Arctic climate extremes: the role of changing interactions between atmospheric modes (MARSHALLUBAS21ARIES)

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:

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

You will employ statistical analyses to evaluate the interplay between the different atmospheric modes that impact Arctic climate. Utilising an array of historical meteorological observations, you 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, you will determine the regional ‘fingerprints’ that these large-scale interactions have on Arctic climate extremes. This will allow you 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, you will have training opportunities in statistical methods, data analysis and visualisation techniques, climate modelling, machine learning tools for analysing ‘big data’ and public outreach.

This studentship will be hosted at BAS.

Person Specification:

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

For more information on the supervisor for this project, please go here https://www.bas.ac.uk/profile/gjma/

This is a PhD programme.

The start date is 1st October 2021.

The mode of study is full or part time (visa restrictions may apply).

The studentship length is 3.5 years.

Funding Notes:

This project has been shortlisted for funding by the ARIES NERC DTP.

Successful candidates who meet UKRI’s eligibility criteria are awarded a NERC studentship covering fees, stipend (£15,285 p.a., 2020-21) and research funding. International applicants (EU/non-EU) are eligible for fully-funded studentships. Please note ARIES funding does not cover visa costs (including immigration health surcharge) or other additional costs associated with relocation to the UK.

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.

ARIES is committed to equality, diversity, widening participation and inclusion in all areas of its operation. We encourage enquiries and applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Academic qualifications are considered alongside significant relevant non-academic experience.

For further information, please visit www.aries-dtp.ac.uk