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ABSTRACT: Above forest canopies, eddy covariance (EC) measurements of mass (CO2, H2O vapor) and energy exchange, assumed to represent ecosystem fluxes, are commonly made at one point in the roughness sublayer (RSL). A spatial variability experiment, in which EC measurements were made from six towers within the RSL in a uniform pine plantation, quantified large and dynamic spatial variation in fluxes. The spatial coefficient of variation (CV) of the scalar fluxes decreased with increasing integration time, stabilizing at a minimum that was independent of further lengthening the averaging period (hereafter a ‘stable minimum’). For all three fluxes, the stable minimum (CV=9–11%) was reached at averaging times (τp) of 6–7 h during daytime, but higher stable minima (CV=46–158%) were reached at longer τp (>12 h) during nighttime. To the extent that decreasing CV of EC fluxes reflects reduction in micrometeorological sampling errors, half of the observed variability at τp=30 min is attributed to sampling errors. The remaining half (indicated by the stable minimum CV) is attributed to underlying variability in ecosystem structural properties, as determined by leaf area index, and perhaps associated ecosystem activity attributes. We further assessed the spatial variability estimates in the context of uncertainty in annual net ecosystem exchange (NEE). First, we adjusted annual NEE values obtained at our long-term observation tower to account for the difference between this tower and the mean of all towers from this experiment; this increased NEE by up to 55 g C m−2 yr−1. Second, we combined uncertainty from gap filling and instrument error with uncertainty because of spatial variability, producing an estimate of variability in annual NEE ranging from 79 to 127 g C m−2 yr−1. This analysis demonstrated that even in such a uniform pine plantation, in some years spatial variability can contribute ∼50% of the uncertainty in annual NEE estimates.
Global Change Biology 04/2006; 12(5):883 - 896. · 6.86 Impact Factor
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ABSTRACT: One of the defining syndromes of turbulence is nonlinear stochasticity. This view of turbulence motivated the development
of statistical mechanics theories that have served to connect the basic Navier-Stokes (NS) equations of motion to the statistical
results of numerous field experiments. In general, the proper averaging operator for stochastic processes is ensemble averaging.
Given the transient nature of flow boundary conditions in natural systems, field experiments are typically unable to capture
a suitable ensemble, in a strict sense. Instead, field experiments typically focus on time averaged statistics. Stationarity
and ergodicity are two central concepts (required conditions) used to link field measurements and the NS equations or field
measurements to “boundary conditions” at the land-atmosphere interface. In this Chapter, we present an elementary review of
these two concepts for the atmospheric surface layer (ASL) and canopy sublayer (CSL) and proceed to show why the stable CSL
tends to violate both conditions. A weaker form of these two conditions may be applicable to CSL flows that are only moderately
stably stratified. Practical implications for night time CO2 flux corrections are also discussed.
01/2006: pages 161-180;
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ABSTRACT: Temperate grasslands represent about 32% of the earth's land area and cover approximately 56% of the area of Ireland; yet their role as sources/sinks of atmospheric CO2 is not well quantified. We used an eddy covariance (EC) system to measure the net ecosystem exchange (NEE) at a managed grassland site in southern Ireland for 2 years. Rainfall in 2002 and 2003 was 1785 and 1185 mm, respectively, compared to an annual average of 1470 mm. The EC measured NEE was less in the wet year (−193 ± 50 g C m−2, uptake) than in the dry year (−258 ± 50 g C m−2, uptake). Combining NEE measurements with estimates of the components of the farm scale carbon (C) balance we estimated the amount of C fixed to the soil as −24 ± 62 g C m−2 for 2002 and −89 ± 62 g C m−2 for 2003, indicating that this ecosystem was a small sink for carbon. For the same months in different years, we found that the NEE was similar, although their soil moisture status was very different. This was due to the fact that the soil moisture status in this region, even in dry periods, was always well above the wilting point which resulted in no moisture stress on the vegetation at any time over the 2 years. We concluded that the NEE for this humid grassland ecosystem was not very sensitive to the variation in precipitation over the 2 years. We found that herbage harvesting had a direct effect of reducing the NEE in the month of harvest. We conclude that the interannual variation in NEE of 65 g C m−2 is of the order of uncertainty of the EC measurements.
Agricultural and Forest Meteorology. 01/2006;
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Gabriel G Katul,
Cheng-I Hsieh,
David Bowling,
Kenneth Clark,
Narasinha Shurpali,
Andrew Turnipseed, John Albertson,
Kevin Tu,
Dave Hollinger,
Bob Evans,
Brian Offerle,
Dean Anderson,
David S. Ellsworth,
Christoph S. Vogel,
Ram Oren
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ABSTRACT: The spatial variability of turbulent flow statistics in the roughness sublayer (RSL) of a uniform even-aged 14 m (= h) tall loblolly pine forest was investigated experimentally. Using seven existing walkup towers at this stand, high frequency velocity, temperature, water vapour and carbon dioxide concentrations were measured at 15.5 m above the ground surface from October 6 to 10 in 1997. These seven towers were separated by at least 100m from each other. The objective of this study was to examine whether single tower turbulence statistics measurements represent the flow properties of RSL turbulence above a uniform even-aged managed loblolly pine forest as a best-case scenario for natural forested ecosystems. From the intensive space-time series measurements, it was demonstrated that standard deviations of longitudinal and vertical velocities (σ u , σ w ) and temperature (σ T ) are more planar homogeneous than their vertical flux of momentum (u * 2 ) and sensible heat (H) counterparts. Also, the measured H is more horizontally homogeneous when compared to fluxes of other scalar entities such as CO 2 and water vapour. While the spatial variability in fluxes was significant (>15 %), this unique data set confirmed that single tower measurements represent the ‘canonical’ structure of single-point RSL turbulence statistics, especially flux-variance relationships. Implications to extending the ‘moving-equilibrium’ hypothesis for RSL flows are discussed. The spatial variability in all RSL flow variables was not constant in time and varied strongly with spatially averaged friction velocity u * , especially when u * was small. It is shown that flow properties derived from two-point temporal statistics such as correlation functions are more sensitive to local variability in leaf area density when compared to single point flow statistics. Specifically, that the local relationship between the reciprocal of the vertical velocity integral time scale (I w ) and the arrival frequency of organized structures (ū/h) predicted from a mixing-layer theory exhibited dependence on the local leaf area index. The broader implications of these findings to the measurement and modelling of RSL flows are also discussed. Peer Reviewed http://deepblue.lib.umich.edu/bitstream/2027.42/42512/1/10546_2004_Article_234383.pdf
Boundary-Layer Meteorology 09/1999; · 1.74 Impact Factor
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ABSTRACT: . High frequency longitudinal velocity (u) measurements were performed in the atmospheric boundary layer to investigate the inertial subrange structure of turbulence. Global and local scaling exponent distributions and other statistical properties were derived using continuous (CWT ) and critically sampled orthonormal (OWT ) wavelet transformations. These statistical measures were contrasted to similar statistical measures derived by applying CWT and OWT to a fractional Brownian motion (fBm) time series with a Hurst exponent of 1=3. This study demonstrated that both CWT and OWT were able to resolve intermittency-based departures from global power-laws observed in higher-order structure functions. Particularly, the global power laws inferred from OWT were in excellent agreement with the She-L'eveque vortex filament model. However, these wavelet computed intermittency departures were smaller than those computed by the extended self similarity structure function approach. The effects of...
08/1999;
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ABSTRACT: The variability in land surface heat (H), water vapor (LE), and CO2 (or net ecosystem exchange, NEE) fluxes was investigated at scales ranging from fractions of seconds to years using eddy-covariance flux measurements above a pine forest. Because these fluxes significantly vary at all these time scales and because large gaps in the record are unavoidable in such experiments, standard Fourier expansion methods for computing the spectral and cospectral statistical properties were not possible. Instead, orthonormal wavelet transformations are proposed and used. The are ideal at resolving process variability with respect to both scale and time and are able to isolate and remove the effects of missing data (or gaps) from spectral and cospectral calculations. Using the spectra, we demonstrated unique aspects in three appropriate ranges of time scales: turbulent time scales (fractions of seconds to minutes), meteorological time scales (hour to weeks), and seasonal to interannual time scales corresponding to climate and vegetation dynamics. We have shown that: (1) existing turbulence theories describe the short time scales well, (2) coupled physiological and transport models (e.g. CANVEG) reproduce the wavelet spectral characteristics of all three land surface fluxes for meteorological time scales, and (3) seasonal dynamics in vegetation physiology and structure inject strong correlations between land surface fluxes and forcing variables at monthly to seasonal time scales. The broad implications of this study center on the possibility of developing low-dimensional models of land surface water, energy, and carbon exchange. If the bulk of the flux variability is dominated by a narrow band or bands of modes, and these modes “resonate” with key state and forcing variables, then low-dimensional models may relate these forcing and state variables to NEE and LE.
Advances in Water Resources.
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ABSTRACT: Modeling scalar transport within canopies remains a vexing research problem in eco-hydrology and eco-hydraulics. Canopy turbulence is inhomogeneous, non-Gaussian, and highly dissipative, thereby posing unique challenges to three-dimensional Lagrangian Dispersion Models (LDM). Standard LDM approaches usually satisfy the well-mixed condition and account for turbulence inhomogeneity but not for its non-Gaussian statistics and enhanced dissipation. While numerous studies evaluated the importance of the former (with mixed results), few studies to date considered the latter. In this paper we present new data and explore: (1) the skill of LDM in reproducing mean scalar concentration distributions within dense and rigid canopies for source releases near the canopy top and near the ground, and (2) the extent to which these estimates are sensitive to the formulation of the mean turbulent kinetic energy dissipation rate ([epsilon]) profile. Toward this end, Laser Induced Florescence (LIF) and Laser Doppler Anemom
Advances in Water Resources. 29(2):326-335.
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ABSTRACT: Modeling scalar transport within canopies remains a vexing research problem in eco-hydrology and eco-hydraulics. Canopy turbulence is inhomogeneous, non-Gaussian, and highly dissipative, thereby posing unique challenges to three-dimensional Lagrangian Dispersion Models (LDM). Standard LDM approaches usually satisfy the well-mixed condition and account for turbulence inhomogeneity but not for its non-Gaussian statistics and enhanced dissipation. While numerous studies evaluated the importance of the former (with mixed results), few studies to date considered the latter. In this paper we present new data and explore: (1) the skill of LDM in reproducing mean scalar concentration distributions within dense and rigid canopies for source releases near the canopy top and near the ground, and (2) the extent to which these estimates are sensitive to the formulation of the mean turbulent kinetic energy dissipation rate ([epsilon]) profile. Toward this end, Laser Induced Florescence (LIF) and Laser Doppler Anemometry (LDA) were used to measure scalar concentration and Eulerian flow statistics within a dense model canopy in a rectangular flume. It is shown that LDM concentration predictions are sensitive to how [epsilon] is estimated. Good agreement between measured and modelled mean concentration distributions were obtained when [epsilon] was estimated from the mean squared longitudinal velocity gradients and isotropic turbulence principles. However, when [epsilon] was estimated from the widely used scaling arguments that employ a constant Lagrangian time scale (Tl) and a specified vertical velocity variance profile, the predicted concentrations diverged significantly from the LIF measurements. Better agreement was obtained when a constant mixing length scale was used with the profile.
Advances in Water Resources. 29(2):326-335.
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[show abstract]
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ABSTRACT: Modeling scalar transport within canopies remains a vexing research problem in eco-hydrology and eco-hydraulics. Canopy turbulence is inhomogeneous, non-Gaussian, and highly dissipative, thereby posing unique challenges to three-dimensional Lagrangian Dispersion Models (LDM). Standard LDM approaches usually satisfy the well-mixed condition and account for turbulence inhomogeneity but not for its non-Gaussian statistics and enhanced dissipation. While numerous studies evaluated the importance of the former (with mixed results), few studies to date considered the latter. In this paper we present new data and explore: (1) the skill of LDM in reproducing mean scalar concentration distributions within dense and rigid canopies for source releases near the canopy top and near the ground, and (2) the extent to which these estimates are sensitive to the formulation of the mean turbulent kinetic energy dissipation rate (ϵ) profile. Toward this end, Laser Induced Florescence (LIF) and Laser Doppler Anemometry (LDA) were used to measure scalar concentration and Eulerian flow statistics within a dense model canopy in a rectangular flume. It is shown that LDM concentration predictions are sensitive to how ϵ is estimated. Good agreement between measured and modelled mean concentration distributions were obtained when ϵ was estimated from the mean squared longitudinal velocity gradients and isotropic turbulence principles. However, when ϵ was estimated from the widely used scaling arguments that employ a constant Lagrangian time scale (Tl) and a specified vertical velocity variance profile, the predicted concentrations diverged significantly from the LIF measurements. Better agreement was obtained when a constant mixing length scale was used with the profile.
Advances in Water Resources.
