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Why do weather and climate models get the Indian Ocean wrong? (WEBBER_UENV22ARIES)


   School of Environmental Sciences


About the Project

Primary Supervisor - Dr Benjamin Webber (UEA, ENV)

Secondary Supervisor - Professor Adrian Matthews (UEA, ENV)

Supervisory Team - Dr José Rodríguez (UK Met Office), Dr Dan Copsey (UK Met Office)

Scientific 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.

For more information on the supervisor for this project, please visit the UEA website www.uea.ac.uk

The start date is 1 October 2022


Funding Notes

This project is funded by ARIES NERC DTP and will start on 1st October 2022.

Successful candidates who meet UKRI’s eligibility criteria will be awarded a NERC studentship covering 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.

ARIES students benefit from bespoke graduate training and £2,500 for external training, travel and conferences.

ARIES is committed to equality, diversity, widening participation and inclusion. Academic qualifications are considered alongside non-academic experience. Our recruitment process considers potential with the same weighting as past experience.

For information and full eligibility visit View Website

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

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