Quality control of CarboEurope flux data – Part 1: Coupling footprint analyses with flux data quality assessment to evaluate sites in forest ecosystems

Göckede, Mathias; Foken, Thomas; Aubinet, Marc; Aurela, Mika; Banza, J.; Bernhofer, Christian; Bonnefond, Jean-Marc; Brunet, Yves; Carrara, Arnaud; Clement, Robert; Dellwik, Ebba; Elbers, J.A.; Eugster, Werner; Fuhrer, Jürg; Granier, André; Grünwald, Thomas; Heinesch, Bernard; Janssens, Ivan A.; Knohl, Alexander; Koeble, Renate; Laurila, Tuomas; Longdoz, Bernard; Manca, Giovanni; Marek, Michal V.; Markkanen, Tiina; Mateus, João; Matteucci, Giorgio; Mauder, Matthias; Migliavacca, Mirco; Minerbi, Stefano; Moncrieff, John; Montagnani, Leonardo; Moors, E.J.; Ourcival, Jean‐Marc; Papale, Dario; Pereira, J. S.; Pilegaard, Kim; Pita, Gabriel; Rambal, Serge; Rebmann, Corinna; Rodrigues, Abel; Rotenberg, Eyal; Sanz, M. J.; Sedlák, Pavel; Seufert, G.; Siebicke, Lukas; Soussana, Jean‐François; Valentini, Riccardo; Vesala, Timo; Verbeeck, Hans; Yakir, Dan

doi:10.5194/bg-5-433-2008

Cited by 210 publications

(148 citation statements)

References 66 publications

(68 reference statements)

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“…For wind sectors parallel to the shoreline, 95 % of the residual mean vertical wind velocity stays within ±0.12 ms −1 . These values stay within acceptable limits, compared to a multi-site quality analysis by Göckede et al (2008).…”

Section: Coordinate Rotation and Footprint Analysismentioning

confidence: 80%

“…The footprint analysis includes not only the calculation of the footprint, but also the spatial distribution of flux quality according to Göckede et al (2008), which enables the user to identify spatial patterns such as obstacles or heterogeneities contributing to the quality of the measured fluxes. In our study no such patterns could be identified for either station.…”

Section: Coordinate Rotation and Footprint Analysismentioning

confidence: 99%

“…The footprint analysis was conducted following Göckede et al (2004Göckede et al ( , 2008. The approach is based on a Lagrangian stochastic forward model providing two dimensional contributions of source areas (Rannik et al 2000).…”

Section: Coordinate Rotation and Footprint Analysismentioning

confidence: 99%

See 2 more Smart Citations

Turbulent flux observations and modelling over a shallow lake and a wet grassland in the Nam Co basin, Tibetan Plateau

Biermann

Babel

et al. 2013

Theor Appl Climatol

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The Tibetan Plateau plays an important role in the global water cycle and is strongly influenced by climate change. While energy and matter fluxes have been more intensely studied over land surfaces, a large proportion of lakes have either been neglected or parameterised with simple bulk approaches. Therefore, turbulent fluxes were measured over wet grassland and a shallow lake with a single eddy-covariance complex at the shoreline in the Nam Co basin in summer 2009. Footprint analysis was used to split observations according to the underlying surface, and two sophisticated surface models were utilised to derive gap-free time series. Results were then compared with observations and simulations from a nearby eddy-covariance station over dry grassland, yielding pronounced differences. Observations and footprint integrated simulations compared well, even for situations with flux contributions including grassland and lake. The accessibility problem for EC measurements on lakes can be overcome by combining standard meteorological measurements at the shoreline with model simulations, only requiring representative estimates of lake surface temperature.

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Section: Coordinate Rotation and Footprint Analysismentioning

confidence: 80%

Section: Coordinate Rotation and Footprint Analysismentioning

confidence: 99%

See 1 more Smart Citation

Turbulent flux observations and modelling over a shallow lake and a wet grassland in the Nam Co basin, Tibetan Plateau

Biermann

Babel

et al. 2013

Theor Appl Climatol

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show abstract

“…Data-quality selection criteria were applied in this study in order to examine time series of fluxes and generate a high-quality database [24]. The internal boundary layer estimation and footprint analysis were performed so as to compute the contribution from the target surface [25,26]. In the rice field, the fetch ranged from 37 m (northwest) to 60 m (northeast), generating the internal boundary layer height ranging from 3.0 m to 3.9 m and 68% to 82% of the flux contributed by the rice field.…”

Section: Research Sites and Field Campaignsmentioning

confidence: 99%

Parameterization of Evapotranspiration Estimation for Two Typical East Asian Crops

Zhao

Lüers

2017

Atmosphere

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Estimation of evapotranspiration plays an important role in understanding the water cycle on the earth, especially the water budget in agricultural ecosystems. The parameterization approach of the Penman-Monteith-Katerji-Perrier (PM-KP) model, accounting for the influence of meteorological variables and aerodynamic resistance on surface resistance, was proposed in the literature, but it has not been applied to Asian croplands, and its error and sensitivity have not been reported yet. In this study, the estimation of evapotranspiration on half-hourly scale was carried out for two typical East Asian cropland research sites, and evaluated by using eddy-covariance measurements corrected with the energy-balance-closure concept. Sensitivity coefficients as well as systematic bias and random errors of the PM-KP approach were used to evaluate the model performance. Different distributions of the calibration coefficients between different crops were reported for the first time, indicating that the calibration of this model was more stable for the rice field than for the potato field. The commonly-used parameterization approach suggested by the Food and Agriculture Organization (FAO) was used as reference and was site-specifically optimized. The results suggest that the PM-KP approach would be a better alternative than the PM-FAO approach for estimating evapotranspiration for the flooded rice field, and an acceptable alternative for rain-fed croplands when the soil is well watered and the air is humid during the summer monsoon.

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“…Flux footprint climatology is a practical method to illustrate the portion of the sampled landscape that contributes the most to EC vertical turbulent flux at a given point over long-term periods (Amiro, 1998;Kljun, 2010a;Cai et al, 2011;Aubinet et al, 2012;Zhang et al, 2012). This method is used to understand carbon budgets, assess the quality of EC data, and upscale the representativeness of a tower flux to regional or global scales (Rebmann et al, 2005;Göckede et al, 2008;Chen et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Flux footprint climatology estimated by three analytical models over a subtropical coniferous plantation in Southeast China

Zhang¹,

Wen

2015

J Meteorol Res

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Spatial heterogeneity poses a major challenge for the appropriate interpretation of eddy covariance data. The quantification of footprint climatology is fundamental to improving our understanding of carbon budgets, assessing the quality of eddy covariance data, and upscaling the representativeness of a tower flux to regional or global scales. In this study, we elucidated the seasonal variation of flux footprint climatologies and the major factors that influence them using the analytical FSAM (Flux Source Area Model), KM (Kormann and Meixner, 2001), and H (Hsieh et al., 2000) models based on eddy covariance measurements at two and three times the canopy height at the Qianyanzhou site of ChinaFLUX in 2003. The differences in footprints among the three models resulted from different underlying theories used to construct the models. A comparison demonstrated that atmospheric stability was the main factor leading to differences among the three models. In neutral and stable conditions, the KM and FSAM values agreed with each other, but they were both lower than the H values. In unstable conditions, the agreement among the three models for rough surfaces was better than that for smooth surfaces, and the models showed greater agreement for a low measurement height than for a high measurement height. The seasonal flux footprint climatologies were asymmetrically distributed around the tower and corresponded well to the prevailing wind direction, which was north-northwest in winter and south-southeast in summer. The average sizes of the 90% flux footprint climatologies were 0.36-0.74 and 1.5-3.2 km 2 at altitudes of two and three times the canopy height, respectively. The average sizes were ranked by season as follows: spring > summer > winter > autumn. The footprint climatology depended more on atmospheric stability on daily scale than on seasonal scale, and it increased with the increasing standard deviation of the lateral wind fluctuations.

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Quality control of CarboEurope flux data – Part 1: Coupling footprint analyses with flux data quality assessment to evaluate sites in forest ecosystems

Cited by 210 publications

References 66 publications

Turbulent flux observations and modelling over a shallow lake and a wet grassland in the Nam Co basin, Tibetan Plateau

Turbulent flux observations and modelling over a shallow lake and a wet grassland in the Nam Co basin, Tibetan Plateau

Parameterization of Evapotranspiration Estimation for Two Typical East Asian Crops

Flux footprint climatology estimated by three analytical models over a subtropical coniferous plantation in Southeast China

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