Article

Leung, T. Y. ORCID: https://orcid.org/0000-0003-0056-284X, Leutbecher, M., Reich, S. and Shepherd, T. G. ORCID: https://orcid.org/0000-0002-6631-9968 (2021) Forecast verification: relating deterministic and probabilistic metrics. Quarterly Journal of the Royal Meteorological Society, 147 (739). pp. 3124-3134. ISSN 1477-870X doi: https://doi.org/10.1002/qj.4120

Leung, T. Y. ORCID: https://orcid.org/0000-0003-0056-284X, Leutbecher, M., Reich, S. and Shepherd, T. G. ORCID: https://orcid.org/0000-0002-6631-9968 (2020) Impact of the mesoscale range on error growth and the limits to atmospheric predictability. Journal of the Atmospheric Sciences, 77 (11). pp. 3769-3779. ISSN 1520-0469 doi: https://doi.org/10.1175/JAS-D-19-0346.1

Leung, T. Y. ORCID: https://orcid.org/0000-0003-0056-284X, Leutbecher, M., Reich, S. and Shepherd, T. G. ORCID: https://orcid.org/0000-0002-6631-9968 (2019) Atmospheric predictability: revisiting the inherent finite-time barrier. Journal of the Atmospheric Sciences, 76 (12). pp. 3883-3892. ISSN 1520-0469 doi: https://doi.org/10.1175/JAS-D-19-0057.1

Reich, S. (2019) Data assimilation: the Schrödinger perspective. Acta Numerica, 28. pp. 635-711. ISSN 0962-4929 doi: https://doi.org/10.1017/S0962492919000011

Taghvaei, A., de Wiljes, J., Mehta, P. and Reich, S. (2018) Kalman filter and its modern extensions for the continuous-time nonlinear filtering problem. Journal of Dynamic Systems, Measurement, and Control, 140 (3). 030904. ISSN 0022-0434 doi: https://doi.org/10.1115/1.4037780

de Wiljes, J., Reich, S. and Stannat, W. (2018) Long-time stability and accuracy of the ensemble Kalman--Bucy filter for fully observed processes and small measurement noise. SIAM Journal on Applied Dynamical Systems, 17 (2). pp. 1152-1181. ISSN 1536-0040 doi: https://doi.org/10.1137/17M1119056

Acevedo, W., de Wiljes, J. and Reich, S. (2017) Second-order accurate ensemble transform particle filters. SIAM Journal on Scientific Computing, 39 (5). A1834-A1850. ISSN 1095-7197 doi: https://doi.org/10.1137/16M1095184

Chustagulprom, N., Reich, S. and Reinhardt, M. (2016) A hybrid ensemble transform particle filter for nonlinear and spatially extended dynamical systems. SIAM/ASA Journal on Uncertainty Quantification, 4 (1). pp. 592-608. ISSN 2166-2525 doi: https://doi.org/10.1137/15M1040967

Acevedo, W., Reich, S. and Cubasch, U. (2016) Towards the assimilation of tree-ring-width records using ensemble Kalman filtering techniques. Climate Dynamics, 46 (5-6). pp. 1909-1920. ISSN 0930-7575 doi: https://doi.org/10.1007/s00382-015-2683-1

Gregory, A., Cotter, C. J. and Reich, S. (2016) Multilevel ensemble transform particle filtering. SIAM Journal on Scientific Computing, 38 (3). A1317-A1338. ISSN 1064-8275 doi: https://doi.org/10.1137/15M1038232

Aizinger, V., Korn, P., Giorgetta, M. and Reich, S. (2015) Large-scale turbulence modelling via α-regularisation for atmospheric simulations. Journal of Turbulence, 16 (4). pp. 367-391. ISSN 1468-5248 doi: https://doi.org/10.1080/14685248.2014.991443

Escribano, B., Akhmatskaya, E., Reich, S. and Azpiroz, J. M. (2015) Multiple-time-stepping generalized hybrid Monte Carlo methods. Journal of Computational Physics, 280. pp. 1-20. ISSN 0021-9991 doi: https://doi.org/10.1016/j.jcp.2014.08.052

Grewe, V., Brinkop, S., Joeckel, P., Shin, S., Reich, S. and Yserentant, H. (2014) On the theory of mass conserving transformations for Lagrangian methods in 3D atmosphere-chemistry models. Meteorologische Zeitschrift, 23 (4). pp. 441-447. ISSN 0941-2948 doi: https://doi.org/10.1127/0941-2948/2014/0552

Reich, S. and Shin, S. (2014) On the consistency of ensemble transform filter formulations. Journal of Computational Dynamics, 1 (1). pp. 177-189. ISSN 2158-2491 doi: https://doi.org/10.3934/jcd.2014.1.177

Amezcua, J., Ide, K., Kalnay, E. and Reich, S. (2013) Ensemble transform Kalman-Bucy filters. Quarterly Journal of the Royal Meteorological Society, 140 (680). pp. 995-1004. ISSN 1477-870X doi: https://doi.org/10.1002/qj.2186

Reich, S. (2013) A nonparametric ensemble transform method for Bayesian inference. SIAM Journal on Scientific Computing, 35 (4). A2013-A2024. ISSN 1095-7197 doi: https://doi.org/10.1137/130907367

Reich, S. (2012) A Gaussian-mixture ensemble transform filter. Quarterly Journal of the Royal Meteorological Society, 138 (662). pp. 222-233. ISSN 1477-870X doi: https://doi.org/10.1002/qj.898

Reich, S. (2011) A dynamical systems framework for intermittent data assimilation. BIT Numerical Mathematics, 51 (1). pp. 235-249. ISSN 1572-9125 doi: https://doi.org/10.1007/s10543-010-0302-4

Akhmatskaya, E. and Reich, S. (2008) GSHMC: an efficient method for molecular simulation. Journal of Computational Physics, 227 (10). pp. 4934-4954. ISSN 0021-9991 doi: https://doi.org/10.1016/j.jcp.2008.01.023

Conference or Workshop Item

Asgarimehr, M., Zavorotny, V., Zhelavskaya, I., Foti, G., Wickert, J. and Reich, S. (2019) Evolving ocean monitoring with GNSS-R: promises in surface wind speed and prospects for rain detection. In: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 28 JUL- 2 AUG 2019, Yokohoma, Japan, pp. 8692-8695. doi: https://doi.org/10.1109/IGARSS.2019.8900414 (Proceedings of IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium)

Book

Van Leeuwen, P. J., Cheng, Y. and Reich, S. (2015) Nonlinear data assimilation. Frontiers in Applied Dynamical Systems: Reviews and Tutorials, 2. Springer. ISBN 9783319183466