[PDF] Top 20 Improved variational methods in statistical data assimilation
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Improved variational methods in statistical data assimilation
... the data we presented came ei- ther from a completely different model system or from enor- mously noisy data, we presented data from a collection of 1963 Lorenz model (Lorenz, 1963) oscillators to a ... See full document
9
Variational methods for geometric statistical inference
... For a finite number of observations we allow a soft classification however the scaling is chosen such that in the data rich limit classifiers are binary valued. The motivation for our approach is to validate ... See full document
150
Variational data assimilation with the YAO platform for hydrological forecasting
... Variational assimilation (4D-VAR) (Le Dimet et ...variables), assimilation seeks to infer the physical variables that led to the observation ...gradient methods, which implies the use of the ... See full document
6
Quasi-static ensemble variational data assimilation: a theoretical and numerical study with the iterative ensemble Kalman smoother
... Goodliff et al. (2015) have applied QSVA numerically to a collection of hybrid and EnVar techniques on the Lorenz 1963 model (Lorenz, 1963), where they vary the magnitude of nonlinearity. Nonetheless the focus of their ... See full document
20
Variational Data Assimilation in the Mathematical Model of the Black Sea Dynamics
... control methods [1, 10, 11] and four-dimensional variational assimilation of observational data [8, ...four-dimensional variational assimilation (4D-Var) and the use of more ... See full document
13
Evaluation of the Four-dimensional Ensemble-Variational Hybrid Data Assimilation with Self-consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts
... GSI-4DEnVar data assimilation systems can lead to noticeable improvements in the vortex initializations and forecasts of hurricanes using ...the data assimilation results also need to be ... See full document
22
On optimal solution error covariances in variational data assimilation problems
... The methods of data assimilation (DA) have become an important tool for analysis of complex physical phenomena in various fields of science and ...These methods allow us to combine ... See full document
20
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 ... See full document
16
Four-dimensional ensemble-variational data assimilation for global deterministic weather prediction
... In conclusion, the results from this study suggest that the EnVar approach is a viable alternative to 4D-Var, especially when the simplicity and computational efficiency of EnVar are considered. It should be emphasized ... See full document
14
Optimal solution error covariance in highly nonlinear problems of variational data assimilation
... few methods feasible for solv- ing these non-stationary large-scale problems, the variational data assimilation (DA) method, called “4D-Var”, is the pre- ferred method implemented at some ... See full document
8
Variational data assimilation for a forced, inertia-free magnetohydrodynamic dynamo model
... instrumental in demonstrating the feasibility of this picture of dynamo action in the core. The computer codes that simulate this dynamical system have now reached a level of maturity such that, additionally, various ... See full document
28
Variational assimilation of altimeter data into a non-linear ocean model: temporal strategies
... of variational assimilation in a mid- latitudes ocean model is addressed for the case of altimetric ...altimeter data to control deep ...altimeter data into ocean models is indeed for a large ... See full document
37
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 ... See full document
38
On analysis error covariances in variational data assimilation
... small n the ensemble variance deviates from the H -variance more strongly. In Fig.7.2 we show the H-covariance (upper/left), and the ensemble covariance for n = 100 (upper/right), n = 400 (lower/left) and n = 1600 ... See full document
28
A variational formulation for translation and assimilation of coherent structures
... Most data assimilation algorithms rely on the best linear unbiased estimation (BLUE, Tala- grand, 1997), which is a statistical estimator that requires the prior knowledge of the bias and variance of ... See full document
9
A pre-operational three Dimensional variational data assimilation system in the North/Baltic Sea
... be improved in several ...suitable data assimilation technique so that the real ocean observations can be utilized to improve the forecasting skill of the ... See full document
11
Optimal transport for variational data assimilation
... Understanding and forecasting the evolution of a given sys- tem is a crucial topic in an ever-increasing number of appli- cation domains. To achieve this goal, one can rely on multi- ple sources of information, namely ... See full document
12
A framework for variational data assimilation with superparameterization
... only statistical in- formation about the small scales, and this information can be used as a prior in the data assimilation ...new data assimilation framework, and existing toy models ... See full document
11
A multilevel approach for computing the limited-memory Hessian and its inverse in variational data assimilation
... material. Methods of data assimilation (DA) have become an important tool for analysis of complex physical phenomena in various fields of science and ...These methods allow us to combine ... See full document
30
The impact of aerosol optical depth assimilation on aerosol forecasts and radiative effects during a wild fire event over the United States
... Gridpoint Statistical Inter- polation (GSI) three-dimensional variational (3DVAR) DA system coupled to the Goddard Chemistry Aerosol Radi- ation and Transport (GOCART) (Chin et ...demonstrated ... See full document
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