Articles | Volume 14, issue 2
https://doi.org/10.5194/amt-14-1205-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-1205-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Feb 2021
Research article |
| 16 Feb 2021
| 16 Feb 2021
The De-Icing Comparison Experiment (D-ICE): a study of broadband radiometric measurements under icing conditions in the Arctic
Christopher J. Cox
CORRESPONDING AUTHOR
NOAA Physical Sciences Laboratory (PSL), Boulder, Colorado, 80305, USA
Sara M. Morris
NOAA Physical Sciences Laboratory (PSL), Boulder, Colorado, 80305, USA
Taneil Uttal
NOAA Physical Sciences Laboratory (PSL), Boulder, Colorado, 80305, USA
Ross Burgener
NOAA Global Monitoring Laboratory (GML), Boulder, Colorado, 80305, USA
Emiel Hall
NOAA Global Monitoring Laboratory (GML), Boulder, Colorado, 80305, USA
Cooperative Institute for Research in Environmental Sciences (CIRES),
Boulder, Colorado, 80305, USA
University of Colorado, Boulder, Colorado, 80305, USA
Mark Kutchenreiter
National Renewable Energy Laboratory (NREL), Golden, Colorado, 80401,
USA
Allison McComiskey
Brookhaven National Laboratory (BNL), Upton, New York, 11973, USA
Charles N. Long
NOAA Global Monitoring Laboratory (GML), Boulder, Colorado, 80305, USA
Cooperative Institute for Research in Environmental Sciences (CIRES),
Boulder, Colorado, 80305, USA
University of Colorado, Boulder, Colorado, 80305, USA
deceased
Bryan D. Thomas
NOAA Global Monitoring Laboratory (GML), Boulder, Colorado, 80305, USA
James Wendell
NOAA Global Monitoring Laboratory (GML), Boulder, Colorado, 80305, USA
Related authors
Aidan D. Pantoya, Stephanie R. Simonsen, Elisabeth Andrews, Ross Burgener, Christopher J. Cox, Gijs de Boer, Bryan D. Thomas, and Naruki Hiranuma
Aerosol Research, 3, 253–270, https://doi.org/10.5194/ar-3-253-2025, https://doi.org/10.5194/ar-3-253-2025, 2025
Short summary
Short summary
We present continuous ice-nucleating particle data that were measured in the Alaskan Arctic from October 2021 to December 2023. We found a greater efficiency in the arctic immersion freezing during fall compared to those found previously at two mid-latitude sites, together with profound freezing efficiencies in spring, presumably due to arctic haze events. Our study will be useful for improving atmospheric models to simulate cloud feedback and determine their impact on the global radiative energy budget.
Christopher J. Cox, Janet M. Intrieri, Brian J. Butterworth, Gijs de Boer, Michael R. Gallagher, Jonathan Hamilton, Erik Hulm, Tilden Meyers, Sara M. Morris, Jackson Osborn, P. Ola G. Persson, Benjamin Schmatz, Matthew D. Shupe, and James M. Wilczak
Earth Syst. Sci. Data, 17, 1481–1499, https://doi.org/10.5194/essd-17-1481-2025, https://doi.org/10.5194/essd-17-1481-2025, 2025
Short summary
Short summary
Snow is an essential water resource in the intermountain western United States, and predictions are made using models. We made observations to validate, constrain, and develop the models. The data are from the Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH) campaign in Colorado's East River valley, 2021–2023. The measurements include meteorology and variables that quantify energy transfer between the atmosphere and surface. The data are available publicly.
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.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
Short summary
Short summary
A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
Short summary
Short summary
During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Gina C. Jozef, John J. Cassano, Sandro Dahlke, Mckenzie Dice, Christopher J. Cox, and Gijs de Boer
Atmos. Chem. Phys., 24, 1429–1450, https://doi.org/10.5194/acp-24-1429-2024, https://doi.org/10.5194/acp-24-1429-2024, 2024
Short summary
Short summary
Observations collected during MOSAiC were used to identify the range in vertical structure and stability of the central Arctic lower atmosphere through a self-organizing map analysis. Characteristics of wind features (such as low-level jets) and atmospheric moisture features (such as clouds) were analyzed in the context of the varying vertical structure and stability. Thus, the results of this paper give an overview of the thermodynamic and kinematic features of the central Arctic atmosphere.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
Short summary
Short summary
Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
Gina C. Jozef, John J. Cassano, Sandro Dahlke, Mckenzie Dice, Christopher J. Cox, and Gijs de Boer
Atmos. Chem. Phys., 23, 13087–13106, https://doi.org/10.5194/acp-23-13087-2023, https://doi.org/10.5194/acp-23-13087-2023, 2023
Short summary
Short summary
Observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) were used to determine the frequency of occurrence of various central Arctic lower atmospheric stability regimes and how the stability regimes transition between each other. Wind and radiation observations were analyzed in the context of stability regime and season to reveal the relationships between Arctic atmospheric stability and mechanically and radiatively driven turbulent forcings.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
Short summary
Short summary
Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Gijs de Boer, Steven Borenstein, Radiance Calmer, Christopher Cox, Michael Rhodes, Christopher Choate, Jonathan Hamilton, Jackson Osborn, Dale Lawrence, Brian Argrow, and Janet Intrieri
Earth Syst. Sci. Data, 14, 19–31, https://doi.org/10.5194/essd-14-19-2022, https://doi.org/10.5194/essd-14-19-2022, 2022
Short summary
Short summary
This article provides a summary of the collection of atmospheric data over the near-coastal zone upwind of Barbados during the ATOMIC and EUREC4A field campaigns. These data were collected to improve our understanding of the structure and dynamics of the lower atmosphere in the tropical trade-wind regime over the Atlantic Ocean and the influence of that portion of the atmosphere on the development and maintenance of clouds.
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
Short summary
Short summary
We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Joseph J. Michalsky, John A. Augustine, Emiel Hall, and Benjamin R. Sheffer
EGUsphere, https://doi.org/10.5194/egusphere-2025-3787, https://doi.org/10.5194/egusphere-2025-3787, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
We examine four equations for calculating infrared radiation (3–50 mm) measured with a Eppley PIR pyrgeometer. These equations are used to transfer calibrations from the World Infrared Standard Group at the World Radiation Center in Davos, Switzerland, to the three PIR pyrgeometers we use as standards. A clear choice in terms of the most precise method to follow emerges from this study. Furthermore, we evaluate the stability of the Eppley PIR, necessary for long-term trend analysis.
Aidan D. Pantoya, Stephanie R. Simonsen, Elisabeth Andrews, Ross Burgener, Christopher J. Cox, Gijs de Boer, Bryan D. Thomas, and Naruki Hiranuma
Aerosol Research, 3, 253–270, https://doi.org/10.5194/ar-3-253-2025, https://doi.org/10.5194/ar-3-253-2025, 2025
Short summary
Short summary
We present continuous ice-nucleating particle data that were measured in the Alaskan Arctic from October 2021 to December 2023. We found a greater efficiency in the arctic immersion freezing during fall compared to those found previously at two mid-latitude sites, together with profound freezing efficiencies in spring, presumably due to arctic haze events. Our study will be useful for improving atmospheric models to simulate cloud feedback and determine their impact on the global radiative energy budget.
Christopher J. Cox, Janet M. Intrieri, Brian J. Butterworth, Gijs de Boer, Michael R. Gallagher, Jonathan Hamilton, Erik Hulm, Tilden Meyers, Sara M. Morris, Jackson Osborn, P. Ola G. Persson, Benjamin Schmatz, Matthew D. Shupe, and James M. Wilczak
Earth Syst. Sci. Data, 17, 1481–1499, https://doi.org/10.5194/essd-17-1481-2025, https://doi.org/10.5194/essd-17-1481-2025, 2025
Short summary
Short summary
Snow is an essential water resource in the intermountain western United States, and predictions are made using models. We made observations to validate, constrain, and develop the models. The data are from the Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH) campaign in Colorado's East River valley, 2021–2023. The measurements include meteorology and variables that quantify energy transfer between the atmosphere and surface. The data are available publicly.
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.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
Short summary
Short summary
The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
Short summary
Short summary
A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
Short summary
Short summary
During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Xin Yang, Kimberly Strong, Alison S. Criscitiello, Marta Santos-Garcia, Kristof Bognar, Xiaoyi Zhao, Pierre Fogal, Kaley A. Walker, Sara M. Morris, and Peter Effertz
Atmos. Chem. Phys., 24, 5863–5886, https://doi.org/10.5194/acp-24-5863-2024, https://doi.org/10.5194/acp-24-5863-2024, 2024
Short summary
Short summary
This study uses snow samples collected from a Canadian high Arctic site, Eureka, to demonstrate that surface snow in early spring is a net sink of atmospheric bromine and nitrogen. Surface snow bromide and nitrate are significantly correlated, indicating the oxidation of reactive nitrogen is accelerated by reactive bromine. In addition, we show evidence that snow photochemical release of reactive bromine is very weak, and its emission flux is much smaller than the deposition flux of bromide.
Gina C. Jozef, John J. Cassano, Sandro Dahlke, Mckenzie Dice, Christopher J. Cox, and Gijs de Boer
Atmos. Chem. Phys., 24, 1429–1450, https://doi.org/10.5194/acp-24-1429-2024, https://doi.org/10.5194/acp-24-1429-2024, 2024
Short summary
Short summary
Observations collected during MOSAiC were used to identify the range in vertical structure and stability of the central Arctic lower atmosphere through a self-organizing map analysis. Characteristics of wind features (such as low-level jets) and atmospheric moisture features (such as clouds) were analyzed in the context of the varying vertical structure and stability. Thus, the results of this paper give an overview of the thermodynamic and kinematic features of the central Arctic atmosphere.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
Short summary
Short summary
Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
Gina C. Jozef, John J. Cassano, Sandro Dahlke, Mckenzie Dice, Christopher J. Cox, and Gijs de Boer
Atmos. Chem. Phys., 23, 13087–13106, https://doi.org/10.5194/acp-23-13087-2023, https://doi.org/10.5194/acp-23-13087-2023, 2023
Short summary
Short summary
Observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) were used to determine the frequency of occurrence of various central Arctic lower atmospheric stability regimes and how the stability regimes transition between each other. Wind and radiation observations were analyzed in the context of stability regime and season to reveal the relationships between Arctic atmospheric stability and mechanically and radiatively driven turbulent forcings.
Xin Yang, Kimberly Strong, Alison S. Criscitiello, Marta Santos-Garcia, Kristof Bognar, Xiaoyi Zhao, Pierre Fogal, Kaley A. Walker, Sara M. Morris, and Peter Effertz
EGUsphere, https://doi.org/10.5194/egusphere-2022-696, https://doi.org/10.5194/egusphere-2022-696, 2022
Preprint archived
Short summary
Short summary
Snow pack in high Arctic plays a key role in polar atmospheric chemistry, especially in spring when photochemistry becomes active. By sampling surface snow from a Canadian high Arctic location at Eureka, Nunavut (80° N, 86° W), we demonstrate that surface snow is a net sink rather than a source of atmospheric reactive bromine and nitrate. This finding is new and opposite to previous conclusions that snowpack is a large and direct source of reactive bromine in polar spring.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
Short summary
Short summary
Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Gijs de Boer, Steven Borenstein, Radiance Calmer, Christopher Cox, Michael Rhodes, Christopher Choate, Jonathan Hamilton, Jackson Osborn, Dale Lawrence, Brian Argrow, and Janet Intrieri
Earth Syst. Sci. Data, 14, 19–31, https://doi.org/10.5194/essd-14-19-2022, https://doi.org/10.5194/essd-14-19-2022, 2022
Short summary
Short summary
This article provides a summary of the collection of atmospheric data over the near-coastal zone upwind of Barbados during the ATOMIC and EUREC4A field campaigns. These data were collected to improve our understanding of the structure and dynamics of the lower atmosphere in the tropical trade-wind regime over the Atlantic Ocean and the influence of that portion of the atmosphere on the development and maintenance of clouds.
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
Short summary
Short summary
We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Jessie M. Creamean, Gijs de Boer, Hagen Telg, Fan Mei, Darielle Dexheimer, Matthew D. Shupe, Amy Solomon, and Allison McComiskey
Atmos. Chem. Phys., 21, 1737–1757, https://doi.org/10.5194/acp-21-1737-2021, https://doi.org/10.5194/acp-21-1737-2021, 2021
Short summary
Short summary
Arctic clouds play a role in modulating sea ice extent. Importantly, aerosols facilitate cloud formation, and thus it is crucial to understand the interactions between aerosols and clouds. Vertical measurements of aerosols and clouds are needed to tackle this issue. We present results from balloon-borne measurements of aerosols and clouds over the course of 2 years in northern Alaska. These data shed light onto the vertical distributions of aerosols relative to clouds spanning multiple seasons.
Xin Yang, Anne-M. Blechschmidt, Kristof Bognar, Audra McClure-Begley, Sara Morris, Irina Petropavlovskikh, Andreas Richter, Henrik Skov, Kimberly Strong, David W. Tarasick, Taneil Uttal, Mika Vestenius, and Xiaoyi Zhao
Atmos. Chem. Phys., 20, 15937–15967, https://doi.org/10.5194/acp-20-15937-2020, https://doi.org/10.5194/acp-20-15937-2020, 2020
Short summary
Short summary
This is a modelling-based study on Arctic surface ozone, with a particular focus on spring ozone depletion events (i.e. with concentrations < 10 ppbv). Model experiments show that model runs with blowing-snow-sourced sea salt aerosols implemented as a source of reactive bromine can reproduce well large-scale ozone depletion events observed in the Arctic. This study supplies modelling evidence of the proposed mechanism of reactive-bromine release from blowing snow on sea ice (Yang et al., 2008).
Cited articles
Alados-Arboledas, L., Vida, J., and Jiménez, J. I.: Effects of solar
radiation on performance of pyrgeometers with silicon domes, J. Atmos.
Ocean. Tech., 5, 666–670, https://doi.org/10.1175/1520-0426(1988)005<0666:EOSROT>2.0.CO;2, 1988.
Albrecht, B. and Cox, S. K.: Procedures for improving pyrgeometer
performance, J. Appl. Meteorol., 16, 188–197, https://doi.org/10.1175/1520-0450(1977)016<0190:PFIPP>2.0.CO;2, 1977.
Atmospheric Radiation Measurement (ARM) user facility: Balloon-Borne Sounding System (SONDEWNPN), 1/23/2018, North Slope Alaska (NSA) Central Facility, Barrow AK (C1), compiled by: Keeler, E., Ritsche, M., Coulter, R., Kyrouac, J., and Holdridge, D., ARM Data Center, https://doi.org/10.5439/1021460, updated hourly, 1994.
Atmospheric Radiation Measurement (ARM) user facility: Data Quality Assessment for ARM Radiation Data (QCRAD1LONG), 8/1/2017 to 8/1/2018, North Slope Alaska (NSA) Central Facility, Barrow AK (C1), compiled by: Riihimaki, L., Shi, Y., Zhang, D., and Long, C., ARM Data Center, https://doi.org/10.5439/1027372, updated hourly. 1996.
Atmospheric Radiation Measurement (ARM) user facility: Ceilometer (CEIL), 1/23/2018, North Slope Alaska (NSA) Central Facility, Barrow AK (C1), compiled by: Morris, V., ARM Data Center, https://doi.org/10.5439/1181954, updated hourly, 2010.
BSRN: Report of the 12th Baseline Surface Radiation Network (BSRN)
Scientific Review and Workshop, 1–3 August 2012, Alfred Wegener Institute,
Potsdam, Germany, WCRP Report No. 20/2012, available at: https://www.wcrp-climate.org/documents/bsrn-12_report.pdf (last access: 4 February 2021), 2012.
BSRN: 14th Baseline Surface Radiation Network (BSRN) Scientific Review
and Workshop, 26–29 April 2016, Australian Bureau of Meteorology, Canberra,
Australia, WCRP Report No. 17/2016, available at: https://www.wcrp-climate.org/WCRP-publications/2016/WCRP_Report_17_2016_14th_BSRN_Meeting_Report.pdf (last access: 4 February 2021),
2016.
Cox, C.: De-Icing Comparison Experiment (D-ICE) campaign data: Radiometric
and icing condition observations from the NOAA Barrow Atmospheric Baseline
Observatory, August 2017–July 2018 (NCEI Accession 0209059), NOAA National
Centers for Environmental Information, Dataset, available at: https://accession.nodc.noaa.gov/0209059 (last access: 4 February 2021), 2020a.
Cox, C.: De-Icing Comparison Experiment (D-ICE) campaign data: Best-estimate
downwelling longwave and shortwave radiometric fluxes from the NOAA Barrow
Atmospheric Baseline Observatory, August 2017–July 2018 (NCEI Accession
0209058), NOAA National Centers for Environmental Information, Dataset, available at: https://accession.nodc.noaa.gov/0209058 (last access: 4 February 2021), 2020b.
Cox, C. J., Walden, V. P., and Rowe, P. M.: A comparison of the atmospheric
conditions at Eureka, Canada, and Barrow, Alaska (2006–2008), J. Geophys.
Res., 117, D12204, https://doi.org/10.1029/2011JD017164, 2012.
Cox, C. J., Walden, V. P., Rowe, P. M., and Shupe, M. D.: Humidity trends imply increased sensitivity to clouds in a warming Arctic, Nat. Commun., 6, 10117, https://doi.org/10.1038/ncomms10117, 2015.
Cox, C. J., Stone, R. S., Douglas, D. C., Stanitski, D. M., Divoky, G. J.,
Dutton, G. S., Sweeney, C., George, J. Craig, and Longenecker, D.: Drivers
and environmental responses to the changing annual snow cycle of northern
Alaska, B. Amer. Meteorol. Soc., 98, 2559–2577,
https://doi.org/10.1175/BAMS-D-16-0201.1, 2017.
Cox, C. J., Morris, S. M., Uttal, T., Long, C. N., and McComiskey, A.: The
De-Icing Comparison Experiment – ARM Contribution (DICEXACO) Field Campaign
Report, edited by: Stafford, R., ARM user facility, DOE/SC-ARM-19-020, https://doi.org/10.5439/1507148, 2019.
Driemel, A., Augustine, J., Behrens, K., Colle, S., Cox, C., Cuevas-Agulló, E., Denn, F. M., Duprat, T., Fukuda, M., Grobe, H., Haeffelin, M., Hodges, G., Hyett, N., Ijima, O., Kallis, A., Knap, W., Kustov, V., Long, C. N., Longenecker, D., Lupi, A., Maturilli, M., Mimouni, M., Ntsangwane, L., Ogihara, H., Olano, X., Olefs, M., Omori, M., Passamani, L., Pereira, E. B., Schmithüsen, H., Schumacher, S., Sieger, R., Tamlyn, J., Vogt, R., Vuilleumier, L., Xia, X., Ohmura, A., and König-Langlo, G.: Baseline Surface Radiation Network (BSRN): structure and data description (1992–2017), Earth Syst. Sci. Data, 10, 1491–1501, https://doi.org/10.5194/essd-10-1491-2018, 2018.
Dutton, E. G., Michalsky, J. J., Stoffel, T., Forgan, B. W., Hickey, J.,
Nelson, D. W., Alberta, T. L., and Reda, I.: Measurement of broadband
diffuse solar irradiance using current commercial instrumentation with a
correction for thermal offset errors, J. Atmos. Ocean. Tech., 18,
297–314, https://doi.org/10.1175/1520-0426(2001)018<0297:MOBDSI>2.0.CO;2, 2001.
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., 119,
7083–7090, https://doi.org/10.1002/2014JD021630, 2014.
Kandula, M.: Frost growth and densification in laminar flow over flat
surfaces, Int. J. Heat Mass. Trans., 54, 3719–3731,
https://doi.org/10.1016/j.ijheatmasstransfer.2011.02.056, 2011.
Koerner, R. M., Gill, A., Apollonio, S., Greenhouse, J. P., and Hyndman, R. D.: The Devon Island Expedition 1960–64, Arctic,
16, 57–76, https://doi.org/10.14430/arctic3523, 1963.
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.
Lenschow, D. H.: The measurement of air velocity and temperature using the
NCAR Buffalo Aircraft Measurement System, National Center for Atmospheric
Research, NCAR-TN/EDD-74, University Corporation for Atmospheric Research, https://doi.org/10.5065/D6C8277W,
1972.
Long, C. N. and Shi, Y.: An automated quality assessment and control
algorithm for surface radiation measurements, Open Atmos. Sci. J., 2, 23–37,
https://doi.org/10.2174/1874282300802010023, 2008.
Marty, C., Philipona, R., Delamere, J., Dutton, E. G., Michalsky, J., Stamnes, K., Storvold, R., Stoffel, T., Clough, S. A., and Mlawer, E. J.: Downward longwave irradiance uncertainty under arctic atmospheres: Measurements and modeling, J. Geophys. Res., 108, 4358, https://doi.org/10.1029/2002JD002937, 2003.
Matsui, N., Long, C. N., Augustine, J., Halliwell, D., Uttal, T., Longenecker, D., Niebergall, O., Wendell, J., and Albee, R.: Evaluation of Arctic broadband surface radiation measurements, Atmos. Meas. Tech., 5, 429–438, https://doi.org/10.5194/amt-5-429-2012, 2012.
McArthur, B.: World Climate Research Programme Baseline Surface Radiation
Network (BSRN) Operations Manual Version 2.1, WCRP-121 WMO/TD-No. 1274, 176
pp., available at: https://bsrn.awi.de/fileadmin/user_upload/bsrn.awi.de/Publications/McArthur.pdf (last access: 4 February 2021), 2005.
Michalsky, J. J., Harrison, L. C., and Berkheiser III, W. E.: Cosine
response characteristics of some radiometric and photometric sensors, Sol.
Energy, 54, 397–402,
https://doi.org/10.1016/0038-092X(95)00017-L, 1995.
Michalsky, J. J., Kutchenreiter, M., and Long, C. N.: Significant
improvements in pyranometer nighttime offsets using high-flow DC
ventilation, J. Atmos. Ocean. Tech., 34, 1323–1332,
https://doi.org/10.1175/JTECH-D-16-0224.1, 2017.
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.
Miller, N. B., Shupe, M. D., Cox, C. J., Noone, D., Persson, P. O. G., and Steffen, K.: Surface energy budget responses to radiative forcing at Summit, Greenland, The Cryosphere, 11, 497–516, https://doi.org/10.5194/tc-11-497-2017, 2017.
National Oceanic and Atmospheric Administration (NOAA): Meteorology measurements from the NOAA/GML Barrow Baseline Observatory, available at: https://www.esrl.noaa.gov/gmd/obop/brw/, last access: 6 March 2018.
National Oceanic and Atmospheric Administration (NOAA): D-ICE De-Icing Comparison Experiment, available at: https://www.esrl.noaa.gov/psd/arctic/d-ice/, last access: 4 February 2021.
Ohmura, A., Dutton, E. G., Forgan, B., Flöhlich, C., Gilgen, H., Hegner, H., Heimo, A., König-Langlo, G., McArthur, B., Müller, G., Philipona, R., Pinker, R., Whitlock, C. H., Dehne, K., and Wild, M.: Baseline Surface Radiation Network (BSRN/WCRP):
New precision radiometery for climate research, B. Amer. Meteorol. Soc.,
79, 2115–2136,
https://doi.org/10.1175/1520-0477(1998)079<2115:BSRNBW>2.0.CO;2, 1998.
Overland, J. E. and Wang, M.: Arctic-midlatitude weather linkages in North
America, Polar Sci., 16, 1–9,
https://doi.org/10.1016/j.polar.2018.02.001, 2018.
Persson, P. O. G. and Semmer, S.: Impacts of Riming on Arctic Surface Energy
Budget Measurements, Autonomous Polar Observing Systems Workshop (https://www.iris.edu/hq/polar_workshop2010/, last access: 12 February 2021), Potomac,
MD, 30 September–1 October 2010 (poster accessed through personal communication with P. O. G. Persson, 29 August 2016).
Persson, P. O. G., Blomquist, B., Guest, P., Stammerjohn, S., Fairall, C.
W., Rainville, L., Lund, B., Ackley, S., and Thomson, J.: Shipboard
observations of meteorology and near-surface environment during autumn
freezeup in the Beaufort/Chukchi Seas, J. Geophys. Res., 123, 4930–4969,
https://doi.org/10.1029/2018JC013786, 2018.
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, https://doi.org/10.1007/s00382-010-0937-5, 2011.
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.
Stuefer, M., Cassella, V., Korevaar, M., and Wong, T.: Heater Pyrheliometer
Field Campaign Report, edited by: Stafford, R., ARM user facility,
DOE/SC-ARM-19-030, 2019.
Thompson, D. C.: Aerodynamic heating of miniature bead thermistor
thermometers in a rarified airstream, J. Appl. Meteorol., 7, 504–508,
https://doi.org/10.1175/1520-0450(1968)007<0504:AHOMBT>2.0.CO;2, 1968.
van den Broeke, M., van As, D., Reijmer, C., and van de Wal, R.: Assessing
and improving the quality of unattended radiation measurements in
Antarctica, J. Atmos. Ocean. Tech., 21, 1417–1431,
https://doi.org/10.1175/1520-0426(2004)021<1417:AAITQO>2.0.CO;2, 2004.
Wang, W., Zender, C. S., and van As, D.: Temporal characteristics of cloud
radiative effects on the Greenland ice sheet: discoveries from multiyear
automatic weather station measurements, J. Geophys. Res., 123, 11348–11361,
https://doi.org/10.1029/2018JD028540, 2018.
Weisser, U.: Status update of BSRN station Sonnblick (SON) – (Apr 2016),
14th VSRN Science Review and Workshop, Canberra, Australia, 26–29 April 2016, available at: https://www.esrl.noaa.gov/gmd/grad/meetings/BSRN_talks/P1_7_Poster_BSRN_Canberra_Olefs_Weiser_2016.pdf (last access: 4 February 2021), 2016.
Wendler, G., Moore, B., and Galloway, K.: Strong temperature increase and
shrinking sea ice in Arctic Alaska, Open Atmos. Sci. J., 8, 7–15,
https://doi.org/10.2174/1874282301408010007, 2014.
Short summary
Solar and infrared radiation are measured regularly for research, industry, and climate monitoring. In cold climates, icing of sensors is a poorly constrained source of uncertainty. D-ICE was carried out in Alaska to document the effectiveness of ice-mitigation technology and quantify errors associated with ice. Technology was more effective than anticipated, and while instantaneous errors were large, mean biases were small. Attributes of effective ice mitigation design were identified.
Solar and infrared radiation are measured regularly for research, industry, and climate...
