error covariance
Analysis error covariance versus posterior covariance in variational data assimilation
... The error in the optimal solution (or ‘analysis error’) is naturally defined as a difference between the solution u and the true state u t ; this error is quantified by the analysis error ...
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Impact of a time-dependent background error covariance matrix on air quality analysis
... Data assimilation techniques are frequently used in many fields of application especially in Geosciences, such as weather forecasting and oceanography (Swinbank et al., 2003). They are used to provide an estimate of the ...
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Impact of different estimations of the background-error covariance matrix on climate reconstructions based on data assimilation
... One popular DA method is the Kalman filter (KF; Kalman, 1960). In standard applications, the processes of the KF can be summarized in two main steps (Ide et al., 1997). In the update step, the background state and the ...
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Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation
... forecast error covariance ...forecast error co- variance produced by the WRF-Chem, we anticipate that the ensemble-based coupled atmosphere–chemistry data ...
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ERROR COVARIANCE ESTIMATION IN OBJECT TRACKING SCENARIOS USING KALMAN FILTER
... In order to study in depth the essence of these algorithms developed based on their mathematical and environment of their applications, complex situations like partial and full occlusion are chosen and are successfully ...
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Estimating model error covariance matrix parameters in extended Kalman filtering
... model error covariance matrix is often seen as a tuning pa- rameter in EKF, which is often simply postulated by the ...model error covariance ma- ...the covariance matrix parameters ...
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Background error covariance with balance constraints for aerosol species and applications in variational data assimilation
... Abstract. Balance constraints are important for background error covariance (BEC) in data assimilation to spread infor- mation between different variables and produce balance anal- ysis fields. Using ...
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Generalized background error covariance matrix model (GEN_BE v2.0)
... background error statis- tics is a key component of data assimilation since it affects the impact observations will have on the ...background error covariance matrix (B) are usually too large to be ...
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On the Kalman Filter error covariance collapse into the unstable subspace
... and error covariance ...EKF error covariance matrices asymptotically becomes as small as the dimension of the unstable and neutral manifold of the original system ...
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Construction of non-diagonal background error covariance matrices for global chemical data assimilation
... background error covariance matrix, which contains information about the magnitude of the back- ground errors and about their ...background error covariance matrices which ac- count for the ...
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Evaluation of Analysis by Cross-Validation. Part II: Diagnostic and Optimization of Analysis Error Covariance
... uncorrelated with the background error. Right panel, with correlated errors. the analysis error variance) is minimum. Yet, the principles and theory still hold in that case[r] ...
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Optimal solution error covariance in highly nonlinear problems of variational data assimilation
... one may conclude that δu from Eq. (5) is bound to remain asymptotically normal. In practice the observation window [0,T ] and time step dt are always finite implying the finite number of i.i.d. observations. Moreover, it ...
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A radar reflectivity operator with ice-phase hydrometeors for variational data assimilation (version 1.0) and its evaluation with real radar data
... background error covariance, can be partially resolved by us- ing radar-retrieved hydrometeors in a preprocessing step and tuning the spatial correlation length scales of the background ...
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Merged ozone profiles from four MIPAS processors
... The merged profile is constructed as a weighted mean of the four parent profiles. For each processor, the errors at dif- ferent height levels are correlated because of error propaga- tion patterns typical for limb ...
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Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error
... unfiltered error, outside of the span of the anomalies, is transmitted by the dynamics into the fil- tered ...unfiltered error. The dynamic upwelling of unfiltered error, characterized by the term ...
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On analysis error covariances in variational data assimilation
... analysis error covariance matrix can be used as a basis for computing the background covariances or as a hind-cast solution quality ...analysis error may be related to the errors of the input data ...
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Diagnostics on the cost-function in variational assimilations for meteorological models
... the errors in the innovation vector. In the perfect case, the minimum value of the cost function has a χ p 2 distribution where p is the number of scalar observations assimilated in the system (Bennett et al., 1993; ...
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Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables
... The present paper is motivated by these considerations. Faced with uncer- tainty over the nature of parameter change, we want an econometric method which will discover its nature in a data-based fashion. And faced with ...
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Robust transceiver design for MIMO relay systems with tomlinson harashima precoding
... estimation error covariance, we optimise the processors to minimise the expected arithmetic mean square error (MSE) subject to transmission power constraints at the source and ...
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Development of a hybrid variational-ensemble data assimilation technique for observed lightning tested in a mesoscale model
... The following results correspond to 00:00 UTC, 28 April 2011, cycle 5 in the data assimilation time line, at the time when an EF-4 tornado affected Tuscaloosa and Birmingham, Alabama. Fields of wind, absolute vortic- ity ...
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