beej67 said:
So what, in your opinion, is wrong with the models, rconnor? Do you think that the volcano thing is the key to unlocking what's wrong with our climate models, or do you think something else is at fault?
Re-read my post
here at 4 Apr 14 17:45. In a nutshell, the bulk of the variance between models and observations can be explained by:
- ENSO (Kosaka and Xie 2013, England et al 2014, Foster and Rahmstorf 2011 and many others)
- Lack of coverage of arctic warming in some data sets (Cowtan and Way 2013)
- Underestimating the amount of anthropogenic aerosols
- Underestimating the short term impact of smaller volcanic activity (Santer et al 2014, Ridley et al 2014)
- Required update to OHC (Durack et al 2014)
- The fact that models were never intended on matching short-term fluctuations perfectly
When you account for these factors (which are mainly notable over the short-term but not the long-term) models match observations very well (Schmidt et al 2014, Huber and Knutti 2014). None of these factors suggest that climate sensitivity is too high in models. None of these factors suggest that we are greatly underestimating a negative feedback or greatly overestimating a positive feedback. And so there appears very little to no evidence that the recent variances between models and observations severely threatens the core of our understanding of climate science.
(Regarding the image, GCM’s aim to calculate surface temperature. Balloons and Satellites measure the mid troposphere temperature. No one that knows what they’re talking about and is trying to be honest would compare the two. It’s apples and oranges or, at best, red delicious and granny smith.
Averaging model runs, without showing the range, is meaningless. The average isn’t the “best guess”. Models incorporate the uncertainty of various factors; some are stochastic (volcanoes and ENSO), others we don’t know with 100% certainty (cloud feedbacks). So, over the short term, models that get the short-term variability right (i.e. predict the right ENSO state) will be accurate and ones that don't will not. The average might mean more over the long-term but is rather meaningless in the short-term. No one that knows what they’re talking about and is trying to be honest would represent short-term model predictions as a single, averaged line.
The graph, which you didn’t source (but no worries, I know it was from CATO), is meaningless but purposefully designed to get a mistaken point across. Completely (yet unsurprising) garbage from a garbage institution.)