A Bayesian hierarchical model for climate change detection and attribution

Methods for climate change detection and attribution

Detection and attribution (D&A) have played a central role within the assessment of the human influence on climate and within IPCC’s reports. Detection involves the statistical demonstration that a change has happened within climatic observations. Attribution consists in assessing the respective contributions of one or several causes to some observed change. Both require the use of climate mode...

A Generalizable Hierarchical Bayesian Model for Persistent SAR Change Detection

This paper proposes a hierarchical Bayesian model for multiple-pass, multiple antenna synthetic aperture radar (SAR) systems with the goal of adaptive change detection. We model the SAR phenomenology directly, including antenna and spatial dependencies, speckle and specular noise, and stationary clutter. We extend previous work by estimating the antenna covariance matrix directly, leading to im...

Detection and attribution of climate change: a regional perspective

The Intergovernmental Panel on Climate Change fourth assessment report, published in 2007 came to a more confident assessment of the causes of global temperature change than previous reports and concluded that ‘it is likely that there has been significant anthropogenic warming over the past 50 years averaged over each continent except Antarctica.’ Since then, warming over Antarctica has also be...

Climate Change Detection and Attribution: Beyond Mean Temperature Signals

A significant influence of anthropogenic forcing has been detected in globaland continental-scale surface temperature, temperature of the free atmosphere, and global ocean heat uptake. This paper reviews outstanding issues in the detection of climate change and attribution to causes. The detection of changes in variables other than temperature, on regional scales and in climate extremes, is imp...

Detection of Climate Change and Attribution of Causes