Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations

Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first ti...

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Published in:Atmospheric Chemistry and Physics
Main Authors: Raman, Aishwarya, Hill, Thomas, DeMott, Paul J., Singh, Balwinder, Zhang, Kai, Ma, Po-Lun, Wu, Mingxuan, Wang, Hailong, Alexander, Simon P., Burrows, Susannah M.
Language:unknown
Published: 2023
Subjects:
Online Access:http://www.osti.gov/servlets/purl/1985656
https://www.osti.gov/biblio/1985656
https://doi.org/10.5194/acp-23-5735-2023
id ftosti:oai:osti.gov:1985656
record_format openpolar
spelling ftosti:oai:osti.gov:1985656 2023-07-30T04:04:48+02:00 Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations Raman, Aishwarya Hill, Thomas DeMott, Paul J. Singh, Balwinder Zhang, Kai Ma, Po-Lun Wu, Mingxuan Wang, Hailong Alexander, Simon P. Burrows, Susannah M. 2023-06-28 application/pdf http://www.osti.gov/servlets/purl/1985656 https://www.osti.gov/biblio/1985656 https://doi.org/10.5194/acp-23-5735-2023 unknown http://www.osti.gov/servlets/purl/1985656 https://www.osti.gov/biblio/1985656 https://doi.org/10.5194/acp-23-5735-2023 doi:10.5194/acp-23-5735-2023 54 ENVIRONMENTAL SCIENCES 2023 ftosti https://doi.org/10.5194/acp-23-5735-2023 2023-07-11T10:27:54Z Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first time, how model-simulated INP concentrations compare with year-round INP measurements during the Macquarie Island Cloud Radiation Experiment (MICRE) campaign from 2017–2018. We simulate immersion-mode INP concentrations using the Energy Exascale Earth System Model version 1 (E3SMv1) by combining simulated aerosols with recently developed deterministic INP parameterizations and the native classical nucleation theory (CNT) for mineral dust in E3SMv1. Because MICRE did not collect aerosol measurements of super-micron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and overestimates sea spray aerosol concentrations by 1 to 2 orders of magnitude for most of the high-latitude sites in the Southern Hemisphere. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 d) and processed offline using the Colorado State University ice spectrometer (IS) in immersion freezing mode. We find that when deterministic parameterizations for both dust and sea spray INPs are used, simulated INPs are within a factor of 10 of observed INPs more than 60 % of the time during summer. Our results also indicate that the E3SM's current treatment of mineral dust immersion freezing in the SO is impacted by compensating biases – an underprediction of dust amount was compensated by an overprediction of its effectiveness as INPs. We also perform idealized droplet freezing experiments to quantify the implications of the time-dependent behavior assumed by the E3SM's CNT-parameterization and compare with the ice ... Other/Unknown Material Macquarie Island Southern Ocean SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Southern Ocean Atmospheric Chemistry and Physics 23 10 5735 5762
institution Open Polar
collection SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy)
op_collection_id ftosti
language unknown
topic 54 ENVIRONMENTAL SCIENCES
spellingShingle 54 ENVIRONMENTAL SCIENCES
Raman, Aishwarya
Hill, Thomas
DeMott, Paul J.
Singh, Balwinder
Zhang, Kai
Ma, Po-Lun
Wu, Mingxuan
Wang, Hailong
Alexander, Simon P.
Burrows, Susannah M.
Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations
topic_facet 54 ENVIRONMENTAL SCIENCES
description Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first time, how model-simulated INP concentrations compare with year-round INP measurements during the Macquarie Island Cloud Radiation Experiment (MICRE) campaign from 2017–2018. We simulate immersion-mode INP concentrations using the Energy Exascale Earth System Model version 1 (E3SMv1) by combining simulated aerosols with recently developed deterministic INP parameterizations and the native classical nucleation theory (CNT) for mineral dust in E3SMv1. Because MICRE did not collect aerosol measurements of super-micron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and overestimates sea spray aerosol concentrations by 1 to 2 orders of magnitude for most of the high-latitude sites in the Southern Hemisphere. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 d) and processed offline using the Colorado State University ice spectrometer (IS) in immersion freezing mode. We find that when deterministic parameterizations for both dust and sea spray INPs are used, simulated INPs are within a factor of 10 of observed INPs more than 60 % of the time during summer. Our results also indicate that the E3SM's current treatment of mineral dust immersion freezing in the SO is impacted by compensating biases – an underprediction of dust amount was compensated by an overprediction of its effectiveness as INPs. We also perform idealized droplet freezing experiments to quantify the implications of the time-dependent behavior assumed by the E3SM's CNT-parameterization and compare with the ice ...
author Raman, Aishwarya
Hill, Thomas
DeMott, Paul J.
Singh, Balwinder
Zhang, Kai
Ma, Po-Lun
Wu, Mingxuan
Wang, Hailong
Alexander, Simon P.
Burrows, Susannah M.
author_facet Raman, Aishwarya
Hill, Thomas
DeMott, Paul J.
Singh, Balwinder
Zhang, Kai
Ma, Po-Lun
Wu, Mingxuan
Wang, Hailong
Alexander, Simon P.
Burrows, Susannah M.
author_sort Raman, Aishwarya
title Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations
title_short Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations
title_full Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations
title_fullStr Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations
title_full_unstemmed Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations
title_sort long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations
publishDate 2023
url http://www.osti.gov/servlets/purl/1985656
https://www.osti.gov/biblio/1985656
https://doi.org/10.5194/acp-23-5735-2023
geographic Southern Ocean
geographic_facet Southern Ocean
genre Macquarie Island
Southern Ocean
genre_facet Macquarie Island
Southern Ocean
op_relation http://www.osti.gov/servlets/purl/1985656
https://www.osti.gov/biblio/1985656
https://doi.org/10.5194/acp-23-5735-2023
doi:10.5194/acp-23-5735-2023
op_doi https://doi.org/10.5194/acp-23-5735-2023
container_title Atmospheric Chemistry and Physics
container_volume 23
container_issue 10
container_start_page 5735
op_container_end_page 5762
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