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

Model code and software

total-var N. Hamilton https://doi.org/10.5281/zenodo.3630875

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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.