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Numerical Investigation of Observational Flux Partitioning Methods for Water Vapor and Carbon Dioxide
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  • Einara Zahn,
  • Khaled Ghannam,
  • Marcelo Chamecki,
  • Arnold F. Moene,
  • William P. Kustas,
  • Stephen Paul Good,
  • Elie Bou-Zeid
Einara Zahn
Princeton University

Corresponding Author:[email protected]

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Khaled Ghannam
Northeastern University
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Marcelo Chamecki
University of California, Los Angeles
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Arnold F. Moene
Wageningen University
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William P. Kustas
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Stephen Paul Good
Oregon State University
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Elie Bou-Zeid
Princeton University
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While yearly budgets of CO2 and evapotranspiration (ET) above forests can be readily obtained from eddy-covariance measurements, the quantification of their respective soil (respiration and evaporation) and canopy (photosynthesis and transpiration) components remains an elusive yet critical research objective. To this end, methods capable of reliably partitioning the measured ET and F_c fluxes into their respective soil and plant sources and sinks are highly valuable. In this work, we investigate four partitioning methods (two new, and two existing) that are based on analysis of conventional high frequency eddy-covariance (EC) data. The physical validity of the assumptions of all four methods, as well as their performance under different scenarios, are tested with the aid of large eddy simulations, which are used to replicate eddy-covariance field experiments. Our results indicate that canopies with large, exposed soil patches increase the mixing and correlation of scalars; this negatively impacts the performance of the partitioning methods, all of which require some degree of uncorrelatedness between CO2 and water vapor. In addition, best performance for all partitioning methods were found when all four flux components are non-negligible, and measurements are collected close to the canopy top. Methods relying on the water-use efficiency (W) perform better when W is known a priori, but are shown to be very sensitive to uncertainties in this input variable especially when canopy fluxes dominate. We conclude by showing how the correlation coefficient between CO2 and water vapor can be used to infer the reliability of different W parameterizations.
03 Feb 2024Submitted to ESS Open Archive
05 Feb 2024Published in ESS Open Archive