Publications    

Submitted

1.      Driscoll, S., Carrassi, A., Bertino, L., Brajard, J., Ólason, E. Ö., Bocquet, M. and Lawless, A.S. (2024), Data-driven emulation of melt ponds on Arctic sea ice.

2.      Chen, Y., Nerger, L. and Lawless, A.S. (2024), A Python interface to the Fortran-based Parallel Data Assimilation Framework: pyPDAF v1.0.0.

3.      Skakala, J. & 22 co-authors (2024), Marine data assimilation in the UK: the past, the present and the vision for the future.

4.      Fowler, A.M., Francis, D.J., Lawless, A.S., Eyre, J.R. and Migliorini, S. (2024), The importance of the timing of anchor observations in 4D variational bias correction.

Refereed journal publications

1.      Cartis, C., Kaouri, M.H., Lawless, A.S. and Nichols, N.K. (2024), Convergent least-squares optimization methods for variational data assimilation. Optimization. doi.org/10.1080/02331934.2024.2390119

2.      Wright, A., Lawless, A.S., Nichols, N.K., Lea, D. and Martin, M. (2024), Assessment of short-range forecast error atmosphere-ocean cross-correlations from the Met Office coupled NWP system. Quart. J. Royal Met. Soc, doi.org/10.1002/qj.4735.

3.      Shataer, S., Lawless, A.S. and Nichols, N.K. (2023), The Conditioning of Hybrid Variational Data Assimilation. Numerical Linear Algebra with Applications. doi.org/10.1002/nla.2534.

4.      Francis, D., Fowler, A.M., Lawless, A.S., Eyre, J.R., Migliorini, S. (2023), The Effective Use of Anchor Observations in Variational Bias Correction in the Presence of Model Bias. Quart. J. Royal Met. Soc. doi.org/10.1002/qj.4482

5.      Leung, T.Y., Lawless, A.S., Nichols, N.K., Lea, D. and Martin, M. (2022), The impact of hybrid oceanic data assimilation in a coupled model: a case study of a tropical cyclone. Quart. J. Royal Met. Soc, doi.org/10.1002/qj.4309.

6.      Daužickaitė, I., Lawless, A.S., Scott, J.A. and van Leeuwen. P.J. (2021), Randomised preconditioning for the forcing formulation of weak constraint 4D-Var. Quart. J. Royal Met. Soc, doi.org/10.1002/qj.4151.

7.      Daužickaitė, I., Lawless, A.S., Scott, J.A. and van Leeuwen. P.J. (2021), On time-parallel preconditioning for the state formulation of incremental weak constraint 4D-Var. Quart. J. Royal Met. Soc, doi.org/10.1002/qj.4140.

8.      Tabeart, J.M., Dance, S.L., Lawless, A.S., Nichols, N.K. and Waller J.A (2021), New bounds on the condition number of the Hessian of the preconditioned variational data assimilation problem. Numerical Linear Algebra with Applications, e2405. (Open access article)

9.      Otkin, J.A., Potthast, R.W.E. and Lawless, A.S. (2021), Nonlinear conditional model bias estimation for data assimilation. SIAM Journal on Applied Dynamical Systems, 20, 299-332. https://doi.org/10.1137/19M1294848

10.  Daužickaitė, I., Lawless, A.S., Scott, J.A. and van Leeuwen. P.J. (2020), Spectral estimates for saddle point matrices arising in weak constraint four-dimensional variational data assimilation. Numerical Linear Algebra with Applications, e2313. doi.org/10.1002/nla.2313.

11.  Smith, P.J., Lawless, A.S. and Nichols, N.K. (2020), The role of cross-domain error correlations in strongly coupled 4D-Var atmosphere-ocean data assimilation. Quart. J. Royal Met. Soc.  doi.org/10.1002/qj.3802.

12.  Owens, N.J., Lang, M., Riley, P., Lockwood, M. and Lawless, A.S. (2020), Quantifying the latitudinal representivity of in situ solar wind speed observations. J. Space Weather Space Clim. 2020, 10, 8, doi.org/10.1051/swsc/2020009.

13. Tabeart, J.M., Dance, S.L., Lawless,  A.S., Migliorini, S., Nichols, N. K., Smith, F., Waller, J. A. (2020), The impact of using reconditioned correlated observation error covariance matrices in the Met Office 1D-Var system. Quart. J. Royal Met. Soc. https://doi.org/10.1002/qj.3741.

14. Tabeart, J.M., Dance, S.L., Lawless, A.S., Nichols, N.K. and Waller J.A. (2020), Improving the condition number of estimated covariance matrices. Tellus A. 72:1, 1-19, doi 10.1080/16000870.2019.1696646.

15.  Pinnington, E., Quaife, T., Lawless, A., Williams, K., Arkebauer, T., and Scoby, D. (2020), The Land Variational Ensemble Data Assimilation fRamework: LaVEnDAR, Geosci. Model Dev. Discuss., 13, 55-69. (Open access article)

16.  Tabeart, J.M., Dance, S.L., Haben, S.A., Lawless, A.S., Nichols, N.K. and Waller J.A. (2018), The conditioning of least squares problems in variational data assimilation. Numerical Linear Algebra with Applications, 25, e2165. (Open access article)

17.  Sgura, I., Lawless, A.S. and Bozzini, B. (2018), Parameter estimation for a morphochemical reaction-diffusion model of electrochemical pattern formation. Inverse Problems in Science and Engineering, doi:10.1080/17415977.2018.1490278.

18.  Otkin, J.A., Potthast, R.W.E. and Lawless, A.S. (2018), Nonlinear bias correction for satellite data assimilation using Taylor series polynomials. Monthly Weather Review, 146, 263–285, https://doi.org/10.1175/MWR-D-17-0171.1.

19.  Smith, P.J., Lawless, A.S. and Nichols, N.K. (2018), Treating sample covariances for use in strongly coupled atmosphere-ocean data assimilation. Geophysical Research Letters, 45, 445-454. (Open access article)

20.  Smith, P.J., Lawless, A.S. and Nichols, N.K. (2017), Estimating forecast error covariances for strongly coupled atmosphere-ocean 4D-Var data assimilation. Monthly Weather Review, 145, 4011-4035. (Open access article)

21.  Pinnington, E.M., Casella, E., Dance, S.L., Lawless, A.S., Morison, J.I.L., Nichols, N.K., Wilkinson, M. and Quaife, T.L. (2017), Understanding the effect of disturbance from selective felling on the carbon dynamics of a managed woodland by combining observations with model predictions, J. Geophys. Res. Biogeosci., 122, doi:10.1002/2017JG003760. (Open access article)

22. Howes, K.E., Fowler, A.M. and Lawless, A.S. (2016), Accounting for model error in strong-constraint 4DVar data assimilation, Quart. J. Royal Met. Soc. , 143, 1227-1240. (Open access article)

23.  Fowler, A.M. and Lawless, A.S. (2016), An idealized study of coupled atmosphere-ocean 4D-Var in the presence of model error. Monthly Weather Review, 144, 4007-4030. (Open access article)

24.  Pinnington, E.M., Casella, E., Dance, S.L., Lawless, A.S., Morison, J.I.L., Nichols, N.K., Quaife, T.L. and Wilkinson, M. (2016), Investigating the role of background and observation error correlations in improving a model forecast of forest carbon balance using four dimensional variational data assimilation. Agricultural and Forest Meteorology,228-229, 299-314. (Open access article)

25.  Smith, P.J., Fowler, A.M. and Lawless, A.S. (2015), Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model. Tellus A, 67, 27025, http://dx.doi.org/10.3402/tellusa.v67.27025. (Open access)

26.  Waller, J.A., Dance, S.L., Lawless, A.S. and Nichols, N.K. (2014), Estimating correlated observation errors with an ensemble transform Kalman filter, Tellus A, 66, 23294, http://dx.doi.org/10.3402/tellusa.v66.23294. (Open access)

27.  Waller, J.A., Dance, S.L., Lawless, A.S., Nichols, N.K. and Eyre, J.R. (2013), Representativity error for temperature and humidity using the Met Office high resolution model. Quart. J. Royal Met. Soc., 140, 1189-1197. (Preprint - MPS-2012-19)

28.  1Moodey, A.J.F., Lawless, A.S., Potthast, R.W.E. and van Leeuwen, P.J. (2013), Nonlinear error dynamics for cycled data assimilation methods, Inverse Problems, 29, 025002. (Preprint - MPS-2012-13)

29.  Smith, P.J., Thornhill, G.D., Dance, S.L., Lawless, A.S., Mason, D.M. and Nichols, N.K. (2013), Data assimilation for state and parameter estimation: application to morphodynamic modelling. Quart. J. Royal Met. Soc. 139, 314-327. (Preprint - MPS-2011-16)

30.  Thornhill, G.D., Mason, D.M., Dance, S.L., Lawless, A.S. and Nichols, N.K. (2012), Integration of a 3D Variational data assimilation scheme with a coastal area morphodynamic model of Morecambe Bay. Coastal Engineering, 69, 82-96. (Preprint - MPS-2012-01)

31.  Haben, S., Lawless, A.S. and Nichols, N.K. (2011), Conditioning of incremental variational data assimilation, with application to the Met Office system. Tellus A, 63, 782-792. (Preprint - MPS_2010_22)

32.  Katz, D., Lawless, A.S., Nichols, N.K., Cullen, M.J.P. and Bannister, R.N. (2011), Correlations of control variables in variational data assimilation. Quart. J. Royal Met. Soc., 137, 620-630. (Preprint - MPS_2010_11)

33.  Baxter, G.M., Dance, S.L., Lawless, A.S. and Nichols, N.K. (2011), Four-dimensional variational data assimilation for high resolution nested models. Comput. Fluids, 46, 137-141. (Preprint - MPS_2010_13)

34.  Boess, C., Lawless, A.S., Nichols, N.K. and Bunse-Gerstner, A. (2011), State estimation using model order reduction for unstable systems. Comput. Fluids, 46, 155-160. (Preprint - MPS_2010_15)

35.  Haben, S., Lawless, A.S. and Nichols, N.K. (2011), Conditioning and Preconditioning of the Variational Data Assimilation Problem. Comput. Fluids, 46, 252-256. (Preprint - MPS_2010_16)

36.  Pocock, J.A., Dance, S.L. and Lawless, A.S. (2011), State Estimation using the Particle Filter with Mode Tracking. Comput. Fluids, 393-397. (Preprint - MPS_2010_18)

37.  Lawless, A.S. (2010), A note on the analysis error associated with 3D-FGAT, Quart. J. Royal Met. Soc., 136, 1094-1098. (Preprint - MPS_2010_07)

38.  Lawless, A.S., Nichols, N.K., Boess, C. and Bunse-Gerstner, A. (2008), Using model reduction methods within incremental 4D-Var. Monthly Weather Review, 136, 1511-1522. (Preprint - Numerical analysis report 10/06)

39.  Lawless, A.S., Nichols, N.K., Boess, C. and Bunse-Gerstner, A. (2008), Approximate Gauss-Newton methods for optimal state estimation using reduced order models. Int. J. Numer. Methods in Fluids,  56, 1367-1373. (Preprint - Numerical analysis report 5/07)

40.  Bannister, R.N., Katz, D., Cullen, M.J.P, Lawless, A.S. and Nichols, N.K. (2008), Modelling of Forecast Errors in Geophysical Fluid Flows. Int. J. Numer. Methods in Fluids, 56, 1147-1153. (Preprint - Numerical analysis report 4/07)

41.  Watkinson, L.R., Lawless, A.S., Nichols, N.K. and Roulstone, I. (2007), Weak constraints in four-dimensional variational data assimilation. Meteorologische Zeitschrift, 16, 767-776. (Preprint - Numerical analysis report 1/07)

42.  Gratton, S., Lawless, A.S. and Nichols, N.K. (2007), Approximate Gauss-Newton methods for nonlinear least squares problems, SIAM J. on Optimization, 18, 106-132. (Preprint - Numerical analysis report 9/04)

43.  Lawless, A.S. and Nichols, N.K. (2006), Inner loop stopping criteria for incremental four-dimensional variational data assimilation, Monthly Weather Review, 134, 3425-3435. (Preprint - Numerical analysis report 5/05)

44.  Lawless, A.S., Gratton. S. and Nichols, N.K. (2005), Approximate iterative methods for variational data assimilation, Int. J. Numer. Methods in Fluids, 47, 1129-1135. (Preprint - Numerical analysis report 3/04)

45.  Watkinson, L.R., Lawless, A.S., Nichols, N.K. and Roulstone, I. (2005), Variational data assimilation for Hamiltonian problems, Int. J. Numer. Methods in Fluids, 47, 1362-1367. (Preprint - Numerical analysis report 4/04)

46.  Lawless, A.S., Gratton, S. and Nichols, N.K. (2005), An investigation of incremental 4D-Var using non-tangent linear models, Quart. J. Royal Met. Soc., 131, 459-476. (Preprint - Numerical analysis report 2/04)

47.  Lawless, A.S., Nichols, N.K. and Ballard, S.P. (2003), A comparison of two methods for developing the linearization of a shallow water model, Quart. J. Royal Met. Soc., 129, 1237-1254.

Book chapter

  1. Lawless, A.S. (2013), Variational data assimilation for very large environmental problems. (Preprint - MPS-2012-18). In Large Scale Inverse Problems: Computational Methods and Applications in the Earth Sciences (2013), Eds. Cullen, M.J.P., Freitag, M. A., Kindermann, S., Scheichl, R., Radon Series on Computational and Applied Mathematics 13. De Gruyter, pp. 55-90.

 

Conference proceedings

  1. Baxter, G.M., Dance, S.L., Lawless, A.S., Nichols, N.K., and Ballard, S. (2007), Multiscale data assimilation for high resolution nested models, Proceedings of the Institute for Computational Fluid Dynamics conference on Numerical Methods for Fluid Dynamics, Reading, U.K.
  2. Watkinson, L.R., Lawless, A.S., Nichols, N.,K. and Roulstone, I. (2006), Data assimilation and the 2- and 3- body problems, Oberwolfach Workshop on Mathematical Theory and Modelling in Atmosphere-Ocean Science, Report 39/2006. Oberwolfach Reports, 3, 2356-2359.
  3. Lawless, A.S., Nichols, N.K., Reinmueller, K. and Ballard, S.P. (1999), A comparison of two methods for deriving the tangent linear model, Proceedings of the 3rd International Symposium on Assimilation of Observations in Meteorology and Oceanography, Quebec City, 1999, p.105-108.
  4. Lawless, A.S. (1998), An adjoint approach to data assimilation, In Numerical Methods for Fluid Dynamics VI, ed.  M.J. Baines. ICFD, 1998, 379-386.
  5. Lawless, A.S. (1996), A perturbation forecast model and its adjoint, In Preprints volume for American Meteorological Society, 11th Conference on Numerical Weather Prediction, Virginia, August 1996, 128-129.

 

Other reports

 

  1. Lawless, A.S. (2012), Report from International Workshop on Coupled Data Assimilation, University of Reading, 10-12 Sept 2012.
  2. Potthast, R.W.E., Moodey, A.J.F., Lawless, A.S. and van Leeuwen, P.J. (2012), On error dynamics and instability in data assimilation. (Preprint - MPS-2012-05)
  3. Haben, S., Lawless, A.S. and Nichols, N.K. (2009), Conditioning of the 3DVAR Data Assimilation Problem, Mathematics Report 3/2009, Department of Mathematics, The University of Reading.
  4. Baxter, G.M., Dance, S.L., Lawless, A.S., Nichols, N.K. and Ballard, S.P. (2007), Towards Data Assimilation for High Resolution Nested Models, Numerical analysis report 2/07, Department of Mathematics, The University of Reading.
  5. Baxter, G.M., Dance, S.L., Lawless, A.S. and Nichols, N.K. (2006), Scale analysis of observational information in data assimilation, Numerical analysis report 11/06, Department of Mathematics, The University of Reading.
  6. Katz, D., Lawless, A.S., Nichols, N.K., Cullen, M.J.P. and Bannister, R.N. (2006), A comparison of potential vorticity-based and vorticity-based control variables, Numerical analysis report 8/06, Department of Mathematics, The University of Reading.
  7. Lawless, A.S. and Nichols, N.K. (2003), The convergence of incremental 4D-Var using non-tangent linear models In "Research activities in atmospheric and oceanic modelling", ed. J. Cote, pp. 01-17--01-18, WMO CAS/JSG Working Group on Numerical Experimentation, April 2003.
  8. Johnson, C., Nichols, N.K., Hoskins, B.J., Ballard, S.P. and Lawless, A.S. (2002), Four dimensional variational data assimilation in the presence of idealised rapidly growing weather systems, Numerical analysis report 1/02, Department of Mathematics, The University of Reading.
  9. Lawless, A.S. and Nichols, N.K. (1998), A comparison of two methods of deriving the tangent linear model, Forecasting Research Technical Report 257, Met Office, December 1998.
  10. Lawless, A.S. (1998), What will the weather be tomorrow? Why do forecasts go wrong? (In Italian), In Kos (Italian science magazine), March 1998.