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Title: Asymmetries in cloud microphysical properties ascribed to sea ice leads via water vapour transport in the central Arctic

Abstract

To investigate the influence of sea ice openings like leads on wintertime Arctic clouds, the air mass transport is exploited as a heat and humidity feeding mechanism which can modify Arctic cloud properties. Cloud microphysical properties in the central Arctic are analysed as a function of sea ice conditions during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2019–2020. The Cloudnet classification algorithm is used to characterize the clouds based on remote sensing observations and the atmospheric thermodynamic state from the observatory on board the research vessel (RV) Polarstern. To link the sea ice conditions around the observational site with the cloud observations, the water vapour transport (WVT) being conveyed towards RV Polarstern has been utilized as a mechanism to associate upwind sea ice conditions with the measured cloud properties. This novel methodology is used to classify the observed clouds as coupled or decoupled to the WVT based on the location of the maximum vertical gradient of WVT height relative to the cloud-driven mixing layer. Only a conical sub-sector of sea ice concentration (SIC) and the lead fraction (LF) centred on the RV Polarstern location and extending up to 50 km in radius and withmore » an azimuth angle governed by the time-dependent wind direction measured at the maximum WVT is related to the observed clouds. We found significant asymmetries for cases when the clouds are coupled or decoupled to the WVT and selected by LF regimes. Liquid water path of low-level clouds is found to increase as a function of LF, while the ice water path does so only for deep precipitating systems. Clouds coupled to WVT are found to generally have a lower cloud base and larger thickness than decoupled clouds. Thermodynamically, for coupled cases the cloud-top temperature is warmer and accompanied by a temperature inversion at the cloud top, whereas the decoupled cases are found to be closely compliant with the moist adiabatic temperature lapse rate. The ice water fraction within the cloud layer has been found to present a noticeable asymmetry when comparing coupled versus decoupled cases. This novel approach of coupling sea ice to cloud properties via the WVT mechanism unfolds a new tool to study Arctic surface–atmosphere processes. With this formulation, long-term observations can be analysed to enforce the statistical significance of the asymmetries. Furthermore, our results serve as an opportunity to better understand the dynamic linkage between clouds and sea ice and to evaluate its representation in numerical climate models for the Arctic system.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]
  1. University of Leipzig (Germany)
  2. Alfred Wegener Institute for Polar and Marine Research, Bremerhaven (Germany)
  3. Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
  4. University of Bremen (Germany)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Archive
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER); German Research Foundation (DFG)
Contributing Org.:
Pacific Northwest National Laboratory (PNNL); Brookhaven National Laboratory (BNL); Argonne National Laboratory (ANL); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
OSTI Identifier:
2217649
Grant/Contract Number:  
AC05-76RL01830; 268020496
Resource Type:
Accepted Manuscript
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 23; Journal Issue: 22; Journal ID: ISSN 1680-7324
Publisher:
Copernicus Publications, EGU
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Garfias, Pablo Saavedra, Kalesse-Los, Heike, von Albedyll, Luisa, Griesche, Hannes, and Spreen, Gunnar. Asymmetries in cloud microphysical properties ascribed to sea ice leads via water vapour transport in the central Arctic. United States: N. p., 2023. Web. doi:10.5194/acp-23-14521-2023.
Garfias, Pablo Saavedra, Kalesse-Los, Heike, von Albedyll, Luisa, Griesche, Hannes, & Spreen, Gunnar. Asymmetries in cloud microphysical properties ascribed to sea ice leads via water vapour transport in the central Arctic. United States. https://doi.org/10.5194/acp-23-14521-2023
Garfias, Pablo Saavedra, Kalesse-Los, Heike, von Albedyll, Luisa, Griesche, Hannes, and Spreen, Gunnar. Fri . "Asymmetries in cloud microphysical properties ascribed to sea ice leads via water vapour transport in the central Arctic". United States. https://doi.org/10.5194/acp-23-14521-2023. https://www.osti.gov/servlets/purl/2217649.
@article{osti_2217649,
title = {Asymmetries in cloud microphysical properties ascribed to sea ice leads via water vapour transport in the central Arctic},
author = {Garfias, Pablo Saavedra and Kalesse-Los, Heike and von Albedyll, Luisa and Griesche, Hannes and Spreen, Gunnar},
abstractNote = {To investigate the influence of sea ice openings like leads on wintertime Arctic clouds, the air mass transport is exploited as a heat and humidity feeding mechanism which can modify Arctic cloud properties. Cloud microphysical properties in the central Arctic are analysed as a function of sea ice conditions during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2019–2020. The Cloudnet classification algorithm is used to characterize the clouds based on remote sensing observations and the atmospheric thermodynamic state from the observatory on board the research vessel (RV) Polarstern. To link the sea ice conditions around the observational site with the cloud observations, the water vapour transport (WVT) being conveyed towards RV Polarstern has been utilized as a mechanism to associate upwind sea ice conditions with the measured cloud properties. This novel methodology is used to classify the observed clouds as coupled or decoupled to the WVT based on the location of the maximum vertical gradient of WVT height relative to the cloud-driven mixing layer. Only a conical sub-sector of sea ice concentration (SIC) and the lead fraction (LF) centred on the RV Polarstern location and extending up to 50 km in radius and with an azimuth angle governed by the time-dependent wind direction measured at the maximum WVT is related to the observed clouds. We found significant asymmetries for cases when the clouds are coupled or decoupled to the WVT and selected by LF regimes. Liquid water path of low-level clouds is found to increase as a function of LF, while the ice water path does so only for deep precipitating systems. Clouds coupled to WVT are found to generally have a lower cloud base and larger thickness than decoupled clouds. Thermodynamically, for coupled cases the cloud-top temperature is warmer and accompanied by a temperature inversion at the cloud top, whereas the decoupled cases are found to be closely compliant with the moist adiabatic temperature lapse rate. The ice water fraction within the cloud layer has been found to present a noticeable asymmetry when comparing coupled versus decoupled cases. This novel approach of coupling sea ice to cloud properties via the WVT mechanism unfolds a new tool to study Arctic surface–atmosphere processes. With this formulation, long-term observations can be analysed to enforce the statistical significance of the asymmetries. Furthermore, our results serve as an opportunity to better understand the dynamic linkage between clouds and sea ice and to evaluate its representation in numerical climate models for the Arctic system.},
doi = {10.5194/acp-23-14521-2023},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 22,
volume = 23,
place = {United States},
year = {Fri Nov 24 00:00:00 EST 2023},
month = {Fri Nov 24 00:00:00 EST 2023}
}

Works referenced in this record:

Estimation of Heat and Mass Fluxes Over Arctic Leads
journal, December 1980


Convective heat transfer over wintertime leads and polynyas
journal, November 1999

  • Andreas, Edgar L.; Cash, Benjamin A.
  • Journal of Geophysical Research: Oceans, Vol. 104, Issue C11
  • DOI: 10.1029/1999JC900241

Evidence for Changes in Arctic Cloud Phase Due to Long‐Range Pollution Transport
journal, October 2018

  • Coopman, Q.; Riedi, J.; Finch, D. P.
  • Geophysical Research Letters, Vol. 45, Issue 19
  • DOI: 10.1029/2018GL079873

Author Correction: Annual cycle observations of aerosols capable of ice formation in central Arctic clouds
journal, October 2022


Exploring relations between cloud morphology, cloud phase, and cloud radiative properties in Southern Ocean's stratocumulus clouds
journal, August 2022

  • Danker, Jessica; Sourdeval, Odran; McCoy, Isabel L.
  • Atmospheric Chemistry and Physics, Vol. 22, Issue 15
  • DOI: 10.5194/acp-22-10247-2022

Atmospheric temperature, water vapour and liquid water path from two microwave radiometers during MOSAiC
journal, September 2022


The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: the neXT generation
journal, January 2016

  • Engelmann, Ronny; Kanitz, Thomas; Baars, Holger
  • Atmospheric Measurement Techniques, Vol. 9, Issue 4
  • DOI: 10.5194/amt-9-1767-2016

On cloud radar and microwave radiometer measurements of stratus cloud liquid water profiles
journal, September 1998

  • Frisch, A. S.; Feingold, G.; Fairall, C. W.
  • Journal of Geophysical Research: Atmospheres, Vol. 103, Issue D18
  • DOI: 10.1029/98JD01827

The Retrieval of Stratus Cloud Droplet Effective Radius with Cloud Radars
journal, June 2002


Low-level mixed-phase clouds in a complex Arctic environment
journal, January 2020

  • Gierens, Rosa; Kneifel, Stefan; Shupe, Matthew D.
  • Atmospheric Chemistry and Physics, Vol. 20, Issue 6
  • DOI: 10.5194/acp-20-3459-2020

Application of the shipborne remote sensing supersite OCEANET for profiling of Arctic aerosols and clouds during Polarstern cruise PS106
journal, January 2020

  • Griesche, Hannes J.; Seifert, Patric; Ansmann, Albert
  • Atmospheric Measurement Techniques, Vol. 13, Issue 10
  • DOI: 10.5194/amt-13-5335-2020

Contrasting ice formation in Arctic clouds: surface-coupled vs. surface-decoupled clouds
journal, January 2021

  • Griesche, Hannes J.; Ohneiser, Kevin; Seifert, Patric
  • Atmospheric Chemistry and Physics, Vol. 21, Issue 13
  • DOI: 10.5194/acp-21-10357-2021

Turbulent Heat Exchange Over Polar Leads Revisited: A Large Eddy Simulation Study
journal, June 2023

  • Gryschka, M.; Gryanik, V. M.; Lüpkes, C.
  • Journal of Geophysical Research: Atmospheres, Vol. 128, Issue 12
  • DOI: 10.1029/2022JD038236

The Retrieval of Ice Water Content from Radar Reflectivity Factor and Temperature and Its Use in Evaluating a Mesoscale Model
journal, February 2006

  • Hogan, Robin J.; Mittermaier, Marion P.; Illingworth, Anthony J.
  • Journal of Applied Meteorology and Climatology, Vol. 45, Issue 2
  • DOI: 10.1175/JAM2340.1

Cloudnet: Continuous Evaluation of Cloud Profiles in Seven Operational Models Using Ground-Based Observations
journal, June 2007

  • Illingworth, A. J.; Hogan, R. J.; O'Connor, E. J.
  • Bulletin of the American Meteorological Society, Vol. 88, Issue 6
  • DOI: 10.1175/BAMS-88-6-883

Contrasting the impact of aerosols at northern and southern midlatitudes on heterogeneous ice formation: AEROSOL EFFECT ON ICE FORMATION
journal, September 2011

  • Kanitz, T.; Seifert, P.; Ansmann, A.
  • Geophysical Research Letters, Vol. 38, Issue 17
  • DOI: 10.1029/2011GL048532

How Are Mixed‐Phase Clouds Mixed?
journal, September 2022

  • Korolev, Alexei; Milbrandt, Jason
  • Geophysical Research Letters, Vol. 49, Issue 18
  • DOI: 10.1029/2022GL099578

MOSAiC drift expedition from October 2019 to July 2020: sea ice conditions from space and comparison with previous years
journal, January 2021

  • Krumpen, Thomas; von Albedyll, Luisa; Goessling, Helge F.
  • The Cryosphere, Vol. 15, Issue 8
  • DOI: 10.5194/tc-15-3897-2021

Relationship Between Wintertime Leads and Low Clouds in the Pan‐Arctic
journal, September 2020

  • Li, Xia; Krueger, Steven K.; Strong, Courtenay
  • Journal of Geophysical Research: Atmospheres, Vol. 125, Issue 18
  • DOI: 10.1029/2020JD032595

Midwinter Arctic leads form and dissipate low clouds
journal, January 2020


Evaluation of a New Merged Sea-Ice Concentration Dataset at 1 km Resolution from Thermal Infrared and Passive Microwave Satellite Data in the Arctic
journal, September 2020

  • Ludwig, Valentin; Spreen, Gunnar; Pedersen, Leif Toudal
  • Remote Sensing, Vol. 12, Issue 19
  • DOI: 10.3390/rs12193183

Influence of leads in sea ice on the temperature of the atmospheric boundary layer during polar night
journal, January 2008

  • Lüpkes, C.; Vihma, T.; Birnbaum, G.
  • Geophysical Research Letters, Vol. 35, Issue 3
  • DOI: 10.1029/2007GL032461

Variability of mixed-phase clouds in the Arctic with a focus on the Svalbard region: a study based on spaceborne active remote sensing
journal, January 2015

  • Mioche, G.; Jourdan, O.; Ceccaldi, M.
  • Atmospheric Chemistry and Physics, Vol. 15, Issue 5
  • DOI: 10.5194/acp-15-2445-2015

Resilience of persistent Arctic mixed-phase clouds
journal, December 2011

  • Morrison, Hugh; de Boer, Gijs; Feingold, Graham
  • Nature Geoscience, Vol. 5, Issue 1
  • DOI: 10.1038/ngeo1332

Method for detection of leads from Sentinel-1 SAR images
journal, March 2018

  • Murashkin, Dmitrii; Spreen, Gunnar; Huntemann, Marcus
  • Annals of Glaciology, Vol. 59, Issue 76pt2
  • DOI: 10.1017/aog.2018.6

Overview of the MOSAiC expedition
journal, January 2022

  • Nicolaus, Marcel; Perovich, Donald K.; Spreen, Gunnar
  • Elementa: Science of the Anthropocene, Vol. 10, Issue 1
  • DOI: 10.1525/elementa.2021.000046

Strong Ocean/Sea‐Ice Contrasts Observed in Satellite‐Derived Ice Crystal Number Concentrations in Arctic Ice Boundary‐Layer Clouds
journal, July 2022

  • Papakonstantinou‐Presvelou, Iris; Sourdeval, Odran; Quaas, Johannes
  • Geophysical Research Letters, Vol. 49, Issue 13
  • DOI: 10.1029/2022GL098207

Microphysics of Clouds and Precipitation
book, June 2010


Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks
journal, September 2022

  • Schimmel, Willi; Kalesse-Los, Heike; Maahn, Maximilian
  • Atmospheric Measurement Techniques, Vol. 15, Issue 18
  • DOI: 10.5194/amt-15-5343-2022

On the Relationship between Thermodynamic Structure and Cloud Top, and Its Climate Significance in the Arctic
journal, April 2012

  • Sedlar, Joseph; Shupe, Matthew D.; Tjernström, Michael
  • Journal of Climate, Vol. 25, Issue 7
  • DOI: 10.1175/JCLI-D-11-00186.1

Processes and impacts of Arctic amplification: A research synthesis
journal, May 2011


A ground-based multisensor cloud phase classifier
journal, January 2007


Overview of the MOSAiC expedition: Atmosphere
journal, January 2022

  • Shupe, Matthew D.; Rex, Markus; Blomquist, Byron
  • Elementa: Science of the Anthropocene, Vol. 10, Issue 1
  • DOI: 10.1525/elementa.2021.00060

The thermodynamic structure of summer Arctic stratocumulus and the dynamic coupling to the surface
journal, January 2014

  • Sotiropoulou, G.; Sedlar, J.; Tjernström, M.
  • Atmospheric Chemistry and Physics, Vol. 14, Issue 22
  • DOI: 10.5194/acp-14-12573-2014

Sea ice remote sensing using AMSR-E 89-GHz channels
journal, January 2008

  • Spreen, G.; Kaleschke, L.; Heygster, G.
  • Journal of Geophysical Research, Vol. 113, Issue C2
  • DOI: 10.1029/2005JC003384

The LAGRANTO Lagrangian analysis tool – version 2.0
journal, January 2015


CloudnetPy: A Python package for processing cloud remote sensing data
journal, September 2020

  • Tukiainen, Simo; O’Connor, Ewan; Korpinen, Anniina
  • Journal of Open Source Software, Vol. 5, Issue 53
  • DOI: 10.21105/joss.02123

Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations
journal, January 2021

  • von Albedyll, Luisa; Haas, Christian; Dierking, Wolfgang
  • The Cryosphere, Vol. 15, Issue 5
  • DOI: 10.5194/tc-15-2167-2021

Thermodynamik der atnwsphäre. Von Dr. Alfred Wegener. Leipzig : Verlag von Johann Ambrosius Barth, 1911. 8vo. 8 + 331 pp. 17 plates
journal, January 1913

  • Gold, E.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 39, Issue 165
  • DOI: 10.1002/qj.49703916510

Understanding Causes and Effects of Rapid Warming in the Arctic
journal, January 2017


Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)3 Project
journal, January 2023

  • Wendisch, M.; Brückner, M.; Crewell, S.
  • Bulletin of the American Meteorological Society, Vol. 104, Issue 1
  • DOI: 10.1175/BAMS-D-21-0218.1

Evidence that ice forms primarily in supercooled liquid clouds at temperatures > −27°C: ICE NUCLEATION IN MID-LEVEL CLOUDS
journal, July 2011

  • Westbrook, C. D.; Illingworth, A. J.
  • Geophysical Research Letters, Vol. 38, Issue 14
  • DOI: 10.1029/2011GL048021

A Proposed Algorithm for Moisture Fluxes from Atmospheric Rivers
journal, March 1998