Articles | Volume 13, issue 2
https://doi.org/10.5194/amt-13-1019-2020
https://doi.org/10.5194/amt-13-1019-2020
Research article
 | 
03 Mar 2020
Research article |  | 03 Mar 2020

Atmospheric condition identification in multivariate data through a metric for total variation

Nicholas Hamilton

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Cited articles

Ali, N., Hamilton, N., Calaf, M., and Cal, R. B.: Turbulence kinetic energy budget and conditional sampling of momentum, scalar, and intermittency fluxes in thermally stratified wind farms, J. Turbul., 1, 32–63, https://doi.org/10.1080/14685248.2018.1564831, 2019. a
Anderson, T. W.: An introduction to multivariate statistical analysis, Tech. rep., Wiley New York, 1962. a
Barthelmie, R., Crippa, P., Wang, H., Smith, C., Krishnamurthy, R., Choukulkar, A., Calhoun, R., Valyou, D., Marzocca, P., Matthiesen, D., et al.: 3D wind and turbulence characteristics of the atmospheric boundary layer, B. Am. Meteorol. Soc., 95, 743–756, 2014. a
Barthelmie, R., Churchfield, M. J., Moriarty, P. J., Lundquist, J. K., Oxley, G., Hahn, S., and Pryor, S.: The role of atmospheric stability/turbulence on wakes at the Egmond aan Zee offshore wind farm, in: Journal of Physics: Conference Series, 625, p. 012002, IOP Publishing, 2015. a
Belušić, D. and Mahrt, L.: Is geometry more universal than physics in atmospheric boundary layer flow?, J. Geophys. Res.-Atmos., 117, https://doi.org/10.1029/2011JD016987, 2012. a
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Short summary
The identification of atmospheric conditions within a multivariable atmospheric data set is an important step in validating emerging and existing models used to simulate wind plant flows and operational strategies. The total variation approach developed here offers a method founded in tested mathematical metrics and can be used to identify and characterize periods corresponding to quiescent conditions or specific events of interest for study or wind energy development.