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Geosci. Model Dev., 11, 665-679, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Development and technical paper
22 Feb 2018
The dynamical core of the Aeolus 1.0 statistical–dynamical atmosphere model: validation and parameter optimization
Sonja Totz1,2, Alexey V. Eliseev1,3,4,5,6, Stefan Petri1, Michael Flechsig1, Levke Caesar1,2, Vladimir Petoukhov1, and Dim Coumou1,7 1Potsdam Institute for Climate Impact Research (PIK), Leibniz Foundation, Potsdam, Germany
2Department of Physics, Potsdam University, Potsdam, Germany
3A.M. Obukhov Institute of Atmospheric Physics RAS, Moscow, Russia
4Kazan Federal University, Kazan, Russia
5Institute of Applied Physics, Russian Academy of Sciences, Nizhny Novgorod, Russia
6Lomonosov Moscow State University, Faculty of Physics, Moscow, Russia
7Institute for Environmental Studies (IVM), Department of Water & Climate Risk, VU University Amsterdam, Amsterdam, the Netherlands
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.

Citation: Totz, S., Eliseev, A. V., Petri, S., Flechsig, M., Caesar, L., Petoukhov, V., and Coumou, D.: The dynamical core of the Aeolus 1.0 statistical–dynamical atmosphere model: validation and parameter optimization, Geosci. Model Dev., 11, 665-679,, 2018.
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