The Eddy Covariance Method EddyPro™ Software - Page 1 Eddy Covariance Flux Processing Software Powerful. Intuitive. Flexible. EddyPro™ 3.0 is a powerful software application for processing eddy covariance data. It computes fluxes of momentum, carbon dioxide, water vapor, methane, and other trace gases with the eddy covariance method. Building upon the success of the initial release (EddyPro Express), EddyPro adds multiple advanced options to fit a wide variety of sites and systems. EddyPro still maintains the simplicity and ease of EddyPro Express by providing two processing modes. In Express Mode, EddyPro quickly processes data with commonly used processing selections. In Advanced Mode, a large variety of choices are provided for researchers who need flexibility and control over the data processing options. EddyPro is specially optimized for data collected in LI-COR GHG formats from LI-COR Analyzers. Why EddyPro™? Built on the proven IMECC* platform; Results validated against EdiRE and other commonly accepted flux processing software tools Extensive data processing options (see descriptions on back) Intuitive interface - Easy to learn & simple to use Integrated online help with video tutorials Seamless processing of LI-COR GHG files (.ghg files are raw flux data files, collected by LI-COR Analyzers, compressed and zipped with a corresponding metadata file) *Infrastructure for Measurements of the European Carbon Cycle Support for multiple raw data formats (Generic ASCII, Generic Binary, TOB1, SLT) Output includes fluxes, quality flags, footprint estimations, full and binned spectra, co-spectra, binned Ogives Data output is compliant with GHG-Europe and AmeriFlux standard data submission formats Backed by the LI-COR Technical Support team EddyPro Software - Page 2 The Eddy Covariance Method Data Processing Options in EddyPro™ 3.0 (Express Mode selections in italics) Axis rotation for sonic anemometer tilt correction Double rotation Triple rotation Sector-wise planar fit (Wilczak et al 2010) Sector-wise planar fit with no velocity bias (van Dijk et al. 2004) Detrending of raw time series Block averaging Linear detrending Running mean Exponentially running mean Compensation of time lag between sonic anemometer and gas analyzer measurements Maximum covariance with default (circular correlation) Maximum covariance without default Constant None (Option to not apply compensation) Statistical tests for raw time series data Spike count/removal Amplitude resolution Dropouts Absolute limits Skewness and kurtosis Discontinuities Time lags Angle of attack Steadiness of horizontal wind None (Option to not apply tests) Available outputs Full (rich) output with fluxes, quality flags and much more (standard format or available results only) Ameriflux format GHG Europe format Raw data Statistics Full Length Spectra and Co-Spectra Binned Spectra and Co-Spectra Binned Ogives Details of steady state and turbulence tests Details of steady state and turbulence tests Raw data time series after each statistical tests/correction Compensation of gas analyzer measurements for density fluctuations Webb et al., 1980 (open path) / Ibrom et al., 2007 (closed path) Use (or convert to) mixing ration (Burba et al. 2011) Optional off-season upatake correction for LI-7500 (Burba et al. 2008) None (Option to not apply compensation) Correction for frequency response (attenuation) Analytic high-pass filtering correction (Moncrieff et al., 2004) Low-pass filtering, select and configure: Moncrieff et al. (1997) Horst (1997) Ibrom et al. (2007) Horst and Lenschow (2009) Quality control flags for computed fluxes Tests according to Mauder and Foken (2004) Flagging according to Foken (2003) Flagging after Göckede et al. (2006) Flux footprint estimation Kljun et al. (2004) Kormann and Meixner (2001) Hsieh et al. (2000) Other options applied in both Express and Advanced Mode include: Sonic temperature correction for humidity following van Dijk et al. (2004) Spectroscopic correction for LI-7700 following McDermitt et al. (2010) Angle of attack corrections References: Foken, T., M. Göckede, M. Mauder, L. Mahrt, B. D. Amiro, and J. W. Munger. 2004. Post-field data quality control. In X. Lee, et al. (ed.), Handbook of Meteorology. 35: 409-414. Moncrieff, J. B., R. Clement, J. Finnigan, and T. Meyers. 2004. Averaging, detrending and filtering of eddy covariance time series, in Handbook of micrometeorology: A guide for surface flux measurements, eds. Lee, X., W. J. Massman and B. E. Law. Dordrecht: Kluwer Academic, 7-31. Fratini, G., N. Arriga, C. Trotta, D. Papale. 2010. Underestimation of water vapour fluxes by eddy covariance closed-path systems due to relative humidity effects. American Geophysical Union Fall Meeting. Moncrieff, J. B., J. M. Massheder, H. de Bruin, J. Elbers, T. Friborg, B. Heusinkveld, P. Kabat, S. Scott, Abstract #B11D-0400. H. Soegaard, and A. Verhoef. 1997. A system to measure surface fluxes of momentum, sensible heat, water vapor and carbon dioxide. Journal of Hydrology, 188-189: 589-611. Göckede, M., C. Rebmann, T. Foken, 2004. A combination of quality assessment tools for eddy covariance measurements with footprint modelling for the characterisation of complex sites. Agricultural and Forest Meteorology, 127: 175-188. Horst, T. W. 1997. A simple formula for attenuation of eddy fluxes measured with first-order-response scalar sensors. Boundary Layer Meteorology, 82: 219-233. Ibrom, A., E. Dellwik, H. Flyvbjerg, N. O. Jensen, and K. Pilegaard. 2007. Strong low-pass filtering effects on water vapour flux measurements with closed path eddy covariance systems. Agricultural and Forest Meteorology, 147: 140-156. Kaimal, J. C., and J. E. Gaynor. 1991. Another look at sonic thermometry, Boundary Layer Meteorology, 56: 401-410. Kljun, N., P. Calanca, M. W. Rotach, and H. P. Schmid. 2004. A simple parameterization for flux footprint predictions. Boundary Layer Meteorology, 112: 503-523. Schuepp, P. H., M. Y. Leclerc, J. I. MacPherson, and R. L. Desjardins. 1990. Footprint prediction of scalar fluxes from analytical solutions of the diffusion equation. Boundary Layer Meteorology, 50: 355-373. Van Dijk, A., A. F. Moene, and H. A. R. de Bruin. 2004. The principles of surface flux physics: Theory, practice and description of the ECPACK library, Internal Report 2004/1, Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands, 99 pp. Vickers, D. and L. Mahrt. 1997. Quality control and flux sampling problems for tower and aircraft data. Journal of Atmospheric and Oceanic Technology, 14: 512-526. Webb, E. K., G. I. Pearman, and R. Leuning. 1980. Correction of flux measurements for density effects due to heat and water vapour transfer. Quarterly Journal of the Royal Meteorological Society, 106: 85-100. McDermitt, D., G. Burba, L. Xu, T. Anderson, A. Komissarov, B. Riensche, J. Schedlbauer, G. Starr, D. Zona, and W. Oechel, S. Oberbauer, and S. Hastings. 2010. A new low-power, open path instrument for measuring methane flux by eddy covariance. Applied Physics B: Laser and Optics, 102: 391-405. EddyPro™ is an open source software application developed, maintained and supported by LI-COR Biosciences. It originates from ECO2S, the Eddy COvariance COmmunity Software project, which was developed as part of the Infrastructure for Measurement of the European Carbon Cycle (IMECC-EU) research project. We gratefully acknowledge the IMECC consortium, the ECO2S development team, the University of Tuscia (Italy) and scientists around the world who assisted with development and testing of the original version of this software. 1-402-467-3576 www.licor.com 3/2012 982-11966