(This one includes the dynamite John Christy graph showing the rapidly growing divergence of climate model global temperature forecasts
with real world observations.)
GIGO — All of the GCMs fail validation testing, which means GCMs do no agree
with real world observations — i.e., none of the GCMs demonstrate any predictive ability whatsoever.
Much of this has already been covered in earlier posts as well as in my book, Environmentalism Gone Mad; this post is intended to summarize some of the new hypotheses generated by comparisons
with real world observations.
And some versions aren't even internally consistent, never mind consistent
with real world observations.
I have to admit that this is exactly the kind of physics I enjoy, good simple theory joined at the hip
with real world observation, and I find it very convincing.
Not exact matches
«Critical consciousness» seems to entail a conviction that our ideas are in touch
with the
real world only if they pass the test of being «verifiable» or «falsifiable» according to methods of
observation that are publicly accessible.
The researchers looked at
real -
world observations and confirmed that this temperature pattern does correspond
with the double - peaked jet stream and waveguide patter associated
with persistent extreme weather events in the late spring and summer such as droughts, floods and heat waves.
If
real -
world observations don't match the models forecasting catastrophic species loss, why do you nonetheless side
with models anyway?
«This field site exhibits a typical North Atlantic biofouling community, most notably a population of blue mussels (Mytilus edulis), which allowed to compare the findings obtained in the laboratory
with observations in
real -
world conditions,» says Stefan Kolle, a Research Associate in the Aizenberg lab at the Wyss Institute and SEAS who is also a co-first author of the paper.
Personally, I'm doubtful that emergent constraint approaches generally tell one much about the relationship to the
real world of aspects of model behaviour other than those which are closely related to the comparison
with observations.
The basic idea is that across the CMIP3 models there was a strong correlation of mid-tropospheric humidity variations
with the model sensitivity, and combined
with observations of the
real world variations, this gives a way to suggest which models are most realistic, and by extension, what sensitivities are more likely.
Scientists are creating simulated universes — complete
with dark matter mock - ups, computer - generated galaxies, quasi quasars, and pseudo supernovae — to better understand
real -
world observations.
They clarify complex concepts by articulating
observations and learning
with real -
world context.
The lab supplies our students
with resources that are normally available only from a major publisher, including 10 group testing stations, a living room style lab
with an
observation booth for
real -
world evaluations, and
real - time high definition recording and broadcasting equipment.
It's something of an abstract concept, but
with real world implications, and the universality of such physical models, based on things like radiative balance, atmospheric composition and density, distance from the local Sun, etc., is a very strong argument in favor of general acceptance of the results of climate models and
observations on Earth.
So you try to simulate some aspect of the
real world and compare the simulation
with observations.
A simple comparison of
observations with projections based on
real world climate forcings shows a very close match, especially if we take natural unforced variability into account as well (mainly ENSO).
The basic idea is that across the CMIP3 models there was a strong correlation of mid-tropospheric humidity variations
with the model sensitivity, and combined
with observations of the
real world variations, this gives a way to suggest which models are most realistic, and by extension, what sensitivities are more likely.
And since the
real world did not have those large eruptions (1963 Agung and 1982 El Chichón repeated), the agreement of
observations with the forecasts is not as good as it appears.
This essay is an attempt to link
real world observations (the failure of surface temperatures to rise in tandem
with atmospheric CO2) to basic physics and thereby show why the radiative characteristics of Greenhouse Gases can not increase the surface temperature of a planet when atmospheric mass, the strength of the gravitational field and the power of insolation at the top of the atmosphere remain the same.
They might also ask you to explain why for long term projections, initial conditions matter little,
with the model outputs converging toward a common and relatively accurate simulation of
real world observations.
However, before they should be provided to the impacts communities as anything more than a model sensitivity study, they must be shown to have skill
with respect to
real world observations.
These studies are not Type 4 applications when run in a hindcast mode (which is the only scientific way (i.e. the comparison
with actual
real world observations) to evaluate their skill.
How to Lie
With Data (or, «Melting Away Global Warming») New
Observations Confirm Greenland, Antarctica Losing Land Ice Rapidly The Top of the
World Sinks Ever Lower New Study: Climate Scientists Overwhelmingly Agree Global Warming Is
Real and Our Fault Slaying the Zombie Ideas of Climate Change Denial
«Comparing prediction
with observation» is not confirmation that the
real -
world physics operate as one believes they do.
These uni-dimensional junk science professors are confident in their intellectual abilities to continue getting away
with indulging in their idle speculations and spreading their flapdoodle about things that have proven to be untrue; and, they demand that we appoint them as elites to rule over the rest of us despite a complete absence of supporting evidence for their many predictions that have been falsified by
real -
world observations.
Part of the process involves adjusting model parameters within limits dictated by
observations and the principles of physics so as to coax the simulations into good agreement
with the
real world climate.
Firstly, on a factual matter, the OHC comparison which I published above...... was not intended to be a comparison
with real -
world observations, only a comparison
with the GISS E ensemble mean result, which should correspond to the reported GISS E temperature profile which was simultaneously matched.
The two things which make science different from religion are that nothing in science is sacred, and everything in science must ultimately fit
with observations of the
real world.
Personally, I'm doubtful that emergent constraint approaches generally tell one much about the relationship to the
real world of aspects of model behaviour other than those which are closely related to the comparison
with observations.
«Our approach facilitates comparisons and produces results that agree more closely
with real -
world observations than previous approaches,» said Dr. Po - Lun Ma, PNNL atmospheric scientist and lead author of the paper.
He doesn't need the complete data to affirm his presupposed beliefs, just as he doesn't need experimental evidence or physical measurements or
real -
world observations to affirm his belief that humans are heating up the oceans
with their CO2 emissions.
They then compared their model results
with the set of
real -
world observations.
Let's just sum it up by saying that I find that the mechanisms needed to provide even a partial explanation of
observations happen to diverge from that which the reconstructions might suggest and my approach to resolving the discrepancy is continuing
observation of the
real world with the likely mechanisms in mind.
Every time the models have been adjusted using guesswork (or informed judgement as some would say) to bring them back into line
with ongoing
real world observations a new divergence between model expectations and
real world events has begun to develop.
You said: «narrative is replete
with opportunities for falsification if the future
real world observations diverge from the pattern of cause and effect that I have set out.»
My continuing disagreement
with Leif here is becoming centred on one such
real world observation which, if substantiated, is contrary to his view but accommodated by mine.
Every time the models have been adjusted using guesswork (or informed judgment as some would say) to bring them back into line
with ongoing
real world observations a new divergence between model expectations and
real world events has begun to develop.
There is a deep literature on the basic theory developed from first principles, models, experiments and
observations (in many areas of physics, chemistry, geology, biology), and a large published body of empirical geophysical and biological evidence from
real world systems, the majority of which is consistent
with this underpinning science.
We should wait until the science is definitive and backed up
with evidence based
observations of the
real world before getting all skyrockety and hysterical.
Every time I come face to face
with the idea that somehow GCMs have a life of their own (literally) and are therefore of equal value as
observations of the
real world, I sense a deep philosophical divide that goes to the heart of modern scientific method and empiricism.