Back to Existing Special Sessions >>
Ensemble Forecasting in Environmental Modeling
Conveners: Jasper A. Vrugt, Los Alamos National Laboratory and Souheil Ezzedine, Lawrence Livermore National Laboratory
In the last few decades, much progress has been made in the use of dynamic simulation models for the analysis and understanding of environmental systems. In many fields of study, however, predictions with these models have historically focused on a single forecast, without an explicit estimate of the associated uncertainty. This broad session is open to contributions concerning methods, strategies, and applications of ensemble forecasting in environmental modeling. Particular interests lie in methods and applications of state-space filtering techniques for merging measurements with model predictions, and methods characterizing simulation uncertainty through multimodel ensembles. Examples of these include (but are not limited to) Kalman and Particle Filtering strategies, Bayesian Model Averaging and non-parametric approaches. We welcome contributions from different disciplinary fields, including water resources modeling, surface and subsurface hydrology, petroleum engineering, and climate change.
