Articles | Volume 12, issue 12
https://doi.org/10.5194/amt-12-6401-2019
https://doi.org/10.5194/amt-12-6401-2019
Research article
 | 
05 Dec 2019
Research article |  | 05 Dec 2019

Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign

Norman Wildmann, Nicola Bodini, Julie K. Lundquist, Ludovic Bariteau, and Johannes Wagner

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Cited articles

Adler, B. and Kalthoff, N.: Multi-scale Transport Processes Observed in the Boundary Layer over a Mountainous Island, Bound.-Lay. Meteorol., 153, 515–537, 2014. a
Balsley, B. B., Frehlich, R. G., Jensen, M. L., Meillier, Y., and Muschinski, A.: Extreme Gradients in the Nocturnal Boundary Layer: Structure, Evolution, and Potential Causes, J. Atmos. Sci., 60, 2496–2508, 2003. a
Barlow, R. J.: Statistics: a guide to the use of statistical methods in the physical sciences, vol. 29, John Wiley & Sons, 1989. a
Belcher, S. E., Harman, I. N., and Finnigan, J. J.: The Wind in the Willows: Flows in Forest Canopies in Complex Terrain, Annu. Rev. Fluid Mech., 44, 479–504, https://doi.org/10.1146/annurev-fluid-120710-101036, 2012. a
Bell, T., Klein, P., Wildmann, N., and Menke, R.: Analysis of Flow in Complex Terrain Using Multi-Doppler Lidar Retrievals, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-417, in review, 2019. a
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Short summary
Turbulence is the variation of wind velocity on short timescales. In this study we introduce a new method to measure turbulence in a two-dimensionial plane with lidar instruments. The method allows for the detection and quantification of subareas of distinct turbulence conditions in the observed plane. We compare the results to point and profile measurements with more established instruments. It is shown that turbulence below low-level jets and in wind turbine wakes can be investigated this way.
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