The water and carbon cycles are coupled by processes operating at different spatial and temporal scales ranging from plant stomata response to atmospheric carbon dioxide, and dryness to vegetation dynamics, and adaptation to long-term water cycle conditions. Consequently, the statistical relationships between water and carbon cycle variables emerge, while the mechanisms and feedbacks of carbon-water cycle interactions often remain unclear. This PhD research may address the questions: “Who drives whom and at which spatio-temporal scales?” and “How do carbon-water cycle interactions shape the variability and the relationships of key carbon and water cycle observations?”. The research will combine multiple carbon and water cycle observational data streams ranging from local measurements atmospheric carbon dioxide growth rate to satellite retrievals of terrestrial water storage variations through model-data fusion approaches. Within the research, a simple model will be optimized against these multiple constraints and thus acts to bridge across different and heterogeneous data streams. This ultimately should facilitate a joint interpretation of water-carbon interaction. The PhD work will be embedded in a joint initiative of the Global Diagnostic Modelling and the Model-Data-Fusion groups in the Department of Biogeochemical Integration at the MPI-BGC and would capitalize on previous work and experiences. The PhD research, in itself, would also contribute to other ongoing efforts in the groups. The PhD candidate should have experience with programming (e.g. MATLAB, Python, R) and with handling large and diverse data. A background in the carbon cycle, hydrology, ecohydrology, ecology, environmental physics, or related disciplines is advantageous along with experiences with modelling, model-data fusion, or remote sensing.
The Max Planck Society seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply. The Max Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals.