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Geoscientific Instrumentation, Methods and Data Systems An interactive open-access journal of the European Geosciences Union
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GI | Articles | Volume 9, issue 1
Geosci. Instrum. Method. Data Syst., 9, 239–254, 2020
https://doi.org/10.5194/gi-9-239-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Instrum. Method. Data Syst., 9, 239–254, 2020
https://doi.org/10.5194/gi-9-239-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 29 May 2020

Research article | 29 May 2020

Soil CO2 efflux errors are lognormally distributed – implications and guidance

Thomas Wutzler et al.

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.
Continuous data of soil CO2 efflux can improve model prediction of climate warming, and...
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