Arctic climate extremes: the role of changing interactions between atmospheric modes

(MARSHALL_UBAS20ARIES)

Arctic climate extremes: the role of changing interactions between atmospheric modes

(MARSHALL_UBAS20ARIES)

Project Description

Supervisors

Dr Gareth Marshall, British Antarctic Survey

Prof Ian Renfrew, School of Environmental Sciences, University of East Anglia

Dr Scott Hosking, British Antarctic Survey

Dr Jones, Department of Geography, University of Sheffield

Scientific Background

During the past few decades the Arctic has experienced the greatest warming on Earth: the resultant sea ice loss, permafrost melting and snow cover changes have affected the regional hydrology, ecosystems and indigenous peoples. One of the primary drivers is changes in atmospheric circulation. A small number of studies have demonstrated that the interplay between some of the many different circulation patterns or modes that influence Arctic climate variability can markedly change both the magnitude and spatial extent of their impact. Thus, there is a clear need to fully understand the interactions between all these different atmospheric modes to better constrain projections of how the Arctic climate will evolve, and in particular climate extremes, which have the greatest impact on human and natural systems.

Research methodology

The successful candidate will aim to answer the question, “To what extent are atmospheric mode interactions responsible for recent and projected changes in Arctic climate extremes?”

They will employ statistical analyses to evaluate the interplay between the different atmospheric modes that impact Arctic climate. Utilising an array of historical meteorological observations, they will define the ‘key’ mode interactions that have had the greatest impact on Arctic climate extremes.

Subsequently, using a combination of regional climate modelling and machine learning techniques, the student will determine the regional ‘fingerprints’ that these large-scale interactions have on Arctic climate extremes. This will allow them to efficiently downscale output from an ensemble of global climate models, as used by the Intergovernmental Panel on Climate Change (IPCC), in order to analyse the magnitude and uncertainty that future changes in the ‘key’ mode interactions will have on Arctic climate extremes under different climate scenarios.

Training

In addition to the ARIES training programme, the candidate will have training opportunities in statistical methods, data analysis and visualisation techniques, climate modelling, machine learning tools for analysing ‘big data’ and public outreach.

Person specification

We are looking for enthusiastic, self-reliant, and self-motivated candidates with a strong numerical background in MTH, physics or the ENV. Previous programming experience in one of Python, MatLab, IDL or similar computing environment would be advantageous.

 

Successful candidates for this project will be hosted at the British Antarctic Survey, in Cambridge, UK

References

  • Comas-Bru L, & McDermott F. 2014. Impacts of the EA and SCA patterns on the European twentieth century NAO-winter climate relationship. Quarterly Journal of the Royal Meteorological Society, 140: 354‒363, doi:10.1002/qj.2158.
  • Marshall GJ, Kivinen S, Jylhä K, Vignols RM, & Rees WG. 2018. The accuracy of climate variability and trends across Arctic Fennoscandia in four reanalyses. International Journal of Climatology, 38: 3878‒3895, doi:10.1002/joc.5541.
  • Moore GWK, Renfrew IA, & Pickart RS. 2013. Multidecadal mobility of the North Atlantic Oscillation. Journal of Climate, 26: 2453‒2466, doi:10.1175/JCLI-D-12-00023.1.
  • Overland JE, & Wang M. 2005. The third Arctic climate pattern: 1930s and early 2000s. Geophysical Research Letters, 32: L23808, doi:10.1029/2005GL024254.
  • Turner J, & Marshall GJ. 2011. Climate Change in the Polar Regions. Cambridge University Press, pp 434.

Key Information

  • This project has been shortlisted for funding by the ARIES NERC Doctoral Training Partnership, and will involve attendance at mandatory training events throughout the course of the PhD.
  • Successful candidates who meet UKRI’s eligibility criteria will be awarded a NERC studentship - UK and EU nationals who have been resident in the UK for 3 years are eligible for a full award.
  • Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses in the subject area (see https://www.aries-dtp.ac.uk/supervisors/additional-funding/).
  • This studentship will start on 1st October 2020, and the closing date for applications is 12:00 on 7th January 2020.
  • Shortlisted applicants will be interviewed on 18/19 February 2020.
  • For further information, please contact the supervisor.
  • Please note that the joint NERC-ESRC ARIES-SeNSS studentship projects have different deadlines and funding arrangements. For full details please visit https://senss-dtp.ac.uk/aries-senss-joint-studentship, or contact SeNSS.dtp@uea.ac.uk.

Studentship Open for Applications

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