On the representation error in data assimilation T Janjić, N Bormann, M Bocquet, JA Carton, SE Cohn, SL Dance, ... Quarterly Journal of the Royal Meteorological Society 144 (713), 1257-1278, 2018 | 310* | 2018 |
Theoretical insight into diagnosing observation error correlations using observation‐minus‐background and observation‐minus‐analysis statistics JA Waller, SL Dance, NK Nichols Quarterly Journal of the Royal Meteorological Society 142 (694), 418-431, 2016 | 104 | 2016 |
Diagnosing observation error correlations for Doppler radar radial winds in the Met Office UKV model using observation-minus-background and observation-minus-analysis statistics JA Waller, D Simonin, SL Dance, NK Nichols, SP Ballard Monthly Weather Review 144 (10), 3533-3551, 2016 | 88 | 2016 |
Diagnosing horizontal and inter-channel observation error correlations for SEVIRI observations using observation-minus-background and observation-minus-analysis statistics JA Waller, SP Ballard, SL Dance, G Kelly, NK Nichols, D Simonin Remote sensing 8 (7), 581, 2016 | 77 | 2016 |
Diagnosing atmospheric motion vector observation errors for an operational high‐resolution data assimilation system M Cordoba, SL Dance, GA Kelly, NK Nichols, JA Waller Quarterly Journal of the Royal Meteorological Society 143 (702), 333-341, 2017 | 76 | 2017 |
Representativity error for temperature and humidity using the Met Office high‐resolution model JA Waller, SL Dance, AS Lawless, NK Nichols, JR Eyre Quarterly Journal of the Royal Meteorological Society 140 (681), 1189-1197, 2014 | 70 | 2014 |
On the interaction of observation and prior error correlations in data assimilation AM Fowler, SL Dance, JA Waller Quarterly Journal of the Royal Meteorological Society 144 (710), 48-62, 2018 | 51 | 2018 |
Estimating correlated observation error statistics using an ensemble transform Kalman filter JA Waller, SL Dance, AS Lawless, NK Nichols Tellus A: Dynamic Meteorology and Oceanography 66 (1), 23294, 2014 | 42 | 2014 |
A pragmatic strategy for implementing spatially correlated observation errors in an operational system: An application to Doppler radial winds D Simonin, JA Waller, SP Ballard, SL Dance, NK Nichols Quarterly Journal of the Royal Meteorological Society 145 (723), 2772-2790, 2019 | 38 | 2019 |
On diagnosing observation‐error statistics with local ensemble data assimilation JA Waller, SL Dance, NK Nichols Quarterly Journal of the Royal Meteorological Society 143 (708), 2677-2686, 2017 | 35 | 2017 |
Improvements in forecasting intense rainfall: Results from the FRANC (Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection) project SL Dance, SP Ballard, RN Bannister, P Clark, HL Cloke, T Darlington, ... Atmosphere 10 (3), 125, 2019 | 34 | 2019 |
Collecting and utilising crowdsourced data for numerical weather prediction: Propositions from the meeting held in Copenhagen, 4–5 December 2018 KS Hintz, K O'Boyle, SL Dance, S Al‐Ali, I Ansper, D Blaauboer, M Clark, ... Atmospheric Science Letters 20 (7), e921, 2019 | 33 | 2019 |
The conditioning of least‐squares problems in variational data assimilation JM Tabeart, SL Dance, SA Haben, AS Lawless, NK Nichols, JA Waller Numerical Linear Algebra with Applications 25 (5), e2165, 2018 | 31 | 2018 |
Recommendations for improving integration in national end-to-end flood forecasting systems: An overview of the FFIR (Flooding From Intense Rainfall) programme DLA Flack, CJ Skinner, L Hawkness-Smith, G O’Donnell, RJ Thompson, ... Water 11 (4), 725, 2019 | 29 | 2019 |
Improving the condition number of estimated covariance matrices JM Tabeart, SL Dance, AS Lawless, NK Nichols, JA Waller Tellus A: Dynamic Meteorology and Oceanography 72 (1), 1-19, 2020 | 28 | 2020 |
Observation error statistics for Doppler radar radial wind superobservations assimilated into the DWD COSMO-KENDA system JA Waller, E Bauernschubert, SL Dance, NK Nichols, R Potthast, ... Monthly Weather Review 147 (9), 3351-3364, 2019 | 25 | 2019 |
Assessment of observation quality for data assimilation in flood models JA Waller, J García-Pintado, DC Mason, SL Dance, NK Nichols Hydrology and Earth System Sciences 22 (7), 3983-3992, 2018 | 18* | 2018 |
State estimation using the particle filter with mode tracking JA Pocock, SL Dance, AS Lawless Computers & fluids 46 (1), 392-397, 2011 | 18 | 2011 |
The impact of using reconditioned correlated observation‐error covariance matrices in the Met Office 1D‐Var system JM Tabeart, SL Dance, AS Lawless, S Migliorini, NK Nichols, F Smith, ... Quarterly Journal of the Royal Meteorological Society 146 (728), 1372-1390, 2020 | 16 | 2020 |
Using observations at different spatial scales in data assimilation for environmental prediction JA Waller University of Reading, Department of Mathematics and Statistics (School of …, 2013 | 15 | 2013 |