[PDF] Top 20 Using ensemble data assimilation to forecast hydrological flumes
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Using ensemble data assimilation to forecast hydrological flumes
... Pure 2-D simulations of hydrological flows suffer from several handicaps. Because the numerical flow is two- dimensional, it cannot capture the true three-dimensional flow, in particular turbulence: the numerical ... See full document
10
A study on WRF radar data assimilation for hydrological rainfall prediction
... 1987). Assimilation of suitable real-time observations into the NWP models can help significantly reduce the spin-up effect and improve the initial and lateral boundary conditions of the mesoscale model (Sokol and ... See full document
16
Data assimilation in integrated hydrological modelling in the presence of observation bias
... this true model. The same model, but with perturbed param- eter values, denoted the base model, forms the basis of the ensemble that is used for data assimilation. Note that both the true model and ... See full document
16
Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation
... forcing data and model parameters for each basin elevation band were provided by the Colorado River Basin River Forecast Center ...the data assimilation portion of this study, the precipita- ... See full document
12
Multivariate hydrological data assimilation of soil moisture and groundwater head
... The ensemble is generated by adding an appropriate model error to the deterministic ...The ensemble runs freely from 1 December 1969 to 1 January 1973 as a warm-up ...each ensemble member starts with ... See full document
17
Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation
... and Forecast- ing (WRF) model coupled with Chemistry (WRF-Chem) ver- sion ...meteorology using the governing equations with mass and scalar conserving flux form and the terrain- following mass vertical ... See full document
6
Model error estimation in ensemble data assimilation
... However, apart from stochastic model uncertainties, the EnKF is based on a perfect model assumptions. It is thus not able to deal with deficiencies in the model, which may play a major role in environmental forecasting ... See full document
13
Representing model error in ensemble data assimilation
... the ensemble (see Raynaud et ...4D-Var assimilation sys- tem (Raynaud et ...the ensemble has been completed) by us- ing a posteriori diagnostics (Desroziers and Ivanov, ...of forecast ... See full document
15
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, ...to ... See full document
18
Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate
... Multimodel Ensemble system for seasonal to inTERannual prediction; Palmer et ...for hydrological fore- casting on a watershed in Ohio during ...to hydrological ensemble forecasts based on NCEP ... See full document
16
Probabilistic forecasting of wind power production losses in cold climates: a case study
... the ensemble prediction system HarmonEPS is ...an ensemble in HarmonEPS since ...the forecast period. The HarmonEPS ensemble consists of 10 perturbed members and 1 control ...of ... See full document
14
Role of forcing uncertainty and background model error characterization in snow data assimilation
... (1) using the forcing climatology in combination with the input forcing to spec- ify the ensemble (EXP-FCLIM) and (2) using an ensemble of forcing datasets to drive the ensemble ...20 ... See full document
11
Variational data assimilation with the YAO platform for hydrological forecasting
... the forecast lead time (p = 2 days), augmenting the assimilation window to n = 3 days, we note an important decline of the prediction accuracy (Table ...variational assimilation results in a lower ... See full document
6
Optimal adjustment of the atmospheric forcing parameters of ocean models using sea surface temperature data assimilation
... sequential data assimilation methodology to estimate monthly corrections of ERAi forcing parameters using real-SST ...monthly data assimilation experiments have been performed over the ... See full document
17
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)
... Epistemic uncertainties in ash dispersal forecasts may have different origins, including the following: (i) uncertain- ties in the source term (i.e., eruption column height, mass eruption rate, particle grain size ... See full document
22
Observation operators for assimilation of satellite observations in fluvial inundation forecasting
... rapidly. Data assimilation allows us to combine valuable SAR-derived observed information with continuous predictions from a computational hydrodynamic model and thus to produce a better forecast ... See full document
19
Data assimilation in integrated hydrological modeling using ensemble Kalman filtering: evaluating the effect of ensemble size and localization on filter performance
... required ensemble size signif- ...obtained using the common distance-based methods, and direct comparison of the adap- tive localization and distance-based localization also showed that adaptive ... See full document
15
Analysis of the effects of biases in ensemble streamflow prediction (ESP) forecasts on electricity production in hydropower reservoir management
... in ensemble mean (bias) and spread (dispersion and variability) when compared to the actual outcomes as measured over a long time pe- riod (Wood and Schaake, ...The hydrological commu- nity has found clever ... See full document
16
Systematic evaluation of the impacts of GPSRO data on the prediction of typhoons over the northwestern Pacific in 2008–2010
... refractivity data from CHAMP and SAC- C to investigate its impact on the forecast of Typhoon Nari (2001) and Nakri ...the assimilation of GPSRO improves the track and intensity forecast of Ty- ... See full document
12
Concept of dealing with uncertainty in radar-based data for hydrological purpose
... tional Weather Service Forecast Office in Tulsa, Oklahoma (Amburn, Frederick, 2006). That is derived from two quan- tities: deterministic QPF, that is treated as mean precipita- tion amount, and Probability of ... See full document
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