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<h2>Improving Turbulence and Cloud Representation Without Breaking the Bank</h2>
<i>Peter Bogenschutz & Steven Krueger</i><p></p>

CMMAP's Multiscale Modeling Framework (MMF) represents a coupling between NCAR's
Community Atmosphere Model (CAM) and a cloud resolving model (CRM). However, in
the current standard configuration of the MMF, shallow convection remains
largely unresolved. This is due to the fact that the embedded CRM (System for
Atmospheric Modeling, SAM) is typically run with a horizontal grid spacing of 4
km, which is adequate to resolve deep convection but certainly not cumulus
clouds or boundary layer turbulence. Shallow convective cloud systems, such as
stratocumulus and trade wind cumulus, significantly affect the global radiation
budget and play an important role in the energy and hydrological cycles of the
atmosphere (Slingo 1990), therefore there is a need for better representation of
these types of clouds in the MMF.<p></p>

One of the major challenges associated with this problem is computational cost,
as the MMF is about 100 times more expensive to run than the standard CAM. This
presents a challenge in implementing higher order turbulence schemes (meaning
the turbulent moments are predicted) as the increase in computational cost of
the MMF may then become too large and prohibit long term climate simulations.
Recently a method known as the "assumed PDF" technique shows great promise in
providing a unified parameterization of sub-grid scale (SGS) shallow convection
(Larson et al. 2002, Golaz et al. 2002, Cheng and Xu 2006). The assumed PDF
approach allows for SGS variability in the condensation scheme, as opposed to
the so called "all-or-nothing" condensation approach currently implemented into
SAM.<p></p>

Our approach to improving SAM follows that of the assumed PDF method. However,
our scheme is non-traditional in the fact that we do not add any predictive
equations into the SAM code and thus the turbulent input moments needed for the
assumed PDF are diagnosed. We find that as long as the sub-grid scale turbulent
kinetic energy (TKE) is predicted accurately then the diagnostic turbulent
moments can be well represented and thus the assumed PDF returns results of
comparable quality to those produced by similar higher order closure models.
The TKE equation is improved by a better representation of the SGS dissipation
rate and the buoyancy flux. The result is a better representation of SGS
turbulence and shallow cloud properties (i.e. nonprecipitating cloud condensate
mixing ratio and cloud fraction) that comes at a computational cost only a
factor of ~1.1 more compared to the standard SAM model. Currently this closure
is undergoing preliminary tests within the MMF.<p></p>

<center><img src="/images/research/bogenHighlight1.jpg" border=0><br /></center>
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<b>References</b><ul>
<li> Cheng, A., K.-M. Xu, 2006: Simulation of shallow cumuli and their transition to deep con- vective clouds by cloud-resolving models with different third-order turbulence closures. <i>Quart. J. Roy. Meteor. Soc.</i>, <b>132</b>, 359-382.</li>
<li> Golaz, J. C., V. E. Larson, and W. R. Cotton, 2002: A pdf-based model for boundary layer clouds part I: Method and model description. <i>J. Atmos. Sci.</i>, <b>59</b>, 3540-3551</li>
<li> Larson, V. E., J. C. Golaz, and W. R. Cotton, 2002: Small-scale and mesoscale variability in cloud boundary layers: Joint probability density functions. <i>J. Atmos. Sci.</i>, <b>59</b>, 3519-3539</li>
<li> Slingo, A., 1990: Sensitivity of the Earth's radiation budget to changes in low clouds. <i>Nature</i>, <b>343</b>, 49-51</li></ul>


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