|From||Erich Fischer <email@example.com>|
|Date||Fri, 20 Apr 2018 14:45:27 +0200|
PhD in Climate Science – Understanding and quantifying low probability-high impact extremes
https://apply.refline.ch/845721/6175/pub/1/index.htmlThe overall objective is to improve our understanding and the quantification of the occurrence of low probability-high impact extremes in a changing climate. The project combines novel climate model experiments with advanced methods of extreme value analysis in order to advance research on temperature and precipitation extremes beyond the traditionally studied moderate definitions. (A) The objective of the first PhD project is to improve our understanding of the physical mechanisms driving very rare extremes with a focus on atmospheric dynamics, surface energy budget, and anomalous land surface conditions. A novel approach is introduced and tested to efficiently generate very rare extremes using the NCAR CESM global climate model. Very long control simulations and large ensembles are used as a testbed to identify physical constraints leading to potential upper bounds in extremes and how they are affected by climate change. (B) The objective of the second PhD project is to identify strengths and limitations of stationary and non-stationary extreme value analysis in estimating return levels of very rare events and to quantify temporal clustering and compound aspects of very rare extremes. Limitations of stationarity and added value of non-stationary extreme value analysis using process-based covariates will be analysed using very long climate model simulations as testbeds. Finally, the project will further explore characteristics of low-probability high-impact extremes that arise through temporal clustering and compound aspects of multivariate extremes.
Successful applicants have a Master’s degree, Diploma or equivalent in physics, climate sciences, or related subjects, ideally experience with UNIX/Linux operating systems, shell scripting and advanced statistics and data analysis systems (such as NCL, Python, R, etc.). Regardless of background, the successful applicant will have an interactive personality, motivation to work with cutting-edge numerical climate models and their output, the ability to carry out research in an interdisciplinary and international environment, and a strong desire to disseminate results in conference talks and journal articles. Fluency in English (written and spoken) and strong communication skills are required.
We offer a dynamic and inspiring research environment, excellent work conditions, supercomputing infrastructure, and a large degree of freedom for the successful candidate to bring in her/his own research ideas and experience. The positions are fully funded for 3-4 years, the typical time to complete a PhD at ETH. Starting date is summer or autumn 2018. The Institute for Atmospheric and Climate Science www.iac.ethz.ch is a world-leading institute in the field of research on global and regional climate change. ETH Zurich offers leading-edge research infrastructure and a comprehensive education at postgraduate level as one of the leading international universities for natural sciences and technology. Scientific computing support is provided.
We look forward to receiving your online application including a CV, publication list, a PDF file of your Master’s thesis, an academic transcript of your studies, a one page statement on your motivation, past research experience and research interests (in English), and contact details of three persons (academic if possible) that may be contacted for reference. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. Review of applications will continue until the positions are filled.
For further information, please contact Dr. Erich Fischer by e-mail firstname.lastname@example.org (no applications) and visit our website www.iac.ethz.ch.
Erich Fischer http://www.iac.ethz.ch/people/fischer Reto Knutti http://www.iac.ethz.ch/people/knuttir
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