Articles | Volume 22, issue 14
https://doi.org/10.5194/acp-22-9313-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-9313-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Radiative closure and cloud effects on the radiation budget based on satellite and shipborne observations during the Arctic summer research cruise, PS106
Carola Barrientos-Velasco
CORRESPONDING AUTHOR
Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Hartwig Deneke
Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Anja Hünerbein
Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Hannes J. Griesche
Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Patric Seifert
Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Andreas Macke
Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Related authors
Carola Barrientos-Velasco, Christopher J. Cox, Hartwig Deneke, J. Brant Dodson, Anja Hünerbein, Matthew D. Shupe, Patrick C. Taylor, and Andreas Macke
Atmos. Chem. Phys., 25, 3929–3960, https://doi.org/10.5194/acp-25-3929-2025, https://doi.org/10.5194/acp-25-3929-2025, 2025
Short summary
Short summary
Understanding how clouds affect the climate, especially in the Arctic, is crucial. This study used data from the largest polar expedition in history, MOSAiC, and the CERES satellite to analyse the impact of clouds on radiation. Simulations showed accurate results, aligning with observations. Over the year, clouds caused the atmospheric surface system to lose 5.2 W m−² of radiative energy to space, while the surface gained 25 W m−² and the atmosphere cooled by 30.2 W m−².
Hannes Jascha Griesche, Carola Barrientos-Velasco, Hartwig Deneke, Anja Hünerbein, Patric Seifert, and Andreas Macke
Atmos. Chem. Phys., 24, 597–612, https://doi.org/10.5194/acp-24-597-2024, https://doi.org/10.5194/acp-24-597-2024, 2024
Short summary
Short summary
The Arctic is strongly affected by climate change and the role of clouds therein is not yet completely understood. Measurements from the Arctic expedition PS106 were used to simulate radiative fluxes with and without clouds at very low altitudes (below 165 m), and their radiative effect was calculated to be 54 Wm-2. The low heights of these clouds make them hard to observe. This study shows the importance of accurate measurements and simulations of clouds and gives suggestions for improvements.
Hartwig Deneke, Carola Barrientos-Velasco, Sebastian Bley, Anja Hünerbein, Stephan Lenk, Andreas Macke, Jan Fokke Meirink, Marion Schroedter-Homscheidt, Fabian Senf, Ping Wang, Frank Werner, and Jonas Witthuhn
Atmos. Meas. Tech., 14, 5107–5126, https://doi.org/10.5194/amt-14-5107-2021, https://doi.org/10.5194/amt-14-5107-2021, 2021
Short summary
Short summary
The SEVIRI instrument flown on the European geostationary Meteosat satellites acquires multi-spectral images at a relatively coarse pixel resolution of 3 × 3 km2, but it also has a broadband high-resolution visible channel with 1 × 1 km2 spatial resolution. In this study, the modification of an existing cloud property and solar irradiance retrieval to use this channel to improve the spatial resolution of its output products as well as the resulting benefits for applications are described.
Hannes J. Griesche, Patric Seifert, Albert Ansmann, Holger Baars, Carola Barrientos Velasco, Johannes Bühl, Ronny Engelmann, Martin Radenz, Yin Zhenping, and Andreas Macke
Atmos. Meas. Tech., 13, 5335–5358, https://doi.org/10.5194/amt-13-5335-2020, https://doi.org/10.5194/amt-13-5335-2020, 2020
Short summary
Short summary
In summer 2017, the research vessel Polarstern performed cruise PS106 to the Arctic north of Svalbard. In the frame of the cruise, remote-sensing observations of the atmosphere were performed on Polarstern to continuously monitor aerosol and clouds above the vessel. In our study, we present the deployed instrumentation and applied data analysis methods and provide case studies of the aerosol and cloud observations made during the cruise. Statistics of low-cloud occurrence are presented as well.
Job I. Wiltink, Hartwig Deneke, Chiel C. van Heerwaarden, and Jan Fokke Meirink
Atmos. Meas. Tech., 18, 3917–3936, https://doi.org/10.5194/amt-18-3917-2025, https://doi.org/10.5194/amt-18-3917-2025, 2025
Short summary
Short summary
Global horizontal irradiance retrievals from satellite observations are affected by spatial displacements due to parallax and cloud shadows. We assess different approaches to correct for these displacements and quantify their added value by comparison with a network of ground-based pyranometer observations. The corrections are found to become increasingly important at higher spatial resolutions and are most relevant for variable cloud types.
Kevin Ohneiser, Markus Hartmann, Heike Wex, Patric Seifert, Anja Hardt, Anna Miller, Katharina Baudrexl, Werner Thomas, Veronika Ettrichrätz, Maximilian Maahn, Tom Gaudek, Willi Schimmel, Fabian Senf, Hannes Griesche, Martin Radenz, and Jan Henneberger
EGUsphere, https://doi.org/10.5194/egusphere-2025-3675, https://doi.org/10.5194/egusphere-2025-3675, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This study highlights the efficiency of supercooled stratus clouds to remove ice-nucleating particles (INPs). In our measurement scenarios within the planetary boundary layer lower concentrations of INP under supercooled stratus conditions were found than with temperatures above freezing. Within the free troposphere a lot more INPs were found to be available which means that the free troposphere must be taken into account as an important source of INPs.
Zhaolong Wu, Patric Seifert, Yun He, Holger Baars, Haoran Li, Cristofer Jimenez, Chengcai Li, and Albert Ansmann
Atmos. Meas. Tech., 18, 3611–3634, https://doi.org/10.5194/amt-18-3611-2025, https://doi.org/10.5194/amt-18-3611-2025, 2025
Short summary
Short summary
This study introduces a novel method to detect horizontally oriented ice crystals (HOICs) using two ground-based polarization lidars at different zenith angles, based on a yearlong dataset collected in Beijing. Combined with cloud radar and reanalysis data, the fine categorization results reveal HOICs occur in calm winds and moderately cold temperatures and are influenced by turbulence near cloud bases. The results enhance our understanding of cloud processes and improve atmospheric models.
Hossein Panahifar, Maria Poutli, George Kotsias, Argyro Nisantzi, Silas Michaelides, Diofantos Hadjimitsis, Patric Seifert, Albert Ansmann, and Rodanthi-Elisavet Mamouri
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-G-2025, 1153–1158, https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-1153-2025, https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-1153-2025, 2025
Jean Lac, Hélène Chepfer, Matthew D. Shupe, and Hannes Griesche
EGUsphere, https://doi.org/10.5194/egusphere-2025-3549, https://doi.org/10.5194/egusphere-2025-3549, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Satellite observations show that Arctic spring experiences a rapid increase in liquid-containing clouds over sea ice. Our study shows that this transition is mostly driven by warmer temperatures in early spring than in late spring, favoring more liquid clouds formation, rather than a limited moisture source in early spring. It suggests that, in the future, this transition is likely to occur earlier in spring considering the rapid Arctic warming.
Kevin Ohneiser, Patric Seifert, Willi Schimmel, Fabian Senf, Tom Gaudek, Martin Radenz, Audrey Teisseire, Veronika Ettrichrätz, Teresa Vogl, Nina Maherndl, Nils Pfeifer, Jan Henneberger, Anna J. Miller, Nadja Omanovic, Christopher Fuchs, Huiying Zhang, Fabiola Ramelli, Robert Spirig, Anton Kötsche, Heike Kalesse-Los, Maximilian Maahn, Heather Corden, Alexis Berne, Majid Hajipour, Hannes Griesche, Julian Hofer, Ronny Engelmann, Annett Skupin, Albert Ansmann, and Holger Baars
EGUsphere, https://doi.org/10.5194/egusphere-2025-2482, https://doi.org/10.5194/egusphere-2025-2482, 2025
Short summary
Short summary
This study focuses on a seeder-feeder cloud system on 8 Jan 2024 in Eriswil, Switzerland. It is shown how the interaction of these cloud systems changes the cloud microphysical properties and the precipitation patterns. A big set of advanced remote-sensing techniques and retrieval algorithms are applied, so that a detailed view on the seeder-feeder cloud system is available. The gained knowledge can be used to improve weather models and weather forecasts.
Albert Ansmann, Cristofer Jimenez, Johanna Roschke, Johannes Bühl, Kevin Ohneiser, Ronny Engelmann, Martin Radenz, Hannes Griesche, Julian Hofer, Dietrich Althausen, Daniel A. Knopf, Sandro Dahlke, Tom Gaudek, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 25, 4847–4866, https://doi.org/10.5194/acp-25-4847-2025, https://doi.org/10.5194/acp-25-4847-2025, 2025
Short summary
Short summary
In this study, we focus on the potential impact of wildfire smoke on cirrus formation. For the first time, state-of-the-art aerosol and cirrus observations with lidar and radar, presented in this paper (Part 1 of a series of two articles), are closely linked to the comprehensive modeling of gravity-wave-induced ice nucleation in cirrus evolution processes, presented in a companion paper (Part 2). We found a clear impact of wildfire smoke on cirrus evolution.
Benedikt Gast, Cristofer Jimenez, Albert Ansmann, Moritz Haarig, Ronny Engelmann, Felix Fritzsch, Athena A. Floutsi, Hannes Griesche, Kevin Ohneiser, Julian Hofer, Martin Radenz, Holger Baars, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 25, 3995–4011, https://doi.org/10.5194/acp-25-3995-2025, https://doi.org/10.5194/acp-25-3995-2025, 2025
Short summary
Short summary
In this study, we discuss the enhanced detection capabilities of a fluorescence lidar in the case of optically thin aerosol layers in the upper troposphere and lower stratosphere (UTLS) region. Our results suggest that such thin aerosol layers are not so rare in the UTLS and can potentially trigger and impact cirrus cloud formation through heterogeneous ice nucleation. By altering the microphysical cloud properties, this could affect clouds' evolution and lifetime and thus their climate effect.
Carola Barrientos-Velasco, Christopher J. Cox, Hartwig Deneke, J. Brant Dodson, Anja Hünerbein, Matthew D. Shupe, Patrick C. Taylor, and Andreas Macke
Atmos. Chem. Phys., 25, 3929–3960, https://doi.org/10.5194/acp-25-3929-2025, https://doi.org/10.5194/acp-25-3929-2025, 2025
Short summary
Short summary
Understanding how clouds affect the climate, especially in the Arctic, is crucial. This study used data from the largest polar expedition in history, MOSAiC, and the CERES satellite to analyse the impact of clouds on radiation. Simulations showed accurate results, aligning with observations. Over the year, clouds caused the atmospheric surface system to lose 5.2 W m−² of radiative energy to space, while the surface gained 25 W m−² and the atmosphere cooled by 30.2 W m−².
Audrey Teisseire, Anne-Claire Billault-Roux, Teresa Vogl, and Patric Seifert
Atmos. Meas. Tech., 18, 1499–1517, https://doi.org/10.5194/amt-18-1499-2025, https://doi.org/10.5194/amt-18-1499-2025, 2025
Short summary
Short summary
This study demonstrates the ability of a new method delivering the vertical distribution of particle shape to highlight riming and aggregation processes, identifying graupel and aggregates, respectively, as isometric particles. The distinction between these processes can be achieved using lidar or spectral techniques, as demonstrated in the case studies. The capability of the new method to identify rimed particles and aggregates without differentiating them can simplify statistical work.
Cristofer Jimenez, Albert Ansmann, Kevin Ohneiser, Hannes Griesche, Ronny Engelmann, Martin Radenz, Julian Hofer, Dietrich Althausen, Daniel Alexander Knopf, Sandro Dahlke, Johannes Bühl, Holger Baars, Patric Seifert, and Ulla Wandinger
EGUsphere, https://doi.org/10.5194/egusphere-2025-967, https://doi.org/10.5194/egusphere-2025-967, 2025
Short summary
Short summary
Using advanced remote sensing on the icebreaker Polarstern, we studied mixed-phase clouds (MPCs) in the central Arctic during the 2019–2020 MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) campaign. For the first time, lidar and radar techniques tracked the year-round evolution of liquid and ice phases in MPCs. The study provides cloud statistics and explores key processes driving cloud longevity, offering new insights into Arctic cloud formation and persistence.
Christopher Fuchs, Fabiola Ramelli, Anna J. Miller, Nadja Omanovic, Robert Spirig, Huiying Zhang, Patric Seifert, Kevin Ohneiser, Ulrike Lohmann, and Jan Henneberger
EGUsphere, https://doi.org/10.5194/egusphere-2025-688, https://doi.org/10.5194/egusphere-2025-688, 2025
Short summary
Short summary
We quantify diffusional ice crystal growth in natural clouds using cloud seeding experiments. We report growth rates for 14 experiments between -5.1°C and -8.3°C and observe strong variations depending on the cloud characteristics. Comparing our growth rates to laboratory data, we found similar temperature-dependent trends, but the laboratory rates are higher. This data fills the gap in quantitative in situ observation of ice crystal growth, helping to validate models and laboratory experiments.
Marcus Klingebiel, André Ehrlich, Micha Gryschka, Nils Risse, Nina Maherndl, Imke Schirmacher, Sophie Rosenburg, Sabine Hörnig, Manuel Moser, Evelyn Jäkel, Michael Schäfer, Hartwig Deneke, Mario Mech, Christiane Voigt, and Manfred Wendisch
EGUsphere, https://doi.org/10.5194/egusphere-2025-201, https://doi.org/10.5194/egusphere-2025-201, 2025
Short summary
Short summary
Our study is using aircraft measurements from the HALO-(𝒜𝒞)³ campaign to investigate the transition from organized Arctic cloud street structures to more scattered cloud shapes. We show that lower wind speeds cause this transition. In addition we look at the changes of the cloud coverage, the height of the clouds, the cloud particles and the radiative properties.
Majid Hajipour, Patric Seifert, Hannes Griesche, Kevin Ohneiser, and Martin Radenz
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-173, https://doi.org/10.5194/amt-2024-173, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This study presents an approach that enables the detection of the shape and orientation of multiple types of co-located hydrometeors in mixed-phase cloud systems. This information is key for improving the understanding of these clouds, as they do contain ice and liquid water simultaneously, making them relevant for the precipitation budget and radiative balance of the Earth's atmosphere. The retrieval is based on elevation scans of polarimetric cloud radars and can therefore be flexibly applied.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
Short summary
Short summary
We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Job I. Wiltink, Hartwig Deneke, Yves-Marie Saint-Drenan, Chiel C. van Heerwaarden, and Jan Fokke Meirink
Atmos. Meas. Tech., 17, 6003–6024, https://doi.org/10.5194/amt-17-6003-2024, https://doi.org/10.5194/amt-17-6003-2024, 2024
Short summary
Short summary
Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) global horizontal irradiance (GHI) retrievals are validated at standard and increased spatial resolution against a network of 99 pyranometers. GHI accuracy is strongly dependent on the cloud regime. Days with variable cloud conditions show significant accuracy improvements when retrieved at higher resolution. We highlight the benefits of dense network observations and a cloud-regime-resolved approach in validating GHI retrievals.
Zili He, Quentin Libois, Najda Villefranque, Hartwig Deneke, Jonas Witthuhn, and Fleur Couvreux
Atmos. Chem. Phys., 24, 11391–11408, https://doi.org/10.5194/acp-24-11391-2024, https://doi.org/10.5194/acp-24-11391-2024, 2024
Short summary
Short summary
This study uses observations and simulations to analyze how cumulus clouds affect spacial solar radiation variability on the ground. Results show that the simulations reproduce the observations well and improve understanding of cloud impacts on radiation. The research also indicates that a few strategically placed sensors, capitalizing on measurement timing, can effectively measure these variations, aiding in the development of detailed weather prediction models.
Nadja Omanovic, Sylvaine Ferrachat, Christopher Fuchs, Jan Henneberger, Anna J. Miller, Kevin Ohneiser, Fabiola Ramelli, Patric Seifert, Robert Spirig, Huiying Zhang, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 6825–6844, https://doi.org/10.5194/acp-24-6825-2024, https://doi.org/10.5194/acp-24-6825-2024, 2024
Short summary
Short summary
We present simulations with a high-resolution numerical weather prediction model to study the growth of ice crystals in low clouds following glaciogenic seeding. We show that the simulated ice crystals grow slower than observed and do not consume as many cloud droplets as measured in the field. This may have implications for forecasting precipitation, as the ice phase is crucial for precipitation at middle and high latitudes.
Junghwa Lee, Patric Seifert, Tempei Hashino, Maximilian Maahn, Fabian Senf, and Oswald Knoth
Atmos. Chem. Phys., 24, 5737–5756, https://doi.org/10.5194/acp-24-5737-2024, https://doi.org/10.5194/acp-24-5737-2024, 2024
Short summary
Short summary
Spectral bin model simulations of an idealized supercooled stratiform cloud were performed with the AMPS model for variable CCN and INP concentrations. We performed radar forward simulations with PAMTRA to transfer the simulations into radar observational space. The derived radar reflectivity factors were compared to observational studies of stratiform mixed-phase clouds. These studies report a similar response of the radar reflectivity factor to aerosol perturbations as we found in our study.
Nicole Docter, Anja Hünerbein, David P. Donovan, Rene Preusker, Jürgen Fischer, Jan Fokke Meirink, Piet Stammes, and Michael Eisinger
Atmos. Meas. Tech., 17, 2507–2519, https://doi.org/10.5194/amt-17-2507-2024, https://doi.org/10.5194/amt-17-2507-2024, 2024
Short summary
Short summary
MSI is the imaging spectrometer on board EarthCARE and will provide across-track information on clouds and aerosol properties. The MSI solar channels exhibit a spectral misalignment effect (SMILE) in the measurements. This paper describes and evaluates how the SMILE will affect the cloud and aerosol retrievals that do not account for it.
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
Short summary
Short summary
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.
Shannon L. Mason, Howard W. Barker, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
Short summary
Short summary
When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
Julian Hofer, Patric Seifert, J. Ben Liley, Martin Radenz, Osamu Uchino, Isamu Morino, Tetsu Sakai, Tomohiro Nagai, and Albert Ansmann
Atmos. Chem. Phys., 24, 1265–1280, https://doi.org/10.5194/acp-24-1265-2024, https://doi.org/10.5194/acp-24-1265-2024, 2024
Short summary
Short summary
An 11-year dataset of polarization lidar observations from Lauder, New Zealand / Aotearoa, was used to distinguish the thermodynamic phase of natural clouds. The cloud dataset was separated to assess the impact of air mass origin on the frequency of heterogeneous ice formation. Ice formation efficiency in clouds above Lauder was found to be lower than in the polluted Northern Hemisphere midlatitudes but higher than in very clean and pristine environments, such as Punta Arenas in southern Chile.
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
Short summary
Short summary
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.
Hannes Jascha Griesche, Carola Barrientos-Velasco, Hartwig Deneke, Anja Hünerbein, Patric Seifert, and Andreas Macke
Atmos. Chem. Phys., 24, 597–612, https://doi.org/10.5194/acp-24-597-2024, https://doi.org/10.5194/acp-24-597-2024, 2024
Short summary
Short summary
The Arctic is strongly affected by climate change and the role of clouds therein is not yet completely understood. Measurements from the Arctic expedition PS106 were used to simulate radiative fluxes with and without clouds at very low altitudes (below 165 m), and their radiative effect was calculated to be 54 Wm-2. The low heights of these clouds make them hard to observe. This study shows the importance of accurate measurements and simulations of clouds and gives suggestions for improvements.
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
Short summary
Short summary
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.
Pablo Saavedra Garfias, Heike Kalesse-Los, Luisa von Albedyll, Hannes Griesche, and Gunnar Spreen
Atmos. Chem. Phys., 23, 14521–14546, https://doi.org/10.5194/acp-23-14521-2023, https://doi.org/10.5194/acp-23-14521-2023, 2023
Short summary
Short summary
An important Arctic climate process is the release of heat fluxes from sea ice openings to the atmosphere that influence the clouds. The characterization of this process is the objective of this study. Using synergistic observations from the MOSAiC expedition, we found that single-layer cloud properties show significant differences when clouds are coupled or decoupled to the water vapour transport which is used as physical link between the upwind sea ice openings and the cloud under observation.
Rodanthi-Elisavet Mamouri, Albert Ansmann, Kevin Ohneiser, Daniel A. Knopf, Argyro Nisantzi, Johannes Bühl, Ronny Engelmann, Annett Skupin, Patric Seifert, Holger Baars, Dragos Ene, Ulla Wandinger, and Diofantos Hadjimitsis
Atmos. Chem. Phys., 23, 14097–14114, https://doi.org/10.5194/acp-23-14097-2023, https://doi.org/10.5194/acp-23-14097-2023, 2023
Short summary
Short summary
For the first time, rather clear evidence is found that wildfire smoke particles can trigger strong cirrus formation. This finding is of importance because intensive and large wildfires may occur increasingly often in the future as climate change proceeds. Based on lidar observations in Cyprus in autumn 2020, we provide detailed insight into the cirrus formation at the tropopause in the presence of aged wildfire smoke (here, 8–9 day old Californian wildfire smoke).
James Barry, Stefanie Meilinger, Klaus Pfeilsticker, Anna Herman-Czezuch, Nicola Kimiaie, Christopher Schirrmeister, Rone Yousif, Tina Buchmann, Johannes Grabenstein, Hartwig Deneke, Jonas Witthuhn, Claudia Emde, Felix Gödde, Bernhard Mayer, Leonhard Scheck, Marion Schroedter-Homscheidt, Philipp Hofbauer, and Matthias Struck
Atmos. Meas. Tech., 16, 4975–5007, https://doi.org/10.5194/amt-16-4975-2023, https://doi.org/10.5194/amt-16-4975-2023, 2023
Short summary
Short summary
Measured power data from solar photovoltaic (PV) systems contain information about the state of the atmosphere. In this work, power data from PV systems in the Allgäu region in Germany were used to determine the solar irradiance at each location, using state-of-the-art simulation and modelling. The results were validated using concurrent measurements of the incoming solar radiation in each case. If applied on a wider scale, this algorithm could help improve weather and climate models.
Albert Ansmann, Kevin Ohneiser, Ronny Engelmann, Martin Radenz, Hannes Griesche, Julian Hofer, Dietrich Althausen, Jessie M. Creamean, Matthew C. Boyer, Daniel A. Knopf, Sandro Dahlke, Marion Maturilli, Henriette Gebauer, Johannes Bühl, Cristofer Jimenez, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 23, 12821–12849, https://doi.org/10.5194/acp-23-12821-2023, https://doi.org/10.5194/acp-23-12821-2023, 2023
Short summary
Short summary
The 1-year MOSAiC (2019–2020) expedition with the German ice breaker Polarstern was the largest polar field campaign ever conducted. The Polarstern, with our lidar aboard, drifted with the pack ice north of 85° N for more than 7 months (October 2019 to mid-May 2020). We measured the full annual cycle of aerosol conditions in terms of aerosol optical and cloud-process-relevant properties. We observed a strong contrast between polluted winter and clean summer aerosol conditions.
Holger Baars, Joshua Walchester, Elizaveta Basharova, Henriette Gebauer, Martin Radenz, Johannes Bühl, Boris Barja, Ulla Wandinger, and Patric Seifert
Atmos. Meas. Tech., 16, 3809–3834, https://doi.org/10.5194/amt-16-3809-2023, https://doi.org/10.5194/amt-16-3809-2023, 2023
Short summary
Short summary
In 2018, the Aeolus satellite of the European Space Agency (ESA) was launched to improve weather forecasts through global measurements of wind profiles. Given the novel lidar technique onboard, extensive validation efforts have been needed to verify the observations. For this reason, we performed long-term validation measurements in Germany and Chile. We found significant improvement in the data products due to a new algorithm version and can confirm the general validity of Aeolus observations.
Anja Hünerbein, Sebastian Bley, Stefan Horn, Hartwig Deneke, and Andi Walther
Atmos. Meas. Tech., 16, 2821–2836, https://doi.org/10.5194/amt-16-2821-2023, https://doi.org/10.5194/amt-16-2821-2023, 2023
Short summary
Short summary
The Multi-Spectral Imager (MSI) on board the EarthCARE satellite will provide the information needed for describing the cloud and aerosol properties in the cross-track direction, complementing the measurements from the Cloud Profiling Radar, Atmospheric Lidar and Broad-Band Radiometer. The accurate discrimination between clear and cloudy pixels is an essential first step. Therefore, the cloud mask algorithm provides a cloud flag, cloud phase and cloud type product for the MSI observations.
Athena Augusta Floutsi, Holger Baars, Ronny Engelmann, Dietrich Althausen, Albert Ansmann, Stephanie Bohlmann, Birgit Heese, Julian Hofer, Thomas Kanitz, Moritz Haarig, Kevin Ohneiser, Martin Radenz, Patric Seifert, Annett Skupin, Zhenping Yin, Sabur F. Abdullaev, Mika Komppula, Maria Filioglou, Elina Giannakaki, Iwona S. Stachlewska, Lucja Janicka, Daniele Bortoli, Eleni Marinou, Vassilis Amiridis, Anna Gialitaki, Rodanthi-Elisavet Mamouri, Boris Barja, and Ulla Wandinger
Atmos. Meas. Tech., 16, 2353–2379, https://doi.org/10.5194/amt-16-2353-2023, https://doi.org/10.5194/amt-16-2353-2023, 2023
Short summary
Short summary
DeLiAn is a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements and currently covers two wavelengths, 355 and 532 nm, for 13 aerosol categories ranging from basic aerosol types to mixtures.
Samuel Kwakye, Heike Kalesse-Los, Maximilian Maahn, Patric Seifert, Roel van Klink, Christian Wirth, and Johannes Quaas
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-69, https://doi.org/10.5194/amt-2023-69, 2023
Publication in AMT not foreseen
Short summary
Short summary
Insect numbers in the atmosphere can be calculated using polarimetric weather radar but they have to be identified and separated from other echoes, especially weather phenomena. Here, the separation is demonstrated using three machine-learning algorithms and insect count data from suction traps and the nature of radar measurements of different radar echoes is revealed. Random forest is the best separating algorithm and insect echoes radar measurements are distinct.
Kevin Ohneiser, Albert Ansmann, Jonas Witthuhn, Hartwig Deneke, Alexandra Chudnovsky, Gregor Walter, and Fabian Senf
Atmos. Chem. Phys., 23, 2901–2925, https://doi.org/10.5194/acp-23-2901-2023, https://doi.org/10.5194/acp-23-2901-2023, 2023
Short summary
Short summary
This study shows that smoke layers can reach the tropopause via the self-lofting effect within 3–7 d in the absence of pyrocumulonimbus convection if the
aerosol optical thickness is larger than approximately 2 for a longer time period. When reaching the stratosphere, wildfire smoke can sensitively influence the stratospheric composition on a hemispheric scale and thus can affect the Earth’s climate and the ozone layer.
Willi Schimmel, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert
Atmos. Meas. Tech., 15, 5343–5366, https://doi.org/10.5194/amt-15-5343-2022, https://doi.org/10.5194/amt-15-5343-2022, 2022
Short summary
Short summary
This study introduces the novel Doppler radar spectra-based machine learning approach VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn). VOODOO is a powerful probability-based extension to the existing Cloudnet hydrometeor target classification, enabling the detection of liquid-bearing cloud layers beyond complete lidar attenuation via user-defined p* threshold. VOODOO performs best for (multi-layer) stratiform and deep mixed-phase clouds with liquid water path > 100 g m−2.
Albert Ansmann, Kevin Ohneiser, Alexandra Chudnovsky, Daniel A. Knopf, Edwin W. Eloranta, Diego Villanueva, Patric Seifert, Martin Radenz, Boris Barja, Félix Zamorano, Cristofer Jimenez, Ronny Engelmann, Holger Baars, Hannes Griesche, Julian Hofer, Dietrich Althausen, and Ulla Wandinger
Atmos. Chem. Phys., 22, 11701–11726, https://doi.org/10.5194/acp-22-11701-2022, https://doi.org/10.5194/acp-22-11701-2022, 2022
Short summary
Short summary
For the first time we present a systematic study on the impact of wildfire smoke on ozone depletion in the Arctic (2020) and Antarctic stratosphere (2020, 2021). Two major fire events in Siberia and Australia were responsible for the observed record-breaking stratospheric smoke pollution. Our analyses were based on lidar observations of smoke parameters (Polarstern, Punta Arenas) and NDACC Arctic and Antarctic ozone profiles as well as on Antarctic OMI satellite observations of column ozone.
Xianda Gong, Martin Radenz, Heike Wex, Patric Seifert, Farnoush Ataei, Silvia Henning, Holger Baars, Boris Barja, Albert Ansmann, and Frank Stratmann
Atmos. Chem. Phys., 22, 10505–10525, https://doi.org/10.5194/acp-22-10505-2022, https://doi.org/10.5194/acp-22-10505-2022, 2022
Short summary
Short summary
The sources of ice-nucleating particles (INPs) are poorly understood in the Southern Hemisphere (SH). We studied INPs in the boundary layer in the southern Patagonia region. No seasonal cycle of INP concentrations was observed. The majority of INPs are biogenic particles, likely from local continental sources. The INP concentrations are higher when strong precipitation occurs. While previous studies focused on marine INP sources in SH, we point out the importance of continental sources of INPs.
Jörg Wieder, Nikola Ihn, Claudia Mignani, Moritz Haarig, Johannes Bühl, Patric Seifert, Ronny Engelmann, Fabiola Ramelli, Zamin A. Kanji, Ulrike Lohmann, and Jan Henneberger
Atmos. Chem. Phys., 22, 9767–9797, https://doi.org/10.5194/acp-22-9767-2022, https://doi.org/10.5194/acp-22-9767-2022, 2022
Short summary
Short summary
Ice formation and its evolution in mixed-phase clouds are still uncertain. We evaluate the lidar retrieval of ice-nucleating particle concentration in dust-dominated and continental air masses over the Swiss Alps with in situ observations. A calibration factor to improve the retrieval from continental air masses is proposed. Ice multiplication factors are obtained with a new method utilizing remote sensing. Our results indicate that secondary ice production occurs at temperatures down to −30 °C.
Philipp Richter, Mathias Palm, Christine Weinzierl, Hannes Griesche, Penny M. Rowe, and Justus Notholt
Earth Syst. Sci. Data, 14, 2767–2784, https://doi.org/10.5194/essd-14-2767-2022, https://doi.org/10.5194/essd-14-2767-2022, 2022
Short summary
Short summary
We present a dataset of cloud optical depths, effective radii and water paths from optically thin clouds observed in the Arctic around Svalbard. The data have been retrieved from infrared spectral radiance measured using a Fourier-transform infrared (FTIR) spectrometer. Besides a description of the measurements and retrieval technique, the data are put into context with results of corresponding measurements from microwave radiometer, lidar and cloud radar.
Kevin Ohneiser, Albert Ansmann, Bernd Kaifler, Alexandra Chudnovsky, Boris Barja, Daniel A. Knopf, Natalie Kaifler, Holger Baars, Patric Seifert, Diego Villanueva, Cristofer Jimenez, Martin Radenz, Ronny Engelmann, Igor Veselovskii, and Félix Zamorano
Atmos. Chem. Phys., 22, 7417–7442, https://doi.org/10.5194/acp-22-7417-2022, https://doi.org/10.5194/acp-22-7417-2022, 2022
Short summary
Short summary
We present and discuss 2 years of long-term lidar observations of the largest stratospheric perturbation by wildfire smoke ever observed. The smoke originated from the record-breaking Australian fires in 2019–2020 and affects climate conditions and even the ozone layer in the Southern Hemisphere. The obvious link between dense smoke occurrence in the stratosphere and strong ozone depletion found in the Arctic and in the Antarctic in 2020 can be regarded as a new aspect of climate change.
Heike Kalesse-Los, Willi Schimmel, Edward Luke, and Patric Seifert
Atmos. Meas. Tech., 15, 279–295, https://doi.org/10.5194/amt-15-279-2022, https://doi.org/10.5194/amt-15-279-2022, 2022
Short summary
Short summary
It is important to detect the vertical distribution of cloud droplets and ice in mixed-phase clouds. Here, an artificial neural network (ANN) previously developed for Arctic clouds is applied to a mid-latitudinal cloud radar data set. The performance of this technique is contrasted to the Cloudnet target classification. For thick/multi-layer clouds, the machine learning technique is better at detecting liquid than Cloudnet, but if lidar data are available Cloudnet is at least as good as the ANN.
Martin Radenz, Johannes Bühl, Patric Seifert, Holger Baars, Ronny Engelmann, Boris Barja González, Rodanthi-Elisabeth Mamouri, Félix Zamorano, and Albert Ansmann
Atmos. Chem. Phys., 21, 17969–17994, https://doi.org/10.5194/acp-21-17969-2021, https://doi.org/10.5194/acp-21-17969-2021, 2021
Short summary
Short summary
This study brings together long-term ground-based remote-sensing observations of mixed-phase clouds at three key locations of aerosol–cloud interactions in the Northern and Southern Hemisphere midlatitudes. The findings contribute several new aspects on the nature of the excess of supercooled liquid clouds in the Southern Hemisphere, such as a long-term lidar-based estimate of ice-nucleating particle profiles as well as the effects of boundary layer coupling and gravity waves on ice formation.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
Short summary
Short summary
The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Kevin Ohneiser, Albert Ansmann, Alexandra Chudnovsky, Ronny Engelmann, Christoph Ritter, Igor Veselovskii, Holger Baars, Henriette Gebauer, Hannes Griesche, Martin Radenz, Julian Hofer, Dietrich Althausen, Sandro Dahlke, and Marion Maturilli
Atmos. Chem. Phys., 21, 15783–15808, https://doi.org/10.5194/acp-21-15783-2021, https://doi.org/10.5194/acp-21-15783-2021, 2021
Short summary
Short summary
The highlight of the lidar measurements during the 1-year MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition of the German icebreaker Polarstern (October 2019–October 2020) was the detection of a persistent, 10 km deep Siberian wildfire smoke layer in the upper troposphere and lower stratosphere (UTLS) from about 7–8 km to 17–18 km height that could potentially have impacted the record-breaking ozone depletion over the Arctic in the spring of 2020.
Jonas Witthuhn, Anja Hünerbein, Florian Filipitsch, Stefan Wacker, Stefanie Meilinger, and Hartwig Deneke
Atmos. Chem. Phys., 21, 14591–14630, https://doi.org/10.5194/acp-21-14591-2021, https://doi.org/10.5194/acp-21-14591-2021, 2021
Short summary
Short summary
Knowledge of aerosol–radiation interactions is important for understanding the climate system and for the renewable energy sector. Here, two complementary approaches are used to assess the consistency of the underlying aerosol properties and the resulting radiative effect in clear-sky conditions over Germany in 2015. An approach based on clear-sky models and broadband irradiance observations is contrasted to the use of explicit radiative transfer simulations using CAMS reanalysis data.
Ronny Engelmann, Albert Ansmann, Kevin Ohneiser, Hannes Griesche, Martin Radenz, Julian Hofer, Dietrich Althausen, Sandro Dahlke, Marion Maturilli, Igor Veselovskii, Cristofer Jimenez, Robert Wiesen, Holger Baars, Johannes Bühl, Henriette Gebauer, Moritz Haarig, Patric Seifert, Ulla Wandinger, and Andreas Macke
Atmos. Chem. Phys., 21, 13397–13423, https://doi.org/10.5194/acp-21-13397-2021, https://doi.org/10.5194/acp-21-13397-2021, 2021
Short summary
Short summary
A Raman lidar was operated aboard the icebreaker Polarstern during MOSAiC and monitored aerosol and cloud layers in the central Arctic up to 30 km height. The article provides an overview of the spectrum of aerosol profiling observations and shows aerosol–cloud interaction studies for liquid-water and ice clouds. A highlight was the detection of a 10 km deep wildfire smoke layer over the North Pole up to 17 km height from the fire season of 2019, which persisted over the whole winter period.
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
Short summary
Short summary
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.
Hartwig Deneke, Carola Barrientos-Velasco, Sebastian Bley, Anja Hünerbein, Stephan Lenk, Andreas Macke, Jan Fokke Meirink, Marion Schroedter-Homscheidt, Fabian Senf, Ping Wang, Frank Werner, and Jonas Witthuhn
Atmos. Meas. Tech., 14, 5107–5126, https://doi.org/10.5194/amt-14-5107-2021, https://doi.org/10.5194/amt-14-5107-2021, 2021
Short summary
Short summary
The SEVIRI instrument flown on the European geostationary Meteosat satellites acquires multi-spectral images at a relatively coarse pixel resolution of 3 × 3 km2, but it also has a broadband high-resolution visible channel with 1 × 1 km2 spatial resolution. In this study, the modification of an existing cloud property and solar irradiance retrieval to use this channel to improve the spatial resolution of its output products as well as the resulting benefits for applications are described.
Hannes J. Griesche, Kevin Ohneiser, Patric Seifert, Martin Radenz, Ronny Engelmann, and Albert Ansmann
Atmos. Chem. Phys., 21, 10357–10374, https://doi.org/10.5194/acp-21-10357-2021, https://doi.org/10.5194/acp-21-10357-2021, 2021
Short summary
Short summary
Heterogeneous ice formation in Arctic mixed-phase clouds under consideration of their surface-coupling state is investigated. Cloud phase and macrophysical properties were determined by means of lidar and cloud radar measurements, the coupling state, and cloud minimum temperature by radiosonde profiles. Above −15 °C cloud minimum temperature, surface-coupled clouds are more likely to contain ice by a factor of 2–6. By means of a literature survey, causes of the observed effects are discussed.
Albert Ansmann, Kevin Ohneiser, Rodanthi-Elisavet Mamouri, Daniel A. Knopf, Igor Veselovskii, Holger Baars, Ronny Engelmann, Andreas Foth, Cristofer Jimenez, Patric Seifert, and Boris Barja
Atmos. Chem. Phys., 21, 9779–9807, https://doi.org/10.5194/acp-21-9779-2021, https://doi.org/10.5194/acp-21-9779-2021, 2021
Short summary
Short summary
We present retrievals of tropospheric and stratospheric height profiles of particle mass, volume, surface area concentration of wildfire smoke layers, and related cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations. The new analysis scheme is applied to ground-based lidar observations of stratospheric Australian smoke over southern South America and to spaceborne lidar observations of tropospheric North American smoke.
Fabiola Ramelli, Jan Henneberger, Robert O. David, Johannes Bühl, Martin Radenz, Patric Seifert, Jörg Wieder, Annika Lauber, Julie T. Pasquier, Ronny Engelmann, Claudia Mignani, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 6681–6706, https://doi.org/10.5194/acp-21-6681-2021, https://doi.org/10.5194/acp-21-6681-2021, 2021
Short summary
Short summary
Orographic mixed-phase clouds are an important source of precipitation, but the ice formation processes within them remain uncertain. Here we investigate the origin of ice crystals in a mixed-phase cloud in the Swiss Alps using aerosol and cloud data from in situ and remote sensing observations. We found that ice formation primarily occurs in cloud top generating cells. Our results indicate that secondary ice processes are active in the feeder region, which can enhance orographic precipitation.
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
Short summary
Short summary
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.
Fabiola Ramelli, Jan Henneberger, Robert O. David, Annika Lauber, Julie T. Pasquier, Jörg Wieder, Johannes Bühl, Patric Seifert, Ronny Engelmann, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 5151–5172, https://doi.org/10.5194/acp-21-5151-2021, https://doi.org/10.5194/acp-21-5151-2021, 2021
Short summary
Short summary
Interactions between dynamics, microphysics and orography can enhance precipitation. Yet the exact role of these interactions is still uncertain. Here we investigate the role of low-level blocking and turbulence for precipitation by combining remote sensing and in situ observations. The observations show that blocked flow can induce the formation of feeder clouds and that turbulence can enhance hydrometeor growth, demonstrating the importance of local flow effects for orographic precipitation.
Martin Radenz, Patric Seifert, Holger Baars, Athena Augusta Floutsi, Zhenping Yin, and Johannes Bühl
Atmos. Chem. Phys., 21, 3015–3033, https://doi.org/10.5194/acp-21-3015-2021, https://doi.org/10.5194/acp-21-3015-2021, 2021
Cristofer Jimenez, Albert Ansmann, Ronny Engelmann, David Donovan, Aleksey Malinka, Jörg Schmidt, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 20, 15247–15263, https://doi.org/10.5194/acp-20-15247-2020, https://doi.org/10.5194/acp-20-15247-2020, 2020
Short summary
Short summary
A novel lidar method to study cloud microphysical properties (of liquid water clouds) and to study aerosol–cloud interaction (ACI) is developed and presented in this paper. In Part 1, the theoretical framework including an error analysis is given together with an overview of the aerosol information that the same lidar system can obtain. The ACI concept based on aerosol and cloud information is also explained. Applications of the proposed approach to lidar measurements are presented in Part 2.
Cristofer Jimenez, Albert Ansmann, Ronny Engelmann, David Donovan, Aleksey Malinka, Patric Seifert, Robert Wiesen, Martin Radenz, Zhenping Yin, Johannes Bühl, Jörg Schmidt, Boris Barja, and Ulla Wandinger
Atmos. Chem. Phys., 20, 15265–15284, https://doi.org/10.5194/acp-20-15265-2020, https://doi.org/10.5194/acp-20-15265-2020, 2020
Short summary
Short summary
Part 2 presents the application of the dual-FOV polarization lidar technique introduced in Part 1. A lidar system was upgraded with a second polarization telescope, and it was deployed at the southernmost tip of South America. A comparison with alternative remote sensing techniques and the evaluation of the aerosol–cloud–wind relation in a convective boundary layer in pristine marine conditions are presented in two case studies, demonstrating the potential of the approach for ACI studies.
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
Short summary
Short summary
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.
Martin Bauch, Thomas Labbé, Annabell Engel, and Patric Seifert
Clim. Past, 16, 2343–2358, https://doi.org/10.5194/cp-16-2343-2020, https://doi.org/10.5194/cp-16-2343-2020, 2020
Short summary
Short summary
The onset of Little Ice Age cooling around 1310 CE was preceded in Europe by a series of droughts in the first decade of the 14th century that were uniquely severe in the period 1200–1400. Based mainly on information from chronicles and other historical texts, we reconstructed the socioeconomic and cultural impact of these events but also a seesaw pattern of multiannual droughts in the Mediterranean and Europe north of the Alps that has remarkable resemblances to the 2018–2019 dry period.
Hannes J. Griesche, Patric Seifert, Albert Ansmann, Holger Baars, Carola Barrientos Velasco, Johannes Bühl, Ronny Engelmann, Martin Radenz, Yin Zhenping, and Andreas Macke
Atmos. Meas. Tech., 13, 5335–5358, https://doi.org/10.5194/amt-13-5335-2020, https://doi.org/10.5194/amt-13-5335-2020, 2020
Short summary
Short summary
In summer 2017, the research vessel Polarstern performed cruise PS106 to the Arctic north of Svalbard. In the frame of the cruise, remote-sensing observations of the atmosphere were performed on Polarstern to continuously monitor aerosol and clouds above the vessel. In our study, we present the deployed instrumentation and applied data analysis methods and provide case studies of the aerosol and cloud observations made during the cruise. Statistics of low-cloud occurrence are presented as well.
Cited articles
Achtert, P., O'Connor, E. J., Brooks, I. M., Sotiropoulou, G., Shupe, M. D., Pospichal, B., Brooks, B. J., and Tjernström, M.: Properties of Arctic liquid and mixed-phase clouds from shipborne Cloudnet observations during ACSE 2014, Atmos. Chem. Phys., 20, 14983–15002, https://doi.org/10.5194/acp-20-14983-2020, 2020. a
Anstey, J. A. and Shepherd, T. G.: High-latitude influence of the
quasi-biennial oscillation,
Q. J. Roy. Meteor. Soc., 140, 1–21, 2014. a
Bahramvash Shams, S., Walden, V. P., Petropavlovskikh, I., Tarasick, D., Kivi, R., Oltmans, S., Johnson, B., Cullis, P., Sterling, C. W., Thölix, L., and Errera, Q.: Variations in the vertical profile of ozone at four high-latitude Arctic sites from 2005 to 2017, Atmos. Chem. Phys., 19, 9733–9751, https://doi.org/10.5194/acp-19-9733-2019, 2019. a, b
Ballinger, T. J., Overland, J. E., Wang, M., Bhatt, U. S., Hanna, E.,
Hanssen-Bauer, I., Kim, S. J., Thoman, R. L., and Walsh, J. E.: Surface Air
Temperature, United States. National Oceanic and Atmospheric Administration. Office of Oceanic and Atmospheric Research. Pacific Marine Environmental Laboratory (U.S.) Cooperative Institute for Climate, Ocean, and Ecosystem Studies International Arctic Research Center University of Alaska Fairbanks. Geophysical Institute University of Lincoln Norske meteorologiske institutt/Norwegian Meteorological Institute Han’guk Haeyang Yŏn’guwŏn. Pusŏl Kŭkchi Yŏn’guso/Korea Polar Research Institute, https://doi.org/10.25923/gcw8-2z06, 2020. a
Barker, H. W., Stephens, G. L., Partain, P. T., Bergman, J. W., Bonnel, B.,
Campana, K., Clothiaux, E. E., Clough, S., Cusack, S., Delamere, J., Edwards,
J., Evans, K. F., Fouquart, Y., Freidenreich, S., Galin, V., Hou, Y., Kato,
S., Li, J., Mlawer, E., Morcrette, J.-J., O'Hirok, W., Räisänen, P.,
Ramaswamy, V., Ritter, B., Rozanov, E., Schlesinger, M., Shibata, K.,
Sporyshev, P., Sun, Z., Wendisch, M., Wood, N., and Yang, F.: Assessing 1D
Atmospheric Solar Radiative Transfer Models: Interpretation and Handling of
Unresolved Clouds, J. Climate, 16, 2676–2699,
https://doi.org/10.1175/1520-0442(2003)016<2676:ADASRT>2.0.CO;2, 2003. a
Barlakas, V., Deneke, H., and Macke, A.: The sub-adiabatic model as a concept for evaluating the representation and radiative effects of low-level clouds in a high-resolution atmospheric model, Atmos. Chem. Phys., 20, 303–322, https://doi.org/10.5194/acp-20-303-2020, 2020. a
Barrientos Velasco, C., Deneke, H., Griesche, H., Seifert, P., Engelmann, R., and Macke, A.: Spatiotemporal variability of solar radiation introduced by clouds over Arctic sea ice, Atmos. Meas. Tech., 13, 1757–1775, https://doi.org/10.5194/amt-13-1757-2020, 2020. a, b, c, d
Barrientos Velasco, C., Deneke, H., and Hünerbein, A.: Radiative transfer
simulations for the Arctic research expedition PS106, Zenodo [data set],
https://doi.org/10.5281/zenodo.5725382, 2021. a
Bright, R. M. and O'Halloran, T. L.: Developing a monthly radiative kernel for surface albedo change from satellite climatologies of Earth's shortwave radiation budget: CACK v1.0, Geosci. Model Dev., 12, 3975–3990, https://doi.org/10.5194/gmd-12-3975-2019, 2019. a
Bühl, J., Seifert, P., Myagkov, A., and Ansmann, A.: Measuring ice- and liquid-water properties in mixed-phase cloud layers at the Leipzig Cloudnet station, Atmos. Chem. Phys., 16, 10609–10620, https://doi.org/10.5194/acp-16-10609-2016, 2016. a
Chen, Y., Sun-Mack, S., Arduini, R., and Minnis, P.: Clear-sky and surface
narrowband albedo variations derived from VIRS and MODIS data, 12th
Conference on Cloud Physics, and 12th Conference on Atmospheric Radiation,
10–14 July 2006, Madison, WI, 2006. a
Christensen, M. W., Behrangi, A., L’ecuyer, T. S., Wood, N. B., Lebsock,
M. D., and Stephens, G. L.: Arctic Observation and Reanalysis Integrated
System: A New Data Product for Validation and Climate Study,
B. Am. Meteorol. Soc., 97, 907–916,
https://doi.org/10.1175/BAMS-D-14-00273.1, 2016. a
Clough, S., Shephard, M., Mlawer, E., Delamere, J., Iacono, M., Cady-Pereira,
K., Boukabara, S., and Brown, P.: Atmospheric radiative transfer modeling: a
summary of the AER codes,
J. Quant. Spectrosc. Ra., 91, 233–244, https://doi.org/10.1016/j.jqsrt.2004.05.058,
2005. a
Collins, W. D., Rasch, P. J., Eaton, B. E., Khattatov, B. V., Lamarque, J.-F.,
and Zender, C. S.: Simulating aerosols using a chemical transport model with
assimilation of satellite aerosol retrievals: Methodology for INDOEX, J. Geophys. Res.-Atmos., 106, 7313–7336,
https://doi.org/10.1029/2000JD900507, 2001. a
Curry, J. A., Schramm, J. L., Rossow, W. B., and Randall, D.: Overview of
Arctic Cloud and Radiation Characteristics, J. Climate, 9,
1731–1764, https://doi.org/10.1175/1520-0442(1996)009<1731:OOACAR>2.0.CO;2, 1996. a
de Boer, G., Collins, W. D., Menon, S., and Long, C. N.: Using surface remote sensors to derive radiative characteristics of Mixed-Phase Clouds: an example from M-PACE, Atmos. Chem. Phys., 11, 11937–11949, https://doi.org/10.5194/acp-11-11937-2011, 2011. a, b
Delamere, J. S., Clough, S. A., Payne, V. H., Mlawer, E. J., Turner, D. D., and
Gamache, R. R.: A far-infrared radiative closure study in the Arctic:
Application to water vapor, J. Geophys. Res.-Atmos.,
115, https://doi.org/10.1029/2009JD012968, 2010. a
Delanoë, J., Protat, A., Bouniol, D., Heymsfield, A., Bansemer, A., and
Brown, P.: The Characterization of Ice Cloud Properties from Doppler Radar
Measurements, J. Appl. Meteorol. Clim., 46, 1682–1698,
https://doi.org/10.1175/JAM2543.1, 2007. a
Deshler, T., Stübi, R., Schmidlin, F. J., Mercer, J. L., Smit, H. G. J., Johnson, B. J., Kivi, R., and Nardi, B.: Methods to homogenize electrochemical concentration cell (ECC) ozonesonde measurements across changes in sensing solution concentration or ozonesonde manufacturer, Atmos. Meas. Tech., 10, 2021–2043, https://doi.org/10.5194/amt-10-2021-2017, 2017. a
Devasthale, A., Sedlar, J., Kahn, B. H., Tjernström, M., Fetzer, E. J., Tian,
B., Teixeira, J., and Pagano, T. S.: A Decade of Spaceborne Observations of
the Arctic Atmosphere: Novel Insights from NASA’s AIRS Instrument, B. Am. Meteorol. Soc., 97, 2163–2176,
https://doi.org/10.1175/BAMS-D-14-00202.1, 2016. a
Dolinar, E. K., Dong, X., Xi, B., Jiang, J. H., and Loeb, N. G.: A clear-sky
radiation closure study using a one-dimensional radiative transfer model and
collocated satellite-surface-reanalysis data sets, J. Geophys. Res.-Atmos., 121, 13698–13714,
https://doi.org/10.1002/2016JD025823, 2016. a
Dong, X., Xi, B., Crosby, K., Long, C. N., Stone, R. S., and Shupe, M. D.: A 10
year climatology of Arctic cloud fraction and radiative forcing at Barrow,
Alaska, J. Geophys. Res.-Atmos., 115,
https://doi.org/10.1029/2009JD013489, 2010. a, b, c, d
Dong, X., Xi, B., Qiu, S., Minnis, P., Sun-Mack, S., and Rose, F.: A radiation
closure study of Arctic stratus cloud microphysical properties using the
collocated satellite-surface data and Fu-Liou radiative transfer model,
J. Geophys. Res.-Atmos., 121, 10175–10198,
https://doi.org/10.1002/2016JD025255, 2016. a, b, c, d, e
Doyle, J. G., Lesins, G., Thackray, C. P., Perro, C., Nott, G. J., Duck, T. J.,
Damoah, R., and Drummond, J. R.: Water vapor intrusions into the High Arctic
during winter, Geophys. Res. Lett., 38,
https://doi.org/10.1029/2011GL047493, 2011. a
Eastwood, S., Lavergne, T., and Tonboe, R.: Algorithm theoretical basis
document for the OSI SAF global reprocessed sea ice concentration product,
EUMETSAT Network Satellite Application Facilities, 28, https://osisaf-hl.met.no/sites/osisaf-hl.met.no/files/baseline_document/osisaf_cdop2_ss2_atbd_sea-ice-conc-reproc_v1p1.pdf (last access: 15 July 2022), 2014. a
Egerer, U., Ehrlich, A., Gottschalk, M., Griesche, H., Neggers, R. A. J., Siebert, H., and Wendisch, M.: Case study of a humidity layer above Arctic stratocumulus and potential turbulent coupling with the cloud top, Atmos. Chem. Phys., 21, 6347–6364, https://doi.org/10.5194/acp-21-6347-2021, 2021. a
Frisch, A. S., Feingold, G., Fairall, C. W., Uttal, T., and Snider, J. B.: On
cloud radar and microwave radiometer measurements of stratus cloud liquid
water profiles, J. Geophys. Res.-Atmos., 103,
23195–23197, https://doi.org/10.1029/98JD01827, 1998. a
Frisch, S., Shupe, M., Djalalova, I., Feingold, G., and Poellot, M.: The
Retrieval of Stratus Cloud Droplet Effective Radius with Cloud Radars,
J. Atmos. Ocean. Tech., 19, 835–842,
https://doi.org/10.1175/1520-0426(2002)019<0835:TROSCD>2.0.CO;2, 2002. a, b
Fu, Q. and Liou, K. N.: On the Correlated k-Distribution Method for Radiative
Transfer in Nonhomogeneous Atmospheres, J. Atmos. Sci.,
49, 2139–2156, https://doi.org/10.1175/1520-0469(1992)049<2139:OTCDMF>2.0.CO;2, 1992. a
Griesche, H., Seifert, P., Engelmann, R., Radenz, M., and Bühl,
J.: Cloudnet target classification during PS106, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.919463, 2020a. a
Griesche, H., Seifert, P., Engelmann, R., Radenz, M., and Bühl,
J.: Cloudnet IWC during PS106, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.919452,
2020b. a
Griesche, H., Seifert, P., Engelmann, R., Radenz, M., and Bühl,
J.: Cloudnet LWC during PS106, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.919383,
2020c. a
Griesche, H., Seifert, P., Engelmann, R., Radenz, M., and Bühl,
J.: Cloudnet ice particles effective radius during PS106, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.919386, 2020d. a
Griesche, H., Seifert, P., Engelmann, R., Radenz, M., and Bühl,
J.: Cloudnet liquid droplet effective radius during PS106, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.919399, 2020e. a
Griesche, H., Seifert, P., Engelmann, R., Radenz, M., and Bühl,
J.: OCEANET-ATMOSPHERE low level stratus clouds during PS106, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.920246, 2020f. a
Griesche, H. J., Seifert, P., Ansmann, A., Baars, H., Barrientos Velasco, C., Bühl, J., Engelmann, R., Radenz, M., Zhenping, Y., and Macke, A.: Application of the shipborne remote sensing supersite OCEANET for profiling of Arctic aerosols and clouds during Polarstern cruise PS106, Atmos. Meas. Tech., 13, 5335–5358, https://doi.org/10.5194/amt-13-5335-2020, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r
Gröbner, J. and Wacker, S.: Pyrgeometer Calibration Procedure at the
PMOD/WRC-IRS, World Meteorological Organization,
https://library.wmo.int/doc_num.php?explnum_id=7365 (last access: 13 July 2022), 2015. a
Gröbner, J., Reda, I., Wacker, S., Nyeki, S., Behrens, K., and Gorman, J.: A
new absolute reference for atmospheric longwave irradiance measurements with
traceability to SI units, J. Geophys. Res.-Atmos., 119,
7083–7090, https://doi.org/10.1002/2014JD021630, 2014. a
Gupta, S. K., Kratz, D. P., Stackhouse, Paul W., J., Wilber, A. C., Zhang, T.,
and Sothcott, V. E.: Improvement of Surface Longwave Flux Algorithms Used in
CERES Processing, J. Appl. Meteorol. Clim., 49,
1579–1589, https://doi.org/10.1175/2010JAMC2463.1, 2010. a
Hanschmann, T., Deneke, H., Roebeling, R., and Macke, A.: Evaluation of the shortwave cloud radiative effect over the ocean by use of ship and satellite observations, Atmos. Chem. Phys., 12, 12243–12253, https://doi.org/10.5194/acp-12-12243-2012, 2012. a, b
Hartmann, D. L. and Ceppi, P.: Trends in the CERES Dataset, 2000–13: The
Effects of Sea Ice and Jet Shifts and Comparison to Climate Models, J. Climate, 27, 2444–2456, https://doi.org/10.1175/JCLI-D-13-00411.1, 2014. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A.,
Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers,
D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on
pressure levels from 1979 to present, Copernicus Climate Change Service (C3S)
Climate Data Store (CDS) [data set],
https://doi.org/10.24381/cds.bd0915c6, 2018a. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A.,
Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers,
D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on
single levels from 1979 to present, Copernicus Climate Change Service (C3S)
Climate Data Store (CDS) [data set],
https://doi.org/10.24381/cds.adbb2d47, 2018b. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons,
A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati,
G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M.,
Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P.,
Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global
reanalysis, Q. J. Roy. Meteor. Soc., 146,
1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hirahara, S., Balmaseda, M. A., de Boisseson, E., and Hersbach, H.: 26 sea
surface temperature and sea ice concentration for ERA5, Eur. Centre Medium
Range Weather Forecasts, Berkshire, UK, ERA Rep. Ser, 26, https://www.ecmwf.int/sites/default/files/elibrary/2016/16555-sea-surface-temperature-and-sea-ice-concentration-era5.pdf (last access: 15 July 2022), 2016. a
Hogan, R. and Connor, E.: Facilitating cloud radar and lidar algorithms: the
Cloudnet Instrument Synergy/Target Categorization product, http://www.met.rdg.ac.uk/~swrhgnrj/publications/categorization.pdf
(last access: 13 July 2022),
2004. a
Hogan, R. J., Mittermaier, M. P., and Illingworth, A. J.: The Retrieval of Ice
Water Content from Radar Reflectivity Factor and Temperature and Its Use in
Evaluating a Mesoscale Model, J. Appl. Meteorol. Clim.,
45, 301–317, https://doi.org/10.1175/JAM2340.1, 2006. a, b
Hogan, R. J., O'Connor, E. J., and Illingworth, A. J.: Verification of
cloud-fraction forecasts, Q. J. Roy. Meteor. Soc., 135, 1494–1511, https://doi.org/10.1002/qj.481, 2009. a
Hori, M., Aoki, T., Tanikawa, T., Motoyoshi, H., Hachikubo, A., Sugiura, K.,
Yasunari, T. J., Eide, H., Storvold, R., Nakajima, Y., and Takahashi, F.:
In-situ measured spectral directional emissivity of snow and ice in the
8–14 µm atmospheric window, Remote Sens. Environ., 100, 486–502, https://doi.org/10.1016/j.rse.2005.11.001, 2006. a
Hu, Y. X. and Stamnes, K.: An Accurate Parameterization of the Radiative
Properties of Water Clouds Suitable for Use in Climate Models, J. Climate, 6, 728–742, https://doi.org/10.1175/1520-0442(1993)006<0728:AAPOTR>2.0.CO;2,
1993. a
Huang, Y., Dong, X., Xi, B., Dolinar, E. K., Stanfield, R. E., and Qiu, S.:
Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation
Properties Using Satellite Surface Observations, J. Climate, 30,
8007–8029, https://doi.org/10.1175/JCLI-D-16-0722.1, 2017. a, b, c
Illingworth, A. J., Hogan, R. J., O'Connor, E., Bouniol, D., Brooks, M. E.,
Delanoë, J., Donovan, D. P., Eastment, J. D., Gaussiat, N., Goddard, J.
W. F., Haeffelin, M., Baltink, H. K., Krasnov, O. A., Pelon, J., Piriou,
J.-M., Protat, A., Russchenberg, H. W. J., Seifert, A., Tompkins, A. M., van
Zadelhoff, G.-J., Vinit, F., Willén, U., Wilson, D. R., and Wrench, C. L.:
Cloudnet, B. Am. Meteorol. Soc., 88, 883–898,
https://doi.org/10.1175/BAMS-88-6-883, 2007. a, b, c, d, e, f
Intrieri, J. M., Fairall, C. W., Shupe, M. D., Persson, P. O. G., Andreas,
E. L., Guest, P. S., and Moritz, R. E.: An annual cycle of Arctic surface
cloud forcing at SHEBA, J. Geophys. Res.-Oceans, 107, SHE
13-1–SHE 13-14, https://doi.org/10.1029/2000JC000439, 2002. a, b
Johannessen, O. M., Bengtsson, L., Miles, M. W., Kuzmina, S. I., Semenov,
V. A., Alekseev, G. V., Nagurnyi, A. P., Zakharov, V. F., Bobylev, L. P.,
Pettersson, L. H., Hasselmann, K., and Cattle, H. P.: Arctic climate change:
observed and modelled temperature and sea-ice variability, Tellus A, 56,
328–341, https://doi.org/10.1111/j.1600-0870.2004.00060.x, 2004. a
Kalesse, H., Vogl, T., Paduraru, C., and Luke, E.: Development and validation of a supervised machine learning radar Doppler spectra peak-finding algorithm, Atmos. Meas. Tech., 12, 4591–4617, https://doi.org/10.5194/amt-12-4591-2019, 2019. a
Kalisch, J. and Macke, A.: Radiative budget and cloud radiative effect over the Atlantic from ship-based observations, Atmos. Meas. Tech., 5, 2391–2401, https://doi.org/10.5194/amt-5-2391-2012, 2012. a, b
Kanitz, T., Ansmann, A., Engelmann, R., and Althausen, D.: North-south cross
sections of the vertical aerosol distribution over the Atlantic Ocean from
multiwavelength Raman/polarization lidar during Polarstern cruises, J. Geophys. Res.-Atmos., 118, 2643–2655,
https://doi.org/10.1002/jgrd.50273, 2013. a, b
Karlsson, K.-G., Anttila, K., Trentmann, J., Stengel, M., Fokke Meirink, J., Devasthale, A., Hanschmann, T., Kothe, S., Jääskeläinen, E., Sedlar, J., Benas, N., van Zadelhoff, G.-J., Schlundt, C., Stein, D., Finkensieper, S., Håkansson, N., and Hollmann, R.: CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data, Atmos. Chem. Phys., 17, 5809–5828, https://doi.org/10.5194/acp-17-5809-2017, 2017. a
Kato, S., Rose, F. G., Rutan, D. A., Thorsen, T. J., Loeb, N. G., Doelling,
D. R., Huang, X., Smith, W. L., Su, W., and Ham, S.-H.: Surface Irradiances
of Edition 4.0 Clouds and the Earth’s Radiant Energy System (CERES) Energy
Balanced and Filled (EBAF) Data Product, J. Climate, 31, 4501–4527,
https://doi.org/10.1175/JCLI-D-17-0523.1, 2018. a
Kay, J. E. and L'Ecuyer, T.: Observational constraints on Arctic Ocean clouds
and radiative fluxes during the early 21st century, J. Geophys. Res.-Atmos., 118, 7219–7236,
https://doi.org/10.1002/jgrd.50489, 2013. a, b, c
Kay, J. E., L'Ecuyer, T., Chepfer, H., Loeb, N., Morrison, A., and Cesana, G.:
Recent Advances in Arctic Cloud and Climate Research,
Current Climate Change Reports, 2, 159–169, https://doi.org/10.1007/s40641-016-0051-9, 2016. a, b
Key, J.: Streamer user's guide, Tech. Rep., Boston University, 96–01, 85, https://geocryos.ssec.wisc.edu/streamer/userman.pdf (last access: 15 July 2022), 1996. a
Knudsen, E. M., Heinold, B., Dahlke, S., Bozem, H., Crewell, S., Gorodetskaya, I. V., Heygster, G., Kunkel, D., Maturilli, M., Mech, M., Viceto, C., Rinke, A., Schmithüsen, H., Ehrlich, A., Macke, A., Lüpkes, C., and Wendisch, M.: Meteorological conditions during the ACLOUD/PASCAL field campaign near Svalbard in early summer 2017, Atmos. Chem. Phys., 18, 17995–18022, https://doi.org/10.5194/acp-18-17995-2018, 2018. a, b
Lanconelli, C., Busetto, M., Dutton, E. G., König-Langlo, G., Maturilli, M., Sieger, R., Vitale, V., and Yamanouchi, T.: Polar baseline surface radiation measurements during the International Polar Year 2007–2009, Earth Syst. Sci. Data, 3, 1–8, https://doi.org/10.5194/essd-3-1-2011, 2011. a
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F.,
Kato, S., Manalo-Smith, N., and Wong, T.: Toward Optimal Closure of the
Earth's Top-of-Atmosphere Radiation Budget, J. Climate, 22,
748–766, https://doi.org/10.1175/2008JCLI2637.1, 2009. a
Löhnert, U. and Crewell, S.: Accuracy of cloud liquid water path from
ground-based microwave radiometry 1. Dependency on cloud model statistics,
Radio Sci., 38, https://doi.org/10.1029/2002RS002654, 2003. a, b
Mace, G. G., Benson, S., and Kato, S.: Cloud radiative forcing at the
Atmospheric Radiation Measurement Program Climate Research Facility: 2.
Vertical redistribution of radiant energy by clouds, J. Geophys. Res.-Atmos., 111, https://doi.org/10.1029/2005JD005922, 2006. a
Macke, A. and Flores, H.: The Expeditions PS106/1 and 2 of the Research Vessel
POLARSTERN to the Arctic Ocean in 2017, Berichte zur Polar- und
Meeresforschung, 714, https://doi.org/10.2312/BzPM_0714_2017, 2018. a, b
Markowicz, K., Lisok, J., and Xian, P.: Simulation of long-term direct aerosol
radiative forcing over the arctic within the framework of the iAREA project,
Atmos. Environ., 244, 117882, https://doi.org/10.1016/j.atmosenv.2020.117882, 2021. a
Meredith, M., Sommerkorn, M., Cassotta, S., Derksen, C., Ekaykin, A., Hollowed,
A., Kofinas, G., Mackintosh, A., Melbourne-Thomas, J., Muelbert, M.,
Ottersen, G., Pritchard, H., and Schuur, E.: Polar Regions, in: IPCC Special
Report on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H.-O.,
Roberts, D. C., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E.,
Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N. M.,
Cambridge University Press,
https://www.ipcc.ch/srocc/chapter/chapter-3-2/ (last access: 13 July 2022), 2019. a
Miller, N. B., Shupe, M. D., Cox, C. J., Walden, V. P., Turner, D. D., and
Steffen, K.: Cloud Radiative Forcing at Summit, Greenland, J. Climate, 28, 6267–6280, https://doi.org/10.1175/JCLI-D-15-0076.1, 2015. a, b, c, d
Minnis, P., Sun-Mack, S., Smith Jr., W. L., Hong, G., and Chen, Y.: Advances in
neural network detection and retrieval of multilayer clouds for CERES using
multispectral satellite data, in: Remote Sensing of Clouds and the Atmosphere
XXIV, 11152, p. 1115202, International Society for Optics and Photonics,
2019. a
Minnis, P., Sun-Mack, S., Chen, Y., Chang, F., Yost, C. R., Smith,
W. L., Heck, P. W., Arduini, R. F., Bedka, S. T., Yi, Y., Hong, G.,
Jin, Z., Painemal, D., Palikonda, R., Scarino, B. R., Spangenberg,
D. A., Smith, R. A., Trepte, Q. Z., Yang, P., and Xie, Y.: CERES
MODIS Cloud Product Retrievals for Edition 4–Part I: Algorithm Changes, IEEE
T. Geosci. Remote, 11152, 1–37, https://doi.org/10.1117/12.2532931, 2020. a, b, c, d, e, f, g, h, i, j, k, l
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.:
Radiative transfer for inhomogeneous atmospheres: RRTM, a validated
correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102, 16663–16682, https://doi.org/10.1029/97JD00237, 1997. a
Morrison, H., de Boer, G., Feingold, G., Harrington, J., Shupe, M. D., and
Sulia, K.: Resilience of persistent Arctic mixed-phase clouds, Nat.
Geosci., 5, 11–17, https://doi.org/10.1038/ngeo1332, 2012. a, b
NASA/LARC/SD/ASDC: CERES and GEO-Enhanced TOA, Within-Atmosphere and Surface
Fluxes, Clouds and Aerosols 1-Hourly Terra-Aqua Edition4A, Atmospheric Science Data Center [data set],
https://doi.org/10.5067/TERRA+AQUA/CERES/SYN1DEG-1HOUR_L3.004A,
2017. a
Nomokonova, T., Ebell, K., Löhnert, U., Maturilli, M., Ritter, C., and O'Connor, E.: Statistics on clouds and their relation to thermodynamic conditions at Ny-Ålesund using ground-based sensor synergy, Atmos. Chem. Phys., 19, 4105–4126, https://doi.org/10.5194/acp-19-4105-2019, 2019. a, b
Palm, S. P., Strey, S. T., Spinhirne, J., and Markus, T.: Influence of Arctic
sea ice extent on polar cloud fraction and vertical structure and
implications for regional climate, J. Geophys. Res.-Atmos., 115, https://doi.org/10.1029/2010JD013900, 2010. a
Pohl, C., Istomina, L., Tietsche, S., Jäkel, E., Stapf, J., Spreen, G., and Heygster, G.: Broadband albedo of Arctic sea ice from MERIS optical data, The Cryosphere, 14, 165–182, https://doi.org/10.5194/tc-14-165-2020, 2020. a
Radenz, M., Bühl, J., Seifert, P., Griesche, H., and Engelmann, R.: peakTree: a framework for structure-preserving radar Doppler spectra analysis, Atmos. Meas. Tech., 12, 4813–4828, https://doi.org/10.5194/amt-12-4813-2019, 2019. a
Randel, W. J. and Wu, F.: Cooling of the Arctic and Antarctic polar
stratospheres due to ozone depletion, J. Climate, 12, 1467–1479,
1999. a
Rastak, N., Silvergren, S., Zieger, P., Wideqvist, U., Ström, J., Svenningsson, B., Maturilli, M., Tesche, M., Ekman, A. M. L., Tunved, P., and Riipinen, I.: Seasonal variation of aerosol water uptake and its impact on the direct radiative effect at Ny-Ålesund, Svalbard, Atmos. Chem. Phys., 14, 7445–7460, https://doi.org/10.5194/acp-14-7445-2014, 2014. a
Riihelä, A., Key, J. R., Meirink, J. F., Kuipers Munneke, P., Palo, T., and
Karlsson, K.-G.: An intercomparison and validation of satellite-based surface
radiative energy flux estimates over the Arctic, J. Geophys. Res.-Atmos., 122, 4829–4848, https://doi.org/10.1002/2016JD026443, 2017. a, b, c, d, e, f
Rinke, A., Segger, B., Crewell, S., Maturilli, M., Naakka, T., Nygård, T.,
Vihma, T., Alshawaf, F., Dick, G., Wickert, J., and Keller, J.: Trends of vertically
integrated water vapor over the Arctic during 1979–2016: Consistent
moistening all over?, J. Climate, 32, 6097–6116, 2019. a
Rose, F. G., Rutan, D. A., Charlock, T., Smith, G. L., and Kato, S.: An
Algorithm for the Constraining of Radiative Transfer Calculations to
CERES-Observed Broadband Top-of-Atmosphere Irradiance, J.
Atmos. Ocean. Tech., 30, 1091–1106,
https://doi.org/10.1175/JTECH-D-12-00058.1, 2013. a
Rutan, D. A., Kato, S., Doelling, D. R., Rose, F. G., Nguyen, L. T., Caldwell,
T. E., and Loeb, N. G.: CERES Synoptic Product: Methodology and Validation
of Surface Radiant Flux, J. Atmos. Ocean. Tech., 32,
1121–1143, https://doi.org/10.1175/JTECH-D-14-00165.1, 2015. a, b, c
Schmithüsen, H.: Upper air soundings during POLARSTERN cruise PS106/1
(ARK-XXXI/1.1), PANGAEA, https://doi.org/10.1594/PANGAEA.882736, 2017a. a
Schmithüsen, H.: Upper air soundings during POLARSTERN cruise PS106/2
(ARK-XXXI/1.2), PANGAEA, https://doi.org/10.1594/PANGAEA.882843, 2017b. a
Sedlar, J. and Devasthale, A.: Clear-sky thermodynamic and radiative anomalies
over a sea ice sensitive region of the Arctic, J. Geophys.
Res.-Atmos., 117, 1–11, https://doi.org/10.1029/2012JD017754, 2012. a
Sedlar, J. and Tjernström, M.: Clouds, warm air, and a climate cooling signal
over the summer Arctic, Geophy. Res. Lett., 44, 1095–1103,
https://doi.org/10.1002/2016GL071959, 2017. a
Sedlar, J., Tjernström, M., Mauritsen, T., Shupe, M. D., Brooks, I. M.,
Persson, P. O. G., Birch, C. E., Leck, C., Sirevaag, A., and Nicolaus, M.: A
transitioning Arctic surface energy budget: the impacts of solar zenith
angle, surface albedo and cloud radiative forcing, Clim. Dynam., 37,
1643–1660, 2011. a, b, c
Serreze, M. C. and Barry, R. G.: Processes and impacts of Arctic amplification:
A research synthesis, Global Planet. Change, 77, 85–96,
https://doi.org/10.1016/j.gloplacha.2011.03.004, 2011. a
Shupe, M. D. and Intrieri, J. M.: Cloud Radiative Forcing of the Arctic
Surface: The Influence of Cloud Properties, Surface Albedo, and Solar Zenith
Angle, J. Climate, 17, 616–628,
https://doi.org/10.1175/1520-0442(2004)017<0616:CRFOTA>2.0.CO;2, 2004. a
Shupe, M. D., Uttal, T., and Matrosov, S. Y.: Arctic Cloud Microphysics
Retrievals from Surface-Based Remote Sensors at SHEBA, J. Appl.
Meteorol., 44, 1544–1562, https://doi.org/10.1175/JAM2297.1, 2005. a
Shupe, M. D., Walden, V. P., Eloranta, E., Uttal, T., Campbell, J. R.,
Starkweather, S. M., and Shiobara, M.: Clouds at Arctic Atmospheric
Observatories. Part I: Occurrence and Macrophysical Properties, J. Appl. Meteorol. Clim., 50, 626–644,
https://doi.org/10.1175/2010JAMC2467.1, 2011. a
Shupe, M. D., Turner, D. D., Zwink, A., Thieman, M. M., Mlawer, E. J., and
Shippert, T.: Deriving Arctic Cloud Microphysics at Barrow, Alaska:
Algorithms, Results, and Radiative Closure, J. Appl. Meteorol. Clim., 54, 1675–1689, https://doi.org/10.1175/JAMC-D-15-0054.1, 2015. a, b
Shupe, M. D., Rex, M., Blomquist, B., Persson, P. O. G., Schmale, J., Uttal,
T., Althausen, D., Angot, H., Archer, S., Bariteau, L., Beck, I., Bilberry,
J., Bucci, S., Buck, C., Boyer, M., Brasseur, Z., Brooks, I. M., Calmer, R.,
Cassano, J., Castro, V., Chu, D., Costa, D., Cox, C. J., Creamean, J.,
Crewell, S., Dahlke, S., Damm, E., de Boer, G., Deckelmann, H., Dethloff, K.,
Dütsch, M., Ebell, K., Ehrlich, A., Ellis, J., Engelmann, R., Fong, A. A.,
Frey, M. M., Gallagher, M. R., Ganzeveld, L., Gradinger, R., Graeser, J.,
Greenamyer, V., Griesche, H., Griffiths, S., Hamilton, J., Heinemann, G.,
Helmig, D., Herber, A., Heuzé, C., Hofer, J., Houchens, T., Howard, D.,
Inoue, J., Jacobi, H.-W., Jaiser, R., Jokinen, T., Jourdan, O., Jozef, G.,
King, W., Kirchgaessner, A., Klingebiel, M., Krassovski, M., Krumpen, T.,
Lampert, A., Landing, W., Laurila, T., Lawrence, D., Lonardi, M., Loose, B.,
Lüpkes, C., Maahn, M., Macke, A., Maslowski, W., Marsay, C., Maturilli, M.,
Mech, M., Morris, S., Moser, M., Nicolaus, M., Ortega, P., Osborn, J.,
Pätzold, F., Perovich, D. K., Petäjä, T., Pilz, C., Pirazzini, R., Posman,
K., Powers, H., Pratt, K. A., Preußer, A., Quéléver, L., Radenz, M., Rabe,
B., Rinke, A., Sachs, T., Schulz, A., Siebert, H., Silva, T., Solomon, A.,
Sommerfeld, A., Spreen, G., Stephens, M., Stohl, A., Svensson, G., Uin, J.,
Viegas, J., Voigt, C., von der Gathen, P., Wehner, B., Welker, J. M.,
Wendisch, M., Werner, M., Xie, Z., and Yue, F.: Overview of the MOSAiC
expedition–Atmosphere, Elementa: Science of the Anthropocene, 10,
00060, https://doi.org/10.1525/elementa.2021.00060, 2022. a
Soden, B. J., Held, I. M., Colman, R., Shell, K. M., Kiehl, J. T., and Shields,
C. A.: Quantifying Climate Feedbacks Using Radiative Kernels, J. Climate, 21, 3504–3520, https://doi.org/10.1175/2007JCLI2110.1, 2008. a
Stapf, J., Ehrlich, A., Jäkel, E., Lüpkes, C., and Wendisch, M.: Reassessment of shortwave surface cloud radiative forcing in the Arctic: consideration of surface-albedo–cloud interactions, Atmos. Chem. Phys., 20, 9895–9914, https://doi.org/10.5194/acp-20-9895-2020, 2020. a, b, c
Stapf, J., Ehrlich, A., Lüpkes, C., and Wendisch, M.: Radiative energy budget and cloud radiative forcing in the daytime marginal sea ice zone during Arctic spring and summer, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2021-279, 2021. a
Stubenrauch, C. J., Rossow, W. B., Kinne, S., Ackerman, S., Cesana, G.,
Chepfer, H., Girolamo, L. D., Getzewich, B., Guignard, A., Heidinger, A.,
Maddux, B. C., Menzel, W. P., Minnis, P., Pearl, C., Platnick, S., Poulsen,
C., Riedi, J., Sun-Mack, S., Walther, A., Winker, D., Zeng, S., and Zhao, G.:
Assessment of Global Cloud Datasets from Satellites: Project and Database
Initiated by the GEWEX Radiation Panel, B. Am. Meteorol. Soc., 94, 1031–1049, https://doi.org/10.1175/BAMS-D-12-00117.1,
2013. a
Sun-Mack, S., Chen, Y., Arduini, R., and Minnis, P.: Clear-sky narrowband
albedo variations derived from VIRS and MODIS data, 13th Conference on
Satellite Meteorology and Oceanography, 20–23 September 2004, Nortfolk Waterside Marriot in Norfolk, Virginian, USA, p. 6, 2006. a
Sun-Mack, S., Minnis, P., Chen, Y., Doelling, D. R., Scarino, B. R.,
Haney, C. O., and Smith, W. L.: Calibration Changes to Terra MODIS
Collection-5 Radiances for CERES Edition 4 Cloud Retrievals, IEEE
T. Geosci. Remote, 56, 6016–6032,
https://doi.org/10.1109/TGRS.2018.2829902, 2018. a
Tan, I. and Storelvmo, T.: Evidence of Strong Contributions From Mixed-Phase
Clouds to Arctic Climate Change, Geophys. Res. Lett., 46,
2894–2902, https://doi.org/10.1029/2018GL081871, 2019. a, b
Tjernström, M., Shupe, M. D., Brooks, I. M., Persson, P. O. G., Prytherch,
J., Salisbury, D. J., Sedlar, J., Achtert, P., Brooks, B. J., Johnston,
P. E., Sotiropoulou, G., and Wolfe, D.: Warm-air advection, air mass
transformation and fog causes rapid ice melt, Geophys. Res. Lett.,
42, 5594–5602, https://doi.org/10.1002/2015GL064373, 2015. a
Tjernström, M., Shupe, M. D., Brooks, I. M., Achtert, P., Prytherch, J., and
Sedlar, J.: Arctic Summer Airmass Transformation, Surface Inversions, and the
Surface Energy Budget, J. Climate, 32, 769–789,
https://doi.org/10.1175/JCLI-D-18-0216.1, 2019. a
Trepte, Q. Z., Minnis, P., Sun-Mack, S., Yost, C. B., Chen, Y., Jin, Z., Hong,
G., Chang, F.-L., Smith Jr., W. L., Bedka, K. M., and Chee, T. L.: Global
cloud detection for CERES Edition 4 using Terra and Aqua MODIS data, IEEE
T. Geosci. Remote, 57, 9410–9449, https://doi.org/10.1109/TGRS.2019.2926620,
2019. a
Turner, D. D.: Improved ground-based liquid water path retrievals using a
combined infrared and microwave approach, J. Geophys. Res.-Atmos., 112, https://doi.org/10.1029/2007JD008530, 2007. a
Uttal, T., Curry, J. A., McPhee, M. G., Perovich, D. K., Moritz, R. E.,
Maslanik, J. A., Guest, P. S., Stern, H. L., Moore, J. A., Turenne, R.,
Heiberg, A., Serreze, M. C., Wylie, D. P., Persson, O. G., Paulson, C. A.,
Halle, C., Morison, J. H., Wheeler, P. A., Makshtas, A., Welch, H., Shupe,
M. D., Intrieri, J. M., Stamnes, K., Lindsey, R. W., Pinkel, R., Pegau,
W. S., Stanton, T. P., and Grenfeld, T. C.: Surface Heat Budget of the Arctic
Ocean, B. Am. Meteorol. Soc., 83, 255–276,
https://doi.org/10.1175/1520-0477(2002)083<0255:SHBOTA>2.3.CO;2, 2002. a
Viceto, C., Gorodetskaya, I. V., Rinke, A., Maturilli, M., Rocha, A., and Crewell, S.: Atmospheric rivers and associated precipitation patterns during the ACLOUD and PASCAL campaigns near Svalbard (May–June 2017): case studies using observations, reanalyses, and a regional climate model, Atmos. Chem. Phys., 22, 441–463, https://doi.org/10.5194/acp-22-441-2022, 2022. a
Walsh, J. E., Chapman, W. L., and Portis, D. H.: Arctic Cloud Fraction and
Radiative Fluxes in Atmospheric Reanalyses, J. Climate, 22,
2316–2334, https://doi.org/10.1175/2008JCLI2213.1, 2009. a
Wang, W., Zender, C. S., van As, D., and Miller, N. B.: Spatial Distribution of
Melt Season Cloud Radiative Effects Over Greenland: Evaluating Satellite
Observations, Reanalyses, and Model Simulations Against In Situ Measurements,
J. Geophys. Res.-Atmos., 124, 57–71,
https://doi.org/10.1029/2018JD028919, 2019. a
Wendisch, M., Pilewskie, P., Pommier, J., Howard, S., Yang, P., Heymsfield,
A. J., Schmitt, C. G., Baumgardner, D., and Mayer, B.: Impact of cirrus
crystal shape on solar spectral irradiance: A case study for subtropical
cirrus, J. Geophys. Res.-Atmos., 110,
https://doi.org/10.1029/2004JD005294, 2005. a
Wendisch, M., Macke, A., Ehrlich, A., Lüpkes, C., Mech, M., Chechin, D.,
Dethloff, K., Velasco, C. B., Bozem, H., Brückner, M., Clemen, H.-C.,
Crewell, S., Donth, T., Dupuy, R., Ebell, K., Egerer, U., Engelmann, R.,
Engler, C., Eppers, O., Gehrmann, M., Gong, X., Gottschalk, M., Gourbeyre,
C., Griesche, H., Hartmann, J., Hartmann, M., Heinold, B., Herber, A.,
Herrmann, H., Heygster, G., Hoor, P., Jafariserajehlou, S., Jäkel, E.,
Järvinen, E., Jourdan, O., Kästner, U., Kecorius, S., Knudsen, E. M.,
Köllner, F., Kretzschmar, J., Lelli, L., Leroy, D., Maturilli, M., Mei, L.,
Mertes, S., Mioche, G., Neuber, R., Nicolaus, M., Nomokonova, T., Notholt,
J., Palm, M., van Pinxteren, M., Quaas, J., Richter, P., Ruiz-Donoso, E.,
Schäfer, M., Schmieder, K., Schnaiter, M., Schneider, J., Schwarzenböck,
A., Seifert, P., Shupe, M. D., Siebert, H., Spreen, G., Stapf, J., Stratmann,
F., Vogl, T., Welti, A., Wex, H., Wiedensohler, A., Zanatta, M., and
Zeppenfeld, S.: The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multiplatform
Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic
Amplification, B. Am. Meteorol. Soc., 100,
841–871, https://doi.org/10.1175/BAMS-D-18-0072.1, 2019. a
Winton, M.: Amplified Arctic climate change: What does surface albedo feedback
have to do with it?, Geophys. Res. Lett., 33,
https://doi.org/10.1029/2005GL025244, 2006. a
Witthuhn, J., Hünerbein, A., Filipitsch, F., Wacker, S., Meilinger, S., and Deneke, H.: Aerosol properties and aerosol–radiation interactions in clear-sky conditions over Germany, Atmos. Chem. Phys., 21, 14591–14630, https://doi.org/10.5194/acp-21-14591-2021, 2021. a, b
Wu, F. and Fu, C.: Assessment of GEWEX/SRB version 3.0 monthly global radiation
dataset over China, Meteorol. Atmos. Phys., 112, 155–166, 2011. a
Wyser, K., Jones, C., Du, P., Girard, E., Willen, U., Cassano, J., Christensen,
J., Curry, J. A., Dethloff, K., Haugen, J.-E., Jacob, D., Koltzow, M., Laprise, R., Lynch, A., Pfeifer, S., Rinke, A., Serreze, M., Shaw, M. J., Tjernström, M., and Zagar, M.: An evaluation of
Arctic cloud and radiation processes during the SHEBA year: simulation
results from eight Arctic regional climate models, Clim. Dynam., 30,
203–223, 2008. a, b
Yost, C. R., Minnis, P., Sun-Mack, S., Chen, Y., and Smith, W. L.:
CERES MODIS Cloud Product Retrievals for Edition 4–Part II: Comparisons to
CloudSat and CALIPSO, IEEE T. Geosci. Remote, 5,
3695–3724,
https://doi.org/10.1109/TGRS.2020.3015155, 2020. a, b
Young, D. F., Minnis, P., Doelling, D. R., Gibson, G. G., and Wong, T.:
Temporal Interpolation Methods for the Clouds and the Earth’s Radiant
Energy System (CERES) Experiment, J. Appl. Meteorol., 37,
572–590, https://doi.org/10.1175/1520-0450(1998)037<0572:TIMFTC>2.0.CO;2, 1998. a
Zib, B. J., Dong, X., Xi, B., and Kennedy, A.: Evaluation and Intercomparison
of Cloud Fraction and Radiative Fluxes in Recent Reanalyses over the Arctic
Using BSRN Surface Observations, J. Climate, 25, 2291–2305,
https://doi.org/10.1175/JCLI-D-11-00147.1, 2012. a
Short summary
This article describes an intercomparison of radiative fluxes and cloud properties from satellite, shipborne observations, and 1D radiative transfer simulations. The analysis focuses on research for PS106 expedition aboard the German research vessel, Polarstern. The results are presented in detailed case studies, time series for the PS106 cruise and extended to the central Arctic region. The findings illustrate the main periods of agreement and discrepancies of both points of view.
This article describes an intercomparison of radiative fluxes and cloud properties from...
Altmetrics
Final-revised paper
Preprint