PhD project on data-driven upscaling of permafrost carbon fluxes

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PhD project on data-driven upscaling of permafrost carbon fluxes

Mathias Goeckede

PhD project on data-driven upscaling of permafrost carbon fluxes

 

The Max Planck Institute for Biogeochemistry in Jena, Germany, currently has an opening for a PhD project starting in summer or fall of 2017. We seek an enthusiastic student who will explore different pathways to optimize the use of observational data to constrain regional to pan-Arctic scale carbon budgets. As a core technique, this project will use data-driven approaches to assimilate information from various ground-based and remote sensing data sources to constrain greenhouse gas budgets. We will test what information is needed to adequately capture the dominating controls for carbon fluxes within permafrost landscapes, and also what is required to describe their spatio-temporal variability. Based on the findings, modeling frameworks will be restructured to improve representation of ecosystem characteristics. A direct comparison of data-driven approaches with process-based models and atmospheric inversion, both of which are covered by ongoing research within this research group, is regarded as a first step towards integrating these approaches into a unified framework, and therefore maximizing data assimilation on carbon processes in the Arctic. More information on this project, including required qualifications, can be found through this link:

 

http://www.imprs-gbgc.de/applications/imprs2017jan/projectdescriptions_outputone.php?PN=A2

 

This position is initially funded for three years. The successful candidate will be enrolled as a member of our institute’s graduate program, the international Max Planck Research School for global biogeochemical cycles (IMPRS-gBGC, http://www.imprs-gbgc.de/index.php/Main/Home). To apply, please go to the IMPRS webpage (http://www.imprs-gbgc.de/index.php/Application/HowTo), where the required documentation as well as the application procedure is described in detail. Application deadline is March 15, 2017.

 

For more questions on this PhD project, please contact Dr. Mathias Goeckede ([hidden email]).


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