Data Assimilation In Meteorology and Oceanography With Variational and Sequential Methods
Hybridizing Bayesian and variational data assimilation for high resolution hydrologic forecasting
... Bayesian data assimilation and variational data ...Bayesian data assimilation creates probabilistic estimates of the state vari- ables in an attempt to also capture their ...
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Variational Data Assimilation in the Mathematical Model of the Black Sea Dynamics
... years, data assimilation methods have been widely used in Earth sciences, providing the relationship between the two main components that permit monitoring of the environment ...Such methods ...
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Optimal solution error covariance in highly nonlinear problems of variational data assimilation
... in meteorology and oceanography. Among the few methods feasible for solv- ing these non-stationary large-scale problems, the variational data assimilation (DA) method, called ...
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A variational formulation for translation and assimilation of coherent structures
... (meteorology, oceanography, hydrology, ...Most data assimilation algorithms rely on the best linear unbiased estimation (BLUE, Tala- grand, 1997), which is a statistical estimator that ...
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Variational data assimilation with the YAO platform for hydrological forecasting
... prediction. Data assimilation was found to be one of the main tools to achieve this task (Seo et ...(variational data assimilation) is used in geophysics, applied to physically-based ...
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Variational data assimilation for a forced, inertia-free magnetohydrodynamic dynamo model
... Variational data assimilation (4DVar) is a powerful technique for tuning dynamical models to observa- tions, in order not only to forecast future time evolution of the system, but to make inferences ...
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A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes: L95-GRS (v1.0)
... testing data assimilation schemes with an on- line ...istry meteorology model (CCMM), the L95-GRS (generic reaction set) model, mimics continental and transcontinental transport and the ...
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Analysis error covariance versus posterior covariance in variational data assimilation
... the variational approach in the framework of sequential methods (filtering) (see, for example, Dobricic, 2009, ...next assimilation window if the Bayesian approach is to be consistently ...
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Data Assimilation Methods for Neuronal State and Parameter Estimation
... of data assimilation algorithms to estimate unobserved variables and unknown parameters of conductance-based neuronal mod- ...Modern data assimilation (DA) techniques are widely used in ...
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Background error covariance with balance constraints for aerosol species and applications in variational data assimilation
... tional data assimilation system, a few methods have been de- veloped to estimate and simplify the expression of the BEC, such as the analysis of innovations, the NMC (National Me- teorological ...
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A Kalman filter application to a spectral wave model
... dependent methods two main classes can be considered: sequential data assimilation meth- ods and variational ...tional methods have the benefit of avoiding the problem of ...
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Southern North Sea storm surge event of 5 December 2013: water levels, waves and coastal impacts
... In the immediate (day + 1) aftermath of the surge, and for two weeks thereafter, high resolution measurements of maximum water level elevations — from the highest, landward margins of unequivocal debris lines; soft rock ...
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Four-dimensional ensemble-variational data assimilation for global deterministic weather prediction
... the data as- similation experiment, the minimization is performed both with (dashed line) and without (solid line) the estimate from the previous analysis used to initialize the ...
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Intra-seasonal climate predictions - linking weather and climate forecasts
... PC1-15. Coastal sea level response associated with frontal systems using conventional and NCEP/NCAR Reanalysis data, in Paranaguá Bay, Paraná State, Brazil. Oliveira, Marilia Mitidieri Fernandes de; Ebecken, ...
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Improved variational methods in statistical data assimilation
... the data. In particular, we generated the data with f = ...the variational method to include all parameters as state variables with a zero vector field, allowing the estimation of the parameters ...
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An Operator Smoothing with ILU(0) for Aggregation based Algebraic Multigrid
... Abstract. Due to the potential optimal convergence, algebraic multigrid is widely used in solving large sparse linear systems. The aggregation-based version is one of the widely used methods for its cheap cost and ...
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Sensitivity analysis with respect to observations in variational data assimilation for parameter estimation
... in variational data assimilation aimed at restoration of unknown parameters of a dynamic ...ational data assimilation is not limited to operational fore- ...
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Using adjoint sensitivity as a local structure function in variational data assimilation
... The results are shown in Fig. 7. First, it is important to notice that it is difficult for the standard 3D-Var assimila- tion procedure to improve the score of the background. As an average, the score of the forecasts ...
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Variational assimilation of altimeter data into a non-linear ocean model: temporal strategies
... Geosat data between 1985 and 1989, and since August 1992, of Topex/Poseidon data, that the oceanographic community began intensive exploitation of these new obser- vational ...
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Improvement of operational flood forecasting through the assimilation of satellite observations and multiple river flow data
... of data assimilation in hydrology has been demonstrated by several studies ...of data assimilation in distributed hydrologic models for operational flood forecasts is limited by many issues: ...
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