A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements

Mauder, Matthias; Cuntz, Matthias; Drüe, Clemens; Graf, Alexander; Rebmann, Corinna; Schmid, Hans Peter; Schmidt, Marius; Steinbrecher, R.

doi:10.1016/j.agrformet.2012.09.006

Cited by 455 publications

(447 citation statements)

References 68 publications

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“…As shown in Figure 1, a dirt road and several scientific instruments were located within the UAS imaging area. The turbulent energy fluxes and corresponding flux footprints were computed in 30 min intervals (Mauder et al 2013; Mauder and Foken 2015) and were combined with ancillary meteorological data listed in Table 1. The observed energy fluxes were adjusted in order to reach EB closure using a method that preserves the observed BR (Twine et al 2000).…”

Section: Methodsmentioning

confidence: 99%

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Brenner

Zeeman

Bernhardt

et al. 2018

International Journal of Remote Sensing

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Spatially distributed high-resolution data of land surface temperature (LST) and evapotranspiration (ET) are important information for crop water management and other applications in the agricultural sector. While satellite data can provide LST high-resolution data of 100 m, the current development of unmanned aerial systems (UAS) and affordable low-weight thermal cameras allows LST and subsequent ET to be derived at resolutions down to centimetre scale.In this study, UAS-based images in the thermal infrared (TIR) and visible spectral range were collected over a managed temperate grassland in July 2016 at the Terrestrial Environmental Observatories Networks TERENO preAlpine observatory site at Fendt, Germany. The UAS set-up included a lightweight thermal camera (Optris Pi Lightweight) and a regular digital camera (Sony α 6000) that allowed for the acquisition of thermal and optical images with a ground resolution of 5 cm and 1 cm, respectively. Three TIR-based ET models of different complexity were applied and the resulting ET estimates were compared to the Eddy covariance (EC) observations of turbulent energy fluxes and also to the evaporative fraction. While the Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature (DATTUTDUT) model and the Triangle Method belong to the group of simpler contextual models, the Two-Source Energy Balance (TSEB) model incorporates a more physically based formulation of the surface energy balance. In addition to the comparison of UAS-based estimates of latent heat fluxes to EC observations, the effect of the spatial resolution of the model imagery input on the modelled results was analysed by running the models with imagery from the native resolution of the acquired images to resolutions that were aggregated up to 30 m.The results show that both contextual models are sensitive to the input image resolution and that the agreement with the EC observations improves with increasing image resolution. The TSEB model assumes that LST pixels represent a mixed signal of the soil and canopy components, thus an image resolution coarse enough to ensure this assumption should be chosen. However, with the exception of the native image resolution of 5 cm, we found no effect of image resolution on the spatially weighted mean TSEB estimates.For the studied grassland, the comparison of model estimates with EC observations indicates that all three models are able to reproduce observed energy fluxes with comparable accuracy with mean absolute errors of ET between 20 and 40 W m−2. The TSEB model showed larger deviations from the reference observations under cloudy conditions with rapid fluctuations of LST within the 30 min averaging period for EC. The two contextual models yielded similar results for most of the flights. The good performance of the DATTUTDUT model, which had the lowest input requirements of the three models, is especially promising in view of the application of UAS for routine near-real-time ET monitoring.

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Section: Methodsmentioning

confidence: 99%

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Brenner

Zeeman

Bernhardt

et al. 2018

International Journal of Remote Sensing

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“…Unlike in the original equation given in Mauder et al (2013), the contribution of instrumental noise in w was neglected since the focus was on comparing the gas analysers. This method is sensitive only to random noise, i.e.…”

Section: Random Errors In the Fluxmentioning

confidence: 99%

“…Contribution of this noise to uncertainty in the covariance is estimated using error propagation (Eq. 7 in Mauder et al, 2013):…”

Section: Random Errors In the Fluxmentioning

confidence: 99%

“…In this method, the error variance of the covariance is estimated based on cross-covariances and auto-covariances and thus the uncertainty estimate contains contributions originating from sampling uncertainty and instrumental noise. Lenschow et al (2000) introduced a method to estimate instrumental noise of LiDAR measurements, and later Mauder et al (2013) applied it to eddy covariance data. Due to the fact that instrumental noise is uncorrelated with the turbulent signal, it can be assumed that the noise contributes to the auto-covariance only at lag zero.…”

Section: Random Errors In the Fluxmentioning

confidence: 99%

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Evaluating the performance of commonly used gas analysers for methane eddy covariance flux measurements: the InGOS inter-comparison field experiment

et al. 2014

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Abstract. The performance of eight fast-response methane (CH 4 ) gas analysers suitable for eddy covariance flux measurements were tested at a grassland site near the Cabauw tall tower (Netherlands) during June 2012. The instruments were positioned close to each other in order to minimise the effect of varying turbulent conditions. The moderate CH 4 fluxes observed at the location, of the order of 25 nmol m −2 s −1 , provided a suitable signal for testing the instruments' performance.Generally, all analysers tested were able to quantify the concentration fluctuations at the frequency range relevant for turbulent exchange and were able to deliver high-quality data. The tested cavity ringdown spectrometer (CRDS) instruments from Picarro, models G2311-f and G1301-f, were superior to other CH 4 analysers with respect to instrumental noise. As an open-path instrument susceptible to the effects of rain, the LI-COR LI-7700 achieved lower data coverage and also required larger density corrections; however, the system is especially useful for remote sites that are restricted in power availability. In this study the open-path LI-7700 results were compromised due to a data acquisition problem in our data-logging setup. Some of the older closed-path analysers tested do not measure H 2 O concentrations alongside CH 4 (i.e. FMA1 and DLT-100 by Los Gatos Research) and this complicates data processing since the required corrections for dilution and spectroscopic interactions have to be based on external information. To overcome this issue, we used H 2 O mole fractions measured by other gas analysers, adjusted them with different methods and then applied them to correct the CH 4 fluxes. Following this procedure we estimated a bias of the order of 0.1 g (CH 4 ) m −2 (8 % of the measured mean flux) in the processed and corrected CH 4 fluxes on a monthly scale due to missing H 2 O concentration measurements. Finally, cumulative CH 4 fluxes over 14 days from three closed-path gas analysers, G2311-f (Picarro Inc.), FGGA (Los Gatos Research) and FMA2 (Los Gatos Research), which were measuring H 2 O concentrations in addition to CH 4 , agreed within 3 % (355-367 mg (CH 4 ) m −2 ) and were not clearly different from each other, whereas the other instruments derived total fluxes which showed small but distinct differences (±10 %, 330-399 mg (CH 4 ) m −2 ).Published by Copernicus Publications on behalf of the European Geosciences Union. 3164O. Peltola et al.: Evaluating the performance of gas analysers for CH 4 EC flux measurements

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“…Here L is the Obukhov length, k is the von Karman constant, g is the acceleration due to gravity, w θ s is the vertical kinematic potential temperature flux at the surface, θ V is the mean virtual potential temperature and u * is the friction velocity. L was determined from data obtained from the energy balance stations using TK3 software (Mauder et al 2013). The mounting of the instruments was 4 m above the ground, therefore z = 4 m was used.…”

Section: Data Handlingmentioning

confidence: 99%

Turbulent Structures and Coherence in the Atmospheric Surface Layer

Träumner

Damian

Stawiarski

et al. 2014

Boundary-Layer Meteorol

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Organized structures in turbulent flow fields are a well-known and still fascinating phenomenon. Although these so-called coherent structures are obvious from visual inspection, quantitative assessment is a challenge and many aspects e.g., formation mechanisms and contribution to turbulent fluxes, are discussed controversially. During the "High Definition Clouds and Precipitation for Advancing Climate Prediction" Observational Prototype Experiment (HOPE) from April to May 2013, an advanced dual Doppler lidar technique was used to image the horizontal wind field near the surface for approximately 300 h. A visual inspection method, as well as a two-dimensional integral length scale analysis, were performed to characterize the observations qualitatively and quantitatively. During situations with forcing due to shear, the wind fields showed characteristic patterns in the form of clearly bordered, elongated areas of enhanced or reduced wind speed, which can be associated with near-surface streaks. During calm situations with strong buoyancy forcing, open cell patterns in the horizontal divergence field were observed. The measurement technique used enables the calculation of integral length scales of both horizontal wind components in the streamwise and cross-stream directions. The individual length scales varied considerably during the observation period but were on average shorter during situations with z/L < 0 compared to strongly stable situations. During unstable situations, which were dominated by wind fields with structures, the streamwise length scales increased with increasing wind speed, whereas the cross-stream length scales decreased. Consequently, the anisotropy increased from 1 for calm situations to values of 2-3 for wind speeds of 8-10 m s −1 . During neutral to stable situations, the eddies were on average quite isotropic in the horizontal plane.

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A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements

Cited by 455 publications

References 68 publications

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Evaluating the performance of commonly used gas analysers for methane eddy covariance flux measurements: the InGOS inter-comparison field experiment

Turbulent Structures and Coherence in the Atmospheric Surface Layer

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