Location: Soil, Water & Air Resources ResearchTitle: A new eddy-covariance method using empirical mode decomposition Author
Submitted to: Boundary Layer Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/10/2012
Publication Date: 6/22/2012
Citation: Barnhart, B.L., Eichinger, W.E., Prueger, J.H. 2012. A new eddy-covariance method using empirical mode decomposition. Boundary Layer Meteorology. Available: http://www.springerlink.com/content/b276k3578r01658w/. DOI:10.1007/s10546-012-9741-6. Interpretive Summary: Heat and water vapor turbulent transport require fast response (20 Hz) measurements of wind velocity, temperature and water vapor using an approach called eddy covariance. Interpreting these types of measurements have used traditional signal processing techniques involving spectral analysis. A new type of spectral processing technique was found to calculate contributions of turbulent transport of heat and water vapor. This approach allows for improved estimates of heat and water vapor transport by calculating all contributions and thereby avoiding the undersampling of the data. This approach will improve evaporation estimates that will benefit farmers in understanding water use by crops and scientists studying surface energy balance closure issues.
Technical Abstract: We introduce a new eddy-covariance method that uses a spectral decomposition algorithm called empirical mode decomposition. The technique is able to calculate contributions to near-surface fluxes from different periodic components. Unlike traditional Fourier methods, this method allows for non-orthogonal contributions to the total flux, which are shown to be errors due to the undersampling of low-frequency processes. Inspection of the non-orthogonal terms with relation to sampling duration and periodicity reveals that a measured periodic process requires approximately six cycles in order to be sufficiently sampled. This determines the maximum eddy size sufficiently measured given a particular sampling duration.