Seminar: Danilo Custodio
- Datum: 07.12.2023
- Uhrzeit: 14:30
- Vortragende(r): Danilo Custodio
- (Zaehle department)
- Raum: Hörsaal (C0.001)
The presentation is crafted within the framework of the national initiative, the Integrated Greenhouse Gas Monitoring System for Germany – ITMS. This initiative's primary aim is to quantify greenhouse gas (GHG) fluxes between the Earth's surface and the atmosphere by combining atmospheric observations with inverse atmospheric transport modelling. Advancing our current understanding of the carbon budget, including anthropogenic emissions as well as natural fluxes, will allow for more accurate predictions of its future behaviour. The Jena CarboScope inversion has been developed in this context based on Bayesian inverse methods and is used to obtain data-driven estimates of sources and sinks of CO2 and CH4. This work focuses on using aircraft high vertical resolution profiles up to and beyond the boundary layer top to constrain atmospheric transport and reduce uncertainties/errors introduced in the full retrieval chain of the GHG inversion system.
To reduce the uncertainty in flux estimates as well as in the transport of atmospheric CO2 from the surface into the troposphere, the reliability of this data product should be evaluated based on independent observations. Quantifying the quality of the inversion estimation by decomposing the inherent uncertainty components is a challenging and key component in product reliability and its use. The overall objective in validating and evaluating uncertainties of the Bayesian data product provided by Jena CarboScope, is to explicitly answer the question: How good is the inversion estimation? The assessment of these products is of special importance for further development.
CarboScope strength and concerns are enhanced and spotted by
understanding the differences among observations and the inversion
estimation. In comprehensive statistics comparing measurement data from
hundreds of flights, we assess the compliance of CarboScope`s estimation
and parametrization. Furthermore, we discuss the estimation and
observation mismatches, exploiting the model constraints to reproduce
atmospheric transport from the boundary layer to the upper troposphere.
Understanding such constraints has the potential to reduce uncertainties
of the atmospheric inversion estimates.