Constraining the role of tropical clouds in climate change using novel satellite observations
Background
Changes to clouds are the most uncertain climate feedback, limiting confidence in warming projections. Clouds can amplify or reduce warming by reflecting sunlight or trapping heat. Evidence suggests warming will alter cloud patterns to enhance warming, though the magnitude remains unclear.
A major challenge in quantifying cloud feedbacks is the wide variety of cloud types—differing in composition and thickness—and their interdependence. Most studies examine individual cloud types, but interactions matter: for instance, more convective storms can reduce cooling low-level clouds and increase heat-trapping high-level clouds.
Satellite observations are vital for studying cloud complexity. Launched in 2024, EarthCARE combines radiation sensors with radar and lidar, providing the most comprehensive view of clouds yet. This PhD project will leverage EarthCARE data to advance our understanding of the linkages between cloud types and their response to climate change.
PhD Opportunity
Tropical clouds may drive some of the strongest, and most uncertain, cloud feedbacks. This PhD will develop a new perspective of clouds which aims to expose the connections between different tropical cloud types, and demonstrate ways in which understanding the interconnectedness of clouds provides an opportunity to reduce cloud feedback uncertainty.
This PhD will study multi-decadal spaceborne records to characterise the co-variation of tropical cloud types and their influence on radiation and climate. Applying advanced statistical and data science methods such as clustering and principal component analysis, the work will produce a dataset capturing cloud responses in combination, rather than independently. The student will evaluate whether this approach defines a set of cloud radiative responses to global temperature with smaller confidence intervals, and therefore uncertainty, than the existing cloud types used for feedback analysis.
Building on the newly defined framework for studying tropical cloud interactions, this project will apply it to the new EarthCARE dataset to offer an unprecedented view of cloud–climate coupling. The PhD student will get to focus on specific cloud connections that interest them, and use EarthCARE to assess the framework’s value for physically interpreting the processes that govern clouds and climate.
Finally, the project will assess how tropical clouds are represented in numerical models. Guided by the student’s evolving interests, this could involve evaluating historical cloud simulations and their co-variability, or analysing projected future cloud responses in global climate models. Using methods, such cloud controlling factor analysis, consistent observed and modelled physical drivers of cloud feedback will be applied to further constrain feedback uncertainty.
Dr Shannon Mason (ECMWF) will co-supervise. The student will undertake a placement at ECMWF, and present their work to researchers at the European Space Agency.
Applicant Profile
Students with a strong background in mathematics or physical sciences, and who wish to apply their skills to state-of-the-art satellite data to understand climate. Previous experience of data analysis and computer programming (e.g. python, Matlab, R) is desirable.
Other information
https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-7/#7.4.2.4
https://environment.leeds.ac.uk/institute-climate-atmospheric-science/staff/1261/dr-declan-finney
