  This study proposes a novel framework based on magnitude cumulant and
surrogate analyses to reliably detect and estimate the intermittency
coefficient from short-length coarse-resolution turbulent time series.
Intermittency coefficients estimated from a large number of neutrally
stratified atmospheric surface layer turbulent series from various field
campaigns are shown to remarkably concur with well-known laboratory
experimental results. In addition, surrogate-based hypothesis testing
significantly reduces the likelihood of detecting a spurious non-zero
intermittency coefficient from non-intermittent series. The discriminatory
power of the proposed framework is promising for addressing the unresolved
question of how atmospheric stability affects the intermittency properties of
boundary layer turbulence.
