Our People
Professor Amos Lawless
Professor of Data Assimilation
Data Assimilation
Research interests
I am interested in the mathematical theory of data assimilation and its application to environmental problems. I work on developing new methods to assimilate data into Earth-system models and their different components, which will allow us to extract more information from Earth observation measurements.
Recent publications
Assessment of short‐range forecast error atmosphere–ocean cross‐correlations from the Met Office coupled numerical weather prediction system. 2024-07
DOI: http://dx.doi.org/10.1002/qj.4735
Conditioning of hybrid variational data assimilation. 2024-03
DOI: http://dx.doi.org/10.1002/nla.2534
The effective use of anchor observations in variational bias correction in the presence of model bias. 2023-07
DOI: http://dx.doi.org/10.1002/qj.4482
The impact of hybrid oceanic data assimilation in a coupled model: A case study of a tropical cyclone. 2022-07
DOI: http://dx.doi.org/10.1002/qj.4309
New bounds on the condition number of the Hessian of the preconditioned variational data assimilation problem. 2022-01
DOI: http://dx.doi.org/10.1002/nla.2405
On time‐parallel preconditioning for the state formulation of incremental weak constraint 4D‐Var. 2021-10
DOI: http://dx.doi.org/10.1002/qj.4140
Randomised preconditioning for the forcing formulation of weak‐constraint 4D‐Var. 2021-10
DOI: http://dx.doi.org/10.1002/qj.4151
Nonlinear Conditional Model Bias Estimation for Data Assimilation. 2021-01
DOI: http://dx.doi.org/10.1137/19m1294848
Spectral estimates for saddle point matrices arising in weak constraint four‐dimensional variational data assimilation. 2020-06-29
DOI: http://dx.doi.org/10.1002/nla.2313
Improving the condition number of estimated covariance matrices. 2020
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-85076514479&partnerID=MN8TOARS
Quantifying the latitudinal representivity of in situ solar wind observations. 2020
DOI: http://dx.doi.org/10.1051/swsc/2020009
The Land Variational Ensemble Data Assimilation Framework: LAVENDAR v1.0.0. 2020
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-85077737116&partnerID=MN8TOARS
The impact of using reconditioned correlated observation-error covariance matrices in the Met Office 1D-Var system. 2020
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-85078671323&partnerID=MN8TOARS
The role of cross-domain error correlations in strongly coupled 4D-Var atmosphere–ocean data assimilation. 2020
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-85084468249&partnerID=MN8TOARS
Parameter estimation for a morphochemical reaction-diffusion model of electrochemical pattern formation. 2019
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-85049803271&partnerID=MN8TOARS
Nonlinear bias correction for satellite data assimilation using taylor series polynomials. 2018
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-85040908543&partnerID=MN8TOARS
The conditioning of least-squares problems in variational data assimilation. 2018
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-85042368501&partnerID=MN8TOARS
Treating Sample Covariances for Use in Strongly Coupled Atmosphere-Ocean Data Assimilation. 2018
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-85040649428&partnerID=MN8TOARS
Estimating forecast error covariances for strongly coupled atmosphere-ocean 4D-var data assimilation. 2017
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-85032186677&partnerID=MN8TOARS
Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model. 2015
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-84940417087&partnerID=MN8TOARS
Estimating correlated observation error statistics using an ensemble transform Kalman filter. 2014
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-84928137346&partnerID=MN8TOARS
Representativity error for temperature and humidity using the Met Office high-resolution model. 2014
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-84902296169&partnerID=MN8TOARS
Data assimilation for state and parameter estimation: Application to morphodynamic modelling. 2013
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-84875373708&partnerID=MN8TOARS
Integration of a 3D variational data assimilation scheme with a coastal area morphodynamic model of Morecambe Bay. 2012
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-84863783294&partnerID=MN8TOARS
Conditioning and preconditioning of the variational data assimilation problem. 2011
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-79954847227&partnerID=MN8TOARS
Conditioning of incremental variational data assimilation, with application to the Met Office system. 2011
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-79960400760&partnerID=MN8TOARS
Correlations of control variables in variational data assimilation. 2011
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-79955437609&partnerID=MN8TOARS
Four-dimensional variational data assimilation for high resolution nested models. 2011
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-79954667315&partnerID=MN8TOARS
State estimation using model order reduction for unstable systems. 2011
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-79954667333&partnerID=MN8TOARS
State estimation using the particle filter with mode tracking. 2011
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-79954675817&partnerID=MN8TOARS
A note on the analysis error associated with 3D-FGAT. 2010
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-77954513708&partnerID=MN8TOARS
Data assimilation for morphodynamic prediction and predictability. 2009
EID: http://www.scopus.com/inward/record.url?eid=2-s2.0-84873862594&partnerID=MN8TOARS
Approximate Gauss-Newton methods for optimal state estimation using reduced-order models. 2008
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-40749147172&partnerID=MN8TOARS
Modelling of forecast errors in geophysical fluid flows. 2008
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-40749112719&partnerID=MN8TOARS
Using model reduction methods within incremental four-dimensional variational data assimilation. 2008
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-45749113079&partnerID=MN8TOARS
Approximate Gauss-newton methods for nonlinear least squares problems. 2007
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-34548808885&partnerID=MN8TOARS
Inner-loop stopping criteria for incremental four-dimensional variational data assimilation. 2006
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-33845440376&partnerID=MN8TOARS
An investigation of incremental 4D-Var using non-tangent linear models. 2005
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-27744580710&partnerID=MN8TOARS
Approximate iterative methods for variational data assimilation. 2005
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-16344394714&partnerID=MN8TOARS
Variational data assimilation for Hamiltonian problems. 2005
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-16244380487&partnerID=MN8TOARS
A comparison of two methods for developing the linearization of a shallow-water model. 2003
DOI: http://www.scopus.com/inward/record.url?eid=2-s2.0-0037255418&partnerID=MN8TOARS
