Articles | Volume 6, issue 3
https://doi.org/10.5194/amt-6-539-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-6-539-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
01 Mar 2013
Research article |
| 01 Mar 2013
Thermodynamic phase retrieval of convective clouds: impact of sensor viewing geometry and vertical distribution of cloud properties
E. Jäkel
Leipzig Institute for Meteorology (LIM), University of Leipzig, Leipzig, Germany
J. Walter
Leipzig Institute for Meteorology (LIM), University of Leipzig, Leipzig, Germany
M. Wendisch
Leipzig Institute for Meteorology (LIM), University of Leipzig, Leipzig, Germany
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Lara Foth, Wolfgang Dorn, Annette Rinke, Evelyn Jäkel, and Hannah Niehaus
The Cryosphere, 18, 4053–4064, https://doi.org/10.5194/tc-18-4053-2024, https://doi.org/10.5194/tc-18-4053-2024, 2024
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It is demonstrated that the explicit consideration of the cloud dependence of the snow surface albedo in a climate model results in a more realistic simulation of the surface albedo during the snowmelt period in late May and June. Although this improvement appears to be relatively insubstantial, it has significant impact on the simulated sea-ice volume and extent in the model due to an amplification of the snow/sea-ice albedo feedback, one of the main contributors to Arctic amplification.
Manfred Wendisch, Susanne Crewell, André Ehrlich, Andreas Herber, Benjamin Kirbus, Christof Lüpkes, Mario Mech, Steven J. Abel, Elisa F. Akansu, Felix Ament, Clémantyne Aubry, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Marlen Brückner, Hans-Christian Clemen, Sandro Dahlke, Georgios Dekoutsidis, Julien Delanoë, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Irina V. Gorodetskaya, Sarah Grawe, Silke Groß, Jörg Hartmann, Silvia Henning, Lutz Hirsch, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsofia Jurányi, Michail Karalis, Mona Kellermann, Marcus Klingebiel, Michael Lonardi, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Marion Maturilli, Bernhard Mayer, Johanna Mayer, Stephan Mertes, Janosch Michaelis, Michel Michalkov, Guillaume Mioche, Manuel Moser, Hanno Müller, Roel Neggers, Davide Ori, Daria Paul, Fiona M. Paulus, Christian Pilz, Felix Pithan, Mira Pöhlker, Veronika Pörtge, Maximilian Ringel, Nils Risse, Gregory C. Roberts, Sophie Rosenburg, Johannes Röttenbacher, Janna Rückert, Michael Schäfer, Jonas Schaefer, Vera Schemann, Imke Schirmacher, Jörg Schmidt, Sebastian Schmidt, Johannes Schneider, Sabrina Schnitt, Anja Schwarz, Holger Siebert, Harald Sodemann, Tim Sperzel, Gunnar Spreen, Bjorn Stevens, Frank Stratmann, Gunilla Svensson, Christian Tatzelt, Thomas Tuch, Timo Vihma, Christiane Voigt, Lea Volkmer, Andreas Walbröl, Anna Weber, Birgit Wehner, Bruno Wetzel, Martin Wirth, and Tobias Zinner
Atmos. Chem. Phys., 24, 8865–8892, https://doi.org/10.5194/acp-24-8865-2024, https://doi.org/10.5194/acp-24-8865-2024, 2024
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The Arctic is warming faster than the rest of the globe. Warm-air intrusions (WAIs) into the Arctic may play an important role in explaining this phenomenon. Cold-air outbreaks (CAOs) out of the Arctic may link the Arctic climate changes to mid-latitude weather. In our article, we describe how to observe air mass transformations during CAOs and WAIs using three research aircraft instrumented with state-of-the-art remote-sensing and in situ measurement devices.
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 Discuss., https://doi.org/10.5194/essd-2024-281, https://doi.org/10.5194/essd-2024-281, 2024
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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.
Hanno Müller, André Ehrlich, Evelyn Jäkel, Johannes Röttenbacher, Benjamin Kirbus, Michael Schäfer, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 4157–4175, https://doi.org/10.5194/acp-24-4157-2024, https://doi.org/10.5194/acp-24-4157-2024, 2024
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A weather model is used to compare solar radiation with measurements from an aircraft campaign in the Arctic. Model and observations agree on the downward radiation but show differences in the radiation reflected by the surface and the clouds, which in the model is too low above sea ice and too high above open ocean. The model–observation bias is reduced above open ocean by a realistic fraction of clouds and less cloud liquid water and above sea ice by less dark sea ice and more cloud droplets.
Evelyn Jäkel, Sebastian Becker, Tim R. Sperzel, Hannah Niehaus, Gunnar Spreen, Ran Tao, Marcel Nicolaus, Wolfgang Dorn, Annette Rinke, Jörg Brauchle, and Manfred Wendisch
The Cryosphere, 18, 1185–1205, https://doi.org/10.5194/tc-18-1185-2024, https://doi.org/10.5194/tc-18-1185-2024, 2024
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The results of the surface albedo scheme of a coupled regional climate model were evaluated against airborne and ground-based measurements conducted in the European Arctic in different seasons between 2017 and 2022. We found a seasonally dependent bias between measured and modeled surface albedo for cloudless and cloudy situations. The strongest effects of the albedo model bias on the net irradiance were most apparent in the presence of optically thin clouds.
Marcus Klingebiel, André Ehrlich, Elena Ruiz-Donoso, Nils Risse, Imke Schirmacher, Evelyn Jäkel, Michael Schäfer, Kevin Wolf, Mario Mech, Manuel Moser, Christiane Voigt, and Manfred Wendisch
Atmos. Chem. Phys., 23, 15289–15304, https://doi.org/10.5194/acp-23-15289-2023, https://doi.org/10.5194/acp-23-15289-2023, 2023
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In this study we explain how we use aircraft measurements from two Arctic research campaigns to identify cloud properties (like droplet size) over sea-ice and ice-free ocean. To make sure that our measurements make sense, we compare them with other observations. Our results show, e.g., larger cloud droplets in early summer than in spring. Moreover, the cloud droplets are also larger over ice-free ocean than compared to sea ice. In the future, our data can be used to improve climate models.
Manfred Wendisch, Johannes Stapf, Sebastian Becker, André Ehrlich, Evelyn Jäkel, Marcus Klingebiel, Christof Lüpkes, Michael Schäfer, and Matthew D. Shupe
Atmos. Chem. Phys., 23, 9647–9667, https://doi.org/10.5194/acp-23-9647-2023, https://doi.org/10.5194/acp-23-9647-2023, 2023
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Atmospheric radiation measurements have been conducted during two field campaigns using research aircraft. The data are analyzed to see if the near-surface air in the Arctic is warmed or cooled if warm–humid air masses from the south enter the Arctic or cold–dry air moves from the north from the Arctic to mid-latitude areas. It is important to study these processes and to check if climate models represent them well. Otherwise it is not possible to reliably forecast the future Arctic climate.
Sophie Rosenburg, Charlotte Lange, Evelyn Jäkel, Michael Schäfer, André Ehrlich, and Manfred Wendisch
Atmos. Meas. Tech., 16, 3915–3930, https://doi.org/10.5194/amt-16-3915-2023, https://doi.org/10.5194/amt-16-3915-2023, 2023
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Snow layer melting and melt pond formation on Arctic sea ice are important seasonal processes affecting the surface reflection and energy budget. Sea ice reflectivity was surveyed by airborne imaging spectrometers in May–June 2017. Adapted retrieval approaches were applied to find snow layer liquid water fraction, snow grain effective radius, and melt pond depth. The retrievals show the potential and limitations of spectral airborne imaging to map melting snow layer and melt pond properties.
Sebastian Becker, André Ehrlich, Evelyn Jäkel, Tim Carlsen, Michael Schäfer, and Manfred Wendisch
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Airborne radiation measurements are used to characterize the solar directional reflection of a mixture of Arctic sea ice and open-ocean surfaces in the transition zone between both surface types. The mixture reveals reflection properties of both surface types. It is shown that the directional reflection of the mixture can be reconstructed from the directional reflection of the individual surfaces, accounting for the special conditions present in the transition zone.
Michael Schäfer, Kevin Wolf, André Ehrlich, Christoph Hallbauer, Evelyn Jäkel, Friedhelm Jansen, Anna Elizabeth Luebke, Joshua Müller, Jakob Thoböll, Timo Röschenthaler, Bjorn Stevens, and Manfred Wendisch
Atmos. Meas. Tech., 15, 1491–1509, https://doi.org/10.5194/amt-15-1491-2022, https://doi.org/10.5194/amt-15-1491-2022, 2022
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The new airborne thermal infrared imager VELOX is introduced. It measures two-dimensional fields of spectral thermal infrared radiance or brightness temperature within the large atmospheric window. The technical specifications as well as necessary calibration and correction procedures are presented. Example measurements from the first field deployment are analysed with respect to cloud coverage and cloud top altitude.
Linlu Mei, Vladimir Rozanov, Evelyn Jäkel, Xiao Cheng, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2781–2802, https://doi.org/10.5194/tc-15-2781-2021, https://doi.org/10.5194/tc-15-2781-2021, 2021
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This paper presents a new snow property retrieval algorithm from satellite observations. This is Part 2 of two companion papers and shows the results and validation. The paper performs the new retrieval algorithm on the Sea and Land
Surface Temperature Radiometer (SLSTR) instrument and compares the retrieved snow properties with ground-based measurements, aircraft measurements and other satellite products.
Evelyn Jäkel, Tim Carlsen, André Ehrlich, Manfred Wendisch, Michael Schäfer, Sophie Rosenburg, Konstantina Nakoudi, Marco Zanatta, Gerit Birnbaum, Veit Helm, Andreas Herber, Larysa Istomina, Linlu Mei, and Anika Rohde
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-14, https://doi.org/10.5194/tc-2021-14, 2021
Preprint withdrawn
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Different approaches to retrieve the optical-equivalent snow grain size using satellite, airborne, and ground-based observations were evaluated and compared to modeled data. The study is focused on low Sun and partly rough surface conditions encountered North of Greenland in March/April 2018. We proposed an adjusted airborne retrieval method to reduce the retrieval uncertainty.
Tim Carlsen, Gerit Birnbaum, André Ehrlich, Veit Helm, Evelyn Jäkel, Michael Schäfer, and Manfred Wendisch
The Cryosphere, 14, 3959–3978, https://doi.org/10.5194/tc-14-3959-2020, https://doi.org/10.5194/tc-14-3959-2020, 2020
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The angular reflection of solar radiation by snow surfaces is particularly anisotropic and highly variable. We measured the angular reflection from an aircraft using a digital camera in Antarctica in 2013/14 and studied its variability: the anisotropy increases with a lower Sun but decreases for rougher surfaces and larger snow grains. The applied methodology allows for a direct comparison with satellite observations, which generally underestimated the anisotropy measured within this study.
Johannes Stapf, André Ehrlich, Evelyn Jäkel, Christof Lüpkes, and Manfred Wendisch
Atmos. Chem. Phys., 20, 9895–9914, https://doi.org/10.5194/acp-20-9895-2020, https://doi.org/10.5194/acp-20-9895-2020, 2020
Tobias Donth, Evelyn Jäkel, André Ehrlich, Bernd Heinold, Jacob Schacht, Andreas Herber, Marco Zanatta, and Manfred Wendisch
Atmos. Chem. Phys., 20, 8139–8156, https://doi.org/10.5194/acp-20-8139-2020, https://doi.org/10.5194/acp-20-8139-2020, 2020
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Solar radiative effects of Arctic black carbon (BC) particles (suspended in the atmosphere and in the surface snowpack) were quantified under cloudless and cloudy conditions. An atmospheric and a snow radiative transfer model were coupled to account for radiative interactions between both compartments. It was found that (i) the warming effect of BC in the snowpack overcompensates for the atmospheric BC cooling effect, and (ii) clouds tend to reduce the atmospheric BC cooling and snow BC warming.
Elena Ruiz-Donoso, André Ehrlich, Michael Schäfer, Evelyn Jäkel, Vera Schemann, Susanne Crewell, Mario Mech, Birte Solveig Kulla, Leif-Leonard Kliesch, Roland Neuber, and Manfred Wendisch
Atmos. Chem. Phys., 20, 5487–5511, https://doi.org/10.5194/acp-20-5487-2020, https://doi.org/10.5194/acp-20-5487-2020, 2020
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Mixed-phase clouds, formed of water droplets and ice crystals, appear frequently in Arctic regions. Characterizing the distribution of liquid water and ice inside the cloud appropriately is important because it influences the cloud's impact on the surface temperature. In this study, we combined images of the cloud top with measurements inside the cloud to analyze in detail the 3D spatial distribution of liquid and ice in two mixed-phase clouds occurring under different meteorological scenarios.
Christine Pohl, Larysa Istomina, Steffen Tietsche, Evelyn Jäkel, Johannes Stapf, Gunnar Spreen, and Georg Heygster
The Cryosphere, 14, 165–182, https://doi.org/10.5194/tc-14-165-2020, https://doi.org/10.5194/tc-14-165-2020, 2020
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A spectral to broadband conversion is developed empirically that can be used in combination with the Melt Pond Detector algorithm to derive broadband albedo (300–3000 nm) of Arctic sea ice from MERIS data. It is validated and shows better performance compared to existing conversion methods. A comparison of MERIS broadband albedo with respective values from ERA5 reanalysis suggests a revision of the albedo values used in ERA5. MERIS albedo might be useful for improving albedo representation.
André Ehrlich, Manfred Wendisch, Christof Lüpkes, Matthias Buschmann, Heiko Bozem, Dmitri Chechin, Hans-Christian Clemen, Régis Dupuy, Olliver Eppers, Jörg Hartmann, Andreas Herber, Evelyn Jäkel, Emma Järvinen, Olivier Jourdan, Udo Kästner, Leif-Leonard Kliesch, Franziska Köllner, Mario Mech, Stephan Mertes, Roland Neuber, Elena Ruiz-Donoso, Martin Schnaiter, Johannes Schneider, Johannes Stapf, and Marco Zanatta
Earth Syst. Sci. Data, 11, 1853–1881, https://doi.org/10.5194/essd-11-1853-2019, https://doi.org/10.5194/essd-11-1853-2019, 2019
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During the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign, two research aircraft (Polar 5 and 6) jointly performed 22 research flights over the transition zone between open ocean and closed sea ice. The data set combines remote sensing and in situ measurement of cloud, aerosol, and trace gas properties, as well as turbulent and radiative fluxes, which will be used to study Arctic boundary layer and mid-level clouds and their role in Arctic amplification.
Evelyn Jäkel, Johannes Stapf, Manfred Wendisch, Marcel Nicolaus, Wolfgang Dorn, and Annette Rinke
The Cryosphere, 13, 1695–1708, https://doi.org/10.5194/tc-13-1695-2019, https://doi.org/10.5194/tc-13-1695-2019, 2019
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The sea ice surface albedo parameterization of a coupled regional climate model was validated against aircraft measurements performed in May–June 2017 north of Svalbard. The albedo parameterization was run offline from the model using the measured parameters surface temperature and snow depth to calculate the surface albedo and the individual fractions of the ice surface subtypes. An adjustment of the variables and additionally accounting for cloud cover reduced the root-mean-squared error.
Tobias Zinner, Ulrich Schwarz, Tobias Kölling, Florian Ewald, Evelyn Jäkel, Bernhard Mayer, and Manfred Wendisch
Atmos. Meas. Tech., 12, 1167–1181, https://doi.org/10.5194/amt-12-1167-2019, https://doi.org/10.5194/amt-12-1167-2019, 2019
Trismono C. Krisna, Manfred Wendisch, André Ehrlich, Evelyn Jäkel, Frank Werner, Ralf Weigel, Stephan Borrmann, Christoph Mahnke, Ulrich Pöschl, Meinrat O. Andreae, Christiane Voigt, and Luiz A. T. Machado
Atmos. Chem. Phys., 18, 4439–4462, https://doi.org/10.5194/acp-18-4439-2018, https://doi.org/10.5194/acp-18-4439-2018, 2018
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The optical thickness and particle effective radius of a cirrus above liquid water clouds and a DCC topped by an anvil cirrus are retrieved based on SMART and MODIS radiance measurements. For the cirrus, retrieved particle effective radius are validated with corresponding in situ data using a vertical weighting method. This approach allows to assess the measurements, retrieval algorithms, and derived cloud products.
Evelyn Jäkel, Manfred Wendisch, Trismono C. Krisna, Florian Ewald, Tobias Kölling, Tina Jurkat, Christiane Voigt, Micael A. Cecchini, Luiz A. T. Machado, Armin Afchine, Anja Costa, Martina Krämer, Meinrat O. Andreae, Ulrich Pöschl, Daniel Rosenfeld, and Tianle Yuan
Atmos. Chem. Phys., 17, 9049–9066, https://doi.org/10.5194/acp-17-9049-2017, https://doi.org/10.5194/acp-17-9049-2017, 2017
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Vertical profiles of the cloud particle phase state in tropical deep convective clouds (DCCs) were investigated using airborne imaging spectrometer measurements during the ACRIDICON-CHUVA campaign, which was conducted over the Brazilian rainforest in September 2014. A phase discrimination retrieval was applied to observations of clouds formed in different aerosol conditions. The profiles were compared to in situ and satellite measurements.
Michael Schäfer, Eike Bierwirth, André Ehrlich, Evelyn Jäkel, Frank Werner, and Manfred Wendisch
Atmos. Chem. Phys., 17, 2359–2372, https://doi.org/10.5194/acp-17-2359-2017, https://doi.org/10.5194/acp-17-2359-2017, 2017
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Cloud optical thickness fields, retrieved from solar spectral radiance measurements, are used to investigate the directional structure of horizontal cloud inhomogeneities with scalar one-dimensional inhomogeneity parameters, two-dimensional auto-correlation functions, and two-dimensional Fourier analysis. The investigations reveal that it is not sufficient to quantify horizontal cloud inhomogeneities by one-dimensional inhomogeneity parameters; two-dimensional parameters are necessary.
E. Jäkel, B. Mey, R. Levy, X. Gu, T. Yu, Z. Li, D. Althausen, B. Heese, and M. Wendisch
Atmos. Meas. Tech., 8, 5237–5249, https://doi.org/10.5194/amt-8-5237-2015, https://doi.org/10.5194/amt-8-5237-2015, 2015
E. Jäkel, M. Wendisch, and B. Mayer
Atmos. Meas. Tech., 6, 527–537, https://doi.org/10.5194/amt-6-527-2013, https://doi.org/10.5194/amt-6-527-2013, 2013
Lara Foth, Wolfgang Dorn, Annette Rinke, Evelyn Jäkel, and Hannah Niehaus
The Cryosphere, 18, 4053–4064, https://doi.org/10.5194/tc-18-4053-2024, https://doi.org/10.5194/tc-18-4053-2024, 2024
Short summary
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It is demonstrated that the explicit consideration of the cloud dependence of the snow surface albedo in a climate model results in a more realistic simulation of the surface albedo during the snowmelt period in late May and June. Although this improvement appears to be relatively insubstantial, it has significant impact on the simulated sea-ice volume and extent in the model due to an amplification of the snow/sea-ice albedo feedback, one of the main contributors to Arctic amplification.
Manfred Wendisch, Susanne Crewell, André Ehrlich, Andreas Herber, Benjamin Kirbus, Christof Lüpkes, Mario Mech, Steven J. Abel, Elisa F. Akansu, Felix Ament, Clémantyne Aubry, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Marlen Brückner, Hans-Christian Clemen, Sandro Dahlke, Georgios Dekoutsidis, Julien Delanoë, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Irina V. Gorodetskaya, Sarah Grawe, Silke Groß, Jörg Hartmann, Silvia Henning, Lutz Hirsch, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsofia Jurányi, Michail Karalis, Mona Kellermann, Marcus Klingebiel, Michael Lonardi, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Marion Maturilli, Bernhard Mayer, Johanna Mayer, Stephan Mertes, Janosch Michaelis, Michel Michalkov, Guillaume Mioche, Manuel Moser, Hanno Müller, Roel Neggers, Davide Ori, Daria Paul, Fiona M. Paulus, Christian Pilz, Felix Pithan, Mira Pöhlker, Veronika Pörtge, Maximilian Ringel, Nils Risse, Gregory C. Roberts, Sophie Rosenburg, Johannes Röttenbacher, Janna Rückert, Michael Schäfer, Jonas Schaefer, Vera Schemann, Imke Schirmacher, Jörg Schmidt, Sebastian Schmidt, Johannes Schneider, Sabrina Schnitt, Anja Schwarz, Holger Siebert, Harald Sodemann, Tim Sperzel, Gunnar Spreen, Bjorn Stevens, Frank Stratmann, Gunilla Svensson, Christian Tatzelt, Thomas Tuch, Timo Vihma, Christiane Voigt, Lea Volkmer, Andreas Walbröl, Anna Weber, Birgit Wehner, Bruno Wetzel, Martin Wirth, and Tobias Zinner
Atmos. Chem. Phys., 24, 8865–8892, https://doi.org/10.5194/acp-24-8865-2024, https://doi.org/10.5194/acp-24-8865-2024, 2024
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The Arctic is warming faster than the rest of the globe. Warm-air intrusions (WAIs) into the Arctic may play an important role in explaining this phenomenon. Cold-air outbreaks (CAOs) out of the Arctic may link the Arctic climate changes to mid-latitude weather. In our article, we describe how to observe air mass transformations during CAOs and WAIs using three research aircraft instrumented with state-of-the-art remote-sensing and in situ measurement devices.
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 Discuss., https://doi.org/10.5194/essd-2024-281, https://doi.org/10.5194/essd-2024-281, 2024
Preprint under review for ESSD
Short summary
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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.
Johannes Röttenbacher, André Ehrlich, Hanno Müller, Florian Ewald, Anna E. Luebke, Benjamin Kirbus, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 8085–8104, https://doi.org/10.5194/acp-24-8085-2024, https://doi.org/10.5194/acp-24-8085-2024, 2024
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Weather prediction models simplify the physical processes related to light scattering by clouds consisting of complex ice crystals. Whether these simplifications are the cause for uncertainties in their prediction can be evaluated by comparing them with measurement data. Here we do this for Arctic ice clouds over sea ice using airborne measurements from two case studies. The model performs well for thick ice clouds but not so well for thin ones. This work can be used to improve the model.
Andreas Walbröl, Janosch Michaelis, Sebastian Becker, Henning Dorff, Kerstin Ebell, Irina Gorodetskaya, Bernd Heinold, Benjamin Kirbus, Melanie Lauer, Nina Maherndl, Marion Maturilli, Johanna Mayer, Hanno Müller, Roel A. J. Neggers, Fiona M. Paulus, Johannes Röttenbacher, Janna E. Rückert, Imke Schirmacher, Nils Slättberg, André Ehrlich, Manfred Wendisch, and Susanne Crewell
Atmos. Chem. Phys., 24, 8007–8029, https://doi.org/10.5194/acp-24-8007-2024, https://doi.org/10.5194/acp-24-8007-2024, 2024
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To support the interpretation of the data collected during the HALO-(AC)3 campaign, which took place in the North Atlantic sector of the Arctic from 7 March to 12 April 2022, we analyze how unusual the weather and sea ice conditions were with respect to the long-term climatology. From observations and ERA5 reanalysis, we found record-breaking warm air intrusions and a large variety of marine cold air outbreaks. Sea ice concentration was mostly within the climatological interquartile range.
Hanno Müller, André Ehrlich, Evelyn Jäkel, Johannes Röttenbacher, Benjamin Kirbus, Michael Schäfer, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 4157–4175, https://doi.org/10.5194/acp-24-4157-2024, https://doi.org/10.5194/acp-24-4157-2024, 2024
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A weather model is used to compare solar radiation with measurements from an aircraft campaign in the Arctic. Model and observations agree on the downward radiation but show differences in the radiation reflected by the surface and the clouds, which in the model is too low above sea ice and too high above open ocean. The model–observation bias is reduced above open ocean by a realistic fraction of clouds and less cloud liquid water and above sea ice by less dark sea ice and more cloud droplets.
Benjamin Kirbus, Imke Schirmacher, Marcus Klingebiel, Michael Schäfer, André Ehrlich, Nils Slättberg, Johannes Lucke, Manuel Moser, Hanno Müller, and Manfred Wendisch
Atmos. Chem. Phys., 24, 3883–3904, https://doi.org/10.5194/acp-24-3883-2024, https://doi.org/10.5194/acp-24-3883-2024, 2024
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A research aircraft is used to track the changes in air temperature, moisture, and cloud properties for air that moves from cold Arctic sea ice onto warmer oceanic waters. The measurements are compared to two reanalysis models named ERA5 and CARRA. The biggest differences are found for air temperature over the sea ice and moisture over the ocean. CARRA data are more accurate than ERA5 because they better simulate the sea ice, the transition from sea ice to open ocean, and the forming clouds.
Evelyn Jäkel, Sebastian Becker, Tim R. Sperzel, Hannah Niehaus, Gunnar Spreen, Ran Tao, Marcel Nicolaus, Wolfgang Dorn, Annette Rinke, Jörg Brauchle, and Manfred Wendisch
The Cryosphere, 18, 1185–1205, https://doi.org/10.5194/tc-18-1185-2024, https://doi.org/10.5194/tc-18-1185-2024, 2024
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The results of the surface albedo scheme of a coupled regional climate model were evaluated against airborne and ground-based measurements conducted in the European Arctic in different seasons between 2017 and 2022. We found a seasonally dependent bias between measured and modeled surface albedo for cloudless and cloudy situations. The strongest effects of the albedo model bias on the net irradiance were most apparent in the presence of optically thin clouds.
Michael Lonardi, Elisa F. Akansu, André Ehrlich, Mauro Mazzola, Christian Pilz, Matthew D. Shupe, Holger Siebert, and Manfred Wendisch
Atmos. Chem. Phys., 24, 1961–1978, https://doi.org/10.5194/acp-24-1961-2024, https://doi.org/10.5194/acp-24-1961-2024, 2024
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Profiles of thermal-infrared irradiance were measured at two Arctic sites. The presence or lack of clouds influences the vertical structure of these observations. In particular, the cloud top region is a source of radiative energy that can promote cooling and mixing in the cloud layer. Simulations are used to further characterize how the amount of water in the cloud modifies this forcing. A case study additionally showcases the evolution of the radiation profiles in a dynamic atmosphere.
Elisa F. Akansu, Sandro Dahlke, Holger Siebert, and Manfred Wendisch
Atmos. Chem. Phys., 23, 15473–15489, https://doi.org/10.5194/acp-23-15473-2023, https://doi.org/10.5194/acp-23-15473-2023, 2023
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The height of the mixing layer is an important measure of the surface-level distribution of energy or other substances. The experimental determination of this height is associated with large uncertainties, particularly under stable conditions that we often find during the polar night or in the presence of clouds. We present a reference method using turbulence measurements on a tethered balloon, which allows us to evaluate approaches based on radiosondes or surface observations.
Marcus Klingebiel, André Ehrlich, Elena Ruiz-Donoso, Nils Risse, Imke Schirmacher, Evelyn Jäkel, Michael Schäfer, Kevin Wolf, Mario Mech, Manuel Moser, Christiane Voigt, and Manfred Wendisch
Atmos. Chem. Phys., 23, 15289–15304, https://doi.org/10.5194/acp-23-15289-2023, https://doi.org/10.5194/acp-23-15289-2023, 2023
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In this study we explain how we use aircraft measurements from two Arctic research campaigns to identify cloud properties (like droplet size) over sea-ice and ice-free ocean. To make sure that our measurements make sense, we compare them with other observations. Our results show, e.g., larger cloud droplets in early summer than in spring. Moreover, the cloud droplets are also larger over ice-free ocean than compared to sea ice. In the future, our data can be used to improve climate models.
Imke Schirmacher, Pavlos Kollias, Katia Lamer, Mario Mech, Lukas Pfitzenmaier, Manfred Wendisch, and Susanne Crewell
Atmos. Meas. Tech., 16, 4081–4100, https://doi.org/10.5194/amt-16-4081-2023, https://doi.org/10.5194/amt-16-4081-2023, 2023
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CloudSat’s relatively coarse spatial resolution, low sensitivity, and blind zone limit its assessment of Arctic low-level clouds, which affect the surface energy balance. We compare cloud fractions from CloudSat and finely resolved airborne radar observations to determine CloudSat’s limitations. Cloudsat overestimates cloud fractions above its blind zone, especially during cold-air outbreaks over open water, and misses a cloud fraction of 32 % and half of the precipitation inside its blind zone.
Olivia Linke, Johannes Quaas, Finja Baumer, Sebastian Becker, Jan Chylik, Sandro Dahlke, André Ehrlich, Dörthe Handorf, Christoph Jacobi, Heike Kalesse-Los, Luca Lelli, Sina Mehrdad, Roel A. J. Neggers, Johannes Riebold, Pablo Saavedra Garfias, Niklas Schnierstein, Matthew D. Shupe, Chris Smith, Gunnar Spreen, Baptiste Verneuil, Kameswara S. Vinjamuri, Marco Vountas, and Manfred Wendisch
Atmos. Chem. Phys., 23, 9963–9992, https://doi.org/10.5194/acp-23-9963-2023, https://doi.org/10.5194/acp-23-9963-2023, 2023
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Lapse rate feedback (LRF) is a major driver of the Arctic amplification (AA) of climate change. It arises because the warming is stronger at the surface than aloft. Several processes can affect the LRF in the Arctic, such as the omnipresent temperature inversion. Here, we compare multimodel climate simulations to Arctic-based observations from a large research consortium to broaden our understanding of these processes, find synergy among them, and constrain the Arctic LRF and AA.
Manfred Wendisch, Johannes Stapf, Sebastian Becker, André Ehrlich, Evelyn Jäkel, Marcus Klingebiel, Christof Lüpkes, Michael Schäfer, and Matthew D. Shupe
Atmos. Chem. Phys., 23, 9647–9667, https://doi.org/10.5194/acp-23-9647-2023, https://doi.org/10.5194/acp-23-9647-2023, 2023
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Atmospheric radiation measurements have been conducted during two field campaigns using research aircraft. The data are analyzed to see if the near-surface air in the Arctic is warmed or cooled if warm–humid air masses from the south enter the Arctic or cold–dry air moves from the north from the Arctic to mid-latitude areas. It is important to study these processes and to check if climate models represent them well. Otherwise it is not possible to reliably forecast the future Arctic climate.
Sophie Rosenburg, Charlotte Lange, Evelyn Jäkel, Michael Schäfer, André Ehrlich, and Manfred Wendisch
Atmos. Meas. Tech., 16, 3915–3930, https://doi.org/10.5194/amt-16-3915-2023, https://doi.org/10.5194/amt-16-3915-2023, 2023
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Snow layer melting and melt pond formation on Arctic sea ice are important seasonal processes affecting the surface reflection and energy budget. Sea ice reflectivity was surveyed by airborne imaging spectrometers in May–June 2017. Adapted retrieval approaches were applied to find snow layer liquid water fraction, snow grain effective radius, and melt pond depth. The retrievals show the potential and limitations of spectral airborne imaging to map melting snow layer and melt pond properties.
Manuel Moser, Christiane Voigt, Tina Jurkat-Witschas, Valerian Hahn, Guillaume Mioche, Olivier Jourdan, Régis Dupuy, Christophe Gourbeyre, Alfons Schwarzenboeck, Johannes Lucke, Yvonne Boose, Mario Mech, Stephan Borrmann, André Ehrlich, Andreas Herber, Christof Lüpkes, and Manfred Wendisch
Atmos. Chem. Phys., 23, 7257–7280, https://doi.org/10.5194/acp-23-7257-2023, https://doi.org/10.5194/acp-23-7257-2023, 2023
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This study provides a comprehensive microphysical and thermodynamic phase analysis of low-level clouds in the northern Fram Strait, above the sea ice and the open ocean, during spring and summer. Using airborne in situ cloud data, we show that the properties of Arctic low-level clouds vary significantly with seasonal meteorological situations and surface conditions. The observations presented in this study can help one to assess the role of clouds in the Arctic climate system.
Sebastian Becker, André Ehrlich, Michael Schäfer, and Manfred Wendisch
Atmos. Chem. Phys., 23, 7015–7031, https://doi.org/10.5194/acp-23-7015-2023, https://doi.org/10.5194/acp-23-7015-2023, 2023
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This study analyses the variability of the warming or cooling effect of clouds on the Arctic surface. Therefore, aircraft radiation measurements were performed over sea ice and open ocean during three seasonally different campaigns. It is found that clouds cool the open-ocean surface most strongly in summer. Over sea ice, clouds warm the surface in spring but have a neutral effect in summer. Due to the variable sea ice extent, clouds warm the surface during spring but cool it during late summer.
Dmitry G. Chechin, Christof Lüpkes, Jörg Hartmann, André Ehrlich, and Manfred Wendisch
Atmos. Chem. Phys., 23, 4685–4707, https://doi.org/10.5194/acp-23-4685-2023, https://doi.org/10.5194/acp-23-4685-2023, 2023
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Clouds represent a very important component of the Arctic climate system, as they strongly reduce the amount of heat lost to space from the sea ice surface. Properties of clouds, as well as their persistence, strongly depend on the complex interaction of such small-scale properties as phase transitions, radiative transfer and turbulence. In this study we use airborne observations to learn more about the effect of clouds and radiative cooling on turbulence in comparison with other factors.
André Ehrlich, Martin Zöger, Andreas Giez, Vladyslav Nenakhov, Christian Mallaun, Rolf Maser, Timo Röschenthaler, Anna E. Luebke, Kevin Wolf, Bjorn Stevens, and Manfred Wendisch
Atmos. Meas. Tech., 16, 1563–1581, https://doi.org/10.5194/amt-16-1563-2023, https://doi.org/10.5194/amt-16-1563-2023, 2023
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Measurements of the broadband radiative energy budget from aircraft are needed to study the effect of clouds, aerosol particles, and surface conditions on the Earth's energy budget. However, the moving aircraft introduces challenges to the instrument performance and post-processing of the data. This study introduces a new radiometer package, outlines a greatly simplifying method to correct thermal offsets, and provides exemplary measurements of solar and thermal–infrared irradiance.
Yunfan Liu, Hang Su, Siwen Wang, Chao Wei, Wei Tao, Mira L. Pöhlker, Christopher Pöhlker, Bruna A. Holanda, Ovid O. Krüger, Thorsten Hoffmann, Manfred Wendisch, Paulo Artaxo, Ulrich Pöschl, Meinrat O. Andreae, and Yafang Cheng
Atmos. Chem. Phys., 23, 251–272, https://doi.org/10.5194/acp-23-251-2023, https://doi.org/10.5194/acp-23-251-2023, 2023
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The origins of the abundant cloud condensation nuclei (CCN) in the upper troposphere (UT) of the Amazon remain unclear. With model developments of new secondary organic aerosol schemes and constrained by observation, we show that strong aerosol nucleation and condensation in the UT is triggered by biogenic organics, and organic condensation is key for UT CCN production. This UT CCN-producing mechanism may prevail over broader vegetation canopies and deserves emphasis in aerosol–climate feedback.
Sebastian Becker, André Ehrlich, Evelyn Jäkel, Tim Carlsen, Michael Schäfer, and Manfred Wendisch
Atmos. Meas. Tech., 15, 2939–2953, https://doi.org/10.5194/amt-15-2939-2022, https://doi.org/10.5194/amt-15-2939-2022, 2022
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Airborne radiation measurements are used to characterize the solar directional reflection of a mixture of Arctic sea ice and open-ocean surfaces in the transition zone between both surface types. The mixture reveals reflection properties of both surface types. It is shown that the directional reflection of the mixture can be reconstructed from the directional reflection of the individual surfaces, accounting for the special conditions present in the transition zone.
Michael Schäfer, Kevin Wolf, André Ehrlich, Christoph Hallbauer, Evelyn Jäkel, Friedhelm Jansen, Anna Elizabeth Luebke, Joshua Müller, Jakob Thoböll, Timo Röschenthaler, Bjorn Stevens, and Manfred Wendisch
Atmos. Meas. Tech., 15, 1491–1509, https://doi.org/10.5194/amt-15-1491-2022, https://doi.org/10.5194/amt-15-1491-2022, 2022
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The new airborne thermal infrared imager VELOX is introduced. It measures two-dimensional fields of spectral thermal infrared radiance or brightness temperature within the large atmospheric window. The technical specifications as well as necessary calibration and correction procedures are presented. Example measurements from the first field deployment are analysed with respect to cloud coverage and cloud top altitude.
Anna E. Luebke, André Ehrlich, Michael Schäfer, Kevin Wolf, and Manfred Wendisch
Atmos. Chem. Phys., 22, 2727–2744, https://doi.org/10.5194/acp-22-2727-2022, https://doi.org/10.5194/acp-22-2727-2022, 2022
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A combination of aircraft and satellite observations is used to show how the characteristics of tropical shallow clouds interact with incoming and outgoing energy. A complete depiction of these clouds is challenging to obtain, but such data are useful for understanding how models can correctly represent them. The amount of cloud is found to be the most important factor, while other cloud characteristics become increasingly impactful when more cloud is present.
Ramon Campos Braga, Barbara Ervens, Daniel Rosenfeld, Meinrat O. Andreae, Jan-David Förster, Daniel Fütterer, Lianet Hernández Pardo, Bruna A. Holanda, Tina Jurkat-Witschas, Ovid O. Krüger, Oliver Lauer, Luiz A. T. Machado, Christopher Pöhlker, Daniel Sauer, Christiane Voigt, Adrian Walser, Manfred Wendisch, Ulrich Pöschl, and Mira L. Pöhlker
Atmos. Chem. Phys., 21, 17513–17528, https://doi.org/10.5194/acp-21-17513-2021, https://doi.org/10.5194/acp-21-17513-2021, 2021
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Interactions of aerosol particles with clouds represent a large uncertainty in estimates of climate change. Properties of aerosol particles control their ability to act as cloud condensation nuclei. Using aerosol measurements in the Amazon, we performed model studies to compare predicted and measured cloud droplet number concentrations at cloud bases. Our results confirm previous estimates of particle hygroscopicity in this region.
Heike Konow, Florian Ewald, Geet George, Marek Jacob, Marcus Klingebiel, Tobias Kölling, Anna E. Luebke, Theresa Mieslinger, Veronika Pörtge, Jule Radtke, Michael Schäfer, Hauke Schulz, Raphaela Vogel, Martin Wirth, Sandrine Bony, Susanne Crewell, André Ehrlich, Linda Forster, Andreas Giez, Felix Gödde, Silke Groß, Manuel Gutleben, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Theresa Lang, Bernhard Mayer, Mario Mech, Marc Prange, Sabrina Schnitt, Jessica Vial, Andreas Walbröl, Manfred Wendisch, Kevin Wolf, Tobias Zinner, Martin Zöger, Felix Ament, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 5545–5563, https://doi.org/10.5194/essd-13-5545-2021, https://doi.org/10.5194/essd-13-5545-2021, 2021
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The German research aircraft HALO took part in the research campaign EUREC4A in January and February 2020. The focus area was the tropical Atlantic east of the island of Barbados. We describe the characteristics of the 15 research flights, provide auxiliary information, derive combined cloud mask products from all instruments that observe clouds on board the aircraft, and provide code examples that help new users of the data to get started.
Ramon Campos Braga, Daniel Rosenfeld, Ovid O. Krüger, Barbara Ervens, Bruna A. Holanda, Manfred Wendisch, Trismono Krisna, Ulrich Pöschl, Meinrat O. Andreae, Christiane Voigt, and Mira L. Pöhlker
Atmos. Chem. Phys., 21, 14079–14088, https://doi.org/10.5194/acp-21-14079-2021, https://doi.org/10.5194/acp-21-14079-2021, 2021
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Quantifying the precipitation within clouds is crucial for our understanding of the Earth's hydrological cycle. Using in situ measurements of cloud and rain properties over the Amazon Basin and Atlantic Ocean, we show here a linear relationship between the effective radius (re) and precipitation water content near the tops of convective clouds for different pollution states and temperature levels. Our results emphasize the role of re to determine both initiation and amount of precipitation.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Linlu Mei, Vladimir Rozanov, Evelyn Jäkel, Xiao Cheng, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2781–2802, https://doi.org/10.5194/tc-15-2781-2021, https://doi.org/10.5194/tc-15-2781-2021, 2021
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This paper presents a new snow property retrieval algorithm from satellite observations. This is Part 2 of two companion papers and shows the results and validation. The paper performs the new retrieval algorithm on the Sea and Land
Surface Temperature Radiometer (SLSTR) instrument and compares the retrieved snow properties with ground-based measurements, aircraft measurements and other satellite products.
Ulrike Egerer, André Ehrlich, Matthias Gottschalk, Hannes Griesche, Roel A. J. Neggers, Holger Siebert, and Manfred Wendisch
Atmos. Chem. Phys., 21, 6347–6364, https://doi.org/10.5194/acp-21-6347-2021, https://doi.org/10.5194/acp-21-6347-2021, 2021
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This paper describes a case study of a three-day period with a persistent humidity inversion above a mixed-phase cloud layer in the Arctic. It is based on measurements with a tethered balloon, complemented with results from a dedicated high-resolution large-eddy simulation. Both methods show that the humidity layer acts to provide moisture to the cloud layer through downward turbulent transport. This supply of additional moisture can contribute to the persistence of Arctic clouds.
Johannes Stapf, André Ehrlich, Christof Lüpkes, and Manfred Wendisch
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-279, https://doi.org/10.5194/acp-2021-279, 2021
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Airborne observations of the surface radiative energy budget in the marginal sea ice zone (the region between open ocean and closed sea ice) are presented. Atmospheric thermodynamic profiles and surface properties change on small spatial scales in this area and influence the impact of clouds on the radiative energy budget. The radiation budget over sea ice is compared to available studies in the Arctic and the influence of cold air outbreaks and warm air intrusions is illustrated.
Evelyn Jäkel, Tim Carlsen, André Ehrlich, Manfred Wendisch, Michael Schäfer, Sophie Rosenburg, Konstantina Nakoudi, Marco Zanatta, Gerit Birnbaum, Veit Helm, Andreas Herber, Larysa Istomina, Linlu Mei, and Anika Rohde
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-14, https://doi.org/10.5194/tc-2021-14, 2021
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Different approaches to retrieve the optical-equivalent snow grain size using satellite, airborne, and ground-based observations were evaluated and compared to modeled data. The study is focused on low Sun and partly rough surface conditions encountered North of Greenland in March/April 2018. We proposed an adjusted airborne retrieval method to reduce the retrieval uncertainty.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
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Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Tim Carlsen, Gerit Birnbaum, André Ehrlich, Veit Helm, Evelyn Jäkel, Michael Schäfer, and Manfred Wendisch
The Cryosphere, 14, 3959–3978, https://doi.org/10.5194/tc-14-3959-2020, https://doi.org/10.5194/tc-14-3959-2020, 2020
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The angular reflection of solar radiation by snow surfaces is particularly anisotropic and highly variable. We measured the angular reflection from an aircraft using a digital camera in Antarctica in 2013/14 and studied its variability: the anisotropy increases with a lower Sun but decreases for rougher surfaces and larger snow grains. The applied methodology allows for a direct comparison with satellite observations, which generally underestimated the anisotropy measured within this study.
Jan Kretzschmar, Johannes Stapf, Daniel Klocke, Manfred Wendisch, and Johannes Quaas
Atmos. Chem. Phys., 20, 13145–13165, https://doi.org/10.5194/acp-20-13145-2020, https://doi.org/10.5194/acp-20-13145-2020, 2020
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This study compares simulations with the ICON model at the kilometer scale to airborne radiation and cloud microphysics observations that have been derived during the ACLOUD aircraft campaign around Svalbard, Norway, in May/June 2017. We find an overestimated surface warming effect of clouds compared to the observations in our setup. This bias was reduced by considering subgrid-scale vertical motion in the activation of cloud condensation nuclei in the two-moment microphysical scheme used.
Li Li, Zhengqiang Li, Wenyuan Chang, Yang Ou, Philippe Goloub, Chengzhe Li, Kaitao Li, Qiaoyun Hu, Jianping Wang, and Manfred Wendisch
Atmos. Chem. Phys., 20, 10845–10864, https://doi.org/10.5194/acp-20-10845-2020, https://doi.org/10.5194/acp-20-10845-2020, 2020
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Dust Aerosol Observation-Kashi (DAO-K) campaign was conducted near the Taklimakan Desert in April 2019 to obtain comprehensive aerosol, atmosphere, and surface parameters. Estimations of aerosol solar radiative forcing by a radiative transfer (RT) model were improved based on the measured aerosol parameters, additionally considering atmospheric profiles and diurnal variations of surface albedo. RT simulations agree well with simultaneous irradiance observations, even in dust-polluted conditions.
Johannes Stapf, André Ehrlich, Evelyn Jäkel, Christof Lüpkes, and Manfred Wendisch
Atmos. Chem. Phys., 20, 9895–9914, https://doi.org/10.5194/acp-20-9895-2020, https://doi.org/10.5194/acp-20-9895-2020, 2020
Tobias Donth, Evelyn Jäkel, André Ehrlich, Bernd Heinold, Jacob Schacht, Andreas Herber, Marco Zanatta, and Manfred Wendisch
Atmos. Chem. Phys., 20, 8139–8156, https://doi.org/10.5194/acp-20-8139-2020, https://doi.org/10.5194/acp-20-8139-2020, 2020
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Solar radiative effects of Arctic black carbon (BC) particles (suspended in the atmosphere and in the surface snowpack) were quantified under cloudless and cloudy conditions. An atmospheric and a snow radiative transfer model were coupled to account for radiative interactions between both compartments. It was found that (i) the warming effect of BC in the snowpack overcompensates for the atmospheric BC cooling effect, and (ii) clouds tend to reduce the atmospheric BC cooling and snow BC warming.
Elena Ruiz-Donoso, André Ehrlich, Michael Schäfer, Evelyn Jäkel, Vera Schemann, Susanne Crewell, Mario Mech, Birte Solveig Kulla, Leif-Leonard Kliesch, Roland Neuber, and Manfred Wendisch
Atmos. Chem. Phys., 20, 5487–5511, https://doi.org/10.5194/acp-20-5487-2020, https://doi.org/10.5194/acp-20-5487-2020, 2020
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Mixed-phase clouds, formed of water droplets and ice crystals, appear frequently in Arctic regions. Characterizing the distribution of liquid water and ice inside the cloud appropriately is important because it influences the cloud's impact on the surface temperature. In this study, we combined images of the cloud top with measurements inside the cloud to analyze in detail the 3D spatial distribution of liquid and ice in two mixed-phase clouds occurring under different meteorological scenarios.
Bruna A. Holanda, Mira L. Pöhlker, David Walter, Jorge Saturno, Matthias Sörgel, Jeannine Ditas, Florian Ditas, Christiane Schulz, Marco Aurélio Franco, Qiaoqiao Wang, Tobias Donth, Paulo Artaxo, Henrique M. J. Barbosa, Stephan Borrmann, Ramon Braga, Joel Brito, Yafang Cheng, Maximilian Dollner, Johannes W. Kaiser, Thomas Klimach, Christoph Knote, Ovid O. Krüger, Daniel Fütterer, Jošt V. Lavrič, Nan Ma, Luiz A. T. Machado, Jing Ming, Fernando G. Morais, Hauke Paulsen, Daniel Sauer, Hans Schlager, Johannes Schneider, Hang Su, Bernadett Weinzierl, Adrian Walser, Manfred Wendisch, Helmut Ziereis, Martin Zöger, Ulrich Pöschl, Meinrat O. Andreae, and Christopher Pöhlker
Atmos. Chem. Phys., 20, 4757–4785, https://doi.org/10.5194/acp-20-4757-2020, https://doi.org/10.5194/acp-20-4757-2020, 2020
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Biomass burning smoke from African savanna and grassland is transported across the South Atlantic Ocean in defined layers within the free troposphere. The combination of in situ aircraft and ground-based measurements aided by satellite observations showed that these layers are transported into the Amazon Basin during the early dry season. The influx of aged smoke, enriched in black carbon and cloud condensation nuclei, has important implications for the Amazonian aerosol and cloud cycling.
Fan Mei, Jian Wang, Jennifer M. Comstock, Ralf Weigel, Martina Krämer, Christoph Mahnke, John E. Shilling, Johannes Schneider, Christiane Schulz, Charles N. Long, Manfred Wendisch, Luiz A. T. Machado, Beat Schmid, Trismono Krisna, Mikhail Pekour, John Hubbe, Andreas Giez, Bernadett Weinzierl, Martin Zoeger, Mira L. Pöhlker, Hans Schlager, Micael A. Cecchini, Meinrat O. Andreae, Scot T. Martin, Suzane S. de Sá, Jiwen Fan, Jason Tomlinson, Stephen Springston, Ulrich Pöschl, Paulo Artaxo, Christopher Pöhlker, Thomas Klimach, Andreas Minikin, Armin Afchine, and Stephan Borrmann
Atmos. Meas. Tech., 13, 661–684, https://doi.org/10.5194/amt-13-661-2020, https://doi.org/10.5194/amt-13-661-2020, 2020
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In 2014, the US DOE G1 aircraft and the German HALO aircraft overflew the Amazon basin to study how aerosols influence cloud cycles under a clean condition and around a tropical megacity. This paper describes how to meaningfully compare similar measurements from two research aircraft and identify the potential measurement issue. We also discuss the uncertainty range for each measurement for further usage in model evaluation and satellite data validation.
Pascal Polonik, Christoph Knote, Tobias Zinner, Florian Ewald, Tobias Kölling, Bernhard Mayer, Meinrat O. Andreae, Tina Jurkat-Witschas, Thomas Klimach, Christoph Mahnke, Sergej Molleker, Christopher Pöhlker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, Christiane Voigt, Ralf Weigel, and Manfred Wendisch
Atmos. Chem. Phys., 20, 1591–1605, https://doi.org/10.5194/acp-20-1591-2020, https://doi.org/10.5194/acp-20-1591-2020, 2020
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A realistic representation of cloud–aerosol interactions is central to accurate climate projections. Here we combine observations collected during the ACRIDICON-CHUVA campaign with chemistry-transport simulations to evaluate the model’s ability to represent the indirect effects of biomass burning aerosol on cloud microphysics. We find an upper limit for the model sensitivity on cloud condensation nuclei concentrations well below the levels reached during the burning season in the Amazon Basin.
Christine Pohl, Larysa Istomina, Steffen Tietsche, Evelyn Jäkel, Johannes Stapf, Gunnar Spreen, and Georg Heygster
The Cryosphere, 14, 165–182, https://doi.org/10.5194/tc-14-165-2020, https://doi.org/10.5194/tc-14-165-2020, 2020
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A spectral to broadband conversion is developed empirically that can be used in combination with the Melt Pond Detector algorithm to derive broadband albedo (300–3000 nm) of Arctic sea ice from MERIS data. It is validated and shows better performance compared to existing conversion methods. A comparison of MERIS broadband albedo with respective values from ERA5 reanalysis suggests a revision of the albedo values used in ERA5. MERIS albedo might be useful for improving albedo representation.
André Ehrlich, Manfred Wendisch, Christof Lüpkes, Matthias Buschmann, Heiko Bozem, Dmitri Chechin, Hans-Christian Clemen, Régis Dupuy, Olliver Eppers, Jörg Hartmann, Andreas Herber, Evelyn Jäkel, Emma Järvinen, Olivier Jourdan, Udo Kästner, Leif-Leonard Kliesch, Franziska Köllner, Mario Mech, Stephan Mertes, Roland Neuber, Elena Ruiz-Donoso, Martin Schnaiter, Johannes Schneider, Johannes Stapf, and Marco Zanatta
Earth Syst. Sci. Data, 11, 1853–1881, https://doi.org/10.5194/essd-11-1853-2019, https://doi.org/10.5194/essd-11-1853-2019, 2019
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During the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign, two research aircraft (Polar 5 and 6) jointly performed 22 research flights over the transition zone between open ocean and closed sea ice. The data set combines remote sensing and in situ measurement of cloud, aerosol, and trace gas properties, as well as turbulent and radiative fluxes, which will be used to study Arctic boundary layer and mid-level clouds and their role in Arctic amplification.
Ulrike Egerer, Matthias Gottschalk, Holger Siebert, André Ehrlich, and Manfred Wendisch
Atmos. Meas. Tech., 12, 4019–4038, https://doi.org/10.5194/amt-12-4019-2019, https://doi.org/10.5194/amt-12-4019-2019, 2019
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In this study, we introduce the new tethered balloon system BELUGA, which includes different modular instrument packages for measuring turbulence and radiation in the atmospheric boundary layer. BELUGA was deployed in an Arctic field campaign in 2017, providing details of boundary layer processes in combination with low-level clouds. Those processes are still not fully understood and in situ measurements in the Arctic improve our understanding of the Arctic response in terms of global warming.
Evelyn Jäkel, Johannes Stapf, Manfred Wendisch, Marcel Nicolaus, Wolfgang Dorn, and Annette Rinke
The Cryosphere, 13, 1695–1708, https://doi.org/10.5194/tc-13-1695-2019, https://doi.org/10.5194/tc-13-1695-2019, 2019
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The sea ice surface albedo parameterization of a coupled regional climate model was validated against aircraft measurements performed in May–June 2017 north of Svalbard. The albedo parameterization was run offline from the model using the measured parameters surface temperature and snow depth to calculate the surface albedo and the individual fractions of the ice surface subtypes. An adjustment of the variables and additionally accounting for cloud cover reduced the root-mean-squared error.
Kevin Wolf, André Ehrlich, Marek Jacob, Susanne Crewell, Martin Wirth, and Manfred Wendisch
Atmos. Meas. Tech., 12, 1635–1658, https://doi.org/10.5194/amt-12-1635-2019, https://doi.org/10.5194/amt-12-1635-2019, 2019
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Using passive spectral solar radiation and active lidar, radar, and microwave measurements with HALO during NARVAL-II, the cloud droplet number concentration of shallow trade wind cumulus is estimated. With stepwise inclusion of the different instruments into the retrieval, the benefits of the synergetic approach based on artificial measurements and two cloud cases are demonstrated. Significant improvement with the synergetic method compared to the solar-radiation-only method is reported.
Tobias Zinner, Ulrich Schwarz, Tobias Kölling, Florian Ewald, Evelyn Jäkel, Bernhard Mayer, and Manfred Wendisch
Atmos. Meas. Tech., 12, 1167–1181, https://doi.org/10.5194/amt-12-1167-2019, https://doi.org/10.5194/amt-12-1167-2019, 2019
Erlend M. Knudsen, Bernd Heinold, Sandro Dahlke, Heiko Bozem, Susanne Crewell, Irina V. Gorodetskaya, Georg Heygster, Daniel Kunkel, Marion Maturilli, Mario Mech, Carolina Viceto, Annette Rinke, Holger Schmithüsen, André Ehrlich, Andreas Macke, Christof Lüpkes, and Manfred Wendisch
Atmos. Chem. Phys., 18, 17995–18022, https://doi.org/10.5194/acp-18-17995-2018, https://doi.org/10.5194/acp-18-17995-2018, 2018
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The paper describes the synoptic development during the ACLOUD/PASCAL airborne and ship-based field campaign near Svalbard in spring 2017. This development is presented using near-surface and upperair meteorological observations, satellite, and model data. We first present time series of these data, from which we identify and characterize three key periods. Finally, we put our observations in historical and regional contexts and compare our findings to other Arctic field campaigns.
Emma Järvinen, Olivier Jourdan, David Neubauer, Bin Yao, Chao Liu, Meinrat O. Andreae, Ulrike Lohmann, Manfred Wendisch, Greg M. McFarquhar, Thomas Leisner, and Martin Schnaiter
Atmos. Chem. Phys., 18, 15767–15781, https://doi.org/10.5194/acp-18-15767-2018, https://doi.org/10.5194/acp-18-15767-2018, 2018
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Using light diffraction it is possible to detect microscopic features within ice particles that have not yet been fully characterized. Here, this technique was applied in airborne measurements, where it was found that majority of atmospheric ice particles have features that significantly change the way ice particles interact with solar light. The microscopic features make ice-containing clouds more reflective than previously thought, which could have consequences for predicting our climate.
Christiane Schulz, Johannes Schneider, Bruna Amorim Holanda, Oliver Appel, Anja Costa, Suzane S. de Sá, Volker Dreiling, Daniel Fütterer, Tina Jurkat-Witschas, Thomas Klimach, Christoph Knote, Martina Krämer, Scot T. Martin, Stephan Mertes, Mira L. Pöhlker, Daniel Sauer, Christiane Voigt, Adrian Walser, Bernadett Weinzierl, Helmut Ziereis, Martin Zöger, Meinrat O. Andreae, Paulo Artaxo, Luiz A. T. Machado, Ulrich Pöschl, Manfred Wendisch, and Stephan Borrmann
Atmos. Chem. Phys., 18, 14979–15001, https://doi.org/10.5194/acp-18-14979-2018, https://doi.org/10.5194/acp-18-14979-2018, 2018
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Aerosol chemical composition measurements in the tropical upper troposphere over the Amazon region show that 78 % of the aerosol in the upper troposphere consists of organic matter. Up to 20 % of the organic aerosol can be attributed to isoprene epoxydiol secondary organic aerosol (IEPOX-SOA). Furthermore, organic nitrates were identified, suggesting a connection to the IEPOX-SOA formation.
Michael Schäfer, Katharina Loewe, André Ehrlich, Corinna Hoose, and Manfred Wendisch
Atmos. Chem. Phys., 18, 13115–13133, https://doi.org/10.5194/acp-18-13115-2018, https://doi.org/10.5194/acp-18-13115-2018, 2018
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Airborne observed horizontal fields of cloud optical thickness are compared with semi-idealized large eddy simulations of Arctic stratus. The comparison focuses on horizontal cloud inhomogeneities and directional features of the small-scale cloud structures. Using inhomogeneity parameters and autocorrelation analysis it is investigated, if the observed small-scale cloud inhomogeneities can be represented by the model. Forcings for cloud inhomogeneities are investigated in a sensitivity study.
Jorge Saturno, Florian Ditas, Marloes Penning de Vries, Bruna A. Holanda, Mira L. Pöhlker, Samara Carbone, David Walter, Nicole Bobrowski, Joel Brito, Xuguang Chi, Alexandra Gutmann, Isabella Hrabe de Angelis, Luiz A. T. Machado, Daniel Moran-Zuloaga, Julian Rüdiger, Johannes Schneider, Christiane Schulz, Qiaoqiao Wang, Manfred Wendisch, Paulo Artaxo, Thomas Wagner, Ulrich Pöschl, Meinrat O. Andreae, and Christopher Pöhlker
Atmos. Chem. Phys., 18, 10391–10405, https://doi.org/10.5194/acp-18-10391-2018, https://doi.org/10.5194/acp-18-10391-2018, 2018
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This study uses satellite observations to track volcanic emissions in eastern Congo and their subsequent transport across the Atlantic Ocean into the Amazon Basin. Aircraft and ground-based observations are used to characterize the influence of volcanogenic aerosol on the chemical and microphysical properties of Amazonian aerosols. Further, this work is an illustrative example of the conditions and dynamics driving the transatlantic transport of African emissions to South America.
Luiz A. T. Machado, Alan J. P. Calheiros, Thiago Biscaro, Scott Giangrande, Maria A. F. Silva Dias, Micael A. Cecchini, Rachel Albrecht, Meinrat O. Andreae, Wagner F. Araujo, Paulo Artaxo, Stephan Borrmann, Ramon Braga, Casey Burleyson, Cristiano W. Eichholz, Jiwen Fan, Zhe Feng, Gilberto F. Fisch, Michael P. Jensen, Scot T. Martin, Ulrich Pöschl, Christopher Pöhlker, Mira L. Pöhlker, Jean-François Ribaud, Daniel Rosenfeld, Jaci M. B. Saraiva, Courtney Schumacher, Ryan Thalman, David Walter, and Manfred Wendisch
Atmos. Chem. Phys., 18, 6461–6482, https://doi.org/10.5194/acp-18-6461-2018, https://doi.org/10.5194/acp-18-6461-2018, 2018
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This overview discuss the main precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin. It presents a review of the knowledge acquired about cloud processes and rainfall formation in Amazonas. In addition, this study provides a characterization of the seasonal variation and rainfall sensitivities to topography, surface cover, and aerosol concentration. Airplane measurements were evaluated to characterize and contrast cloud microphysical properties.
Trismono C. Krisna, Manfred Wendisch, André Ehrlich, Evelyn Jäkel, Frank Werner, Ralf Weigel, Stephan Borrmann, Christoph Mahnke, Ulrich Pöschl, Meinrat O. Andreae, Christiane Voigt, and Luiz A. T. Machado
Atmos. Chem. Phys., 18, 4439–4462, https://doi.org/10.5194/acp-18-4439-2018, https://doi.org/10.5194/acp-18-4439-2018, 2018
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The optical thickness and particle effective radius of a cirrus above liquid water clouds and a DCC topped by an anvil cirrus are retrieved based on SMART and MODIS radiance measurements. For the cirrus, retrieved particle effective radius are validated with corresponding in situ data using a vertical weighting method. This approach allows to assess the measurements, retrieval algorithms, and derived cloud products.
Meinrat O. Andreae, Armin Afchine, Rachel Albrecht, Bruna Amorim Holanda, Paulo Artaxo, Henrique M. J. Barbosa, Stephan Borrmann, Micael A. Cecchini, Anja Costa, Maximilian Dollner, Daniel Fütterer, Emma Järvinen, Tina Jurkat, Thomas Klimach, Tobias Konemann, Christoph Knote, Martina Krämer, Trismono Krisna, Luiz A. T. Machado, Stephan Mertes, Andreas Minikin, Christopher Pöhlker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, Daniel Sauer, Hans Schlager, Martin Schnaiter, Johannes Schneider, Christiane Schulz, Antonio Spanu, Vinicius B. Sperling, Christiane Voigt, Adrian Walser, Jian Wang, Bernadett Weinzierl, Manfred Wendisch, and Helmut Ziereis
Atmos. Chem. Phys., 18, 921–961, https://doi.org/10.5194/acp-18-921-2018, https://doi.org/10.5194/acp-18-921-2018, 2018
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We made airborne measurements of aerosol particle concentrations and properties over the Amazon Basin. We found extremely high concentrations of very small particles in the region between 8 and 14 km altitude all across the basin, which had been recently formed by gas-to-particle conversion at these altitudes. This makes the upper troposphere a very important source region of atmospheric particles with significant implications for the Earth's climate system.
Micael A. Cecchini, Luiz A. T. Machado, Manfred Wendisch, Anja Costa, Martina Krämer, Meinrat O. Andreae, Armin Afchine, Rachel I. Albrecht, Paulo Artaxo, Stephan Borrmann, Daniel Fütterer, Thomas Klimach, Christoph Mahnke, Scot T. Martin, Andreas Minikin, Sergej Molleker, Lianet H. Pardo, Christopher Pöhlker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, and Bernadett Weinzierl
Atmos. Chem. Phys., 17, 14727–14746, https://doi.org/10.5194/acp-17-14727-2017, https://doi.org/10.5194/acp-17-14727-2017, 2017
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This study introduces and explores the concept of gamma phase space. This space is able to represent all possible variations in the cloud droplet size distributions (DSDs). The methodology was applied to recent in situ aircraft measurements over the Amazon. It is shown that the phase space is able to represent several processes occurring in the clouds in a simple manner. The consequences for cloud studies, modeling, and the representation of the transition from warm to mixed phase are discussed.
Ramon Campos Braga, Daniel Rosenfeld, Ralf Weigel, Tina Jurkat, Meinrat O. Andreae, Manfred Wendisch, Ulrich Pöschl, Christiane Voigt, Christoph Mahnke, Stephan Borrmann, Rachel I. Albrecht, Sergej Molleker, Daniel A. Vila, Luiz A. T. Machado, and Lucas Grulich
Atmos. Chem. Phys., 17, 14433–14456, https://doi.org/10.5194/acp-17-14433-2017, https://doi.org/10.5194/acp-17-14433-2017, 2017
Tim Carlsen, Gerit Birnbaum, André Ehrlich, Johannes Freitag, Georg Heygster, Larysa Istomina, Sepp Kipfstuhl, Anaïs Orsi, Michael Schäfer, and Manfred Wendisch
The Cryosphere, 11, 2727–2741, https://doi.org/10.5194/tc-11-2727-2017, https://doi.org/10.5194/tc-11-2727-2017, 2017
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The optical size of snow grains (ropt) affects the reflectivity of snow surfaces and thus the local surface energy budget in particular in polar regions. The temporal evolution of ropt retrieved from ground-based, airborne, and spaceborne remote sensing could reproduce optical in situ measurements for a 2-month period in central Antarctica (2013/14). The presented validation study provided a unique testbed for retrievals of ropt under Antarctic conditions where in situ data are scarce.
Anja Costa, Jessica Meyer, Armin Afchine, Anna Luebke, Gebhard Günther, James R. Dorsey, Martin W. Gallagher, Andre Ehrlich, Manfred Wendisch, Darrel Baumgardner, Heike Wex, and Martina Krämer
Atmos. Chem. Phys., 17, 12219–12238, https://doi.org/10.5194/acp-17-12219-2017, https://doi.org/10.5194/acp-17-12219-2017, 2017
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The paper presents 38 h of in situ cloud spectrometer observations of microphysical cloud properties in the Arctic, midlatitudes and tropics. The clouds are classified via particle concentrations, size distributions, and – as a novelty – small particle aspherical fractions. Cloud-type profiles are given for different temperatures and locations. The results confine regions where different cloud transformation processes occurred and emphasise the importance of small particle shape detection.
Marcus Klingebiel, André Ehrlich, Fanny Finger, Timo Röschenthaler, Suad Jakirlić, Matthias Voigt, Stefan Müller, Rolf Maser, Manfred Wendisch, Peter Hoor, Peter Spichtinger, and Stephan Borrmann
Atmos. Meas. Tech., 10, 3485–3498, https://doi.org/10.5194/amt-10-3485-2017, https://doi.org/10.5194/amt-10-3485-2017, 2017
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Microphysical and radiation measurements were collected with the unique AIRcraft TOwed Sensor Shuttle (AIRTOSS) – Learjet tandem platform. It is a combination of a Learjet 35A research aircraft and an instrumented aerodynamic bird, which can be detached from and retracted back to the aircraft during flight.
AIRTOSS and Learjet are equipped with radiative, cloud microphysical, trace gas,
and meteorological instruments to study cirrus clouds.
André Ehrlich, Eike Bierwirth, Larysa Istomina, and Manfred Wendisch
Atmos. Meas. Tech., 10, 3215–3230, https://doi.org/10.5194/amt-10-3215-2017, https://doi.org/10.5194/amt-10-3215-2017, 2017
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In the Arctic, uncertainties in passive solar remote sensing of cloud properties arise from uncertainties in the assumed spectral surface albedo, mainly determined by the generally unknown effective snow grain size. Therefore, a retrieval method is presented that simultaneously derives liquid water cloud and snow surface parameters, including cloud optical thickness, droplet effective radius, and effective snow grain size. Airborne measurements were used to test the retrieval procedure.
Micael A. Cecchini, Luiz A. T. Machado, Meinrat O. Andreae, Scot T. Martin, Rachel I. Albrecht, Paulo Artaxo, Henrique M. J. Barbosa, Stephan Borrmann, Daniel Fütterer, Tina Jurkat, Christoph Mahnke, Andreas Minikin, Sergej Molleker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, Christiane Voigt, Bernadett Weinzierl, and Manfred Wendisch
Atmos. Chem. Phys., 17, 10037–10050, https://doi.org/10.5194/acp-17-10037-2017, https://doi.org/10.5194/acp-17-10037-2017, 2017
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We study the effects of aerosol particles and updraft speed on the warm phase of Amazonian clouds. We expand the sensitivity analysis usually found in the literature by concomitantly considering cloud evolution and the effects on droplet size distribution (DSD) shape. The quantitative results show that particle concentration is the primary driver for the vertical profiles of effective diameter and droplet concentration in the warm phase of Amazonian convective clouds.
Evelyn Jäkel, Manfred Wendisch, Trismono C. Krisna, Florian Ewald, Tobias Kölling, Tina Jurkat, Christiane Voigt, Micael A. Cecchini, Luiz A. T. Machado, Armin Afchine, Anja Costa, Martina Krämer, Meinrat O. Andreae, Ulrich Pöschl, Daniel Rosenfeld, and Tianle Yuan
Atmos. Chem. Phys., 17, 9049–9066, https://doi.org/10.5194/acp-17-9049-2017, https://doi.org/10.5194/acp-17-9049-2017, 2017
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Vertical profiles of the cloud particle phase state in tropical deep convective clouds (DCCs) were investigated using airborne imaging spectrometer measurements during the ACRIDICON-CHUVA campaign, which was conducted over the Brazilian rainforest in September 2014. A phase discrimination retrieval was applied to observations of clouds formed in different aerosol conditions. The profiles were compared to in situ and satellite measurements.
Ramon Campos Braga, Daniel Rosenfeld, Ralf Weigel, Tina Jurkat, Meinrat O. Andreae, Manfred Wendisch, Mira L. Pöhlker, Thomas Klimach, Ulrich Pöschl, Christopher Pöhlker, Christiane Voigt, Christoph Mahnke, Stephan Borrmann, Rachel I. Albrecht, Sergej Molleker, Daniel A. Vila, Luiz A. T. Machado, and Paulo Artaxo
Atmos. Chem. Phys., 17, 7365–7386, https://doi.org/10.5194/acp-17-7365-2017, https://doi.org/10.5194/acp-17-7365-2017, 2017
Kevin Wolf, André Ehrlich, Tilman Hüneke, Klaus Pfeilsticker, Frank Werner, Martin Wirth, and Manfred Wendisch
Atmos. Chem. Phys., 17, 4283–4303, https://doi.org/10.5194/acp-17-4283-2017, https://doi.org/10.5194/acp-17-4283-2017, 2017
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The potential of airborne radiance measurements in the sideward and nadir directions for cirrus remote sensing is investigated. Therefore radiative transfer simulations were used and the sensitivity of upward radiance with respect to optical thickness, effective radius, surface albedo, wavelength and viewing angle was studied. It was shown that sideward observations lead to more accurate retrieval results. Investigating a case study of ML-CIRRUS, these findings are confirmed.
Michael Schäfer, Eike Bierwirth, André Ehrlich, Evelyn Jäkel, Frank Werner, and Manfred Wendisch
Atmos. Chem. Phys., 17, 2359–2372, https://doi.org/10.5194/acp-17-2359-2017, https://doi.org/10.5194/acp-17-2359-2017, 2017
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Cloud optical thickness fields, retrieved from solar spectral radiance measurements, are used to investigate the directional structure of horizontal cloud inhomogeneities with scalar one-dimensional inhomogeneity parameters, two-dimensional auto-correlation functions, and two-dimensional Fourier analysis. The investigations reveal that it is not sufficient to quantify horizontal cloud inhomogeneities by one-dimensional inhomogeneity parameters; two-dimensional parameters are necessary.
Fanny Finger, Frank Werner, Marcus Klingebiel, André Ehrlich, Evelyn Jäkel, Matthias Voigt, Stephan Borrmann, Peter Spichtinger, and Manfred Wendisch
Atmos. Chem. Phys., 16, 7681–7693, https://doi.org/10.5194/acp-16-7681-2016, https://doi.org/10.5194/acp-16-7681-2016, 2016
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Solar spectra of optical layer properties of cirrus have been derived from the first truly collocated airborne radiation measurements using an aircraft and a towed sensor platform. The measured layer properties differ slightly due to horizontal cirrus inhomogeneities and the influence of low-level water clouds. Applying a 1-D radiative transfer model sensitivity studies were performed. It was found that if a low-level cloud is not considered, the solar cooling of the cirrus is strongly overestimated.
S. T. Martin, P. Artaxo, L. A. T. Machado, A. O. Manzi, R. A. F. Souza, C. Schumacher, J. Wang, M. O. Andreae, H. M. J. Barbosa, J. Fan, G. Fisch, A. H. Goldstein, A. Guenther, J. L. Jimenez, U. Pöschl, M. A. Silva Dias, J. N. Smith, and M. Wendisch
Atmos. Chem. Phys., 16, 4785–4797, https://doi.org/10.5194/acp-16-4785-2016, https://doi.org/10.5194/acp-16-4785-2016, 2016
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The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment took place in central Amazonia throughout 2014 and 2015. The experiment focused on the complex links among vegetation, atmospheric chemistry, and aerosol production on the one hand and their connections to aerosols, clouds, and precipitation on the other, especially when altered by urban pollution. This article serves as an introduction to the special issue of publications presenting findings of this experiment.
E. Jäkel, B. Mey, R. Levy, X. Gu, T. Yu, Z. Li, D. Althausen, B. Heese, and M. Wendisch
Atmos. Meas. Tech., 8, 5237–5249, https://doi.org/10.5194/amt-8-5237-2015, https://doi.org/10.5194/amt-8-5237-2015, 2015
A. Ehrlich and M. Wendisch
Atmos. Meas. Tech., 8, 3671–3684, https://doi.org/10.5194/amt-8-3671-2015, https://doi.org/10.5194/amt-8-3671-2015, 2015
M. Schäfer, E. Bierwirth, A. Ehrlich, E. Jäkel, and M. Wendisch
Atmos. Chem. Phys., 15, 8147–8163, https://doi.org/10.5194/acp-15-8147-2015, https://doi.org/10.5194/acp-15-8147-2015, 2015
M. Klingebiel, A. de Lozar, S. Molleker, R. Weigel, A. Roth, L. Schmidt, J. Meyer, A. Ehrlich, R. Neuber, M. Wendisch, and S. Borrmann
Atmos. Chem. Phys., 15, 617–631, https://doi.org/10.5194/acp-15-617-2015, https://doi.org/10.5194/acp-15-617-2015, 2015
C. Fricke, A. Ehrlich, E. Jäkel, B. Bohn, M. Wirth, and M. Wendisch
Atmos. Chem. Phys., 14, 1943–1958, https://doi.org/10.5194/acp-14-1943-2014, https://doi.org/10.5194/acp-14-1943-2014, 2014
M. Schäfer, E. Bierwirth, A. Ehrlich, F. Heyner, and M. Wendisch
Atmos. Meas. Tech., 6, 1855–1868, https://doi.org/10.5194/amt-6-1855-2013, https://doi.org/10.5194/amt-6-1855-2013, 2013
E. Bierwirth, A. Ehrlich, M. Wendisch, J.-F. Gayet, C. Gourbeyre, R. Dupuy, A. Herber, R. Neuber, and A. Lampert
Atmos. Meas. Tech., 6, 1189–1200, https://doi.org/10.5194/amt-6-1189-2013, https://doi.org/10.5194/amt-6-1189-2013, 2013
E. Jäkel, M. Wendisch, and B. Mayer
Atmos. Meas. Tech., 6, 527–537, https://doi.org/10.5194/amt-6-527-2013, https://doi.org/10.5194/amt-6-527-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
PEAKO and peakTree: tools for detecting and interpreting peaks in cloud radar Doppler spectra – capabilities and limitations
An advanced spatial coregistration of cloud properties for the atmospheric Sentinel missions: application to TROPOMI
Contrail altitude estimation using GOES-16 ABI data and deep learning
The Ice Cloud Imager: retrieval of frozen water column properties
Supercooled liquid water cloud classification using lidar backscatter peak properties
Marine cloud base height retrieval from MODIS cloud properties using machine learning
How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties
ampycloud: an open-source algorithm to determine cloud base heights and sky coverage fractions from ceilometer data
Simulation and detection efficiency analysis for measurements of polar mesospheric clouds using a spaceborne wide-field-of-view ultraviolet imager
The Chalmers Cloud Ice Climatology: retrieval implementation and validation
The algorithm of microphysical-parameter profiles of aerosol and small cloud droplets based on the dual-wavelength lidar data
Dual-frequency (Ka-band and G-band) radar estimates of liquid water content profiles in shallow clouds
Bayesian cloud-top phase determination for Meteosat Second Generation
Lidar–radar synergistic method to retrieve ice, supercooled water and mixed-phase cloud properties
Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements
A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations
Using machine learning algorithm to retrieve cloud fraction based on FY-4A AGRI observations
Identification of ice-over-water multilayer clouds using multispectral satellite data in an artificial neural network
A new approach to crystal habit retrieval from far-infrared spectral radiance measurements
Severe hail detection with C-band dual-polarisation radars using convolutional neural networks
Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds
Optimal estimation of cloud properties from thermal infrared observations with a combination of deep learning and radiative transfer simulation
Retrieval of cloud fraction and optical thickness from multi-angle polarization observations
Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI
A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations
Infrared Radiometric Image Classification and Segmentation of Cloud Structure Using Deep-learning Framework for Ground-based Infrared Thermal Camera Observations
Geometrical and optical properties of cirrus clouds in Barcelona, Spain: analysis with the two-way transmittance method of 4 years of lidar measurements
Determination of the vertical distribution of in-cloud particle shape using SLDR-mode 35 GHz scanning cloud radar
Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data
The EarthCARE mission: science data processing chain overview
3-D Cloud Masking Across a Broad Swath using Multi-angle Polarimetry and Deep Learning
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products
Raman lidar-derived optical and microphysical properties of ice crystals within thin Arctic clouds during PARCS campaign
Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements
Deep convective cloud system size and structure across the global tropics and subtropics
A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images
Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system
Segmentation of polarimetric radar imagery using statistical texture
Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization
Particle inertial effects on radar Doppler spectra simulation
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data
Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS
Global evaluation of Doppler velocity errors of EarthCARE cloud-profiling radar using a global storm-resolving simulation
Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product
Teresa Vogl, Martin Radenz, Fabiola Ramelli, Rosa Gierens, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 6547–6568, https://doi.org/10.5194/amt-17-6547-2024, https://doi.org/10.5194/amt-17-6547-2024, 2024
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In this study, we present a toolkit of two Python algorithms to extract information from Doppler spectra measured by ground-based cloud radars. In these Doppler spectra, several peaks can be formed due to populations of droplets/ice particles with different fall velocities coexisting in the same measurement time and height. The two algorithms can detect peaks and assign them to certain particle types, such as small cloud droplets or fast-falling ice particles like graupel.
Athina Argyrouli, Diego Loyola, Fabian Romahn, Ronny Lutz, Víctor Molina García, Pascal Hedelt, Klaus-Peter Heue, and Richard Siddans
Atmos. Meas. Tech., 17, 6345–6367, https://doi.org/10.5194/amt-17-6345-2024, https://doi.org/10.5194/amt-17-6345-2024, 2024
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This paper describes a new treatment of the spatial misregistration of cloud properties for Sentinel-5 Precursor, when the footprints of different spectral bands are not perfectly aligned. The methodology exploits synergies between spectrometers and imagers, like TROPOMI and VIIRS. The largest improvements have been identified for heterogeneous scenes at cloud edges. This approach is generic and can also be applied to future Sentinel-4 and Sentinel-5 instruments.
Vincent R. Meijer, Sebastian D. Eastham, Ian A. Waitz, and Steven R. H. Barrett
Atmos. Meas. Tech., 17, 6145–6162, https://doi.org/10.5194/amt-17-6145-2024, https://doi.org/10.5194/amt-17-6145-2024, 2024
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Aviation's climate impact is partly due to contrails: the clouds that form behind aircraft and which can linger for hours under certain atmospheric conditions. Accurately forecasting these conditions could allow aircraft to avoid forming these contrails and thus reduce their environmental footprint. Our research uses deep learning to identify three-dimensional contrail locations in two-dimensional satellite imagery, which can be used to assess and improve these forecasts.
Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson
Atmos. Meas. Tech., 17, 5957–5987, https://doi.org/10.5194/amt-17-5957-2024, https://doi.org/10.5194/amt-17-5957-2024, 2024
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The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.
Luke Edgar Whitehead, Adrian James McDonald, and Adrien Guyot
Atmos. Meas. Tech., 17, 5765–5784, https://doi.org/10.5194/amt-17-5765-2024, https://doi.org/10.5194/amt-17-5765-2024, 2024
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Supercooled liquid water cloud is important to represent in weather and climate models, particularly in the Southern Hemisphere. Previous work has developed a new machine learning method for measuring supercooled liquid water in Antarctic clouds using simple lidar observations. We evaluate this technique using a lidar dataset from Christchurch, New Zealand, and develop an updated algorithm for accurate supercooled liquid water detection at mid-latitudes.
Julien Lenhardt, Johannes Quaas, and Dino Sejdinovic
Atmos. Meas. Tech., 17, 5655–5677, https://doi.org/10.5194/amt-17-5655-2024, https://doi.org/10.5194/amt-17-5655-2024, 2024
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Clouds play a key role in the regulation of the Earth's climate. Aspects like the height of their base are of essential interest to quantify their radiative effects but remain difficult to derive from satellite data. In this study, we combine observations from the surface and satellite retrievals of cloud properties to build a robust and accurate method to retrieve the cloud base height, based on a computer vision model and ordinal regression.
Johanna Mayer, Bernhard Mayer, Luca Bugliaro, Ralf Meerkötter, and Christiane Voigt
Atmos. Meas. Tech., 17, 5161–5185, https://doi.org/10.5194/amt-17-5161-2024, https://doi.org/10.5194/amt-17-5161-2024, 2024
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This study uses radiative transfer calculations to characterize the relation of two satellite channel combinations (namely infrared window brightness temperature differences – BTDs – of SEVIRI) to the thermodynamic cloud phase. A sensitivity analysis reveals the complex interplay of cloud parameters and their contribution to the observed phase dependence of BTDs. This knowledge helps to design optimal cloud-phase retrievals and to understand their potential and limitations.
Frédéric P. A. Vogt, Loris Foresti, Daniel Regenass, Sophie Réthoré, Néstor Tarin Burriel, Mervyn Bibby, Przemysław Juda, Simone Balmelli, Tobias Hanselmann, Pieter du Preez, and Dirk Furrer
Atmos. Meas. Tech., 17, 4891–4914, https://doi.org/10.5194/amt-17-4891-2024, https://doi.org/10.5194/amt-17-4891-2024, 2024
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ampycloud is a new algorithm developed at MeteoSwiss to characterize the height and sky coverage fraction of cloud layers above aerodromes via ceilometer data. This algorithm was devised as part of a larger effort to fully automate the creation of meteorological aerodrome reports (METARs) at Swiss civil airports. The ampycloud algorithm is implemented as a Python package that is made publicly available to the community under the 3-Clause BSD license.
Ke Ren, Haiyang Gao, Shuqi Niu, Shaoyang Sun, Leilei Kou, Yanqing Xie, Liguo Zhang, and Lingbing Bu
Atmos. Meas. Tech., 17, 4825–4842, https://doi.org/10.5194/amt-17-4825-2024, https://doi.org/10.5194/amt-17-4825-2024, 2024
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Ultraviolet imaging technology has significantly advanced the research and development of polar mesospheric clouds (PMCs). In this study, we proposed the wide-field-of-view ultraviolet imager (WFUI) and built a forward model to evaluate the detection capability and efficiency. The results demonstrate that the WFUI performs well in PMC detection and has high detection efficiency. The relationship between ice water content and detection efficiency follows an exponential function distribution.
Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson
Atmos. Meas. Tech., 17, 4337–4368, https://doi.org/10.5194/amt-17-4337-2024, https://doi.org/10.5194/amt-17-4337-2024, 2024
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The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limitations of currently available data records of cloud properties. In this work, we address this issue by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.
Huige Di, Xinhong Wang, Ning Chen, Jing Guo, Wenhui Xin, Shichun Li, Yan Guo, Qing Yan, Yufeng Wang, and Dengxin Hua
Atmos. Meas. Tech., 17, 4183–4196, https://doi.org/10.5194/amt-17-4183-2024, https://doi.org/10.5194/amt-17-4183-2024, 2024
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This study proposes an inversion method for atmospheric-aerosol or cloud microphysical parameters based on dual-wavelength lidar data. It is suitable for the inversion of uniformly mixed and single-property aerosol layers or small cloud droplets. For aerosol particles, the inversion range that this algorithm can achieve is 0.3–1.7 μm. For cloud droplets, it is 1.0–10 μm. This algorithm can quickly obtain the microphysical parameters of atmospheric particles and has better robustness.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2024-2090, https://doi.org/10.5194/egusphere-2024-2090, 2024
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This article presents a novel technique to estimate the liquid water content (LWC) in shallow warm clouds using a pair of collocated Ka-band (35 GHz) and G-band (239 GHz) radars. We demonstrate that the use of a G-band radar allows to retrieve the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of the LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.
Johanna Mayer, Luca Bugliaro, Bernhard Mayer, Dennis Piontek, and Christiane Voigt
Atmos. Meas. Tech., 17, 4015–4039, https://doi.org/10.5194/amt-17-4015-2024, https://doi.org/10.5194/amt-17-4015-2024, 2024
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ProPS (PRObabilistic cloud top Phase retrieval for SEVIRI) is a method to detect clouds and their thermodynamic phase with a geostationary satellite, distinguishing between clear sky and ice, mixed-phase, supercooled and warm liquid clouds. It uses a Bayesian approach based on the lidar–radar product DARDAR. The method allows studying cloud phases, especially mixed-phase and supercooled clouds, rarely observed from geostationary satellites. This can be used for comparison with climate models.
Clémantyne Aubry, Julien Delanoë, Silke Groß, Florian Ewald, Frédéric Tridon, Olivier Jourdan, and Guillaume Mioche
Atmos. Meas. Tech., 17, 3863–3881, https://doi.org/10.5194/amt-17-3863-2024, https://doi.org/10.5194/amt-17-3863-2024, 2024
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Radar–lidar synergy is used to retrieve ice, supercooled water and mixed-phase cloud properties, making the most of the radar sensitivity to ice crystals and the lidar sensitivity to supercooled droplets. A first analysis of the output of the algorithm run on the satellite data is compared with in situ data during an airborne Arctic field campaign, giving a mean percent error of 49 % for liquid water content and 75 % for ice water content.
Gerald G. Mace
Atmos. Meas. Tech., 17, 3679–3695, https://doi.org/10.5194/amt-17-3679-2024, https://doi.org/10.5194/amt-17-3679-2024, 2024
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The number of cloud droplets per unit volume, Nd, in a cloud is important for understanding aerosol–cloud interaction. In this study, we develop techniques to derive cloud droplet number concentration from lidar measurements combined with other remote sensing measurements such as cloud radar and microwave radiometers. We show that deriving Nd is very uncertain, although a synergistic algorithm seems to produce useful characterizations of Nd and effective particle size.
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, https://doi.org/10.5194/amt-17-3583-2024, 2024
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This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Jinyi Xia and Li Guan
EGUsphere, https://doi.org/10.5194/egusphere-2024-977, https://doi.org/10.5194/egusphere-2024-977, 2024
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This study presents a method for estimating cloud cover from FY4A AGRI observations using LSTM neural networks. The results demonstrate excellent performance in distinguishing clear sky scenes and reducing errors in cloud cover estimation. It shows significant improvements compared to existing methods.
Sunny Sun-Mack, Patrick Minnis, Yan Chen, Gang Hong, and William L. Smith Jr.
Atmos. Meas. Tech., 17, 3323–3346, https://doi.org/10.5194/amt-17-3323-2024, https://doi.org/10.5194/amt-17-3323-2024, 2024
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Multilayer clouds (MCs) affect the radiation budget differently than single-layer clouds (SCs) and need to be identified in satellite images. A neural network was trained to identify MCs by matching imagery with lidar/radar data. This method correctly identifies ~87 % SCs and MCs with a net accuracy gain of 7.5 % over snow-free surfaces. It is more accurate than most available methods and constitutes a first step in providing a reasonable 3-D characterization of the cloudy atmosphere.
Gianluca Di Natale, Marco Ridolfi, and Luca Palchetti
Atmos. Meas. Tech., 17, 3171–3186, https://doi.org/10.5194/amt-17-3171-2024, https://doi.org/10.5194/amt-17-3171-2024, 2024
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This work aims to define a new approach to retrieve the distribution of the main ice crystal shapes occurring inside ice and cirrus clouds from infrared spectral measurements. The capability of retrieving these shapes of the ice crystals from satellites will allow us to extend the currently available climatologies to be used as physical constraints in general circulation models. This could could allow us to improve their accuracy and prediction performance.
Vincent Forcadell, Clotilde Augros, Olivier Caumont, Kévin Dedieu, Maxandre Ouradou, Cloe David, Jordi Figueras i Ventura, Olivier Laurantin, and Hassan Al-Sakka
EGUsphere, https://doi.org/10.5194/egusphere-2024-1336, https://doi.org/10.5194/egusphere-2024-1336, 2024
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This study demonstrates the potential for enhancing severe hail detection through the application of convolutional neural networks (CNNs) to dual-polarization radar data. It is shown that current methods can be calibrated to significantly enhance their performance for severe hail detection. This study establishes the foundation for the solution of a more complex problem: the estimation of the maximum size of hailstones on the ground using deep learning applied to radar data.
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech., 17, 3011–3028, https://doi.org/10.5194/amt-17-3011-2024, https://doi.org/10.5194/amt-17-3011-2024, 2024
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We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on the multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere. The MS effect on lidar signals always decreases with the increasing distance from the cloud far edge. The decrease is the direct consequence of the fact that the forward peak of particle phase functions is much larger than the receiver field of view.
He Huang, Quan Wang, Chao Liu, and Chen Zhou
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-87, https://doi.org/10.5194/amt-2024-87, 2024
Revised manuscript accepted for AMT
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This study introduces a cloud property retrieval method which integrates traditional radiative transfer simulations with a machine-learning method. Retrievals from a machine learning algorithm are used to provide initial guesses, and a radiative transfer model is used to create radiance lookup tables for later iteration processes. The new method combines the advantages of traditional and machine learning algorithms, and is applicable both daytime and nighttime conditions.
Claudia Emde, Veronika Pörtge, Mihail Manev, and Bernhard Mayer
EGUsphere, https://doi.org/10.5194/egusphere-2024-1180, https://doi.org/10.5194/egusphere-2024-1180, 2024
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We introduce an innovative method to retrieve cloud fraction and optical thickness based on polarimetry, well-suited for satellite observations providing multi-angle polarization measurements. The cloud fraction and the cloud optical thickness can be derived from measurements at two viewing angles: one within the cloudbow and a second in the sun-glint region or at a scattering angle of approximately 90°.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-40, https://doi.org/10.5194/amt-2024-40, 2024
Revised manuscript accepted for AMT
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Our study investigates the impact of cloud shadows on satellite-based aerosol index measurements over Europe by TROPOMI. Using a cloud shadow detection algorithm and simulations, we found that the overall effect on the aerosol index is minimal. Interestingly, we measured that cloud shadows are significantly bluer than their shadow-free surroundings, but the traditional algorithm already (partly) automatically corrects for this increased blueness.
Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, and Matthias Tesche
Atmos. Meas. Tech., 17, 1739–1757, https://doi.org/10.5194/amt-17-1739-2024, https://doi.org/10.5194/amt-17-1739-2024, 2024
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We present a novel method for studying aerosol–cloud interactions. It combines cloud-relevant aerosol concentrations from polar-orbiting lidar observations with the development of individual clouds from geostationary observations. Application to 1 year of data gives first results on the impact of aerosols on the concentration and size of cloud droplets and on cloud phase in the regime of heterogeneous ice formation. The method could enable the systematic investigation of warm and cold clouds.
Kélian Sommer, Wassim Kabalan, and Romain Brunet
EGUsphere, https://doi.org/10.5194/egusphere-2024-101, https://doi.org/10.5194/egusphere-2024-101, 2024
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Our research introduces a novel deep-learning approach for classifying and segmenting ground-based infrared thermal images, a crucial step in cloud monitoring. Tests on self-captured data showcase its excellent accuracy in distinguishing image types and in structure segmentation. With potential applications in astronomical observations, our work pioneers a robust solution for ground-based sky quality assessment, promising advancements in the photometric observations experiments.
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
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In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024, https://doi.org/10.5194/amt-17-999-2024, 2024
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The vertical distribution of particle shape (VDPS) method, introduced in this study, aids in characterizing the density-weighted shape of cloud particles from scanning slanted linear depolarization ratio (SLDR)-mode cloud radar observations. The VDPS approach represents a new, versatile way to study microphysical processes by combining a spheroidal scattering model with real measurements of SLDR.
Sarah Brüning, Stefan Niebler, and Holger Tost
Atmos. Meas. Tech., 17, 961–978, https://doi.org/10.5194/amt-17-961-2024, https://doi.org/10.5194/amt-17-961-2024, 2024
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We apply the Res-UNet to derive a comprehensive 3D cloud tomography from 2D satellite data over heterogeneous landscapes. We combine observational data from passive and active remote sensing sensors by an automated matching algorithm. These data are fed into a neural network to predict cloud reflectivities on the whole satellite domain between 2.4 and 24 km height. With an average RMSE of 2.99 dBZ, we contribute to closing data gaps in the representation of clouds in observational data.
Michael Eisinger, Fabien Marnas, Kotska Wallace, Takuji Kubota, Nobuhiro Tomiyama, Yuichi Ohno, Toshiyuki Tanaka, Eichi Tomita, Tobias Wehr, and Dirk Bernaerts
Atmos. Meas. Tech., 17, 839–862, https://doi.org/10.5194/amt-17-839-2024, https://doi.org/10.5194/amt-17-839-2024, 2024
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The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) is an ESA–JAXA satellite mission to be launched in 2024. We presented an overview of the EarthCARE processors' development, with processors developed by teams in Europe, Japan, and Canada. EarthCARE will allow scientists to evaluate the representation of cloud, aerosol, precipitation, and radiative flux in weather forecast and climate models, with the objective to better understand cloud processes and improve weather and climate models.
Sean R. Foley, Kirk D. Knobelspiesse, Andrew M. Sayer, Meng Gao, James Hays, and Judy Hoffman
EGUsphere, https://doi.org/10.5194/egusphere-2023-2392, https://doi.org/10.5194/egusphere-2023-2392, 2024
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Measuring the shape of clouds helps scientists understand how the Earth will continue to respond to climate change. Satellites measure clouds in different ways. One way is to take pictures of clouds from multiple angles, and to use the differences between the pictures to measure cloud structure. However, doing this accurately can be challenging. We propose a way to use machine learning to recover the shape of clouds from multi-angle satellite data.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
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The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
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The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
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The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Damao Zhang, Andrew M. Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William I. Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
Atmos. Meas. Tech., 16, 5827–5846, https://doi.org/10.5194/amt-16-5827-2023, https://doi.org/10.5194/amt-16-5827-2023, 2023
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Cloud droplet number concentration can be retrieved from remote sensing measurements. Aircraft measurements are used to validate four ground-based retrievals of cloud droplet number concentration. We demonstrate that retrieved cloud droplet number concentrations align well with aircraft measurements for overcast clouds, but they may substantially differ for broken clouds. The ensemble of various retrievals can help quantify retrieval uncertainties and identify reliable retrieval scenarios.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
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A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
Atmos. Meas. Tech., 16, 5305–5326, https://doi.org/10.5194/amt-16-5305-2023, https://doi.org/10.5194/amt-16-5305-2023, 2023
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Near-infrared satellite images have information on clouds that is complementary to what is available from the visible and infrared parts of the spectrum. Using this information for data assimilation and model evaluation requires a fast, accurate forward operator to compute synthetic images from numerical weather prediction model output. We discuss a novel, neural-network-based approach for the 1.6 µm near-infrared channel that is suitable for this purpose and also works for other solar channels.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, https://doi.org/10.5194/amt-16-4927-2023, 2023
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The EarthCARE satellite mission Level 2 algorithm development requires realistic 3D cloud and aerosol scenes along the satellite orbits. One of the best ways to produce these scenes is to use a high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This paper describes the production and validation of three EarthCARE test scenes.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
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We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
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Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
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We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
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We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
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We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
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JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
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This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
Christian Matar, Céline Cornet, Frédéric Parol, Laurent C.-Labonnote, Frédérique Auriol, and Marc Nicolas
Atmos. Meas. Tech., 16, 3221–3243, https://doi.org/10.5194/amt-16-3221-2023, https://doi.org/10.5194/amt-16-3221-2023, 2023
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The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular measurements to retrieve COT and Reff. The corresponding uncertainties related to measurement errors, which are up to 6 and 12 %, the non-retrieved parameters, which are less than 0.5 %, and the cloud model assumptions show that the heterogeneous vertical profiles and the 3D radiative transfer effects lead to average uncertainties of 5 and 4 % for COT and 13 and 9 % for Reff.
Yuichiro Hagihara, Yuichi Ohno, Hiroaki Horie, Woosub Roh, Masaki Satoh, and Takuji Kubota
Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
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The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
Kamil Mroz, Bernat Puidgomènech Treserras, Alessandro Battaglia, Pavlos Kollias, Aleksandra Tatarevic, and Frederic Tridon
Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
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We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
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