Publications of the DARC group

Below a list of publications are given, but please realise that it is difficult to keep this up to date...

Please also visit individual's websites found on the who's who page.

2012| 2011| 2010|

In Preparation/Press

• Kramer, W., H.A. Dijkstra, S. Pierini, and P.J. van Leeuwen (2012) Measuring the impact of observations on the predictability of the Kuroshio Extension in a shallow-water model. Accepted for J. Phys. Oceanogr.
• Van Leeuwen, P.J. and M. Ades (2012) Efficient fully nonlinear data assimilation for geophysical fluid dynamics. Computers and Geosciences, http://dx.doi.org/10.1016/j.cageo.2012.04.015. (In Press)
• Vetra-Carvalho, S., Dixon, M., Migliorini, S., Nichols, N. K. and Ballard, S. P. (2012) Breakdown of hydrostatic balance at convective scales in the forecast errors in the Met Office Unified Model. Quarterly Journal of the Royal Meteorological Society. ISSN 1477-870X doi: 10.1002/qj.1925 (In Press)
• Smith, P. J., Thornhill, G. D., Dance, S. L., Lawless, A. S., Mason, D. C. and Nichols, N. K. (2012) Data assimilation for state and parameter estimation: application to morphodynamic modelling. Quarterly Journal of the Royal Meteorological Society. ISSN 1477-870X (In Press)

2012

• Rudd A. C., Robins, A. G., Lepley, J.J. and Belcher, S. E. (2012) An inverse method for determining source characteristics for emergency response applications Boundary-Layer Meteorology
• Rudd A. C., Roulstone, I. and Eyre, J. R. (2012) A simple column model to explore anticipated problems in variational assimilation of satellite observations Journal of Environmental Modelling & Software, 27-28: 23-39
• Migliorini, S. (2012), On the equivalence between radiance and retrieval assimilation. Mon. Wea. Rev., 140, 258-265. doi: http://dx.doi.org/10.1175/MWR-D-10-05047.1
• Fowler, A. and P.J. van Leeuwen (2012) Measures of observation impact in non-Gaussian data assimilation. Tellus A, 64, 17192.
• Fowler, A., Bannister, R., Eyre, J. (2012) A new floating model level scheme for the assimilation of boundary layer top inversions: The univariate assimilation of temperature. Q. J. R. Met. Soc., 138, 682-698.

2011

• 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.
• 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.
• A.K. Kaiser-Weiss, S. Migliorini (2011), Quasi-optimal assimilation of satellite retrievals for incremental 4D-Var Computers & Fluids, Volume 46, Issue 1, 10th ICFD Conference Series on Numerical Methods for Fluid Dynamics (ICFD 2010), 287-292, doi: 10.1016/j.compfluid.2010.11.016.
• Haben, S., Lawless, A.S. and Nichols, N.K. (2011), Conditioning and Preconditioning of the Variational Data Assimilation Problem. Comput. Fluids, 46, 252-256.
• Bannister R.N.,(2011) Issues in the assimilation of the sources of a trace gas by inverse modelling. Computers & Fluids 46, 106-112.
• Katz D., Lawless A.S., Nichols N.K., Cullen M.J.P., Bannister R.N., (2011) Correlations of control variables in variational data assimilation. Quarterly Journal of the Royal Meteorological Society, 137, 620-630.
• Rennie, S. J., Dance, S. L., Illingworth, A. J., Ballard, S. and Simonin, D. (2011) 3D-Var assimilation of insect-derived Doppler radar radial winds in convective cases using a high resolution model. Monthly Weather Review, 139, 1148-1163
• J.A. Pocock, S.L. Dance and A.S. Lawless (2011) State Estimation using the Particle Filter with Mode Tracking . Computers and Fluids, 46, pp 392-397 doi:10.1016/j.compfluid.2011.02.009
• Brugge, R, Irvine, R., 2011: Readers' forum , Weather, 66 82. doi: 10.1002/wea.760
• G.M. Baxter, S.L. Dance, A.S. Lawless and N.K. Nichols, 2011: Four-dimensional variational data assimilation for high resolution nested models. Computers and Fluids, 46, pp137-141 doi: 10.1016/j.compfluid.2011.01.023
• Polly J. Smith, Sarah L. Dance, Nancy K. Nichols (2011) A hybrid data assimilation scheme for model parameter estimation: application to morphodynamic modelling. Computers and Fluids, 46, pp 436-441 doi:10.1016/j.compfluid.2011.01.010
• Migliorini, S., Dixon, M., Bannister, R., Ballard, S, 2011: Ensemble Prediction for Nowcasting with a Convection-Permitting Model. Part I: Description of the System and the Impact of Radar-Derived Surface Precipitation Rates. Tellus A, 63: 468-496. doi: 10.1111/j.1600-0870.2010.00503.x
• Bannister, R., Migliorini, S., Dixon, M, 2011: Ensemble prediction for nowcasting with a convection-permitting model. Part II: Forecast error statistics. Tellus A, 63: 497-512. doi: 10.1111/j.1600-0870.2010.00500.x
• Vetra-Carvalho S., Migliorini, S. and Nichols, N., 2011 Ensemble data assimilation in the presence of cloud. Comput Fluids, doi:10.1016/j.compfluid.2011.01.033
• Petrie, R.E. and Bannister, R.N., 2011 A method for merging flow-dependent forecast error statistics from an ensemble with static statistics for use in high resolution variational data assimilation, The Journal of Computers and Fluids, 46:387-391 DOI: 10.1016/j.compfluid.2011.01.037
• van Leeuwen, P.J., 2011. Efficient nonlinear Data Assimilation in Geophysical Fluid Dyn amics. Computers and Fluids, In Press, doi:10,1016/j.compfluid.2010.1\ 1.011.

2010

• Nichols, N. K. (2010) Mathematical concepts of data assimilation. In: Lahoz, W., Khattatov, B. and Menard, R. (eds.) Data assimilation: making sense of observations. Springer, pp. 13-40. ISBN 9783540747024
• Brugge, R., 2010. A very wet day over Ireland Weather, 65, 298.
• Brugge, R., 2010: Forty years of the Climatological Observers Link Weather, 65, 139-143.
• Lawless, A.S. (2010) A note on the analysis error associated with 3D-FGAT Q.J.R.Meteorol. Soc., 136, 1094-1098.
• Fowler A.M., Bannister R.N., J. Eyre, 2010 Characterising the background errors for the boundary layer capping inversion. Australian Meteorological and Oceanographic Journal 59, pp. 17-24.
• Bannister R.N.,A.D. Fitt, J. Norbury, H. Ockendon, E. Wilson, (Ed.), 2010 The role of balance in data assimilation. Progress in Industrial Mathematics at ECMI, Mathematics in Industry Series, Vol. 15, 393-400, Springer, 1083 pp.
• Dance, S.L. and Q. P. Zou, 2010: HESS Opinions Ensembles, uncertainty and flood prediction Hydrol. Earth. Syst. Sci. Discuss., 7, 3591-3611 doi: 10.5194/hessd-7-3591-2010
• Rennie, S. J., A. J. Illingworth, and S. L. Dance, 2010: On the differentiation of ground clutter and insects using single-polarisation C-band radars. Atm. Meas. Tech. Discuss., 3, 1843-1860 www.atmos-meas-tech-discuss.net/3/1843/2010/
• D.C. Mason, T.R. Scott, S.L. Dance (2010) Remote sensing of intertidal morphological change in Morecambe Bay, U.K., between 1991 and 2007, Estuarine. Coastal and Shelf Science, Vol 87. No. 3 p487, DOI: 10.1016/j.ecss.2010.01.015.
• Rennie, S.J., Illingworth, A.J., Dance, S.L., Ballard, S. (2010) The accuracy of Doppler radar wind retrievals using insects as targets. Meteorological Applications, Vol. 17, No. 4, pp 419-432, DOI: 10.1002/met.174
• Petrie, R.E., and Dance, S.L. (2010) Ensemble-based data assimilation and the localisation problem. Weather, Vol 65, No. 3, pp65-69, DOI:10.1002/wea.505.
• Migliorini, S., Kaiser-Weiss, A., 2010 Quasi-optimal assimilation of satellite retrievals for incremental 4D-Var Computer & Fluids, in press,doi:10.1016/j.compfluid.2010.11.016.
• Potthast, R, 2010 Orthogonality Sampling for Object Visualization Inverse Problems.
• Potthast, R., Fazi, F. and Nelson, Ph., 2010 Source Splitting via the Point Source Method. Inverse Problems.
• Potthast, R., Ben Hassen, F., Erhard, K. , 2010 The singular sources method for 3d inverse acoustic obstacle scattering problems IMA J.Appl. Math.
• Potthast, R., Burkard, C., 2010 A multi-section approach for rough surface reconstruction via the Kirsch-Kress scheme Inverse Problems Vol. 26, No.4.
• van Leeuwen, P.J., 2010 Nonlinear Data Assimilation in geosciences: an extremely effic ient Particle Filter Q.J.R.Meteorol. Soc., 136, 1991-1996, doi:10,1002/qj699.