- Provide first ever aerosol’s fingerprint on ice-cloud on a global scale for improving climate models
- Marriage of modern satellite Earth observations and data-science techniques
- Collaboration with a wide range of national and international world-leading research groups, including opportunity of placement in the renowned UK Met Office.
Climate change is a global challenge. Extreme weather situations that we encountered recently including heat-waves, wild-fires, floods and droughts reveal the devastating impact that climate change can have on our society. These climate-related risks depend on how fast our Earth warms in the future. The state-of-the-art climate models still have very large uncertainty in projecting future climate change. According to the recent IPCC AR6 report, aerosol-cloud-climate interactions remain arguably the largest uncertainty, especially how ice-cloud response to aerosol is poorly understood.
Ice-cloud plays a vital role in global hydrological cycle, since most of continental precipitation is triggered by ice-cloud. Human emissions of air pollutants (e.g. aerosols) can influence both liquid and ice clouds. Almost all liquid cloud droplets form on tiny aerosol particles, while, only a few aerosol particles can serve as ice nuclei to trigger the formation of ice-cloud from supercool water droplets. The formation of ice-cloud can dramatically change cloud properties, precipitation and the climate effect of clouds. One big challenge for improving climate models is the lack of understanding in the sources of ice nucleation particles and how they influence clouds.
Figure 1. Increase of liquid cloud cover due to Icelandic volcano, distinguished by machine-learning. Source from Chen et al. (2022).
This is a CENTA Flagship Project
This project is suitable for CASE funding
HostUniversity of Birmingham
- Climate and Environmental Sustainability
Previous studies struggle to rule out contamination of meteorology co-variability in aerosol’s fingerprint on clouds. This project will take the advantage of the marriage of modern satellite observations and modern data-science to tackle this critical question using natural experiments, as demonstrated in our recent study for liquid clouds (Fig. 1). These natural experiments include but not limited to California and Australian wildfires, volcanic eruptions, and COVID-cessation of flying, which inject (or reduce) aerosol at much higher altitudes where aerosols interact with ice-clouds. Satellite observations will be used to quantify the amount of injected aerosols and the changes in ice-cloud properties, and advanced machine-learning techniques will be used to disentangle the aerosol’s fingerprints on ice-cloud from the noise of meteorological co-variability. The findings will be used to help improve the next generation of climate models to better represent aerosol-cloud-climate interactions, and therefore the hydrological cycle and better project climate change.
Training and skills
Students will be awarded CENTA2 Training Credits (CTCs) for participation in CENTA2-provided and ‘free choice’ external training. One CTC equates to 1⁄2 day session and students must accrue 100 CTCs across the three years of their PhD.
You will be trained in multiple aspects of satellite Earth observation system, data-science analysis and climate modelling skills. You will receive support and training in disseminating the project outcomes through various outlets, including publications, international conferences and public media. The project also offers an option of 3-18 months placement in the UK Met Office to gain understanding of atmospheric data collection and how climate projection and weather forecast work. You will be a member of the atmospheric research team here in Birmingham, also part of a wider international team of world-leading researchers, allowing you to build and develop your global network.
Partners and collaboration
The project is offered in collaboration with the UK Met Office, University of Cambridge and NCAS who are world-leading institutes in atmospheric research and professional service. The project also involves a number of collaborators, including from ETH Zurich, NASA, Oxford, NCAS, Manchester, Norway and Germany, ensuring the student has a broad range of international expertise to draw from. The student will also be part of an exciting and growing team in Birmingham researching global environmental change issues. Optional placement opportunity is offered by Met Office, with additional funding support for travel and subsistence.
Further details on how to contact the supervisor for this project and how to apply for this project can be found here:
For any enquiries related to this project please contact Dr Ying Chen ([email protected]). Please use email title “CENTA PhD – [your name]”, and provide a Cover Letter explaining your motivation and why you feel you are a suitable candidate (1 page), alongside a CV.
To apply to this project:
- You must include a CENTA studentship application form, downloadable from: CENTA Studentship Application Form 2024.
- You must include a CV with the names of at least two referees (preferably three) who can comment on your academic abilities.
- Please submit your application and complete the host institution application process via: https://sits.bham.ac.uk/lpages/LES068.htm. Please select the PhD Geography and Environmental Science (CENTA) 2024/25 Apply Now button. The CENTA application form 2024 and CV can be uploaded to the Application Information section of the online form. Please quote CENTA 2024-B8 when completing the application form.
Applications must be submitted by 23:59 GMT on Wednesday 10th January 2024.
More about Dr Ying Chen: https://research.birmingham.ac.uk/en/persons/ying-chen
More about Dr Cyril Morcrette: https://mathematics.exeter.ac.uk/staff/cm1082
More about Dr Luke Abraham: https://www.ch.cam.ac.uk/group/atm/person/nla27
Familiarisation with concepts, the relevant theories of climate change and cloud microphysics, and the project datasets. Collect information and relevant data of the natural experiments. Training in the data-science and climate modelling skills.
Using a range of statistical and machine-learning method to design natural experiments and distinguish ice-cloud response to the change of aerosols. Continued training in data-science analysis, satellite observation interpreting. Placement in Met Office.
A global level analysis of aerosol’s impacts (fingerprint) on ice-cloud. Evaluate, constrain and improve the-state-of-art climate models, which participates in the CMIP6-CovidMIP (Coupled Model Intercomparison Project of COVID pandemic experiments). Presentation of results in international conferences, draft publications, and start writing up of thesis.
Chen, Y., Haywood, J., et al. (2022), Machine learning reveals climate forcing from aerosols is dominated by increased cloud cover, Nature Geoscience, doi:10.1038/s41561-022-00991-6.
Lohmann, U., F. Friebel, Z. A. Kanji, F. Mahrt, A. A. Mensah, and D. Neubauer (2020), Future warming exacerbated by aged-soot effect on cloud formation, Nature Geoscience, 13(10), 674-680, doi:10.1038/s41561-020-0631-0.
Malavelle, F. F., Haywood, J., et al. (2017), Strong constraints on aerosol–cloud interactions from volcanic eruptions, Nature, 546(7659), 485-491, doi:10.1038/nature22974.
Ghan, S., et al. (2016), Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability, Proceedings of the National Academy of Sciences, 113(21), 5804-5811, doi:10.1073/pnas.1514036113.
Glassmeier, F., F. Hoffmann, J. S. Johnson, T. Yamaguchi, K. S. Carslaw, and G. Feingold (2021), Aerosol-cloud-climate cooling overestimated by ship-track data, Science, 371(6528), 485-489, doi:10.1126/science.abd3980.
Seinfeld, J. H., et al. (2016), Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system, Proceedings of the National Academy of Sciences, 113(21), 5781-5790, doi:10.1073/pnas.1514043113.
Zhao, B., Y. Wang, Y. Gu, K.-N. Liou, J. H. Jiang, J. Fan, X. Liu, L. Huang, and Y. L. Yung (2019), Ice nucleation by aerosols from anthropogenic pollution, Nature Geoscience, doi:10.1038/s41561-019-0389-4.