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Abstract The Monin‐Obukhov Similarity Theory (MOST) links turbulent statistics to surface fluxes through universal functions. Here, we investigate its performance over a large lake, where none of its assumptions (flat homogeneous surface) are obviously violated. We probe the connection between the variance budget terms and departure from the nondimensional flux‐variance function for CO2, water vapor, and temperature. Our results indicate that both the variance storage and its vertical transport affect MOST, and these terms are most significant when small fluxes and near neutral conditions were prevalent. Such conditions are common over lakes and oceans, especially for CO2, underlining the limitation of using any MOST‐based methods to compute small fluxes. We further show that the relaxed eddy accumulation (REA) method is more robust and less sensitive to storage and transport, adequately reproducing the eddy‐covariance fluxes even for the smallest flux magnitudes. Therefore, we recommend REA over MOST methods for trace‐gas flux estimation.
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Numerical Investigation of Observational Flux Partitioning Methods for Water Vapor and Carbon Dioxide
While yearly budgets of CO$$_2$$ flux ($$F_c$$) and evapotranspiration ($ET$) above vegetation can be readily obtained from eddy-covariance measurements, the separate quantification of their soil (respiration and evaporation) and canopy (photosynthesis and transpiration) components remains an elusive yet critical research objective. In this work, we investigate four methods to partition observed total fluxes into soil and plant sources: two new and two existing approaches that are based solely 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 CO$$_2$$ and water vapor. In addition, best performances 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 CO$$_2$$ and water vapor can be used to infer the reliability of different $$W$$ parameterizations.
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- Award ID(s):
- 2128345
- PAR ID:
- 10539589
- Publisher / Repository:
- American Geophysical Union / Wiley
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Biogeosciences
- Volume:
- 129
- Issue:
- 6
- ISSN:
- 2169-8953
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1029/2024JG008025
