Our research

At the University of Reading we specialise in a broad range of research areas in data assimilation. These areas span mathematical theory to applied data assimilation in the geosciences. Applications include: meteorology, atmospheric chemistry, oceanography, land surface physics, coastal sediment transport, and space.

We use a range of data assimilation methods to tackle these problems from variational data assimilation to particle filters.

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Current Projects

Below is a list of the current projects we are working on, along with the group members working on the project and the funding body. Click on the links for more information.

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PhD projects

    • Zak Bell (supervisors Sarah Dance and Joanne Waller) Using urban observations in numerical weather prediction: mathematical techniques for multi-scale filtering.
    • Ieva Dauzickaite (Supervisors Peter Jan van Leeuwen, Jennifer Scott, Amos Lawless) Efficient weak-constraint data assimilation for geophysical systems
    • Amsalework Ejigu (Supervisors Tristan Quaife, Amos Lawless and Gernot Geppert) Combining multiple streams of environmental data into a soil moisture dataset for maize-based systems in Sub-Saharan Africa.
    • Maha Kaouri (supervisors Amos Lawless, Nancy Nichols, Coralia Cartis) Novel optimization methods for data assimilation.
    • Laura Mansfield (supervisors Sarah Dance, Brian Hoskins, Richard Everitt, Apostolos Voulgarakis) Model reduction using emulation for understanding and predicting climate responses to different regional emission forcing
    • Haonen Ren (supervisors Peter Jan van Leeuwen, Javier Amezcua) Iterative Ensemble Kalman Smoother with correlated model error
    • Jemima Tabeart (supervisors Sarah DanceAmos LawlessNancy Nichols, Joanne Waller, Sue Ballard) On the treatment of correlated observation errors in data assimilation
    • Nicholas Williams (supervisors Daniel Feltham, Peter Jan Van Leeuwen, David Schroeder, Andy Shepherd, Ross Bannister) Arctic Sea-Ice Reduction: Gaining New Knowledge from Data Assimilation

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