Posts Tagged ‘Roy Spencer’

Climate models stretch credulity

June 6, 2013

What is perplexing is the blind faith in the climate models and reluctance to revisit the assumptions on which the clearly fallacious models are based.

UPDATE!!

Dr. Spencer has also provided the “un-linearised” data  and writes:

In response to those who complained in my recent post that linear trends are not a good way to compare the models to observations (even though the modelers have claimed that it’s the long-term behavior of the models we should focus on, not individual years), here are running 5-year averages for the tropical tropospheric temperature, models versus observations (click for full size):
CMIP5-73-models-vs-obs-20N-20S-MT-5-yr-means
In this case, the models and observations have been plotted so that their respective 1979-2012 trend lines all intersect in 1979, which we believe is the most meaningful way to simultaneously plot the models’ results for comparison to the observations.

In my opinion, the day of reckoning has arrived. The modellers and the IPCC have willingly ignored the evidence for low climate sensitivity for many years, despite the fact that some of us have shown that simply confusing cause and effect when examining cloud and temperature variations can totally mislead you on cloud feedbacks (e.g. Spencer & Braswell, 2010). The discrepancy between models and observations is not a new issue…just one that is becoming more glaring over time. ….

….

Reblogged from Dr. Roy Spencer

Courtesy of John Christy, a comparison between 73 CMIP5 models (archived at the KNMI Climate Explorer website) and observations for the tropical bulk tropospheric temperature (aka “MT”) since 1979 (click for large version):
CMIP5-73-models-vs-obs-20N-20S-MT
Rather than a spaghetti plot of the models’ individual years, we just plotted the linear temperature trend from each model and the observations for the period 1979-2012.

Note that the observations (which coincidentally give virtually identical trends) come from two very different observational systems: 4 radiosonde datasets, and 2 satellite datasets (UAH and RSS).

If we restrict the comparison to the 19 models produced by only U.S. research centers, the models are more tightly clustered:
CMIP5-19-USA-models-vs-obs-20N-20S-MT

Now, in what universe do the above results not represent an epic failure for the models?

I continue to suspect that the main source of disagreement is that the models’ positive feedbacks are too strong…and possibly of even the wrong sign.

The lack of a tropical upper tropospheric hotspot in the observations is the main reason for the disconnect in the above plots, and as I have been pointing out this is probably rooted in differences in water vapor feedback. The models exhibit strongly positive water vapor feedback, which ends up causing a strong upper tropospheric warming response (the “hot spot”), while the observation’s lack of a hot spot would be consistent with little water vapor feedback.

Chaos of climate models only shows that “we don’t know what we don’t know”

April 17, 2013

I spent a large part of my early career in mathematical modelling (of combustion systems and of heat flow) and have a very clear idea of what models can do and what they can’t. Models after all are used primarily to simplify complex systems which are otherwise intractable. They are – always – severely limited by the assumptions and simplifying approximations that have to be introduced. Models are a powerful tool for investigation but are only as good as their most inaccurate assumption. But they are a tool primarily for investigation — and can be dangerous when used for decision making based on their imperfect predictions. The spectacular failures of mathematical models of the global economy are a case in point. It is worth noting that in spite of the great strides made in weather forecasting  for example – much of which is empirical – the simple statement that “tomorrows weather will be like today’s”  is as correct – statistically – as the most complex model running on some super-computer somewhere.

It has therefore always amazed me that so-called “scientists” would be so certain about their approximate models of climate systems – which are perhaps as complex, chaotic and “unknown” systems as any one could study. It has been a boon for politicians looking for new ways of raising revenue. It has been exploited by the alarmists since the alarmist predictions cannot be tested. The wide spread of results from climate models is rarely mentioned.

When reality does not match model forecasts it is time to back off and rethink the models and hopefully they will be better next time. And it is time to back track from all the political decisions made on the basis of patently incomplete and inaccurate models.

The simple reality about climate is that rather than being a “settled science”

  • we don’t know the impact of solar effects on climate
  • we don’t know the impact of clouds or even if they are net “warmers” or net “coolers”
  • we don’t know how much of the earth’s radiative energy balance is dependent upon carbon dioxide
  • we don’t know how much carbon dioxide is absorbed  by the oceans and living things
  • we don’t know the impact of aerosols and particles in the atmosphere
  • we don’t know the role of the oceans in transporting heat around the globe
  • we don’t know how much heat is stored in the oceans and how it varies
  • we don’t know the impact of solar effects on cloud formation
  • we don’t know what triggers ice ages, and
  • we don’t know what we don’t know.

This from Dr. Roy Spencer and the ridiculously wide spread of the model results and the obvious deviation of reality from model results are particularly striking:

Global Warming Slowdown: The View from Space

Since the slowdown in surface warming over the last 15 years has been a popular topic recently, I thought I would show results for the lower tropospheric temperature (LT) compared to climate models calculated over the same atmospheric layers the satellites sense.

Courtesy of John Christy, and based upon data from the KNMI Climate Explorer, below is a comparison of 44 climate models versus the UAH and RSS satellite observations for global lower tropospheric temperature variations, for the period 1979-2012 from the satellites, and for 1975 – 2025 for the models:

CMIP5-global-LT-vs-UAH-and-RSS

CMIP5-global-LT-vs-UAH-and-RSS

Clearly, there is increasing divergence over the years between the satellite observations (UAH, RSS) and the models. The reasons for the disagreement are not obvious, since there are at least a few possibilities:

……… 

The dark line in the above plot is the 44-model average, and it approximately represents what the IPCC uses for its official best estimate of projected warming. Obviously, there is a substantial disconnect between the models and observations for this statistic.

I find it disingenuous for those who claim that, because not ALL of individual the models disagree with the observations, the models are somehow vindicated. What those pundits fail to mention is that the few models which support weaker warming through 2012 are usually those with lower climate sensitivity.

So, if you are going to claim that the observations support some of the models, and least be honest and admit they support the models that are NOT consistent with the IPCC best estimates of warming.


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