Duncan Watson-Parris

Duncan Watson-Parris

Duncan Watson-Parris is an atmospheric physicist working at the interface of climate research and machine learning. Currently his research focusses on understanding the interactions between aerosols and clouds, and their representation within global climate models. These interactions are numerous and complex, involving non-linearities and feedbacks which make modelling average responses to any perturbation in aerosol extremely challenging. Duncan has recently led the development of a variety of machine learning (ML) tools and techniques to alleviate these difficulties and optimally combine a variety of observational datasets, including global satellite and aircraft measurements, to constrain and evaluate these models. Duncan also works to foster the application of machine learning to climate science questions more broadly and is Course Director of the iMIRACLI Innovative Training Network, convenes the Machine Learning in Climate research forum within the University of Oxford and co-chaired the recent Climate Informatics 2020 conference.

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  • Organization
    University of Oxford
  • Profession
    Postdoctoral Research Associate
Related sessions
28 September 2022
17:00 - 18:30 CEST, Geneva | 11:00-12:30 EST, New York | 23:00-00:30 CST, Beijing
Laurent Durieux (GEO), Philip Stier (University of Oxford), Xiao Xiang Zhu (Technical University of Munich)...
11 May 2022
17:00 - 18:30 CEST, Geneva | 11:00-12:30 EDT, New York | 23:00-00:30 CST, Beijing
Elizabeth Barnes (Colorado State University), Duncan Watson-Parris (University of Oxford), Philip Stier (University of Oxford)
17 November 2021
17:00 - 18:30 CET, Geneva | 8:00 - 9:30 PDT, Los Angeles | 11:00 - 12:30 EDT, New York | 16:00 - 17:30 BST, London
Philip Stier (University of Oxford), Pierre Gentine (Columbia University), Veronika Eyring (DLR)...