Quantifying the model structural error in carbon cycle data assimilation systems
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
Quantifying the model structural error in carbon cycle data assimilation systems ; volume:6 ; number:1 ; year:2013 ; pages:45-55
Geoscientific model development ; 6, Heft 1 (2013), 45-55
- Urheber
-
Kuppel, S.
Chevallier, F.
Peylin, P.
- DOI
-
10.5194/gmd-6-45-2013
- URN
-
urn:nbn:de:101:1-201711063786
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:29 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Kuppel, S.
- Chevallier, F.
- Peylin, P.
Ähnliche Objekte (12)
Representing model error in ensemble data assimilation
Model error estimation in ensemble data assimilation
Quantifying mangrove carbon assimilation rates using UAV imagery
Quantifying geocode location error using GIS methods
On deterministic error analysis in variational data assimilation
Consistent assimilation of multiple data streams in a carbon cycle data assimilation system
Quantifying the impact of structural reforms
Quantifying the Structural Stability of Simplicial Homology
Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation
Quantifying the constraint of biospheric process parameters by CO 2 concentration and flux measurement networks through a carbon cycle data assimilation system
Optimal solution error covariance in highly nonlinear problems of variational data assimilation
Quantifying location error to define uncertainty in volcanic mass flow hazard simulations
Representing model error in ensemble data assimilation
Model error estimation in ensemble data assimilation
Quantifying mangrove carbon assimilation rates using UAV imagery
Quantifying geocode location error using GIS methods
On deterministic error analysis in variational data assimilation
Consistent assimilation of multiple data streams in a carbon cycle data assimilation system
Quantifying the impact of structural reforms
Quantifying the Structural Stability of Simplicial Homology
Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation
Quantifying the constraint of biospheric process parameters by CO 2 concentration and flux measurement networks through a carbon cycle data assimilation system
Optimal solution error covariance in highly nonlinear problems of variational data assimilation
Quantifying location error to define uncertainty in volcanic mass flow hazard simulations
Representing model error in ensemble data assimilation
Model error estimation in ensemble data assimilation
Quantifying mangrove carbon assimilation rates using UAV imagery
Quantifying geocode location error using GIS methods
On deterministic error analysis in variational data assimilation
Consistent assimilation of multiple data streams in a carbon cycle data assimilation system
Quantifying the impact of structural reforms
Quantifying the Structural Stability of Simplicial Homology
Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation
Quantifying the constraint of biospheric process parameters by CO 2 concentration and flux measurement networks through a carbon cycle data assimilation system
Optimal solution error covariance in highly nonlinear problems of variational data assimilation