The paper is Douville et al. (2015) The recent global warming hiatus: What is the role of Pacific variability? [paywalled]. The abstract reads (my boldface):
The observed global mean surface air temperature (GMST) has not risen over the last 15 years, spurring outbreaks of skepticism regarding the nature of global warming and challenging the upper range transient response of the current-generation global climate models. Recent numerical studies have, however, tempered the relevance of the observed pause in global warming by highlighting the key role of tropical Pacific internal variability. Here we first show that many climate models overestimate the influence of the El Niño–Southern Oscillation on GMST, thereby shedding doubt on their ability to capture the tropical Pacific contribution to the hiatus. Moreover, we highlight that model results can be quite sensitive to the experimental design. We argue that overriding the surface wind stress is more suitable than nudging the sea surface temperature for controlling the tropical Pacific ocean heat uptake and, thereby, the multidecadal variability of GMST. Using the former technique, our model captures several aspects of the recent climate evolution, including the weaker slowdown of global warming over land and the transition toward a negative phase of the Pacific Decadal Oscillation. Yet the observed global warming is still overestimated not only over the recent 1998–2012 hiatus period but also over former decades, thereby suggesting that the model might be too sensitive to the prescribed radiative forcings.
That’s something you don’t normally see from the climate science community.
[Thanks to blogger Alec aka Daffy Duck for the heads-up.]
Yes, this overestimation is key to the failure during the global warming period that ended with the 1998 El Niño. But there are more fundamental problems, like the failure to model the oceans.
Sorry for changing the subject.
Jo Bastardi is going big on the AMO tonight, calling it a potential climate shift. do you have any up to date information to explain what he is seeing.
All I can find is this http://www.esrl.noaa.gov/psd/data/correlation/amon.sm.data
Andrew, I have no idea. I’ll post the monthly update later today or tomorrow. There’s nothing unusual about the North Atlantic sea surface temperature anomalies.
The paper writes:
“The observed global mean surface air temperature (GMST) has not risen over the last 15 years.”
That’s a huge mistake.
Cowtan & Way’s dataset shows +0.16 C of warming over the last 15 years.
GISS shows +0.13 C warming. HadCRUT4 shows +0.10 C warming. NCDC shows +0.08 C of warming.
So who are these guys trying to kid??
Andrew: Perhaps Joe Bastardi should pay more attention to the PDO, which is clearly flipping now — it was net positive in 2014, for the first time in 8 years.
Andres Valencia wrote:
“But there are more fundamental problems, like the failure to model the oceans.”
How would you model the oceans, to correct the flaws you see in the current models?
Epiphron Elpis, welcome troll.
Regarding model simulations of the oceans, they will need to simulate well-known coupled ocean-atmosphere processes such as ENSO and the AMO. Because climate models can’t simulate those processes, they fail miserably at simulating sea surface temperatures over the past 33 years:
Regarding Cowtan and Way, the last time I looked the Cowtan and Way infilling exaggerated the warming at the poles but did nothing to explain the slowdown for the remainder of the planet.
Regarding Joe Bastardi and the PDO, Joe includes the state of the PDO in his long-term forecasts. Maybe you should research before commenting. Then again, you’re a troll.
Have a good day.
Looks like this is what Jo was excited about: https://twitter.com/philklotzbach/status/564878796960968704
Somewhat related and probably of interest to you Bob is a comment I made on the discussion over at CA about marotzke-and-forster’s paper.
I think that paper is actually proving what you have been saying for a long time about models being bad at historical backcasting and internal variability.
In fact the “pause” problem is not a new divergence, the models just as bad at backcasting as they are prediction.