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  • Bannister RN. 2008a. A review of forecast-error covariance statistics in atmospheric variational data assimilation. I: Characteristics and measurements of forecast-error covariances. Q. J. R. Meteorol. Soc. 134: 19551970.
  • Bannister RN. 2008b. A review of forecast-error covariance statistics in atmospheric variational data assimilation. II: Modelling the forecast-error covariance statistics. Q. J. R. Meteorol. Soc. 134: 19711996.
  • Bell MJ, Martin MJ, Nichols NK. 2004. Assimilation of data into an ocean model with systematic errors near the Equator. Q. J. R. Meteorol. Soc. 130: 873894.
  • Beven K, Binley A. 1992. The future of distributed models: model calibration and uncertainty prediction. Hydrol. Proc. 6: 279298.
  • Brown JD, Spencer T, Moeller I. 2007. Modeling storm surge flooding of an urban area with particular reference to modeling uncertainities: A case study of Canvey Island, UK. Water Resources Res. 43: W06402, DOI: 10.1029/2005WR004597.
  • Daley R. 1991. Atmospheric Data Analysis. Cambridge University Press: Cambridge, UK.
  • Dee DP. 2005. Bias and data assimilation. Q. J. R. Meteorol. Soc. 131: 33233343.
  • Ehrendorfer M. 2007. A review of issues in ensemble-based Kalman filtering. Meteorol. Z. 16: 795818.
  • Ghil M, Malanotte-Rizzoli P. 1991. Data assimilation in meteorology and oceanography. Adv. Geophys. 33: 141266.
  • Gill PE, Murray W, Wright MH. 1981. Practical Optimization. Academic Press.
  • Griffith AK, Nichols NK. 2000. Adjoint techniques in data assimilation for treating systematic model error. J. Flow Turb. Combust. 65: 469488.
  • Hansen JA, Penland C. 2007. On stochastic parameter estimation using data assimilation. Physica D 230: 8898.
  • Hesselink AW, Stelling GS, Kwadijk JCJ, Middelkoop H. 2003. Inundation of a Dutch river polder; sensitivity analysis of a physically based inundation model using historic data. Water Resources Res. 39: 1234, DOI: 10.1029/2002WR001334.
  • Hill DC, Jones SE, Prandle D. 2003. Derivation of sediment resuspension rates from acoustic backscatter time-series in tidal waters. Continental Shelf Res. 23: 1940.
  • Houtekamer PL, Mitchell HL. 1998. Data assimilation using an Ensemble Kalman Filter technique. Mon. Weather Rev. 126: 796811.
  • Houtekamer PL, Mitchell HL. 2005. Ensemble Kalman filtering. Q. J. R. Meteorol. Soc. 131: 32693289.
  • Hudson J. 2001. ‘Numerical techniques for morphodynamic modelling’. PhD thesis, University of Reading, UK. Available at http://www.reading.ac.uk/maths-and-stats/research/maths-phdtheses.aspx.
  • Ide KP, Courtier P, Ghil M, Lorenc AC. 1997. Unified notation for data assimilation: Operational, sequential and variational. J. Meteorol. Soc. Japan 75: 181189.
  • Jazwinski AH. 1970. Stochastic Processes and Filtering Theory. Academic Press.
  • Johnson C. 2003. ‘Information content of observations in variational data assimilation’. PhD thesis, University of Reading, UK. Available at http://www.reading.ac.uk/maths-and-stats/research/maths-phdtheses.aspx.
  • Johnson C, Hoskins BJ, Nichols NK. 2005. A singular vector perspective of 4D-Var: Filtering and interpolation. Q. J. R. Meteorol. Soc. 131: 119.
  • Kalnay E. 2003. Atmospheric Modeling, Data Assimilation and Predictability. Cambridge University Press: Cambridge, UK.
  • Knaapen MAF, Hulscher SJMH. 2003. Use of a genetic algorithm to improve prediction of alternate bar dynamics. Water Resources Res. 39: 1231, DOI: 10.1029/2002WR001793.
  • Lesser GR, Roelvink JA, van Kester JATM, Stelling GS. 2004. Development and validation of a three-dimensional morphological model. Coastal Eng. 51: 883915.
  • Lewis JM, Lakshmivarahan S, Dhall SK. 2006. Dynamic Data Assimilation: A Least Squares Approach. Encyclopedia of Mathematics and its applications 104: Cambridge University Press: Cambridge, UK.
  • Long W, Kirby JT, Shao Z. 2008. A numerical scheme for morphological bed level calculations. Coastal Eng. 55: 167180.
  • Lorenc AC. 1981. A global three-dimensional multivariate statistical interpolation scheme. Mon. Weather Rev. 109: 701721.
  • Martin MJ, Nichols NK, Bell MJ. 1999. ‘Treatment of systematic errors in sequential data assimilation’. Technical Note No. 21, Ocean Applications Division, Met Office: Exeter, UK.
  • Mason DC, Garg PK. 2001. Morphodynamic modelling of intertidal sediment transport in Morecambe Bay. Estuar. Coast. Shelf Sci. 53: 7992.
  • Mason DC, Amin M, Davenport IJ, Flather RA, Robinson GJ, Smith JA. 1999. Measurement of recent intertidal sediment transport in Morecambe Bay using the waterline method. Estuar. Coast. Shelf Sci. 49: 427456.
  • Mason DC, Davenport IJ, Flather RA, Gurney C, Robinson GJ, Smith JA. 2001. A sensitivity analysis of the waterline method of constructing a digital elevation model for intertidal areas in an ERS SAR scene of eastern England. Estuar. Coast. Shelf Sci. 53: 759778.
  • Navon IM. 1997. Practical and theoretical aspects of adjoint parameter estimation and identifiability in meteorology and oceanography. Dyn. Atmos. Oceans 27: 5579.
  • Nichols NK. 2009. Mathematical concepts of data assimilation. In Data Assimilation: Making Sense of Observations. Lahoz WA, Swinbank R, Khattatov B. (eds) Springer: Berlin. 1340.
  • Nicholls RJ, Wong PP, Burkett VR, Codignotto JO, Hay JE, McLean RF, Ragoonaden S, Woodroffe CD. 2007. Coastal systems and low-lying areas. Chapter 6 in Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE. (eds) Cambridge University Press: Cambridge, UK. 315356.
  • Rodgers CD. 2000. Inverse Methods for Atmospheric Sounding: Theory and Practice. Series on Atmospheric, Oceanic and Planetary Physics, 2: World Scientific, Singapore.
  • Ruessink BG. 2005a. Calibration of nearshore process models—application of a hybrid genetic algorithm. J. Hydroinform. 7: 135149.
  • Ruessink BG. 2005b. Predictive uncertainity of a nearshore bed evolution model. Cont. Shelf Res. 25: 10531069.
  • Ruessink BG. 2006. A Bayesian estimation of parameter-induced uncertainty in a nearshore alongshore current model. J. Hydroinform. 7: 3749.
  • Scott TR, Mason DC. 2007. Data assimilation for a coastal area morphodynamic model: Morecambe Bay. Coastal Eng. 54: 91109.
  • Scott TR, Smith PJ, Dance SL, Mason DC, Baines MJ, Nichols NK, Horsburgh KJ, Sweby PK, Lawless AS. 2009. Data assimilation for morphodynamic prediction and predictability. In Coastal Engineering 2008, Proceedings of the 31st Internat. Conference, Hamburg, Germany, 31 Aug–5 Sept 2008. 3: 23862398.
  • Shoreline Management Partnership. 1996. Morecambe Bay Shoreline Management Plan. Report to the Cumbria Coastal Consortium. Consultation Document, Stage 1, Volume 2.
  • Smith PJ. 2010. ‘Joint state and parameter estimation using data assimilation with application to morphodynamic modelling’. PhD thesis, University of Reading, UK. Available at http://www.reading.ac.uk/maths-and-stats/research/maths-phdtheses.aspx.
  • Smith PJ, Baines MJ, Dance SL, Nichols NK, Scott TR. 2009a. Variational data assimilation for parameter estimation: application to a simple morphodynamic model. Ocean Dyn. 59: 697708.
  • Smith PJ, Dance SL, Nichols NK. 2009b. ‘Data assimilation for morphodynamic model parameter estimation: a hybrid approach’. Mathematics Report 2/2009, Department of Mathematics, University of Reading, UK. Available at http://www.reading.ac.uk/maths-and-stats/research/maths-research.aspx.
  • Smith PJ, Dance SL, Nichols NK. 2010. ‘A hybrid sequential data assimilation scheme for model state and parameter estimation’. Mathematics Report 2/2010, Department of Mathematics, University of Reading, UK. Available at http://www.reading.ac.uk/maths-and-stats/research/maths-research.aspx.
  • Smith PJ, Dance SL, Nichols NK. 2011. A hybrid data assimilation scheme for model parameter estimation: application to morphodynamic modelling. 10th ICFD Conference Series on Numerical Methods for Fluid Dynamics (ICFD 2010). Computers & Fluids 46: 436441.
  • Soulsby RL. 1997. Dynamics of marine sands. Thomas Telford Publications: London.
  • Spiegelman M, Katz RF. 2006. A semi-Lagrangian Crank–Nicolson algorithm for the numerical solution of advection-diffusion problems. Geochem. Geophys. Geosyst. 7: Q04014, DOI: 10.1029/2005GC001073.
  • Sutherland J, Peet AH, Soulsby RL. 2004. Evaluating the performance of morphological models. Coastal Eng. 51: 917939.
  • Thornhill GD, Mason DC, Dance SL, Lawless AS, Nichols NK, Forbes H. 2012. ‘Integration of a 3D variational data assimilation scheme with a coastal area morphodynamic model’. Preprint Series, number MPS 2012-01, Department of Mathematics: University of Reading, UK. Available at http://www.reading.ac.uk/maths-and-stats/research/maths-research.aspx.
  • Trudinger CM, Raupach MR, Rayner PJ, Enting IG. 2008. Using the Kalman filter for parameter estimation in biogeochemical models. Environmetrics 19: 849870.
  • van Rijn LC. 1993. Principles of Sediment Transport in Rivers, Estuaries and Coastal Seas. Aqua Publications: Blokzijl, the Netherlands.
  • Wüst JC. 2004. Data-driven probabilistic predictions of sand wave bathymetry. In Marine Sandwave and River Dune Dynamics II. Hulsher SJMH, Garlan T, Idier D. (eds) Proceedings of International Workshop, University of Twente, the Netherlands. 338345.