Momentum, heat and water vapour transfer to and from natural and artificial surfaces

Garratt, J. R.; Hicks, B. B.

doi:10.1002/qj.49709942209

Cited by 423 publications

(155 citation statements)

References 15 publications

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“…The turbulent mixing coefficient K is inferred or parameterized, unlike the molecular diffusion coefficient in Fick's first law that can be derived from first principles using molecular kinetic theory. Fluxgradient methods assume that, at a given time and place, the eddy diffusivity is invariant for mass, heat, and momentum (e.g., Reynold's analogy) (Garratt and Hicks, 1973;Sinclair and Lemon, 1975;.…”

Section: Flux-gradient Methodsmentioning

confidence: 99%

“…Integrating volumes (known also as buffer volumes) have been used in previous studies to dampen temporal fluctuations in trace gas mole fractions for flux-gradient measurements (Griffith et al, 2002), for contributions of advection (Yi et al, 2008), and for flask sampling (Bowling et al, 2003). A block-averaging effect is accomplished in flux-gradient measurements that trap the compound of interest over periods of minutes or hours (Müller et al, 1993;Goldstein et al, 1995Goldstein et al, , 1996Goldstein et al, , 1998Meyers et al, 1996) and eddy accumulation methods that use high-precision differential collection apparatus to trap and then sample air from upand down-drafts to determine the flux (Businger and Onlcey, 1990;Guenther et al, 1996;Bowling et al, 1998).…”

Section: Sampling Errormentioning

confidence: 99%

“…The volume was pre-flushed at 3 L min −1 (τ V = 8.3 min) and then sampled by all sample streams at 2 L min −1 total flow (τ V = 12.5 min). Similar systems have been engineered to sample air from the same inlet height by temporarily placing inlets at the same height or frequently interchanging the inlet positions (Goldstein et al, 1995;Meyers et al, 1996;Wesely et al, 1989), but that ambient air is still subject to atmospheric variability. Our goal was to have an automated nulling procedure where all inlets would sample from the same reservoir of air that had nearly the same thermal, barometric, and chemical characteristics as the ambient air, but with the high-frequency atmospheric variability filtered out.…”

Section: Measurement Accuracymentioning

confidence: 99%

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Ecosystem fluxes of hydrogen: a comparison of flux-gradient methods

et al. 2014

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Abstract. Our understanding of biosphere-atmosphere exchange has been considerably enhanced by eddy covariance measurements. However, there remain many trace gases, such as molecular hydrogen (H 2 ), that lack suitable analytical methods to measure their fluxes by eddy covariance. In such cases, flux-gradient methods can be used to calculate ecosystem-scale fluxes from vertical concentration gradients. The budget of atmospheric H 2 is poorly constrained by the limited available observations, and thus the ability to quantify and characterize the sources and sinks of H 2 by fluxgradient methods in various ecosystems is important. We developed an approach to make nonintrusive, automated measurements of ecosystem-scale H 2 fluxes both above and below the forest canopy at the Harvard Forest in Petersham, Massachusetts, for over a year. We used three flux-gradient methods to calculate the fluxes: two similarity methods that do not rely on a micrometeorological determination of the eddy diffusivity, K, based on (1) trace gases or (2) sensible heat, and one flux-gradient method that (3) parameterizes K. We quantitatively assessed the flux-gradient methods using CO 2 and H 2 O by comparison to their simultaneous independent flux measurements via eddy covariance and soil chambers. All three flux-gradient methods performed well in certain locations, seasons, and times of day, and the best methods were trace gas similarity for above the canopy and K parameterization below it. Sensible heat similarity required several independent measurements, and the results were more variable, in part because those data were only available in the winter, when heat fluxes and temperature gradients were small and difficult to measure. Biases were often observed between flux-gradient methods and the independent flux measurements, and there was at least a 26 % difference in nocturnal eddy-derived net ecosystem exchange (NEE) and chamber measurements. H 2 fluxes calculated in a summer period agreed within their uncertainty and pointed to soil uptake as the main driver of H 2 exchange at Harvard Forest, with H 2 deposition velocities ranging from 0.04 to 0.10 cm s −1 .

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Section: Flux-gradient Methodsmentioning

confidence: 99%

Section: Sampling Errormentioning

confidence: 99%

Section: Measurement Accuracymentioning

confidence: 99%

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Ecosystem fluxes of hydrogen: a comparison of flux-gradient methods

et al. 2014

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“…The issue arises in examination of proposed methods to use the thermal roughness length (z 0T ) derived from consideration of the sensible heat flux and the bulk temperature difference between the surface and the air as a basis for atmospheric surface-layer and planetary boundary-layer (PBL) computations. These methods derive from experimental findings that z 0T differs from z 0 , the conventional aerodynamic roughness length associated with the wind profile (Owen and Thomson 1963;Plate 1971;Brutsaert 1982;Garratt 1992). The issue also arises in air pollution modelling.…”

Section: Introductionmentioning

confidence: 99%

“…Garratt and Hicks (1973, hereafter G&H) extended the resulting formulations to the real world, by summarizing data from micrometeorological field studies as well as from physical modelling. Subsequent presentations by Garratt and Francey (1978) and Garratt (1992) refined the G&H analysis, with the focus on the dependence of ln(z 0 /z 0T ) = kB −1 on surface properties, represented by the roughness Reynolds number…”

Section: Introductionmentioning

confidence: 99%

On the Relevance of ln(z0/z0T) = kB-1

Hicks

Pendergrass

Baker

et al. 2017

Boundary-Layer Meteorol

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The assumption that the roughness Reynolds number (Re * ) can be used as a basis for quantifying the boundary-layer property kB −1 (= ln(z 0 /z 0T )) as in some modern numerical models is questioned. While Re * is a useful property in studies of pipe flow, it appears to have only marginal applicability in the case of treeless terrain, as studied in the two experimental situations presented here. For both the daytime and night-time cases there appears to be little correlation between kB −1 and Re * . For daytime, the present studies indicate that the assumption kB −1 ≈ 2 is acceptable, while for night-time, the scatter involved in relating kB −1 to Re * suggests there is little reason to assume a direct relationship. However, while the scatter affecting all of the night-time results is large, there remains a significant correlation between the heat and momentum fluxes upon which an alternative methodology for describing bulk air-surface exchange at night could be constructed. The friction coefficient (C f ) and the turbulent Stanton number (St * ) are discussed as possible alternatives for describing bulk properties of the air layer adjacent to the surface. While describing the surface roughness in terms of the friction coefficient provides an attractive simplification relative to the conventional methodologies based on roughness length and stability considerations, use of the Stanton number shares many of uncertainties that affect kB −1 . The transitions at dawn and dusk remain demanding situations to address.

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