Open access Data Sets of Vertical Profiles for Turbulent Ekman Flow generated by DNS tlab code

In the pursuit of advancing our comprehension of the atmospheric boundary layer and the associated exchange processes near the surface, the accessibility of high-quality data assumes a pivotal role. An open-access approach is acknowledged for catalyzing collaborative efforts, empowering researchers globally to harness available information for their investigations. This has the potential to refine existing models, validate hypotheses, and instigate innovations in climate modeling and predictive simulations. Here, we introduce an open benchmark data repository, accessible through static collection of DOIs, to share the statistics of simulations for turbulent Ekman flow. This data, forming the foundation for numerous publications on Ekman flow, has been established as a suitable virtual lab environment in prior works for studying crucial aspects of the atmospheric boundary layer. We believe that the availability of this data under the FAIR paradigm has the potential to facilitate further exploitation, enhancing our understanding of process-level intricacies in the atmospheric boundary layer.
The data is being generated since 2011 using the tLab tool-suite (github.com/turbulencia/tlab) for direct numerical simulation (DNS) on some of Europe’s largest supercomputers, including juqueen and juwels at Jülich Supercomputing Centre, and hawk at Höchstleistungsrechenzentrum Stuttgart. It is now accessible in the long-term data repository refubium.fu-berlin.de of Freie Universität Berlin.
The inaugural contribution to this repository is a comprehensive, curated set of data exploring the influence of turbulence scale separation, specifically the Reynolds number. A series of simulations spans a range of Reynolds numbers, corresponding to a variation of approximately tenfold in the friction Reynolds number Re_τ. The shared dataset encompasses various parameters, including vertical profiles of velocity, budget terms of scalar and momentum budgets, statistical moments up to the third order of velocities, scalars, and derivatives, providing a holistic view of Ekman flow dynamics across a range of Reynolds numbers. This enables the identification of inviscid scaling behavior and the development of scaling theories for the application of these simulations to real-world problems.
While the dataset also captures effects of stable stratification and rough surfaces, these aspects are, beyond the scope of this abstract.

Keywords— Numerical simulation, Ekman flow, Turbulence, Surface layer, Simulation Theory

∗ This work is funded by the ERC Starting Grant "Turbulence-Resolving Approaches of the Intermittently Turbulent Atmos-
pheric Boundary Layer [trainABL]" of the European Research Council (funding ID 851347). The data was generated under that
computing grants hhh07, hku24, stadit at Jülich supercomputing centre and trainABL / Bundesprojekt 44187 at Höchstleistungs-
rechenzentrum Stuttgart)