$${\mathscr {L}}$$-moments Reveal the Scales of Momentum Transport in Dense Canopy Flows

Abstract The interaction between a dense forest canopy and atmosphere is a complex fluid-dynamical problem with a wide range of practical applications, spanning from the aspects of carbon sequestration to the spread of wildfires through a forest. To delineate the eddy processes specific to canopy flows, we develop an $${\mathscr {L}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>L</mml:mi> </mml:math> -moment based event framework and apply it on a suite of observational datasets encompassing both canopy and atmospheric surface layer flows. In this framework, the turbulent fluctuations are considered as a chronicle of positive and negative events having finite lengths or time scales, whose statistical distributions are quantified through the $${\mathscr {L}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>L</mml:mi> </mml:math> moments. $${\mathscr {L}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>L</mml:mi> </mml:math> moments are statistically more robust than the conventional moments and have earlier been used in hydrology applications, but here we show how this concept is useful to identify the contrasting features between canopy and atmospheric surface layer flows. The $${\mathscr {L}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>L</mml:mi> </mml:math> -moment framework is complemented with wavelet analysis, revealing how differently the canopy-scale coherent structures modulate the horizontal and vertical velocity components in sub-canopy environments. We hypothesize that a consequence of this phenomenon is the existence of two different eddy processes with distinct scaling properties that transport momentum in the gradient and counter-gradient directions, respectively. These findings shed light on a long-standing issue in canopy flows: why the integral timescale of vertical velocity increases as the heights approach the forest floor?