Flux Footprint Research Articles

Effects of variable fetch and footprint on surface renewal measurements of sensible and latent heat fluxes in cotton

Understanding crop evapotranspiration (ET) is important for efficient irrigation management. The eddy covariance (EC) technique is useful in measuring whole canopy latent heat flux from field crops. However, it requires expensive equipment and complex data analysis; hence, is relevant for research only. With the aim of developing a low-cost and simple method, we investigated here the surface-renewal (SR) method. This method estimates sensible heat flux from high frequency temperature measurements by using a fine wire thermocouple (TC). Next, latent heat flux is derived from the energy balance closure. Since fine wire thermocouple measurements of air temperature can be performed near the canopy top, it was hypothesized (Castellvi, 2012) that fetch requirements can be relaxed relatively to those for EC, and a relatively small fetch is sufficient for reliable flux measurements by SR. In the present study, the SR technique was examined in a cotton field in southern Israel. Seven fine wire thermocouples were installed at various distances from field edges and at different heights above the ground, providing variable fetch from 50 to 200 m, depending on field geometry and wind direction. An EC system was installed within the field at a position that provided sufficient fetch (400 m) for reliable reference values of sensible and latent heat fluxes. Excellent energy balance closure of 0.96 (R2 = 0.95) was obtained from a non-continuous period of 31 days of measurements. SR data from fine-wire thermocouples at all heights were classified by either available fetch or by 90% flux footprint. Only cases in which footprint was smaller than the available fetch were included in the analysis. Two footprint models were examined, KJ (Kljun et al., 2015) and HS (Hsieh et al., 2000). Results of fetch classification showed that the SR weighting factor varied between 0.67 and 1.34 and was independent of fetch. Footprint classification provided weighting factors between 0.46 and 1.18 for the KJ model and between 0.8 and 1.26 for the HS model. LE derived from SR sensible heat flux and energy balance closure, was regressed against LE reference values measured by the eddy covariance. Results showed deviations of up to 15% and 30% between SR and EC, for the KJ and HS model data, respectively. We conclude that in the cotton field under study the SR technique was reliable in estimating sensible and latent heat fluxes and the weighting factor was essentially independent of the geometrical fetch and the flux footprint of the sensors.

CO2 flux variation and its contribution area in the debris-covered area of Koxkar Glacier, Mt. Tianshan in China

During the formation and development of glacial meltwater runoff, hydrochemical erosion is abundant, especially the hydrolysis of K/Na feldspar and carbonates, which can consume H+ in the water, promote the formation of bicarbonate by dissolving atmospheric CO2, and affect the regional carbon cycle. From July 21, 2015, to July 18, 2017, the CO2 concentration and flux were observed by the eddy covariance (EC) method in the relatively flat and open moraine cover area of Koxkar Glacier in western Mt. Tianshan, China. We found that: (1) atmospheric CO2 fluxes ranged from − 408.95 to 81.58 mmol m−2 day−1 (average − 58.68 mmol m−2 day−1), suggesting that the study area is a significant carbon sink, (2) the CO2 flux footprint contribution areas were primarily within 150 m of the EC station, averaging total contribution rates of 93.30%, 91.39%, and 90.17% of the CO2 flux in the snow accumulation, snow melting, and glacial melting periods, respectively. Therefore, the contribution areas with significant influences on CO2 flux observed at EC stations were concentrated, demonstrating that grassland CO2 flux around the glaciers had little effect at the EC stations, (3) in the predominant wind direction, under stable daytime atmospheric stratification, the measurement of CO2 flux, as interpreted by the Agroscope Reckenholz Tanikon footprint tool, was 79.09% ± 1.84% in the contribution area. This was slightly more than seen at night, but significantly lower than the average under unstable atmospheric stratification across the three periods of interest (89%). The average distance of the farthest point of the flux footprint under steady state atmospheric conditions was 202.61 ± 69.33 m, markedly greater than that under non-steady state conditions (68.55 ± 10.34 m). This also indicates that the CO2 flux observed using EC was affected primarily by hydrochemical erosion reactions in the glacier area, (4) a good negative correlation was found between net glacier exchange (NGE) of CO2 and air temperature on precipitation-free days. Strong ice and snow ablation could promote hydrochemical reactions of soluble substances in the debris area and accelerated sinking of atmospheric CO2. Precipitation events might reduce snow and ice melting, driven by reduced regional temperatures. However, a connection between NGE and precipitation, when less than 8.8 mm per day, was not obvious. When precipitation was greater than 8.8 mm per day, NGE decreased with increasing precipitation, (5) graphically, the slope of NGE, related to daily runoff, followed a trend: snow melting period > snow accumulation period > early glacial ablation period > late glacier ablation period > dramatic glacier ablation period. The slope was relatively large during snow melting, likely because of CO2 sinking caused by water–rock interactions. The chemical reaction during elution in the snow layer might also promote atmospheric CO2 drawdown. At the same time, the damping effect of snow cover and the almost-closed glacier hydrographic channel inhibited the formation of regional runoff, possibly providing sufficient time for the chemical reaction, thus promoting further CO2 drawdown.

Dynamic divertor control using resonant mixed toroidal harmonic magnetic fields during ELM suppression in DIII-D

Experiments using Resonant Magnetic Perturbations (RMPs), with a rotating n = 2 toroidal harmonic combined with a stationary n = 3 toroidal harmonic, have validated predictions that divertor heat and particle flux can be dynamically controlled while maintaining Edge Localized Mode (ELM) suppression in the DIII-D tokamak. Here, n is the toroidal mode number. ELM suppression over one full cycle of a rotating n = 2 RMP that was mixed with a static n = 3 RMP field has been achieved. Prominent heat flux splitting on the outer divertor has been observed during ELM suppression by RMPs in low collisionality regime in DIII-D. Strong changes in the three dimensional heat and particle flux footprint in the divertor were observed during the application of the mixed toroidal harmonic magnetic perturbations. These results agree well with modeling of the edge magnetic field structure using the TOP2D code, which takes into account the plasma response from the MARS-F code. These results expand the potential effectiveness of the RMP ELM suppression technique for the simultaneous control of divertor heat and particle load required in ITER.

A Backward-Lagrangian-Stochastic Footprint Model for the Urban Environment

Built terrains, with their complexity in morphology, high heterogeneity, and anthropogenic impact, impose substantial challenges in Earth-system modelling. In particular, estimation of the source areas and footprints of atmospheric measurements in cities requires realistic representation of the landscape characteristics and flow physics in urban areas, but has hitherto been heavily reliant on large-eddy simulations. In this study, we developed physical parametrization schemes for estimating urban footprints based on the backward-Lagrangian-stochastic algorithm, with the built environment represented by street canyons. The vertical profile of mean streamwise velocity is parametrized for the urban canopy and boundary layer. Flux footprints estimated by the proposed model show reasonable agreement with analytical predictions over flat surfaces without roughness elements, and with experimental observations over sparse plant canopies. Furthermore, comparisons of canyon flow and turbulence profiles and the subsequent footprints were made between the proposed model and large-eddy simulation data. The results suggest that the parametrized canyon wind and turbulence statistics, based on the simple similarity theory used, need to be further improved to yield more realistic urban footprint modelling.

A Multivariate Estimate of the Cold Season Atmospheric Response to North Pacific SST Variability

The Generalized Equilibrium Feedback Analysis (GEFA) is used to distinguish the influence of the Oyashio Extension (OE) and the Kuroshio Extension (KE) variability on the atmosphere from 1979 to 2014 from that of the main SST variability modes, using seasonal mean anomalies. Remote SST anomalies are associated with each single oceanic regressor, but the multivariate approach efficiently confines their SST footprints. In autumn [October–December (OND)], the OE meridional shifts are followed by a North Pacific Oscillation (NPO)-like signal. The OE influence is not investigated in winter [December–February (DJF)] because of multicollinearity, but a robust response with a strong signal over the Bering Sea is found in late winter/early spring [February–April (FMA)], a northeastward strengthening of the Aleutian low following a northward OE shift. A robust response to the KE variability is found in autumn, but not in winter and late winter when the KE SST footprint becomes increasingly small and noisy as regressors are added in GEFA. In autumn, a positive PDO is followed by a northward strengthening of the Aleutian low and a southward shift of the storm track in the central Pacific, reflecting the surface heat flux footprint in the central Pacific. In winter, the PDO shifts the maximum baroclinicity and storm track southward, the response strongly tilts westward with height in the North Pacific, and there is a negative NAO-like teleconnection. In late winter, the North Pacific NPO-like response to the PDO interferes negatively with the response to the OE and is only detected when the OE is represented in GEFA. A different PDO influence on the atmospheric circulation is found from 1958 to 1977.

Turbulence scales for eddy covariance quality control over a tropical dry forest in complex terrain

The assessment of the potential for carbon sequestration in tropical dry forests has lagged behind the work done in other tropical environments; the particularities of the carbon dynamics in these ecosystems are largely absent from models of global primary productivity and effects of climate change on vegetation. In Mexico, the largest portions of preserved tropical dry forests have been confined to conservation areas on hilly terrain where productive activities like agriculture are difficult. The location of these remnants of original tropical dry forest in complex terrain presents an operational challenge to directly assess CO2 exchange between the forest and the atmosphere by means of the eddy covariance (EC) technique. We installed and maintained an EC system over an intact tropical dry forest in the Chamela-Cuixmala Biosphere Reserve in the lowlands of the Pacific Coast of Mexico, to assess the suitability of this technique to measure CO2 flux, sensible heat and latent heat flux over moderately complex topography in a remote location. The quality of the datasets produced was evaluated through the degree of energy balance closure achieved. Modelling the incoming and outgoing radiation to take into account the slope and aspect of the underlying terrain raised the energy balance closure from 71% to 75%. We also compared the effect of applying three different filters to discriminate conditions of well-developed turbulence: the friction velocity u*, the standard deviation of the vertical wind σw, and two dimensionless indices based on a modified turbulence intensity scale uTKE. u* and σw discriminated fluxes coming from topographically complex areas, according to a flux footprint model, but the filtered subset of data did not showed higher energy balance closure compared to the unfiltered dataset. The uTKE-based filters were more effective screening out periods dominated by horizontal or vertical advective transport instead of turbulence exchange, and raised the slope of the energy balance regression in the filtered data between 3%–17% – depending on the season-,compared to the unfiltered dataset. Together, these procedures of quality assurance and control produced a flux dataset of quality comparable to those obtained in more ideal surfaces.

Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling

Abstract. Conventional footprint models cannot account for the heterogeneity of the urban landscape imposing a pronounced uncertainty on the spatial interpretation of eddy-covariance (EC) flux measurements in urban studies. This work introduces a computational methodology that enables the generation of detailed footprints in arbitrarily complex urban flux measurements sites. The methodology is based on conducting high-resolution large-eddy simulation (LES) and Lagrangian stochastic (LS) particle analysis on a model that features a detailed topographic description of a real urban environment. The approach utilizes an arbitrarily sized target volume set around the sensor in the LES domain, to collect a dataset of LS particles which are seeded from the potential source area of the measurement and captured at the sensor site. The urban footprint is generated from this dataset through a piecewise postprocessing procedure, which divides the footprint evaluation into multiple independent processes that each yield an intermediate result. These results are ultimately selectively combined to produce the final footprint. The strategy reduces the computational cost of the LES–LS simulation and incorporates techniques to account for the complications that arise when the EC sensor is mounted on a building instead of a conventional flux tower. The presented computational framework also introduces a result assessment strategy which utilizes the obtained urban footprint together with a detailed land cover type dataset to estimate the potential error that may arise if analytically derived footprint models were employed instead. The methodology is demonstrated with a case study that concentrates on generating the footprint for a building-mounted EC measurement station in downtown Helsinki, Finland, under the neutrally stratified atmospheric boundary layer.

Overview and preliminary results of the Surface Ocean Aerosol Production (SOAP) campaign

Abstract. Establishing the relationship between marine boundary layer (MBL) aerosols and surface water biogeochemistry is required to understand aerosol and cloud production processes over the remote ocean and represent them more accurately in earth system models and global climate projections. This was addressed by the SOAP (Surface Ocean Aerosol Production) campaign, which examined air–sea interaction over biologically productive frontal waters east of New Zealand. This overview details the objectives, regional context, sampling strategy and provisional findings of a pilot study, PreSOAP, in austral summer 2011 and the following SOAP voyage in late austral summer 2012. Both voyages characterized surface water and MBL composition in three phytoplankton blooms of differing species composition and biogeochemistry, with significant regional correlation observed between chlorophyll a and DMSsw. Surface seawater dimethylsulfide (DMSsw) and associated air–sea DMS flux showed spatial variation during the SOAP voyage, with maxima of 25 nmol L−1 and 100 µmol m−2 d−1, respectively, recorded in a dinoflagellate bloom. Inclusion of SOAP data in a regional DMSsw compilation indicates that the current climatological mean is an underestimate for this region of the southwest Pacific. Estimation of the DMS gas transfer velocity (kDMS) by independent techniques of eddy covariance and gradient flux showed good agreement, although both exhibited periodic deviations from model estimates. Flux anomalies were related to surface warming and sea surface microlayer enrichment and also reflected the heterogeneous distribution of DMSsw and the associated flux footprint. Other aerosol precursors measured included the halides and various volatile organic carbon compounds, with first measurements of the short-lived gases glyoxal and methylglyoxal in pristine Southern Ocean marine air indicating an unidentified local source. The application of a real-time clean sector, contaminant markers and a common aerosol inlet facilitated multi-sensor measurement of uncontaminated air. Aerosol characterization identified variable Aitken mode and consistent submicron-sized accumulation and coarse modes. Submicron aerosol mass was dominated by secondary particles containing ammonium sulfate/bisulfate under light winds, with an increase in sea salt under higher wind speeds. MBL measurements and chamber experiments identified a significant organic component in primary and secondary aerosols. Comparison of SOAP aerosol number and size distributions reveals an underprediction in GLOMAP (GLObal Model of Aerosol Processes)-mode aerosol number in clean marine air masses, suggesting a missing marine aerosol source in the model. The SOAP data will be further examined for evidence of nucleation events and also to identify relationships between MBL composition and surface ocean biogeochemistry that may provide potential proxies for aerosol precursors and production.

Flux footprint of winter wheat farmland ecosystem in the North China Plain

The flux data of winter wheat farmland ecosystem observed by eddy covariance system in the North China Plain from 2013 to 2014 were used to combine with the footprint model FSAM. The temporal and spatial distributions of footprint of winter wheat farmland ecosystem in the North China Plain were analyzed. The differences of footprint distribution in different atmospheric stratification and growing seasons were contrastively studied. The results indicated that in the predominant wind direction, the source areas of stable atmospheric stratification were larger than unstable atmospheric stratification during the growing season of winter wheat. When the wind direction was between 0°-90°, the source area of stable atmospheric stratification was about 17.8 m longer than unstable atmospheric stratification in initial growing season. The source area of stable atmospheric stratification was about 11 m longer than unstable atmospheric stratification in late growing season. The location of the maximum flux footprint in initial growing season was 15 m (stable atmospheric stratification) and 12.4 m (unstable atmospheric stratification) further away from the observing tower than late growing season, respectively. Meanwhile, the location of the maximum flux footprint in stable atmospheric stratification was 5 m (initial growing season) and 2.4 m (late growing season) further away from the observing tower than unstable atmospheric stratification, respectively. When the wind direction was non-dominant between 90°-180°, the location of the maximum flux footprint in diffe-rent growing seasons and atmospheric stratification were 67.8 and 53.4, 47.0 and 30.8 m away from the observing tower, respectively. When the wind direction was between 270°-360°, the location of the maximum flux footprint in different growing seasons and atmospheric stratification were 58.8 and 42.0, 41.1 and 33.1 m away from the observing tower, respectively. The flux information was mainly from the northeast, southwest and southeast, which accounted for 35.4%, 32.5% and 19.4% of the whole gro-wing season scale, respectively. The major changes of flux footprint in the whole gro-wing season of winter wheat were observed from 16.0 to 173.8 m in the northeast and from 14.7 to 209 m in the southwest. The flux information was all from the farmland ecosystem. The characteristics of diurnal variations of flux footprint in two typical dates were obvious. The source area changed with atmospheric stratification and wind direction. The flux information was all from farmland ecosystem at night, while little flux information was from residential area and orchard at daytime. The quantitative results of this study could provide basis for the research of flux footprint in farmland ecosystem.

Evidence and modeling of 3D divertor footprint induced by lower hybrid waves on EAST with tungsten divertor operations

Three dimensional (3D) divertor particle flux footprints induced by the lower hybrid wave (LHW) have been systematically investigated in the EAST superconducting tokamak during the recent experimental campaign. We find that the striated particle flux (SPF) peaks away from the strike point (SP) closely fit the pitch of the edge magnetic field line for different safety factors q95, as predicted by a field line tracing code taking into account the helical current filaments (HCFs) in the scrape-off-layer (SOL). As LHW power increases, it requires the fuelling to be increased e.g. by super molecular beam injection (SMBI), to maintain a similar plasma density, which may be attributed to the pump-out effect due to LHW, and may thus be beneficial for EAST steady state operations. The 3D SPF structure is observed with a LHW power threshold (PLHW ~ 0.9 MW). The ratio of the particle fluxes between SPF and outer strike point (OSP), i.e. , increases with the LHW power. Upon transition to divertor detachment, the particle flux at the main OSP decreases, as expected, however, the particle flux at SPF continues increasing, in contrast to the RMP-induced striations that vanish with increasing divertor density. In addition, we also find that the in–out asymmetry of the 3D particle flux footprint pattern exhibits a clear dependence on the toroidal field direction (B × ∇ B ↓ and B × ∇ B↑). Experiments using neon impurity seeding show a promising capability in 3D particle and heat flux control on EAST. LHW-induced particle and heat flux striations are also present in the H-mode plasmas, reducing the peak heat flux and erosion at the main strike point, thus facilitating long-pulse operation with a new steady-state H-mode over 60 s being recently achieved in EAST.

Surface-atmosphere exchange in a box: Space-time resolved storage and net vertical fluxes from tower-based eddy covariance

Systematic bias in eddy-covariance flux measurements are pervasive. These arise both from unmeasured terms such as advection, and sampling bias in representativeness of the footprint for both turbulent and storage fluxes. As a result, the majority of eddy-covariance towers suffer from unaccounted bias when comparing to gridded earth system models and fail to close the surface energy balance. We hypothesize that one cause for these two problems is a mismatch between mass and energy fluxes measured within a time-varying source area and the actual storage and net vertical flux over a presumed “control volume”, a novel concept derived theoretically in Metzger (this issue). Here, we practically implement this theory to estimate the true net surface-atmosphere exchange (NSAE) over such control volume, thus resolving “storage flux” and “vertical advection” issues by applying the environmental response function (ERF) technique to a virtual control volume (VCV). In this method, flux observations are related at high spatio-temporal resolution to meteorological forcings and surface properties within the estimated flux footprint, and these relationships are utilized to map the control volume explicitly in 3-D over space and time. Volume integration then allows, for the first time, retrieval of the NSAE. When ERF was applied to eddy covariance and profile observations in July and August 2014 from the AmeriFlux Park Falls WLEF tower in Wisconsin, USA, heat emission integrated over the target domain increased substantially over the tower observations by +18.2 Wm−2 (+20.6%). Storage flux contributes up to 30% of NSAE at hourly timescale. The systematic uncertainty of ERF-VCV method applied for vertical flux and storage flux is within 15% and 20%, respectively. This systematic uncertainty is effectively corrected in projections. Volume-controlled NSAE provides improvements for mapping unbiased surface-atmosphere exchange for model-data comparison, assimilation and model building at model grid scale. These advances also present a promising direction for reconciling energy balance non-closure.

The challenge of reconciling bottom-up agricultural methane emissions inventories with top-down measurements

Agriculture is estimated to produce more than 40% of anthropogenic methane (CH4) emissions, contributing to global climate change. Bottom-up, IPCC based methodologies are typically used to estimate the agriculture sector’s contribution, but these estimates are rarely verified beyond the farm gate, due to the challenge of separating interspersed sources. We present flux measurements of CH4, using eddy covariance (EC), relaxed eddy accumulation (REA) and wavelet covariance obtained using an aircraft-based measurement platform and compare these top-down estimates with bottom-up footprint adjusted inventory estimates of CH4 emissions for an agricultural region in eastern Ontario, Canada. Top-down CH4 fluxes agree well (mean±1 standard error: EC=17±4mg CH4m−2d−1; REA=19±3mg CH4m−2d−1, wavelet covariance=16±3mgCH4m−2d−1), and are not statistically different, but significantly exceed bottom-up inventory estimates of CH4 emissions based on animal husbandry (8±1mgCH4m−2d−1). The discrepancy between top-down and bottom-up estimates was found to be related to both increasing fractional area of wetlands in the flux footprint, and increasing surface temperature. For the case when the wetland area in the flux footprint was less than 10% fractional coverage, the top-down and bottom-up estimates were within the measurement error. This result provides the first independent verification of agricultural methane emissions inventories at the regional scale. Wavelet analysis, which provides spatially resolved fluxes, was used to attempt to separate CH4 emissions from managed and unmanaged CH4 sources. Opportunities to minimize the challenges of verifying agricultural CH4 emissions inventories using aircraft flux measuring systems are discussed.

Estimating methane emissions from beef cattle in a feedlot using the eddy covariance technique and footprint analysis

Measurements of methane (CH4) emissions from cattle could provide invaluable data to reduce uncertainties in the global CH4 budget and to evaluate mitigation strategies to lower greenhouse gas emissions. The eddy covariance (EC) technique has recently been applied as an alternative to measure CH4 emissions from livestock systems, but heterogeneities in the source area and fetch limitations impose challenges to EC measurements. The main objective of this study was to estimate CH4 emissions rates per pen surface (Fpens) and per animal (Fanimal) from a beef cattle feedlot using the EC technique combined with two footprint models: an analytical footprint model (KM01) and a parametrization of a Lagrangian dispersion model (FFP). Fluxes of CH4 were measured using a closed-path EC system in a commercial feedlot. The footprint models were used to investigate fetch requirements and to estimate Fpens and Fanimal. The aggregated footprint area predicted by KM01 was 5–6 times larger than FFP estimates. On average, Fpens was 8 (FFP) to 14% (KM01) higher than the raw EC flux, but differences between Fpens and EC flux varied substantially depending on the location and size of the flux footprint. The monthly average Fanimal, calculated using Fpens and the footprint weighed stocking density, ranged from 83 to 125ganimal−1d−1 (KM01) and 75–114ganimal−1d−1 (FFP). The emission values are consistent with the results from previous studies in feedlots. These results suggest that the EC technique can be combined with footprint analysis to estimate gas emissions from livestock systems.

Turbulent flux variability and energy balance closure in the TERENO prealpine observatory: a hydrometeorological data analysis

The temporal multiscale variability of the surface heat fluxes is assessed by the analysis of the turbulent heat and moisture fluxes using the eddy covariance (EC) technique at the TERrestrial ENvironmental Observatories (TERENO) prealpine region. The fast and slow response variables from three EC sites located at Fendt, Rottenbuch, and Graswang are gathered for the period of 2013 to 2014. Here, the main goals are to characterize the multiscale variations and drivers of the turbulent fluxes, as well as to quantify the energy balance closure (EBC) and analyze the possible reasons for the lack of EBC at the EC sites. To achieve these goals, we conducted a principal component analysis (PCA) and a climatological turbulent flux footprint analysis. The results show significant differences in the mean diurnal variations of the sensible heat (H) and latent heat (LE) fluxes, because of variations in the solar radiation, precipitation patterns, soil moisture, and the vegetation fraction throughout the year. LE was the main consumer of net radiation. Based on the first principal component (PC1), the radiation and temperature components with a total mean contribution of 29.5 and 41.3%, respectively, were found to be the main drivers of the turbulent fluxes at the study EC sites. A general lack of EBC is observed, where the energy imbalance values amount 35, 44, and 35% at the Fendt, Rottenbuch, and Graswang sites, respectively. An average energy balance ratio (EBR) of 0.65 is obtained in the region. The best closure occurred in the afternoon peaking shortly before sunset with a different pattern and intensity between the study sites. The size and shape of the annual mean half-hourly turbulent flux footprint climatology was analyzed. On average, 80% of the flux footprint was emitted from a radius of approximately 250 m around the EC stations. Moreover, the overall shape of the flux footprints was in good agreement with the prevailing wind direction for all three TERENO EC sites.

Experimental evaluation of flux footprint models

In this study we experimentally evaluate analytical flux footprint models, as well as models based on Lagrangian stochastic particle dispersion. For this purpose, we conducted tracer experiments at a grassland site in southern Germany. An artificial tracer was released continuously over a number of flux-averaging intervals from a surface source. The flux contributions from the tracer source were measured by eddy covariance and compared to those predicted by footprint models. Furthermore, an additional eddy covariance measurement tower was used to evaluate the along-wind distribution of footprint models, as well as to analyze to what extent a forest edge upwind of the measurement tower affects model performance. Additionally, we quantify footprint model uncertainty resulting from the random error of input parameters.Our measurements show that all evaluated models match observations roughly, but tend to underestimate the value of the footprint maximum, and overestimate its distance. The analysis of stability dependence of model performances indicates that one model, based on simulation outputs of a Lagrangian stochastic model, clearly underestimates observations for near neutral to stable conditions, while no clear stability dependence could be identified for the performance of the other models.As expected, model performance is sensitive to an abrupt change in surface roughness and sensible heat flux at a forest edge in the near upwind fetch of the measurement tower. Using the local apparent roughness length (derived from measured wind speed and friction velocity) only slightly or negligibly improved model performance compared to the use of a constant local roughness length (determined from local surface characteristics). Thus we confirm experimentally that footprint estimates and related data quality assessments should be handled with care at sites with inhomogeneities in surface roughness.

Modeling the Footprint and Equivalent Radiance Transfer Path Length for Tower-Based Hemispherical Observations of Chlorophyll Fluorescence.

The measurement of solar-induced chlorophyll fluorescence (SIF) is a new tool for estimating gross primary production (GPP). Continuous tower-based spectral observations together with flux measurements are an efficient way of linking the SIF to the GPP. Compared to conical observations, hemispherical observations made with cosine-corrected foreoptic have a much larger field of view and can better match the footprint of the tower-based flux measurements. However, estimating the equivalent radiation transfer path length (ERTPL) for hemispherical observations is more complex than for conical observations and this is a key problem that needs to be addressed before accurate retrieval of SIF can be made. In this paper, we first modeled the footprint of hemispherical spectral measurements and found that, under convective conditions with light winds, 90% of the total radiation came from an FOV of width 72°, which in turn covered 75.68% of the source area of the flux measurements. In contrast, conical spectral observations covered only 1.93% of the flux footprint. Secondly, using theoretical considerations, we modeled the ERTPL of the hemispherical spectral observations made with cosine-corrected foreoptic and found that the ERTPL was approximately equal to twice the sensor height above the canopy. Finally, the modeled ERTPL was evaluated using a simulated dataset. The ERTPL calculated using the simulated data was about 1.89 times the sensor’s height above the target surface, which was quite close to the results for the modeled ERTPL. Furthermore, the SIF retrieved from atmospherically corrected spectra using the modeled ERTPL fitted well with the reference values, giving a relative root mean square error of 18.22%. These results show that the modeled ERTPL was reasonable and that this method is applicable to tower-based hemispherical observations of SIF.

Flux footprints for a tall tower in a land–water mosaic area: A case study of the area around the Risø tower

The understanding of scalar fluxes observed in the lower atmosphere is a challenging task, when the underlying surface is non-uniform. In this paper, we apply a micro-scale flow model with a two-equation closure scheme to analyse the influence of the surface heterogeneity on a flux measurement in the area surrounding the 122-m tower at Risø (Denmark), which is a mosaic of water, agricultural areas and forests. These heterogeneities are clearly reflected in the tower-based observations of the turbulence statistics from a profile of six sonic anemometers and are also reproduced by the flow model. Using the two-dimensional mode of the model, in combination with the footprint estimator, we calculate the scalar flux footprints for the 122m eddy-covariance location and compare these results to analytical footprint estimators, which are only valid for homogeneous terrain, but are commonly applied also for heterogeneous terrain. Whereas the results by the analytical footprint estimator indicate smooth source areas regardless of the surface heterogeneities, the footprint estimator based on the micro-scale model indicates source hotspots, which have a stronger weight in the footprint. The hotspots coincide with areas, where the mean vertical velocity is positive. The positive mean vertical velocity is, in turn, related to topography and forest edge effects on the flow. Relative to the surface roughness estimated from a sonic anemometer, a higher value of the surface roughness was needed for the analytical footprint estimator in order to coarsely match the flow model-based footprint result. Although neither footprint model can be directly verified, the difference in the results underlines that the analytical model should be used with caution in heterogeneous areas. We also estimate the effect of the surface flux source-strength on the observed CO2 flux. This step demonstrates a novel way of evaluating the CO2 exchange with the surface, which is useful for constraining models of the surface source or sink.

Using High Resolution LiDAR Data and a Flux Footprint Parameterization to Scale Evapotranspiration Estimates to Lower Pixel Resolutions

ABSTRACTOver the last several decades the hydrologically sensitive Boreal Plains ecoregion of Western Canada has experienced significant warming and drying. To better predict implications of land cover changes on evapotranspiration (ET) and future water resources in this region, high resolution light detection and ranging and energy balance data are used here to spatially parameterize the Penman-Monteith ET model. Within a 5 km × 5 km area of peatland ecosystems, riparian boundaries, and upland mixedwood forests, the influence of land cover heterogeneity on the accuracy of modeled ET is examined at pixel sizes of 1, 10, 25, 250, 500, and 1,000 m, representing resolutions common to popular satellite products (SPOT, Landsat, and MODIS). Modeled ET was compared with tower-based eddy covariance measurements using a weighted flux footprint model. Errors range from 10% to 36% of measured fluxes and results indicate that sensors with small pixel sizes (1 m) offer significantly better accuracy in large heterogeneous flux footprints, while a wider range of pixel sizes (<25 m) can be suitably applied to smaller homogeneous footprints. Mid (250 m) and coarse (>500 m) pixel sizes offered significantly less accuracy, although changes in pixel size within this range offered comparable results.

Direct whole-farm greenhouse gas flux measurements for a beef cattle operation

Landscape-scale measurements of greenhouse gas exchange from whole farms can bracket the magnitude of fluxes, identify sources and sinks, and provide data for model development and validation. Greenhouse gas fluxes were measured for an annual cycle on a 123-ha beef-cattle farm in southwestern Manitoba, Canada. Carbon dioxide and methane fluxes were measured from a central eddy covariance flux tower. These measurements were supplemented by a secondary flux tower, and by static chambers that measured carbon dioxide, methane and nitrous oxide fluxes. The farm had 104 backgrounding steers and an additional 160 cow-calf pairs occupied the farm for part of the period. Cattle occupied a winter bale-grazing field, a confined feeding paddock, a summer pasture, and a cereal-crop swath-grazing field in sequence. Cattle within the flux footprint exhibited large respiration and methane fluxes, and the cattle respiration was separated from the land CO2 exchange. The largest fluxes of nitrous oxide from cattle excreta (urine, manure) were emitted from the confined feeding paddock and from the location of the winter-feed bales, but only the confined feeding paddock had a net emission of methane from excreta. Despite challenges with cattle movements and scaling in space and time, a greenhouse gas budget was estimated: over the annual cycle, cattle respiration dominated the budget with an emission of 20t CO2 equivalent ha−1y−1; CO2 from the plant/soil system was a net emission of 10t CO2 equivalent ha−1 y−1; enteric methane was 11t CO2 equivalent ha−1y−1; methane from soil/excreta was 0.06t CO2 equivalent ha−1y−1; and nitrous oxide from soil/excreta/fertilizer was 4t CO2 equivalent ha−1y−1. The farm was a net greenhouse gas source of 46t CO2 equivalent ha−1 y−1 and the plant/soil system was a contributing source in this year, partly because of respiration of imported feed.

Evaluating an eddy covariance technique to estimate point-source emissions and its potential application to grazing cattle

Measurement of gas emissions from grazing cattle presents a challenging application of the eddy-covariance (EC) technique. A cattle herd represents point sources on the landscape, violating the assumptions of spatial homogeneity made in typical EC applications. A proper evaluation of EC fluxes in this case requires an analysis based on the overlap between the EC flux footprint and animal positions. A controlled gas release study was conducted to evaluate the potential of a Lagrangian stochastic (LS) dispersion model to interpret EC fluxes and estimate emissions from point sources. Methane (CH4) gas was released from eight fixed points within a confined area (representing animals in a paddock) while two EC systems monitored CH4 fluxes at two distances downwind of the source area (a near and far tower). Overall accuracy was greater at the far tower location with estimates within 3% of the actual emission rate. The near tower overestimated total emissions by 16%. Deviations from the true emission rate were greatest for night-time and morning periods and least for mid-afternoon to early evening periods when neutral stability and favorable wind directions prevailed. We also investigated the effect of treating the simulated paddock as a homogeneous area emission source. The near tower emission estimate improved with the area source approach (9% overestimation). The far tower suffered a loss of accuracy (17% underestimation), but this was substantially improved (7% underestimation) by reducing the source area to the minimum required to contain the eight release points. Our study suggests that EC can be used to measure animal emissions from grazing cattle on pasture with a level of accuracy similar to other micrometeorological approaches.