Abstract
The eddy-covariance method is the primary way of measuring turbulent fluxes directly. Many investigators have found that these flux measurements often do not satisfy a fundamental criterion—closure of the surface energy balance. This study investigates to what extent the eddy-covariance measurement technology can be made responsible for this deficiency, in particular the effects of instrumentation or of the post-field data processing. Therefore, current eddy-covariance sensors and several post-field data processing methods were compared. The differences in methodology resulted in deviations of 10% for the sensible heat flux and of 15% for the latent heat flux for an averaging time of 30 min. These disparities were mostly due to different sensor separation corrections and a linear detrending of the data. The impact of different instrumentation on the resulting heat flux estimates was significantly higher. Large deviations from the reference system of up to 50% were found for some sensor combinations. However, very good measurement quality was found for a CSAT3 sonic together with a KH20 krypton hygrometer and also for a UW sonic together with a KH20. If these systems are well calibrated and maintained, an accuracy of better than 5% can be achieved for 30-min values of sensible and latent heat flux measurements. The results from the sonic anemometers Gill Solent-HS, ATI-K, Metek USA-1, and R.M. Young 81000 showed more or less larger deviations from the reference system. The LI-COR LI-7500 open-path H2O/CO2 gas analyser in the test was one of the first serial numbers of this sensor type and had technical problems regarding direct solar radiation sensitivity and signal delay. These problems are known by the manufacturer and improvements of the sensor have since been made.
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The National Center for Atmospheric Research is supported by the National Science Foundation.
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Mauder, M., Oncley, S.P., Vogt, R. et al. The energy balance experiment EBEX-2000. Part II: Intercomparison of eddy-covariance sensors and post-field data processing methods. Boundary-Layer Meteorol 123, 29–54 (2007). https://doi.org/10.1007/s10546-006-9139-4
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DOI: https://doi.org/10.1007/s10546-006-9139-4