We develop a novel data-driven approach to modeling the atmospheric boundarylayer . This approach leads to a nonlocal, anisotropic synthetic turbulencemodel which we refer to as the deep rapid distortion (DRD) model . After calibration, the model can be used to generate syntheticturbulent velocity fields . We demonstrate the robustness of our approach with both filtered and noisy data coming from the 1968 AirForce Cambridge Research Laboratory Kansas experiments. Using this data, we witness exceptional accuracy with the DRD model, especially when compared to the International Electrotechnical Commission standard. To this end, we provide a new numerical method basedon domain decomposition which delivers scalable, memory-efficient turbulencegeneration with theDRD model as well as others. We provide a method based on domain decompositions which delivers a new method of analysis of turbulence. We also demonstrate the strength of our new numerical model. We demonstrate

Author(s) : Brendan Keith, Ustim Khristenko, Barbara Wohlmuth

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Keywords : model - data - demonstrate - approach - method -

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