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 »
- Authors:
-
- University of Leipzig (Germany)
- Alfred Wegener Institute for Polar and Marine Research, Bremerhaven (Germany)
- Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
- 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}
}
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