Improving temperature observations from Space to close the energy budget of the Earth in support of UNFCCC objectives and the Paris Agreement

The main impact of greenhouse gases on the Earth’s system is a reduction in energy exiting the top of the atmosphere and increased energy storage in the Earth system. The ability of observations to close the energy budget of the Earth is therefore crucial. Improving quantification of land surface temperature (LST) should reduce the budget imbalance. A key objective for the UN Framework Convention on Climate Change (UNFCCC) is how Earth observations could support the Paris Agreement.

LST is a fundamental, spatial quantity which is an emerging observable for environmental science. LST is a key state variable in land surface models, which determine the surface-to-atmosphere fluxes of heat, water and carbon compounds and represents the boundary condition in climate models. It also influences cloud cover, precipitation and atmospheric chemistry predictions within these models. Model deficiencies in representing LST often provide an indication of problems in surface energy fluxes and soil moisture that can affect the actual performance of Earth System Models at various temporal scales. There is an increasing focus on the opportunity to exploit satellite LST data to confront the challenges of climate science; and our research group is leading the international effort on LST science.

LST can be determined from thermal emission in either infrared (IR) or microwave (MW) atmospheric windows. Retrievals in the IR are generally more accurate than MW retrievals. Nevertheless, MW measurements have been shown to complement those in the IR due to their lower sensitivity to clouds, thus increasing sampling in cloudy conditions; although their spatial resolutions are significantly lower than their IR counterparts.

Use of LST for climate studies has been hindered because longer-term datasets are based on IR observations, which are limited to clear-sky. This presents a problem for many applications as resulting trends may be clear-sky biased, and climate models include both cloudy and clear-sky simulations. This project will progress our ability to overcome this by better understanding the physical differences between the observations and how robust relationships can be developed to enable observations to be merged into a consistent record and thus to better improve climate model prediction skill.

Entry requirements
UK Bachelor Degree with at least 2:1 in a relevant subject or overseas equivalent. Evidence of English may apply.

Enquiries
Project Enquiries: Dr Darren Ghent, [Email Address Removed]

Funding Enquiries: [Email Address Removed]

How to apply
Please refer to the How to Apply section at https://le.ac.uk/study/research-degrees/funded-opportunities/centa-phd-studentships and use the PHYSICS Apply button to submit your PhD application. Upload your CENTA Studentship Form in the proposal section of the application form.

In the funding section of the application please indicate you wish to be considered for NERC CENTA Studentship
Under the proposal section please provide the name of the supervisor and project title/project code you want to apply for.

Eligibility
Available for UK and EU applicants only

Applicants must meet requirements for both academic qualifications and residential eligibility: http://www.nerc.ac.uk/skills/postgrad/