Articles | Volume 10, issue 1
https://doi.org/10.5194/essd-10-325-2018
© Author(s) 2018. 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-10-325-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
22 Feb 2018
| 22 Feb 2018
The Alberta smoke plume observation study
Kerry Anderson
CORRESPONDING AUTHOR
Natural Resources Canada, 5320 122 Street, Edmonton, Alberta T6H 3S5, Canada
Al Pankratz
Environment and Climate Change Canada, 9250 49 Street, Edmonton, Alberta T6B 1K5, Canada
Curtis Mooney
Environment and Climate Change Canada, 9250 49 Street, Edmonton, Alberta T6B 1K5, Canada
Kelly Fleetham
Alberta Agriculture and Forestry, 9920 108 Street, Edmonton, Alberta T5K 2M4, Canada
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We assess the complementarity of the greater temporal coverage provided by ground-based remote sensing data with the spatial coverage of satellite observations when these data are used together to quantify CO emissions from extreme wildfires in 2023. Our results reveal that the commonly used biomass burning emission inventories significantly underestimate the fire emissions and emphasize the importance of the ground-based remote sensing data in reducing uncertainties in the estimated emissions.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
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Debora Griffin, Jack Chen, Kerry Anderson, Paul Makar, Chris A. McLinden, Enrico Dammers, and Andre Fogal
Atmos. Chem. Phys., 24, 10159–10186, https://doi.org/10.5194/acp-24-10159-2024, https://doi.org/10.5194/acp-24-10159-2024, 2024
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Paul A. Makar, Ayodeji Akingunola, Jack Chen, Balbir Pabla, Wanmin Gong, Craig Stroud, Christopher Sioris, Kerry Anderson, Philip Cheung, Junhua Zhang, and Jason Milbrandt
Atmos. Chem. Phys., 21, 10557–10587, https://doi.org/10.5194/acp-21-10557-2021, https://doi.org/10.5194/acp-21-10557-2021, 2021
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We have examined the effects of airborne particles on absorption and scattering of incoming sunlight by the particles themselves via cloud formation. We used an advanced, combined high-resolution weather forecast and chemical transport computer model, for western North America, and simulations with and without the connections between particles and weather enabled. Feedbacks improved weather and air pollution forecasts and changed cloud behaviour and forest-fire pollutant amount and height.
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Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Debora Griffin, Jack Chen, Kerry Anderson, Paul Makar, Chris A. McLinden, Enrico Dammers, and Andre Fogal
Atmos. Chem. Phys., 24, 10159–10186, https://doi.org/10.5194/acp-24-10159-2024, https://doi.org/10.5194/acp-24-10159-2024, 2024
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Satellite-derived CO emissions provide new insights into the understanding of global CO emission rates from wildfires. We use TROPOMI satellite data to create a global inventory database of wildfire CO emissions. These satellite-derived wildfire emissions are used for the evaluation and improvement of existing fire emission inventories and to examine how the wildfire CO emissions have changed over the past 2 decades.
Paul A. Makar, Ayodeji Akingunola, Jack Chen, Balbir Pabla, Wanmin Gong, Craig Stroud, Christopher Sioris, Kerry Anderson, Philip Cheung, Junhua Zhang, and Jason Milbrandt
Atmos. Chem. Phys., 21, 10557–10587, https://doi.org/10.5194/acp-21-10557-2021, https://doi.org/10.5194/acp-21-10557-2021, 2021
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We have examined the effects of airborne particles on absorption and scattering of incoming sunlight by the particles themselves via cloud formation. We used an advanced, combined high-resolution weather forecast and chemical transport computer model, for western North America, and simulations with and without the connections between particles and weather enabled. Feedbacks improved weather and air pollution forecasts and changed cloud behaviour and forest-fire pollutant amount and height.
Jack Chen, Kerry Anderson, Radenko Pavlovic, Michael D. Moran, Peter Englefield, Dan K. Thompson, Rodrigo Munoz-Alpizar, and Hugo Landry
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Emissions from wildland fires can cause significant impacts on regional air quality. We introduce the Canadian Forest Fire Emissions Prediction System and demonstrate its integration with Canada's FireWork operational air quality forecast system with biomass burning emissions. The coupled system shows improved skill in providing short-term, 48 h forecasts of surface air pollutant concentrations (PM2.5, O3, and NO2) from the impacts of regional wildland fires across the North American domain.
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A comprehensive in situ and remote sensing data set collected during the HALO–(𝒜 𝒞)3 aircraft campaign
Biologically effective daily radiant exposure for erythema appearance, previtamin D3 synthesis and clearing of psoriatic lesions from erythema biometers at Belsk, Poland, for the period 1976–2023
Calm ocean, stormy sea: atmospheric and oceanographic observations of the Atlantic during the Atlantic References and Convection (ARC) ship campaign
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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.
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.
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.
Philippe Marbaix, Alexandre K. Magnan, Veruska Muccione, Peter W. Thorne, and Zinta Zommers
Earth Syst. Sci. Data, 17, 317–349, https://doi.org/10.5194/essd-17-317-2025, https://doi.org/10.5194/essd-17-317-2025, 2025
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Since 2001, the Intergovernmental Panel on Climate Change (IPCC) has used burning-ember diagrams to show how risks increase with global warming. We bring these data into a harmonized framework available through an online Climate Risks Embers Explorer. Without high levels of adaptation, most risks reach a high level around 2 to 2.3 °C of global warming. Improvements in future reports could include systematic collection of explanatory information and broader coverage of regions and adaptation.
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.
Alex T. Archibald, Bablu Sinha, Maria R. Russo, Emily Matthews, Freya A. Squires, N. Luke Abraham, Stephane J.-B. Bauguitte, Thomas J. Bannan, Thomas G. Bell, David Berry, Lucy J. Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian A. King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Bengamin I. Moat, Katie Read, Chris Reed, Malcolm J. Roberts, Reinhard Schiemann, David Schroeder, Timothy J. Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Mingxi Yang
Earth Syst. Sci. Data, 17, 135–164, https://doi.org/10.5194/essd-17-135-2025, https://doi.org/10.5194/essd-17-135-2025, 2025
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Here, we present an overview of the data generated as part of the North Atlantic Climate System Integrated Study (ACSIS) programme that are available through dedicated repositories at the Centre for Environmental Data Analysis (CEDA; www.ceda.ac.uk) and the British Oceanographic Data Centre (BODC; bodc.ac.uk). The datasets described here cover the North Atlantic Ocean, the atmosphere above (it including its composition), and Arctic sea ice.
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.
Peiyuan Jiao, Chengzhi Xing, Yikai Li, Xiangguang Ji, Wei Tan, Qihua Li, Haoran Liu, and Cheng Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-562, https://doi.org/10.5194/essd-2024-562, 2024
Revised manuscript accepted for ESSD
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This study provides a dataset of high-resolution vertical profiles of aerosol, NO2, and HCHO, observed over periods ranging from 5 months to 5 years at 32 sites across China between 2019 and 2023. The dataset captures the vertical distribution, diurnal pattern and seasonal variations of these compositions. It has been validated against TROPOMI satellite observations and ground-based CNEMC measurements, showing good correlations.
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.
Yuanyuan Wu, Jihu Liu, Yannian Zhu, Yu Zhang, Yang Cao, Kang-En Huang, Boyang Zheng, Yichuan Wang, Yanyun Li, Quan Wang, Chen Zhou, Yuan Liang, Jianning Sun, Minghuai Wang, and Daniel Rosenfeld
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-536, https://doi.org/10.5194/essd-2024-536, 2024
Revised manuscript accepted for ESSD
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In this paper, based on deep learning method, we established a global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology. It aims to promote a comprehensive understanding of the cloud dynamics and cloud-climate feedback. Closed mesoscale cellular convection (MCC) clouds occur more frequently at night, while suppressed cumulus exhibit remarkable decrease. Solid stratus and MCC cloud types show clear seasonal variations.
Juan A. Añel, Juan-Carlos Antuña-Marrero, Antonio Cid Samamed, Celia Pérez-Souto, Laura de la Torre, Maria Antonia Valente, Yuri Brugnara, Alfonso Saiz-López, and Luis Gimeno
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-366, https://doi.org/10.5194/essd-2024-366, 2024
Revised manuscript accepted for ESSD
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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 color changes. Here we present the data, covering over sixty years of daily observations, conducted along the East Atlantic coast, spanning from the tropics to the northern extratropics.
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.
Rui Li, Guofeng Zhu, Longhu Chen, Xiaoyu Qi, Siyu Lu, Gaojia Meng, Yuhao Wang, Wenmin Li, Zhijie Zheng, Jiangwei Yang, and Yani Gun
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-297, https://doi.org/10.5194/essd-2024-297, 2024
Revised manuscript accepted for ESSD
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The study of hydrogen and oxygen stable isotopes in surface water is vital for understanding the global water cycle and its response to climate change. Analyzing data from 22432 global sampling stations over 67 years, we uncover spatial and temporal variations in isotopes, showing depletion from the equator to the poles and from coastal to inland areas. These variations, influenced by geographic, topographic, and meteorological factors, reveal the water cycle's heterogeneity.
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.
Aku Riihelä, Emmihenna Jääskeläinen, and Viivi Kallio-Myers
Earth Syst. Sci. Data, 16, 1007–1028, https://doi.org/10.5194/essd-16-1007-2024, https://doi.org/10.5194/essd-16-1007-2024, 2024
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We describe a new climate data record describing the surface albedo, or reflectivitity, of Earth's surface (called CLARA-A3 SAL). The climate data record spans over 4 decades of satellite observations, beginning in 1979. We conduct a quality assessment of the generated data, comparing them against other satellite data and albedo observations made on the ground. We find that the new data record in general matches surface observations well and is stable through time.
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.
Sandip S. Dhomse and Martyn P. Chipperfield
Earth Syst. Sci. Data, 15, 5105–5120, https://doi.org/10.5194/essd-15-5105-2023, https://doi.org/10.5194/essd-15-5105-2023, 2023
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There are no long-term stratospheric profile data sets for two very important greenhouse gases: methane (CH4) and nitrous oxide (N2O). Along with radiative feedback, these species play an important role in controlling ozone loss in the stratosphere. Here, we use machine learning to fuse satellite measurements with a chemical model to construct long-term gap-free profile data sets for CH4 and N2O. We aim to construct similar data sets for other important trace gases (e.g. O3, Cly, NOy species).
Tobias Erhardt, Camilla Marie Jensen, Florian Adolphi, Helle Astrid Kjær, Remi Dallmayr, Birthe Twarloh, Melanie Behrens, Motohiro Hirabayashi, Kaori Fukuda, Jun Ogata, François Burgay, Federico Scoto, Ilaria Crotti, Azzurra Spagnesi, Niccoló Maffezzoli, Delia Segato, Chiara Paleari, Florian Mekhaldi, Raimund Muscheler, Sophie Darfeuil, and Hubertus Fischer
Earth Syst. Sci. Data, 15, 5079–5091, https://doi.org/10.5194/essd-15-5079-2023, https://doi.org/10.5194/essd-15-5079-2023, 2023
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The presented paper provides a 3.8 kyr long dataset of aerosol concentrations from the East Greenland Ice coring Project (EGRIP) ice core. The data consists of 1 mm depth-resolution profiles of calcium, sodium, ammonium, nitrate, and electrolytic conductivity as well as decadal averages of these profiles. Alongside the data a detailed description of the measurement setup as well as a discussion of the uncertainties are given.
Cited articles
Achtemeier, G. L., Goodrick, S. A., Liu, Y., Garcia-Menendez, F., Hu, Y., and Odman, M. T.: Modeling smoke plume-rise and dispersion from southern United States prescribed burns with daysmoke, Atmosphere, 2, 358–388, 2011.
Anderson, K., Englefield, P., Little, J., and Reuter, G.: An approach to operational forest fire growth predictions for Canada, Int. J. Wildland Fire, 18, 893–905, https://doi.org/10.1071/WF08046, 2009.
Anderson, K., Pankratz, A., and Mooney, C.: 9.2 A thermodynamic approach to estimating smoke plume heights, in: Proceedings of Ninth Symposium on Fire and Forest Meteorology, Palms Springs, CA, 17–21 October 2011, AMS, Boston, MA, 2011.
Briggs, G.: A plume rise model compared with observations, JAPCA J. Air Waste Ma., 15, 433–438, https://doi.org/10.1080/00022470.1965.10468404, 1965.
Byram, G.: Combustion of forest fuels, in: Forest fire: control and use, edited by: Brown, A. A. and Davis, K. P., 61–89, McGraw-Hill, New York, 1959.
Ecological Stratification Working Group (Canada), Center for Land and Biological Resources Research (Canada), and Canada. State of the Environment Directorate: A national ecological framework for Canada, Centre for Land and Biological Resources Research; Hull, Quebec: State of the Environment Directorate, 1996.
Englefield, P., Lee, B., Fraser, R., Landry, R., Hall, R., Lynham, T., Cihlar, J., Li, Z., Jin, J., and Ahern, F.: Applying geographic information systems and remote sensing to forest fire monitoring, mapping, and modeling in Canada, in: Proceedings of the 22nd Tall Timbers Fire Ecology Conference: Fire in Temperate, Boreal and Montane Ecosystems, 240–245, 2004.
Flannigan, M. D., Krawchuk, M. A., de Groot, W. J., Wotton, B. M., and Gowman, L. M.: Implications of changing climate for global wildland fire, Int. J. Wildland Fire, 18, 483–507, 2009.
Forestry Canada Fire Danger Group: Development and Structure of the Canadian Forest Fire Behavior Prediction System, Tech. Rep. S-T-X-3, Forestry Canada, Science and Sustainable Development Directorate, 1992.
Freitas, S. R., Longo, K. M., Chatfield, R., Latham, D., Silva Dias, M. A. F., Andreae, M. O., Prins, E., Santos, J. C., Gielow, R., and Carvalho Jr., J. A.: Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models, Atmos. Chem. Phys., 7, 3385–3398, https://doi.org/10.5194/acp-7-3385-2007, 2007.
Goodrick, S., Achtemeier, G., Larkin, N., Liu, Y., and Strand, T.: Modelling smoke transport from wildland fires: A review, Int. J. Wildland Fire, 22, 83–94, https://doi.org/10.1071/WF11116, 2013.
Harrison, H. and Hardy, C.: Plume rise from gigawatt fires: observations and models, unpublished manuscript, available at: http://www.atmos.washington.edu/~harrison/reports/plume3.pdf (last access: 19 February 2018), 2002.
Heilman, W., Liu, Y., Urbanski, S., Kovalev, V., and Mickler, R.: Wildland fire emissions, carbon, and climate: plume rise, atmospheric transport, and chemistry processes, Forest Ecol. Manag., 317, 70–79, https://doi.org/10.1016/j.foreco.2013.02.001, 2014.
Kovalev, V. A., Petkov, A., Wold, C., Urbanski, S., and Hao, W. M.: Determination of smoke plume and layer heights using scanning lidar data, Appl. Optics, 48, 5287–5294, 2009.
Lareau, N. P. and Clements, C. B.: Environmental controls on pyrocumulus and pyrocumulonimbus initiation and development, Atmos. Chem. Phys., 16, 4005–4022, https://doi.org/10.5194/acp-16-4005-2016, 2016.
Larkin, N., O'Neill, S., Solomon, R., Raffuse, S., Strand, T., Sullivan, D., Krull, C., Rorig, M., Peterson, J., and Ferguson, S.: The BlueSky smoke modeling framework, Int. J. Wildland Fire, 18, 906–920, https://doi.org/10.1071/WF07086, 2009.
Larkin, N., Strand, T., Drury, S., Raffuse, S., Solomon, R., O'Neill, S., Wheeler, N., Huang, S., Roring, M., and Hafner, H.: Phase 1 of the Smoke and Emissions Model Intercomparison Project (SEMIP): creation of SEMIP and evaluation of current models, available at: https://digitalcommons.unl.edu/jfspresearch/42/ (last access: 19 February 2018), 2012.
Lavrov, A., Utkin, A. B., Vilar, R., and Fernandes, A.: Evaluation of smoke dispersion from forest fire plumes using lidar experiments and modelling, Int. J. Therm. Sci., 45, 848–859, 2006.
Lee, B., Alexander, M., Hawkes, B., Lynham, T., Stocks, B., and Englefield, P.: Information systems in support of wildland fire management decision making in Canada, Comput. Electron. Agr., 37, 185–198, https://doi.org/10.1016/S0168-1699(02)00120-5, 2003.
Liu, Y., Achtemeier, G. L., Goodrick, S. L., and Jackson, W. A.: Important parameters for smoke plume rise simulation with Daysmoke, Atmos. Pollut. Res., 1, 250–259, 2010.
Liu, Y., Goodrick, S. L., Achtemeier, G. L., Forbus, K., and Combs, D.: Smoke plume height measurement of prescribed burns in the south-eastern United States, Int. J. Wildland Fire, 22, 130–147, 2013.
Natural Resources Canada: Canadian Wildland Fire Information System, CWFIS Datamart, Natural Resources Canada: Ottawa, ON, available at: http://cwfis.cfs.nrcan.gc.ca/datamart, last access: 19 February 2018.
Pouliot, D., Latifovic, R., Olthof, I., and Fraser, R.: Supervised Classification Approaches for the Development of Land-Cover Time Series, in: Remote Sensing of Land Use and Land Cover: Principles and Applications, edited by: Giri, C. P., 177–190, CRC Press, Boca Raton FL, 2012.
Power, K. and Gillis, M.: Canada's forest inventory 2001, vol. 408, Pacific Forestry Centre, Victoria, BC, 2006.
Raffuse, S., Craig, K., Larkin, N., Strand, T., Sullivan, D., Wheeler, N., and Solomon, R.: An evaluation of modeled plume injection height with satellite-derived observed plume height, Atmosphere, 3, 103–123, https://doi.org/10.3390/atmos3010103, 2012.
Rolph, G. D., Draxler, R. R., Stein, A. F., Taylor, A., Ruminski, M. G., Kondragunta, S., Zeng, J., Huang, H.-C., Manikin, G., McQueen, J. T., et al.: Description and verification of the NOAA smoke forecasting system: the 2007 fire season, Weather Forecast., 24, 361–378, 2009.
Sofiev, M., Vankevich, R., Lotjonen, M., Prank, M., Petukhov, V., Ermakova, T., Koskinen, J., and Kukkonen, J.: An operational system for the assimilation of the satellite information on wild-land fires for the needs of air quality modelling and forecasting, Atmos. Chem. Phys., 9, 6833–6847, https://doi.org/10.5194/acp-9-6833-2009, 2009.
Sofiev, M., Ermakova, T., and Vankevich, R.: Evaluation of the smoke-injection height from wild-land fires using remote-sensing data, Atmos. Chem. Phys., 12, 1995–2006, https://doi.org/10.5194/acp-12-1995-2012, 2012.
Stieb, D., Yao, J., Henderson, S., Pinault, L., Smith-Doiron, M., Robichaud, A., van Donkelaar, A., Martin, R., Menard, R., and Brook, J. R.: Variability in ambient air pollution concentrations and population susceptibility among Canadian health regions, C. J. Public Health, in review, 2018.
Stocks, B., Lawson, B., Alexander, M., Van Wagner, C., McAlpine, R., Lynham, T., and Dubé, D, E.: The Canadian Forest Fire Danger Rating System: an overview, Forest. Chron., 65, 450–457, 1989.
Val Martin, M., Logan, J. A., Kahn, R. A., Leung, F.-Y., Nelson, D. L., and Diner, D. J.: Smoke injection heights from fires in North America: analysis of 5 years of satellite observations, Atmos. Chem. Phys., 10, 1491–1510, https://doi.org/10.5194/acp-10-1491-2010, 2010.
Val Martin, M., Kahn, R., Logan, J., Paugam, R., Wooster, M., and Ichoku, C.: Space-based observational constraints for 1-D fire smoke plume-rise models, J. Geophys. Res.-Atmos., 117, published online, 18 pp., https://doi.org/10.1029/2012JD018370, 2012.
Van Wagner, C.: Development and structure of the Canadian Forest Fire Weather Index System, Tech. Rep. 35, Canadian Forestry Service, Ottawa, ON, 1987.
Short summary
A field project was conducted to measure smoke plumes from wildland fires in Alberta. This study used handheld inclinometers and photos taken at fire lookout towers. Observations of 222 plumes were collected from 2010 to 2015.
Unanticipated issues were uncovered including instrument limitations, environmental conditions, and subjectivity of observations. Despite these problems, the data set showed responses to fire behaviour conditions consistent with processes leading to plume rise.
Unanticipated issues were uncovered including instrument limitations, environmental conditions, and subjectivity of observations. Despite these problems, the data set showed responses to fire behaviour conditions consistent with processes leading to plume rise.
A field project was conducted to measure smoke plumes from wildland fires in Alberta. This study...
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