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Thomas Foken - One of the best experts on this subject based on the ideXlab platform.
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high quality Eddy Covariance co2 budgets under cold climate conditions
Journal of Geophysical Research, 2017Co-Authors: Fanny Kittler, Werner Eugster, Thomas Foken, Martin Heimann, Olaf Kolle, Mathias GockedeAbstract:This study aimed at quantifying potential negative effects of instrument heating to improve Eddy Covariance flux data quality in cold environments. Our overarching objective was to minimize heating-related bias in annual CO2 budgets from an Arctic permafrost system. We used continuous Eddy-Covariance measurements covering three full years within an Arctic permafrost ecosystem with parallel sonic anemometers operation with activated heating and without heating as well as parallel operation of open- and closed-path gas analyzers, the latter serving as a reference. Our results demonstrate that the sonic anemometer heating has a direct effect on temperature measurements while the turbulent wind field is not affected. As a consequence, fluxes of sensible heat are increased by an average 5 W m-2 with activated heating, while no direct effect on other scalar fluxes was observed. However, the biased measurements in sensible heat fluxes can have an indirect effect on the CO2 fluxes in case they are used as input for a density-flux WPL correction of an open-path gas analyzer. Evaluating the self-heating effect of the open-path gas analyzer by comparing CO2 flux measurements between open- and closed-path gas analyzers we found systematically higher CO2 uptake recorded with the open-path sensor, leading to a cumulative annual offset of 96 gC m-2, which was not only the result of the cold winter season but also due to substantial self-heating effects during summer. With an inclined sensor mounting, only a fraction of the self-heating correction for vertically mounted instruments is required.
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Extension of the Averaging Time in Eddy-Covariance Measurements and Its Effect on the Energy Balance Closure
Boundary-Layer Meteorology, 2014Co-Authors: Doojdao Charuchittipan, Matthias Mauder, Wolfgang Babel, Jens-peter Leps, Thomas FokenAbstract:The modified ogive analysis and the block ensemble average were employed to investigate the impact of the averaging time extension on the energy balance closure over six land-use types. The modified ogive analysis, which requires a steady-state condition, can extend the averaging time up to a few hours and suggests that an averaging time of 30 min is still overall sufficient for Eddy-Covariance measurements over low vegetation. The block ensemble average, which does not require a steady-state condition, can extend the averaging time to several days. However, it can improve the energy balance closure for some sites during specific periods, when secondary circulations exist in the vicinity of the sensor. These near-surface secondary circulations mainly transport sensible heat, and when near-ground warm air is transported upward, the sensible heat flux observed by the block ensemble average will increase at longer averaging times. These findings suggest an alternative energy balance correction for a ground-based Eddy-Covariance measurement, in which the attribution of the residual depends on the ratio of sensible heat flux to the buoyancy flux. The fraction of the residual attributed to the sensible heat flux by this energy balance correction is larger than in the energy balance correction that preserves the Bowen ratio.
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net ecosystem co 2 exchange measurements by the closed chamber method and the Eddy Covariance technique and their dependence on atmospheric conditions
Atmospheric Measurement Techniques, 2014Co-Authors: Michael Riederer, Andrei Serafimovich, Thomas FokenAbstract:Abstract. Carbon dioxide flux measurements in ecosystem sciences are mostly conducted by Eddy Covariance technique or the closed chamber method. But there is a lack of detailed comparisons that assess present differences and uncertainties. To determine underlying processes, a 10-day, side-by-side measurement of the net ecosystem exchange with both techniques was evaluated with regard to various atmospheric conditions during the diurnal cycle. It was found that, depending on the particular atmospheric condition, the chamber carbon dioxide flux was either (i) equal to the carbon dioxide flux measured by the reference method Eddy Covariance, by day with well-developed atmospheric turbulence; (ii) higher, in the afternoon in times of oasis effect; (iii) lower, predominantly at night while large coherent structure fluxes or high wind velocities prevailed; or (iv) showed less variation in the flux pattern, at night while stable stratification was present. At night – when respiration forms the net ecosystem exchange – lower chamber carbon dioxide fluxes were found. In the afternoon – when the ecosystem is still a net carbon sink – the carbon dioxide fluxes measured by the chamber prevailed. These two complementary aspects resulted in an overestimation of the ecosystem sink capacity by the chamber of 40% in this study.
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measurements of nitrogen oxides and ozone fluxes by Eddy Covariance at a meadow evidence for an internal leaf resistance to no2
Biogeosciences, 2013Co-Authors: Patrick Stella, Thomas Foken, Michael Kortner, Christof Ammann, Franz X Meixner, Ivonne TrebsAbstract:Nitrogen dioxide (NO 2 ) plays an important role in atmospheric pollution, in particular for tropospheric ozone production. However, the removal processes involved in NO 2 deposition to terrestrial ecosystems are still the subject of ongoing discussion. This study reports NO 2 flux measurements made over a meadow using the Eddy Covariance method. The measured NO 2 deposition fluxes during daytime were about a factor of two lower than a priori calculated fluxes using the Surfatm model without taking into account an internal (also called mesophyllic or sub-stomatal) resistance. Neither an underestimation of the measured NO 2 deposition flux due to chemical divergence or an in-canopy NO 2 source nor an underestimation of the resistances used to model the NO 2 deposition explained the large difference between measured and modelled NO 2 fluxes. Thus, only the existence of the internal resistance could account for this large discrepancy between model and measurements. The median internal resistance was estimated to be 300 s m −1 during daytime, but exhibited a large variability (100–800 s m −1 ). In comparison, the stomatal resistance was only around 100 s m −1 during daytime. Hence, the internal resistance accounted for 50–90% of the total leaf resistance to NO 2 . This study presents the first clear evidence and quantification of the internal resistance using the Eddy Covariance method; i.e. plant functioning was not affected by changes of microclimatological (turbulent) conditions that typically occur when using enclosure methods.
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Eddy Covariance flux measurements with a weight shift microlight aircraft
Atmospheric Measurement Techniques, 2012Co-Authors: Stefan Metzger, W Junkermann, Matthias Mauder, Frank Beyrich, Klaus Butterbachbahl, H P Schmid, Thomas FokenAbstract:Abstract. The objective of this study is to assess the feasibility and quality of Eddy-Covariance flux measurements from a weight-shift microlight aircraft (WSMA). Firstly, we investigate the precision of the wind measurement (σu,v ≤ 0.09 m s−1, σw = 0.04 m s−1), the lynchpin of flux calculations from aircraft. From here, the smallest resolvable changes in friction velocity (0.02 m s−1), and sensible- (5 W m−2) and latent (3 W m−2) heat flux are estimated. Secondly, a seven-day flight campaign was performed near Lindenberg (Germany). Here we compare measurements of wind, temperature, humidity and respective fluxes between a tall tower and the WSMA. The maximum likelihood functional relationship (MLFR) between tower and WSMA measurements considers the random error in the data, and shows very good agreement of the scalar averages. The MLFRs for standard deviations (SDs, 2–34%) and fluxes (17–21%) indicate higher estimates of the airborne measurements compared to the tower. Considering the 99.5% confidence intervals, the observed differences are not significant, with exception of the temperature SD. The comparison with a large-aperture scintillometer reveals lower sensible heat flux estimates at both tower (−40 to −25%) and WSMA (−25–0%). We relate the observed differences to (i) inconsistencies in the temperature and wind measurement at the tower and (ii) the measurement platforms' differing abilities to capture contributions from non-propagating eddies. These findings encourage the use of WSMA as a low cost and highly versatile flux measurement platform.
Mathias Gockede - One of the best experts on this subject based on the ideXlab platform.
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high quality Eddy Covariance co2 budgets under cold climate conditions
Journal of Geophysical Research, 2017Co-Authors: Fanny Kittler, Werner Eugster, Thomas Foken, Martin Heimann, Olaf Kolle, Mathias GockedeAbstract:This study aimed at quantifying potential negative effects of instrument heating to improve Eddy Covariance flux data quality in cold environments. Our overarching objective was to minimize heating-related bias in annual CO2 budgets from an Arctic permafrost system. We used continuous Eddy-Covariance measurements covering three full years within an Arctic permafrost ecosystem with parallel sonic anemometers operation with activated heating and without heating as well as parallel operation of open- and closed-path gas analyzers, the latter serving as a reference. Our results demonstrate that the sonic anemometer heating has a direct effect on temperature measurements while the turbulent wind field is not affected. As a consequence, fluxes of sensible heat are increased by an average 5 W m-2 with activated heating, while no direct effect on other scalar fluxes was observed. However, the biased measurements in sensible heat fluxes can have an indirect effect on the CO2 fluxes in case they are used as input for a density-flux WPL correction of an open-path gas analyzer. Evaluating the self-heating effect of the open-path gas analyzer by comparing CO2 flux measurements between open- and closed-path gas analyzers we found systematically higher CO2 uptake recorded with the open-path sensor, leading to a cumulative annual offset of 96 gC m-2, which was not only the result of the cold winter season but also due to substantial self-heating effects during summer. With an inclined sensor mounting, only a fraction of the self-heating correction for vertically mounted instruments is required.
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quality analysis applied on Eddy Covariance measurements at complex forest sites using footprint modelling
Theoretical and Applied Climatology, 2005Co-Authors: Corinna Rebmann, Christian Bernhofer, Thomas Foken, Mika Aurela, Marc Aubinet, Mathias Gockede, Paul Berbigier, Nina Buchmann, Arnaud Carrara, Alessandro CescattiAbstract:Measuring turbulent fluxes with the Eddy Covariance method has become a widely accepted and powerful tool for the determination of long term data sets for the exchange of momentum, sensible and latent heat, and trace gases such as CO2 between the atmosphere and the underlying surface. Several flux networks developed continuous measurements above complex terrain, e.g. AmeriFlux and EUROFLUX, with a strong focus on the net exchange of CO2 between the atmosphere and the underlying surface. Under many conditions basic assumptions for the Eddy Covariance method in its simplified form, such as stationarity of the flow, homogeneity of the surface and fully developed turbulence of the flow field, are not fulfilled. To deal with non-ideal conditions which are common at many FLUXNET sites, quality tests have been developed to check if these basic theoretical assumptions are valid.
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a combination of quality assessment tools for Eddy Covariance measurements with footprint modelling for the characterisation of complex sites
Agricultural and Forest Meteorology, 2004Co-Authors: Mathias Gockede, Corinna Rebmann, Thomas FokenAbstract:The adoption of the Eddy Covariance technique to estimate surface exchange is based on the assumption that certain meteorological conditions are valid. The most important of these are horizontal homogeneity, steady-state, and non-advective conditions. Since such conditions are often violated under complex terrain conditions, e.g. at flux monitoring sites over forests, this study aims to evaluate the influence of surface heterogeneity to permit a correct interpretation of the measurement results. Quality assessment tools for Eddy Covariance measurements have been combined with footprint modelling. This makes it possible to define the spatial context of the fluxes, and to include land use features of the surrounding terrain in the analysis. The quality of the flux data for different wind sectors and varying meteorological conditions is also determined, so that the most suitable situations for the collection of high-quality data sets can be identified. Additionally, the flux contribution of the different land use types present in the footprint area is calculated. The results are presented as two-dimensional graphs, which show the spatial distribution of the quality of different fluxes. These graphs identify terrain influences affecting the flux data quality. The evaluation is especially useful for checking to what extent the measured fluxes at a site are representative of a specific type of land use. # 2004 Elsevier B.V. All rights reserved.
Dario Papale - One of the best experts on this subject based on the ideXlab platform.
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Effects of the Gill-Solent WindMaster-Pro “w-boost” firmware bug on Eddy Covariance fluxes and some simple recovery strategies
Agricultural and Forest Meteorology, 2019Co-Authors: Dave Billesbach, Dario Papale, David R Cook, S.w. Chan, R. Bracho-garrillo, J. Verfallie, Rodrigo Vargas, Sebastien C. BiraudAbstract:Abstract In late 2015 and early 2016, work done by the AmeriFlux Management Project Technical Team (amerilfux.lbl.gov) helped to uncover an issue with Gill WindMaster and WindMaster Pro sonic anemometers used by many researchers for Eddy Covariance flux measurements. Gill has addressed this issue and has since sent out a notice that the vertical wind speed component (a critical piece of all Eddy Covariance fluxes) was being erroneously computed and reported. The problem (known as the “w-boost” bug) resulted in positive (upward) wind speeds being under-reported by 16.6% and negative (downward) wind speeds being under-reported by 28.9%. This has the potential to cause similar under estimates in fluxes derived from measurements using these instruments. Additionally, the bug affects corrections for angle of attack as derived by Nakai and Shimoyama, rendering them invalid. While the manufacturer has offered a firmware upgrade for existing instruments that will fix this issue, many existing data sets have been affected by it and are currently in use by the scientific community. To address the issue of affected data, currently in use, we analyzed multi-year and short-term data sets from a variety of ecosystems to assess methods of correcting existing flux data. We found that simple multiplicative correction factors (∼1.18) may be used to remove most of the “w-boost” bias from fluxes in existing data sets that do not include angle of attack corrections.
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evaluating the convergence between Eddy Covariance and biometric methods for assessing carbon budgets of forests
Nature Communications, 2016Co-Authors: Matteo Campioli, Dario Papale, Markus Reichstein, Mirco Migliavacca, Yadvinder Malhi, Sara Vicca, Sebastiaan Luyssaert, Josep Penuelas, M A Arain, Ivan A JanssensAbstract:The Eddy-Covariance (EC) micro-meteorological technique and the ecology-based biometric methods (BM) are the primary methodologies to quantify CO2 exchange between terrestrial ecosystems and the atmosphere (net ecosystem production, NEP) and its two components, ecosystem respiration and gross primary production. Here we show that EC and BM provide different estimates of NEP, but comparable ecosystem respiration and gross primary production for forest ecosystems globally. Discrepancies between methods are not related to environmental or stand variables, but are consistently more pronounced for boreal forests where carbon fluxes are smaller. BM estimates are prone to underestimation of net primary production and overestimation of leaf respiration. EC biases are not apparent across sites, suggesting the effectiveness of standard post-processing procedures. Our results increase confidence in EC, show in which conditions EC and BM estimates can be integrated, and which methodological aspects can improve the convergence between EC and BM.
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use of change point detection for friction velocity threshold evaluation in Eddy Covariance studies
Agricultural and Forest Meteorology, 2013Co-Authors: A G Barr, Gil Bohrer, T. A. Black, David Y Hollinger, Dario Papale, Andrew D Richardson, Danilo Dragoni, Marc L Fischer, Lianhong Gu, Hank A MargolisAbstract:a b s t r a c t The Eddy-Covariance method often underestimates fluxes under stable, low-wind conditions at night when turbulence is not well developed. The most common approach to resolve the problem of nighttime flux underestimation is to identify and remove the deficit periods using friction-velocity (u*) threshold filters (u* Th ). This study modifies an accepted method for u* Th evaluation by incorporating change-point-
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relative humidity effects on water vapour fluxes measured with closed path Eddy Covariance systems with short sampling lines
Agricultural and Forest Meteorology, 2012Co-Authors: Gerardo Fratini, Andreas Ibrom, Nicola Arriga, George Burba, Dario PapaleAbstract:Abstract It has been formerly recognised that increasing relative humidity in the sampling line of closed-path Eddy-Covariance systems leads to increasing attenuation of water vapour turbulent fluctuations, resulting in strong latent heat flux losses. This occurrence has been analyzed for very long (50 m) and long (7 m) sampling lines. To date, only a few analytical or in situ analyses have been proposed to quantify and correct such effects, among which the comprehensive method by Ibrom et al. (2007) was proved effective for the very long sampling line of a forest Eddy-Covariance setup. Here we analyze data from Eddy-Covariance systems featuring short (4 m) and very short (1 m) sampling lines running at the same clover field and show that relative humidity effects persist also for these setups, and should not be neglected. Starting from the work of Ibrom and co-workers, we propose a mixed method, a composite of two existing approaches, for correcting Eddy-Covariance fluxes. By means of a comparison with parallel open-path measurements, we show that the mixed method leads to an improved estimation of latent heat fluxes, with respect to the method described by Ibrom et al. (2007) . The quantification and correction method proposed here is deemed applicable to closed-path systems featuring a broad range of sampling lines, and indeed applicable also to passive gases as a special case. The methods described in this paper are incorporated, as processing options, in the free and open-source Eddy-Covariance software packages ECO2S and EddyPro.
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Eddy Covariance a practical guide to measurement and data analysis
2012Co-Authors: Marc Aubinet, Timo Vesala, Dario PapaleAbstract:Preface Chapter 1 : The Eddy Covariance method 1.1 History 1.2 Preliminaries 1.3. One point conservation equations 1.4 Integrated relations 1.5 Spectral analysis Chapter 2 : Measurement set-up 2.1 Introduction 2.2 Tower considerations 2.3 Sonic Anemometer 2.4 Eddy CO2 / H2O analyzer 2.5 Profile measurement Chapter 3 : Data Acquisition and Flux Calculations 3.1 Data Transfer and Acquisition 3.2 Flux calculation from raw data 3.3 Flux Determination Chapter 4 : Corrections and data quality control 4.1. Flux data correction 4.2. Effect of the unclosed energy balance 4.3 Data quality analysis 4.4. Accuracy of turbulent fluxes after correction and quality control 4.5 Overview of available correction software Chapter 5 : Night time Flux correction 5.1 Introduction 5.2 Is this problem really important? 5.3. How to implement the filtering procedure ? 5.4 Correction procedures Chapter 6: Data gap filling 6.1 Introduction 6.2 Gap-filling: why and when is it needed? 6.3 Gap-filling methods 6.4 Uncertainty and quality flags 6.5 Final remarks Chapter 7: Uncertainty quantification 7.1 Introduction 7.2 Random errors in flux measurements 7.3 Systematic errors in flux measurements 7.4 Closing ecosystem carbon budgets Conclusion Chapter 8 : Footprint analysis 8.1 Concept of footprint 8.2 Footprint models for atmospheric boundary layer 8.3 Footprint models for high vegetation 8.4 Complicated landscapes and inhomogeneous canopies 8.5 Quality assessment using footprint models 8.6 Validation of footprint models Chapter 9: Partitioning of net fluxes 9.1 Motivation 9.2 Definitions 9.3 Standard methods 9.4 Additional considerations and new approaches 9.5 Recommendations Chapter 10 : Disjunct Eddy Covariance method 10.1 Introduction 10.2 Theory 10.3 Practical applications of DEC 10.4 DEC in spectral space 10.5 Uncertainty due to DEC 10.6 On the history of the DEC approach Chapter 11: Eddy Covariance measurements over forests 11.1 Introduction 11.2 Flux computation, selection and dependence 11.3 Additional measurements 11.4 Impact of ecosystem management and manipulation Chapter 12: Eddy Covariance measurements over crops 12.1 Introduction 12.2 Measurement system 12.3 Flux calculation 12.4 Flux corrections 12.5. Data gap filling and footprint evaluation 12.6. Cumulated carbon exchange 12.7. Additional measurements 12.8. Future experimentations Chapter 13: Eddy Covariance measurements over grasslands 13.1 Historic overview of grassland EC flux measurements 13.2 Peculiarities of Eddy Covariance flux measurements over grasslands 13.3 Estimating grassland carbon sequestration from flux measurements 13. 4 Additional measurements 13.5 Other green house gases Chapter 14: Eddy Covariance measurements over wetlands 14.1 Introduction 14.2 Historic overview 14.3 Ecosystem-specific considerations 14.4 Complementary measurements 14.5 EC measurements in the wintertime 14.6 Carbon balances and climate effects 14.7 Concluding remarks Chapter 15: Eddy Covariance measurements over lakes 15.1. Introduction 15.2. Existing studies 15.3. Surface-specific siting problems Chapter 16: Eddy Covariance measurements over urban areas 16.1 Introduction 16.2 Conceptual framework for urban EC measurements 16.3 Challenges in the siting of urban EC stations 16.4 Implications of the peculiarities of the urban boundary layer on EC measurements 16.5 Summary and conclusions Chapter 17: Database maintenance, data sharing policy, collaboration 17.1 Data Management 17.2 Data Practices 17.3 Data User Services 17.4 Data Sharing and Policy of Uses Symbol Index Subject Index
Timo Vesala - One of the best experts on this subject based on the ideXlab platform.
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monthly gridded data product of northern wetland methane emissions based on upscaling Eddy Covariance observations
Earth System Science Data, 2019Co-Authors: Olli Peltola, Timo Vesala, Yao Gao, Olle Raty, Pavel Alekseychik, Mika Aurela, Bogdan H Chojnicki, Ankur R Desai, A J Dolman, E S EuskirchenAbstract:Abstract. Natural wetlands constitute the largest and most uncertain source of methane ( CH4 ) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 Eddy Covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45 ∘ N). Eddy Covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47 ) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4 . Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg( CH4 ) yr −1 . To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).
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revised Eddy Covariance flux calculation methodologies effect on urban energy balance
Tellus B, 2012Co-Authors: Annika Nordbo, Leena Jarvi, Timo VesalaAbstract:Eddy Covariance (EC) measurements of turbulent fluxes of momentum, sensible heat and latent heat – in addition to net radiation measurements – were conducted for three consecutive years in an urban environment: Helsinki, Finland. The aims were to: (1) quantify the detection limit and random uncertainty of turbulent fluxes, (2) assess the systematic error caused by EC calculation-procedure choices on the energy balance residual and (3) report the energy balance of the world's northernmost urban flux station. The mean detection limits were about 10% of the observed flux, and the random uncertainty was 9–16%. Of all fluxes, the latent heat flux – as measured with a closed-path gas analyser – was most prone to systematic calculation errors due to water vapour interactions with tube walls: using a lag window that is too small can cause a 15% lack of data (due to the dependency of lag time on relative humidity) and omitting spectral corrections can cause on average a 26% underestimation of the flux. The systematic errors in EC calculation propagate into the energy balance residual and can be larger than the residual itself: for example, omitting spectral corrections overestimates the residual by 13% or 18% on average, depending on the analyser. Keywords: Eddy Covariance; urban; energy balance; flux uncertainty; flux error (Published: 19 April 2012) Citation: Tellus B 2012, 64 , 18184, http://dx.doi.org/10.3402/tellusb.v64i0.18184
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Eddy Covariance a practical guide to measurement and data analysis
2012Co-Authors: Marc Aubinet, Timo Vesala, Dario PapaleAbstract:Preface Chapter 1 : The Eddy Covariance method 1.1 History 1.2 Preliminaries 1.3. One point conservation equations 1.4 Integrated relations 1.5 Spectral analysis Chapter 2 : Measurement set-up 2.1 Introduction 2.2 Tower considerations 2.3 Sonic Anemometer 2.4 Eddy CO2 / H2O analyzer 2.5 Profile measurement Chapter 3 : Data Acquisition and Flux Calculations 3.1 Data Transfer and Acquisition 3.2 Flux calculation from raw data 3.3 Flux Determination Chapter 4 : Corrections and data quality control 4.1. Flux data correction 4.2. Effect of the unclosed energy balance 4.3 Data quality analysis 4.4. Accuracy of turbulent fluxes after correction and quality control 4.5 Overview of available correction software Chapter 5 : Night time Flux correction 5.1 Introduction 5.2 Is this problem really important? 5.3. How to implement the filtering procedure ? 5.4 Correction procedures Chapter 6: Data gap filling 6.1 Introduction 6.2 Gap-filling: why and when is it needed? 6.3 Gap-filling methods 6.4 Uncertainty and quality flags 6.5 Final remarks Chapter 7: Uncertainty quantification 7.1 Introduction 7.2 Random errors in flux measurements 7.3 Systematic errors in flux measurements 7.4 Closing ecosystem carbon budgets Conclusion Chapter 8 : Footprint analysis 8.1 Concept of footprint 8.2 Footprint models for atmospheric boundary layer 8.3 Footprint models for high vegetation 8.4 Complicated landscapes and inhomogeneous canopies 8.5 Quality assessment using footprint models 8.6 Validation of footprint models Chapter 9: Partitioning of net fluxes 9.1 Motivation 9.2 Definitions 9.3 Standard methods 9.4 Additional considerations and new approaches 9.5 Recommendations Chapter 10 : Disjunct Eddy Covariance method 10.1 Introduction 10.2 Theory 10.3 Practical applications of DEC 10.4 DEC in spectral space 10.5 Uncertainty due to DEC 10.6 On the history of the DEC approach Chapter 11: Eddy Covariance measurements over forests 11.1 Introduction 11.2 Flux computation, selection and dependence 11.3 Additional measurements 11.4 Impact of ecosystem management and manipulation Chapter 12: Eddy Covariance measurements over crops 12.1 Introduction 12.2 Measurement system 12.3 Flux calculation 12.4 Flux corrections 12.5. Data gap filling and footprint evaluation 12.6. Cumulated carbon exchange 12.7. Additional measurements 12.8. Future experimentations Chapter 13: Eddy Covariance measurements over grasslands 13.1 Historic overview of grassland EC flux measurements 13.2 Peculiarities of Eddy Covariance flux measurements over grasslands 13.3 Estimating grassland carbon sequestration from flux measurements 13. 4 Additional measurements 13.5 Other green house gases Chapter 14: Eddy Covariance measurements over wetlands 14.1 Introduction 14.2 Historic overview 14.3 Ecosystem-specific considerations 14.4 Complementary measurements 14.5 EC measurements in the wintertime 14.6 Carbon balances and climate effects 14.7 Concluding remarks Chapter 15: Eddy Covariance measurements over lakes 15.1. Introduction 15.2. Existing studies 15.3. Surface-specific siting problems Chapter 16: Eddy Covariance measurements over urban areas 16.1 Introduction 16.2 Conceptual framework for urban EC measurements 16.3 Challenges in the siting of urban EC stations 16.4 Implications of the peculiarities of the urban boundary layer on EC measurements 16.5 Summary and conclusions Chapter 17: Database maintenance, data sharing policy, collaboration 17.1 Data Management 17.2 Data Practices 17.3 Data User Services 17.4 Data Sharing and Policy of Uses Symbol Index Subject Index
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long term direct co2 flux measurements over a boreal lake five years of Eddy Covariance data
Geophysical Research Letters, 2011Co-Authors: Jussi Huotari, Annika Nordbo, Anne Ojala, Elina Peltomaa, Samuli Launiainen, Jukka Pumpanen, Terhi Rasilo, Pertti Hari, Timo VesalaAbstract:[1] Significant amounts of terrestrial carbon are processed in lakes and emitted into the atmosphere as CO2. However, due to lack of appropriate measurements the absolute role of lakes in the landscape as sinks or sources of CO2 is still uncertain. We conducted the first long-term, ecosystem-level CO2 flux measurements with Eddy Covariance technique in a boreal lake within a natural-state catchment covering 5 years. The aim was to reveal the natural level of CO2 flux between a lake and the atmosphere and its role in regional carbon cycling. On average, the lake emitted ca 10% of the terrestrial net ecosystem production of the surrounding old-growth forest and the main immediate drivers behind the fluxes were physical rather than biological. Our results suggest that lakes are an integral part of terrestrial carbon cycling.
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towards a standardized processing of net ecosystem exchange measured with Eddy Covariance technique algorithms and uncertainty estimation
Biogeosciences, 2006Co-Authors: Dario Papale, Christian Bernhofer, Marc Aubinet, Markus Reichstein, E Canfora, Werner L Kutsch, Bernard Longdoz, Serge Rambal, R Valentini, Timo VesalaAbstract:Abstract. Eddy Covariance technique to measure CO2, water and energy fluxes between biosphere and atmosphere is widely spread and used in various regional networks. Currently more than 250 Eddy Covariance sites are active around the world measuring carbon exchange at high temporal resolution for different biomes and climatic conditions. In this paper a new standardized set of corrections is introduced and the uncertainties associated with these corrections are assessed for eight different forest sites in Europe with a total of 12 yearly datasets. The uncertainties introduced on the two components GPP (Gross Primary Production) and TER (Terrestrial Ecosystem Respiration) are also discussed and a quantitative analysis presented. Through a factorial analysis we find that generally, uncertainties by different corrections are additive without interactions and that the heuristic u*-correction introduces the largest uncertainty. The results show that a standardized data processing is needed for an effective comparison across biomes and for underpinning inter-annual variability. The methodology presented in this paper has also been integrated in the European database of the Eddy Covariance measurements.
Matthias Mauder - One of the best experts on this subject based on the ideXlab platform.
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Extension of the Averaging Time in Eddy-Covariance Measurements and Its Effect on the Energy Balance Closure
Boundary-Layer Meteorology, 2014Co-Authors: Doojdao Charuchittipan, Matthias Mauder, Wolfgang Babel, Jens-peter Leps, Thomas FokenAbstract:The modified ogive analysis and the block ensemble average were employed to investigate the impact of the averaging time extension on the energy balance closure over six land-use types. The modified ogive analysis, which requires a steady-state condition, can extend the averaging time up to a few hours and suggests that an averaging time of 30 min is still overall sufficient for Eddy-Covariance measurements over low vegetation. The block ensemble average, which does not require a steady-state condition, can extend the averaging time to several days. However, it can improve the energy balance closure for some sites during specific periods, when secondary circulations exist in the vicinity of the sensor. These near-surface secondary circulations mainly transport sensible heat, and when near-ground warm air is transported upward, the sensible heat flux observed by the block ensemble average will increase at longer averaging times. These findings suggest an alternative energy balance correction for a ground-based Eddy-Covariance measurement, in which the attribution of the residual depends on the ratio of sensible heat flux to the buoyancy flux. The fraction of the residual attributed to the sensible heat flux by this energy balance correction is larger than in the energy balance correction that preserves the Bowen ratio.
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towards a consistent Eddy Covariance processing an intercomparison of Eddypro and tk3
Atmospheric Measurement Techniques, 2014Co-Authors: Gerardo Fratini, Matthias MauderAbstract:Abstract. A comparison of two popular Eddy-Covariance software packages is presented, namely, EddyPro and TK3. Two approximately 1-month long test data sets were processed, representing typical instrumental setups (i.e., CSAT3/LI-7500 above grassland and Solent R3/LI-6262 above a forest). The resulting fluxes and quality flags were compared. Achieving a satisfying agreement and understanding residual discrepancies required several iterations and interventions of different nature, spanning from simple software reconfiguration to actual code manipulations. In this paper, we document our comparison exercise and show that the two software packages can provide utterly satisfying agreement when properly configured. Our main aim, however, is to stress the complexity of performing a rigorous comparison of Eddy-Covariance software. We show that discriminating actual discrepancies in the results from inconsistencies in the software configuration requires deep knowledge of both software packages and of the Eddy-Covariance method. In some instances, it may be even beyond the possibility of the investigator who does not have access to and full knowledge of the source code. Being the developers of EddyPro and TK3, we could discuss the comparison at all levels of details and this proved necessary to achieve a full understanding. As a result, we suggest that researchers are more likely to get comparable results when using EddyPro (v5.1.1) and TK3 (v3.11) – at least with the setting presented in this paper – than they are when using any other pair of EC software which did not undergo a similar cross-validation. As a further consequence, we also suggest that, to the aim of assuring consistency and comparability of centralized flux databases, and for a confident use of Eddy fluxes in synthesis studies on the regional, continental and global scale, researchers only rely on software that have been extensively validated in documented intercomparisons.
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a strategy for quality and uncertainty assessment of long term Eddy Covariance measurements
Agricultural and Forest Meteorology, 2013Co-Authors: Matthias Mauder, H P Schmid, Corinna Rebmann, Matthias Cuntz, Clemens Drue, Alexander Graf, Marius Schmidt, Rainer SteinbrecherAbstract:Abstract Eddy-Covariance measurements are performed at several hundred sites all over the world on a long-term basis. The gathered data are used to characterise ecosystem exchanges of trace gases, water and energy and to validate or constrain process-based models. There is an increasing demand on standardised and comprehensive quality flagging and uncertainty quantification of these fluxes. In this paper, we review established quality assessment procedures and present a comprehensive newly composed strategy emphasising tests on high-frequency raw data, expanding existing tests on statistics, fluxes and corrections, plus quantification of errors. Moreover, representativity of fluxes is checked by footprint analysis. This strategy is applied within the recently launched TERENO network of ecosystem observatories, and its robustness is demonstrated for data acquired with different measurement set-ups. Four test data sets from TERENO and one data set from CarboEurope-IP were subjected to this quality assessment. The presented strategy is compared with established quality assessment schemes, and it is demonstrated that unrealistic fluxes are now efficiently excluded while retaining the largest possible amount of high quality data. Additionally, the algorithms applied provide comprehensive, reproducible, qualitative and quantitative uncertainty estimates for users of Eddy-Covariance flux data.
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Eddy Covariance flux measurements with a weight shift microlight aircraft
Atmospheric Measurement Techniques, 2012Co-Authors: Stefan Metzger, W Junkermann, Matthias Mauder, Frank Beyrich, Klaus Butterbachbahl, H P Schmid, Thomas FokenAbstract:Abstract. The objective of this study is to assess the feasibility and quality of Eddy-Covariance flux measurements from a weight-shift microlight aircraft (WSMA). Firstly, we investigate the precision of the wind measurement (σu,v ≤ 0.09 m s−1, σw = 0.04 m s−1), the lynchpin of flux calculations from aircraft. From here, the smallest resolvable changes in friction velocity (0.02 m s−1), and sensible- (5 W m−2) and latent (3 W m−2) heat flux are estimated. Secondly, a seven-day flight campaign was performed near Lindenberg (Germany). Here we compare measurements of wind, temperature, humidity and respective fluxes between a tall tower and the WSMA. The maximum likelihood functional relationship (MLFR) between tower and WSMA measurements considers the random error in the data, and shows very good agreement of the scalar averages. The MLFRs for standard deviations (SDs, 2–34%) and fluxes (17–21%) indicate higher estimates of the airborne measurements compared to the tower. Considering the 99.5% confidence intervals, the observed differences are not significant, with exception of the temperature SD. The comparison with a large-aperture scintillometer reveals lower sensible heat flux estimates at both tower (−40 to −25%) and WSMA (−25–0%). We relate the observed differences to (i) inconsistencies in the temperature and wind measurement at the tower and (ii) the measurement platforms' differing abilities to capture contributions from non-propagating eddies. These findings encourage the use of WSMA as a low cost and highly versatile flux measurement platform.
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the energy balance experiment ebex 2000 part ii intercomparison of Eddy Covariance sensors and post field data processing methods
Boundary-Layer Meteorology, 2007Co-Authors: Christian Bernhofer, Matthias Mauder, Thomas Foken, Steven P Oncley, Roland Vogt, Tamas Weidinger, Luis Frolen Ribeiro, W Kohsiek, Henk A R De BruinAbstract:The Eddy-Covariance method is the primary way of measuring turbulent fluxes directly. Many investigators have found that these flux measurements often do not satisfy a fundamental criterion—closure of the surface energy balance. This study investigates to what extent the Eddy-Covariance measurement technology can be made responsible for this deficiency, in particular the effects of instrumentation or of the post-field data processing. Therefore, current Eddy-Covariance sensors and several post-field data processing methods were compared. The differences in methodology resulted in deviations of 10% for the sensible heat flux and of 15% for the latent heat flux for an averaging time of 30 min. These disparities were mostly due to different sensor separation corrections and a linear detrending of the data. The impact of different instrumentation on the resulting heat flux estimates was significantly higher. Large deviations from the reference system of up to 50% were found for some sensor combinations. However, very good measurement quality was found for a CSAT3 sonic together with a KH20 krypton hygrometer and also for a UW sonic together with a KH20. If these systems are well calibrated and maintained, an accuracy of better than 5% can be achieved for 30-min values of sensible and latent heat flux measurements. The results from the sonic anemometers Gill Solent-HS, ATI-K, Metek USA-1, and R.M. Young 81000 showed more or less larger deviations from the reference system. The LI-COR LI-7500 open-path H2O/CO2 gas analyser in the test was one of the first serial numbers of this sensor type and had technical problems regarding direct solar radiation sensitivity and signal delay. These problems are known by the manufacturer and improvements of the sensor have since been made.
