TRACE-Python: tracer-based rapid anthropogenic carbon estimation implemented in Python (version 1.0)

Sandborn, Daniel E.; Carter, Brendan R.; Warner, Mark J.; Dias, Larissa M.

doi:10.5194/gmd-19-5961-2026

Articles | Volume 19, issue 13

https://doi.org/10.5194/gmd-19-5961-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-5961-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 13

Development and technical paper

|

08 Jul 2026

Development and technical paper |

| 08 Jul 2026

TRACE-Python: tracer-based rapid anthropogenic carbon estimation implemented in Python (version 1.0)

Daniel E. Sandborn, Brendan R. Carter, Mark J. Warner, and Larissa M. Dias

Data sets

Global Ocean Anthropogenic Carbon Concentrations from Preindustrial to 2500 c.e. Estimated Using TRACE-Python Daniel Sandborn et al. https://doi.org/10.5281/zenodo.17246805

Model code and software

d-sandborn/TRACE: Tracer-based Rapid Anthropogenic Carbon Estimation (TRACE) (v1.0.0) Daniel Sandborn et al. https://doi.org/10.5281/zenodo.17822675

BRCScienceProducts/TRACEv1: TRACEv1_publication Brendan R. Carter https://doi.org/10.5281/ZENODO.15692788

Short summary

We present a new implementation of our method for estimation of human-created carbon dioxide in the ocean. Tracer-based Rapid Anthropogenic Carbon Estimation relies on transient tracer measurements to infer gas exchange and circulation. Our work implements practical and fundamental improvements increasing accessibility, flexibility, and skill of the method. We provide an updated data product of global ocean carbon inventories spanning the industrial era and a range of future projections.