scholarly journals A Functional Approach to Vertical Turbulent Transport of Scalars in the Atmospheric Surface Layer

2019 ◽  
Vol 173 (3) ◽  
pp. 373-408
Author(s):  
Robert J. Clement ◽  
John B. Moncrieff
Keyword(s):  
Surface Layer ◽  
Eddy Covariance ◽  
Turbulent Transport ◽  
Low Frequency ◽  
Surface Fluxes ◽  
Scalar Flux ◽  
Data Retention ◽  
Averaging Operator ◽  
Flux Estimation ◽  
Reynolds Averaging

Abstract Eddy covariance has been the de facto method of analyzing scalar turbulent transport data. To refine the information available from these data, we derive a simplified version of the turbulent scalar-transport equation for the surface layer, which employs a more explicit form of signal decomposition and dispenses with Reynolds averaging in favour of an averaging operator based on the relevant scalar-flux driving variables. The resulting method, termed functional covariance, provides five areas of improvement in flux estimation: (i) Better representation of surface fluxes through closer correspondence of turbulent exchange with variations in the driving variables. (ii) An approximate 25% reduction in flux uncertainty resulting from improved independence of turbulent-flux samples. (iii) Improved data retention through less onerous quality control (stationarity) testing. (iv) Improved estimation of low-frequency flux contributions through reduced uncertainty and avoidance of driving-variable nonstationarity. (v) Potential elimination of flux-storage estimation when state driving-variables are used to define the functional-covariance flux averaging. We describe the important considerations required for application of functional covariance, apply both functional- and eddy-covariance methods to an example dataset, compare the resulting eddy- and functional-covariance estimates, and demonstrate the aforementioned benefits of functional covariance.

scholarly journals Some aspects of the energy balance closure problem

2006 ◽  
Vol 6 (12) ◽  
pp. 4395-4402 ◽  
Author(s):  
T. Foken ◽  
F. Wimmer ◽  
M. Mauder ◽  
C. Thomas ◽  
C. Liebethal
Keyword(s):  
Surface Layer ◽  
Energy Balance ◽  
Eddy Covariance ◽  
Low Frequency ◽  
Turbulent Fluxes ◽  
Closure Problem ◽  
Energy Balance Closure ◽  
Considerable Influence ◽  
Turbulence Spectrum ◽  
Eddy Covariance Method

Abstract. After briefly discussing several reasons for the energy balance closure problem in the surface layer, the paper focuses on the influence of the low frequency part of the turbulence spectrum on the residual. Changes in the turbulent fluxes in this part of the turbulence spectrum were found to have a significant influence on the changes of the residual. Using the ogive method, it was found that the eddy-covariance method underestimates turbulent fluxes in the case of ogives converging for measuring times longer than the typical averaging interval of 30 min. Additionally, the eddy-covariance method underestimates turbulent fluxes for maximal ogive functions within the averaging interval, both mainly due to advection and non-steady state conditions. This has a considerable influence on the use of the eddy-covariance method.

scholarly journals Estimating surface fluxes using eddy covariance and numerical ogive optimization

2015 ◽  
Vol 15 (4) ◽  
pp. 2081-2103 ◽  
Author(s):  
J. Sievers ◽  
T. Papakyriakou ◽  
S. E. Larsen ◽  
M. M. Jammet ◽  
S. Rysgaard ◽  
...  
Keyword(s):  
Heat Flux ◽  
Eddy Covariance ◽  
Conventional Method ◽  
Sensible Heat Flux ◽  
Low Frequency ◽  
Turbulent Fluxes ◽  
Relative Difference ◽  
Surface Fluxes ◽  
Physical Parameters ◽  
Flux Analysis

Abstract. Estimating representative surface fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modelling efforts, low-frequency contributions interfere with our ability to isolate local biogeochemical processes of interest, as represented by turbulent fluxes. No method currently exists to disentangle low-frequency contributions on flux estimates. Here, we present a novel comprehensive numerical scheme to identify and separate out low-frequency contributions to vertical turbulent surface fluxes. For high flux rates (|Sensible heat flux| > 40 Wm−2, |latent heat flux|> 20 Wm−2 and |CO2 flux|> 100 mmol m−2 d−1 we found that the average relative difference between fluxes estimated by ogive optimization and the conventional method was low (5–20%) suggesting negligible low-frequency influence and that both methods capture the turbulent fluxes equally well. For flux rates below these thresholds, however, the average relative difference between flux estimates was found to be very high (23–98%) suggesting non-negligible low-frequency influence and that the conventional method fails in separating low-frequency influences from the turbulent fluxes. Hence, the ogive optimization method is an appropriate method of flux analysis, particularly in low-flux environments.

scholarly journals Some aspects of the energy balance closure problem

2006 ◽  
Vol 6 (2) ◽  
pp. 3381-3402 ◽  
Author(s):  
T. Foken ◽  
F. Wimmer ◽  
M. Mauder ◽  
C. Thomas ◽  
C. Liebethal
Keyword(s):  
Surface Layer ◽  
Energy Balance ◽  
Eddy Covariance ◽  
Low Frequency ◽  
Turbulent Fluxes ◽  
Closure Problem ◽  
Energy Balance Closure ◽  
Considerable Influence ◽  
Turbulence Spectrum ◽  
Eddy Covariance Method

Abstract. After briefly discussing several reasons for the energy balance closure problem in the surface layer, the paper focuses on the influence of the low frequency part of the turbulence spectrum on the residual. Changes in the turbulent fluxes in this part of the turbulence spectrum were found to have a significant influence on the changes of the residual. Using the ogive method, it was found that the eddy-covariance method underestimates turbulent fluxes in the case of ogives converging for measuring times longer than the typical averaging interval of 30 min. Additionally, the eddy-covariance method underestimates turbulent fluxes for maximal ogive functions within the averaging interval, both mainly due to advection and non-steady state conditions. This has a considerable influence on the use of the eddy-covariance method.

Turbulent flux estimation in the atmospheric surface layer through flux-gradient similarity during the ALEX17 field campaign

2020 ◽  
Author(s):  
Belén Martí ◽  
Daniel Martínez-Villagrasa ◽  
Joan Cuxart
Keyword(s):  
Heat Flux ◽  
Surface Layer ◽  
Eddy Covariance ◽  
Friction Velocity ◽  
Turbulent Flux ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Flux Gradient ◽  
Eddy Covariance System ◽  
Flux Estimation

<p>Turbulent flux measurements require high frequency sampling in order to characterize appropriately all the variability scales of the atmosphere. A 3D sonic anemometer coupled with a gas detector allows for applying the eddy-covariance method which has become the standard. However, the high cost of this system often implies to look for alternative methods, specially when multiple stations are required. Turbulent fluxes can also be estimated through the flux-gradient similarity theory, requiring observations of mean quantities of (at least) air temperature and humidity at two levels and wind at one height. This approach is more sensitive to the disturbing influence of heterogeneous and complex surfaces and a comparison between methodologies is required under these conditions.<br><br>The data used in this study is part of the ALaiz EXperiment 2017-2018 (ALEX17). This campaign was the last within the New European Altas project. It had a duration of over a year with measurements in complex terrain. The location of the experiment is a valley bounded by two mountain ranges that rise 150 m north and over 600 m south. A central site in the centre of the valley was instrumented with a sodar-RASS, an 80-m tower, a surface energy balance (SEB) station with an eddy-covariance system and a surface-layer station (SLS) with the necessary measurements to estimate the turbulent fluxes. In addition, eight supplementary SLS were deployed along the longitudinal and transverse valley axes to characterize the surface layer variability within the valley.<br><br>This communication will present a comparison of the friction velocity and sensible heat flux obtained from both the eddy-covariance system and the flux-gradient method at the central site for a time series of 8 months. Friction velocity is highly comparable between methodologies with a correlation of 0.92 and a standard deviation of 0.05. The performance of the sensible heat flux estimation differs between stable and unstable cases, with a correlation of 0.70 and 0.89, respectively, after applying a quality control procedure. The poorer results obtained under stable conditions points out the need for alternative estimations of the sensible heat flux for these cases.</p>

Area-Averaged Surface Fluxes Over the Litfass Region Based on Eddy-Covariance Measurements

2006 ◽  
Vol 121 (1) ◽  
pp. 33-65 ◽  
Author(s):  
Frank Beyrich ◽  
Jens-Peter Leps ◽  
Matthias Mauder ◽  
Jens Bange ◽  
Thomas Foken ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Surface Fluxes ◽  
Eddy Covariance Measurements

scholarly journals Inferring <sup>222</sup>Rn soil fluxes from ambient <sup>222</sup>Rn activity and eddy covariance measurements of CO<sub>2</sub>

2016 ◽  
Vol 9 (11) ◽  
pp. 5523-5533 ◽  
Author(s):  
Sander van der Laan ◽  
Swagath Manohar ◽  
Alex Vermeulen ◽  
Fred Bosveld ◽  
Harro Meijer ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Activity Concentration ◽  
Regional Scale ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Spatial And Temporal Variability ◽  
Single Pair ◽  
The South ◽  
Practical Applications ◽  
Soil Flux

Abstract. We present a new methodology, which we call Single Pair of Observations Technique with Eddy Covariance (SPOT-EC), to estimate regional-scale surface fluxes of 222Rn from tower-based observations of 222Rn activity concentration, CO2 mole fractions and direct CO2 flux measurements from eddy covariance. For specific events, the regional (222Rn) surface flux is calculated from short-term changes in ambient (222Rn) activity concentration scaled by the ratio of the mean CO2 surface flux for the specific event to the change in its observed mole fraction. The resulting 222Rn surface emissions are integrated in time (between the moment of observation and the last prior background levels) and space (i.e. over the footprint of the observations). The measurement uncertainty obtained is about ±15 % for diurnal events and about ±10 % for longer-term (e.g. seasonal or annual) means. The method does not provide continuous observations, but reliable daily averages can be obtained. We applied our method to in situ observations from two sites in the Netherlands: Cabauw station (CBW) and Lutjewad station (LUT). For LUT, which is an intensive agricultural site, we estimated a mean 222Rn surface flux of (0.29 ± 0.02) atoms cm−2 s−1 with values  > 0.5 atoms cm−2 s−1 to the south and south-east. For CBW we estimated a mean 222Rn surface flux of (0.63 ± 0.04) atoms cm−2 s−1. The highest values were observed to the south-west, where the soil type is mainly river clay. For both stations good agreement was found between our results and those from measurements with soil chambers and two recently published 222Rn soil flux maps for Europe. At both sites, large spatial and temporal variability of 222Rn surface fluxes were observed which would be impractical to measure with a soil chamber. SPOT-EC, therefore, offers an important new tool for estimating regional-scale 222Rn surface fluxes. Practical applications furthermore include calibration of process-based 222Rn soil flux models, validation of atmospheric transport models and performing regional-scale inversions, e.g. of greenhouse gases via the SPOT 222Rn-tracer method.

scholarly journals Assessing the Impact of Changes in Land Surface Conditions on WRF Predictions in Arid Regions

2020 ◽  
Vol 21 (12) ◽  
pp. 2829-2853 ◽  
Author(s):  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
Michael Weston ◽  
Mohan Thota ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Soil Texture ◽  
Land Surface ◽  
Surface Wind ◽  
Surface Fluxes ◽  
Abu Dhabi ◽  
Horizontal Wind ◽  
Cold Bias ◽  
Near Surface ◽  
The Impact

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.

Two Experiments on Using a Scintillometer to Infer the Surface Fluxes of Momentum and Sensible Heat

2012 ◽  
Vol 51 (9) ◽  
pp. 1685-1701 ◽  
Author(s):  
Edgar L Andreas
Keyword(s):  
Eddy Covariance ◽  
Correlation Coefficients ◽  
Arctic Sea Ice ◽  
Surface Fluxes ◽  
Index Structure ◽  
Quality Data ◽  
Sensible Heat ◽  
Traditional Use ◽  
Similarity Functions ◽  
Essential Question

AbstractA traditional use of scintillometry is to infer path-averaged values of the turbulent surface fluxes of sensible heat Hs and momentum τ (, where ρ is air density and u* is the friction velocity). Many scintillometer setups, however, measure only the path-averaged refractive-index structure parameter ; the wind information necessary for inferring u* and Hs comes from point measurements or is absent. The Scintec AG SLS20 surface-layer scintillometer system, however, measures both and the inner scale of turbulence ℓ0, where ℓ0 is related to the dissipation rate of turbulent kinetic energy ɛ. The SLS20 is thus presumed to provide path-averaged estimates of both u* and Hs. This paper describes comparisons between SLS20-derived estimates of u* and Hs and simultaneous eddy-covariance measurements of these quantities during two experiments: one, over Arctic sea ice; and a second, over a midlatitude land site during spring. For both experiments, the correlation between scintillometer and eddy-covariance fluxes is reasonable: correlation coefficients are typically above 0.7 for the better-quality data. For both experiments, though, the scintillometer usually underestimates u* and underestimates the magnitude of Hs when compared with the corresponding eddy-covariance values. The data also tend to be more scattered when < 10−14 m−2/3: the signal-to-noise ratio for scintillometer-derived fluxes decreases as decreases. An essential question that arises during these comparisons is what similarity functions to use for inferring fluxes from the scintillometer and ℓ0 measurements. The paper thus closes by evaluating whether any of four candidate sets of similarity functions is consistent with the scintillometer data.

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