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Asymptotic Forecast Uncertainty and the Unstable Subspace in the Presence of Additive Model Error
Submitted by webadmin on 18. October 2018 - 21:04
250711
Grudzien, C.
,
Carrassi, A.
&
Bocquet, M.
Asymptotic Forecast Uncertainty and the Unstable Subspace in the Presence of Additive Model Error
.
SIAM/ASA Journal on Uncertainty Quantification (JUQ)
6
, (2018).
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Stochastic parameterization identification using ensemble Kalman filtering combined with maximum likelihood methods
Submitted by webadmin on 27. September 2018 - 14:11
250711
Pulido, M.
,
Tandeo, P.
,
Bocquet, M.
,
Carrassi, A.
&
Lucini, M.
Stochastic parameterization identification using ensemble Kalman filtering combined with maximum likelihood methods
.
Tellus. Series A, Dynamic meteorology and oceanography
70
, (2018).
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Impact of rheology on probabilistic forecasts of sea ice trajectories: Application for search and rescue operations in the Arctic
Submitted by webadmin on 27. September 2018 - 12:42
250711
Rabatel, M.
,
Rampal, P.
,
Carrassi, A.
,
Bertino, L.
&
Jones, C.K.R.T.
Impact of rheology on probabilistic forecasts of sea ice trajectories: Application for search and rescue operations in the Arctic
.
The Cryosphere
12
, (2018).
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Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error
Submitted by webadmin on 26. September 2018 - 16:10
250711
Grudzien, C.
,
Carrassi, A.
&
Bocquet, M.
Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error
.
Nonlinear processes in geophysics
25
, (2018).
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Data assimilation in the geosciences - An overview of methods, issues and perspectives
Submitted by Alberto Carrassi on 19. June 2018 - 13:15
250711
Data Assimilation
Mohn-Sverdrup Center for Global Ocean Studies and Operational Oceanography
Data Assimilation
Carrassi, A.
,
Bocquet, M.
,
Bertino, L.
&
Evensen, G.
Data assimilation in the geosciences - An overview of methods, issues and perspectives
.
WIREs Climate Change
(2018).doi:doi: 10.1002/wcc.535
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Stochastic parametrization identification using ensemble Kalman filtering combined with expectation-minimization and Newton-Raphson maximum likelihood methods
Submitted by Alberto Carrassi on 14. February 2018 - 17:41
250711
Data Assimilation
Mohn-Sverdrup Center for Global Ocean Studies and Operational Oceanography
Data Assimilation
Stochastic parametrization identification using ensemble Kalman filtering combined with expectation-minimization and Newton-Raphson maximum likelihood methods
.
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Scientific challenges of convective-scale numerical weather prediction
Submitted by webadmin on 24. January 2018 - 15:29
250711
Yano, J.-I.
, et al.
Scientific challenges of convective-scale numerical weather prediction
.
Bulletin of The American Meteorological Society - (BAMS)
(2018).doi:10.1175/BAMS-D-17-0125.1
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Rank Deficiency of Kalman Error Covariance Matrices in Linear Time-Varying System With Deterministic Evolution
Submitted by webadmin on 4. April 2017 - 17:10
250711
Gurumoorthry, K.
,
Grudzien, C.
,
Apte, A.
,
Carrassi, A.
&
Jones, C.K.R.T.
Rank Deficiency of Kalman Error Covariance Matrices in Linear Time-Varying System With Deterministic Evolution
.
SIAM Journal of Control and Optimization
55
, (2017).
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Degenerate Kalman filter error covariances and their convergence onto the unstable subspace
Submitted by webadmin on 4. April 2017 - 17:07
250711
Bocquet, M.
, et al.
Degenerate Kalman filter error covariances and their convergence onto the unstable subspace
.
SIAM/ASA Journal on Uncertainty Quantification (JUQ)
5
, (2017).
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Four-dimensional ensemble variational data assimilation and the unstable subspace
Submitted by webadmin on 4. April 2017 - 15:41
250711
Bocquet, M.
&
Carrassi, A.
Four-dimensional ensemble variational data assimilation and the unstable subspace
.
Tellus. Series A, Dynamic meteorology and oceanography
69
, (2017).
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