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Number of items: 25.

Lee, J. C. K., Amezcua, J. and Bannister, R. N. (2024) Variable-dependent and selective multivariate localization for ensemble-variational data assimilation in the tropics. Monthly Weather Review. ISSN 1520-0493 doi: https://doi.org/10.1175/MWR-D-23-0201.1 (In Press)

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

Amezcua, J. ORCID: https://orcid.org/0000-0002-4952-8354, Ren, H. ORCID: https://orcid.org/0000-0003-4342-3305 and Van Leeuwen, P. J. ORCID: https://orcid.org/0000-0003-2325-5340 (2023) Using the (iterative) ensemble Kalman smoother to estimate the time correlation in model error. Tellus A: Dynamic Meteorology and Oceanography, 75 (1). pp. 108-128. ISSN 1600-0870 doi: https://doi.org/10.16993/tellusa.55

Lee, J. C. K., Amezcua, J. and Bannister, R. N. (2022) Hybrid ensemble-variational data assimilation in ABC-DA within a tropical framework. Geoscientific Model Development, 15 (15). pp. 6197-6219. ISSN 1991-9603 doi: https://doi.org/10.5194/gmd-2022-3

Amezcua, J. and Barton, Z. (2021) Assimilating atmospheric infrasound data to constrain atmospheric winds in a two-dimensional grid. Quarterly Journal of the Royal Meteorological Society, 147 (740). pp. 3530-3554. ISSN 1477-870X doi: https://doi.org/10.1002/qj.4141

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

Pinnington, E., Amezcua, J., Cooper, E., Dadson, S., Ellis, R., Peng, J., Robinson, E., Morrison, R., Osborne, S. and Quaife, T. ORCID: https://orcid.org/0000-0001-6896-4613 (2021) Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data. Hydrology and Earth System Sciences, 25 (3). pp. 1617-1641. ISSN 1027-5606 doi: https://doi.org/10.5194/hess-25-1617-2021

Ren, H., Amezcua, J. and Van Leeuwen, P. J. (2021) Effects of misspecified time-correlated model error in the (ensemble) Kalman Smoother. Quarterly Journal of the Royal Meteorological Society, 147 (734). pp. 573-588. ISSN 1477-870X doi: https://doi.org/10.1002/qj.3934

Amezcua, J., Nasholm, P., Blixt, M. and Charlton-Perez, A. (2020) Assimilation of atmospheric infrasound data to constrain tropospheric and stratospheric winds. Quarterly Journal of the Royal Meteorological Society, 146 (731). pp. 2634-2653. ISSN 1477-870X doi: https://doi.org/10.1002/qj.3809

Skauvold, J., Eidsvik, J., Van Leeuwen, P. J. and Amezcua, J. (2019) A revised implicit equal-weights particle filter. Quarterly Journal of the Royal Meteorological Society, 145 (721). ISSN 1477-870X doi: https://doi.org/10.1002/qj.3506

Amezcua, J. and Van Leeuwen, P. J. (2018) Time-correlated model error in the (ensemble) Kalman smoother. Quarterly Journal of the Royal Meteorological Society, 144 (717). pp. 2650-2665. ISSN 1477-870X doi: https://doi.org/10.1002/qj.3378

Chavez-Arroyo, R., Fernades-Correia, P., Lozano-Galiana, S., Sanz-Rodrigo, J., Amezcua, J. and Probst, O. (2018) A novel approach to statistical-dynamical downscaling for long-term wind resource predictions. Meteorological Applications, 25 (2). pp. 171-183. ISSN 1469-8080 doi: https://doi.org/10.1002/met.1678

Goodliff, M., Amezcua, J. and Van Leeuwen, P. J. (2017) A weak-constraint 4DEnsembleVar. Part II: experiments with larger models. Tellus A, 69 (1). 1271565. ISSN 1600-0870 doi: https://doi.org/10.1080/16000870.2016.1271565

Amezcua, J., Goodliff, M. and Van Leeuwen, P. J. (2017) A weak-constraint 4DEnsembleVar. Part I: formulation and simple model experiments. Tellus A, 69 (1). 1271564. ISSN 1600-0870 doi: https://doi.org/10.1080/16000870.2016.1271564

Zhu, M., Van Leeuwen, P. J. and Amezcua, J. (2016) Implicit equal-weights particle filter. Quarterly Journal of the Royal Meteorological Society. ISSN 0035-9009 doi: https://doi.org/10.1002/qj.2784

Amezcua, J. and Williams, P. D. ORCID: https://orcid.org/0000-0002-9713-9820 (2015) The composite-tendency Robert–Asselin–Williams (RAW) filter in semi-implicit integrations. Quarterly Journal of the Royal Meteorological Society, 141 (688). pp. 764-773. ISSN 1477-870X doi: https://doi.org/10.1002/qj.2391

Goodliff, M., Amezcua, J. and Van Leeuwen, P. (2015) Comparing hybrid data assimilation methods on the Lorenz 1963 model with increasing nonlinearity. Tellus A, 67. ISSN 1600-0870 doi: https://doi.org/10.3402/tellusa.v67.26928

Amezcua, J. and Van Leeuwen, P. (2014) Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach. Tellus A, 66. 23493. ISSN 1600-0870 doi: https://doi.org/10.3402/tellusa.v66.23493

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

Amezcua, J., Ide, K., Bishop, C. H. and Kalnay, E. (2012) Ensemble clustering in deterministic ensemble Kalman filters. Tellus A, 64. 18039. ISSN 1600-0870 doi: https://doi.org/10.3402/tellusa.v64i0.18039

Amezcua, J. (2012) Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model. PhD thesis, University of Maryland.

Amezcua, J., Munoz, R. and Probst, O. (2011) Reconstruction of gusty wind speed time series from autonomous data logger records. Wind & Structures, 14 (4). pp. 337-357. ISSN 1226-6116

Romo, A., Amezcua, J. and Probst, O. (2011) Validation of three new measure-correlate-predict models for the long-term prospection of the wind resource. Journal of Renewable and Sustainable Energy, 3 (2). 023105. ISSN 1941-7012 doi: https://doi.org/10.1063/1.3574447

Amezcua, J., Kalnay, E. and Williams, P. D. ORCID: https://orcid.org/0000-0002-9713-9820 (2011) The effects of the RAW filter on the climatology and forecast skill of the SPEEDY model. Monthly Weather Review, 139 (2). pp. 608-619. ISSN 0027-0644 doi: https://doi.org/10.1175/2010MWR3530.1

Gallo, A., Gosch, R., Amezcua, J., Reyes, E. and Probst, O. (2009) Statistical evaluation of the early-stage development of Jatropha energy plantations in Northeastern Mexico. Intenational Journal of Global Warming, 1 (4). pp. 473-492. ISSN 1758-2091 doi: https://doi.org/10.1504/IJGW.2009.029218

This list was generated on Fri Mar 29 00:08:56 2024 UTC.

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