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Article Type:
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Analysis of Convective Transport and Parameter Sensitivity in a Single Column Version of the Goddard Earth Observation System, Version 5, General Circulation Model

L. E. Ott Global Modeling and Assimilation Office, NASA GSFC, Greenbelt, Maryland

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J. Bacmeister Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, Maryland

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S. Pawson Global Modeling and Assimilation Office, NASA GSFC, Greenbelt, Maryland

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K. Pickering NASA GSFC, Greenbelt, Maryland

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G. Stenchikov Department of Environmental Sciences, Rutgers, The State University of New Jersey, New Brunswick, New Jersey

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M. Suarez Global Modeling and Assimilation Office, NASA GSFC, Greenbelt, Maryland

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H. Huntrieser Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, Germany

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M. Loewenstein *NASA ARC, Moffett Field, California

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J. Lopez Bay Area Environmental Research Institute, Sonoma, California

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I. Xueref-Remy Institut Pierre Simon Laplace, Laboratoire des Sciences du Climat et de l’Environnement, UMR CEA/CNRS 1572, Gif-sur-Yvette, France

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Print Publication:
01 Mar 2009
DOI:
https://doi.org/10.1175/2008JAS2694.1
Page(s):
627–646
Restricted access

Abstract

Convection strongly influences the distribution of atmospheric trace gases. General circulation models (GCMs) use convective mass fluxes calculated by parameterizations to transport gases, but the results are difficult to compare with trace gas observations because of differences in scale. The high resolution of cloud-resolving models (CRMs) facilitates direct comparison with aircraft observations. Averaged over a sufficient area, CRM results yield a validated product directly comparable to output from a single global model grid column. This study presents comparisons of vertical profiles of convective mass flux and trace gas mixing ratios derived from CRM and single column model (SCM) simulations of storms observed during three field campaigns. In all three cases, SCM simulations underpredicted convective mass flux relative to CRM simulations. As a result, the SCM simulations produced lower trace gas mixing ratios in the upper troposphere in two of the three storms than did the CRM simulations.

The impact of parameter sensitivity in the moist physics schemes employed in the SCM has also been examined. Statistical techniques identified the most significant parameters influencing convective transport. Convective mass fluxes are shown to be strongly dependent on chosen parameter values. Results show that altered parameter settings can substantially improve the comparison between SCM and CRM convective mass flux. Upper tropospheric trace gas mixing ratios were also improved in two storms. In the remaining storm, the SCM representation of CO2 was not improved because of differences in entrainment and detrainment levels in the CRM and SCM simulations.

Corresponding author address: Lesley Ott, Global Modeling and Assimilation Office, Code 610.1, Goddard Space Flight Center, Greenbelt, MD 20771. Email: lesley.e.ott@nasa.gov

Abstract

Convection strongly influences the distribution of atmospheric trace gases. General circulation models (GCMs) use convective mass fluxes calculated by parameterizations to transport gases, but the results are difficult to compare with trace gas observations because of differences in scale. The high resolution of cloud-resolving models (CRMs) facilitates direct comparison with aircraft observations. Averaged over a sufficient area, CRM results yield a validated product directly comparable to output from a single global model grid column. This study presents comparisons of vertical profiles of convective mass flux and trace gas mixing ratios derived from CRM and single column model (SCM) simulations of storms observed during three field campaigns. In all three cases, SCM simulations underpredicted convective mass flux relative to CRM simulations. As a result, the SCM simulations produced lower trace gas mixing ratios in the upper troposphere in two of the three storms than did the CRM simulations.

The impact of parameter sensitivity in the moist physics schemes employed in the SCM has also been examined. Statistical techniques identified the most significant parameters influencing convective transport. Convective mass fluxes are shown to be strongly dependent on chosen parameter values. Results show that altered parameter settings can substantially improve the comparison between SCM and CRM convective mass flux. Upper tropospheric trace gas mixing ratios were also improved in two storms. In the remaining storm, the SCM representation of CO2 was not improved because of differences in entrainment and detrainment levels in the CRM and SCM simulations.

Corresponding author address: Lesley Ott, Global Modeling and Assimilation Office, Code 610.1, Goddard Space Flight Center, Greenbelt, MD 20771. Email: lesley.e.ott@nasa.gov

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