EasyFlux DL

EasyFlux™ DL is a free CRBasic program that enables a data logger to report fully corrected fluxes of CO₂, latent heat (H₂O), sensible heat, and momentum from a Campbell Scientific open-path and closed-path eddy-covariance (EC) system. Final fluxes are processed from raw high frequency time series data by applying commonly used corrections found in scientific literature.

In the past, Campbell Scientific's data logger EC programs roughly estimated fluxes, and PC post-processing software was used to fully correct the flux measurements. Now with the EasyFlux DL program, fully corrected fluxes are processed by the data logger and reported at the end of each EC averaging interval.

EasyFlux DL has been tested at several stations in various environments, including irrigated alfalfa, grassland, maize, open water, forest, and desert. The results have shown good agreement with fluxes processed using traditional PC-based software applications.

To download EasyFlux DL, refer to the Downloads section.

Fully Corrected Fluxes
Data logger program that computes fully corrected fluxes of CO₂, latent heat, and sensible heat

Provides fully corrected outputs of CO₂ flux, latent heat flux, and sensible heat flux at a user-defined interval (e.g., 30 minutes). Also provides many other variables of atmospheric properties, instrument diagnostics, intermediate corrections, and other energy balance or biomet sensors. Comparisons of flux outputs have shown good agreement with other common post-processing software packages when applying the same set of corrections.

Main correction and processing procedures:

• Despike and filter high frequency time series data using sonic anemometer and gas analyzer diagnostic codes, signal strengths, and measurement output range thresholds.
• Apply coordinate rotations with an option to use the double rotation method (Tanner and Thurtell, 1969) or planar fit method (Wilczak et al., 2001).
• Lag CO₂ and H₂O measurements against sonic wind measurements for maximization of CO₂ and H₂O fluxes (Horst and Lenschow, 2009; Foken et al., 2012), with additional constraints to ensure lags are physically possible.
• Apply frequency corrections using commonly used cospectra (Moore, 1986; van Dijk, 2002; Moncrieff et al., 1997) and transfer functions for block averaging (Kaimal et al., 1989), line/volume averaging (Moore, 1986; Moncrieff et al., 1997; Foken et al., 2012; van Dijk, 2002), low-pass filter (Ibrom et al. 2007; FOR CPEC ONLY), time constants (Montgomery, 1947; Shapland et al., 2014; Geankoplis, 1993, Burgon et al. 2016), and sensor separation (Horst and Lenschow, 2009; Foken et al., 2012).
• Apply a modified SND correction (Schotanus et al., 1983) to derive sensible heat flux from sonic sensible heat flux following the implementation as outlined in van Dijk (2002). Additionally, fully corrected sensible heat flux computed from a fine-wire thermocouple is provided if our FW05, FW1, or FW3 is used.
• Apply correction for air density fluctuations using Webb et al., 1980.
• Assign data quality classifications (QC) based on steady state conditions and surface layer turbulence characteristics following Foken et al., 2002 to conform to AmeriFlux format. In addition, Foken et al., (2012) is also followed to include wind direction. An additional set of QC is provided.
• Calculate footprint characteristics using Kljun et al., 2004 or Kormann and Meixner, 2001.
• If energy balance sensors are used, calculate energy closure based on energy balance measurements and corrected sensible and latent heat fluxes.
• Sonic shadow correction is optional.
• CO₂ spectroscopic correction using air temperature at high frequency nature as default and at convention as an option. CO₂ values corrected using different air temperature are all stored at the measured frequency.