Eddy Covariance Processing Software | Version 5
EddyPro® is a powerful software application for processing eddy covariance data. It computes fluxes of water vapor (evapotranspiration), carbon dioxide, methane, other trace gases, and energy with the eddy covariance method.
EddyPro® in the Field
And at Your Desk
The SMARTFlux™ System brings EddyPro to your research site to provide fully processed flux results in real time.
EddyPro provides the full range of output and processing options for advanced data analysis.
EddyPro is available for free download from LI‑COR Biosciences:
Thank you for requesting a copy of EddyPro Software.
You will receive an email with a link to the software. If you do not receive an email within 24 hours please contact LI‑COR.
Version 5.1 | Released 3/4/2014
Over 2900 downloads in 155 countries.
Online help provides tutorials to help you learn EddyPro and to help you select the best settings for each project. It also provides a comprehensive explanation of data processing and a complete scientific reference.
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. Click here for more information about the ECO2S project.
Recent Advancements Include:
- Support for the SMARTFlux system, for real-time fluxes computed in the field using Advanced or Express settings
- Integrate data from biological and meteorological (biomet) sensors at your site (ambient air temperature, relative humidity, global radiation, etc.) into your flux computations
- Comprehensive spectral assessment using both analytical and in situ methods
- Built on the proven IMECC* platform with easy-to-learn and simple interface
- Seamless processing of LI-COR GHG files and support for multiple file types
- Integrated online help, videos and technical support from LI-COR
- Complete set of processing options, including frequency response correction, footprint estimation, random error estimation, and quality flagging
* Infrastructure for Measurement of the European Carbon Cycle
Dec 14, 2011
The Eddy Covariance Method:
EddyPro 3.0 Data Processing Software with Advanced Settings
Gerardo Fratini & Dave JohnsonWatch this
May 26, 2011
The Eddy Covariance Method:
EddyPro Data Processing Software
Gerardo Fratini & Israel BegashawWatch this
Data Processing Options in EddyPro (Express Mode selections in italics)
- Axis rotation for sonic anemometer tilt correction
- Double rotation
- Triple rotation
- Sector-wise planar fit (Wilczak et al., 2001)
- Sector-wise planar fit with no velocity bias (van Dijk et al., 2004)
- Detrending of raw time series
- Block averaging
- Linear detrending
- Running mean
- Exponential running mean
- Compensation of time lag between sonic anemometer and gas analyzer measurements
- Automatic time lag optimization (optionally as a function of RH for H2O)
- Maximum covariance with default (circular correlation)
- Maximum covariance without default
- None (option to not apply compensation)
- Statistical tests for raw time series data (Vickers and Mahrt, 1997)
- Spike count/removal
- Amplitude resolution
- Absolute limits
- Skewness and kurtosis
- Time lags
- Angle of attack
- Steadiness of horizontal wind
- Individually selectable and customizable
- 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
- Ensemble averaged spectra
- Ensemble averaged cospectra, fitted models and ideal (Kaimal) cospectra
- Details of steady state and turbulence tests
- Raw data time series after each statistical tests/correction
- Averaged biomet data
- Compensation for air density fluctuations
- Webb et al., 1980 (open path) / Ibrom et al., 2007a (closed path)
- Use (or convert to) mixing ratio (Burba et al., 2012)
- 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. (2007b)
- Horst and Lenschow (2009)
- Fratini et. al. (2012)
- Quality control tests for fluxes according to Foken et al. (2004)
- Flagging according to Carbo Europe standard (Mauder and Foken, 2004)
- Flagging according to Foken (2003)
- Flagging after Göckede et al. (2004)
- Random uncertainty estimation
- Mann and Lenschow (1994)
- Finkelstein and Sims (2001)
- Flux footprint estimation
- Kljun et al. (2004)
- Kormann and Meixner (2001)
- Hsieh et al. (2000)
- Other options applied in both Express and/or Advanced Mode include:
- Sonic temperature correction for humidity following van Dijk et al. (2004)
- Spectroscopic correction for LI-7700 following McDermitt et al. (2011)
- Angle of attack corrections for Gill anemometers following Nakai et al. (2006)
- Angle of attack corrections for Gill anemometers following Nakai and Shimoyama (2012)
- Inclusion of biomet data for improved flux computation/correction
Burba et al. (2008) – Global Change Biology, 14:1854–1876.
Burba et al. (2012) – Global Change Biology, 18:385-399.
Finkelstein and Sims (2001) – Journal of Geophysical Research, 106:3,503 – 3,509.
Foken (2003) – Angewandte Meteorologie, Mikrometeorologische Methoden, 289 pp.
Foken et al. (2004) –Handbook of micrometeorology: A guide for surface flux measurements, 81-108.
Fratini et al. (2012) – Agricultural and Forest Meteorology, 165: 53-63
Göckede et al. (2004) – Agricultural and Forest Meteorology, 127: 175-188.
Hsieh et al. (2000) – Advances in Water Resources, 23: 765-772.
Horst (1997) – Boundary Layer Meteorology, 82: 219-233.
Horst and Lenschow (2009) – Boundary Layer Meteorology, 130: 275-300.
Ibrom et al. (2007a) – Tellus Series B-Chemical and Physical Meteorology, 59:937-946.
Ibrom et al. (2007b) – Agricultural and Forest Meteorology, 147: 140-156.
Kljun et al. (2004) – Boundary Layer Meteorology, 112: 503-523.
Kormann and Meixner (2001) – Boundary Layer Meteoroogy, 99:207–224.
Mann and Lenschow (1994) – Journal of Geophysical Research, 99:14,519–14,526.
Mauder and Foken (2004) - Documentation and Instruction Manual of the Eddy Covariance Software Package TK2, Arbeitsergebnisse Nr. 26.
McDermitt et al. (2011) – Applied Physics B: Laser and Optics, 102: 391-405.
Moncrieff et al. (2004) – Handbook of micrometeorology, 7-31.
Moncrieff et al. (1997) – Journal of Hydrology, 188-189: 589-611.
Nakai et al. (2006) – Agricultural and Forest Meteorology, 136: 19-30.
Nakai and Shimoyama (2012) – Agricultural and Forest Meteorology, 162-163: 14-26
Van Dijk et al. (2004) – Meteorology and Air Quality Group, Wageningen, the Netherlands, 99 pp.
Vickers and Mahrt (1997) – Journal of Atmospheric and Oceanic Technology, 14: 512-526.
Webb et al. (1980) – Quarterly Journal of the Royal Meteorological Society, 106: 85-100.
Wilczak et al. (2001) - Boundary Layer Meteorology, 99: 127-150.