Kooperativer Bibliotheksverbund

Berlin Brandenburg

and
and

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Language: English
    In: Agricultural and Forest Meteorology, April 15, 2013, Vol.171-172, p.203(17)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.agrformet.2012.11.019 Byline: Wittaya Kessomkiat, Harrie-Jan Hendricks Franssen, Alexander Graf, Harry Vereecken Keywords: Random error; Measurement error; Eddy covariance; Energy balance closure; Data assimilation Abstract: a* An extended two-tower approach for estimating random errors of EC data is proposed. a* Random errors are smaller for the extended approach compared to the classical one. a* The extended approach is applicable for two towers with different vegetation types. Author Affiliation: Agrosphere, IBG-3, Forschungszentrum Julich GmbH, Leo-Brandt Strasse, 52425 Julich, Germany Article History: Received 9 July 2012; Revised 19 November 2012; Accepted 27 November 2012
    ISSN: 0168-1923
    Source: Cengage Learning, Inc.
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    Language: English
    In: Agricultural and Forest Meteorology, Feb 15, 2015, Vol.201, p.128(13)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.agrformet.2014.10.015 Byline: Laura Gangi, Wolfgang Tappe, Harry Vereecken, Nicolas Bruggemann Abstract: * CO.sup.18O isoforcing decreased at elevated temperature in all species except maize. * CO.sup.18O isoforcing decreased with limited water availability in all plant species. * Degree of isotopic CO.sub.2-H.sub.2O equilibrium significantly below unity in all plant species. Author Affiliation: Forschungszentrum Julich GmbH, Agrosphere Institute (IBG-3), Leo-Brandt-Strasse, 52425 Julich, Germany Article History: Received 15 May 2014; Revised 21 October 2014; Accepted 25 October 2014
    Keywords: Environmental Quality – Environmental Aspects ; Plants (Organisms) – Environmental Aspects
    ISSN: 0168-1923
    Source: Cengage Learning, Inc.
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 3
    Language: English
    In: Agricultural and Forest Meteorology, 15 February 2015, Vol.201, pp.128-140
    Description: The oxygen isotope signature of atmospheric carbon dioxide (δ O–CO ) is significantly influenced by terrestrial vegetation through O-exchange between CO and leaf water. However, the impact of short-term variations of environmental conditions on this O-exchange has not been sufficiently characterized yet for different plant functional types. In the present study, δ O of CO and water vapor were measured in chamber-based experiments with spruce, wheat, poplar and maize using infrared laser spectroscopy. The impact of the plants on ambient δ O–CO was inferred from the chamber-based CO O isoforcing (CO O-Iso), i.e., the product of the net CO flux through the chamber and the δ O–CO of this flux obtained from differential measurements at the chamber inlet and outlet. The measured CO O-Iso was compared to the CO O isoforcing (CO O-Iso ) calculated as a function of the δ O of leaf water at the evaporation site (δ O–H O ) and the degree of oxygen isotope equilibration between CO and leaf water ( ). Plants were exposed to elevated air temperature (35 °C) and cessation of water supply. CO O-Iso was reduced at 35 °C due to the reduction of stomatal conductance ( ) in all plant species except for maize, and at decreasing water availability in all four plant species due to a reduction of , assimilation rate ( ) and , while leaf water became progressively O-enriched. The combination of , , and δ O–H O accounted for up to 98% of the variations in CO O-Iso, which were well represented by CO O-Iso , whereas the relationship between individual determinants and CO O-Iso was weaker. The degree of isotopic CO –H O equilibration calculated from isotopic gas exchange reached maximum values of 0.51 and 0.53 in maize and spruce, and 0.67 and 0.74 in wheat and poplar, respectively. Although was highly sensitive to the parameterization of mesophyll conductance ( ), most of the literature values for each species yielded values for significantly lower than previously reported for the respective plant species. This finding, as well as the observed temporal variations in the oxygen isotopic exchange introduced by varying environmental conditions, should be considered for the parameterization of δ O–CO models.
    Keywords: Carbonic Anhydrase ; Co18o Isoforcing ; Isotopic Equilibrium ; Laser-Based Spectroscopy ; Leaf Water Enrichment ; Oxygen Isotope Exchange ; Agriculture ; Meteorology & Climatology
    ISSN: 0168-1923
    E-ISSN: 1873-2240
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 4
    Language: English
    In: Agricultural and forest meteorology, 2013, Vol.171, pp.203-219
    Description: The incorporation of eddy covariance (EC) data in a land surface model (LSM) with help of data assimilation techniques requires a specification of the uncertainty of EC measurements. EC measurement uncertainty is composed of a systematic and random component. The systematic error is for example related to the energy balance (EB) closure, whereas the random error can be determined on the basis of differences between simultaneous flux measurements from two towers according to Hollinger and Richardson (2005) (Tree Physiol. 25, 873–885, here referred to as classical approach). The two-tower method, however, can be applied only where two towers share very similar environmental conditions. Here, we introduce an extended procedure to estimate the random error from EC data on the basis of the two-tower approach adapted for more heterogeneous environmental conditions. Our extended procedure consists of three main steps: (1) the EB deficit is corrected by distributing the deficit over the latent and sensible heat fluxes according to the evaporative fraction for each tower. This correction is based on the assumption that the EB deficit is due to an underestimation of the turbulent fluxes; (2) heterogeneity (e.g. different soil properties or vegetation characteristics and local variability in precipitation amounts) between two towers can introduce additional systematic flux differences. These differences can be corrected by normalizing turbulent fluxes at each tower according to the averaged evaporative fraction from two towers; (3) the random error can be determined following the two-tower approach using the normalized fluxes for the two towers. EC data from three different sites with different environmental conditions are used to test the classical and our extended approach: (1) three EC towers are placed at the Merken site, Germany and each of the three towers is surrounded by different vegetation types. This allows an evaluation on the basis of three different two-tower pairs. (2) two EC towers are located at the Roccarespampani site, Italy, with the same vegetation type around both towers. However, there are differences in vegetation age and density between these two towers; (3) for the Howland site, Maine, USA also data from two towers are available with very similar environmental conditions around the two towers. The random errors calculated by our extended approach are smaller than random errors from the classical approach, especially for larger net radiation (or large absolute fluxes). In addition, the random errors calculated by our extended approach result also in 9 out of 10 cases in less steep increases of the random error as function of flux magnitude (compared to the classical method). It was also found that atmospheric stability is an interesting alternative explanatory variable for random error of fluxes, which could be of special interest in the context of the extended two-tower approach. We conclude that our extended two-tower approach can be used to determine the random error of EC data for two towers located in more heterogeneous environmental conditions than aimed at by the original approach. ; p. 203-219.
    Keywords: Models ; Environmental Factors ; Soil Properties ; Heat Transfer ; Trees ; Energy Balance ; Uncertainty ; Vegetation Types ; Eddy Covariance
    ISSN: 0168-1923
    Source: AGRIS (Food and Agriculture Organization of the United Nations)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 5
    Language: English
    In: Agricultural and Forest Meteorology, 15 April 2013, Vol.171-172, pp.203-219
    Description: ► An extended two-tower approach for estimating random errors of EC data is proposed. ► Random errors are smaller for the extended approach compared to the classical one. ► The extended approach is applicable for two towers with different vegetation types. The incorporation of eddy covariance (EC) data in a land surface model (LSM) with help of data assimilation techniques requires a specification of the uncertainty of EC measurements. EC measurement uncertainty is composed of a systematic and random component. The systematic error is for example related to the energy balance (EB) closure, whereas the random error can be determined on the basis of differences between simultaneous flux measurements from two towers according to (Tree Physiol. 25, 873–885, here referred to as classical approach). The two-tower method, however, can be applied only where two towers share very similar environmental conditions. Here, we introduce an extended procedure to estimate the random error from EC data on the basis of the two-tower approach adapted for more heterogeneous environmental conditions. Our extended procedure consists of three main steps: (1) the EB deficit is corrected by distributing the deficit over the latent and sensible heat fluxes according to the evaporative fraction for each tower. This correction is based on the assumption that the EB deficit is due to an underestimation of the turbulent fluxes; (2) heterogeneity (e.g. different soil properties or vegetation characteristics and local variability in precipitation amounts) between two towers can introduce additional systematic flux differences. These differences can be corrected by normalizing turbulent fluxes at each tower according to the averaged evaporative fraction from two towers; (3) the random error can be determined following the two-tower approach using the normalized fluxes for the two towers. EC data from three different sites with different environmental conditions are used to test the classical and our extended approach: (1) three EC towers are placed at the Merken site, Germany and each of the three towers is surrounded by different vegetation types. This allows an evaluation on the basis of three different two-tower pairs. (2) two EC towers are located at the Roccarespampani site, Italy, with the same vegetation type around both towers. However, there are differences in vegetation age and density between these two towers; (3) for the Howland site, Maine, USA also data from two towers are available with very similar environmental conditions around the two towers. The random errors calculated by our extended approach are smaller than random errors from the classical approach, especially for larger net radiation (or large absolute fluxes). In addition, the random errors calculated by our extended approach result also in 9 out of 10 cases in less steep increases of the random error as function of flux magnitude (compared to the classical method). It was also found that atmospheric stability is an interesting alternative explanatory variable for random error of fluxes, which could be of special interest in the context of the extended two-tower approach. We conclude that our extended two-tower approach can be used to determine the random error of EC data for two towers located in more heterogeneous environmental conditions than aimed at by the original approach.
    Keywords: Random Error ; Measurement Error ; Eddy Covariance ; Energy Balance Closure ; Data Assimilation ; Agriculture ; Meteorology & Climatology
    ISSN: 0168-1923
    E-ISSN: 1873-2240
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 6
    Language: English
    In: Agricultural and Forest Meteorology, 15 March 2019, Vol.266-267, pp.53-64
    Description: Field-based quantitative observations of hydrological feedbacks of terrestrial vegetation to the atmosphere are crucial for improving land-surface model parametrizations. This is especially true in the specific context of partitioning of evapotranspiration ( ) into soil evaporation ( ) and plant transpiration ( ): land surface models are able to compute and separately while observed transpiration fractions ( / ) are still sparse. In this study, we present the application of an on-line non-destructive method based on gas-permeable tubing for the in-situ collection of soil water vapor. This allowed for monitoring of the hydrogen and oxygen isotopic compositions ( H and O) of soil water during a field campaign where of sugar beet ( ) was partitioned. / estimates obtained with the non-destructive method were compared with the commonly used destructive sampling of soil and subsequent cryogenic extraction of soil water under vacuum. Finally, isotope-based / estimates were compared to those obtained from a combination of micro-lysimeter and eddy covariance (EC) measurements. Significant discrepancies between the values of isotopic composition of evaporation derived destructively and non-destructively from those of soil water using a well-known transfer resistance model led in turn to significant differences in / . This is in line with recent findings on the systematic offsets of soil water isotopic composition values in relation to the water sampling and extraction measurement techniques and calls for further investigation of these isotopic offsets for accurate separation of from in the field. These discrepancies were, however, smaller than those observed between H- or O-based estimates, and more than three times smaller than those between isotope-based and lysimeter-based estimates.
    Keywords: Flux Partitioning ; Evapotranspiration ; Water Stable Isotopes ; Micro-Lysimeter ; Eddy Covariance ; Isotopic Non-Destructive Monitoring ; Agriculture ; Meteorology & Climatology
    ISSN: 0168-1923
    E-ISSN: 1873-2240
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 7
    Language: English
    In: Agricultural and Forest Meteorology, 15 May 2019, Vol.269-270, pp.28-45
    Description: A detailed representation of plant hydraulic traits and stomatal closure in land surface models (LSMs) is a prerequisite for improved predictions of ecosystem drought response. This work presents the integration of a macroscopic root water uptake (RWU) model based on the hydraulic architecture approach in the LSM of the Terrestrial Systems Modeling Platform. The novel RWU approach is based on three parameters derived from first principles that describe the root system equivalent conductance, the compensatory RWU conductance, and the leaf water potential at stomatal closure, which defines the water stress condition for the plants. The developed RWU model intrinsically accounts for changes in the root density as well as for the simulation of the hydraulic lift process. The standard and the new RWU approach are compared by performing point-scale simulations for cropland over a sheltered minirhizotron facility in Selhausen, Germany, and validated against transpiration fluxes estimated from sap flow and soil water content measurements at different depths. Numerical sensitivity experiments are carried out using different soil textures and root distributions in order to evaluate the interplay between soil hydrodynamics and plant characteristics, and the impact of assuming time-constant plant physiological properties. Results show a good agreement between simulated and observed transpiration fluxes for both RWU models, with a more distinct response under water stress conditions and with uncertainty in the soil parameterization prevailing to the differences due to changes in the model formulation. The hydraulic RWU model exhibits also a lower sensitivity to the root distributions when simulating the onset of the water stress period. Finally, an analysis of variability across the soil and root scenarios indicates that differences in soil water content are mainly influenced by the root distribution, while the transpiration flux in both RWU models is additionally determined by the soil characteristics.
    Keywords: Root Water Uptake ; Hydraulic Architecture Model ; Hydraulic Redistribution ; Transpiration ; Crop Water Stress ; Stomata Conductance ; Minirhizotron Facility ; Terrestrial Systems Modeling ; Agriculture ; Meteorology & Climatology
    ISSN: 0168-1923
    E-ISSN: 1873-2240
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 8
    Language: English
    In: Agricultural and Forest Meteorology, 15 August 2019, Vol.274, pp.61-74
    Description: A seven year CO -flux dataset measured in a 70 year old spruce monoculture is presented, of which 22% was deforested three years after the start of the measurements to accelerate regeneration towards natural deciduous vegetation. An eddy covariance (EC) system, mounted on top of a tower within the spruce forest, continuously sampled fluxes of momentum, sensible heat, latent heat and CO . After clear-cutting, a second EC station with an identical set of instruments was installed inside the deforested area. In total, we examined an EC dataset including three years before (forest) and four years after partial deforestation (forest and deforested). Full time series and annual carbon budgets of the net ecosystem exchange (NEE) and its components gross primary production (GPP) and total ecosystem respiration ( ) were calculated for both EC sites. Soil respiration was measured with manual chambers on average every month after the deforestation at 75 measurement points in the forest and deforested area. Annual sums of NEE measured above the forest indicated a strong carbon sink of -660 (-535) g C m y with small interannual variability ±78 (72) g C m y (values in brackets including correction for self-heating of the open-path gas analyzer). In the first year after partial deforestation, regrowth on the clearcut consisted mainly of grasses, with beginning of the second year shrubs and young trees became increasingly important. The regrowth of vegetation is reflected in the annual sums of NEE, which decreased from a carbon source of 521 (548) g C m y towards 82 (236) g C m y over the past four years, due to an increase in the magnitude of GPP from 385 (447) to 892 (1036) g C m y .
    Keywords: Net Ecosystem Exchange (Nee) ; Natural Succession ; Soil Respiration ; Gross Primary Production (Gpp) ; Ecosystem Respiration ; Radiative Forcing ; Agriculture ; Meteorology & Climatology
    ISSN: 0168-1923
    E-ISSN: 1873-2240
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages