Why do weather and climate models get the Indian Ocean wrong?

(WEBBER_UENV22ARIES)

Why do weather and climate models get the Indian Ocean wrong?

(WEBBER_UENV22ARIES)

Project Description

Supervisors

Dr Benjamin Webber (School of Environmental Sciences, University of East Anglia) – Contact me

Professor Adrian Matthews (School of Environmental Sciences, University of East Anglia)

Dr José Rodríguez (UK Met Office)

Dr Dan Copsey (UK Met Office)

 

Project Background

The Indian Ocean is a key component of global climate, surrounded by monsoon systems on which billions of people depend, and warming faster than any other ocean basin. However, state-of-the-art climate models fail to accurately capture the dynamical and thermodynamical processes that govern climatic variability around the Indian Ocean. The UK Met Office has identified model errors and biases in this region to be a significant problem for making seasonal climate forecasts, yet little is known about the source of these errors or how they could be reduced.

Research methodology

You will identify the key processes that generate errors in the Met Office weather and climate models to identify potential model improvements. Initially you will compute the ocean surface mixed layer heat budget, which controls variability in sea-surface temperature and atmosphere-ocean interaction, and compare this budget against observations to identify errors. You will then extend this work to evaluate model experiments where the atmosphere and ocean are “nudged” towards observed values, to identify the role of different regions and components of the climate system in generating model errors and biases. Finally you will run short sensitivity studies to identify optimal model setups and pathways for future development.

Training and research environment

You will join an active research group at UEA in tropical meteorology and climate and will be trained in relevant theory and methods. You will be trained in the analysis of weather forecasting and climate model output using the python programming language, including use of python modules developed by the Met Office for handling and visualising model output. In addition to frequent teleconferences with the Met Office co-supervisors, you will undertake visits to the Met Office for training in running and analysing Met Office models. You will have the opportunity to present your work at national and international conferences.

Person specification

We seek an enthusiastic student with a degree in physical sciences (physics, mathematics, meteorology, oceanography, or similar), good numerical ability and a keen interest in applying theoretical understanding to solve real world environmental problems. Programming skills (e.g., Python, Matlab) would be beneficial.

References

  • 1) Martin, G. M., Levine, R. C., Rodriguez, J. M., & Vellinga, M. (2021). Understanding the development of systematic errors in the Asian summer monsoon. Geoscientific Model Development, 14(2), 1007–1035. https://doi.org/10.5194/gmd-14-1007-2021
  • 2) Webber, B. G. M., Matthews, A. J., Vinayachandran, P. N., Neema, C. P., Sanchez-Franks, A., Vijith, V., et al. (2018). The Dynamics of the Southwest Monsoon Current in 2016 from High-Resolution In Situ Observations and Models. Journal of Physical Oceanography, 48(10), 2259–2282. https://doi.org/10.1175/JPO-D-17-0215.1
  • 3) Vijith, V., Vinayachandran, P. N., Webber, B. G. M., Matthews, A. J., George, J. V., Kannaujia, V. K., et al. (2020). Closing the sea surface mixed layer temperature budget from in situ observations alone: Operation Advection during BoBBLE. Scientific Reports, 10(1), 1–12. https://doi.org/10.1038/s41598-020-63320-0
  • 4) Rodríguez, J. M., Milton, S. F., & Marzin, C. (2017). The East Asian Atmospheric Water Cycle and Monsoon Circulation in the Met Office Unified Model. Journal of Geophysical Research: Atmospheres, 122(19), 10246–10265. https://doi.org/10.1002/2016JD025460
  • 5) Sanchez-Franks, A., Kent, E. C., Matthews, A. J., Webber, B. G. M., Peatman, S. C., & Vinayachandran, P. N. (2018). Intraseasonal Variability of Air–Sea Fluxes over the Bay of Bengal during the Southwest Monsoon. Journal of Climate, 31(17), 7087–7109. https://doi.org/10.1175/JCLI-D-17-0652.1

Key Information

  • This project has been shortlisted for funding by the ARIES NERC DTP and will start on 1st October 2022. The closing date for applications is 23:59 on 12th January 2022.
  • Successful candidates who meet UKRI’s eligibility criteria will be awarded a NERC studentship, which covers fees, stipend (£15,609 p.a. for 2021-22) and research funding. International applicants (EU and non-EU) are eligible for fully-funded UKRI studentships. Please note ARIES funding does not cover visa costs (including immigration health surcharge) or other additional costs associated with relocation to the UK.
  • ARIES students benefit from bespoke graduate training and ARIES provides £2,500 to every student for access to external training, travel and conferences. 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.
  • 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 non-academic experience, and our recruitment process considers potential with the same weighting as past experience.
  • All ARIES studentships may be undertaken on a part-time or full-time basis, visa requirements notwithstanding
  • For further information, please contact the supervisor. To apply for this Studentship click on the “Apply now” link below.
  • ARIES is required by our funders to collect Equality and Diversity Information from all of our applicants. The information you provide will be used solely for monitoring and statistical purposes; it will remain confidential, and will be stored on the UEA sharepoint server. Data will not be shared with those involved in making decisions on the award of Studentships, and will have no influence on the success of your application. It will only be shared outside of this group in an anonymised and aggregated form. You will be ask to complete the form by the University to which you apply.

Applications are open

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