2024

Pasmans, I. ORCID: https://orcid.org/0000-0001-5076-5421, Chen, Y. ORCID: https://orcid.org/0000-0002-2319-6937, Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Jones, C. K. R. T. (2024) Tailoring data assimilation to discontinuous Galerkin models. Quarterly Journal of the Royal Meteorological Society. ISSN 0035-9009 doi: https://doi.org/10.1002/qj.4737

Chen, Y. ORCID: https://orcid.org/0000-0002-2319-6937, Smith, P. ORCID: https://orcid.org/0000-0003-4570-4127, Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Pasmans, I. ORCID: https://orcid.org/0000-0001-5076-5421, Bertino, L., Bocquet, M., Sebastian Finn, T., Rampal, P. and Dansereau, V. (2024) Multivariate state and parameter estimation with data assimilation applied to sea-ice models using a Maxwell elasto-brittle rheology. The Cryosphere, 18 (5). pp. 2381-2406. ISSN 1994-0424 doi: https://doi.org/10.5194/tc-18-2381-2024

Higgs, I., Skákala, J., Bannister, R. ORCID: https://orcid.org/0000-0002-6846-8297, Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Ciavatta, S. (2024) Investigating ecosystem connections in the shelf sea environment using complex networks. Biogeosciences, 21 (3). pp. 731-746. ISSN 1726-4189 doi: https://doi.org/10.5194/bg-21-731-2024

2023

Finn, T. S., Durand, C., Farchi, A., Bocquet, M., Chen, Y. ORCID: https://orcid.org/0000-0002-2319-6937, Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Dansereau, V. (2023) Deep learning subgrid-scale parametrisations for short-term forecasting of sea-ice dynamics with a Maxwell elasto-brittle rheology. The Cryosphere, 17 (7). pp. 2965-2991. ISSN 1994-0424 doi: https://doi.org/10.5194/tc-17-2965-2023

Cheng, S., Quilodrán-Casas, C., Ouala, S., Farchi, A., Liu, C., Tandeo, P., Fablet, R., Lucor, D., Iooss, B., Brajard, J., Xiao, D., Janjic, T., Ding, W., Guo, Y., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Bocquet, M. and Arcucci, R. (2023) Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review. IEEE/CAA Journal of Automatica Sinica, 10 (6). pp. 1361-1387. ISSN 2329-9266 doi: https://doi.org/10.1109/JAS.2023.123537

Cheng, S., Chen, Y. ORCID: https://orcid.org/0000-0002-2319-6937, Aydoğdu, A., Bertino, L., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Rampal, P. and Jones, C. K. R. T. (2023) Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020. The Cryosphere, 17 (4). pp. 1735-1754. ISSN 1994-0424 doi: https://doi.org/10.5194/tc-17-1735-2023

Ayers, D. ORCID: https://orcid.org/0000-0002-5667-8174, Lau, J., Amezcua, J. ORCID: https://orcid.org/0000-0002-4952-8354, Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 (2023) Supervised machine learning to estimate instabilities in chaotic systems: estimation of local Lyapunov exponents. Quarterly Journal of the Royal Meteorological Society, 149 (753). pp. 1236-1262. ISSN 1477-870X doi: https://doi.org/10.1002/qj.4450

2022

Baguis, P., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Roulin, E., Vannitsem, S., Modanesi, S., Lievens, H., Bechtold, M. ORCID: https://orcid.org/0000-0002-8042-9792 and De Lannoy, G. ORCID: https://orcid.org/0000-0002-6743-7122 (2022) Assimilation of backscatter observations into a hydrological model: a case study in Belgium using ASCAT data. Remote Sensing, 14 (22). 5740. ISSN 2072-4292 doi: https://doi.org/10.3390/rs14225740

De Lannoy, G. J. M., Bechtold, M., Albergel, C., Brocca, L., Calvet, J.-C., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Crow, W. T., de Rosnay, P., Durand, M., Forman, B., Geppert, G., Girotto, M., Hendricks Franssen, H.-J., Jonas, T., Kumar, S., Lievens, H., Lu, Y., Massari, C., Pauwels, V. R. N., Reichle, R. H. and Steele-Dunne, S. (2022) Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication. Frontiers in Water, 4. ISSN 2624-9375 doi: https://doi.org/10.3389/frwa.2022.981745

Scheffler, G. ORCID: https://orcid.org/0000-0002-6474-1372, Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Ruiz, J. and Pulido, M. (2022) Dynamical effects of inflation in ensemble‐based data assimilation under the presence of model error. Quarterly Journal of the Royal Meteorological Society, 148 (746). pp. 2368-2383. ISSN 1477-870X doi: https://doi.org/10.1002/qj.4307

Schevenhoven, F. and Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 (2022) Training a supermodel with noisy and sparse observations: a case study with CPT and the synch rule on SPEEDO – v.1. Geoscientific Model Development, 15 (9). pp. 3831-3844. ISSN 1991-9603 doi: https://doi.org/10.5194/gmd-15-3831-2022

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Bocquet, M., Demaeyer, J., Grudzien, C., Raanes, P. and Vannitsem, S. (2022) Data Assimilation for Chaotic Dynamics. In: Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV). Springer International Publishing, pp. 1-42. ISBN 9783030777227 doi: https://doi.org/10.1007/978-3-030-77722-7_1

2021

Chen, Y. ORCID: https://orcid.org/0000-0002-2319-6937, Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Lucarini, V. ORCID: https://orcid.org/0000-0001-9392-1471 (2021) Inferring the instability of a dynamical system from the skill of data assimilation exercises. Nonlinear Processes in Geophysics, 28 (4). pp. 633-649. ISSN 1023-5809 doi: https://doi.org/10.5194/npg-28-633-2021

Evensen, G., Amezcua, J., Bocquet, M., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Farchi, A., Fowler, A. ORCID: https://orcid.org/0000-0003-3650-3948, Houtekamer, P. L., Jones, C. K., de Moraes, R. J., Pulido, M., Sampson, C. and Vossepoel, F. C. (2021) An international initiative of predicting the Sars-Cov-2 pandemic using ensemble data assimilation. Foundations of Data Science, 3 (3). pp. 413-477. ISSN 2639-8001 doi: https://doi.org/10.3934/fods.2021001

Brajard, J. ORCID: https://orcid.org/0000-0003-0634-1482, Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Bocquet, M. and Bertino, L. (2021) Combining data assimilation and machine learning to infer unresolved scale parametrization. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 379 (2194). 20200086. ISSN 1364-503X doi: https://doi.org/10.1098/rsta.2020.0086

Bonavita, M., Arcucci, R., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Dueben, P., Geer, A. J., Le Saux, B., Longépé, N., Mathieu, P.-P. and Raynaud, L. (2021) Machine learning for earth system observation and prediction. Bulletin of the American Meteorological Society, 102 (4). E710-E716. ISSN 1520-0477 doi: https://doi.org/10.1175/BAMS-D-20-0307.1

Sampson, C. ORCID: https://orcid.org/0000-0002-4275-4877, Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Aydogdu, A. ORCID: https://orcid.org/0000-0002-1557-7502 and Jones, C. K.R.T. (2021) Ensemble Kalman Filter for non‐conservative moving mesh solvers with a joint physics and mesh location update. Quarterly Journal of the Royal Meteorological Society, 147 (736). pp. 1539-1567. ISSN 0035-9009 doi: https://doi.org/10.1002/qj.3980

2020

Cheng, S. ORCID: https://orcid.org/0000-0002-7304-2442, Aydoğdu, A. ORCID: https://orcid.org/0000-0002-1557-7502, Rampal, P., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Bertino, L. (2020) Probabilistic forecasts of sea ice trajectories in the arctic: impact of uncertainties in surface wind and ice cohesion. Oceans, 1 (4). pp. 326-342. ISSN 2673-1924 doi: https://doi.org/10.3390/oceans1040022

Tandeo, P., Ailliot, P., Bocquet, M., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Miyoshi, T., Pulido, M. and Zhen, Y. (2020) A review of innovation-based methods to jointly estimate model and observation error covariance matrices in ensemble data assimilation. Monthly Weather Review, 148 (10). ISSN 0027-0644 doi: https://doi.org/10.1175/MWR-D-19-0240.1

Brajard, J., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Bocquet, M. and Bertino, L. (2020) Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model. Journal of Computational Science, 44. 101171. ISSN 2153-4136 doi: https://doi.org/10.1016/j.jocs.2020.101171

Grudzien, C., Bocquet, M. and Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 (2020) On the numerical integration of the Lorenz-96 model, with scalar additive noise, for benchmark twin experiments. Geoscientific Model Development, 13 (4). pp. 1903-1924. ISSN 1991-9603 doi: https://doi.org/10.5194/gmd-13-1903-2020

Bocquet, M., Brajard, J., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Bertino, L. (2020) Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization. Foundations of Data Science, 2 (1). pp. 55-80. ISSN 2639-8001 doi: https://doi.org/10.3934/fods.2020004

Tondeur, M., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Vannitsem, S. and Bocquet, M. (2020) On temporal scale separation in coupled data assimilation with the ensemble Kalman filter. Journal of Statistical Physics, 179 (5-6). pp. 1161-1185. ISSN 0022-4715 doi: https://doi.org/10.1007/s10955-020-02525-z

2019

Schevenhoven, F., Selten, F., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Keenlyside, N. (2019) Improving weather and climate predictions by training of supermodels. Earth System Dynamics, 10 (4). pp. 789-807. ISSN 2190-4987 doi: https://doi.org/10.5194/esd-10-789-2019

Aydoğdu, A., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Guider, C. T., Jones, C. K. R. T. and Rampal, P. (2019) Data assimilation using adaptive, non-conservative, moving mesh models. Nonlinear Processes in Geophysics, 26 (3). pp. 175-193. ISSN 1607-7946 doi: https://doi.org/10.5194/npg-26-175-2019

Bocquet, M., Brajard, J., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Bertino, L. (2019) Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models. Nonlinear Processes in Geophysics, 26 (3). pp. 143-162. ISSN 1607-7946 doi: https://doi.org/10.5194/npg-26-143-2019

Metref, S., Hannart, A., Ruiz, J., Bocquet, M., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Ghil, M. (2019) Estimating model evidence using ensemble‐based data assimilation with localization – the model selection problem. Quarterly Journal of the Royal Meteorological Society, 145 (721). pp. 1571-1588. ISSN 0035-9009 doi: https://doi.org/10.1002/qj.3513

Raanes, P. N., Bocquet, M. and Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 (2019) Adaptive covariance inflation in the ensemble Kalman filter by Gaussian scale mixtures. Quarterly Journal of the Royal Meteorological Society, 145 (718). pp. 53-75. ISSN 0035-9009 doi: https://doi.org/10.1002/qj.3386

2018

Grudzien, C., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Bocquet, M. (2018) Asymptotic forecast uncertainty and the unstable subspace in the presence of additive model error. SIAM/ASA Journal on Uncertainty Quantification, 6 (4). pp. 1335-1363. ISSN 2166-2525 doi: https://doi.org/10.1137/17M114073X

Grudzien, C., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Bocquet, M. (2018) Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error. Nonlinear Processes in Geophysics, 25 (3). pp. 633-648. ISSN 1023-5809 doi: https://doi.org/10.5194/npg-25-633-2018

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Bocquet, M., Bertino, L. and Evensen, G. (2018) Data assimilation in the geosciences: an overview of methods, issues, and perspectives. Wiley Interdisciplinary Reviews: Climate Change, 9 (5). e535. ISSN 1757-7799 doi: https://doi.org/10.1002/wcc.535

Yano, J.-I., Ziemiański, M. Z., Cullen, M., Termonia, P., Onvlee, J., Bengtsson, L., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Davy, R., Deluca, A., Gray, S. ORCID: https://orcid.org/0000-0001-8658-362X, Homar, V., Köhler, M., Krichak, S., Michaelides, S., Phillips, V. T. J., Soares, P. M. M. and Wyszogrodzki, A. A. (2018) Scientific challenges of convective-scale numerical weather prediction. Bulletin of the American Meteorological Society, 99 (4). pp. 699-710. ISSN 1520-0477 doi: https://doi.org/10.1175/bams-d-17-0125.1

Pulido, M., Tandeo, P., Bocquet, M., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Lucini, M. (2018) Stochastic parameterization identification using ensemble Kalman filtering combined with maximum likelihood methods. Tellus A: Dynamic Meteorology and Oceanography, 70 (1). pp. 1-17. ISSN 1600-0870 doi: https://doi.org/10.1080/16000870.2018.1442099

Rabatel, M., Rampal, P., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Bertino, L. and Jones, C. K. R. T. (2018) Impact of rheology on probabilistic forecasts of sea ice trajectories: application for search and rescue operations in the Arctic. The Cryosphere, 12 (3). pp. 935-953. ISSN 1994-0424 doi: https://doi.org/10.5194/tc-12-935-2018

2017

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Bocquet, M., Hannart, A. and Ghil, M. (2017) Estimating model evidence using data assimilation. Quarterly Journal of the Royal Meteorological Society, 143 (703). pp. 866-880. ISSN 1477-870X doi: https://doi.org/10.1002/qj.2972

Bocquet, M., Gurumoorthy, K. S., Apte, A., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Grudzien, C. and Jones, C. K. R. T. (2017) Degenerate Kalman filter error covariances and their convergence onto the unstable subspace. SIAM/ASA Journal on Uncertainty Quantification, 5 (1). pp. 304-333. ISSN 2166-2525 doi: https://doi.org/10.1137/16M1068712

Bocquet, M. and Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 (2017) Four-dimensional ensemble variational data assimilation and the unstable subspace. Tellus A: Dynamic Meteorology and Oceanography, 69 (1). 1304504. ISSN 1600-0870 doi: https://doi.org/10.1080/16000870.2017.1304504

Gurumoorthy, K. S., Grudzien, C., Apte, A., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Jones, C. K. R. T. (2017) Rank deficiency of Kalman error covariance matrices in linear time-varying system with deterministic evolution. SIAM Journal on Control and Optimization, 55 (2). pp. 741-759. ISSN 0363-0129 doi: https://doi.org/10.1137/15M1025839

2016

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Vannitsem, S. (2016) Deterministic treatment of model error in geophysical data assimilation. In: Ancona, F., Cannarsa, P., Jones, C. and Portaluri, A. (eds.) Mathematical Paradigms of Climate Science. Springer INdAM Series, 15. Springer, pp. 175-213. doi: https://doi.org/10.1007/978-3-319-39092-5_9

Pazó, D., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and López, J. M. (2016) Data assimilation by delay-coordinate nudging. Quarterly Journal of the Royal Meteorological Society, 142 (696). pp. 1290-1299. ISSN 0035-9009 doi: https://doi.org/10.1002/qj.2732

Hannart, A., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Bocquet, M., Ghil, M., Naveau, P., Pulido, M., Ruiz, J. and Tandeo, P. (2016) DADA: data assimilation for the detection and attribution of weather and climate-related events. Climatic Change, 136 (2). pp. 155-174. ISSN 0165-0009 doi: https://doi.org/10.1007/s10584-016-1595-3

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Guemas, V., Doblas-Reyes, F. J., Volpi, D. and Asif, M. (2016) Sources of skill in near-term climate prediction: generating initial conditions. Climate Dynamics, 47 (12). pp. 3693-3712. ISSN 0930-7575 doi: https://doi.org/10.1007/s00382-016-3036-4

2015

Weber, R. J. T., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Doblas-Reyes, F. J. (2015) Linking the anomaly initialization approach to the mapping paradigm: a proof-of-concept study. Monthly Weather Review, 143 (11). pp. 4695-4713. ISSN 0027-0644 doi: https://doi.org/10.1175/MWR-D-14-00398.1

Mitchell, L. and Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 (2015) Accounting for model error due to unresolved scales within ensemble Kalman filtering. Quarterly Journal of the Royal Meteorological Society, 141 (689). pp. 1417-1428. ISSN 1477-870X doi: https://doi.org/10.1002/qj.2451

Raanes, P. N., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Bertino, L. (2015) Extending the square root method to account for additive forecast noise in ensemble methods. Monthly Weather Review, 143 (10). pp. 3857-3873. ISSN 0027-0644 doi: https://doi.org/10.1175/MWR-D-14-00375.1

2014

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Weber, R. J. T., Gumeas, V., Doblas-Reyes, F. J., Asif, M. and Volpi, D. (2014) Full-field and anomaly initialization using a low-order climate model: a comparison and proposals for advanced formulations. Nonlinear Processes in Geophysics, 21 (2). pp. 521-537. ISSN 1023-5809 doi: https://doi.org/10.5194/npg-21-521-2014

2013

Palatella, L., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Trevisan, A. (2013) Lyapunov vectors and assimilation in the unstable subspace: theory and applications. Journal of Physics A: Mathematical and Theoretical, 46 (25). 254020. ISSN 1751-8113 doi: https://doi.org/10.1088/1751-8113/46/25/254020

2012

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Hamdi, R., Termonia, P. and Vannitsem, S. (2012) Short time augmented extended Kalman filter for soil analysis: a feasibility study. Atmospheric Science Letters, 13 (4). pp. 268-274. ISSN 1530-261X doi: https://doi.org/10.1002/asl.394

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Vannitsem, S. (2012) Accounting for model error in data assimilation. In: Mathematical and Algorithmic Aspects of Atmosphere-Ocean Data Assimilation from the European Mathematical Society. Oberwolfach Report (58). European Mathematical Society, pp. 3437-3438. doi: https://doi.org/10.4171/OWR/2012/58

2011

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Vannitsem, S. (2011) Treatment of the error due to unresolved scales in sequential data assimilation. International Journal of Bifurcation and Chaos, 21 (12). pp. 3619-3626. ISSN 1793-6551 doi: https://doi.org/10.1142/S0218127411030775

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Vannitsem, S. (2011) State and parameter estimation with the extended Kalman filter: an alternative formulation of the model error dynamics. Quarterly Journal of the Royal Meteorological Society, 137 (655). pp. 435-451. ISSN 1477-870X doi: https://doi.org/10.1002/qj.762

2010

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 and Vannitsem, S. (2010) Accounting for model error in variational data assimilation: a deterministic formulation. Monthly Weather Review, 138 (9). pp. 3369-3386. ISSN 0027-0644 doi: https://doi.org/10.1175/2010MWR3192.1

2009

Porcu, F. and Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 (2009) Toward an estimation of the relationship between cyclonic structures and damages at the ground in Europe. Natural Hazards and Earth System Sciences, 9 (3). pp. 823-829. ISSN 1561-8633 doi: https://doi.org/10.5194/nhess-9-823-2009

Yang, S.-C., Corazza, M., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Kalnay, E. and Miyoshi, T. (2009) Comparison of local ensemble transform Kalman filter, 3DVAR, and 4DVAR in a quasigeostrophic model. Monthly Weather Review, 137 (2). pp. 693-709. ISSN 0027-0644 doi: https://doi.org/10.1175/2008MWR2396.1

2008

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Vannitsem, S. and Nicolis, C. (2008) Model error and sequential data assimilation: a deterministic formulation. Quarterly Journal of the Royal Meteorological Society, 134 (634). pp. 1297-1313. ISSN 1477-870X doi: https://doi.org/10.1002/qj.284

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Trevisan, A., Descamps, L., Talagrand, O. and Uboldi, F. (2008) Controlling instabilities along a 3DVar analysis cycle by assimilating in the unstable subspace: a comparison with the EnKF. Nonlinear Processes in Geophysics, 15 (4). pp. 503-521. ISSN 1023-5809 doi: https://doi.org/10.5194/npg-15-503-2008

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Ghil, M., Trevisan, A. and Uboldi, F. (2008) Data assimilation as a nonlinear dynamical systems problem: stability and convergence of the prediction-assimilation system. Chaos: An Interdisciplinary Journal of Nonlinear Science, 18 (2). 023112. ISSN 1089-7682 doi: https://doi.org/10.1063/1.2909862

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Vannitsem, S., Zupanski, D. and Zupanski, M. (2008) The maximum likelihood ensemble filter performances in chaotic systems. Tellus A: Dynamic Meteorology and Oceanography, 61 (5). pp. 587-600. ISSN 1600-0870 doi: https://doi.org/10.1111/j.1600-0870.2009.00408.x

2007

Porcù, F., Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Medaglia, C. M., Prodi, F. and Mugnai, A. (2007) A study on cut-off low vertical structure and precipitation in the Mediterranean region. Meteorology and Atmospheric Physics, 96. pp. 121-140. ISSN 1436-5065 doi: https://doi.org/10.1007/s00703-006-0224-5

Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600, Trevisan, A. and Uboldi, F. (2007) Adaptive observations and assimilation in the unstable subspace by breeding on the data-assimilation system. Tellus A: Dynamic Meteorology and Oceanography, 59 (1). pp. 101-113. ISSN 1600-0870 doi: https://doi.org/10.1111/j.1600-0870.2006.00210.x

2005

Uboldi, F., Trevisan, A. and Carrassi, A. ORCID: https://orcid.org/0000-0003-0722-5600 (2005) Developing a dynamically based assimilation method for targeted and standard observations. Nonlinear Processes in Geophysics, 12 (1). pp. 149-156. ISSN 1023-5809 doi: https://doi.org/10.5194/npg-12-149-2005