A fully automated reproducible self-documenting workflow implemented in our inverse regional carbon model

The Integrated Carbon Observation System (ICOS) and the Lund University department of Physical Geography and Ecosystem Science have developed the Lund University Modular Inversion Algorithm (LUMIA) that is being used for the inverse modelling of carbon and isotope resolved methane. The work is linked with past and present Horizon 2020 projects like DICE and AVENGERS with the overarching goal of supporting the Paris agreement goals.

The ICOS Carbon Portal (https://data.icos-cp.eu/portal) collects, maintains and supports a large range of greenhouse gas observations as well as some inventory and model data all of which have a unique persistent identifier each, which is a key pre-requisite for achieving a reproducible work-flow.

Here we present a self-documenting fully reproducible work-flow for our inverse carbon model LUMIA, that is based on frameworks discussed in EU initiatives like Copernicus CAMS and CoCO2 as well as our own experiences from actual work-flows routinely used in Australian court cases against illegal land use changes. We will show a live demonstration of the system including its graphical user interfaces and the created provenance and reproducibility meta-data.