English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

. We present and validate a set of equations forrepresenting the atmosphere's large-scale general circulation in an Earthsystem model of intermediate complexity (EMIC). These dynamical equationshave been implemented in Aeolus 1.0, which is a statistical–dynamicalatmosphere model (SDAM) and includes radiative transfer and cloud modules(Coumouet al., 2011; Eliseev et al., 2013). The statistical dynamical approach iscomputationally efficient and thus enables us to perform climatesimulations at multimillennia timescales, which is a prime aim of our modeldevelopment. Further, this computational efficiency enables us to scan largeand high-dimensional parameter space to tune the model parameters, e.g., forsensitivity studies. Here, we present novel equations for the large-scale zonal-mean wind as wellas those for planetary waves. Together with synoptic parameterization (aspresented by Coumou et al., 2011), these form the mathematical descriptionof the dynamical core of Aeolus 1.0. We optimize the dynamical core parameter values by tuning all relevantdynamical fields to ERA-Interim reanalysis data (1983–2009) forcing thedynamical core with prescribed surface temperature, surface humidity andcumulus cloud fraction. We test the model's performance in reproducing theseasonal cycle and the influence of the El Nino–Southern Oscillation (ENSO). We use a simulated annealingoptimization algorithm, which approximates the global minimum of ahigh-dimensional function. With non-tuned parameter values, the model performs reasonably in terms ofits representation of zonal-mean circulation, planetary waves and stormtracks. The simulated annealing optimization improves in particular themodel's representation of the Northern Hemisphere jet stream and stormtracks as well as the Hadley circulation. The regions of high azonal wind velocities (planetary waves) are accuratelycaptured for all validation experiments. The zonal-mean zonal wind and theintegrated lower troposphere mass flux show good results in particular inthe Northern Hemisphere. In the Southern Hemisphere, the model tends toproduce too-weak zonal-mean zonal winds and a too-narrow Hadley circulation.We discuss possible reasons for these model biases as well as planned futuremodel improvements and applications.

The dynamical core of the Aeolus 1.0 statistical–dynamical atmosphere model: validation and parameter optimization