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.
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.
- CUNDA: Causality Relations using nonlinear Data Assimilation: Peter Jan van Leeuwen, Manual Pulido, Magdalena Lucini, Polly Smith, Vincent Faure, Vladimir Stepanov, Matthew Ng, Maria Broadbridge (ERC Advance Investigator Grant)
- Data Assimilation for the REsilient city (DARE): Sarah Dance, EPSRC Senior Fellowship in Digital Technology for Living with Environmental Change (EPSRC EP/P002331/1), Dr David Mason, Prof Sue Grimmond , Dr Javier Garcia-Pintado (Uni Bremen), Dr Joanne Waller , Dr Sanita Vetra-Carvalho , Dr Jon Blower , Prof Onno Bokhove (Uni Leeds)
- Observation impact and observation error covariances:
Alison Fowler, Peter Jan van Leeuwen (funded by NCEO/NERC)
- Next generation Numerical weather prediction: 4DVar ensembles and Particle Filters: Peter Jan van Leeuwen, Javier Amezcua Espinosa (collaboration with ECMWF) (funded by NERC)
- Inverse modelling for the determination of sources and sinks of trace gases: Ross Bannister (funded by NCEO)
- 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 Dance, Amos Lawless, Nancy 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