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Title: Evaluation of Clouds in Version 1 of E3SM Atmosphere Model with Satellite and Simulators

Abstract

This study systematically evaluates clouds simulated by the Energy Exascale Earth System Model (E3SM) Atmosphere Model version one (EAMv1) against satellite and ground-based cloud observations. Both low (1°) and high (0.25°) resolution EAMv1 configurations generally underestimate clouds in low and midlatitutes and overestimate clouds in the Arctic although the error is smaller in the high-resolution model. The underestimate of clouds is due to the underestimate of optically thin to intermediate clouds. EAMv1 overestimates the optically intermediate to thick clouds. Other model errors include the largely under-predicted stratocumulus along the coasts and high clouds over the tropical deep convection regions. The underestimate of thin clouds results in too much LW radiation being emitted to space and too little SW radiation being reflected back to space while the overestimate of optically intermediate and thick clouds leads to too little LW radiation being emitted to space and too much SW radiation being reflected back to space. EAMv1 shows better skill in reproducing the observed distribution of clouds and their properties and has smaller radiatively relevant errors in the distribution of clouds than most of the CFMIP2 models. It produces more supercooled liquid cloud fraction than CAM5 and most CMIP5 models owing to amore » new ice nucleation scheme and a reduction of ice deposition growth rate. It simulates the diurnal variation of clouds during the summer season at SGP qualitatively well, with both the evolution of shallow clouds and the nocturnal peak in high clouds well captured, however, it largely overestimates the observed magnitude.« less

Authors:
 [1];  [1];  [2];  [1];  [1]; ORCiD logo [3];  [3]; ORCiD logo [3];  [4];  [1]
  1. Lawrence Livermore National Laboratory
  2. Brookhaven National Laboratory
  3. BATTELLE (PACIFIC NW LAB)
  4. LAWRENCE LIVERMORE
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1571516
Report Number(s):
PNNL-SA-139643
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Volume: 11; Journal Issue: 5
Country of Publication:
United States
Language:
English

Citation Formats

Zhang, Yuying, Xie, Shaocheng, Lin, Wuyin, Klein, Stephen A., Zelinka, Mark, Ma, Po Lun, Rasch, Philip J., Qian, Yun, Tang, Qi, and Ma, Hsi-Yen. Evaluation of Clouds in Version 1 of E3SM Atmosphere Model with Satellite and Simulators. United States: N. p., 2019. Web. doi:10.1029/2018MS001562.
Zhang, Yuying, Xie, Shaocheng, Lin, Wuyin, Klein, Stephen A., Zelinka, Mark, Ma, Po Lun, Rasch, Philip J., Qian, Yun, Tang, Qi, & Ma, Hsi-Yen. Evaluation of Clouds in Version 1 of E3SM Atmosphere Model with Satellite and Simulators. United States. doi:10.1029/2018MS001562.
Zhang, Yuying, Xie, Shaocheng, Lin, Wuyin, Klein, Stephen A., Zelinka, Mark, Ma, Po Lun, Rasch, Philip J., Qian, Yun, Tang, Qi, and Ma, Hsi-Yen. Thu . "Evaluation of Clouds in Version 1 of E3SM Atmosphere Model with Satellite and Simulators". United States. doi:10.1029/2018MS001562.
@article{osti_1571516,
title = {Evaluation of Clouds in Version 1 of E3SM Atmosphere Model with Satellite and Simulators},
author = {Zhang, Yuying and Xie, Shaocheng and Lin, Wuyin and Klein, Stephen A. and Zelinka, Mark and Ma, Po Lun and Rasch, Philip J. and Qian, Yun and Tang, Qi and Ma, Hsi-Yen},
abstractNote = {This study systematically evaluates clouds simulated by the Energy Exascale Earth System Model (E3SM) Atmosphere Model version one (EAMv1) against satellite and ground-based cloud observations. Both low (1°) and high (0.25°) resolution EAMv1 configurations generally underestimate clouds in low and midlatitutes and overestimate clouds in the Arctic although the error is smaller in the high-resolution model. The underestimate of clouds is due to the underestimate of optically thin to intermediate clouds. EAMv1 overestimates the optically intermediate to thick clouds. Other model errors include the largely under-predicted stratocumulus along the coasts and high clouds over the tropical deep convection regions. The underestimate of thin clouds results in too much LW radiation being emitted to space and too little SW radiation being reflected back to space while the overestimate of optically intermediate and thick clouds leads to too little LW radiation being emitted to space and too much SW radiation being reflected back to space. EAMv1 shows better skill in reproducing the observed distribution of clouds and their properties and has smaller radiatively relevant errors in the distribution of clouds than most of the CFMIP2 models. It produces more supercooled liquid cloud fraction than CAM5 and most CMIP5 models owing to a new ice nucleation scheme and a reduction of ice deposition growth rate. It simulates the diurnal variation of clouds during the summer season at SGP qualitatively well, with both the evolution of shallow clouds and the nocturnal peak in high clouds well captured, however, it largely overestimates the observed magnitude.},
doi = {10.1029/2018MS001562},
journal = {Journal of Advances in Modeling Earth Systems},
number = 5,
volume = 11,
place = {United States},
year = {2019},
month = {5}
}

Works referenced in this record:

COSP: Satellite simulation software for model assessment
journal, August 2011

  • Bodas-Salcedo, A.; Webb, M. J.; Bony, S.
  • Bulletin of the American Meteorological Society, Vol. 92, Issue 8
  • DOI: 10.1175/2011BAMS2856.1

Quantifying the Sources of Intermodel Spread in Equilibrium Climate Sensitivity
journal, January 2016

  • Caldwell, Peter M.; Zelinka, Mark D.; Taylor, Karl E.
  • Journal of Climate, Vol. 29, Issue 2
  • DOI: 10.1175/JCLI-D-15-0352.1

Evaluation of the cloud thermodynamic phase in a climate model using CALIPSO-GOCCP: CALIPSO-GOCCP CLOUD THERMODYNAMIC PHASE
journal, July 2013

  • Cesana, Grégory; Chepfer, Hélène
  • Journal of Geophysical Research: Atmospheres, Vol. 118, Issue 14
  • DOI: 10.1002/jgrd.50376

Ubiquitous low‐level liquid‐containing Arctic clouds: New observations and climate model constraints from CALIPSO‐GOCCP
journal, October 2012

  • Cesana, G.; Kay, J. E.; Chepfer, H.
  • Geophysical Research Letters, Vol. 39, Issue 20
  • DOI: 10.1029/2012GL053385

The GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP)
journal, January 2010

  • Chepfer, H.; Bony, S.; Winker, D.
  • Journal of Geophysical Research, Vol. 115
  • DOI: 10.1029/2009JD012251

Use of CALIPSO lidar observations to evaluate the cloudiness simulated by a climate model
journal, January 2008

  • Chepfer, H.; Bony, S.; Winker, D.
  • Geophysical Research Letters, Vol. 35, Issue 15
  • DOI: 10.1029/2008GL034207

Advanced Two-Moment Bulk Microphysics for Global Models. Part II: Global Model Solutions and Aerosol–Cloud Interactions
journal, February 2015


The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution
journal, July 2019

  • Golaz, Jean‐Christophe; Caldwell, Peter M.; Van Roekel, Luke P.
  • Journal of Advances in Modeling Earth Systems, Vol. 11, Issue 7
  • DOI: 10.1029/2018MS001603

A PDF-Based Model for Boundary Layer Clouds. Part I: Method and Model Description
journal, December 2002


Stratospheric variability and tropospheric ozone
journal, January 2009

  • Hsu, Juno; Prather, Michael J.
  • Journal of Geophysical Research, Vol. 114, Issue D6
  • DOI: 10.1029/2008JD010942

Occurrence, liquid water content, and fraction of supercooled water clouds from combined CALIOP/IIR/MODIS measurements
journal, January 2010

  • Hu, Yongxiang; Rodier, Sharon; Xu, Kuan-man
  • Journal of Geophysical Research, Vol. 115
  • DOI: 10.1029/2009JD012384

Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations: CAM Cloud Phase Evaluation with CALIPSO
journal, April 2016

  • Kay, Jennifer E.; Bourdages, Line; Miller, Nathaniel B.
  • Journal of Geophysical Research: Atmospheres, Vol. 121, Issue 8
  • DOI: 10.1002/2015JD024699

Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator: EVALUATING CLOUDS IN CLIMATE MODELS
journal, February 2013

  • Klein, Stephen A.; Zhang, Yuying; Zelinka, Mark D.
  • Journal of Geophysical Research: Atmospheres, Vol. 118, Issue 3
  • DOI: 10.1002/jgrd.50141

Using Probability Density Functions to Derive Consistent Closure Relationships among Higher-Order Moments
journal, April 2005

  • Larson, Vincent E.; Golaz, Jean-Christophe
  • Monthly Weather Review, Vol. 133, Issue 4
  • DOI: 10.1175/MWR2902.1

Stratocumulus Clouds in Southeastern Pacific Simulated by Eight CMIP5–CFMIP Global Climate Models
journal, April 2014


Description and evaluation of a new four-mode version of the Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model
journal, January 2016


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

  • Liu, Xiaohong; Xie, Shaocheng; Boyle, James
  • Journal of Geophysical Research, Vol. 116
  • DOI: 10.1029/2011JD015889

Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product
journal, January 2018


A review of cloud top height and optical depth histograms from MISR, ISCCP, and MODIS
journal, January 2010

  • Marchand, Roger; Ackerman, Thomas; Smyth, Mike
  • Journal of Geophysical Research, Vol. 115, Issue D16
  • DOI: 10.1029/2009JD013422

Mixed‐phase cloud physics and Southern Ocean cloud feedback in climate models
journal, September 2015

  • McCoy, Daniel T.; Hartmann, Dennis L.; Zelinka, Mark D.
  • Journal of Geophysical Research: Atmospheres, Vol. 120, Issue 18
  • DOI: 10.1002/2015JD023603

Stratospheric ozone in 3-D models: A simple chemistry and the cross-tropopause flux
journal, June 2000

  • McLinden, C. A.; Olsen, S. C.; Hannegan, B.
  • Journal of Geophysical Research: Atmospheres, Vol. 105, Issue D11
  • DOI: 10.1029/2000JD900124

The ‘too few, too bright’ tropical low-cloud problem in CMIP5 models: TOO FEW TOO BRIGHT LOW-CLOUDS
journal, November 2012

  • Nam, C.; Bony, S.; Dufresne, J. -L.
  • Geophysical Research Letters, Vol. 39, Issue 21
  • DOI: 10.1029/2012GL053421

Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits of Instrument Simulators
journal, July 2012


Parametric Sensitivity and Uncertainty Quantification in the Version 1 of E3SM Atmosphere Model Based on Short Perturbed Parameter Ensemble Simulations
journal, December 2018

  • Qian, Yun; Wan, Hui; Yang, Ben
  • Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 23
  • DOI: 10.1029/2018JD028927

A Diagnostic PDF Cloud Scheme to Improve Subtropical Low Clouds in NCAR Community Atmosphere Model ( CAM 5)
journal, February 2018

  • Qin, Yi; Lin, Yanluan; Xu, Shiming
  • Journal of Advances in Modeling Earth Systems, Vol. 10, Issue 2
  • DOI: 10.1002/2017MS001095

Advances in Understanding Clouds from ISCCP
journal, November 1999


Evaluating cloud tuning in a climate model with satellite observations: EVALUATION OF CLOUD TUNING
journal, August 2013

  • Suzuki, Kentaroh; Golaz, Jean-Christophe; Stephens, Graeme L.
  • Geophysical Research Letters, Vol. 40, Issue 16
  • DOI: 10.1002/grl.50874

Sensitivity Study on the Influence of Cloud Microphysical Parameters on Mixed-Phase Cloud Thermodynamic Phase Partitioning in CAM5
journal, February 2016


Different contact angle distributions for heterogeneous ice nucleation in the Community Atmospheric Model version 5
journal, January 2014


Simulations of Arctic mixed-phase clouds in forecasts with CAM3 and AM2 for M-PACE
journal, January 2008

  • Xie, Shaocheng; Boyle, James; Klein, Stephen A.
  • Journal of Geophysical Research, Vol. 113, Issue D4
  • DOI: 10.1029/2007JD009225

Understanding Cloud and Convective Characteristics in Version 1 of the E3SM Atmosphere Model
journal, October 2018

  • Xie, Shaocheng; Lin, Wuyin; Rasch, Philip J.
  • Journal of Advances in Modeling Earth Systems, Vol. 10, Issue 10
  • DOI: 10.1029/2018MS001350

Sensitivity of CAM5-Simulated Arctic Clouds and Radiation to Ice Nucleation Parameterization
journal, August 2013


Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels
journal, June 2012

  • Zelinka, Mark D.; Klein, Stephen A.; Hartmann, Dennis L.
  • Journal of Climate, Vol. 25, Issue 11
  • DOI: 10.1175/JCLI-D-11-00248.1

Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part II: Attribution to Changes in Cloud Amount, Altitude, and Optical Depth
journal, June 2012

  • Zelinka, Mark D.; Klein, Stephen A.; Hartmann, Dennis L.
  • Journal of Climate, Vol. 25, Issue 11
  • DOI: 10.1175/JCLI-D-11-00249.1

Contributions of Different Cloud Types to Feedbacks and Rapid Adjustments in CMIP5
journal, July 2013


Insights from a refined decomposition of cloud feedbacks: REFINED CLOUD FEEDBACK DECOMPOSITION
journal, September 2016

  • Zelinka, Mark D.; Zhou, Chen; Klein, Stephen A.
  • Geophysical Research Letters, Vol. 43, Issue 17
  • DOI: 10.1002/2016GL069917

Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements
journal, January 2005


Evaluation of tropical cloud and precipitation statistics of Community Atmosphere Model version 3 using CloudSat and CALIPSO data
journal, January 2010

  • Zhang, Y.; Klein, S. A.; Boyle, J.
  • Journal of Geophysical Research, Vol. 115, Issue D12
  • DOI: 10.1029/2009JD012006

Regional assessment of the parameter-dependent performance of CAM4 in simulating tropical clouds: REGIONAL TROPICAL CLOUDS IN CAM4
journal, July 2012

  • Zhang, Yuying; Xie, Shaocheng; Covey, Curt
  • Geophysical Research Letters, Vol. 39, Issue 14
  • DOI: 10.1029/2012GL052184

An Analysis of the Short-Term Cloud Feedback Using MODIS Data
journal, July 2013