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Title: Regional assessment of the parameter-dependent performance of CAM4 in simulating tropical clouds

Journal Article · · Geophysical Research Letters
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  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
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Representation of clouds remains among the largest uncertainties in climate models and thus climate projections. Clouds vary significantly over different climate regimes and are controlled by different dynamics and physics. Using the cloud simulator output from perturbed-parameter ensemble climate runs with prescribed monthly sea surface temperature, this study examines the performance of the Community Atmosphere Model version 4 (CAM4) in simulating clouds over different tropical regions. Perturbing 28 selected parameters shows that model performance is quite sensitive to parameter values in different cloud regimes. Carefully adjusting these parameters could lead to a better simulation of clouds over many regions compared with the default model. Latin hypercube runs that pseudo-randomly sample the 28 parameters simultaneously have much wider spread and more spatial variations than the runs with parameters varied One-At-a-Time (OAT), suggesting the importance of non-linearities and interactions among parameters associated with different physical processes. The perturbed parameters have a relatively large impact on the mean bias compared to the pattern error

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
1369383
Report Number(s):
LLNL-JRNL-548674
Journal Information:
Geophysical Research Letters, Vol. 39, Issue 14; ISSN 0094-8276
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (6)

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Parameter Modulation of Madden-Julian Oscillation Behaviors in BCC_CSM1.2: The Key Role of Moisture-Shallow Convection Feedback journal May 2019
Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modeling journal January 2019
Significant improvement of cloud representation in the global climate model MRI-ESM2 journal January 2019
The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 2: Cloud evaluation, aerosol radiative forcing, and climate sensitivity journal January 2019
The global aerosol-climate model ECHAM6.3-HAM2.3-Part 2: Cloud evaluation, aerosol radiative forcing, and climate sensitivity text January 2019

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Related Subjects

54 ENVIRONMENTAL SCIENCES
CAM4
regional assessment
tropical clouds