| Particle filters for high‐dimensional geoscience applications: A review PJ Van Leeuwen, HR Künsch, L Nerger, R Potthast, S Reich Quarterly Journal of the Royal Meteorological Society 145 (723), 2335-2365, 2019 | 230 | 2019 |
| Software for ensemble-based data assimilation systems–implementation strategies and scalability L Nerger, W Hiller Computers & Geosciences 55, 110-118, 2013 | 219 | 2013 |
| 3D grazing collision of two black holes M Alcubierre, W Benger, B Brügmann, G Lanfermann, L Nerger, E Seidel, ... Physical review letters 87 (27), 271103, 2001 | 127 | 2001 |
| A comparison of error subspace Kalman filters L Nerger, W Hiller, J Schröter Tellus A: Dynamic Meteorology and Oceanography 57 (5), 715-735, 2005 | 123 | 2005 |
| A unification of ensemble square root Kalman filters L Nerger, T Janjić, J Schröter, W Hiller Monthly Weather Review 140 (7), 2335-2345, 2012 | 120 | 2012 |
| State-of-the-art stochastic data assimilation methods for high-dimensional non-Gaussian problems S Vetra-Carvalho, PJ Van Leeuwen, L Nerger, A Barth, MU Altaf, ... Tellus A: Dynamic Meteorology and Oceanography 70 (1), 1-43, 2018 | 111 | 2018 |
| Assimilating SMOS sea ice thickness into a coupled ice‐ocean model using a local SEIK filter Q Yang, SN Losa, M Losch, X Tian‐Kunze, L Nerger, J Liu, L Kaleschke, ... Journal of Geophysical Research: Oceans 119 (10), 6680-6692, 2014 | 100 | 2014 |
| On domain localization in ensemble-based Kalman filter algorithms T Janjić, L Nerger, A Albertella, J Schröter, S Skachko Monthly Weather Review 139 (7), 2046-2060, 2011 | 99 | 2011 |
| PDAF-the parallel data assimilation framework: experiences with Kalman filtering L Nerger, W Hiller, J Schröter Use of high performance computing in meteorology, 63-83, 2005 | 97 | 2005 |
| Assimilation of SeaWiFS data into a global ocean-biogeochemical model using a local SEIK filter L Nerger, WW Gregg Journal of Marine Systems 68 (1-2), 237-254, 2007 | 83 | 2007 |
| A regulated localization scheme for ensemble‐based Kalman filters L Nerger, T Janjić, J Schröter, W Hiller Quarterly Journal of the Royal Meteorological Society 138 (664), 802-812, 2012 | 79 | 2012 |
| Using sea-level data to constrain a finite-element primitive-equation ocean model with a local SEIK filter L Nerger, S Danilov, W Hiller, J Schröter Ocean Dynamics 56, 634-649, 2006 | 76 | 2006 |
| Improving sea ice thickness estimates by assimilating CryoSat‐2 and SMOS sea ice thickness data simultaneously L Mu, Q Yang, M Losch, SN Losa, R Ricker, L Nerger, X Liang Quarterly Journal of the Royal Meteorological Society 144 (711), 529-538, 2018 | 67 | 2018 |
| On the choice of an optimal localization radius in ensemble Kalman filter methods P Kirchgessner, L Nerger, A Bunse-Gerstner Monthly Weather Review 142 (6), 2165-2175, 2014 | 65 | 2014 |
| Arctic‐wide sea ice thickness estimates from combining satellite remote sensing data and a dynamic ice‐ocean model with data assimilation during the CryoSat‐2 period L Mu, M Losch, Q Yang, R Ricker, SN Losa, L Nerger Journal of Geophysical Research: Oceans 123 (11), 7763-7780, 2018 | 61 | 2018 |
| Improving assimilation of SeaWiFS data by the application of bias correction with a local SEIK filter L Nerger, WW Gregg Journal of marine systems 73 (1-2), 87-102, 2008 | 41 | 2008 |
| Assimilating summer sea-ice concentration into a coupled ice–ocean model using a LSEIK filter Q Yang, SN Losa, M Losch, J Liu, Z Zhang, L Nerger, H Yang Annals of Glaciology 56 (69), 38-44, 2015 | 39 | 2015 |
| An ensemble Kalman filter for the time‐dependent analysis of the geomagnetic field A Fournier, L Nerger, J Aubert Geochemistry, Geophysics, Geosystems 14 (10), 4035-4043, 2013 | 39 | 2013 |
| Towards reliable Arctic sea ice prediction using multivariate data assimilation J Liu, Z Chen, Y Hu, Y Zhang, Y Ding, X Cheng, Q Yang, L Nerger, ... Science Bulletin 64 (1), 63-72, 2019 | 38 | 2019 |
| On serial observation processing in localized ensemble Kalman filters L Nerger Monthly Weather Review 143 (5), 1554-1567, 2015 | 36 | 2015 |
