Long-Term Carbon and Water Vapour Fluxes

Babel, Wolfgang; Lüers, Johannes; Hübner, Jörg; Rebmann, Corinna; Wichura, Bodo; Thomas, Christoph; Serafimovich, Andrei; Foken, Thomas

doi:10.1007/978-3-319-49389-3_4

Cited by 7 publications

(15 citation statements)

References 41 publications

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“…Figure shows a histogram of time trends from individual sites, for example, slopes, in NEE, determined from published time series that are a decade or longer (Aguilos, Hérault, Burban, Wagner, & Bonal, ; Anić et al, ; Babel et al, ; Clark, Gholz, & Castro, ; Dold et al, ; Elbers, Jacobs, Kruijt, Jans, & Moors, ; Froelich, Croft, Chen, Gonsamo, & Staebler, ; Ge, Kellomäki, Zhou, Wang, & Peltola, ; Granier, Bréda, Longdoz, Gross, & Ngao, ; Grunwald & Bernhofer, ; Helfter et al, ; Ilvesniemi et al, ; Ma, Baldocchi, Wolf, & Verfaillie, ; Pilegaard, Ibrom, Courtney, Hummelshøj, & Jensen, ; Soloway, Amiro, Dunn, & Wofsy, ; Sulman, Roman, Scanlon, Wang, & Novick, ; Tamrakar, Rayment, Moyano, Mund, & Knohl, ; Urbanski et al, ; van Gorsel et al, ; Wilkinson, Eaton, Broadmeadow, & Morison, ). Most of the trends are clustered between −70 and 20 g C m −2 year −2 .…”

Section: What Have We Learned About Carbon Fluxes?mentioning

confidence: 99%

How eddy covariance flux measurements have contributed to our understanding of Global Change Biology

Baldocchi

2019

Global Change Biology

303

164

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A global network of long‐term carbon and water flux measurements has existed since the late 1990s. With its representative sampling of the terrestrial biosphere's climate and ecological spaces, this network is providing background information and direct measurements on how ecosystem metabolism responds to environmental and biological forcings and how they may be changing in a warmer world with more carbon dioxide. In this review, I explore how carbon and water fluxes of the world's ecosystem are responding to a suite of covarying environmental factors, like sunlight, temperature, soil moisture, and carbon dioxide. I also report on how coupled carbon and water fluxes are modulated by biological and ecological factors such as phenology and a suite of structural and functional properties. And, I investigate whether long‐term trends in carbon and water fluxes are emerging in various ecological and climate spaces and the degree to which they may be driven by physical and biological forcings. As a growing number of time series extend up to 20 years in duration, we are at the verge of capturing ecosystem scale trends in the breathing of a changing biosphere. Consequently, flux measurements need to continue to report on future conditions and responses and assess the efficacy of natural climate solutions.

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Section: What Have We Learned About Carbon Fluxes?mentioning

confidence: 99%

How eddy covariance flux measurements have contributed to our understanding of Global Change Biology

Baldocchi

2019

Global Change Biology

303

164

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“…Possibly affected time series are the measurements made with the R2 and R3 sonic anemometer from 1997 to 2006 and the LiCor 6262 gas analyser (LI-COR Inc., Lincoln, NE, USA) from 1997 to 2002. The complete data set was analysed by Babel et al (2017).…”

Section: Data Sets For the Analysismentioning

confidence: 99%

“…Nowadays, data sets from FLUXNET sites are available and many papers have been published which analyse and compare these data and link them to ecosystems, phenology, regions, and climate (Baldocchi, 2008;Williams et al, 2012;Keenan et al, 2013Keenan et al, , 2014Kutsch and Kolari, 2015;Baldocchi et al, 2016;Babel et al, 2017). Among the factors, which possibly influence the resulting budgets, is the quantification (digitalization) error (Ifeachor and Jervis, 2002), arising from the use of a limited 12 bit digitalization of turbulence data which was the state of the art about 15-20 years ago (Vickers and Mahrt, 1997).…”

Section: Introductionmentioning

confidence: 99%

Possible errors in flux measurements due to limited digitalization

2019

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Abstract. Recently reported trends of carbon dioxide uptake pose the question of whether trends may be the result of the limited digitalization of gas analysers and sonic anemometers used in the 1990s. Modifying a 12 bit digitalization and the instrument error reported for the Gill R2 and R3 sonic anemometers found elsewhere, the influence of these deficits in comparison to the now commonly used 16 bit digitalization were quantified. Both issues have an effect only on trace gas fluxes of small magnitude, mainly for the carbon dioxide rather than for the water vapour fluxes. The influence on the annual net ecosystem exchange is negligible, because other errors resulting from gap filling routines, for example, are much larger.

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“…The eddy covariance (EC) method is a micrometeorological technique commonly used to measure the energy, water vapor, and carbon dioxide exchange between biosphere and atmosphere across a large range of scales in time and space (Baldocchi et al, 2001;Reichstein et al, 2012). The measurements help us to understand the temporal and spatial variations of these fluxes at the land-atmosphere interface.…”

Section: Introductionmentioning

confidence: 99%

Source partitioning of H<sub>2</sub>O and CO<sub>2</sub> fluxes based on high-frequency eddy covariance data: a comparison between study sites

Klosterhalfen¹,

Graf²,

Brüggemann³

et al. 2019

Biogeosciences

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Abstract. For an assessment of the roles of soil and vegetation in the climate system, a further understanding of the flux components of H2O and CO2 (e.g., transpiration, soil respiration) and their interaction with physical conditions and physiological functioning of plants and ecosystems is necessary. To obtain magnitudes of these flux components, we applied source partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) to high-frequency eddy covariance measurements of 12 study sites covering different ecosystems (croplands, grasslands, and forests) in different climatic regions. Both partitioning methods are based on higher-order statistics of the H2O and CO2 fluctuations, but proceed differently to estimate transpiration, evaporation, net primary production, and soil respiration. We compared and evaluated the partitioning results obtained with SK10 and TH08, including slight modifications of both approaches. Further, we analyzed the interrelations among the performance of the partitioning methods, turbulence characteristics, and site characteristics (such as plant cover type, canopy height, canopy density, and measurement height). We were able to identify characteristics of a data set that are prerequisites for adequate performance of the partitioning methods. SK10 had the tendency to overestimate and TH08 to underestimate soil flux components. For both methods, the partitioning of CO2 fluxes was less robust than for H2O fluxes. Results derived with SK10 showed relatively large dependencies on estimated water use efficiency (WUE) at the leaf level, which is a required input. Measurements of outgoing longwave radiation used for the estimation of foliage temperature (used in WUE) could slightly increase the quality of the partitioning results. A modification of the TH08 approach, by applying a cluster analysis for the conditional sampling of respiration–evaporation events, performed satisfactorily, but did not result in significant advantages compared to the original method versions developed by Thomas et al. (2008). The performance of each partitioning approach was dependent on meteorological conditions, plant development, canopy height, canopy density, and measurement height. Foremost, the performance of SK10 correlated negatively with the ratio between measurement height and canopy height. The performance of TH08 was more dependent on canopy height and leaf area index. In general, all site characteristics that increase dissimilarities between scalars appeared to enhance partitioning performance for SK10 and TH08.

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Long-Term Carbon and Water Vapour Fluxes

Cited by 7 publications

References 41 publications

How eddy covariance flux measurements have contributed to our understanding of Global Change Biology

How eddy covariance flux measurements have contributed to our understanding of Global Change Biology

Possible errors in flux measurements due to limited digitalization

Source partitioning of H<sub>2</sub>O and CO<sub>2</sub> fluxes based on high-frequency eddy covariance data: a comparison between study sites

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Long-Term Carbon and Water Vapour Fluxes

Cited by 7 publications

References 41 publications

How eddy covariance flux measurements have contributed to our understanding of Global Change Biology

How eddy covariance flux measurements have contributed to our understanding of Global Change Biology

Possible errors in flux measurements due to limited digitalization

Source partitioning of H&lt;sub&gt;2&lt;/sub&gt;O and CO&lt;sub&gt;2&lt;/sub&gt; fluxes based on high-frequency eddy covariance data: a comparison between study sites

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Source partitioning of H<sub>2</sub>O and CO<sub>2</sub> fluxes based on high-frequency eddy covariance data: a comparison between study sites