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Monday, March 19, 2012

"Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset" by Colin P. Morice et al., JGR (2012) in press; doi:10.1029/2011JD017187

Journal of Geophysical Research, (2012); doi:10.1029/2011JD017187
Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset
Colin P. Morice, John J. J. Kennedy, Nick A. Rayner and Philip Douglas Jones
Abstract

Recent developments in observational near-surface air temperature and sea-surface temperature analyses are combined to produce HadCRUT4, a new dataset of global and regional temperature evolution from 1850 to the present. This includes the addition of newly digitised measurement data, both over land and sea, new sea-surface temperature bias adjustments and a more comprehensive error model for describing uncertainties in sea-surface temperature measurements. An ensemble approach has been adopted to better describe complex temporal and spatial interdependencies of measurement and bias uncertainties and to allow these correlated uncertainties to be taken into account in studies that are based upon HadCRUT4. Climate diagnostics computed from the gridded dataset broadly agree with those of other global near-surface temperature analyses. Fitted linear trends in temperature anomalies are approximately 0.07 degC/decade from 1901 to 2010 and 0.17 degC/decade from 1979 to 2010 globally. Northern/southern hemispheric trends are 0.08/0.07 degC/decade over 1901 to 2010 and 0.24/0.10 degC/decade over 1979 to 2010. Linear trends in other prominent near-surface temperature analyses agree well with the range of trends computed from the HadCRUT4 ensemble members.
Received 18 November 2011; accepted 20 February 2012.
Citation: Morice, C. P., J. J. J. Kennedy, N. A. Rayner, and P. D. Jones (2012), Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 datasetJ. Geophys. Res., doi:10.1029/2011JD017187, in press.

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