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Title: Effect of Tropical Nonconvective Condensation on Uncertainty in Modeled Projections of Rainfall

Abstract

Abstract We find that part of the uncertainty in the amplitude and pattern of the modeled precipitation response to CO2 forcing traces to tropical condensation not directly involved with parameterized convection. The fraction of tropical rainfall associated with large-scale condensation can vary from a few percent to well over half depending on model details and parameter settings. In turn, because of the coupling between condensation and tropical circulation, the different ways model assumptions affect the large-scale rainfall fraction also affect the patterns of the response within individual models. In two single-model ensembles based on the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM), versions 3.1 and 5.3, we find strong correlations between the fraction of tropical large-scale rain and both climatological rainfall and circulation and the response to CO2 forcing. While the effects of an increasing tropical large-scale rain fraction are opposite in some ways in the two ensembles—for example, the Hadley circulation weakens with the large-scale rainfall fraction in the CAM3.1 ensemble while strengthening in the CAM5.3 ensemble—we can nonetheless understand these different effects in terms of the relationship between latent heating and circulation, and we propose explanations for each ensemble. We compare these results with datamore » from phase 5 of the Coupled Model Intercomparison Project (CMIP5), for which some of the same patterns hold. Given the importance of this partitioning, there is a need for constraining this source of uncertainty using observations. However, since a “large-scale rainfall fraction” is a modeling construct, it is not clear how observations may be used to test various modeling assumptions determining this fraction.« less

Authors:
 [1];  [2];  [3]
+ Show Author Affiliations
  1. Department of Physics, and Institute for Geophysics, The University of Texas at Austin, Austin, Texas
  2. Institute for Geophysics, The University of Texas at Austin, Austin, Texas
  3. Lawrence Livermore National Laboratory, Livermore, California, and Institute for Geophysics, The University of Texas at Austin, Austin, Texas
Publication Date:
Research Org.:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF)
OSTI Identifier:
1560348
Alternate Identifier(s):
OSTI ID: 1644757
Report Number(s):
LLNL-JRNL-800644
Journal ID: ISSN 0894-8755
Grant/Contract Number:  
SC0016401; SC0006985; OCE 0415738; AC52-07NA27344
Resource Type:
Published Article
Journal Name:
Journal of Climate
Additional Journal Information:
Journal Name: Journal of Climate Journal Volume: 32 Journal Issue: 19; Journal ID: ISSN 0894-8755
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Hadley circulation; precipitation; climate prediction; ensembles; parameterization

Citation Formats

Stephens, Benjamin A., Jackson, Charles S., and Wagman, Benjamin M. Effect of Tropical Nonconvective Condensation on Uncertainty in Modeled Projections of Rainfall. United States: N. p., 2019. Web. doi:10.1175/JCLI-D-18-0833.1.
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Stephens, Benjamin A., Jackson, Charles S., & Wagman, Benjamin M. Effect of Tropical Nonconvective Condensation on Uncertainty in Modeled Projections of Rainfall. United States. https://doi.org/10.1175/JCLI-D-18-0833.1
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Stephens, Benjamin A., Jackson, Charles S., and Wagman, Benjamin M. Thu . "Effect of Tropical Nonconvective Condensation on Uncertainty in Modeled Projections of Rainfall". United States. https://doi.org/10.1175/JCLI-D-18-0833.1.
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@article{osti_1560348,
title = {Effect of Tropical Nonconvective Condensation on Uncertainty in Modeled Projections of Rainfall},
author = {Stephens, Benjamin A. and Jackson, Charles S. and Wagman, Benjamin M.},
abstractNote = {Abstract We find that part of the uncertainty in the amplitude and pattern of the modeled precipitation response to CO2 forcing traces to tropical condensation not directly involved with parameterized convection. The fraction of tropical rainfall associated with large-scale condensation can vary from a few percent to well over half depending on model details and parameter settings. In turn, because of the coupling between condensation and tropical circulation, the different ways model assumptions affect the large-scale rainfall fraction also affect the patterns of the response within individual models. In two single-model ensembles based on the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM), versions 3.1 and 5.3, we find strong correlations between the fraction of tropical large-scale rain and both climatological rainfall and circulation and the response to CO2 forcing. While the effects of an increasing tropical large-scale rain fraction are opposite in some ways in the two ensembles—for example, the Hadley circulation weakens with the large-scale rainfall fraction in the CAM3.1 ensemble while strengthening in the CAM5.3 ensemble—we can nonetheless understand these different effects in terms of the relationship between latent heating and circulation, and we propose explanations for each ensemble. We compare these results with data from phase 5 of the Coupled Model Intercomparison Project (CMIP5), for which some of the same patterns hold. Given the importance of this partitioning, there is a need for constraining this source of uncertainty using observations. However, since a “large-scale rainfall fraction” is a modeling construct, it is not clear how observations may be used to test various modeling assumptions determining this fraction.},
doi = {10.1175/JCLI-D-18-0833.1},
journal = {Journal of Climate},
number = 19,
volume = 32,
place = {United States},
year = {Thu Sep 05 00:00:00 EDT 2019},
month = {Thu Sep 05 00:00:00 EDT 2019}
}
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