The dynamical core of the Aeolus 1.0 statistical–dynamical atmosphere model: validation and parameter optimization
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Published:2018-02-22
Issue:2
Volume:11
Page:665-679
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Totz SonjaORCID, Eliseev Alexey V.ORCID, Petri StefanORCID, Flechsig Michael, Caesar LevkeORCID, Petoukhov Vladimir, Coumou Dim
Abstract
Abstract. We present and validate a set of equations for
representing the atmosphere's large-scale general circulation in an Earth
system model of intermediate complexity (EMIC). These dynamical equations
have been implemented in Aeolus 1.0, which is a statistical–dynamical
atmosphere model (SDAM) and includes radiative transfer and cloud modules
(Coumou
et al., 2011; Eliseev et al., 2013). The statistical dynamical approach is
computationally efficient and thus enables us to perform climate
simulations at multimillennia timescales, which is a prime aim of our model
development. Further, this computational efficiency enables us to scan large
and high-dimensional parameter space to tune the model parameters, e.g., for
sensitivity studies. Here, we present novel equations for the large-scale zonal-mean wind as well
as those for planetary waves. Together with synoptic parameterization (as
presented by Coumou et al., 2011), these form the mathematical description
of the dynamical core of Aeolus 1.0. We optimize the dynamical core parameter values by tuning all relevant
dynamical fields to ERA-Interim reanalysis data (1983–2009) forcing the
dynamical core with prescribed surface temperature, surface humidity and
cumulus cloud fraction. We test the model's performance in reproducing the
seasonal cycle and the influence of the El Niño–Southern Oscillation (ENSO). We use a simulated annealing
optimization algorithm, which approximates the global minimum of a
high-dimensional function. With non-tuned parameter values, the model performs reasonably in terms of
its representation of zonal-mean circulation, planetary waves and storm
tracks. The simulated annealing optimization improves in particular the
model's representation of the Northern Hemisphere jet stream and storm
tracks as well as the Hadley circulation. The regions of high azonal wind velocities (planetary waves) are accurately
captured for all validation experiments. The zonal-mean zonal wind and the
integrated lower troposphere mass flux show good results in particular in
the Northern Hemisphere. In the Southern Hemisphere, the model tends to
produce too-weak zonal-mean zonal winds and a too-narrow Hadley circulation.
We discuss possible reasons for these model biases as well as planned future
model improvements and applications.
Publisher
Copernicus GmbH
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