Multi-scale decomposition of turbulent fluxes above a forest canopy

Zhang, Gengsheng; Leclerc, Monique Y.; Duarte, Henrique F.; Durden, David; Werth, David; Kurzeja, Robert J.; Parker, Matthew

doi:10.1016/j.agrformet.2013.11.010

Cited by 1 publication

(2 citation statements)

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“…Identification and measurement of such structures and their contributions from field observations call for spatially resolving measurement techniques, such as a distributed tower network (Engelmann & Bernhofer, 2016; Mauder, Desjardins, Pattey, Gao, & van Haarlem, 2008; Morrison et al., 2021; Oncley et al., 2007), airborne measurements (Bange et al., 2002, 2006; Mahrt, 1998; Mauder, Oncley, et al., 2007; Strunin & Hiyama, 2004), scintillometers (Foken et al., 2010; Meijninger et al., 2006; F. Xu et al., 2017) and LiDAR measurements (Drobinski et al., 1998; Eder et al., 2015; Higgins et al., 2013) etc. Spectral analysis of tower measured turbulence data can also give some insight into the nature of flux contributions from the lower frequencies (Gao et al., 2020; G. Zhang et al., 2014; Y. Zhang et al., 2010; Zhou et al., 2019).…”

Section: Introductionmentioning

confidence: 99%

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Space‐Scale Resolved Surface Fluxes Across a Heterogeneous, Mid‐Latitude Forested Landscape

et al. 2022

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The Earth's surface is heterogeneous at multiple scales owing to spatial variability in various properties. The atmospheric responses to these heterogeneities through fluxes of energy, water, carbon, and other scalars are scale‐dependent and nonlinear. Although these exchanges can be measured using the eddy covariance technique, widely used tower‐based measurement approaches suffer from spectral losses in lower frequencies when using typical averaging times. However, spatially resolved measurements such as airborne eddy covariance measurements can detect such larger scale (meso‐β, meso‐γ) transport. To evaluate the prevalence and magnitude of these flux contributions, we applied wavelet analysis to airborne flux measurements over a heterogeneous mid‐latitude forested landscape, interspersed with open water bodies and wetlands. The measurements were made during the Chequamegon Heterogeneous Ecosystem Energy‐balance Study Enabled by a High‐density Extensive Array of Detectors intensive field campaign. We ask, how do spatial scales of surface‐atmosphere fluxes vary over heterogeneous surfaces across the day and across seasons? Measured fluxes were separated into smaller‐scale turbulent and larger‐scale mesoscale contributions. We found significant mesoscale contributions to sensible and latent heat fluxes through summer to autumn which would not be resolved in single‐point tower measurements through traditional time‐domain half‐hourly Reynolds decomposition. We report scale‐resolved flux transitions associated with seasonal and diurnal changes of the heterogeneous study domain. This study adds to our understanding of surface‐atmospheric interactions over unstructured heterogeneities and can help inform multi‐scale model‐data integration of weather and climate models at a sub‐grid scale.

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Section: Introductionmentioning

confidence: 99%

“…Xu et al, 2017) and LiDAR measurements (Drobinski et al, 1998;Eder et al, 2015;Higgins et al, 2013) etc. Spectral analysis of tower measured turbulence data can also give some insight into the nature of flux contributions from the lower frequencies (Gao et al, 2020;G. Zhang et al, 2014;Y.…”

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confidence: 99%