Atmospheric Remote Sensing
Airborne trace gas measurements and mesoscale modelling
Inverse data-driven estimation
Integrating surface-atmosphere Exchange Processes Across Scales - Modeling and Monitoring
Tall Tower Atmospheric Gas Measurements
Carbon Cycle Data Assimilation
Satellite-based remote sensing of greenhouse gases
Tonatiuh Guillermo Nuñez Ramirez
Phone: + 49 3641 576322
Global inverse modeling of methane (CH4) fluxes with the additional constraints of the δ13CH4 isotopic signal and the ethane (C2H6) mixing ratio.
I use atmospheric observations of the CH4 and C2H6 (a co-emitted hydrocarbon) mixing ratio and the δ13CH4 isotopic signal to derive the sources driving the observed variability in these tracers in a Bayesian inverse modeling framework. The spatiotemporal patterns extracted from the inversion can be used to elucidate the biogeochemical processes controlling natural sources, primarily wetlands. The ability to quantify anthropogenic emissions is also important in the discussion to set emission reduction targets at global or regional scale.
I have a very interdisciplinary background, which includes mechatronic systems, satellite engineering, earth system science and biogeochemical cycles.