[Stoch] Two papers on Model Uncertainty and Stochastic Parameterizations in Weather and Climate
berner at ucar.edu
Thu May 31 17:13:20 MDT 2012
two recent papers relating to stochastic parameterizations and model
in NWP and climate models that you might be interested in.
Just the literature for the summer :-)
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
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.
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.
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.
Dr. Judith Berner
Boulder, CO 80303
berner at ucar.edu
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