Final Technical Report for "Ice nuclei relation to aerosol properties: Data analysis and model parameterization for IN in mixed-phase clouds" (DOE/SC00002354)

Clouds play an important role in weather and climate. In addition to their key role in the hydrologic cycle, clouds scatter incoming solar radiation and trap infrared radiation from the surface and lower atmosphere. Despite their importance, feedbacks involving clouds remain as one of the largest so...

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Main Authors: DeMott, Paul J., Prenni, Anthony J., Kreidenweis, Sonia M.
Other Authors: United States. Department of Energy., United States. Department of Energy. Office of Biological and Environmental Research.
Format: Report
Language:English
Published: Colorado State University 2012
Subjects:
Online Access:https://doi.org/10.2172/1052155
https://digital.library.unt.edu/ark:/67531/metadc841250/
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author DeMott, Paul J.
Prenni, Anthony J.
Kreidenweis, Sonia M.
author2 United States. Department of Energy.
United States. Department of Energy. Office of Biological and Environmental Research.
author_facet DeMott, Paul J.
Prenni, Anthony J.
Kreidenweis, Sonia M.
author_sort DeMott, Paul J.
collection University of North Texas: UNT Digital Library
description Clouds play an important role in weather and climate. In addition to their key role in the hydrologic cycle, clouds scatter incoming solar radiation and trap infrared radiation from the surface and lower atmosphere. Despite their importance, feedbacks involving clouds remain as one of the largest sources of uncertainty in climate models. To better simulate cloud processes requires better characterization of cloud microphysical processes, which can affect the spatial extent, optical depth and lifetime of clouds. To this end, we developed a new parameterization to be used in numerical models that describes the variation of ice nuclei (IN) number concentrations active to form ice crystals in mixed-phase (water droplets and ice crystals co-existing) cloud conditions as these depend on existing aerosol properties and temperature. The parameterization is based on data collected using the Colorado State University continuous flow diffusion chamber in aircraft and ground-based campaigns over a 14-year period, including data from the DOE-supported Mixed-Phase Arctic Cloud Experiment. The resulting relationship is shown to more accurately represent the variability of ice nuclei distributions in the atmosphere compared to currently used parameterizations based on temperature alone. When implemented in one global climate model, the new parameterization predicted more realistic annually averaged cloud water and ice distributions, and cloud radiative properties, especially for sensitive higher latitude mixed-phase cloud regions. As a test of the new global IN scheme, it was compared to independent data collected during the 2008 DOE-sponsored Indirect and Semi-Direct Aerosol Campaign (ISDAC). Good agreement with this new data set suggests the broad applicability of the new scheme for describing general (non-chemically specific) aerosol influences on IN number concentrations feeding mixed-phase Arctic stratus clouds. Finally, the parameterization was implemented into a regional cloud-resolving model to compare predictions of ice crystal concentrations and other cloud properties to those observed in two intensive case studies of Arctic stratus during ISDAC. Our implementation included development of a prognostic scheme of ice activation using the IN parameterization so that the most realistic treatment of ice nuclei, including their budget (gains and losses), was achieved. Many cloud microphysical properties and cloud persistence were faithfully reproduced, despite a tendency to under-predict (by a few to several times) ice crystal number concentrations and cloud ice mass, in agreement with some other studies. This work serves generally as the basis for improving predictive schemes for cloud ice crystal activation in cloud and climate models, and more specifically as the basis for such a scheme to be used in a Multi-scale Modeling Format (MMF) that utilizes a connected system of cloud-resolving models on a global grid in an effort to better resolve cloud processes and their influence on climate.
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spelling ftunivnotexas:info:ark/67531/metadc841250 2025-01-16T20:29:23+00:00 Final Technical Report for "Ice nuclei relation to aerosol properties: Data analysis and model parameterization for IN in mixed-phase clouds" (DOE/SC00002354) DeMott, Paul J. Prenni, Anthony J. Kreidenweis, Sonia M. United States. Department of Energy. United States. Department of Energy. Office of Biological and Environmental Research. 2012-09-28 2 MB; 17 pages, 6 images Text https://doi.org/10.2172/1052155 https://digital.library.unt.edu/ark:/67531/metadc841250/ English eng Colorado State University rep-no: DOE/SC0002354-1 grantno: SC0002354 doi:10.2172/1052155 osti: 1052155 https://digital.library.unt.edu/ark:/67531/metadc841250/ ark: ark:/67531/metadc841250 Aerosol Indirect Effects Mixed-Phase Clouds Ice Nuclei 54 Environmental Sciences Arctic Clouds 58 Geosciences Ice Nuclei Aerosol-Cloud Interactions Report 2012 ftunivnotexas https://doi.org/10.2172/1052155 2018-04-28T22:08:10Z Clouds play an important role in weather and climate. In addition to their key role in the hydrologic cycle, clouds scatter incoming solar radiation and trap infrared radiation from the surface and lower atmosphere. Despite their importance, feedbacks involving clouds remain as one of the largest sources of uncertainty in climate models. To better simulate cloud processes requires better characterization of cloud microphysical processes, which can affect the spatial extent, optical depth and lifetime of clouds. To this end, we developed a new parameterization to be used in numerical models that describes the variation of ice nuclei (IN) number concentrations active to form ice crystals in mixed-phase (water droplets and ice crystals co-existing) cloud conditions as these depend on existing aerosol properties and temperature. The parameterization is based on data collected using the Colorado State University continuous flow diffusion chamber in aircraft and ground-based campaigns over a 14-year period, including data from the DOE-supported Mixed-Phase Arctic Cloud Experiment. The resulting relationship is shown to more accurately represent the variability of ice nuclei distributions in the atmosphere compared to currently used parameterizations based on temperature alone. When implemented in one global climate model, the new parameterization predicted more realistic annually averaged cloud water and ice distributions, and cloud radiative properties, especially for sensitive higher latitude mixed-phase cloud regions. As a test of the new global IN scheme, it was compared to independent data collected during the 2008 DOE-sponsored Indirect and Semi-Direct Aerosol Campaign (ISDAC). Good agreement with this new data set suggests the broad applicability of the new scheme for describing general (non-chemically specific) aerosol influences on IN number concentrations feeding mixed-phase Arctic stratus clouds. Finally, the parameterization was implemented into a regional cloud-resolving model to compare predictions of ice crystal concentrations and other cloud properties to those observed in two intensive case studies of Arctic stratus during ISDAC. Our implementation included development of a prognostic scheme of ice activation using the IN parameterization so that the most realistic treatment of ice nuclei, including their budget (gains and losses), was achieved. Many cloud microphysical properties and cloud persistence were faithfully reproduced, despite a tendency to under-predict (by a few to several times) ice crystal number concentrations and cloud ice mass, in agreement with some other studies. This work serves generally as the basis for improving predictive schemes for cloud ice crystal activation in cloud and climate models, and more specifically as the basis for such a scheme to be used in a Multi-scale Modeling Format (MMF) that utilizes a connected system of cloud-resolving models on a global grid in an effort to better resolve cloud processes and their influence on climate. Report Arctic University of North Texas: UNT Digital Library Arctic
spellingShingle Aerosol Indirect Effects
Mixed-Phase Clouds
Ice Nuclei
54 Environmental Sciences
Arctic Clouds
58 Geosciences Ice Nuclei
Aerosol-Cloud Interactions
DeMott, Paul J.
Prenni, Anthony J.
Kreidenweis, Sonia M.
Final Technical Report for "Ice nuclei relation to aerosol properties: Data analysis and model parameterization for IN in mixed-phase clouds" (DOE/SC00002354)
title Final Technical Report for "Ice nuclei relation to aerosol properties: Data analysis and model parameterization for IN in mixed-phase clouds" (DOE/SC00002354)
title_full Final Technical Report for "Ice nuclei relation to aerosol properties: Data analysis and model parameterization for IN in mixed-phase clouds" (DOE/SC00002354)
title_fullStr Final Technical Report for "Ice nuclei relation to aerosol properties: Data analysis and model parameterization for IN in mixed-phase clouds" (DOE/SC00002354)
title_full_unstemmed Final Technical Report for "Ice nuclei relation to aerosol properties: Data analysis and model parameterization for IN in mixed-phase clouds" (DOE/SC00002354)
title_short Final Technical Report for "Ice nuclei relation to aerosol properties: Data analysis and model parameterization for IN in mixed-phase clouds" (DOE/SC00002354)
title_sort final technical report for "ice nuclei relation to aerosol properties: data analysis and model parameterization for in in mixed-phase clouds" (doe/sc00002354)
topic Aerosol Indirect Effects
Mixed-Phase Clouds
Ice Nuclei
54 Environmental Sciences
Arctic Clouds
58 Geosciences Ice Nuclei
Aerosol-Cloud Interactions
topic_facet Aerosol Indirect Effects
Mixed-Phase Clouds
Ice Nuclei
54 Environmental Sciences
Arctic Clouds
58 Geosciences Ice Nuclei
Aerosol-Cloud Interactions
url https://doi.org/10.2172/1052155
https://digital.library.unt.edu/ark:/67531/metadc841250/