An updated comparison of model ensemble and observed temperature trends in the tropical troposphere
Stephen McIntyre, Ross McKitrick

TL;DR
This paper reevaluates the discrepancy between climate model predictions and observed tropical troposphere temperature trends, showing that previous claims of no significant difference are not supported when using extended data and consistent methodology.
Contribution
It demonstrates that extending the data period and applying the same methodology reveals significant differences between models and observations, challenging prior claims of resolution.
Findings
Significant difference between model trends and UAH observations with extended data
Approaching significance for RSS data when using updated data
Previous claims of no discrepancy are unwarranted with new analysis
Abstract
A debate exists over whether tropical troposphere temperature trends in climate models are inconsistent with observations (Karl et al. 2006, IPCC (2007), Douglass et al 2007, Santer et al 2008). Most recently, Santer et al (2008, herein S08) asserted that the Douglass et al statistical methodology was flawed and that a correct methodology showed there is no statistically significant difference between the model ensemble mean trend and either RSS or UAH satellite observations. However this result was based on data ending in 1999. Using data up to the end of 2007 (as available to S08) or to the end of 2008 and applying exactly the same methodology as S08 results in a statistically significant difference between the ensemble mean trend and UAH observations and approaching statistical significance for the RSS T2 data. The claim by S08 to have achieved a "partial resolution" of the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsClimate variability and models · Meteorological Phenomena and Simulations · Tropical and Extratropical Cyclones Research
