Upgrades to the reliability ensemble averaging method for producing probabilistic climate-change projections

Conditional Probabilistic Population Projections: An Application to Climate Change

Probabilistic climate change predictions applying Bayesian model averaging.

This study explores the sensitivity of probabilistic predictions of the twenty-first century surface air temperature (SAT) changes to different multi-model averaging methods using available simulations from the Intergovernmental Panel on Climate Change fourth assessment report. A way of observationally constrained prediction is provided by training multi-model simulations for the second half of...

Bayesian model averaging Probabilistic climate change predictions applying

References l.html#ref-list-1 http://rsta.royalsocietypublishing.org/content/365/1857/2103.ful This article cites 24 articles, 1 of which can be accessed free Rapid response 1857/2103 http://rsta.royalsocietypublishing.org/letters/submit/roypta;365/ Respond to this article Email alerting service here in the box at the top right-hand corner of the article or click Receive free email alerts when n...

Probabilistic projections of 21st century climate change over Northern Eurasia

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downsc...

The use of the multi-model ensemble in probabilistic climate projections.

Recent coordinated efforts, in which numerous climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various scenarios. Those multi-model ensembles sample initial condition, parameter as well as structural uncertainties in the model design, and they have prompted a variety of approaches to quantify uncertainty in future cl...