35 research outputs found
Multiyear eddy covariance and meteorological dataset from agroforestry and open cropland or grassland in northern Germany
No full textDataset corresponding to the project SIGNAL (Sustainable intensification of agriculture through agroforestry), subproject TP1.2, entitled "CO2, H2O and energy exchange". Christian Markwitz collected and processed the data corresponding to the 1st phase, 2016-2018. Justus van Ramshorst collected and processed the data corresponding to the 2nd phase, 2019-2021. José Ángel Callejas-Rodelas collected and processed the data corresponding to the 3rd phase, 2022-2024. Lukas Siebicke and Alexander Knohl wrote the project proposals and contributed to data analysis and harmonization. Project funded by the German Ministry of Education and Research (BMBF), project BonaRes, module A (first phase: SIGNAL 031A562A, second phase: SIGNAL 031B0510A, third phase: SIGNAL 031B1063A)
Low-cost eddy covariance: a case study of evapotranspiration over agroforestry in Germany
No full textMicrometeorological measurements and numerical simulations of turbulence and evapotranspiration over agroforestry
No full textMicrometeorological measurements and numerical simulations of turbulence and evapotranspiration over agroforestry
No full textData set supporting journal article: Markwitz, C. and Siebicke, L.: "Low-cost eddy covariance: a case study of evapotranspiration over agroforestry in Germany", Atmos. Meas. Tech., 2019
No full text<p>This data set contains evapotranspiration data obtained by a conventional eddy covariance set-up and a low-cost eddy covariance set-up as described in the research article: Markwitz, C. and Siebicke, L.: "Low-cost eddy covariance: a case study of evapotranspiration over agroforestry in Germany", Atmos. Meas. Tech., 2019.</p>
<p>The data set contains all necessary data needed to replicate figures and analysis presented in the research article. The data sets are sorted and named according to the figure the data were used for. </p>This research was funded by the German Federal Ministry of Education and Research (BMBF, project
BonaRes, Modul A: Signal 031A562A)
Eddy covariance measurements of the dual-isotope composition of evapotranspiration
No full textMeasurements of the isotopic composition of water vapor (H2O) provide valuable insights into the hydrological cycle, whereas eddy covariance (EC) measurements are widely used to quantify biosphere-atmosphere exchange processes. Yet, the direct combination of water isotope approaches and the EC method remains technically challenging. Here, we present the first EC measurements of δ18O and δD of evapotranspiration (ET) over the full growing season of a beech forest in central Germany. This EC implementation is based on 2 Hz measurements of the mole fraction and isotopic composition of water vapor (CH2O,v, δD and δ18O) with a customized version of a commercially available water vapor isotope analyzer. The isotopic composition of ET showed a seasonal variability from −19 to 0‰ for δ18OET and from −140 to −25‰ for δDET. The setup-specific limitations of our measurements yield a mean bias of 0.03 mmol m−2 s−1 of the measured net water flux. Spectral and cospectral analysis showed that high-frequency dampening was less pronounced for our EC setup (which was equipped with heated tubing) than for the standard EC setup at this site. Thus, we conclude that direct EC measurements of the isotopic composition of ET are feasible for both, δ18OET and δDET. We propose that EC-based measurements of the isotopic composition of ET are feasible to improve our understanding of the hydrological cycle, especially where flux gradient methods show limited applicability. Our simultaneous measurements of δDET and δ18OET reveal the difference between transpiration-dominated and evaporation-dominated periods. This study highlights the potential of simultaneous measurements of δ18OET and δDET
Wind regimes above and below a dense oil palm canopy: Detection of decoupling and its implications on CO2 flux estimates
No full textDoes increased spatial replication above heterogeneous agroforestry improve the representativeness of eddy covariance measurements?
No full text
