Articles | Volume 19, issue 7
Atmos. Chem. Phys., 19, 4367–4382, 2019
Atmos. Chem. Phys., 19, 4367–4382, 2019
Research article
04 Apr 2019
Research article | 04 Apr 2019

Spatial and temporal variability of turbulence dissipation rate in complex terrain

Nicola Bodini et al.

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Cited articles

Aitken, M. L., Rhodes, M. E., and Lundquist, J. K.: Performance of a wind-profiling lidar in the region of wind turbine rotor disks, J. Atmos. Ocean. Tech., 29, 347–355,, 2012. a
Albertson, J. D., Parlange, M. B., Kiely, G., and Eichinger, W. E.: The average dissipation rate of turbulent kinetic energy in the neutral and unstable atmospheric surface layer, J. Geophys. Res.-Atmos., 102, 13423–13432, 1997. a
Alemany, S., Beltran, J., Perez, A., and Ganzfried, S.: Predicting Hurricane Trajectories using a Recurrent Neural Network, arXiv preprint, arXiv 1802.02548, 2018. a
Babić, K., Bencetić Klaić, Z., and Večenaj, Ž.: Determining a turbulence averaging time scale by Fourier analysis for the nocturnal boundary layer, Geofizika, 29, 35–51, 2012. a
Baik, J.-J. and Kim, J.-J.: A numerical study of flow and pollutant dispersion characteristics in urban street canyons, J. Appl. Meteorol., 38, 1576–1589, 1999. a
Short summary
To improve the parameterization of the turbulence dissipation rate (ε) in numerical weather prediction models, we have assessed its temporal and spatial variability at various scales in the Columbia River Gorge during the WFIP2 field experiment. The turbulence dissipation rate shows large spatial variability, even at the microscale, with larger values in sites located downwind of complex orographic structures or in wind farm wakes. Distinct diurnal and seasonal cycles in ε have also been found.
Final-revised paper