Approximating Posterior Distributions in Ensemble Forecasting
نویسندگان
چکیده
Ensemble forecasting is used in numerical weather prediction to give an improved estimate of the atmospheric state and to improve measures of forecast accuracy. While the method is effective, there are some fundamental issues in interpreting the ensemble as a statistically valid representation of uncertainty in the state of the atmosphere. Coupled with this interpretation is the difficulty in the specification of large, complex covariance matrices used to combine a numerical forecast with observed data. We approach this problem by representing the prior distribution as a mixture of Gaussian distributions, then generate an ensemble from the posterior and use this ensemble to construct a kernel approximation to the posterior distribution.
منابع مشابه
Ensemble Learning in Bayesian Neural Networks
Bayesian treatments of learning in neural networks are typically based either on a local Gaussian approximation to a mode of the posterior weight distribution, or on Markov chain Monte Carlo simulations. A third approach, called ensemble learning, was introduced by Hinton and van Camp (1993). It aims to approximate the posterior distribution by minimizing the Kullback-Leibler divergence between...
متن کاملEnsemble Learning for Multi-Layer Networks
Bayesian treatments of learning in neural networks are typically based either on local Gaussian approximations to a mode of the posterior weight distribution, or on Markov chain Monte Carlo simulations. A third approach, called ensemble learning, was introduced by Hinton and van Camp (1993). It aims to approximate the posterior distribution by minimizing the Kullback-Leibler divergence between ...
متن کاملAn Introduction to Bayesian Inference Via Variational Approximations: Supplemental Notes
1.1 The Tractability-Fit Tradeoff in Variational Approximations The goal of a variational approximation is to approximate a posterior, p(β|Y ) by making an approximating distribution, q(β), as close as possible to the true posterior (Bishop, 2006). We search over the space of approximating distributions in order to find the particular distribution with the minimum KL-divergence with the actual ...
متن کاملApproximating the Distributions of Singular Quadratic Expressions and their Ratios
Noncentral indefinite quadratic expressions in possibly non- singular normal vectors are represented in terms of the difference of two positive definite quadratic forms and an independently distributed linear combination of standard normal random variables. This result also ap- plies to quadratic forms in singular normal vectors for which no general representation is currently available. The ...
متن کاملUncertainty assessment via Bayesian revision of ensemble streamflow predictions in the operational river Rhine forecasting system
[1] Ensemble streamflow forecasts obtained by using hydrological models with ensemble weather products are becoming more frequent in operational flow forecasting. The uncertainty of the ensemble forecast needs to be assessed for these products to become useful in forecasting operations. A comprehensive framework for Bayesian revision has been recently developed and applied to operational flood ...
متن کامل