Multi-Year Eddy-Covariance Measurements at a Pre-Alpine Humid Grassland Site: Dataset Overview, Drought Responses, and Effects of Land Management

2021 ◽  
Author(s):  
Dominik Michel ◽  
Sonia I. Seneviratne
Keyword(s):  
Eddy Covariance ◽  
Land Management ◽  
Eddy Covariance Measurements ◽  
Grassland Site

scholarly journals Preserving the variance in imputed eddy-covariance measurements: Alternative methods for defensible gap filling

2017 ◽  
Vol 232 ◽  
pp. 635-649 ◽  
Author(s):  
Sujit Kunwor ◽  
Gregory Starr ◽  
Henry W. Loescher ◽  
Christina L. Staudhammer
Keyword(s):  
Eddy Covariance ◽  
Alternative Methods ◽  
Gap Filling ◽  
Eddy Covariance Measurements

Application of an alternative method to derive reliable estimates of nighttime respiration from eddy covariance measurements in moderately complex topography

2008 ◽  
Vol 148 (6-7) ◽  
pp. 1174-1180 ◽  
Author(s):  
Eva van Gorsel ◽  
Ray Leuning ◽  
Helen A. Cleugh ◽  
Heather Keith ◽  
Miko U.F. Kirschbaum ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Complex Topography ◽  
Alternative Method ◽  
Eddy Covariance Measurements

Multi-year eddy covariance measurements of net ecosystem exchange in tropical dry deciduous forest of India

2021 ◽  
Vol 301-302 ◽  
pp. 108351
Author(s):  
Suraj Reddy Rodda ◽  
Kiran Chand Thumaty ◽  
MSS Praveen ◽  
Chandra Shekhar Jha ◽  
Vinay Kumar Dadhwal
Keyword(s):  
Eddy Covariance ◽  
Deciduous Forest ◽  
Net Ecosystem Exchange ◽  
Dry Deciduous Forest ◽  
Eddy Covariance Measurements

scholarly journals Estimating evaporation with thermal UAV data and two-source energy balance models

2016 ◽  
Vol 20 (2) ◽  
pp. 697-713 ◽  
Author(s):  
H. Hoffmann ◽  
H. Nieto ◽  
R. Jensen ◽  
R. Guzinski ◽  
P. Zarco-Tejada ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
High Resolution ◽  
Eddy Covariance ◽  
Land Surface ◽  
Weather Conditions ◽  
Heat Fluxes ◽  
Thermal Camera ◽  
Model Input ◽  
Eddy Covariance Measurements

Abstract. Estimating evaporation is important when managing water resources and cultivating crops. Evaporation can be estimated using land surface heat flux models and remotely sensed land surface temperatures (LST), which have recently become obtainable in very high resolution using lightweight thermal cameras and Unmanned Aerial Vehicles (UAVs). In this study a thermal camera was mounted on a UAV and applied into the field of heat fluxes and hydrology by concatenating thermal images into mosaics of LST and using these as input for the two-source energy balance (TSEB) modelling scheme. Thermal images are obtained with a fixed-wing UAV overflying a barley field in western Denmark during the growing season of 2014 and a spatial resolution of 0.20 m is obtained in final LST mosaics. Two models are used: the original TSEB model (TSEB-PT) and a dual-temperature-difference (DTD) model. In contrast to the TSEB-PT model, the DTD model accounts for the bias that is likely present in remotely sensed LST. TSEB-PT and DTD have already been well tested, however only during sunny weather conditions and with satellite images serving as thermal input. The aim of this study is to assess whether a lightweight thermal camera mounted on a UAV is able to provide data of sufficient quality to constitute as model input and thus attain accurate and high spatial and temporal resolution surface energy heat fluxes, with special focus on latent heat flux (evaporation). Furthermore, this study evaluates the performance of the TSEB scheme during cloudy and overcast weather conditions, which is feasible due to the low data retrieval altitude (due to low UAV flying altitude) compared to satellite thermal data that are only available during clear-sky conditions. TSEB-PT and DTD fluxes are compared and validated against eddy covariance measurements and the comparison shows that both TSEB-PT and DTD simulations are in good agreement with eddy covariance measurements, with DTD obtaining the best results. The DTD model provides results comparable to studies estimating evaporation with similar experimental setups, but with LST retrieved from satellites instead of a UAV. Further, systematic irrigation patterns on the barley field provide confidence in the veracity of the spatially distributed evaporation revealed by model output maps. Lastly, this study outlines and discusses the thermal UAV image processing that results in mosaics suited for model input. This study shows that the UAV platform and the lightweight thermal camera provide high spatial and temporal resolution data valid for model input and for other potential applications requiring high-resolution and consistent LST.

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 Near-zero methane emission from an abandoned boreal peatland pasture based on eddy covariance measurements

PLoS ONE ◽  
2017 ◽  
Vol 12 (12) ◽  
pp. e0189692 ◽  
Author(s):  
Mei Wang ◽  
Jianghua Wu ◽  
Junwei Luan ◽  
Peter Lafleur ◽  
Huai Chen ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Methane Emission ◽  
Eddy Covariance Measurements

Mapping the aerodynamic roughness of the Greenland ice sheet surface using ICESat-2

2021 ◽  
Author(s):  
Maurice van Tiggelen ◽  
Paul C.J.P. Smeets ◽  
Carleen H. Reijmer ◽  
Bert Wouters ◽  
Jakob F. Steiner ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Elevation ◽  
Spatiotemporal Variability ◽  
Atmospheric Models ◽  
Laser Altimeter ◽  
Eddy Covariance Measurements ◽  
Aerodynamic Roughness

<p>The roughness of a natural surface is an important parameter in atmospheric models, as it determines the intensity of turbulent transfer between the atmosphere and the surface. Unfortunately, this parameter is often poorly known, especially in remote areas where neither high-resolution elevation models nor eddy-covariance measurements are available.</p><p>In this study, we take advantage of the measurements of the ICESat-2 satellite laser altimeter. We use the geolocated photons product (ATL03) to retrieve a 1-m resolution surface elevation product over the K-transect (West Greenland ice sheet). In combination with a bulk drag partitioning model, the retrieved surface elevation is used to estimate the aerodynamic roughness length (z<sub>0m</sub>) of the surface.</p><p>We demonstrate the high precision of the retrieved ICESat-2 elevation using co-located UAV photogrammetry, and then evaluate the modelled aerodynamic roughness against multiple in situ eddy-covariance observations. The results point out the importance to use a bulk drag model over a more empirical formulation.</p><p>The currently available ATL03 geolocated photons are used to map the aerodynamic roughness along the K-transect (2018-2020). We find a considerable spatiotemporal variability in z<sub>0m</sub>, ranging between 10<sup>−4</sup> m for a smooth snow surface to more than 10<sup>−1</sup> m for rough crevassed areas, which confirms the need to incorporate a variable aerodynamic roughness in atmospheric models over ice sheets.</p>

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