12 Apr 2022
12 Apr 2022
Status: this preprint is currently under review for the journal ACP.

Long-term Variability in immersion-mode Marine Ice Nucleating Particles from Climate Model Simulations and Observations

Aishwarya Raman1, Thomas Hill2, Paul DeMott2, Balwinder Singh1, Kai Zhang1, Po-Lun Ma1, Mingxuan Wu1, Hailong Wang1, and Susannah Burrows1 Aishwarya Raman et al.
  • 1Pacific Northwest National Laboratory, 902 Battelle Blvd, Richland, WA 99354
  • 2Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523-1371, USA

Abstract. Ice nucleating particles (INPs) are present in extremely low concentrations in the Southern Ocean (SO) atmosphere, but their temporal variability can 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 against 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 supermicron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other Southern high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and sea spray concentrations by one to two orders of magnitude at most of these sites. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 days), 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 is compensated by an overprediction of its effectiveness as INP. Therefore, it is important to correct the biases in E3SM's simulated dust life cycle and update E3SM's INP parameterizations. INP prediction errors of two to three orders of magnitude can have considerable impacts on the simulated cloud and radiative properties in global climate models. On comparing INP concentrations during MICRE against a relative ship-based campaign, Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS), we find that INPs from the latter are significantly higher only in regions closer to the Macquarie Island. This suggests that physical, chemical and biological processes affecting INP concentrations as stimulated by the presence of the island could be partly responsible for the high INP concentrations observed at the Macquarie Island during the MICRE campaign. Therefore, improvements to both aerosol simulation and INP parameterizations are required to adequately simulate INPs and their cloud impacts in E3SM. It will be helpful to include a parallel measurement of the size-resolved aerosol composition, and explore opportunities for long-term at-sea measurement platforms in future field campaigns studying INP sources in remote marine regions.

Aishwarya Raman et al.

Status: open (until 26 Jun 2022)

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  • RC1: 'Review of “Long-term Variability in immersion-mode Marine Ice Nucleating Particles from Climate Model Simulations and Observations” by Raman et al.', Anonymous Referee #1, 10 May 2022 reply

Aishwarya Raman et al.

Aishwarya Raman et al.


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Short summary
Ice nucleating particles (INPs) play an important role in cloud processes and associated precipitation. Yet, INPs are not accurately represented in climate models. This study attempts to uncover these gaps by comparing model-simulated INP concentrations against field campaign measurements in the SO for an entire year, 2017–2018. Differences in INP concentrations and variability between the model and observations have major implications for modeling cloud properties in high latitudes.