Doctoral student in Physical Geography and Ecosystem Science - Hiring in process/Finished, not possible to apply

The PhD student will carry out research within the project “ Model-Data Fusion for improving quantification of methane fluxes from wetlands with LPJ-GUESS, CH4DAS” which is a newly funded collaborative project between the Department of Physical Geography and Ecosystem Science (INES) and the Centre for Mathematical Sciences at Lund University. This PhD student position forms part of an investment in 6 PhD students within the strategic research area of BECC (Biodiversity and Ecosystem Services in a Changing Climate). BECC is an interdisciplinary strategic research environment between Lund and Gothenburg University, whose goal is to assess the impact of climate change on biodiversity and ecosystem services, with particular focus on forest, agricultural and sub-arctic ecosystems, but also related issues in urban environments and how drainage from forest and agricultural land affect aquatic systems. By bringing together researchers from several complementary subject areas in the natural sciences, political science and economics, the connections between climate/ecosystem/biodiversity can be studied on different scales including both basic and applied research. The research within this project also links to the activities of the Carbon Portal of the Integrated Carbon Observation System (ICOS), a European infrastructure for measurement and analysis of greenhouse gas concentration and fluxes from ecosystems and oceans, and to ICOS-Sweden, both hosted at INES. The position is embedded within the inverse modelling group at INES and there is the possibility of establishing international collaborations with colleagues in Germany and the Netherlands.

Jobassignment

Methane (CH4) is a key component of the global carbon cycle and one of the most important greenhouse gases. An increased atmospheric burden of CH4, caused by increased emissions, intensifies the Earth’s greenhouse effect causing a shift in the planetary energy balance involving complex interactions and feedbacks. The amounts of CH4 that conceivably could be released from boreal wetlands are potentially very large. A better understanding of CH4 emissions from wetlands is of paramount importance. It is only since recent years that model-data fusion techniques have successfully been applied to improve our understanding in the global CO2 cycle. In this project, the PhD student will develop a prototype CH4 Data Assimilation System assimilating CH4 flux observations.

In particular, the PhD student will, in collaboration with ecosystem modellers and mathematical statisticians, work with and refine an established model-data fusion method (here based on a Monte Carlo approach) 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 research will lay out the basis for a methane cycle data assimilation system (CH4DAS, analogue to CCDAS; Scholze et al. 2007, J. Geophys. Res. 112, D17305). Data assimilation can be seen as a way of combining observations with ‘prior’ information (i.e. process model formulation and prior model process parameter value) to derive updated (‘posterior’) parameter values that are consistent with the observations. Initial work will focus on using CH4 measurements from one wetland site as part of the ICOS network, scaling up to a broader regional or pan-boreal scale.

A PhD student is committed to conduct independent and original scientific research, to present this research at international conferences and report on it in international scientific journals, and to publish the results of the research in a PhD dissertation, to be completed within 4 years.

Desirable skills and qualifications

• Candidates are expected to hold a university degree (preferably MSc. or equivalent) in a natural science subject such as Physical Geography and Ecosystem Analysis, Atmospheric Sciences, Environmental Sciences, Mathematics, Physics or a related subject of relevance to the research
• Good numerical skills with advanced knowledge of quantitative methods and computer programming experience, as well as interest in climate change and greenhouse gas emissions, are required.
• Knowledge of FORTRAN, Python, MATLAB and previous experience working with atmospheric transport models and large environmental datasets is an important advantage.
• Experience with optimization methods, terrestrial ecosystem models such as LPJ-GUESS or inverse modelling systems is an important advantage.
• Candidates must be fluent in written and spoken English.
• Candidates should have strong interest for climate science.
• We seek a well-motivated candidate who is able to work independently while contributing as part of a team.

Eligibility
Students with basic eligibility for third-cycle studies are those who

• have completed a second-cycle degree
• have completed courses of at least 240 credits, of which at least 60 credits are from second-cycle courses, or
• have acquired largely equivalent knowledge in some other way, in Sweden or abroad.

The employment of doctoral students is regulated in the Swedish Code of Statues 1998: 80. Only those who are or have been admitted to PhD-studies may be appointed to doctoral studentships. When an appointment to a doctoral studentship is made, the ability of the student to benefit from PhD-studies shall primarily be taken into account. In addition to devoting themselves to their studies, those appointed to doctoral studentships may be required to work with educational tasks, research and administration, in accordance with specific regulations in the ordinance.

Type of employment
Limit of tenure, four years according to HF 5 kap 7§.