Determining stationary periods across multiple sensors: An application to observed canopy turbulence response to atmospheric stability

Ying Pan, Edward G. Patton

Research output: Contribution to journalArticlepeer-review

Abstract

A recently proposed multisensor stationarity analysis technique (MSATv1) is improved to eliminate the initial interrogation of time-averaged wind directions, a redundant and potentially biasing procedure for a technique capable of detecting changes in mean wind directions. The new technique, MSATv2, satisfies two basic expectations that are not guaranteed in MSATv1: 1) a nonstationary event should not belong to any stationary interval identified with a given stringency, and 2) nonstationary events identified with an arbitrary stringency should continue to be identified as nonstationary with increasing stringency. These expectations are confirmed by applying MSATv2 to two long periods, during the defoliated phase of the Canopy Horizontal Array Turbulence Study (CHATS), whose durations are determined solely by data availability. MSATv2 successfully determines visually trivial and nontrivial nonstationary transitions, uncovering details of the time evolution of dynamic processes. MSATv2 yields ensemble-average estimates of mean wind speeds and directions with well-controlled and quantifiable uncertainties for atmospheric stability conditions ranging from near neutral to free convection. These results enable interrogation of the observed canopy turbulence response to atmospheric stability in isolation from contamination by spatial variation with position relative to canopy elements. MSATv2 results also reveal the connection between the presence of organized convective structures and variability in mean shear, showing the role of organized convective structures in the observed relationship between the bulk drag coefficient and atmospheric instability.

Original languageEnglish (US)
Pages (from-to)665-685
Number of pages21
JournalJournal of Atmospheric and Oceanic Technology
Volume37
Issue number4
DOIs
StatePublished - Apr 2020

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Atmospheric Science

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