2 PhD positions in data assimilation / inverse modelling of the carbon cycle
The Carbon Cycle Data Assimilation group at the Department of Physical Geography and Ecosystem Science has two openings for PhD students with a strong background in Physical Geography and Ecosystems Analysis, Atmospheric sciences, Environmental Engineering, mathematics or physics.
Topic 1: Quantifying fossil fuel CO2 emissions based on atmospheric radiocarbon within a Fossil Fuel Data Assimilation System
The PhD student will work with an established model-data fusion method to exploit the complementary information of atmospheric radiocarbon (14CO2) observations for estimating fossil fuel CO2 emissions. The approach will build on the Fossil Fuel Data Assimilation System (FFDAS; Asefi-Najafabadi et al, JGR 2014) and the atmospheric transport inversion system LUMIA. The student will have the opportunity to collaborate with colleagues in the USA, Germany and Australia.
Topic 2: Model-Data Fusion for improving quantification of methane fluxes from wetlands with LPJ-GUESS
The PhD student will work with an established model-data fusion method to exploit the observational constraint of methane ecosystem flux measurements on model estimates of CH4 fluxes from wetlands via the optimisation of model process parameters. The approach will build on the Carbon Cycle Data Assimilation SYstem (CCDAS; Scholze et al. 2007. J. Geophys. Res. 112, D17305). The student will have the opportunity to collaborate with colleagues in Germany and the Netherlands.
The PhD positions are for 4 years, with a preferred starting date of 1 March 2019.
Closing date for applications: 20 January 2019
More information can be found here: