[PDF] Top 20 Representing model error in ensemble data assimilation
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Representing model error in ensemble data assimilation
... squared error for single forecasts, and give a measure of the average distance between the forecast and observed distribu- tions; the corresponding skill score, the CRPSSs have been computed using a climatological ... See full document
15
Application of ensemble transform data assimilation methods for parameter estimation in reservoir modeling
... years data assimilation methods have been developed to obtain estimations of uncertain model parameters by taking into account a few observations of a model ...tial ensemble methods ... See full document
16
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
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
On optimal solution error covariances in variational data assimilation problems
... background error correlation radius controlled by c ð x Þ ...the ensemble ^ f (presented in the marked ...the ensemble method are pre- sented in ... See full document
20
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
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
... square error (RMSE) for the JJA ...the model resolution in both the horizontal and vertical ...higher model layers which are less affected by dry deposition and NO ... See full document
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EnKF and 4D-Var data assimilation with chemical transport model BASCOE (version 05.06)
... Aura-MLS data into the BASCOE CTM with a full descrip- tion of stratospheric ...chemistry model with EnKF are taken into ...of error variance parameters that need to be ...servation error ... See full document
16
A non-Gaussian analysis scheme using rank histograms for ensemble data assimilation
... for ensemble data assimi- lation, in the spirit of the method of Reich ...how ensemble analysis schemes perform with such ...63 model, and compared in different setups (corre- sponding to ... See full document
17
Four-dimensional ensemble variational (4D-En-Var) data assimilation for the HIgh Resolution Limited Area Model (HIRLAM)
... localized ensemble weights for each observation time window, corresponding to a strong constraint 4D-Var, and also for each model level, correspond- ing to application of horizontal localization ...ground ... See full document
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Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation
... forecast error covari- ance in data assimilation is to conduct a single observa- tion experiment (Thepaut et ...forecast error covariance before real observations are available and even before ... See full document
6
Analysis error covariance versus posterior covariance in variational data assimilation
... evolution model. In section 4 the equation for analysis error is given through the errors in the input data using the Hessian of the auxiliary DA problem, and the basic relationship between analysis ... See full document
16
Volcanic ash forecast using ensemble-based data assimilation: an ensemble transform Kalman filter coupled with the FALL3D-7.2 model (ETKF–FALL3D version 1.0)
... atmospheric model driving dispersal simulations ...in model parameterizations of the physical pro- cesses occurring both in the eruptive column and during subsequent passive transport ... See full document
22
Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation
... SNOW-17 model is used operationally within the NWS- RFS and is the snow model used in operational ESP fore- ...index model that estimates simplified vertical snow processes (Anderson, ...the ... See full document
12
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
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
Quantifying the model structural error in carbon cycle data assimilation systems
... the error of process-based terrestrial models, in particular, for global ...carbon-cycle model before any obser- vational constraint, we propose to analyse the statistics of the prior residuals ... See full document
11
Using ensemble data assimilation to forecast hydrological flumes
... the model and the measure- ments into account simultaneously in a process of continuous data ...our data as- similation algorithm, we have chosen a recent version of the Ensemble Kalman ... See full document
10
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 ... See full document
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