3R.S. Knox and D.H. Douglass – The missing heat is
not in the ocean.
The dominant explanation for where Trenberth’s missing warming or heat is
that it is in the ocean. This missing heat is the difference between the
climate effects, particularly change in global average temperature, which global
warming predicted we would have and the much lower change in global average
temperature we have had. In 2009 modeling von Shuckmann et al15
seemed to have found this missing heat at depths of 2000 metres in the ocean.
One immediate problem for von Shuckmann et al is found in the NOAA graph in
Figure 3. This graph is based on data for ocean heat content to depths of 700
metres which show no warming from 2003:
The problem this shows for von Shuckmann et al [and other papers which
also use modeling to ‘find’ deep-ocean warming16] is; how could the
ocean depths be warming when the ocean top was cooling?
A second problem was raised in 2 papers by the team of Ablain17
and Cazenave18; they showed that not only was the rate of sea level
rise decreasing but the steric part of the sea level rise, which is based on
ocean heat content, was also decreasing from 2006.
The third contradiction to von Shuckmann et al and the missing heat is in
Knox and Douglass’s paper19. Knox & Douglass are both imminent
atmospheric physicists and have already written a number of papers dealing with
ocean based climatic events and the connection between the ocean radiative rate
of change [Fohc] and the radiative rate of change at the top of the atmosphere [Ftoa].
In their latest paper Knox & Douglass showed that not only was ocean
heat content declining but that the Fohc was negative, which meant more
radiative energy was leaving the ocean than being stored:
Figure 4 From Knox & Douglass page 1. Fohc left scale.
Figure 1. Ocean heat content from
Argo (left scale: blue, original data; red, filtered) and ocean surface
temperatures (right scale, green). Conversion of the OHC slope to W/m2 is made
by multiplying by 0.62, yielding –0.161 W/m2.
Knox & Douglass’s findings about ocean heat content were based on empirical
measurements and are consistent with studies by Willis, Loehle, and Pielke, and
NOAA data [see Figure 3].
Knox & Douglass conclude that because “90% of the variable heat
content resides in the upper ocean” the Fohc can accurately infer the Ftoa.
Therefore if Fohc is negative then Ftoa is as well. A negative Ftoa is contrary
to Trenberth’s claims of missing heat being stored most likely in the oceans.
Without missing heat the models have greatly overestimated the effect of global
– The optical depth of the atmosphere hasn’t changed
5 [from Miskolczi 2010]
Ferenc Miskolczi was a NASA atmospheric physicist whose 2 papers in 200720
and 201021 were both peer reviewed and have never been refuted.
These papers draw on data and calculations made by Miskolczi in a 2004 paper
co-authored by NASA physicist Martin Mlynczak. Miskolczi 200422
shows that radiation leaving the Earth, outgoing long-wave radiation, is based
on zonal and global averages of real atmospheric conditions as shown in the
atmospheric optical thickness.
Miskolczi 2007 and 2010 measure
“the true greenhouse-gas optical thickness” [Abstract, Miskolczi 2010]. This is
made up of two parts which are depicted in Figure 4.
a.τA -- is defined as “the
total IR flux optical depth” [page 5 Miskolczi 2007]. This is a measure of the
total amount of infra-red or long-wave radiation which is absorbed between the
surface and the top of the atmosphere.
b.A -- is the flux absorbance [page 3 Miskolczi 2010] and is a
measure of what wavelengths of long-wave radiation are being absorbed and
transmitted in the atmosphere by 11 greenhouse gases [page 7, Miskolczi 2004].
Together τA and A are the optical depth of the atmosphere The optical depth is
a kind of proxy measure of the greenhouse effect. Global warming says that more
CO2 will increase the optical depth. Miskolczi showed that available
empirical measurements of the optical depth are consistent with no change in 61
years. This means that even though CO2 has increased over the 61
years of measurement and increased the optical depth slightly, “variations in
water vapor column amounts” [Figure 11, Miskolczi 2010] have decreased the optical
depth by a similar amount. Paltridge et al.23 have confirmed a
decrease in water vapor for this period.
If the optical depth has not
increased overall, it suggests the slight warming of the 20th C has
not been due to an increase in the greenhouse effect.
In addition Miskolczi also finds no positive feedback from water vapor on
atmospheric long-wave radiation absorption, which negates what the models have
predicted; this lack of positive feedback has been confirmed by the missing ‘Tropical
hot spot’ [see section 6].
and Wyner24 – The Hockeystick is broken
Figure 6. McShane&Wyner, page 36
Blakeley McShane and Abraham Wyner attempted to replicate Michael Mann’s
infamous hockeystick using Mann’s own data. The hockeystick first appeared in
Mann’s 1998 paper and has been a centre-piece of global warming evidence ever
since. The hockeystick is important because it supposedly shows recent warming
is exceptional and “unprecedented”. The hockeystick is based on dendro-climatic
proxies or tree-rings which supposedly provide evidence for past temperatures. Mann’s
hockeystick shows basically flat temperature until the 20th C and
then a sudden and rapid increase.
Mann’s data was highly problematic. Mann had used the wrong type of tree,
and at times, hardly any samples. Some of the tree-ring records even show the
opposite “temperature” trend to what thermometers show suggesting those trees
don’t make a good or accurate alternative to thermometers.
McShane &Wyner tried to create the same graph from the same data, but,
as Figure 5 above shows, could not. They conclude:
“Using our model, we calculate that there is a 36% posterior probability
that 1998 was the warmest year over the past thousand. If we consider rolling
decades, 1997-2006 is the warmest on record; our model gives an 80% chance that
it was the warmest in the past thousand years. Finally, if we look at rolling
thirty-year blocks, the posterior probability that the last thirty years
(again, the warmest on record) were the warmest over the past thousand is 38%.”[page
So, even using
Mann’s dubious data and employing a variety of statistical methods, McShane
& Wyner’s model suggests that there is only an 80% chance that one recent
decade was the warmest of the last 1000 years, and 1998 is most likely not the warmest year [64% against] and
the last 30 year period, is also unlikely to have been the warmest [62%
against]. In other words, the type of weather we have now has all occurred before,
and in the not too distant past when CO2 was supposedly low.
correctly describes the importance of the hockeystick not only to global
warming but also Green policies:
“the effort of world governments to
pass legislation to cut carbon to pre-industrial levels cannot proceed without
the consent of the governed and historical reconstructions from
paleoclimatological models [ie hockeysticks] have indeed proven persuasive and effective
at winning the hearts and minds of the populace.” [page 2]
It would seem
the hearts and minds have been won with false promises.
of the importance of McShane & Wyner’s paper it was published as an edition
discussion piece in Annals of
Applied Statistics25As well asthe original paper 15 discussion papers were included in the edition.
points emerge from this discussion. The first is noted in McIntyre and
McKitrick’s comment where they say:
McShane & Wyner’s results are, in a sense, a best case as they assume
that the quality of the data set is satisfactory [page 4]
In fact, as noted, the data was not satisfactory. The significance of
this is that the ‘science’ of the hockeystick is the data; the data is the
proxy for the climatic processes which are analysed in McShane & Wyner’s statistical
This statistical analysis is the second point and it is in this respect
that McShane & Wyner are unassailable because they have anticipated every
complaint and objection to their critique of Mann’s statistical justification
for the hockeystick. As this stage therefore their view on the hockeystick is
McIntyre, Herman26 - The hot spot is really missing
Figure 7. Based on Figures 2 and 3, page 13
of McKitrick et al.
If the IPCC models are right about the feedbacks, we would see a hot spot
10km above the tropics. Global warming theory says this should happen because
more water will have been evaporated to this part of the atmosphere and would
have caused rapid warming. Observations as shown in Figure 7 contradict this .
Thus the main, most powerful factor in the climate models turns out to not
match the real world.
Douglass et al 27 pointed out the glaring discrepancy of the
missing hot spot in 2007. However Douglass et al did not adequately distinguish
model variability in terms of single model or ensemble model outputs. Nor did
Douglass et al adjust the data for autocorrelation which meant the data did not
have satisfactory confidence levels or error bars.
As a result Santer et al  28 claimed Douglass got it
wrong, and that the data and the models did agree. But Santer et al used a
truncated set of data ending in 1999 to achieve the model and data correlation.
Christy et al  29 responded to Santer et al by
developing a scaling ratio comparing the atmospheric trend to the surface
trend. Christy et al showed the models predicted a scaling ratio of 1.4 ±0.8 [i.e. the atmosphere should warm 40% faster than the surface].
In reality the observations showed a scaling ratio of 0.8 ± 0.3 [i.e. the atmosphere was
not warming as fast as the surface].
McKitrick et al  also use the extended data and addressed the data
adjustment issues but used a greater range of statistical analysis. They found that
the model predictions are about 4 times higher
and outside the error bars of the weather balloons and satellites measurements
[see Figure 7].
McKitrick et al’s findings have been replicated by Fu et al 30
who also find a discrepancy between the models and observations about
Troposphere warming, although not to the same extent as McKitrick et al do. However,
in a follow-up paper, McKitrick 31 not only confirms that the predictions
of warming by the models have been exaggerated but also shows the small amount
of recent warming was due to a natural climate shift in 1977. This climate
shift has been noted by many other researchers 32 and means global
warming is playing an even smaller role then predicted by the models.
As noted in section 4, the absence of a tropical hot spot vindicates
Miskolczi because either the optical depth is not changing or, if it is, it
means that extra water vapor and CO2, which would change the
optical depth, are not heating in the way predicted by AGW.
7 Anagnostopoulos, G. G., Koutsoyiannis, D., Christofides, A.,
Efstratiadis, A. & Mamassis, N. The only thing certain is the models are
If McKitrick et al shows that the IPCC global computer models can’t model
the present and therefore the future, Professor Demetrius Koutsoyiannis and his
team show those models can’t even model the past
Koutsoyiannis is one of the world’s leading hydrologists and an expert on
Hurst and stochastic effects. Hurst or Long Term Persistence refers to the
uncertainty and random qualities present in all complex natural systems.
Koutsoyiannis argues that global warming modeling does not take into account
In his 2008 paper Koutsoyiannis33 compared the model
predictions from 1990 to 2008 and whether those models could retrospectively
match the actual temperature over the past 100 years. This test of
retrospectivity is called hindcasting. If a model has valid assumptions about
the climatic effect of variables such as greenhouse gases, particularly CO2, then the model should be able to
match past known data.
Koutsoyiannis’s 2008 paper has not had a peer reviewed rebuttal but was
subject to a critique at Real Climate by Gavin Schmidt.34 Schmidt’s
criticism was 4-fold; thatKoutsoyiannis uses a regional
comparison, few models, real temperatures not anomalies and too short a time
Each of Schmidt’s criticisms was either wrong or anticipated by
Koutsoyiannis. The period from 1990-2008 was the period in which IPCC modeling
had occurred; the IPCC had argued that regional effects from global warming would
occur; model ensembles were used by Koutsoyiannis; and since the full 100 year
temperature and rainfall data was used in intra-annual and 30 year periods by
Koutsoyiannis anomalies were irrelevant.
In 2008 Koutsoyiannis found that while the models had some success with
the monthly data all the models were “irrelevant with reality” at the 30 year
Koutsoyiannis’s 201035 paper “is a continuation and expansion
of Koutsoyiannis 2008”. The differences are that (a) Koutsoyiannis 2008 had
tested only eight points, whereas 2010 tests 55 points for each variable; (b) 2010
examines more variables in addition to mean temperature and precipitation; and
(c) 2010 compares at a large scale in addition to point scale. The large,
continental scale in this case is the contiguous US.
Again Koutsoyiannis 2010 found that the models did not hindcast
successfully with real data from all the 55 world regions not matching what the
models produced. The models were even worse in hindcasting against the real
data for the US continent.
So that is 3 strikes for global warming models; they could not predict
the future in 1990; they cannot predict the present and they could not
replicate or match the past.
The global warming models amplify CO2’s effect by 3 – 7 fold,
but no matter how you measure it [outgoing long wave radiation, cloud changes,
optical depth, historical temperatures, vertical heating patterns in the
atmosphere] the real measurements contradict the models and their assumptions
about the feedbacks appear to be unconnected with real data. It follows that
the global warming predictions about climate sensitivity to a doubling of CO2 are exaggerated by at least 3C.
Figure 8 Climate Sensitivity Comparison
The Hansen36 point of 1.2C in Figure 8 is a non-feedback
calculation for the temperature increase from a doubling of CO2. While that non-feedback figure is
essentially meaningless in the real world it is a convenient half-way house
between the climate sensitivity estimates of the IPCC and the models which
assume positive feedback and the empirical measurements of the papers discussed
in this article which consider the actual measured feedbacks to increases in CO2.
The climate sensitivity estimates of the discussed papers establish two
points which are fundamentally opposite to global warming. The first is that a
large portion of the temperature response to 2X CO2 has already occurred. CO2 atmospheric concentrations have risen
approximately 40% since 1900. Any temperature increase due to the increase in CO2 during this period would have already
The second point and as a corollary to the first is that there is no
delay or lag in temperature response as a proxy for climate sensitivity. The
IPCC makes a distinction between transient climate sensitivity and equilibrium
climate sensitivity with transient climate sensitivity being less and on a
shorter term than equilibrium sensitivity [see AR4, WG 1, TS.6.4.2]. These
papers strongly suggest that there is no such distinction between transient and
equilibrium sensitivity and that any CO2 temperature response is not delayed. This aspect of climate sensitivity
has been independently confirmed in the Beenstock and Reingewertz analysis.37
Beenstock finds that any effect CO2
has on temperature is temporary and not related to the absolute level of CO2.
The global warming predictions are contradicted by past, present and
future data. Feynman’s maxim applies and the vast funding which is now being
directed to ‘solving’ global warming should be redirected to hypothesis which
are consistent with empirical data and confirmed by observable evidence.
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