Articles | Volume 16, issue 7
https://doi.org/10.5194/acp-16-4661-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-4661-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Effects of long-range aerosol transport on the microphysical properties of low-level liquid clouds in the Arctic
Quentin Coopman
CORRESPONDING AUTHOR
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, UT, USA
Laboratoire d'Optique Atmosphérique, Université
de Lille/CNRS, Lille, France
Timothy J. Garrett
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, UT, USA
Jérôme Riedi
Laboratoire d'Optique Atmosphérique, Université
de Lille/CNRS, Lille, France
Sabine Eckhardt
Norwegian Institute for Air Research,
Kjeller, Norway
Andreas Stohl
Norwegian Institute for Air Research,
Kjeller, Norway
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Sara Herrero-Anta, Sabine Eckhardt, Nikolaos Evangeliou, Stefania Gilardoni, Sandra Graßl, Dominic Heslin-Rees, Stelios Kazadzis, Natalia Kouremeti, Radovan Krejci, David Mateos, Mauro Mazzola, Christoph Ritter, Roberto Román, Kerstin Stebel, and Tymon Zielinski
EGUsphere, https://doi.org/10.5194/egusphere-2025-3423, https://doi.org/10.5194/egusphere-2025-3423, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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In summer 2019, unusually high aerosol levels were measured in the Arctic, linked to wildfires, volcanic eruptions, and anthropogenic pollution. Using various instruments and models, we traced their origins and found good agreement between methods. The particles were mostly non-absorbing, but still we found a reduction of the solar radiation reaching the surface. This study shows that combining different measurements improves our understanding of how distant events affect the Arctic climate.
Thomas D. DeWitt, Timothy J. Garrett, and Karlie N. Rees
EGUsphere, https://doi.org/10.5194/egusphere-2025-3486, https://doi.org/10.5194/egusphere-2025-3486, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Clouds appear chaotic, but they in fact follow fractal mathematical patterns similar to coastlines. We measured their fractal properties using satellite images and found two key numbers that describe cloud shapes: one for how rough individual cloud edges are, and another for how clouds of different sizes organize together. We recommend methodology that provides objective ways to verify whether climate models accurately simulate real clouds.
Olga B. Popovicheva, Marina A. Chichaeva, Nikolaos Evangeliou, Sabine Eckhardt, Evangelia Diapouli, and Nikolay S. Kasimov
Atmos. Chem. Phys., 25, 7719–7739, https://doi.org/10.5194/acp-25-7719-2025, https://doi.org/10.5194/acp-25-7719-2025, 2025
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High-quality measurements of light-absorbing carbon were performed at the polar aerosol station "Island Bely” (Western Siberian Arctic) from 2019 to 2022. The maximum light absorption coefficients were seen in summer due to gas flaring, which is the most significant source in the region. However, the increasing Siberian wildfires had a special share in carbon contribution at this high Arctic station, with a persistent smoke layer extending over the whole troposphere in summer.
Spencer Donovan, Dhiraj K. Singh, Timothy J. Garrett, and Eric R. Pardyjak
EGUsphere, https://doi.org/10.5194/egusphere-2025-3060, https://doi.org/10.5194/egusphere-2025-3060, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Accurate snowfall prediction requires quantifying how snowflakes interact with atmospheric turbulence. Using field-based imaging techniques, we directly measured the mass, size, density, and fall speed of snowflakes in surface-layer turbulence. We found that turbulence and microstructure jointly modulate fall speed, often deviating from the terminal velocity in still air. These results inform new parameterizations for numerical weather and climate models.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Nikolaos Evangeliou, Ondřej Tichý, Marit Svendby Otervik, Sabine Eckhardt, Yves Balkanski, and Didier A. Hauglustaine
Aerosol Research, 3, 155–174, https://doi.org/10.5194/ar-3-155-2025, https://doi.org/10.5194/ar-3-155-2025, 2025
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The COVID-19 lockdown measures in 2020 reduced emissions of various substances, improving air quality. However, PM2.5 stayed unchanged due to NH3 and related chemical transformations. Higher humidity favoured more SO42- production, as did the accumulated NH3. Excess NH3 reacted with HNO3 to make NO3-. In high-NH3 conditions such as those in 2020, a small reduction in NOx levels drove faster oxidation of NO3- and slower deposition of total inorganic NO3-, causing high secondary PM2.5.
Michel Legrand, Mstislav Vorobyev, Daria Bokuchava, Stanislav Kutuzov, Andreas Plach, Andreas Stohl, Alexandra Khairedinova, Vladimir Mikhalenko, Maria Vinogradova, Sabine Eckhardt, and Susanne Preunkert
Atmos. Chem. Phys., 25, 1385–1399, https://doi.org/10.5194/acp-25-1385-2025, https://doi.org/10.5194/acp-25-1385-2025, 2025
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Past atmospheric NH3 pollution in south-eastern Europe was reconstructed by analysing ammonium in an ice core drilled at the Mount Elbrus (Caucasus, Russia). The observed 3.5-fold increase in ice concentrations between 1750 and 1990 CE is in good agreement with estimated past dominant ammonia emissions from agriculture, mainly from south European Russia and Türkiye. In contrast to present-day conditions, the ammonium level observed in 1750 CE indicates significant natural emissions at that time.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Karlie N. Rees, Timothy J. Garrett, Thomas D. DeWitt, Corey Bois, Steven K. Krueger, and Jérôme C. Riedi
Nonlin. Processes Geophys., 31, 497–513, https://doi.org/10.5194/npg-31-497-2024, https://doi.org/10.5194/npg-31-497-2024, 2024
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The shapes of clouds viewed from space reflect vertical and horizontal motions in the atmosphere. We theorize that, globally, cloud perimeter complexity is related to the dimension of turbulence also governed by horizontal and vertical motions. We find agreement between theory and observations from various satellites and a numerical model and, remarkably, that the theory applies globally using only basic planetary physical parameters from the smallest scales of turbulence to the planetary scale.
Dhiraj K. Singh, Eric R. Pardyjak, and Timothy J. Garrett
Atmos. Meas. Tech., 17, 4581–4598, https://doi.org/10.5194/amt-17-4581-2024, https://doi.org/10.5194/amt-17-4581-2024, 2024
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Accurate measurements of the properties of snowflakes are challenging to make. We present a new technique for the real-time measurement of the density of freshly fallen individual snowflakes. A new thermal-imaging instrument, the Differential Emissivity Imaging Disdrometer (DEID), is shown to be capable of providing accurate estimates of individual snowflake and bulk snow hydrometeor density. The method exploits the rate of heat transfer during the melting of a snowflake on a hotplate.
Thomas D. DeWitt and Timothy J. Garrett
Atmos. Chem. Phys., 24, 8457–8472, https://doi.org/10.5194/acp-24-8457-2024, https://doi.org/10.5194/acp-24-8457-2024, 2024
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There is considerable disagreement on mathematical parameters that describe the number of clouds of different sizes as well as the size of the largest clouds. Both are key defining characteristics of Earth's atmosphere. A previous study provided an incorrect explanation for the disagreement. Instead, the disagreement may be explained by prior studies not properly accounting for the size of their measurement domain. We offer recommendations for how the domain size can be accounted for.
Karl Espen Yttri, Are Bäcklund, Franz Conen, Sabine Eckhardt, Nikolaos Evangeliou, Markus Fiebig, Anne Kasper-Giebl, Avram Gold, Hans Gundersen, Cathrine Lund Myhre, Stephen Matthew Platt, David Simpson, Jason D. Surratt, Sönke Szidat, Martin Rauber, Kjetil Tørseth, Martin Album Ytre-Eide, Zhenfa Zhang, and Wenche Aas
Atmos. Chem. Phys., 24, 2731–2758, https://doi.org/10.5194/acp-24-2731-2024, https://doi.org/10.5194/acp-24-2731-2024, 2024
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We discuss carbonaceous aerosol (CA) observed at the high Arctic Zeppelin Observatory (2017 to 2020). We find that organic aerosol is a significant fraction of the Arctic aerosol, though less than sea salt aerosol and mineral dust, as well as non-sea-salt sulfate, originating mainly from anthropogenic sources in winter and from natural sources in summer, emphasizing the importance of wildfires for biogenic secondary organic aerosol and primary biological aerosol particles observed in the Arctic.
Thomas D. DeWitt, Timothy J. Garrett, Karlie N. Rees, Corey Bois, Steven K. Krueger, and Nicolas Ferlay
Atmos. Chem. Phys., 24, 109–122, https://doi.org/10.5194/acp-24-109-2024, https://doi.org/10.5194/acp-24-109-2024, 2024
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Viewed from space, a defining feature of Earth's atmosphere is the wide spectrum of cloud sizes. A recent study predicted the distribution of cloud sizes, and this paper compares the prediction to observations. Although there is nuance in viewing perspective, we find robust agreement with theory across different climatological conditions, including land–ocean contrasts, time of year, or latitude, suggesting a minor role for Coriolis forces, aerosol loading, or surface temperature.
Ondřej Tichý, Sabine Eckhardt, Yves Balkanski, Didier Hauglustaine, and Nikolaos Evangeliou
Atmos. Chem. Phys., 23, 15235–15252, https://doi.org/10.5194/acp-23-15235-2023, https://doi.org/10.5194/acp-23-15235-2023, 2023
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We show declining trends in NH3 emissions over Europe for 2013–2020 using advanced dispersion and inverse modelling and satellite measurements from CrIS. Emissions decreased by −26% since 2013, showing that the abatement strategies adopted by the European Union have been very efficient. Ammonia emissions are low in winter and peak in summer due to temperature-dependent soil volatilization. The largest decreases were observed in central and western Europe in countries with high emissions.
Jenny Oh, Chubashini Shunthirasingham, Ying Duan Lei, Faqiang Zhan, Yuening Li, Abigaëlle Dalpé Castilloux, Amina Ben Chaaben, Zhe Lu, Kelsey Lee, Frank A. P. C. Gobas, Sabine Eckhardt, Nick Alexandrou, Hayley Hung, and Frank Wania
Atmos. Chem. Phys., 23, 10191–10205, https://doi.org/10.5194/acp-23-10191-2023, https://doi.org/10.5194/acp-23-10191-2023, 2023
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An emerging brominated flame retardant (BFR) called TBECH (1,2-dibromo-4-(1,2-dibromoethyl)cyclohexane) has never been produced or imported for use in Canada yet is found to be one of the most abundant gaseous BFRs in the Canadian atmosphere. The recorded spatial and temporal variability of TBECH suggest that the release from imported consumer products containing TBECH is the most likely explanation for its environmental occurrence in Canada.
Xavier Ceamanos, Bruno Six, Suman Moparthy, Dominique Carrer, Adèle Georgeot, Josef Gasteiger, Jérôme Riedi, Jean-Luc Attié, Alexei Lyapustin, and Iosif Katsev
Atmos. Meas. Tech., 16, 2575–2599, https://doi.org/10.5194/amt-16-2575-2023, https://doi.org/10.5194/amt-16-2575-2023, 2023
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A new algorithm to retrieve the diurnal evolution of aerosol optical depth over land and ocean from geostationary meteorological satellites is proposed and successfully evaluated with reference ground-based and satellite data. The high-temporal-resolution aerosol observations that are obtained from the EUMETSAT Meteosat Second Generation mission are unprecedented and open the door to studies that cannot be conducted with the once-a-day observations available from low-Earth-orbit satellites.
Anja Eichler, Michel Legrand, Theo M. Jenk, Susanne Preunkert, Camilla Andersson, Sabine Eckhardt, Magnuz Engardt, Andreas Plach, and Margit Schwikowski
The Cryosphere, 17, 2119–2137, https://doi.org/10.5194/tc-17-2119-2023, https://doi.org/10.5194/tc-17-2119-2023, 2023
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We investigate how a 250-year history of the emission of air pollutants (major inorganic aerosol constituents, black carbon, and trace species) is preserved in ice cores from four sites in the European Alps. The observed uniform timing in species-dependent longer-term concentration changes reveals that the different ice-core records provide a consistent, spatially representative signal of the pollution history from western European countries.
Huazhe Shang, Souichiro Hioki, Guillaume Penide, Céline Cornet, Husi Letu, and Jérôme Riedi
Atmos. Chem. Phys., 23, 2729–2746, https://doi.org/10.5194/acp-23-2729-2023, https://doi.org/10.5194/acp-23-2729-2023, 2023
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We find that cloud profiles can be divided into four prominent patterns, and the frequency of these four patterns is related to intensities of cloud-top entrainment and precipitation. Based on these analyses, we further propose a cloud profile parameterization scheme allowing us to represent these patterns. Our results shed light on how to facilitate the representation of cloud profiles and how to link them to cloud entrainment or precipitating status in future remote-sensing applications.
Timothy J. Garrett, Matheus R. Grasselli, and Stephen Keen
Earth Syst. Dynam., 13, 1021–1028, https://doi.org/10.5194/esd-13-1021-2022, https://doi.org/10.5194/esd-13-1021-2022, 2022
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Current world economic production is rising relative to energy consumption. This increase in
production efficiencysuggests that carbon dioxide emissions can be decoupled from economic activity through technological change. We show instead a nearly fixed relationship between energy consumption and a new economic quantity, historically cumulative economic production. The strong link to the past implies inertia may play a more dominant role in societal evolution than is generally assumed.
Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
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Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
Christine D. Groot Zwaaftink, Wenche Aas, Sabine Eckhardt, Nikolaos Evangeliou, Paul Hamer, Mona Johnsrud, Arve Kylling, Stephen M. Platt, Kerstin Stebel, Hilde Uggerud, and Karl Espen Yttri
Atmos. Chem. Phys., 22, 3789–3810, https://doi.org/10.5194/acp-22-3789-2022, https://doi.org/10.5194/acp-22-3789-2022, 2022
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We investigate causes of a poor-air-quality episode in northern Europe in October 2020 during which EU health limits for air quality were vastly exceeded. Such episodes may trigger measures to improve air quality. Analysis based on satellite observations, transport simulations, and surface observations revealed two sources of pollution. Emissions of mineral dust in Central Asia and biomass burning in Ukraine arrived almost simultaneously in Norway, and transport continued into the Arctic.
Stephen M. Platt, Øystein Hov, Torunn Berg, Knut Breivik, Sabine Eckhardt, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Markus Fiebig, Rebecca Fisher, Georg Hansen, Hans-Christen Hansson, Jost Heintzenberg, Ove Hermansen, Dominic Heslin-Rees, Kim Holmén, Stephen Hudson, Roland Kallenborn, Radovan Krejci, Terje Krognes, Steinar Larssen, David Lowry, Cathrine Lund Myhre, Chris Lunder, Euan Nisbet, Pernilla B. Nizzetto, Ki-Tae Park, Christina A. Pedersen, Katrine Aspmo Pfaffhuber, Thomas Röckmann, Norbert Schmidbauer, Sverre Solberg, Andreas Stohl, Johan Ström, Tove Svendby, Peter Tunved, Kjersti Tørnkvist, Carina van der Veen, Stergios Vratolis, Young Jun Yoon, Karl Espen Yttri, Paul Zieger, Wenche Aas, and Kjetil Tørseth
Atmos. Chem. Phys., 22, 3321–3369, https://doi.org/10.5194/acp-22-3321-2022, https://doi.org/10.5194/acp-22-3321-2022, 2022
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Here we detail the history of the Zeppelin Observatory, a unique global background site and one of only a few in the high Arctic. We present long-term time series of up to 30 years of atmospheric components and atmospheric transport phenomena. Many of these time series are important to our understanding of Arctic and global atmospheric composition change. Finally, we discuss the future of the Zeppelin Observatory and emerging areas of future research on the Arctic atmosphere.
Karlie N. Rees and Timothy J. Garrett
Atmos. Meas. Tech., 14, 7681–7691, https://doi.org/10.5194/amt-14-7681-2021, https://doi.org/10.5194/amt-14-7681-2021, 2021
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Monte Carlo simulations are used to establish baseline precipitation measurement uncertainties according to World Meteorological Organization standards. Measurement accuracy depends on instrument sampling area, time interval, and precipitation rate. Simulations are compared with field measurements taken by an emerging hotplate precipitation sensor. We find that the current collection area is sufficient for light rain, but a larger collection area is required to detect moderate to heavy rain.
Dhiraj K. Singh, Spencer Donovan, Eric R. Pardyjak, and Timothy J. Garrett
Atmos. Meas. Tech., 14, 6973–6990, https://doi.org/10.5194/amt-14-6973-2021, https://doi.org/10.5194/amt-14-6973-2021, 2021
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This paper describes a new instrument for quantifying the physical characteristics of hydrometeors such as snow and rain. The device can measure the mass, size, density and type of individual hydrometeors as well as their bulk properties. The instrument is called the Differential Emissivity Imaging Disdrometer (DEID) and is composed of a thermal camera and hotplate. The DEID measures hydrometeors at sampling frequencies up to 1 Hz with masses and effective diameters greater than 1 µg and 200 µm.
Karlie N. Rees, Dhiraj K. Singh, Eric R. Pardyjak, and Timothy J. Garrett
Atmos. Chem. Phys., 21, 14235–14250, https://doi.org/10.5194/acp-21-14235-2021, https://doi.org/10.5194/acp-21-14235-2021, 2021
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Accurate predictions of weather and climate require descriptions of the mass and density of snowflakes as a function of their size. Few measurements have been obtained to date because snowflakes are so small and fragile. This article describes results from a new instrument that automatically measures individual snowflake size, mass, and density. Key findings are that small snowflakes have much lower densities than is often assumed and that snowflake density increases with temperature.
Jessica L. McCarty, Juha Aalto, Ville-Veikko Paunu, Steve R. Arnold, Sabine Eckhardt, Zbigniew Klimont, Justin J. Fain, Nikolaos Evangeliou, Ari Venäläinen, Nadezhda M. Tchebakova, Elena I. Parfenova, Kaarle Kupiainen, Amber J. Soja, Lin Huang, and Simon Wilson
Biogeosciences, 18, 5053–5083, https://doi.org/10.5194/bg-18-5053-2021, https://doi.org/10.5194/bg-18-5053-2021, 2021
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Fires, including extreme fire seasons, and fire emissions are more common in the Arctic. A review and synthesis of current scientific literature find climate change and human activity in the north are fuelling an emerging Arctic fire regime, causing more black carbon and methane emissions within the Arctic. Uncertainties persist in characterizing future fire landscapes, and thus emissions, as well as policy-relevant challenges in understanding, monitoring, and managing Arctic fire regimes.
Karl Espen Yttri, Francesco Canonaco, Sabine Eckhardt, Nikolaos Evangeliou, Markus Fiebig, Hans Gundersen, Anne-Gunn Hjellbrekke, Cathrine Lund Myhre, Stephen Matthew Platt, André S. H. Prévôt, David Simpson, Sverre Solberg, Jason Surratt, Kjetil Tørseth, Hilde Uggerud, Marit Vadset, Xin Wan, and Wenche Aas
Atmos. Chem. Phys., 21, 7149–7170, https://doi.org/10.5194/acp-21-7149-2021, https://doi.org/10.5194/acp-21-7149-2021, 2021
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Carbonaceous aerosol sources and trends were studied at the Birkenes Observatory. A large decrease in elemental carbon (EC; 2001–2018) and a smaller decline in levoglucosan (2008–2018) suggest that organic carbon (OC)/EC from traffic/industry is decreasing, whereas the abatement of OC/EC from biomass burning has been less successful. Positive matrix factorization apportioned 72 % of EC to fossil fuel sources and 53 % (PM2.5) and 78 % (PM10–2.5) of OC to biogenic sources.
Nikolaos Evangeliou, Yves Balkanski, Sabine Eckhardt, Anne Cozic, Martin Van Damme, Pierre-François Coheur, Lieven Clarisse, Mark W. Shephard, Karen E. Cady-Pereira, and Didier Hauglustaine
Atmos. Chem. Phys., 21, 4431–4451, https://doi.org/10.5194/acp-21-4431-2021, https://doi.org/10.5194/acp-21-4431-2021, 2021
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Ammonia, a substance that has played a key role in sustaining life, has been increasing in the atmosphere, affecting climate and humans. Understanding the reasons for this increase is important for the beneficial use of ammonia. The evolution of satellite products gives us the opportunity to calculate ammonia emissions easier. We calculated global ammonia emissions over the last 10 years, incorporated them into a chemistry model and recorded notable improvement in reproducing observations.
Souichiro Hioki, Jérôme Riedi, and Mohamed S. Djellali
Atmos. Meas. Tech., 14, 1801–1816, https://doi.org/10.5194/amt-14-1801-2021, https://doi.org/10.5194/amt-14-1801-2021, 2021
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This research estimates the magnitude of a motion-induced error in the measurement of polarimetric state of light by a planned instrument on a future satellite. We discovered that the motion-induced error can not be cancelled out by spatiotemporal averaging, but it can be predicted from the along-track change of the intensity of light. With the estimated statistics and the simulation model, this research paves a way to provide pixel-level quality information in the future satellite products.
Nikolaos Evangeliou, Stephen M. Platt, Sabine Eckhardt, Cathrine Lund Myhre, Paolo Laj, Lucas Alados-Arboledas, John Backman, Benjamin T. Brem, Markus Fiebig, Harald Flentje, Angela Marinoni, Marco Pandolfi, Jesus Yus-Dìez, Natalia Prats, Jean P. Putaud, Karine Sellegri, Mar Sorribas, Konstantinos Eleftheriadis, Stergios Vratolis, Alfred Wiedensohler, and Andreas Stohl
Atmos. Chem. Phys., 21, 2675–2692, https://doi.org/10.5194/acp-21-2675-2021, https://doi.org/10.5194/acp-21-2675-2021, 2021
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Following the transmission of SARS-CoV-2 to Europe, social distancing rules were introduced to prevent further spread. We investigate the impacts of the European lockdowns on black carbon (BC) emissions by means of in situ observations and inverse modelling. BC emissions declined by 23 kt in Europe during the lockdowns as compared with previous years and by 11 % as compared to the period prior to lockdowns. Residential combustion prevailed in Eastern Europe, as confirmed by remote sensing data.
Kyle E. Fitch, Chaoxun Hang, Ahmad Talaei, and Timothy J. Garrett
Atmos. Meas. Tech., 14, 1127–1142, https://doi.org/10.5194/amt-14-1127-2021, https://doi.org/10.5194/amt-14-1127-2021, 2021
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Snow measurements are very sensitive to wind. Here, we compare airflow and snowfall simulations to Arctic observations for a Multi-Angle Snowflake Camera to show that measurements of fall speed, orientation, and size are accurate only with a double wind fence and winds below 5 m s−1. In this case, snowflakes tend to fall with a nearly horizontal orientation; the largest flakes are as much as 5 times more likely to be observed. Adjustments are needed for snow falling in naturally turbulent air.
Cited articles
Ackerman, A. S., Kirkpatrick, M. P., Stevens, D. E., and Toon, O. B.: The impact of humidity above stratiform clouds on indirect aerosol climate forcing, Nature, 432, 1014–1017, https://doi.org/10.1038/nature03137.1, 2004.
Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness, Science, 245, 1227–1230, 1989.
Amann, M., Bertok, I., Borken-Kleefeld, J., Cofala, J., Heyes, C., Höglund-Isaksson, L., Klimont, Z., Nguyen, B., Posch, M., Rafaj, P., Sandler, R., Schöpp, W., Wagner, F., and Winiwarter, W.: Cost-effective control of air quality and greenhouse gases in Europe: Modeling and policy applications, Environ. Modell. Softw., 26, 1489–1501, https://doi.org/10.1016/j.envsoft.2011.07.012, 2011.
Ancellet, G., Pelon, J., Blanchard, Y., Quennehen, B., Bazureau, A., Law, K. S., and Schwarzenboeck, A.: Transport of aerosol to the Arctic: analysis of CALIOP and French aircraft data during the spring 2008 POLARCAT campaign, Atmos. Chem. Phys., 14, 8235–8254, https://doi.org/10.5194/acp-14-8235-2014, 2014.
Andersen, H. and Cermak, J.: How thermodynamic environments control stratocumulus microphysics and interactions with aerosols, Environ. Res. Lett., 10, 24004, https://doi.org/10.1088/1748-9326/10/2/024004, 2015.
Andreae, M. O. and Rosenfeld, D.: Aerosol-cloud-precipitation interactions, Part 1. The nature and sources of cloud-active aerosols, Earth-Sci. Rev., 89, 13–41, https://doi.org/10.1016/j.earscirev.2008.03.001, 2008.
Avey, L., Garrett, T. J., and Stohl, A.: Evaluation of the aerosol indirect effect using satellite, tracer transport model, and aircraft data from the International Consortium for Atmospheric Research on Transport and Transformation, J. Geophys. Res.-Atmos., 112, 1–10, https://doi.org/10.1029/2006JD007581, 2007.
Belchansky, G. I., Douglas, D. C., and Platonov, N. G.: Duration of the Arctic sea ice melt season: Regional and interannual variability, 1979-2001, J. Climate, 17, 67–80, https://doi.org/10.1175/1520-0442(2004)017<0067:DOTASI>2.0.CO;2, 2004.
Berg, L. K., Berkowitz, C. M., Barnard, J. C., Senum, G., and Springston, S. R.: Observations of the first aerosol indirect effect in shallow cumuli, Geophys. Res. Lett., 38, L03809, https://doi.org/10.1029/2010GL046047, 2011.
Berrisford, P., Dee, D., Fielding, K., Fuentes, M., Kallberg, P., Kobayashi, S., and Uppala, S.: The ERA-Interim Archive, ECMWF, Reading, UK, 1, available at: http://old.ecmwf.int/publications/library/do/references/list/782009 (last access: 11 November 2015), 2009.
Bilde, M. and Svenningsson, B.: CCN activation of slightly soluble organics: The importance of small amounts of inorganic salt and particle phase, Tellus B, 56, 128–134, https://doi.org/10.1111/j.1600-0889.2004.00090.x, 2004.
Boisvert, L. N. and Stroeve, J. C.: The Arctic is becoming warmer and wetter as revealed by the Atmospheric Infrared Sounder, Geophys. Res. Lett., 42, 4439–4446, https://doi.org/10.1002/2015GL063775, 2015.
Brenguier, J. and Wood, R.: Observational strategies from the micro to meso scale, in: Clouds in the Perturbed Climate System: Their Relationship to Energy Balance, Atmospheric Dynamics, and Precipitation, edited by: Heintzenberg, J. and Charlson, R. J., 487–510, available at: ftp://ftp-projects.zmaw.de/aerocom/meetings/frankfurt_2007/brenguier.pdf (last access: 11 November 2015), MIT Press, MASS, Cambridge, 2009.
Bréon, F.-M. and Colzy, S.: Cloud detection from the spaceborne POLDER instrument and validation against surface synoptic observations, J. Appl. Meteorol., 38, 777–785, https://doi.org/10.1175/1520-0450(1999)038<0777:CDFTSP>2.0.CO;2, 1999.
Bréon, F.-M., Tanré, D., and Generoso, S.: Aerosol effect on cloud droplet size monitored from satellite, Science (New York, N. Y.), 295, 834–8, https://doi.org/10.1126/science.1066434, 2002.
Buriez, J. C., Vanbauce, C., Parol, F., Goloub, P., Herman, M., Bonnel, B., Fouquart, Y., Couvert, P., and Seze, G.: Cloud detection and derivation of cloud properties from POLDER, Int. J. Remote Sens., 18, 2785–2813, https://doi.org/10.1080/014311697217332, 1997.
Chang, F. L. and Coakley, J. A.: Relationships between marine stratus cloud optical depth and temperature: Inferences from AVHRR observations, J. Climate, 20, 2022–2036, https://doi.org/10.1175/JCLI4115.1, 2007.
Chen, Y.-C., Christensen, M. W., Stephens, G. L., and Seinfeld, J. H.: Satellite-based estimate of global aerosol–cloud radiative forcing by marine warm clouds, Nat. Geosci., advance on, 7, 643–646, https://doi.org/10.1038/ngeo2214, 2014.
Coakley, J. A. and Walsh, C. D.: Limits to the aerosol indirect radiative effect derived from observations of ship tracks, J. Atmos. Sci., 59, 668–680, https://doi.org/10.1175/1520-0469(2002)059<0668:LTTAIR>2.0.CO;2, 2002.
Costantino, L. and Bréon, F. M.: Aerosol indirect effect on warm clouds over South-East Atlantic, from co-located MODIS and CALIPSO observations, Atmos. Chem. Phys., 13, 69–88, https://doi.org/10.5194/acp-13-69-2013, 2013.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., Mcnally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Desmons, M., Ferlay, N., Parol, F., Mcharek, L., and Vanbauce, C.: Improved information about the vertical location and extent of monolayer clouds from POLDER3 measurements in the oxygen A-band, Atmos. Meas. Tech., 6, 2221–2238, https://doi.org/10.5194/amt-6-2221-2013, 2013.
Dusek, U., Frank, G. P., Hildebrandt, L., Curtius, J., Schneider, J., Walter, S., Chand, D., Drewnick, F., Hings, S., Jung, D., Borrmann, S., and Andreae, M. O.: Size matters more than chemistry for cloud-nucleating ability of aerosol particles, Science (New York, N. Y.), 312, 1375–1378, https://doi.org/10.1126/science.1125261, 2006.
Eckhardt, S., Quennehen, B., Olivié, D. J. L., Berntsen, T. K., Cherian, R., Christensen, J. H., Collins, W., Crepinsek, S., Daskalakis, N., Flanner, M., Herber, A., Heyes, C., Hodnebrog, Ø., Huang, L., Kanakidou, M., Klimont, Z., Langner, J., Law, K. S., Lund, M. T., Mahmood, R., Massling, A., Myriokefalitakis, S., Nielsen, I. E., Nøjgaard, J. K., Quaas, J., Quinn, P. K., Raut, J.-C., Rumbold, S. T., Schulz, M., Sharma, S., Skeie, R. B., Skov, H., Uttal, T., von Salzen, K., and Stohl, A.: Current model capabilities for simulating black carbon and sulfate concentrations in the Arctic atmosphere: a multi-model evaluation using a comprehensive measurement data set, Atmos. Chem. Phys., 15, 9413–9433, https://doi.org/10.5194/acp-15-9413-2015, 2015.
Ervens, B., Cubison, M., Andrews, E., Feingold, G., Ogren, J. A., Jimenez, J. L., DeCarlo, P., and Nenes, A.: Prediction of cloud condensation nucleus number concentration using measurements of aerosol size distributions and composition and light scattering enhancement due to humidity, J. Geophys. Res.-Atmos., 112, 1–15, https://doi.org/10.1029/2006JD007426, 2007.
Feingold, G.: Modeling of the first indirect effect: Analysis of measurement requirements, Geophys. Res. Lett., 30, 30, 1997, https://doi.org/10.1029/2003GL017967, 2003a.
Feingold, G.: First measurements of the Twomey indirect effect using ground-based remote sensors, Geophys. Res. Lett., 30, 19–22, https://doi.org/10.1029/2002GL016633, 2003b.
Feingold, G., Remer, L. A., Ramaprasad, J., and Kaufman, Y. J.: Analysis of smoke impact on clouds in Brazilian biomass burning regions: An extension of Twomey's approach, J. Geophys. Res., 106, 22907–22922, 2001.
Fougnie, B., Bracco, G., Lafrance, B., Ruffel, C., Hagolle, O., and Tinel, C.: PARASOL in-flight calibration and performance, Appl. Optics, 46, 5435–5451, https://doi.org/10.1364/AO.46.005435, 2007.
Garrett, T. J. and Zhao, C.: Increased Arctic cloud longwave emissivity associated with pollution from mid-latitudes, Nature 440, 787–789, https://doi.org/10.1038/nature04636, 2006.
Garrett, T. J., Radke, L. F., and Hobbs, P. V.: Aerosol Effects on Cloud Emissivity and Surface Longwave Heating in the Arctic, J. Atmos. Sci., 59, 769–778, https://doi.org/10.1175/1520-0469(2002)059<0769:AEOCEA>2.0.CO;2, 2002.
Garrett, T. J., Zhao, C., Dong, X., Mace, G. G., and Hobbs, P. V.: Effects of varying aerosol regimes on low-level Arctic stratus, Geophys. Res. Lett., 31, L17105, https://doi.org/10.1029/2004GL019928, 2004.
Garrett, T. J., Maestras, M. M., Krueger, S. K., and Shmidt, C. T.: Acceleration by aerosol of a radiative-thermodynamic cloud feedback influencing Arctic surface warming, Geophys. Res. Lett., 36, L19804, https://doi.org/10.1029/2009GL040195, 2009.
Garrett, T. J., Zhao, C., and Novelli, P. C.: Assessing the relative contributions of transport efficiency and scavenging to seasonal variability in Arctic aerosol, Tellus B, 62, 190–196, https://doi.org/10.1111/j.1600-0889.2010.00453.x, 2010.
Garrett, T. J., Brattström, S., Sharma, S., Worthy, D. E. J., and Novelli, P.: The role of scavenging in the seasonal transport of black carbon and sulfate to the Arctic, Geophys. Res. Lett., 38, L16805, https://doi.org/10.1029/2011GL048221, 2011.
Hirdman, D., Sodemann, H., Eckhardt, S., Burkhart, J. F., Jefferson, A., Mefford, T., Quinn, P. K., Sharma, S., Ström, J., and Stohl, A.: Source identification of short-lived air pollutants in the Arctic using statistical analysis of measurement data and particle dispersion model output, Atmos. Chem. Phys., 10, 669–693, https://doi.org/10.5194/acp-10-669-2010, 2010.
Huber, P. J.: The 1972 Wald memorial lectures: robust regression: asymptotics, conjectures, and Monte Carlo, The Annals of Statistics, 1, 799–821, 1973.
Huber, P. J.: Robust Statistics, John Wiley and Sons, Inc., New York, 1981.
Ji, R., Jin, M., and Varpe, Ø.: Sea ice phenology and timing of primary production pulses in the Arctic Ocean, Glob. Change Biol., 19, 734–741, https://doi.org/10.1111/gcb.12074, 2013.
Kaufman, Y. J., Koren, I., Remer, L. A., Rosenfeld, D., and Rudich, Y.: The effect of smoke, dust, and pollution aerosol on shallow cloud development over the Atlantic Ocean, P. Natl. Acad. Sci. USA, 102, 11207–11212, https://doi.org/10.1073/pnas.0505191102, 2005.
Kawamoto, K., Hayasaka, T., Uno, I., and Ohara, T.: A correlative study on the relationship between modeled anthropogenic aerosol concentration and satellite-observed cloud properties over east Asia, J. Geophys. Res.-Atmos., 111, 1–7, https://doi.org/10.1029/2005JD006919, 2006.
Kim, B. G., Miller, M. A., Schwartz, S. E., Liu, Y., and Min, Q.: The role of adiabaticity in the aerosol first indirect effect, J. Geophys. Res.-Atmos., 113, 1–13, https://doi.org/10.1029/2007JD008961, 2008.
King, M. D. and Platnick, S.: Collection 005 change summary for the MODIS cloud optical property (06 _ OD) algorithm high impact change overview: change details:, Terra, 1, 1–23, 2006.
Klein, S. A. and Hartmann, D. L.: The seasonal cycle of low stratiform clouds, J. Climate, 6, 1587–1606, 1993.
Klimont, Z., Smith, S. J., and Cofala, J.: The last decade of global anthropogenic sulfur dioxide: 2000–2011 emissions, Environ. Res. Lett., 8, 014003, https://doi.org/10.1088/1748-9326/8/1/014003, 2013.
Klimont, Z., Hoglund, L., Heyes, C., Rafaj, P., Schoepp, W., Cofala, J., Borken-Kleefeld, J., Purohit, P., Kupiainen, K., Winiwarter, W., Amann, M., Zhao, B., Wang, S. X., Bertok, I., and Sander, R.: Global scenarios of air pollutants and methane: 1990–2050, in preparation, 2016.
Lance, S., Shupe, M. D., Feingold, G., Brock, C. A., Cozic, J., Holloway, J. S., Moore, R. H., Nenes, A., Schwarz, J. P., Spackman, J. R., Froyd, K. D., Murphy, D. M., Brioude, J., Cooper, O. R., Stohl, A., and Burkhart, J. F.: Cloud condensation nuclei as a modulator of ice processes in Arctic mixed-phase clouds, Atmos. Chem. Phys., 11, 8003–8015, https://doi.org/10.5194/acp-11-8003-2011, 2011.
Law, K. S. and Stohl, A.: Arctic air pollution: origins and impacts, Science (New York, N. Y.), 315, 1537–40, https://doi.org/10.1126/science.1137695, 2007.
Law, K. S., Stohl, A., Quinn, P. K., Brock, C., Burkhart, J., Paris, J. D., Ancellet, G., Singh, H. B., Roiger, A., Schlager, H., Dibb, J., Jacob, D. J., Arnold, S. R., Pelon, J., and Thomas, J. L.: Arctic air pollution: new insights from POLARCAT-IPY, B. Am. Meteorol. Soc., 95, 1873–1895, https://doi.org/10.1175/BAMS-D-13-00017.1, 2014.
Lihavainen, H., Kerminen, V. M., and Remer, L. A.: Aerosol-cloud interaction determined by both in situ and satellite data over a northern high-latitude site, Atmos. Chem. Phys., 10, 10987–10995, https://doi.org/10.5194/acp-10-10987-2010, 2009.
Lindholt, L. and Glomsrød, S.: The Arctic: No big bonanza for the global petroleum industry, Energ. Econ., 34, 1465–1474, https://doi.org/10.1016/j.eneco.2012.06.020, 2012.
Lohmann, U. and Feichter, J.: Global indirect aerosol effects: a review, Atmos. Chem. Phys., 5, 715–737, https://doi.org/10.5194/acp-5-715-2005, 2005.
Longley, I. D., Inglis, D. W. F., Gallagher, M. W., Williams, P. I., Allan, J. D., and Coe, H.: Using NOx and CO monitoring data to indicate fine aerosol number concentrations and emission factors in three UK conurbations, Atmos. Environ., 39, 5157–5169, https://doi.org/10.1016/j.atmosenv.2005.05.017, 2005.
Lubin, D. and Vogelmann, A. M.: A climatologically significant aerosol longwave indirect effect in the Arctic, Nature, 439, 453–456, https://doi.org/10.1038/nature04449, 2006.
Lubin, D. and Vogelmann, A. M.: Expected magnitude of the aerosol shortwave indirect effect in springtime Arctic liquid water clouds, Geophys. Res. Lett., 34, L11801, https://doi.org/10.1029/2006GL028750, 2007.
Markus, T., Stroeve, J. C., and Miller, J.: Recent changes in Arctic sea ice melt onset, freezeup, and melt season length, J. Geophys. Res.-Oceans, 114, 1–14, https://doi.org/10.1029/2009JC005436, 2009.
Matsui, T., Masunaga, H., Kreidenweis, S. M., Pielke, R. A., Tao, W. K., Chin, M., and Kaufman, Y. J.: Satellite-based assessment of marine low cloud variability associated with aerosol, atmospheric stability, and the diurnal cycle, J. Geophys. Res.-Atmos., 111, 1–16, https://doi.org/10.1029/2005JD006097, 2006.
Mauger, G. S. and Norris, J. R.: Meteorological bias in satellite estimates of aerosol-cloud relationships, Geophys. Res. Lett., 34, 1–5, https://doi.org/10.1029/2007GL029952, 2007.
Mauritsen, T., Sedlar, J., Tjernström, M., Leck, C., Martin, M., Shupe, M., Sjogren, S., Sierau, B., Persson, P. O. G., Brooks, I. M., and Swietlicki, E.: An Arctic CCN-limited cloud-aerosol regime, Atmos. Chem. Phys., 11, 165–173, https://doi.org/10.5194/acp-11-165-2011, 2011.
Miller, A. W. and Ruiz, G. M.: Arctic shipping and marine invaders, Nature Clim. Change, 4, 413–416, https://doi.org/10.1038/nclimate2244, 2014.
Myhre, G., Stordal, F., Johnsrud, M., Kaufman, Y. J., Rosenfeld, D., Storelvmo, T., Kristjansson, J. E., Berntsen, T. K., Myhre, A., and Isaksen, I. S. A.: Aerosol-cloud interaction inferred from MODIS satellite data and global aerosol models, Atmos. Chem. Phys., 7, 3081–3101, https://doi.org/10.5194/acp-7-3081-2007, 2007.
Nakajima, T., Higurashi, A., Kawamoto, K., and Penner, J. E.: A possible correlation between satellite-derived cloud and aerosol microphysical parameters, Geophys. Res. Lett., 28, 1171–1174, https://doi.org/10.1029/2000GL012186, 2001.
Nygärd, T., Valkonen, T., and Vihma, T.: Characteristics of arctic low-tropospheric humidity inversions based on radio soundings, Atmos. Chem. Phys., 14, 1959–1971, https://doi.org/10.5194/acp-14-1959-2014, 2014.
Overland, J. E. and Wang, M.: When will the summer Arctic be nearly sea ice free?, Geophys. Res. Lett., 40, 2097–2101, https://doi.org/10.1002/grl.50316, 2013.
Painemal, D., Kato, S., and Minnis, P.: Boundary layer regulation in the southeast Atlantic cloud microphysics during the biomass burning season as seen by the A-train satellite constellation, J. Geophys. Res.-Atmos., 119, 11288–11302, https://doi.org/10.1002/2014JD022182, 2014.
Paris, J.-D., Stohl, A., Nédélec, P., Arshinov, M. Yu., Panchenko, M. V., Shmargunov, V. P., Law, K. S., Belan, B. D., and Ciais, P.: Wildfire smoke in the Siberian Arctic in summer: source characterization and plume evolution from airborne measurements, Atmos. Chem. Phys., 9, 9315–9327, https://doi.org/10.5194/acp-9-9315-2009, 2009.
Pincus, R. and Baker, M. B.: Effect of precipitation on the albedo susceptibility of clouds in the marine boundary layer, Nature, 372, 250–252, https://doi.org/10.1038/372250a0, 1994.
Pizzolato, L., Howell, S. E. L., Derksen, C., Dawson, J., and Copland, L.: Changing sea ice conditions and marine transportation activity in Canadian Arctic waters between 1990 and 2012, Climatic Change, 123, 161–173, https://doi.org/10.1007/s10584-013-1038-3, 2014.
Platnick, S., King, M. D., Ackerman, S. A., Menzel, W. P., Baum, B. A., Riédi, J. C., and Frey, R. A.: The MODIS cloud products: Algorithms and examples from terra, IEEE T. Geosci. Remote, 41, 459–472, https://doi.org/10.1109/TGRS.2002.808301, 2003.
Qiu, S., Dong, X., Xi, B., and Li, J. F.: Characterizing Arctic mixed-phase cloud structure and its relationship with humidity and temperature inversion using ARM NSA observations, J. Geophys. Res., 120, 7737–7746, https://doi.org/10.1002/2014JD023022, 2015.
Quinn, P. K., Shaw, G., Andrews, E., Dutton, E. G., Ruoho-Airola, T., and Gong, S. L.: Arctic haze: Current trends and knowledge gaps, Tellus B, 59, 99–114, https://doi.org/10.1111/j.1600-0889.2006.00238.x, 2007.
Richter-Menge, J. and Jeffries, M.: State of the climate in 2010: The Arctic, B. Am. Meteorol. Soc., 92, S143–S160, 2011.
Riedi, J., Marchant, B., Platnick, S., Baum, B. A., Thieuleux, F., Oudard, C., Parol, F., Nicolas, J.-M., and Dubuisson, P.: Cloud thermodynamic phase inferred from merged POLDER and MODIS data, Atmos. Chem. Phys., 10, 11851–11865, https://doi.org/10.5194/acp-10-11851-2010, 2010.
Schwartz, S. E., Harshvardhan, and Benkovitz, C. M.: Influence of anthropogenic aerosol on cloud optical depth and albedo shown by satellite measurements and chemical transport modeling, P. Natl. Acad. Sci. USA, 99, 1784–1789, https://doi.org/10.1073/pnas.261712099, 2002.
Sekiguchi, M.: A study of the direct and indirect effects of aerosols using global satellite data sets of aerosol and cloud parameters, J. Geophys. Res., 108, 1–15, https://doi.org/10.1029/2002JD003359, 2003.
Serreze, M. C. and Francis, J. A.: The Arctic on the fast track of change, Weather, 61, 65–69, https://doi.org/10.1256/wea.197.05, 2006.
Serreze, M. C., Barrett, A. P., Stroeve, J. C., Kindig, D. N., and Holland, M. M.: The emergence of surface-based Arctic amplification, The Cryosphere, 3, 11–19, https://doi.org/10.5194/tc-3-11-2009, 2009.
Shaw, G. E.: The arctic haze phenomenon, B. Am. Meteorol. Soc., 76, 2403–2413, https://doi.org/10.1175/1520-0477(1995)076<2403:TAHP>2.0.CO;2, 1995.
Shindell, D. T., Chin, M., Dentener, F., Doherty, R. M., Faluvegi, G., Fiore, A. M., Hess, P., Koch, D. M., MacKenzie, I. A., Sanderson, M. G., Schultz, M. G., Schulz, M., Stevenson, D. S., Teich, H., Textor, C., Wild, O., Bergmann, D. J., Bey, I., Bian, H., Cuvelier, C., Duncan, B. N., Folberth, G., Horowitz, L. W., Jonson, J., Kaminski, J. W., Marmer, E., Park, R., Pringle, K. J., Schroeder, S., Szopa, S., Takemura, T., Zeng, G., Keating, T. J., and Zuber, A.: A multi-model assessment of pollution transport to the Arctic, Atmos. Chem. Phys., 8, 5353–5372, https://doi.org/10.5194/acp-8-5353-2008, 2008.
Sirois, A. and Barrie, L. A.: Arctic lower tropospheric aerosol trends and composition at Alert, Canada: 1980–1995, J. Geophys. Res., 104, 11599, https://doi.org/10.1029/1999JD900077, 1999.
Sodemann, H., Pommier, M., Arnold, S. R., Monks, S. A., Stebel, K., Burkhart, J. F., Hair, J. W., Diskin, G. S., Clerbaux, C., Coheur, P.-F., Hurtmans, D., Schlager, H., Blechschmidt, A.-M., Kristjánsson, J. E., and Stohl, A.: Episodes of cross-polar transport in the Arctic troposphere during July 2008 as seen from models, satellite, and aircraft observations, Atmos. Chem. Phys., 11, 3631–3651, https://doi.org/10.5194/acp-11-3631-2011, 2011.
Sporre, M. K., Glantz, P., Tunved, P., Swietlicki, E., Kulmala, M., and Lihavainen, H.: A study of the indirect aerosol effect on subarctic marine liquid low-level clouds using MODIS cloud data and ground-based aerosol measurements, Atmos. Res., 116, 56–66, https://doi.org/10.1016/j.atmosres.2011.09.014, 2012.
Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., Sassen, K., Wang, Z., Illingworth, A. J., O'Connor, E. J., Rossow, W. B., Durden, S. L., Miller, S. D., Austin, R. T., Benedetti, A., and Mitrescu, C.: The cloudsat mission and the A-Train: A new dimension of space-based observations of clouds and precipitation, B. Am. Meteorol. Soc., 83, 1771–1790+1742, https://doi.org/10.1175/BAMS-83-12-1771, 2002.
Stohl, A.: Characteristics of atmospheric transport into the Arctic troposphere, J. Geophys. Res., 111, D11306, https://doi.org/10.1029/2005JD006888, 2006.
Stohl, A., Hittenberger, M., and Wotawa, G.: Validation of the lagrangian particle dispersion model FLEXPART against large-scale tracer experiment data, Atmos. Environ., 32, 4245–4264, https://doi.org/10.1016/S1352-2310(98)00184-8, 1998.
Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem. Phys., 5, 2461–2474, https://doi.org/10.5194/acp-5-2461-2005, 2005.
Stohl, A., Berg, T., Burkhart, J. F., Fjǽraa, A. M., Forster, C., Herber, A., Hov, Ø., Lunder, C., McMillan, W. W., Oltmans, S., Shiobara, M., Simpson, D., Solberg, S., Stebel, K., Ström, J., Tørseth, K., Treffeisen, R., Virkkunen, K., and Yttri, K. E.: Arctic smoke – record high air pollution levels in the European Arctic due to agricultural fires in Eastern Europe in spring 2006, Atmos. Chem. Phys., 7, 511–534, https://doi.org/10.5194/acp-7-511-2007, 2007.
Stohl, A., Klimont, Z., Eckhardt, S., Kupiainen, K., Shevchenko, V. P., Kopeikin, V. M., and Novigatsky, A. N.: Black carbon in the Arctic: the underestimated role of gas flaring and residential combustion emissions, Atmos. Chem. Phys., 13, 8833–8855, https://doi.org/10.5194/acp-13-8833-2013, 2013.
Stohl, A., Aamaas, B., Amann, M., Baker, L. H., Bellouin, N., Berntsen, T. K., Boucher, O., Cherian, R., Collins, W., Daskalakis, N., Dusinska, M., Eckhardt, S., Fuglestvedt, J. S., Harju, M., Heyes, C., Hodnebrog, Ø., Hao, J., Im, U., Kanakidou, M., Klimont, Z., Kupiainen, K., Law, K. S., Lund, M. T., Maas, R., MacIntosh, C. R., Myhre, G., Myriokefalitakis, S., Olivié, D., Quaas, J., Quennehen, B., Raut, J.-C., Rumbold, S. T., Samset, B. H., Schulz, M., Seland, Ø., Shine, K. P., Skeie, R. B., Wang, S., Yttri, K. E., and Zhu, T.: Evaluating the climate and air quality impacts of short-lived pollutants, Atmos. Chem. Phys., 15, 10529–10566, https://doi.org/10.5194/acp-15-10529-2015, 2015.
Tietze, K., Riedi, J., Stohl, A., and Garrett, T. J.: Space-based evaluation of interactions between aerosols and low-level Arctic clouds during the Spring and Summer of 2008, Atmos. Chem. Phys., 11, 3359-3373, https://doi.org/10.5194/acp-11-3359-2011, 2011.
Twomey, S.: The influence of Pollution on the shortwave Albedo of Clouds, J. Atmos. Sci., 34, 1149–1152,https://doi.org/10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2 1977.
Venables, W. N. and Ripley, B. D.: Modern Applied Statistics with S-PLUS, Springer Science and Business Media, New York, NY, 2013.
Wang, F., Guo, J., Wu, Y., Zhang, X., Deng, M., Li, X., Zhang, J., and Zhao, J.: Satellite observed aerosol-induced variability in warm cloud properties under different meteorological conditions over eastern China, Atmos. Environ., 84, 122–132, https://doi.org/10.1016/j.atmosenv.2013.11.018, 2014.
Warneke, C., Bahreini, R., Brioude, J., Brock, C. A., De Gouw, J. A., Fahey, D. W., Froyd, K. D., Holloway, J. S., Middlebrook, A., Miller, L., Montzka, S., Murphy, D. M., Peischl, J., Ryerson, T. B., Schwarz, J. P., Spademan, J. R., and Veres, P.: Biomass burning in Siberia and Kazakhstan as an important source for haze over the Alaskan Arctic in April 2008, Geophys. Res. Lett., 36, 2–7, https://doi.org/10.1029/2008GL036194, 2009.
Weisz, E., Li, J., Menzel, W. P., Heidinger, A. K., Kahn, B. H., and Liu, C. Y.: Comparison of AIRS, MODIS, CloudSat and CALIPSO cloud top height retrievals, Geophys. Res. Lett., 34, 1–5, https://doi.org/10.1029/2007GL030676, 2007.
Wesslén, C., Tjernström, M., Bromwich, D. H., De Boer, G., Ekman, A. M. L., Bai, L. S., and Wang, S. H.: The Arctic summer atmosphere: An evaluation of reanalyses using ASCOS data, Atmos. Chem. Phys., 14, 2605–2624, https://doi.org/10.5194/acp-14-2605-2014, 2014.
Westerling, A. L., Hidalgo, H. G., Cayan, D. R., and Swetnam, T. W.: Warming and earlier spring increase western U. S. forest wildfire activity, Science (New York, N. Y.), 313, 940–943, https://doi.org/10.1126/science.1128834, 2006.
Yoshimori, M., Watanabe, M., Abe-Ouchi, A., Shiogama, H., and Ogura, T.: Relative contribution of feedback processes to Arctic amplification of temperature change in MIROC GCM, Clim. Dynam., 42, 1613–1630, https://doi.org/10.1007/s00382-013-1875-9, 2013.
Zhao, C. and Garrett, T. J.: Effects of Arctic Haze on surface Cloud radiative forcing, Geophys. Res. Lett., 42, 557–564, https://doi.org/10.1002/2014GL062015, 2015.
Zhao, C., Klein, S. A., Xie, S., Liu, X., Boyle, J. S., and Zhang, Y.: Aerosol first indirect effects on non-precipitating low-level liquid cloud properties as simulated by CAM5 at ARM sites, Geophys. Res. Lett., 39, 1–7, https://doi.org/10.1029/2012GL051213, 2012.
Zygmuntowska, M., Mauritsen, T., Quaas, J., and Kaleschke, L.: Arctic clouds and surface radiation-a critical comparison of satellite retrievals and the ERA-interim reanalysis, Atmos. Chem. Phys., 12, 6667–6677, https://doi.org/10.5194/acp-12-6667-2012, 2012.
Short summary
We analyze interactions of Arctic clouds with pollution plumes that have been transported long distances from midlatitudes. Constraining for meteorological state, we find that pollution decreases cloud-droplet effective radius and increases cloud optical depth. The impact is highest when the atmosphere is particularly humid and/or stable suggesting that aerosol–cloud interactions depend on the Arctic's climate.
We analyze interactions of Arctic clouds with pollution plumes that have been transported long...
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