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[PDF] Top 20 Model error estimation in ensemble data assimilation

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Model error estimation in ensemble data assimilation

Model error estimation in ensemble data assimilation

... stochastic model uncertainties, the EnKF is based on a perfect model ...the model, which may play a major role in environmental forecasting (Orrell et ...systematic model errors on the ... See full document

13

Estimating surface carbon fluxes based on a local ensemble transform Kalman filter with a short assimilation window and a long observation window: an observing system simulation experiment test in GEOS-Chem 10.1

Estimating surface carbon fluxes based on a local ensemble transform Kalman filter with a short assimilation window and a long observation window: an observing system simulation experiment test in GEOS-Chem 10.1

... once every 14 d with very high spatial resolution. This in- cludes 24 samples per second along the satellite track within ∼ 7 km span. The observations are expected to be highly cor- related over a short length scale. ... See full document

16

Regional scale ozone data assimilation using an ensemble Kalman filter and the CHIMERE chemical transport model

Regional scale ozone data assimilation using an ensemble Kalman filter and the CHIMERE chemical transport model

... An ensemble Kalman filter (EnKF) has been cou- pled to the CHIMERE chemical transport model in order to assimilate ozone ground-based measurements on a regional ...for data assimila- tion and for ... See full document

20

Estimation in a linear multivariate measurement error model with a change point in the data

Estimation in a linear multivariate measurement error model with a change point in the data

... the error covariance matrix may differ from row to ...the error matrix are united into two uncor- related blocks, and in each block, the total covariance structure is supposed to be known up to a ... See full document

22

On optimal solution error covariances in variational data assimilation problems

On optimal solution error covariances in variational data assimilation problems

... evolution model, which is a typical DA problem arising in ...parameter estimation problems such as a distributed coef- ficient estimation problem and a boundary value estimation ...solution ... See full document

20

Estimation of slope for measurement error model
with equation error: applications on serum kanamycin data

Estimation of slope for measurement error model with equation error: applications on serum kanamycin data

... The error-in-variables or measurement error is a real problem and it has been considered by a host of authors since the late nineteenth century (Gillard, ...to error. Berkson (1950) noted that the ... See full document

15

Reservoir Multiscale Data Assimilation Using the Ensemble Kalman Filter

Reservoir Multiscale Data Assimilation Using the Ensemble Kalman Filter

... ity data as additional data on a 5 5  coarse ...coarse-scale data was always assimilated along with wa- ter cut data. The data variance was varied from low to high, to study its impact ... See full document

16

Operational hydrological data assimilation with the recursive ensemble Kalman filter

Operational hydrological data assimilation with the recursive ensemble Kalman filter

... perturbs model precipitation, soil moisture and depth to water ...the error parameters controlling perturbations of depth to wa- ter table were the most sensitive in terms of model ensem- ble spread ... See full document

18

Development of a hybrid variational-ensemble data assimilation technique for observed lightning tested in a mesoscale model

Development of a hybrid variational-ensemble data assimilation technique for observed lightning tested in a mesoscale model

... hybrid ensemble- variational data assimilation method developed at Colorado State ...and ensemble data assimilation methods, a cost func- tion is derived using a Gaussian ... See full document

15

Evaluation of the Four-dimensional Ensemble-Variational Hybrid Data Assimilation with Self-consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts

Evaluation of the Four-dimensional Ensemble-Variational Hybrid Data Assimilation with Self-consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts

... (HWRF) model [11] has operationally provided real-time TC forecasts to the National Hurricane Center (NHC) for the Atlantic and eastern North Pacific basins since 2007 and was extended to all oceanic basins over ... See full document

22

Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation

Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation

... the model for seasonal forecasting with an ensemble of histori- cal forcing ...the model- ing framework, and the sampled forcing data is not necessar- ily representative of the future climate, ... See full document

12

Four-dimensional ensemble-variational data assimilation for global deterministic weather prediction

Four-dimensional ensemble-variational data assimilation for global deterministic weather prediction

... the ensemble-variational data assimilation approach (EnVar) for possible replacement of 4D-Var at Environment Canada for global deterministic weather ...4-D ensemble covariances, obtained from ... See full document

14

A non-Gaussian analysis scheme using rank histograms for ensemble data assimilation

A non-Gaussian analysis scheme using rank histograms for ensemble data assimilation

... geophysical data assimilation is to address the issue of non-Gaussianities in the distributions of the physical variables ensuing, in many cases, from non- linear dynamical ...Non-Gaussian ensemble ... See full document

17

Ensemble Kalman filter versus ensemble smoother for assessing hydraulic conductivity via tracer test data assimilation

Ensemble Kalman filter versus ensemble smoother for assessing hydraulic conductivity via tracer test data assimilation

... physical–biogeochemical model of the North Atlantic, while Schoeniger et ...the assimilation of 3-D hydraulic tomography ...piezometric data used for the estimation of hydraulic ... See full document

15

Assimilation of snow covered area into a hydrologic model

Assimilation of snow covered area into a hydrologic model

... forcing data (i.e. input data) have already been presented in Chapter ...create ensemble of model trajecto- ries. This ensemble, representing the model error or ... See full document

58

Correcting the radar rainfall forcing of a hydrological model with data assimilation: application to flood forecasting in the Lez catchment in Southern France

Correcting the radar rainfall forcing of a hydrological model with data assimilation: application to flood forecasting in the Lez catchment in Southern France

... radar data is often limited by in- creased uncertainties compared to ground rainfall measure- ments due to nonlinearities in the rainfall-reflectivity rela- tionship, ground clutter and beam blocking (Borga, ... See full document

18

Mitigation of coupled model biases induced by dynamical core misfitting through parameter optimization: simulation with a simple pycnocline prediction model

Mitigation of coupled model biases induced by dynamical core misfitting through parameter optimization: simulation with a simple pycnocline prediction model

... the assimilation model includes a “biased” time-differencing scheme from the truth model that is used to produce ...of assimilation experiments is per- formed to examine the impact of ... See full document

10

A hybrid variational-ensemble data assimilation scheme with systematic error correction for limited-area ocean models

A hybrid variational-ensemble data assimilation scheme with systematic error correction for limited-area ocean models

... the data assimilation issues charac- terising ocean limited-area models with dense observational networks, a 3DVAR assimilation scheme was implemented and coupled with the NEMO-based ...background ... See full document

17

Role of forcing uncertainty and background model error characterization in snow data assimilation

Role of forcing uncertainty and background model error characterization in snow data assimilation

... forcing ensemble compared to the use of a single forcing ...forcing ensemble is a result of the poor skill of the ...background model error) and in situ data-based correction of ... See full document

11

Estimation of friction parameters in gravity currents by data assimilation in a model hierarchy

Estimation of friction parameters in gravity currents by data assimilation in a model hierarchy

... Stokes model, it is determined by the position above ground of the thermocline that corresponds to half the initial max- imum temperature anomaly in the gravity current at the as- similation points x, every 1 km, ... See full document

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