Characterizing spatial representativeness of flux tower eddy-covariance measurements across the Canadian Carbon Program Network using remote sensing and footprint analysis

2012 ◽  
Vol 124 ◽  
pp. 742-755 ◽  
Author(s):  
Baozhang Chen ◽  
Nicholas C. Coops ◽  
Dongjie Fu ◽  
Hank A. Margolis ◽  
Brian D. Amiro ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Eddy Covariance ◽  
Flux Tower ◽  
Footprint Analysis ◽  
Eddy Covariance Measurements

scholarly journals Observing Actual Evapotranspiration from Flux Tower Eddy Covariance Measurements within a Hilly Watershed: Case Study of the Kamech Site, Cap Bon Peninsula, Tunisia

Atmosphere ◽  
2018 ◽  
Vol 9 (2) ◽  
pp. 68 ◽  
Author(s):  
Rim Zitouna-Chebbi ◽  
Laurent Prévot ◽  
Amal Chakhar ◽  
Manel Marniche-Ben Abdallah ◽  
Frederic Jacob
Keyword(s):  
Eddy Covariance ◽  
Actual Evapotranspiration ◽  
Flux Tower ◽  
Eddy Covariance Measurements ◽  
Hilly Watershed

scholarly journals Quantifying the carbon uptake by vegetation for Europe on a 1 km<sup>2</sup> resolution using a remote sensing driven vegetation model

2013 ◽  
Vol 6 (5) ◽  
pp. 1623-1640 ◽  
Author(s):  
K. Wißkirchen ◽  
M. Tum ◽  
K. P. Günther ◽  
M. Niklaus ◽  
C. Eisfelder ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Land Cover ◽  
Eddy Covariance ◽  
Remote Sensing Data ◽  
Total Carbon ◽  
Carbon Uptake ◽  
Area Index ◽  
Forest Sites ◽  
Eddy Covariance Measurements

Abstract. In this study we compare monthly gross primary productivity (GPP) time series (2000–2007), computed for Europe with the Biosphere Energy Transfer Hydrology (BETHY/DLR) model with monthly data from the eddy covariance measurements network FLUXNET. BETHY/DLR with a spatial resolution of 1 km2 is designed for regional and continental applications (here Europe) and operated at the German Aerospace Center (DLR). It was adapted from the BETHY scheme to be driven by remote sensing data (leaf area index (LAI) and land cover information) and meteorology. Time series of LAI obtained from the CYCLOPES database are used to control the phenology of vegetation. Meteorological time series from the European Centre for Medium-Range Weather Forecasts (ECMWF) are used as driver. These comprise daily information on temperature, precipitation, wind speed and radiation. Additionally, static maps such as land cover, elevation, and soil type are used. To validate our model results we used eddy covariance measurements from the FLUXNET network of 74 towers across Europe. For forest sites we found that our model predicts between 20 and 40% higher annual GPP sums. In contrast, for cropland sites BETHY/DLR results show about 18% less GPP than eddy covariance measurements. For grassland sites, between 10% more and 16% less GPP was calculated with BETHY/DLR. A mean total carbon uptake of 2.5 PgC a−1 (±0.17 PgC a−1) was found for Europe. In addition, this study reports on risks that arise from the comparison of modelled data to FLUXNET measurements and their interpretation width. Furthermore we investigate reasons for uncertainties in model results and focus here on Vmax values, and finally embed our results into a broader context of model validation studies published during the last years in order to evaluate differences or similarities in analysed error sources.

Assessing eddy-covariance flux tower location bias across the Fluxnet-Canada Research Network based on remote sensing and footprint modelling

2011 ◽  
Vol 151 (1) ◽  
pp. 87-100 ◽  
Author(s):  
Baozhang Chen ◽  
Nicholas C. Coops ◽  
Dongjie Fu ◽  
Hank A. Margolis ◽  
Brian D. Amiro ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Eddy Covariance ◽  
Research Network ◽  
Flux Tower

scholarly journals The Effect of Algal Blooms on Carbon Emissions in Western Lake Erie: An Integration of Remote Sensing and Eddy Covariance Measurements

2017 ◽  
Vol 9 (1) ◽  
pp. 44 ◽  
Author(s):  
Zutao Ouyang ◽  
Changliang Shao ◽  
Housen Chu ◽  
Richard Becker ◽  
Thomas Bridgeman ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Eddy Covariance ◽  
Carbon Emissions ◽  
Algal Blooms ◽  
Lake Erie ◽  
Western Lake ◽  
Eddy Covariance Measurements ◽  
Western Lake Erie

scholarly journals Quantifying the carbon uptake by vegetation for Europe on a 1 km<sup>2</sup> resolution using a remote sensing driven vegetation model

2013 ◽  
Vol 6 (2) ◽  
pp. 2457-2489 ◽  
Author(s):  
K. Wißkirchen ◽  
M. Tum ◽  
K. P. Günther ◽  
M. Niklaus ◽  
C. Eisfelder ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Eddy Covariance ◽  
Remote Sensing Data ◽  
Total Carbon ◽  
Carbon Uptake ◽  
Area Index ◽  
Forest Sites ◽  
Eddy Covariance Measurements ◽  
German Aerospace

Abstract. In this study we compare monthly gross primary productivity (GPP) time series (2000–2007), computed for Europe with the Biosphere Energy Transfer Hydrology (BETHY/DLR) model with monthly data from the eddy covariance measurements network FLUXNET. BETHY/DLR with a spatial resolution of 1 km2 is designed for regional and continental applications (here Europe) and operated at the German Aerospace Center (DLR). It was adapted from the BETHY scheme to be driven by remote sensing data and meteorology. Time series of Leaf Area Index (LAI) are used to control the development of vegetation. These are taken from the CYCLOPES database. Meteorological time series are used to regulate meteorological seasonality. These comprise daily information on temperature, precipitation, wind-speed and radiation. Additionally, static maps such as land cover, elevation, and soil type are used. To validate our model results we used eddy covariance measurements from the FLUXNET network of 74 towers across Europe. For forest sites we found that our model predicts between 20% and 40% higher annual GPP sums. In contrast, for cropland sites BETHY/DLR results show about 18% less GPP than eddy covariance measurements. For grassland sites, between 10% more and 16% less GPP was calculated with BETHY/DLR. A mean total carbon uptake of 2.5 Pg C yr-1 (±0.17 Pg) was found for Europe. In addition, this study states on risks that arise from the comparison of modeled data to FLUXNET measurements and their interpretation width.

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