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Arctic mass, freshwater and heat fluxes in high-resolution global coupled climate models

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  • Full or part time
    Dr L Shaffrey
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (UK Students Only)
    Competition Funded PhD Project (UK Students Only)

Project Description

The Arctic is changing rapidly, which will have implications for the rest of the planet. For example, the recent loss of Arctic sea ice may impact on the mid-latitude atmospheric circulation. Understanding these changes requires trustworthy climate model predictions of the Arctic. However, the trust we can place in climate models depends on their ability to represent fundamental processes in the climate system. Such fundamental processes include the atmospheric and oceanic fluxes of freshwater, heat and mass into and out of the Arctic. The main goal of this PhD project is to evaluate the atmospheric and oceanic Arctic fluxes in a new generation of high-resolution coupled global climate models using recently available observational estimates. A particular focus will be the sensitivity of Arctic fluxes to model resolution both in the atmosphere and the ocean. Increasing model resolution holds great promise for representing the Arctic climate more realistically. In the atmosphere, the benefits of higher resolution have been demonstrated. This includes improving the position of the North Atlantic storm track thought to be important for atmospheric transports into the Arctic [Zappa et al., 2013]. Similarly, ocean transports are sensitive to model resolution, since they occur through four narrow straits (Fram, Davis, Bering Straits; Barents Sea Opening) which are only crudely resolved in coarse ocean models. The climate models used in this project are from the PRIMAVERA project, which are comprised of a multi-model ensemble with controlled increases in horizontal resolution. PRIMAVERA simulations have resolutions of down to 25km grid spacing in the atmosphere and ¼° in the ocean. This corresponds to a four to five fold increase in resolution over typical climate models in the Fifth Coupled Model Intercomparison Project (CMIP5). The initial objective will be to use observational estimates to evaluate the PRIMAVERA coupled ocean-ice-atmosphere climate models. [Bacon et al., 2015] have recently developed a method to calculate Arctic fluxes, applicable both to measurements and models. Modelled fluxes will also be compared with available independent observation-based estimates, for example from inverse modelling of ocean boundary fluxes [Tsubouchi et al., 2012] and atmospheric reanalyses. Later parts of the project will analyse the decadal variability of fluxes into the Arctic, including how high-resolution climate models represent key processes such as Bjerknes compensation between atmospheric and oceanic transports [Shaffrey and Sutton, 2006].

This project is collaboration between two prominent UK research Institutions in atmosphere, ocean and climate science and will provide a wide range of training and networking opportunities. The student will be based at the University of Reading with extended research visits to the National Ocean Centre in Southampton.

The project is supervised by Len Shaffrey (University of Reading), and co-supervised by Richard Schiemann (University of Reading), Sheldon Bacon (National Oceanography Centre), and Yevgeny Aksenov (National Oceanography Centre).

The full project description is available at:

Funding Notes

Funding would be via the NERC SCENARIO Doctoral Training Partnership This project also has CASE funding from the National Oceanography Centre.

To apply for this PhD project please visit

This project would be suitable for students with a natural science background from subjects like meteorology, oceanography, physics or mathematics, with demonstrated strong analytical skills and a keen interest to study the physical processes of the Arctic climate system. The student will also need to have or acquire the necessary programming and data analysis skills required for the quantitative analysis of large climate datasets.


Bacon, S., Y. Aksenov, S. Fawcett, and G. Madec (2015), Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 373(2052), 20140169, doi:10.1098/rsta.2014.0169.

Shaffrey, L., and R. Sutton (2006), Journal of Climate, 19(7), 1167–1181, doi:10.1175/JCLI3652.1.

Tsubouchi, T., S. Bacon, A. C. Naveira Garabato, Y. Aksenov, S. W. Laxon, E
. Fahrbach, A. Beszczynska-Möller, E. Hansen, C. M. Lee, and R. B. Ingvaldsen (2012), Journal of Geophysical Research: Oceans, 117(1), C01024, doi:10.1029/2011JC007174, doi:10.1029/2011JC007174.

Zappa, G., L. C. Shaffrey, and K. I. Hodges (2013), Journal of Climate, 26(15), 5379-5396, doi:10.1175/JCLI-D-12-00501.1.

How good is research at University of Reading in Earth Systems and Environmental Sciences?

FTE Category A staff submitted: 75.68

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