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Peter Isaac edited this page Jun 11, 2022 · 7 revisions

Welcome to the PyFluxPro wiki! This wiki is intended to help new users of PyFluxPro become familiar with how the software works and what options are available.

PyFluxPro takes data recorded at a flux tower and processes this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). Note that PyFluxPro does not calculate fluxes from turbulence data. You will need to use EddyPro (available from LI-COR), EasyFlux-PC (available from Campbell Scientific) or another flux processing package (EdiRE, TK3 etc) to process the turbulence data to average fluxes before using PyFluxPro to quality control, post-process, gap fill and partition these data.

The flux tower data can come from a Campbell Scientific system (including the new EasyFlux-DL systems), a LI-COR GHG system or something you have built yourself. The input flux data can be in the form of an Excel workbook (the easiest way) or one or more CSV files if you really hate Excel. Output from PyFluxPro is mainly as netCDF files (https://www.unidata.ucar.edu/software/netcdf/) with the option to convert these to Excel workbooks if this is preferred.

You can use the side bar to the right to navigate through this Wiki. If you have suggestions or comments or want to offer help, contact Peter Isaac (pisaac.ozflux@gmail.com).

And now a taste of the things PyFluxPro can do for you. Note that all plots were produced by PyFluxPro.

Figure 1: Cumulative NEE, GPP, ER, Precip and ET by year for the Cumberland Plain site.

Figure 2: Carbon budget for Cumberland Plain for 2012 to 2021 as a time series.

Figure 3: Carbon budget for Cumberland Plain for 2012 to 2021 as fingerprints.

Figure 4: Turbulent fluxes for the Calperum site after quality control and before gap filling. Note that the u* filter is not applied to Fco2 until the gap filling stage. The large gap in early 2014 was caused by a wild fire that damaged the site.

Figure 5: Cumulative carbon budget for the Calperum site, quantities with the suffix SOLO use a neural network to estimate ER, suffix LT uses the Lloyd-Taylor respiration model and LL uses the Lasslop et al (2010) method.

Figure 6: Windroses for the Calperum site.

Figure 7: Plot of the turbulent fluxes for the Loxton site produced automatically during post-processing.

Figure 8: Plot of the Fco2 diagnostics for the Loxton site produced automatically during the quality control stage.

And many, many more ...

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