The dynamical core of the Aeolus 1.0 statistical-dynamical atmosphere model: Validation and parameter optimization

Sonja Totz*, Alexey V. Eliseev, Stefan Petri, Michael Flechsig, Levke Caesar, Vladimir Petoukhov, Dim Coumou

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


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.

Original languageEnglish
Pages (from-to)665-679
Number of pages15
JournalGeoscientific Model Development
Issue number2
Publication statusPublished - 22 Feb 2018


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 The work was supported by the German Federal Ministry of Education and Research, grant no. 01LN1304A, (S.T., D.C.). Alexey V. Eliseev’s contribution was partly supported by supported by the Government of the Russian Federation (agreement no. 14.Z50.31.0033). The authors gratefully acknowledge the European Regional Development Fund (ERDF), the German Federal Ministry of Education and Research and the Land Brandenburg for supporting this project by providing resources on the high-performance computer system at the Potsdam Institute for Climate Impact Research.

FundersFunder number
Land Brandenburg
Potsdam Institute for Climate Impact Research
Bundesministerium für Bildung und Forschung01LN1304A
European Regional Development Fund
Government Council on Grants, Russian Federation


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