Ensemble surrogate model uncertainty for salinity C2
An educational model for ensemble streamflow simulation and uncertainty analysis
... Figure 5 presents students’ responses on their learn- ing gains using a five-point ranking scale where: 1 = no gains; 2 = a little gain; 3 = moderate gain; 4 = good gain; and 5 = great gain. Figure 5 (top panel) displays ...
8
Addressing model uncertainty in seasonal and annual dynamical ensemble forecasts
... August) ensemble-mean anomaly correlation and of the spread-to-RMSE ratio for near-surface temperature in the re-forecasts started on 1 May with a lead time of one month is shown in Figure ...the ...
22
Efficient Computation and Uncertainty Analysis of Underwater Acoustic Propagation based on Kriging Surrogate Model
... and salinity. The sound velocity profile also shows a strong uncertainty with the dynamic changes of ocean ...movement. Uncertainty of various ocean parameters, such as sound velocity, horizontal ...
9
Uncertainty handling in surrogate assisted optimisation of games
... 4.1.4.1 Feedback Dimension The process of obtaining appropriate feedback for game content can be relatively complex, and there are many caveats to consider, depending on what type of data is acquired. Feedback Survey For ...
176
Low salinity waterflooding for Enhanced Oil Recovery - stochastic model calibration and uncertainty quantification
... a surrogate model, which is built through a universal Kriging ...low salinity KR curves has been obtained through a set of 200 LH realizations and 6 MHA ...estimated model parameters are then ...
15
Uncertainty quantification of squeal instability via surrogate modelling
... 3. Complex eigenvalue analysis (CEA) Early research on brake squeal was mostly dedicated to the root cause of this phenomenon. Several frictional mechanisms have been proposed for the source of squeal, yet there is no ...
38
Uncertainty-Integrated Surrogate Modeling for Complex System Optimization
... Concurrent Surrogate Model Selection ...existing model selection methods, coherently operates at all the three levels necessary to facilitate optimal selection, ...the model type, (2) ...
284
A method to encapsulate model structural uncertainty in ensemble projections of future climate: EPIC v1.0
... The model orography and vegetation data sets were updated from those used by Drost et ...forecast model (Ackerley et ...of model sim- ulation (the spin-up) is excluded from the analysis, as this is ...
13
Structure of the transport uncertainty in mesoscale inversions of CO 2sources and sinks using ensemble model simulations
... 1092 T. Lauvaux et al.: Atmospheric CO 2 modelling: error correlations of simulation. The 16 singular vectors are combined linearly to generate the 10 perturbed simulations. Our approach to generating the ensemble ...
14
Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short range rainfall prediction
... the model performance is highly dependent on the rapid availability of knowledge of rainfall distribution in advance (Ferraris et ...QPF uncertainty on the whole system can be easily appreciated either ...
11
Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction
... hydrological model, like weather models, is subject to the same factors regarding the uncertainty sources in weather modelling ...cal model, although uncertainties in data inputs, ...of ...
28
Optimum design of hydraulic water retaining structures incorporating uncertainty in estimating heterogeneous hydraulic conductivity utilizing stochastic ensemble surrogate models within a multi-objective multi-realisation optimisation model
... (RBOD) model was used to quantify uncertainty in estimates of seepage characteristics due to uncertainty in heterogeneous hydraulic conductivity ...stochastic ensemble surrogate ...RBOD ...
20
Uncertainty quantification of brake squeal Iistability via surrogate modelling
... “One of the most interesting (and frustrating) features of brake noise is its fugitive nature; it is well known that even across different vehicles of the same make and model with the same brake installation, some ...
201
High dimensional output surrogate models for uncertainty and sensitivity analyses
... a model (lowering the computa- tional burden in other tasks of design and analysis), but SA can also involve a prohibitive time cost, which has motivated the use of ...under uncertainty for multi-output ...
181
Robust Surrogate Models for Uncertainty Quantification and Nuclear Engineering Applications
... the model fits to noise in the individual data points rather than the general trend underlying the data as a ...associated uncertainty and it is more difficult to extract information about the modelled ...
168
Accounting for three sources of uncertainty in ensemble hydrological forecasting
... of uncertainty in relevant modeling processes. Among them, the ensemble Kalman fil- ter (EnKF), multimodel approaches and meteorological en- semble forecasting proved to have the capability to improve upon ...
17
Uncertainty analysis of Langat river flow projections using impact-based multi-model ensemble approaches
... downscaling uncertainty is notably smaller than the GCM uncertainty (Chen et ...GCM uncertainty as one source (Liu et ...downscaling uncertainty is recommended in cases where only one GCM is ...
41
Evaluation of different sources of uncertainty in climate change impact research using a hydro-climatic model ensemble
... of uncertainty that simply cannot be ignored without careful ...of uncertainty and the behaviour of specific components of the modelling chain with respect to various uncertainty components is ...of ...
8
Reduction of predictive uncertainty in estimating irrigation water requirement through multi-model ensembles and ensemble averaging
... the model structural versus model parametric uncertainty for irrigation simulations by considering six evapotranspiration models and five crop coefficient sets to estimate irrigation water re- ...
12
Evaluating tropical cyclone forecast track uncertainty using a grand ensemble of ensemble prediction systems
... Ensemble modeling and various stochastic forecasting techniques have rapidly developed into mainstream operational forecasting over the past decade (Bougault et al. 2011). The development of the TIGGE database and ...
64