Bayesian Climate Change Assessment.

Abstract A Bayesian fingerprinting methodology for assessing anthropogenic impacts on climate was developed. This analysis considers the effect of increased CO2 on near-surface temperatures. A spatial CO2 fingerprint based on control and forced model output from the National Center for Atmospheric Research Climate System Model was developed. The Bayesian approach is distinguished by several new facets. First, the prior model for the amplitude of the fingerprint is a mixture of two distributions: one reflects prior uncertainty in the anticipated value of the amplitude under the hypothesis of “no climate change.” The second reflects behavior assuming“climate change forced by CO2.” Second, within the Bayesian framework, a new formulation of detection and attribution analyses based on practical significance of impacts rather than traditional statistical significance was presented. Third, since Bayesian analyses can be very sensitive to prior inputs, a robust Bayesian approach, which investigates the ranges of...

[1]  Effect of observational sampling error on the detection of anthropogenic climate change , 2001 .

[2]  W. Collins,et al.  Response of the NCAR Climate System Model to Increased CO2 and the Role of Physical Processes , 2000 .

[3]  N. Cressie,et al.  Classes of nonseparable, spatio-temporal stationary covariance functions , 1999 .

[4]  John F. B. Mitchell,et al.  Causes of twentieth-century temperature change near the Earth's surface , 1999, Nature.

[5]  Mark New,et al.  Surface air temperature and its changes over the past 150 years , 1999 .

[6]  Richard A. Levine,et al.  Statistical Principles for Climate Change Studies , 1999 .

[7]  Klaus Hasselmann,et al.  Conventional and Bayesian approach to climate‐change detection and attribution , 1998 .

[8]  P. Gent,et al.  The NCAR Climate System Model, Version One* , 1998 .

[9]  Stephen S. Leroy.  Detecting Climate Signals: Some Bayesian Aspects , 1998 .

[10]  Gerald R. North,et al.  Detecting Climate Signals in the Surface Temperature Record , 1998 .

[11]  Richard S. J. Tol,et al.  A Bayesian Statistical Analysis of the Enhanced Greenhouse Effect , 1998 .

[12]  M. R. Allen,et al.  Checking for model consistency in optimal fingerprinting , 1999 .

[13]  Keith R. Briffa,et al.  Estimating Sampling Errors in Large-Scale Temperature Averages , 1997 .

[14]  Klaus Hasselmann,et al.  Multi-pattern fingerprint method for detection and attribution of climate change , 1997 .

[15]  R. Voss,et al.  Multi-fingerprint detection and attribution analysis of greenhouse gas, greenhouse gas-plus-aerosol and solar forced climate change , 1997 .

[16]  Tom M. L. Wigley,et al.  Towards the detection and attribution of an anthropogenic effect on climate , 1995 .

[17]  P. Jones,et al.  Hemispheric Surface Air Temperature Variations: A Reanalysis and an Update to 1993. , 1994 .

[18]  K. E. Taylor,et al.  Response of the climate system to atmospheric aerosols and greenhouse gases , 1994, Nature.

[19]  K. Hasselmann.  Optimal Fingerprints for the Detection of Time-dependent Climate Change , 1993 .

[20]  J. Berger.  Statistical Decision Theory and Bayesian Analysis , 1988 .

[21]  Edward S Epstein.  Statistical inference and prediction in climatology : a bayesian approach , 1985 .

[22]  Franklin A. Graybill,et al.  Theory and Application of the Linear Model , 1976 .