My research interests lie in the mathematical theory of data assimilation techniques for environmental prediction. Projects I am currently involved in include:
·
Simon
Driscoll, 2022 - (with Alberto Carrassi,
Laurent Bertino, Marc Boquet, Julien Brajard, Einar
Olason).
Data assimilation and machine learning for emulating thermodynamics in the
Arctic sea-ice.
·
Ravi
Shankar Nemani, 2024 – (with Ross Bannister, Hong Wei, Chris Thomas).
Machine learning driven balance relationships for next generation data
assimilation systems
·
Tom Hill (part time), 2025 – (with Yumeng Chen,
Nancy Nichols, Dan Lea, Tsz Yan Leung, Joanne Waller)
Making better use of near-surface observations in coupled
atmosphere-ocean prediction
·
Jesse Gilbert, 2025 – (with Eviatar Bach, Sarah
Dance, Massimo Bonavita)
Large ensembles of machine learning forecasts for advanced
nonlinear filters in atmospheric data assimilation
1.
Laura
Watkinson (nee
Four Dimensional Variational Data
Assimilation for Hamiltonian Problems
2.
David
Katz, 2003 - 2007 (with Nancy Nichols, Ross
Bannister and Mike Cullen)
The application of PV-based control variable transforms in
variational data assimilation
3.
Gillian
Baxter, 2005 - 2009 (with Sarah Dance, Nancy Nichols and Sue Ballard)
4D-Var
for high resolution, nested models with a range of scales
4.
Stephen
Haben, 2007 - 2011 (with Nancy Nichols, Mike Cullen, Gordon Inverarity)
Conditioning
and preconditioning of the minimisation problem in variational data
assimilation
5.
Joanne
Waller (nee Pocock), 2009 - 2013 (with Sarah
Dance, Nancy Nichols)
Using
observations at different spatial scales in data assimilation for environmental
prediction
6.
Alex
Moodey, 2009 - 2013 (with Roland
Potthast, Peter Jan van
Leeuwen)
Instability
and Regularization for Data Assimilation
7.
Adam
El-Said, 2011 – 2015 (with Nancy
Nichols)
Conditioning of the Weak-Constraint
Variational Data Assimilation Problem for Numerical Weather Prediction
8.
Kat
Howes, 2012 – 2016 (with Alison
Fowler)
Accounting for model error in four-dimensional variational data assimilation
9.
Ewan
Pinnington, 2013 – 2017 (with Tristan Quaife, Sarah Dance and Nancy Nichols)
Understanding the information content in diverse observations of forest
carbon stocks and fluxes for data assimilation and ecological modelling
10.
Jemima Tabeart, 2016 – 2019 (with Sarah Dance,
Nancy Nichols and Joanne Waller)
On the treatment of correlated observation errors in data
assimilation.
11.
Jason Otkin (p/t, working away), 2015 - 2020 (with Roland Potthast)
New methods for assimilation of remote sensing satellite observations for
atmospheric and surface predictions.
12.
Amsalework Ejigu, 2015 – 2020 (with Tristan
Quaife)
Ensemble generation in land surface
models for soil moisture data assimilation.
13.
Maha Kaouri, 2016 – 2021 (with Coralia Cartis and Nancy
Nichols)
Novel optimization methods for data
assimilation.
14.
Ieva Dauzickaite, 2018 – 2022 (with Peter Jan
van Leeuwen and Jennifer Scott)
On the preconditioning for weak
constraint four-dimensional variational data assimilation
15.
Devon
Francis, 2019 – 2023 (with Alison Fowler)
Bias correction of satellite data in data assimilation for
numerical weather prediction
16.
Laura Risley, 2021 – 2025 (with Matthew Martin, Met
Office, and Anthony Weaver, CERFACS).
Assimilation
of future ocean-current measurements from satellites.