Geoscientific Instrumentation, Methods and Data Systems
Geoscientific Instrumentation, Methods and Data Systems
GI
Articles | Volume 9, issue 1
Articles | Volume 9, issue 1
https://doi.org/10.5194/gi-9-239-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gi-9-239-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 9, issue 1
Research article
 | 
29 May 2020
Research article |  | 29 May 2020

Soil CO2 efflux errors are lognormally distributed – implications and guidance

Thomas Wutzler, Oscar Perez-Priego, Kendalynn Morris, Tarek S. El-Madany, and Mirco Migliavacca

Supplement

https://doi.org/10.5194/gi-9-239-2020-supplement

Data sets

Data for "Soil CO2 efflux errors are lognormally distributed - Implications and guidance." T. Wutzler, O. Perez-Priego, K. Morris, T. S. El-Madany, M. Migliavacca, M. Schrumpf, M. Pöhlmann, E. Weber, and A. Carrara https://doi.org/10.5281/zenodo.3735751

Model code and software

bgctw/lognorm: GID publication T. Wutzler https://doi.org/10.5281/zenodo.3735804

bgctw/RespChamberProc: GID publication T. Wutzler and T. T. Rademacher https://doi.org/10.5281/zenodo.3735807

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Short summary
Continuous data of soil CO2 efflux can improve model prediction of climate warming, and automated data are becoming increasingly available. However, aggregating chamber-based data to plot scale pose challenges. Therefore, we showed, using 1 year of half-hourly data, how using the lognormal assumption tackles several challenges. We propose that plot-scale SO2 efflux observations should be reported together with lognormally based uncertainties and enter model constraining frameworks at log scale.
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