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Ocean Heat Content from past observations and its role in global warming.

This project is no longer listed in the FindAPhD
database and may not be available.

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  • Full or part time
    Prof K Haines
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

The oceans control the rate of global warming because they have by far the largest heat capacity in the climate system. Earth’s surface may warm rapidly if the excess solar heating is confined to the ocean surface, or the heat may be taken down into the deeper ocean, reducing, or even reversing, the rate of surface temperature change for periods of perhaps decades (eg. the recent ‘hiatus’). Current methods for mapping past changes in ocean heat content from the global database of approx. 10 million ocean profile measurements produce substantially different results depending on how the data are analysed. New analysis methods using Lagrangian interpolation methods that should better reflect the movement of water below the ocean surface may produce improved assessments of ocean heat content changes and lead to a better understanding of the role of the oceans in the Earths energy budget. The patterns of past change will also be used to assess the patterns of ocean heat content change from climate change models as an important means of model testing and evaluation.

The project will be co-supervised by Matt Palmer (Met Office).

The full project description is available here http://www.met.reading.ac.uk/nercdtp/home/available/desc/SC201516_Haines.pdf

Funding Notes

Project available for students with their own funding. To apply for this PhD project please visit http://www.met.reading.ac.uk/pg-research/pgrapplications.html

This project would be suitable for students with a degree in physics, mathematics or a closely related environmental or physical science.

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

FTE Category A staff submitted: 75.68

Research output data provided by the Research Excellence Framework (REF)

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