SO2 globally, including remote areas. Here we describe a new satellite SO2 dataset from the OMPS instrument that flies on the N20 satellite. Results show that the new dataset agrees well with the existing ones from other satellites and can help to continue the global monitoring of SO2 from space.
Jacqueline E. Russell, Richard J. Bantges, Helen E. Brindley, and Alejandro Bodas-Salcedo
Earth Syst. Sci. Data, 16, 4243–4266, https://doi.org/10.5194/essd-16-4243-2024, https://doi.org/10.5194/essd-16-4243-2024, 2024
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We present a dataset of top-of-atmosphere diurnally resolved reflected solar and emitted thermal energy for Earth system model evaluation. The multi-year, monthly hourly dataset, derived from observations made by the Geostationary Earth Radiation Budget instrument, covers the range 60° N–60° S, 60° E–60° W at 1° resolution. Comparison with two versions of the Hadley Centre Global Environmental Model highlight how the data can be used to assess updates to key model parameterizations.
Dominique Gantois, Guillaume Payen, Michaël Sicard, Valentin Duflot, Nelson Bègue, Nicolas Marquestaut, Thierry Portafaix, Sophie Godin-Beekmann, Patrick Hernandez, and Eric Golubic
Earth Syst. Sci. Data, 16, 4137–4159, https://doi.org/10.5194/essd-16-4137-2024, https://doi.org/10.5194/essd-16-4137-2024, 2024
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We describe three instruments that have been measuring interactions between aerosols (particles of various origin) and light over Réunion Island since 2012. Aerosols directly or indirectly influence the temperature in the atmosphere and can interact with clouds. Details are given on how we derived aerosol properties from our measurements and how we assessed the quality of our data before sharing them with the scientific community. A good correlation was found between the three instruments.
Hongfei Hao, Kaicun Wang, Guocan Wu, Jianbao Liu, and Jing Li
Earth Syst. Sci. Data, 16, 4051–4076, https://doi.org/10.5194/essd-16-4051-2024, https://doi.org/10.5194/essd-16-4051-2024, 2024
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In this study, daily PM2.5 concentrations are estimated from 1959 to 2022 using a machine learning method at more than 5000 terrestrial sites in the Northern Hemisphere based on hourly atmospheric visibility data, which are extracted from the Meteorological Terminal Aviation Routine Weather Report (METAR).
Pierre Tulet, Joel Van Baelen, Pierre Bosser, Jérome Brioude, Aurélie Colomb, Philippe Goloub, Andrea Pazmino, Thierry Portafaix, Michel Ramonet, Karine Sellegri, Melilotus Thyssen, Léa Gest, Nicolas Marquestaut, Dominique Mékiès, Jean-Marc Metzger, Gilles Athier, Luc Blarel, Marc Delmotte, Guillaume Desprairies, Mérédith Dournaux, Gaël Dubois, Valentin Duflot, Kevin Lamy, Lionel Gardes, Jean-François Guillemot, Valérie Gros, Joanna Kolasinski, Morgan Lopez, Olivier Magand, Erwan Noury, Manuel Nunes-Pinharanda, Guillaume Payen, Joris Pianezze, David Picard, Olivier Picard, Sandrine Prunier, François Rigaud-Louise, Michael Sicard, and Benjamin Torres
Earth Syst. Sci. Data, 16, 3821–3849, https://doi.org/10.5194/essd-16-3821-2024, https://doi.org/10.5194/essd-16-3821-2024, 2024
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The MAP-IO program aims to compensate for the lack of atmospheric and oceanographic observations in the Southern Ocean by equipping the ship Marion Dufresne with a set of 17 scientific instruments. This program collected 700 d of measurements under different latitudes, seasons, sea states, and weather conditions. These new data will support the calibration and validation of numerical models and the understanding of the atmospheric composition of this region of Earth.
Siwei Li, Yu Ding, Jia Xing, and Joshua S. Fu
Earth Syst. Sci. Data, 16, 3781–3793, https://doi.org/10.5194/essd-16-3781-2024, https://doi.org/10.5194/essd-16-3781-2024, 2024
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Surface PM2.5 data have gained widespread application in health assessments and related fields, while the inherent uncertainties in PM2.5 data persist due to the lack of ground-truth data across the space. This study provides a novel testbed, enabling comprehensive evaluation across the entire spatial domain. The optimized deep-learning model with spatiotemporal features successfully retrieved surface PM2.5 concentrations in China (2013–2021), with reduced biases induced by sample imbalance.
Shuai Wang, Mengyuan Zhang, Hui Zhao, Peng Wang, Sri Harsha Kota, Qingyan Fu, Cong Liu, and Hongliang Zhang
Earth Syst. Sci. Data, 16, 3565–3577, https://doi.org/10.5194/essd-16-3565-2024, https://doi.org/10.5194/essd-16-3565-2024, 2024
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Long-term, open-source, gap-free daily ground-level PM2.5 and PM10 datasets for India (LongPMInd) were reconstructed using a robust machine learning model to support health assessment and air quality management.
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
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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.
Arndt Kaps, Axel Lauer, Rémi Kazeroni, Martin Stengel, and Veronika Eyring
Earth Syst. Sci. Data, 16, 3001–3016, https://doi.org/10.5194/essd-16-3001-2024, https://doi.org/10.5194/essd-16-3001-2024, 2024
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CCClim displays observations of clouds in terms of cloud classes that have been in use for a long time. CCClim is a machine-learning-powered product based on multiple existing observational products from different satellites. We show that the cloud classes in CCClim are physically meaningful and can be used to study cloud characteristics in more detail. The goal of this is to make real-world clouds more easily understandable to eventually improve the simulation of clouds in climate models.
David Winker, Xia Cai, Mark Vaughan, Anne Garnier, Brian Magill, Melody Avery, and Brian Getzewich
Earth Syst. Sci. Data, 16, 2831–2855, https://doi.org/10.5194/essd-16-2831-2024, https://doi.org/10.5194/essd-16-2831-2024, 2024
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Clouds play important roles in both weather and climate. In this paper we describe version 1.0 of a unique global ice cloud data product derived from over 12 years of global spaceborne lidar measurements. This monthly gridded product provides a unique vertically resolved characterization of the occurrence and properties, optical and physical, of thin ice clouds and the tops of deep convective clouds. It should provide significant value for cloud research and model evaluation.
Karam Mansour, Stefano Decesari, Darius Ceburnis, Jurgita Ovadnevaite, Lynn M. Russell, Marco Paglione, Laurent Poulain, Shan Huang, Colin O'Dowd, and Matteo Rinaldi
Earth Syst. Sci. Data, 16, 2717–2740, https://doi.org/10.5194/essd-16-2717-2024, https://doi.org/10.5194/essd-16-2717-2024, 2024
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We propose and evaluate machine learning predictive algorithms to model freshly formed biogenic methanesulfonic acid and sulfate concentrations. The long-term constructed dataset covers the North Atlantic at an unprecedented resolution. The improved parameterization of biogenic sulfur aerosols at regional scales is essential for determining their radiative forcing, which could help further understand marine-aerosol–cloud interactions and reduce uncertainties in climate models
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
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This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data, 16, 2197–2260, https://doi.org/10.5194/essd-16-2197-2024, https://doi.org/10.5194/essd-16-2197-2024, 2024
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This paper describes a new version, called GGG2020, of a data set containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made toward site-to-site consistency. This data set plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Antonin Soulie, Claire Granier, Sabine Darras, Nicolas Zilbermann, Thierno Doumbia, Marc Guevara, Jukka-Pekka Jalkanen, Sekou Keita, Cathy Liousse, Monica Crippa, Diego Guizzardi, Rachel Hoesly, and Steven J. Smith
Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, https://doi.org/10.5194/essd-16-2261-2024, 2024
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Anthropogenic emissions are the result of transportation, power generation, industrial, residential and commercial activities as well as waste treatment and agriculture practices. This work describes the new CAMS-GLOB-ANT gridded inventory of 2000–2023 anthropogenic emissions of air pollutants and greenhouse gases. The methodology to generate the emissions is explained and the datasets are analysed and compared with publicly available global and regional inventories for selected world regions.
Declan L. Finney, Alan M. Blyth, Martin Gallagher, Huihui Wu, Graeme J. Nott, Michael I. Biggerstaff, Richard G. Sonnenfeld, Martin Daily, Dan Walker, David Dufton, Keith Bower, Steven Böing, Thomas Choularton, Jonathan Crosier, James Groves, Paul R. Field, Hugh Coe, Benjamin J. Murray, Gary Lloyd, Nicholas A. Marsden, Michael Flynn, Kezhen Hu, Navaneeth M. Thamban, Paul I. Williams, Paul J. Connolly, James B. McQuaid, Joseph Robinson, Zhiqiang Cui, Ralph R. Burton, Gordon Carrie, Robert Moore, Steven J. Abel, Dave Tiddeman, and Graydon Aulich
Earth Syst. Sci. Data, 16, 2141–2163, https://doi.org/10.5194/essd-16-2141-2024, https://doi.org/10.5194/essd-16-2141-2024, 2024
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The DCMEX (Deep Convective Microphysics Experiment) project undertook an aircraft- and ground-based measurement campaign of New Mexico deep convective clouds during July–August 2022. The campaign coordinated a broad range of instrumentation measuring aerosol, cloud physics, radar signals, thermodynamics, dynamics, electric fields, and weather. The project's objectives included the utilisation of these data with satellite observations to study the anvil cloud radiative effect.
Jianzhong Xu, Xinghua Zhang, Wenhui Zhao, Lixiang Zhai, Miao Zhong, Jinsen Shi, Junying Sun, Yanmei Liu, Conghui Xie, Yulong Tan, Kemei Li, Xinlei Ge, Qi Zhang, and Shichang Kang
Earth Syst. Sci. Data, 16, 1875–1900, https://doi.org/10.5194/essd-16-1875-2024, https://doi.org/10.5194/essd-16-1875-2024, 2024
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A comprehensive aerosol observation project was carried out in the Tibetan Plateau (TP) and its surroundings in recent years to investigate the properties and sources of atmospheric aerosols as well as their regional differences by performing multiple intensive field observations. The release of this dataset can provide basic and systematic data for related research in the atmospheric, cryospheric, and environmental sciences in this unique region.
Xiaoyong Zhuge, Xiaolei Zou, Lu Yu, Xin Li, Mingjian Zeng, Yilun Chen, Bing Zhang, Bin Yao, Fei Tang, Fengjiao Chen, and Wanlin Kan
Earth Syst. Sci. Data, 16, 1747–1769, https://doi.org/10.5194/essd-16-1747-2024, https://doi.org/10.5194/essd-16-1747-2024, 2024
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The Himawari-8/9 level-2 operational cloud product has a low spatial resolution and is available only during the daytime. To supplement this official dataset, a new dataset named the NJIAS Himawari-8/9 Cloud Feature Dataset (HCFD) was constructed. The NJIAS HCFD provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the years 2016–2022 by 30 retrieved cloud variables. The NJIAS HCFD has been demonstrated to outperform the official dataset.
Honglin Pan, Jianping Huang, Jiming Li, Zhongwei Huang, Minzhong Wang, Ali Mamtimin, Wen Huo, Fan Yang, Tian Zhou, and Kanike Raghavendra Kumar
Earth Syst. Sci. Data, 16, 1185–1207, https://doi.org/10.5194/essd-16-1185-2024, https://doi.org/10.5194/essd-16-1185-2024, 2024
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We applied several correction procedures and rigorously checked for data quality constraints during the long observation period spanning almost 14 years (2007–2020). Nevertheless, some uncertainties remain, mainly due to technical constraints and limited documentation of the measurements. Even though not completely accurate, this strategy is expected to at least reduce the inaccuracy of the computed characteristic value of aerosol optical parameters.
Julie Christin Schindlbeck-Belo, Matthew Toohey, Marion Jegen, Steffen Kutterolf, and Kira Rehfeld
Earth Syst. Sci. Data, 16, 1063–1081, https://doi.org/10.5194/essd-16-1063-2024, https://doi.org/10.5194/essd-16-1063-2024, 2024
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Volcanic forcing of climate resulting from major explosive eruptions is a dominant natural driver of past climate variability. To support model studies of the potential impacts of explosive volcanism on climate variability across timescales, we present an ensemble reconstruction of volcanic stratospheric sulfur injection over the last 140 000 years that is based primarily on tephra records.
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, https://doi.org/10.5194/essd-16-681-2024, 2024
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This publication describes the microwave radiometric measurements performed during the EUREC4A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.
Daniela Meloni, Filippo Calì Quaglia, Virginia Ciardini, Annalisa Di Bernardino, Tatiana Di Iorio, Antonio Iaccarino, Giovanni Muscari, Giandomenico Pace, Claudio Scarchilli, and Alcide di Sarra
Earth Syst. Sci. Data, 16, 543–566, https://doi.org/10.5194/essd-16-543-2024, https://doi.org/10.5194/essd-16-543-2024, 2024
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Solar and infrared radiation are key factors in determining Arctic climate. Only a few sites in the Arctic perform long-term measurements of the surface radiation budget (SRB). At the Thule High Arctic Atmospheric Observatory (THAAO, 76.5° N, 68.8° W) in Northern Greenland, solar and infrared irradiance measurements were started in 2009. These data are of paramount importance in studying the impact of the atmospheric (mainly clouds and aerosols) and surface (albedo) parameters on the SRB.
Karoline Block, Mahnoosh Haghighatnasab, Daniel G. Partridge, Philip Stier, and Johannes Quaas
Earth Syst. Sci. Data, 16, 443–470, https://doi.org/10.5194/essd-16-443-2024, https://doi.org/10.5194/essd-16-443-2024, 2024
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Aerosols being able to act as condensation nuclei for cloud droplets (CCNs) are a key element in cloud formation but very difficult to determine. In this study we present a new global vertically resolved CCN dataset for various humidity conditions and aerosols. It is obtained using an atmospheric model (CAMS reanalysis) that is fed by satellite observations of light extinction (AOD). We investigate and evaluate the abundance of CCNs in the atmosphere and their temporal and spatial occurrence.
Jianping Guo, Jian Zhang, Jia Shao, Tianmeng Chen, Kaixu Bai, Yuping Sun, Ning Li, Jingyan Wu, Rui Li, Jian Li, Qiyun Guo, Jason B. Cohen, Panmao Zhai, Xiaofeng Xu, and Fei Hu
Earth Syst. Sci. Data, 16, 1–14, https://doi.org/10.5194/essd-16-1-2024, https://doi.org/10.5194/essd-16-1-2024, 2024
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A global continental merged high-resolution (PBLH) dataset with good accuracy compared to radiosonde is generated via machine learning algorithms, covering the period from 2011 to 2021 with 3-hour and 0.25º resolution in space and time. The machine learning model takes parameters derived from the ERA5 reanalysis and GLDAS product as input, with PBLH biases between radiosonde and ERA5 as the learning targets. The merged PBLH is the sum of the predicted PBLH bias and the PBLH from ERA5.
Karina E. Adcock, Penelope A. Pickers, Andrew C. Manning, Grant L. Forster, Leigh S. Fleming, Thomas Barningham, Philip A. Wilson, Elena A. Kozlova, Marica Hewitt, Alex J. Etchells, and Andy J. Macdonald
Earth Syst. Sci. Data, 15, 5183–5206, https://doi.org/10.5194/essd-15-5183-2023, https://doi.org/10.5194/essd-15-5183-2023, 2023
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We present a 12-year time series of continuous atmospheric measurements of O2 and CO2 at the Weybourne Atmospheric Observatory in the United Kingdom. These measurements are combined into the term atmospheric potential oxygen (APO), a tracer that is not influenced by land biosphere processes. The datasets show a long-term increasing trend in CO2 and decreasing trends in O2 and APO between 2010 and 2021.
Nikos Benas, Irina Solodovnik, Martin Stengel, Imke Hüser, Karl-Göran Karlsson, Nina Håkansson, Erik Johansson, Salomon Eliasson, Marc Schröder, Rainer Hollmann, and Jan Fokke Meirink
Earth Syst. Sci. Data, 15, 5153–5170, https://doi.org/10.5194/essd-15-5153-2023, https://doi.org/10.5194/essd-15-5153-2023, 2023
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This paper describes CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI, which was created based on observations from geostationary Meteosat satellites. CLAAS-3 cloud properties are evaluated using a variety of reference datasets, with very good overall results. The demonstrated quality of CLAAS-3 ensures its usefulness in a wide range of applications, including studies of local- to continental-scale cloud processes and evaluation of climate models.
Cited articles
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Bretherton, C. S., McCoy, I. L., Mohrmann, J., Wood, R., Ghate, V., Gettelman, A., Bardeen, C. G., Albrecht, B. A., and Zuidema, P.: Cloud, Aerosol, and Boundary Layer Structure across the Northeast Pacific Stratocumulus–Cumulus Transition as Observed during CSET, Mon. Weather Rev., 147, 2083–2103, https://doi.org/10.1175/MWR-D-18-0281.1, 2019.
Cao, Y., Zhu, Y., Wang, M., Rosenfeld, D., Zhou, C., Liu, J., Liang, Y., Huang, K.-E., Wang, Q., Bai, H., Wang, Y., Wang, H., and Zhang, H.: Improving Prediction of Marine Low Clouds Using Cloud Droplet Number Concentration in a Convolutional Neural Network, J. Geophys. Res.-Machine Learning and Computation, 1, e2024JH000355, https://doi.org/10.1029/2024JH000355, 2024.
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Lang, F., Ackermann, L., Huang, Y., Truong, S. C. H., Siems, S. T., and Manton, M. J.: A climatology of open and closed mesoscale cellular convection over the Southern Ocean derived from Himawari-8 observations, Atmos. Chem. Phys., 22, 2135–2152, https://doi.org/10.5194/acp-22-2135-2022, 2022.
Lensky, I. M. and Rosenfeld, D.: Clouds-Aerosols-Precipitation Satellite Analysis Tool (CAPSAT), Atmos. Chem. Phys., 8, 6739–6753, https://doi.org/10.5194/acp-8-6739-2008, 2008.
Li, X., Qiu, B., Cao, G., Wu, C., and Zhang, L.: A Novel Method for Ground-Based Cloud Image Classification Using Transformer, Remote Sens., 14, 3978, https://doi.org/10.3390/rs14163978, 2022.
Luo, H., Quaas, J., and Han, Y.: Diurnally asymmetric cloud cover trends amplify greenhouse warming, Sci. Adv., 10, eado5179, https://doi.org/10.1126/sciadv.ado5179, 2024.
McCoy, I. L., Wood, R., and Fletcher, J. K.: Identifying Meteorological Controls on Open and Closed Mesoscale Cellular Convection Associated with Marine Cold Air Outbreaks, J. Geophys. Res.-Atmos., 122, 11678–11702, https://doi.org/10.1002/2017JD027031, 2017.
McCoy, I. L., McCoy, D. T., Wood, R., Zuidema, P., and Bender, F. A.-M.: The Role of Mesoscale Cloud Morphology in the Shortwave Cloud Feedback, Geophys. Res. Lett., 50, e2022GL101042, https://doi.org/10.1029/2022GL101042, 2023.
Mohrmann, J., Wood, R., Yuan, T., Song, H., Eastman, R., and Oreopoulos, L.: Identifying meteorological influences on marine low-cloud mesoscale morphology using satellite classifications, Atmos. Chem. Phys., 21, 9629–9642, https://doi.org/10.5194/acp-21-9629-2021, 2021.
Muhlbauer, A., McCoy, I. L., and Wood, R.: Climatology of stratocumulus cloud morphologies: microphysical properties and radiative effects, Atmos. Chem. Phys., 14, 6695–6716, https://doi.org/10.5194/acp-14-6695-2014, 2014.
Petters, M. D., Snider, J. R., Stevens, B., Vali, G., Faloona, I., and Russell, L. M.: Accumulation mode aerosol, pockets of open cells, and particle nucleation in the remote subtropical Pacific marine boundary layer, J. Geophys. Res.-Atmos., 111, D02206, https://doi.org/10.1029/2004JD005694, 2006.
Platnick, S., Meyer, K. G., King, M. D., Wind, G., Amarasinghe, N., Marchant, B., Arnold, G. T., Zhang, Z., Hubanks, P. A., Holz, R. E., Yang, P., Ridgway, W. L., and Riedi, J.: The MODIS Cloud Optical and Microphysical Products: Collection 6 Updates and Examples From Terra and Aqua, IEEE T. Geosci. Remote Sens., 55, 502–525, https://doi.org/10.1109/TGRS.2016.2610522, 2017.
Rosenfeld, D., Kaufman, Y. J., and Koren, I.: Switching cloud cover and dynamical regimes from open to closed Benard cells in response to the suppression of precipitation by aerosols, Atmos. Chem. Phys., 6, 2503–2511, https://doi.org/10.5194/acp-6-2503-2006, 2006.
Savic-Jovcic, V. and Stevens, B.: The Structure and Mesoscale Organization of Precipitating Stratocumulus, J. Atmos. Sci., 65, 1587–1605, https://doi.org/10.1175/2007JAS2456.1, 2008.
Schulz, H., Eastman, R., and Stevens, B.: Characterization and Evolution of Organized Shallow Convection in the Downstream North Atlantic Trades, J. Geophys. Res.-Atmos., 126, e2021JD034575, https://doi.org/10.1029/2021JD034575, 2021.
Segal Rozenhaimer, M., Nukrai, D., Che, H., Wood, R., and Zhang, Z.: Cloud Mesoscale Cellular Classification and Diurnal Cycle Using a Convolutional Neural Network (CNN), Remote Sens., 15, 1607, https://doi.org/10.3390/rs15061607, 2023.
Stevens, B., Vali, G., Comstock, K., Wood, R., van Zanten, M. C., Austin, P. H., Bretherton, C. S., and Lenschow, D. H.: POCKETS OF OPEN CELLS AND DRIZZLE IN MARINE STRATOCUMULUS, B. Am. Meteorol. Soc., 86, 51–58, https://doi.org/10.1175/BAMS-86-1-51, 2005.
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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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