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Title: Improving Predictability of Mixed-Phase Clouds and Aerosol Interactions in the Community Earth System Model (CESM) with ARM Measurements

Abstract

The objective of this project is to improve the simulation and predictability of mixed-phase clouds and aerosol interactions in the Community Earth System Model (CESM) through comparisons with the DOE ARM observations. There are four major goals of the proposed study: (1) Improve the representation of ice microphysical processes in mixed-phase clouds; (2) Develop a long-term multi-sensor mixed-phase cloud dataset; (3) Test the performance of improved ice microphysics in CESM-CAM5 with the ARM data; and (4) Examine mixed-phase cloud microphysics-aerosol-dynamics-radiation interactions in CESM-CAM5. In this project, we have (1) Improved the representation of ice microphysical processes in mixed-phase clouds that include ice nucleation, ice depositional growth through the Wegener–Bergeron–Findeisen (WBF) process, feedbacks between cloud microphysics, dynamics and radiation, and provides links to aerosol properties in the Community Earth System Model (CESM)-Community Atmosphere Model version 5 (CAM5); (2) Developed a long-term multi-sensor mixed-phase cloud dataset. The mixed-phase cloud retrieval algorithms are improved by refining the phase determinations and ice number concentration retrievals. A multi-year mixed-phase cloud observation dataset (1999-2004; October 2013-February 2017) is regenerated at the ARM Barrow site with the improved algorithms. The dataset has been used in the global model evaluation to improve the model parameterizations; (3) Tested themore » performance of improved ice microphysics in CESM-CAM5 with the ARM data. CESM-CAM5 is run in the DOE Cloud-Associated Parameterizations Testbed (CAPT) and in the single-column model (SCM) mode to facilitate comparison with ARM observations. Multi-year CAPT simulations of seasonal variations of cloud microphysical properties, cloud liquid water path (LWP) and ice water path (IWP), cloud longwave and shortwave forcings, cloud occurrence frequency are evaluated against the ARM multi-sensor mixed-phase cloud retrievals; and (4) Examined mixed-phase cloud microphysics-aerosol-dynamics-radiation interactions in CESM-CAM5 that include the impacts of different ice nucleation mechanisms, sensitivity to dust IN concentration, treatment of the WBF process on mixed-phase cloud properties. Aerosol effect on mixed-phase clouds through the liquid phase (droplet activation) and ice phase processes (e.g., the glaciation indirect effect) is investigated.« less

Authors:
;
Publication Date:
Research Org.:
Univ. of Wyoming, Laramie, WY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23). Climate and Environmental Sciences Division
OSTI Identifier:
1601142
Report Number(s):
DOE-UWY-SC0014239
DOE Contract Number:  
SC0014239
Resource Type:
Technical Report
Resource Relation:
Related Information: 1. Zhang, M., X. Liu, M. Diao, J. D’Alessandro, Y. Wang, C. Wu, D. Zhang, Z. Wang, and S. Xie (2019), Impacts of representing heterogeneous distribution of cloud liquid and ice on phase partitioning of Arctic mixed-phase clouds with NCAR CAM5, Journal of Geophysical Research, 124, 13,071–13,090. https://doi.org/10.1029/2019JD030502.2. Zhang, M., S. Xie, X. Liu, W. Lin, K. Zhang, H.-Y. Ma, X. Zheng, and Y. Zhang (2019), Toward understanding the phase partitioning of Arctic mixed-phase clouds simulated in E3SM with ARM M-PACE observations, Earth and Space Science, in revision.3. Wang, Y., D. Zhang, X. Liu, and Z. Wang (2018), Distinct contributions of ice nucleation, large-scale environment, and shallow cumulus detrainment to cloud phase partitioning with NCAR CAM5, Journal of Geophysical Research, 123, 1132–1154. https://doi.org/10.1002/2017JD027213.4. Shi, Y., and X. Liu (2019), Dust radiative effects on climate by glaciating mixed-phase clouds, Geophysical Research Letters, 46, 6128–6137, https://doi.org/10.1029/2019GL082504.5. Zhao, B., Y. Wang, Y. Gu, K.-N. Liou, J. H. Jiang, J. Fan, X. Liu, L. Huang, and Y. L. Yung (2019), Evidence for the ice nucleation ability of anthropogenic aerosols, Nature Geosciences, 12, 602–607, https://doi.org/10.1038/s41561-019-0389-4.6. D’Alessandro, J., M. Diao, C. Wu, X. Liu, J. B. Jensen, and B. Stephens (2019), Cloud phase and relative humidity distributions over the Southern Ocean in austral summer based on in situ observations and CAM5 simulations, Journal of Climate, 32, 2781–2805. DOI: 10.1175/JCLI-D-18-0232.1.7. Wu, C., X. Liu, M. Diao, K. Zhang, A. Gettelman, Z. Lu, J. E. Penner, and Z. Lin (2017), Direct comparisons of ice cloud macro- and microphysical properties simulated by the Community Atmosphere Model version 5 with HIPPO aircraft observations, Atmospheric Chemistry and Physics, 17, 4731–4749, doi:10.5194/acp-17-4731-2017.8. Fan, J., Y. Wang, D. Rosenfeld, and X. Liu (2016), Review of aerosol-cloud interactions: Mechanisms, significance and challenges, Journal of the Atmospheric Sciences, 73, 4221–4252, doi: 10.1175/JAS-D-16-0037.1.
Country of Publication:
United States
Language:
English

Citation Formats

Liu, Xiaohong, and Wang, Zhien. Improving Predictability of Mixed-Phase Clouds and Aerosol Interactions in the Community Earth System Model (CESM) with ARM Measurements. United States: N. p., 2020. Web.
Liu, Xiaohong, & Wang, Zhien. Improving Predictability of Mixed-Phase Clouds and Aerosol Interactions in the Community Earth System Model (CESM) with ARM Measurements. United States.
Liu, Xiaohong, and Wang, Zhien. Tue . "Improving Predictability of Mixed-Phase Clouds and Aerosol Interactions in the Community Earth System Model (CESM) with ARM Measurements". United States. https://www.osti.gov/servlets/purl/1601142.
@article{osti_1601142,
title = {Improving Predictability of Mixed-Phase Clouds and Aerosol Interactions in the Community Earth System Model (CESM) with ARM Measurements},
author = {Liu, Xiaohong and Wang, Zhien},
abstractNote = {The objective of this project is to improve the simulation and predictability of mixed-phase clouds and aerosol interactions in the Community Earth System Model (CESM) through comparisons with the DOE ARM observations. There are four major goals of the proposed study: (1) Improve the representation of ice microphysical processes in mixed-phase clouds; (2) Develop a long-term multi-sensor mixed-phase cloud dataset; (3) Test the performance of improved ice microphysics in CESM-CAM5 with the ARM data; and (4) Examine mixed-phase cloud microphysics-aerosol-dynamics-radiation interactions in CESM-CAM5. In this project, we have (1) Improved the representation of ice microphysical processes in mixed-phase clouds that include ice nucleation, ice depositional growth through the Wegener–Bergeron–Findeisen (WBF) process, feedbacks between cloud microphysics, dynamics and radiation, and provides links to aerosol properties in the Community Earth System Model (CESM)-Community Atmosphere Model version 5 (CAM5); (2) Developed a long-term multi-sensor mixed-phase cloud dataset. The mixed-phase cloud retrieval algorithms are improved by refining the phase determinations and ice number concentration retrievals. A multi-year mixed-phase cloud observation dataset (1999-2004; October 2013-February 2017) is regenerated at the ARM Barrow site with the improved algorithms. The dataset has been used in the global model evaluation to improve the model parameterizations; (3) Tested the performance of improved ice microphysics in CESM-CAM5 with the ARM data. CESM-CAM5 is run in the DOE Cloud-Associated Parameterizations Testbed (CAPT) and in the single-column model (SCM) mode to facilitate comparison with ARM observations. Multi-year CAPT simulations of seasonal variations of cloud microphysical properties, cloud liquid water path (LWP) and ice water path (IWP), cloud longwave and shortwave forcings, cloud occurrence frequency are evaluated against the ARM multi-sensor mixed-phase cloud retrievals; and (4) Examined mixed-phase cloud microphysics-aerosol-dynamics-radiation interactions in CESM-CAM5 that include the impacts of different ice nucleation mechanisms, sensitivity to dust IN concentration, treatment of the WBF process on mixed-phase cloud properties. Aerosol effect on mixed-phase clouds through the liquid phase (droplet activation) and ice phase processes (e.g., the glaciation indirect effect) is investigated.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {2}
}

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Works referenced in this record:

Direct comparisons of ice cloud macro- and microphysical properties simulated by the Community Atmosphere Model version 5 with HIPPO aircraft observations
journal, January 2017

  • Wu, Chenglai; Liu, Xiaohong; Diao, Minghui
  • Atmospheric Chemistry and Physics, Vol. 17, Issue 7
  • DOI: 10.5194/acp-17-4731-2017

On the freezing time of supercooled drops in developing convective clouds over tropical ocean
journal, October 2018


Dust Radiative Effects on Climate by Glaciating Mixed‐Phase Clouds
journal, June 2019

  • Shi, Yang; Liu, Xiaohong
  • Geophysical Research Letters, Vol. 46, Issue 11
  • DOI: 10.1029/2019GL082504

Cloud Phase and Relative Humidity Distributions over the Southern Ocean in Austral Summer Based on In Situ Observations and CAM5 Simulations
journal, May 2019

  • D’Alessandro, John J.; Diao, Minghui; Wu, Chenglai
  • Journal of Climate, Vol. 32, Issue 10
  • DOI: 10.1175/JCLI-D-18-0232.1

Can cirrus cloud seeding be used for geoengineering?: CIRRUS CLOUD SEEDING
journal, October 2015

  • Penner, Joyce E.; Zhou, Cheng; Liu, Xiaohong
  • Geophysical Research Letters, Vol. 42, Issue 20
  • DOI: 10.1002/2015GL065992

Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges
journal, November 2016

  • Fan, Jiwen; Wang, Yuan; Rosenfeld, Daniel
  • Journal of the Atmospheric Sciences, Vol. 73, Issue 11
  • DOI: 10.1175/JAS-D-16-0037.1

Ice nucleation by aerosols from anthropogenic pollution
journal, July 2019


Distinct Contributions of Ice Nucleation, Large-Scale Environment, and Shallow Cumulus Detrainment to Cloud Phase Partitioning With NCAR CAM5
journal, January 2018

  • Wang, Yong; Zhang, Damao; Liu, Xiaohong
  • Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 2
  • DOI: 10.1002/2017JD027213