[HTML][HTML] Lagrangian data assimilation of surface drifters in a double-gyre ocean model using the local ensemble transform Kalman filter
The assimilation of position data from Lagrangian observing platforms is underdeveloped in
operational applications because of two main challenges: 1) nonlinear growth of model and …
operational applications because of two main challenges: 1) nonlinear growth of model and …
Lagrangian Data Assimilation of Surface Drifters in a Double-Gyre Ocean Model Using the Local Ensemble Transform Kalman Filter
L Sun, SG Penny - 2019 - repository.library.noaa.gov
The assimilation of position data from Lagrangian observing platforms is underdeveloped in
operational applications because of two main challenges: 1) nonlinear growth of model and …
operational applications because of two main challenges: 1) nonlinear growth of model and …
Lagrangian Data Assimilation of Surface Drifters in a Double-Gyre Ocean Model Using the Local Ensemble Transform Kalman Filter.
L SUN, SG PENNY - Monthly Weather Review, 2019 - search.ebscohost.com
The assimilation of position data from Lagrangian observing platforms is underdeveloped in
operational applications because of two main challenges: 1) nonlinear growth of model and …
operational applications because of two main challenges: 1) nonlinear growth of model and …
[PDF][PDF] Lagrangian Data Assimilation of Surface Drifters in a Double-Gyre Ocean Model Using the Local Ensemble Transform Kalman Filter
L SUN, SG PENNY - 2019 - researchgate.net
The assimilation of position data from Lagrangian observing platforms is underdeveloped in
operational applications because of two main challenges: 1) nonlinear growth of model and …
operational applications because of two main challenges: 1) nonlinear growth of model and …
[HTML][HTML] Lagrangian Data Assimilation of Surface Drifters in a Double-Gyre Ocean Model Using the Local Ensemble Transform Kalman Filter
L Sun, SG Penny - Monthly Weather Review, 2019 - journals.ametsoc.org
Lagrangian Data Assimilation of Surface Drifters in a Double-Gyre Ocean Model Using the
Local Ensemble Transform Kalman Filter in: Monthly Weather Review Volume 147 Issue 12 …
Local Ensemble Transform Kalman Filter in: Monthly Weather Review Volume 147 Issue 12 …
Lagrangian Data Assimilation of Surface Drifters in a Double-Gyre Ocean Model Using the Local Ensemble Transform Kalman Filter
L Sun, SG Penny - Monthly Weather Review, 2019 - ui.adsabs.harvard.edu
The assimilation of position data from Lagrangian observing platforms is underdeveloped in
operational applications because of two main challenges: 1) nonlinear growth of model and …
operational applications because of two main challenges: 1) nonlinear growth of model and …
[PDF][PDF] Lagrangian Data Assimilation of Surface Drifters in a Double-Gyre Ocean Model Using the Local Ensemble Transform Kalman Filter
L SUN, SG PENNY - 2019 - scholar.archive.org
The assimilation of position data from Lagrangian observing platforms is underdeveloped in
operational applications because of two main challenges: 1) nonlinear growth of model and …
operational applications because of two main challenges: 1) nonlinear growth of model and …
Lagrangian Data Assimilation of Surface Drifters in a Double-Gyre Ocean Model Using the Local Ensemble Transform Kalman Filter
L Sun, SG Penny - Monthly Weather Review, 2019 - search.proquest.com
The assimilation of position data from Lagrangian observing platforms is underdeveloped in
operational applications because of two main challenges: 1) nonlinear growth of model and …
operational applications because of two main challenges: 1) nonlinear growth of model and …