Inverse data-driven estimation (IDE)

Atmospheric trace gas concentration data, taken regularly at many locations around the world, provide information about large-scale sources and sinks at the Earth surface. Taking account of atmospheric transport through a numerical transport model, these sources and sinks can be estimated quantitatively by inverse methods.

Carbon dioxide (CO₂) is a direct tracer of the carbon cycle and its variability. Regular measurements have been done at more than 100 sites globally by various institutions (including by our MPI Biogeochemistry Jena). Based on these data, we are estimating CO₂ sources and sinks, with a focus on their interannual variations. Relating source/sink variations to climatic variables (temperature, dryness, radiation, etc.) can reveal underlying driving mechanisms. The data-driven results can also be compared to simulations by process models. Our CO₂ flux estimates are available to other groups for use in collaborative projects documentation+download.

The information contained in the atmospheric measurements can also be combined with other sources of information, such as satellite-derived properties of the Earth surface. We are working on diagnostic models that allow to do this combination in a well-defined framework.

Further information about the carbon cycle can be gained by including data of other trace gases besides CO₂. For example, signals in atmospheric oxygen react to oceanic processes that are related to the carbon cycle due to common mechanisms. CO₂ and O₂ can be combined into a tracer called `Atmospheric Potential Oxygen' (APO) in such a way that the oceanic influence is singled out against the terrestrial signals.