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Javier Amezcua
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Implicit equal‐weights particle filter
M Zhu, PJ Van Leeuwen, J Amezcua
Quarterly Journal of the Royal Meteorological Society 142 (698), 1904-1919, 2016
682016
Validation of three new measure-correlate-predict models for the long-term prospection of the wind resource
A Romo Perea, J Amezcua, O Probst
Journal of renewable and sustainable energy 3 (2), 023105, 2011
562011
Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach
J Amezcua, PJ Van Leeuwen
Tellus A: Dynamic Meteorology and Oceanography 66 (1), 23493, 2014
532014
Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data
E Pinnington, J Amezcua, E Cooper, S Dadson, R Ellis, J Peng, ...
Hydrology and Earth System Sciences 25 (3), 1617-1641, 2021
492021
The effects of the RAW filter on the climatology and forecast skill of the SPEEDY model
J Amezcua, E Kalnay, PD Williams
Monthly Weather Review 139 (2), 608-619, 2011
492011
Ensemble transform Kalman–Bucy filters
J Amezcua, K Ide, E Kalnay, S Reich
Quarterly Journal of the Royal Meteorological Society 140 (680), 995-1004, 2014
412014
An international initiative of predicting the SARS-COV-2 pandemic using ensemble data assimilation
G Evensen, J Amezcua, M Bocquet, A Carrassi, A Farchi, A Fowler, ...
Foundations of Data Science, 2020
37*2020
Comparing hybrid data assimilation methods on the Lorenz 1963 model with increasing non-linearity
M Goodliff, J Amezcua, PJ Van Leeuwen
Tellus A: Dynamic Meteorology and Oceanography 67 (1), 26928, 2015
352015
A weak-constraint 4DEnsembleVar. Part I: formulation and simple model experiments
J Amezcua, M Goodliff, PJ Van Leeuwen
Tellus A: Dynamic Meteorology and Oceanography 69 (1), 1271564, 2017
242017
Assimilation of atmospheric infrasound data to constrain tropospheric and stratospheric winds.
A Amezcua, J. , Nasholm, P. , Blixt, M. and Charlton-Perez
Quarterly Journal of the Royal Meteorological Society, 2020
18*2020
A weak-constraint 4DEnsembleVar. Part II: experiments with larger models
M Goodliff, J Amezcua, PJ Van Leeuwen
Tellus A: Dynamic Meteorology and Oceanography 69 (1), 1271565, 2017
142017
A Revised Implicit Equal-Weights Particle Filter
J Skauvold, J Eidsvik, PJ van Leeuwen, J Amezcua
Quarterly Journal of the Royal Meteorological Society, 2019
112019
Assimilating atmospheric infrasound data to constrain atmospheric winds in a two-dimensional grid
J Amezcua, Z Barton
Quarterly Journal of the Royal Meteorological Society, 2021
102021
The composite‐tendency Robert–Asselin–Williams (RAW) filter in semi‐implicit integrations
J Amezcua, PD Williams
Quarterly Journal of the Royal Meteorological Society 141 (688), 764-773, 2015
92015
Ensemble clustering in deterministic ensemble Kalman filters
J Amezcua, K Ide, CH Bishop, E Kalnay
Tellus A: Dynamic Meteorology and Oceanography 64 (1), 18039, 2012
82012
Supervised machine learning to estimate instabilities in chaotic systems: estimation of local Lyapunov exponents
VO Daniel Ayers, Jack Lau, Javier Amezcua, Alberto Carrassi
Quarterly Journal of the Royal Meteorological Society, https://doi.org/10 …, 2023
7*2023
Hybrid ensemble-variational data assimilation in ABC-DA within a tropical framework 2022
JCK Lee, J Amezcua, RN Bannister
Geoscientific Model Development, 2022
6*2022
Time-correlated model error in the (ensemble) Kalman smoother.
PJ Amezcua, J. and Van Leeuwen
Quarterly Journal of the Royal Meteorological Society, ISSN 1477-870X, 2018
5*2018
A novel approach to statistical-dynamical downscaling for long-term wind resource predictions.
O Chavez-Arroyo, R., Fernades-Correia, P., Lozano-Galiana, S., Sanz-Rodrigo ...
Meteorological Applications, 2017
5*2017
Effects of misspecified time-correlated model error in the (ensemble) Kalman Smoother.
PJ Ren, H., Amezcua, J. and Van Leeuwen
Quarterly Journal of the Royal Meteorological Society. 147 (734), Pages 573-588, 2021
32021
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