A Bayesian approach to climate model evaluation and multi‐model averaging with an application to global mean surface temperatures from IPCC AR4 coupled climate models

By S. Min, Andreas N. Hense. 2006

114 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/141bb6153a25514eb49d0622c43cb0955a837699

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. Reto Knutti
2. C. Tebaldi
3. Daniel Simonis
4. Miguel B. Araújo
5. N. Burgess
6. C. Rahbek
7. R. A. Garcia
8. M. Cabeza

In Global and Planetary Change

1. Reto Knutti
2. C. Rahbek
3. C. Tebaldi
4. M. Cabeza
5. R. A. Garcia
6. Miguel B. Araújo
7. N. Burgess
8. S. Min

Citations in the corpus

• Probabilistic climate change predictions applying Bayesian model averaging (2007, methodology): “Greene et al. (2006) fitted a linear model to observation and model simulation, and the method of Min & Hense (2006a) is based on measuring a generalized distance between observation and simulation.”
• How Well Do Coupled Models Simulate Today's Climate? (2008, background): “More recently, Min and Hense (2006) introduced a Bayesian approach into model evaluation, where skill is measured in terms of a likelihood ratio of a model with respect to some reference.”
• Bayesian calibration, comparison and averaging of six forest models, using data from Scots pine stands across Europe (2013, background): “This is not exceptional; BMA has been reported to have higher forecasting skill than each individual model in other fields, such as medical prognosis (Hoeting et al., 1999) and climate prediction (Min and Hense, 2006).”
• The use of the multi-model ensemble in probabilistic climate projections (2007, methodology): “For a given metric and for presentday climate, weighted averages of models were shown to compare better to observations than to raw averages with equal weights ( Min & Hense 2006 ).”
• Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates (2011, background): “They have been shown not to systematically change the results in some cases (e.g. Pierce et al. , 2009) and to improve them in other cases (e.g. Min & Hense, 2006).”