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Developing a long-term merged all-sky surface temperature record for evaluation and application in climate models

This project is no longer listed on and may not be available.

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  • Full or part time
    Prof J Remedios
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Land surface temperature (LST) is a fundamental, spatial quantity which is a fascinating, emerging observable for environmental science. LST is a key boundary condition 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. Infrared skin temperature is defined as the temperature measured by an IR radiometer in cloud-free conditions, typically operating at wavelengths 3.7-12 µm. It is the temperature of the top few micrometres of the surface (whether bare ground or canopy leaves), Microwave skin temperature represents the surface temperature at depths up to a few millimetres, depending on wavelength, view angle and surface conditions.

Retrievals in the IR are generally more accurate than MW retrievals due to smaller variation of surface emissivity’s and stronger dependence of the radiance on temperature. Nevertheless, microwave 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.

To meet the most significant LST requirements for climate science, integrated products can take advantage of the strengths of each data stream (IR and MW; polar orbiting and geostationary; and where available, in situ). The ultimate aim is to provide sub-daily, near-global coverage to better understand the diurnal (24hr) variability in LST. The first steps are to perform some initial comparisons of the IR and MW datasets and then to develop a draft process for merging the data. Much of the detailed research will develop from these key factors and will establish robust relationships between temperature measured from the two different techniques as a function of other parameters such as cloud thickness and wind speed. The results will improve IR and MW retrievals, build a definitive LST dataset derived from the individual data sets and utilise the product to evaluate climate models and other surface temperature datasets.

In the first year, students will be trained on environmental data science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to this project’s themes. Specialist training will include sensor techniques, radiative transfer for infra-red and microwave, non-linear data methods and general remote sensing. The National Centre for Earth Observation will provide access to its Researcher Forum, staff conferences/workshops and national-level training. There is good access to international summer schools.

Entry requirements:

Applicants are required to hold/or expect to obtain a UK Bachelor Degree 2:1 or better in a relevant subject. The University of Leicester English language requirements apply where applicable.

How to apply:

Please refer to the CENTA Studentship application information ( on our website for details of how to apply

As part of the application process you will need to:

• Complete a CENTA Funding form – to be uploaded to your PhD application
• Complete and submit your PhD application online applying for Physics Research. Indicate project CENTA2-NCEO-REME in the funding section.
• Complete an online project selection form Apply for CENTA2-NCEO-REME
Project / Funding Enquiries: Prof. John Remedios, [Email Address Removed]
Application enquiries to [Email Address Removed]
Closing date for applications: 21st January 2019 (12pm midday)

Funding Notes

This studentship is one of a number of fully funded studentships available to the best UK and EU candidates available as part of the NERC DTP CENTA consortium.

For more details of the CENTA consortium please see the CENTA website:
Applicants must meet requirements for both academic qualifications and residential eligibility:

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