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Title: Clouds and more: ARM climate modeling best estimate data: A new data product for climate studies

Abstract

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) was created in 1989 to address scientific uncertainties related to global climate change, with a focus on the crucial role of clouds and their influence on the transfer of radiation atmosphere. Here, a central activity is the acquisition of detailed observations of clouds and radiation, as well as related atmospheric variables for climate model evaluation and improvement.

Authors:
 [1];  [1];  [1];  [1];  [2];  [3];  [4];  [5];  [6];  [2];  [2];  [5];  [4];  [4];  [6];  [4];  [6];  [4];  [7]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States)
  3. The Pennsylvania State Univ., University Park, PA (United States)
  4. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  5. NOAA Geophysical Fluid Dynamics Lab., Princeton, NJ (United States)
  6. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  7. Univ. of Wisconsin, Madison, WI (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab., Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1281659
Report Number(s):
LLNL-JRNL-412676
Journal ID: ISSN 0003-0007
Grant/Contract Number:  
AC52-07NA27344
Resource Type:
Accepted Manuscript
Journal Name:
Bulletin of the American Meteorological Society
Additional Journal Information:
Journal Volume: 91; Journal Issue: 1; Journal ID: ISSN 0003-0007
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Xie, Shaocheng, McCoy, Renata B., Klein, Stephen A., Cederwall, Richard T., Wiscombe, Warren J., Clothiaux, Eugene E., Gaustad, Krista L., Golaz, Jean -Christophe, Hall, Stephanie D., Jensen, Michael P., Johnson, Karen L., Lin, Yanluan, Long, Charles N., Mather, James H., McCord, Raymond A., McFarlane, Sally A., Palanisamy, Giri, Shi, Yan, and Turner, David D. Clouds and more: ARM climate modeling best estimate data: A new data product for climate studies. United States: N. p., 2010. Web. doi:10.1175/2009BAMS2891.1.
Xie, Shaocheng, McCoy, Renata B., Klein, Stephen A., Cederwall, Richard T., Wiscombe, Warren J., Clothiaux, Eugene E., Gaustad, Krista L., Golaz, Jean -Christophe, Hall, Stephanie D., Jensen, Michael P., Johnson, Karen L., Lin, Yanluan, Long, Charles N., Mather, James H., McCord, Raymond A., McFarlane, Sally A., Palanisamy, Giri, Shi, Yan, & Turner, David D. Clouds and more: ARM climate modeling best estimate data: A new data product for climate studies. United States. doi:10.1175/2009BAMS2891.1.
Xie, Shaocheng, McCoy, Renata B., Klein, Stephen A., Cederwall, Richard T., Wiscombe, Warren J., Clothiaux, Eugene E., Gaustad, Krista L., Golaz, Jean -Christophe, Hall, Stephanie D., Jensen, Michael P., Johnson, Karen L., Lin, Yanluan, Long, Charles N., Mather, James H., McCord, Raymond A., McFarlane, Sally A., Palanisamy, Giri, Shi, Yan, and Turner, David D. Fri . "Clouds and more: ARM climate modeling best estimate data: A new data product for climate studies". United States. doi:10.1175/2009BAMS2891.1. https://www.osti.gov/servlets/purl/1281659.
@article{osti_1281659,
title = {Clouds and more: ARM climate modeling best estimate data: A new data product for climate studies},
author = {Xie, Shaocheng and McCoy, Renata B. and Klein, Stephen A. and Cederwall, Richard T. and Wiscombe, Warren J. and Clothiaux, Eugene E. and Gaustad, Krista L. and Golaz, Jean -Christophe and Hall, Stephanie D. and Jensen, Michael P. and Johnson, Karen L. and Lin, Yanluan and Long, Charles N. and Mather, James H. and McCord, Raymond A. and McFarlane, Sally A. and Palanisamy, Giri and Shi, Yan and Turner, David D.},
abstractNote = {The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) was created in 1989 to address scientific uncertainties related to global climate change, with a focus on the crucial role of clouds and their influence on the transfer of radiation atmosphere. Here, a central activity is the acquisition of detailed observations of clouds and radiation, as well as related atmospheric variables for climate model evaluation and improvement.},
doi = {10.1175/2009BAMS2891.1},
journal = {Bulletin of the American Meteorological Society},
number = 1,
volume = 91,
place = {United States},
year = {2010},
month = {1}
}

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Works referencing / citing this record:

CAUSES: Attribution of Surface Radiation Biases in NWP and Climate Models near the U.S. Southern Great Plains
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  • Van Weverberg, K.; Morcrette, C. J.; Petch, J.
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  • DOI: 10.1002/2017jd027188

Introduction to CAUSES: Description of Weather and Climate Models and Their Near‐Surface Temperature Errors in 5 day Hindcasts Near the Southern Great Plains
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Observationally derived rise in methane surface forcing mediated by water vapour trends
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Evaluation of cloud fraction and its radiative effect simulated by IPCC AR4 global models against ARM surface observations
journal, January 2012


An intercomparison of radar-based liquid cloud microphysics retrievals and implication for model evaluation studies
journal, January 2011

  • Huang, D.; Zhao, C.; Dunn, M.
  • Atmospheric Measurement Techniques Discussions, Vol. 4, Issue 6
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Interactions between cumulus convection and its environment as revealed by the MC3E sounding array: Convection with its environment
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  • Xie, Shaocheng; Zhang, Yunyan; Giangrande, Scott E.
  • Journal of Geophysical Research: Atmospheres, Vol. 119, Issue 20
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Scale‐aware parameterization of liquid cloud inhomogeneity and its impact on simulated climate in CESM
journal, August 2015

  • Xie, Xin; Zhang, Minghua
  • Journal of Geophysical Research: Atmospheres, Vol. 120, Issue 16
  • DOI: 10.1002/2015jd023565

Modifications to WRF's dynamical core to improve the treatment of moisture for large-eddy simulations: WRF DY-CORE MOISTURE TREATMENT
journal, October 2015

  • Xiao, Heng; Endo, Satoshi; Wong, May
  • Journal of Advances in Modeling Earth Systems, Vol. 7, Issue 4
  • DOI: 10.1002/2015ms000532

Can MODIS cloud fraction fully represent the diurnal and seasonal variations at DOE ARM SGP and Manus sites?: Time Representation Error in MODIS CF
journal, January 2017

  • Wang, Yang; Zhao, Chuanfeng
  • Journal of Geophysical Research: Atmospheres, Vol. 122, Issue 1
  • DOI: 10.1002/2016jd025954

Using ARM Observations to Evaluate Climate Model Simulations of Land-Atmosphere Coupling on the U.S. Southern Great Plains: Model LAC Evaluation by ARM Data
journal, November 2017

  • Phillips, Thomas J.; Klein, Stephen A.; Ma, Hsi-Yen
  • Journal of Geophysical Research: Atmospheres, Vol. 122, Issue 21
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CAUSES: On the Role of Surface Energy Budget Errors to the Warm Surface Air Temperature Error Over the Central United States
journal, March 2018

  • Ma, H. ‐Y.; Klein, S. A.; Xie, S.
  • Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 5
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CAUSES: Diagnosis of the Summertime Warm Bias in CMIP5 Climate Models at the ARM Southern Great Plains Site
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  • Zhang, Chengzhu; Xie, Shaocheng; Klein, Stephen A.
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Mixed-phase clouds cause climate model biases in Arctic wintertime temperature inversions
journal, October 2013


Testing cloud microphysics parameterizations in NCAR CAM5 with ISDAC and M-PACE observations
journal, January 2011

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Toward understanding of differences in current cloud retrievals of ARM ground-based measurements: UNDERSTANDING CLOUD RETRIEVAL DIFFERENCE
journal, May 2012

  • Zhao, Chuanfeng; Xie, Shaocheng; Klein, Stephen A.
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journal, October 2010


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