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Olli Peltola

Publications and source records attributed to Olli Peltola.

2 recordsLinked to original sources

On the limits of Taylor hypothesis in forest clearcut flow: Effects of random sweeping and an elliptic model analysis

Taylor's hypothesis (TH) converts temporal observations to spatial information of the flow while carrying out measurements on a micrometeorological tower. Other than TH, there exists a more general elliptic model, which converts time to space by focusing on the geometry of the space-time correlation function. In elliptic model, TH is recovered when the space-time correlation functions are straight lines and when TH is invalid, they are approximated as elliptic curves. To test whether TH or an elliptic model was appropriate for a highly heterogeneous forest clearcut flow, we examined the geometry of the space-time correlation function of temperature by using an extensive distributed temperature sensing (DTS) dataset collected during daytime convective conditions at a height of 3.1 m above the clearing. This was complemented with an eddy covariance (EC) dataset that measured the turbulence characteristics. When the mean wind was parallel to a nearby forest edge, the DTS-derived space-time correlation function of temperature fluctuations resembled elliptic curves, rather than straight lines as predicted by TH. Due to large turbulence intensities, the curvatures in the space-time correlation contours were caused by the random sweeping events associated with large-scale eddies that invalidated the frozen turbulence assumption in TH. The velocity scale of these sweeping events correlated with the turbulence kinetic energy of the clearcut flow, thereby lending support to the random sweeping hypothesis. Upon converting time to space through an elliptic and TH-based scaling, our results demonstrated that both temporal DTS and EC temperature measurements were impacted by the random sweeping events.

physics.ao-ph

$\mathcal{L}$-moments reveal the scales of momentum transport in dense canopy flows

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 $\mathcal{L}$-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 $\mathcal{L}$ moments. $\mathcal{L}$ 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 even for canopy flows. The $\mathcal{L}$-moment framework is complemented with wavelet analysis, leading to a discovery of a mixed time scale controlling the momentum exchanges between the atmosphere and the canopy air space. The origin of this mixed-scale is intimately linked to an interaction between two different eddy processes that transport momentum in the gradient and counter-gradient directions, respectively. This finding gives rise to a conceptual model of canopy turbulence that resolves a long-standing issue in canopy flows: why the integral timescale of vertical velocity increases as the heights approach the forest floor? Moreover, this model explains the intermittent nature of the wind inside a canopy despite its average being nearly zero due to canopy drag.

physics.flu-dyn