Powerful. Intuitive. Flexible. Eddy Covariance Flux Processing Software EddyPro Software - Page 1

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
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