An Efficient Stochastic Bayesian Approach to Optimal Parameter and Uncertainty Estimation for Climate Model Predictions

By Charles S. Jackson, Mrinal K. Sen, Paul L. Stoffa. 2004

133 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/dd8478ef9eb33630fd58c1c40fbbbea605af7271

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Y. Qian
2. G. Lin
3. Ben Yang
4. R. Leung
5. Yuehan Zhang
6. Youssef M. Marzouk
7. Stephen P. Grand

In Global and Planetary Change

1. Y. Qian
2. G. Lin
3. Ben Yang
4. R. Leung
5. Yuehan Zhang

Citations in the corpus

• Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model (2011, methodology): “Very Fast Simulated Annealing (VFSA) is a stochastic importance sampling algorithm with high converging efficiency toward the optimal results (Ingber, 1989; Jackson et al., 2004).”
• Stochastic spectral methods for efficient Bayesian solution of inverse problems (2005, background): “Bayesian approaches to inverse problems have seen much recent interest [3,5,2], with applications ranging from geophysics [6,7] and climate modeling [8] to heat transfer [9,10].”
• Error Reduction and Convergence in Climate Prediction (2008, methodology): “Following Jackson et al. (2004), Bayesian inference is used along with a stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA), to efficiently identify the regions of model parameter space of CAM3.”
• Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems (2008, background): “Bayesian approaches to inverse problems have received much recent interest [4, 48, 49], with applications ranging from geophysics [50, 51] and climate modeling [52] to heat transfer [20, 53].”
• GyPSuM: A joint tomographic model of mantle density and seismic wave speeds (2010, methodology): “A grid search or Monte Carlo approach would be computationally 18    daunting and we have therefore adapted a very fast simulated annealing (VFSA) approach [Ingber 1989; Jackson et al. 2004] to identify the optimum set of scaling model adjustment parameters described in Equation (6) and Table 4.”