Our latest research articles

  • Waller, J.A., E. Bauernschubert, S.L. Dance, N.K. Nichols, R. Potthast, and D. Simonin, (2019): Observation error statistics for Doppler Radar radial wind superobservations assimilated into the DWD COSMO-KENDA system. Mon. Wea. Rev., doi:10.1175/MWR-D-19-0104.1
  • Simonin, D. , Waller, J. A., Ballard, S. P., Dance, S. L. and Nichols, N. K. (2019), A pragmatic strategy for implementing spatially correlated observation errors in an operational system: an application to Doppler radial winds. Q J R Meteorol Soc. Accepted Author Manuscript. doi:10.1002/qj.3592
  • Hintz, KSO’Boyle, KDance, SLet alCollecting and utilising crowdsourced data for numerical weather prediction: Propositions from the meeting held in Copenhagen, 4–December 5, 2018Atmos Sci Lett.2019;e921. doi:10.1002/asl.921
  • Cooper, E. S., Dance, S. L., García-Pintado, J., Nichols, N. K., and Smith, P. J. (2019) Observation operators for assimilation of satellite observations in fluvial inundation forecasting, Hydrol. Earth Syst. Sci., 23, 2541-2559, doi:10.5194/hess-23-2541-2019
  • Mirza, A. K., Ballard, S. P., Dance, S. L., Rooney, G. G. and Stone, E. K. (2019), Towards operational use of aircraft‐derived observations: a case study at London Heathrow airport.. Meteorol Appl. Accepted Author Manuscript. doi:10.1002/met.1782
  • J. Holzke and J. A. Waller, ‘Improving Aircraft-Derived Temperature Observations Using Data Assimilation’, Reinvention: an International Journal of Undergraduate Research, Volume 11, Issue 2, 2018, http://centaur.reading.ac.uk/78398/.
  • Mason, D. C., Dance, S. L., Vetra-Carvalho, S. and Cloke, H. L. (2018) Robust algorithm for detecting floodwater in urban areas using Synthetic Aperture Radar images. Journal of Applied Remote Sensing, 12 (4). 045011. doi: 10.1117/1.JRS.12.045011
  • Waller, J. A., Garcia-Pintado, J., Mason, D. C., Dance, S. L. and Nichols, N. K. (2018) Technical note: assessment of observation quality for data assimilation in flood models. Hydrology and Earth System Sciences.  doi: 10.5194/hess-2018-43
  • Cooper ES, Dance SL, Garcia-Pintado J, Nichols NK, Smith PJ (2018)Observation impact, domain length and parameter estimation in data assimilation for flood forecasting. Environmental Modelling and Software. 104. pp. 199-214 doi: 10.1016/j.envsoft.2018.03.013
  • Tabeart JM, Dance SL, Haben SA, Lawless AS, Nichols NK, Waller JA (2018) The conditioning of least-squares problems in variational data assimilation. Numer. Linear Algebra Appl. 2018;e2165. Accepted. doi:10.1002/nla.2165
  • S. Vetra-Carvalho, P. J. Van Leeuwen, L. Nerger, A. Barth, M U. Altaf, P. Brasseur, P. Kirchgessner, J.-M. Beckers, Tellus A: Dynamic Meteorology and Oceanography, (2018). Vol 70:1, p. 1445364. “State-of-the-art stochastic data assimilation methods for high-dimensional non-Gaussian problems”
  • Fowler, A. M., Dance, S. L. and Waller, J. A. (2018), On the interaction of observation and prior error correlations in data assimilation. Q.J.R. Meteorol. Soc., 144: 48-62. doi:10.1002/qj.3183
  • Janjić, T., Bormann, N., Bocquet, M., Carton, J. A., Cohn, S. E., Dance, S. L., Losa, S. N., Nichols, N. K., Potthast, R., Waller, J. A. and Weston, P. (2017), On the representation error in data assimilation. Q.J.R. Meteorol. Soc.. doi:10.1002/qj.3130
  • Waller, J. A., Dance, S. L. and Nichols, N. K. (2017), On diagnosing observation-error statistics with local ensemble data assimilation. Q.J.R. Meteorol. Soc.. doi:10.1002/qj.3117