[Stoch] Two papers on Model Uncertainty and Stochastic Parameterizations in Weather and Climate

[Judith Berner]

Dear all,

two recent papers relating to stochastic parameterizations and model 
error
in NWP and climate models that you might be interested in.

Just the literature for the summer :-)
Judith

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Model Uncertainty in a Mesoscale Ensemble Prediction System: 
Stochastic versus Multiphysics RepresentationsJ. Berner, S.-Y. Ha, J. 
P. Hacker, A. Fournier, C. Snyder
Monthly Weather Review
Volume 139, Issue 6 (June 2011) pp. 1972-1995
doi: http://dx.doi.org/10.1175/2010MWR3595.1

Abstract:
A multiphysics and a stochastic kinetic-energy backscatter scheme are 
employed to represent model uncertainty in a mesoscale ensemble 
prediction system using the Weather Research and Forecasting model. 
Both model-error schemes lead to significant improvements over the 
control ensemble system that is simply a downscaled global ensemble 
forecast with the same physics for each ensemble member. The 
improvements are evident in verification against both observations and 
analyses, but different in some details. Overall the stochastic 
kinetic-energy backscatter scheme outperforms the multiphysics scheme, 
except near the surface. Best results are obtained when both schemes 
are used simultaneously, indicating that the model error can best be 
captured by a combination of multiple schemes.
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Systematic Model Error: The Impact of Increased Horizontal Resolution 
versus Improved Stochastic and Deterministic Parameterizations
J. Berner, T. Jung, T. N. Palmer
Journal of Climate
Volume 0, Issue 0 ( ) pp.
doi: http://dx.doi.org/10.1175/JCLI-D-11-00297.1

Abstract:
Long-standing systematic model errors in both tropics and 
extra-tropics of the ECMWF model run at a horizontal resolution 
typical for climate models are investigated. Based on the hypothesis 
that the misrepresentation of unresolved scales contributes to the 
systematic model error, three model refinements that attempt their 
representation — fluctuating or deterministically — are investigated.

Increasing horizontal resolution to explicitly simulate smaller-scale 
features, representing subgrid-scale fluctuations by a stochastic 
parameterization and improving the deterministic 
physics-parameterizations all lead to a decrease in the systematic 
bias of the Northern Hemispheric circulation. These refinements reduce 
the overly zonal flow and improve the model’s ability to capture the 
frequency of blocking. However, the model refinements differ greatly 
in their impact in the tropics: While improving the deterministic and 
introducing stochastic parameterizations reduces the systematic 
precipitation bias and improves the characteristics of 
convectively-coupled waves and tropical variability in general, 
increasing horizontal resolution has little impact.

The fact that different model refinements can lead to reductions in 
systematic model error is consistent with our hypothesis that 
unresolved scales play an important role. At the same time this 
degeneracy of the response to different forcings can lead to 
compensating model errors. Hence, if one takes the view that 
stochastic parametrization should be an important element of next 
generation climate models, if only to provide reliable estimates of 
model uncertainty, then a fundamental conclusion of this study is that 
stochasticity should be incorporated within the design of 
physical-process parameterizations and improvements of the dynamical 
core and not added a posteriori.
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Dr. Judith Berner
NCAR MMM/CGD
P.O.Box 300
Boulder, CO 80303
berner at ucar.edu