{"id":111,"date":"2021-08-29T02:52:54","date_gmt":"2021-08-29T02:52:54","guid":{"rendered":"https:\/\/australianclimatesceptics.com\/?p=111"},"modified":"2021-08-29T03:05:51","modified_gmt":"2021-08-29T03:05:51","slug":"has-man-made-global-warming-been-disproved-part-2","status":"publish","type":"post","link":"https:\/\/australianclimatesceptics.com\/?p=111","title":{"rendered":"Has Man-made global warming been disproved? (Part: 2)"},"content":{"rendered":"\n

Transfered from our old blog.

by Anthony Cox<\/strong> and Joanne Nova<\/strong>.
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3      R.S. Knox and D.H. Douglass \u2013 The missing heat is not in the ocean.<\/h3>\n\n\n\n

The dominant explanation for where Trenberth\u2019s 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<\/sup>\u00a0seemed 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:Figure 3: <\/p>\n\n\n\n

[http:\/\/www.nodc.noaa.gov\/OC5\/3M_HEAT_CONTENT\/index.html]<\/p>\n\n\n\n

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The problem this shows for von Shuckmann et al [and other papers which also use modeling to \u2018find\u2019 deep-ocean warming16<\/sup>] is; how could the ocean depths be warming when the ocean top was cooling?<\/p>\n\n\n\n

A second problem was raised in 2 papers by the team of Ablain17<\/sup>\u00a0and Cazenave18<\/sup>; 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.<\/p>\n\n\n\n

The third contradiction to von Shuckmann et al and the missing heat is in Knox and Douglass\u2019s paper19<\/sup>. 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].<\/p>\n\n\n\n

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:<\/p>\n\n\n\n

Figure 4 From Knox & Douglass page 1. Fohc left scale.<\/p>\n\n\n\n

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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 \u20130.161 W\/m2.<\/strong><\/p>\n\n\n\n

Knox & Douglass\u2019s 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].<\/p>\n\n\n\n

Knox & Douglass conclude that because \u201c90% of the variable heat content resides in the upper ocean\u201d the Fohc can accurately infer the Ftoa. Therefore if Fohc is negative then Ftoa is as well. A negative Ftoa is contrary to Trenberth\u2019s claims of missing heat being stored most likely in the oceans. Without missing heat the models have greatly overestimated the effect of global warming.<\/p>\n\n\n\n

4      Miskolczi \u2013 The optical depth of the atmosphere hasn\u2019t changed<\/h3>\n\n\n\n

Figure 5 [from Miskolczi 2010]<\/p>\n\n\n\n

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<\/a><\/a><\/a><\/a>Ferenc Miskolczi was a NASA atmospheric physicist whose 2 papers in 200720<\/sup>\u00a0and 201021<\/sup>\u00a0were 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<\/sup>\u00a0shows 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.\u00a0<\/p>\n\n\n\n

Miskolczi 2007 and 2010 measure \u201cthe true greenhouse-gas optical thickness\u201d [Abstract, Miskolczi 2010]. This is made up of two parts which are depicted in Figure 4.<\/p>\n\n\n\n

a.\u00a0\u00a0\u00a0\u00a0\u00a0\u03c4A\u00a0<\/sub><\/em>—\u00a0\u00a0is defined as \u201cthe total IR flux optical depth\u201d [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.<\/p>\n\n\n\n

b.\u00a0\u00a0\u00a0\u00a0\u00a0A<\/em>\u00a0— 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].<\/p>\n\n\n\n


Together\u00a0\u03c4A<\/sub><\/em>\u00a0and\u00a0A<\/em>\u00a0are 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\u00a0<\/sub>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<\/sub>\u00a0has increased over the 61 years of measurement and increased the optical depth slightly, \u201cvariations in water vapor column amounts\u201d [Figure 11, Miskolczi 2010] have decreased the optical depth by a similar amount. Paltridge et al.23<\/sup>\u00a0have confirmed a decrease in water vapor for this period.\u00a0<\/p>\n\n\n\n

If the optical depth has not increased overall, it suggests the slight warming of the 20th<\/sup>\u00a0C has not been due to an increase in the greenhouse effect.<\/p>\n\n\n\n

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 \u2018Tropical hot spot\u2019 [see section 6].<\/p>\n\n\n\n

5      McShane and Wyner24<\/sup> \u2013 The Hockeystick is broken<\/h3>\n\n\n\n

Figure 6. McShane&Wyner, page 36<\/p>\n\n\n\n

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Blakeley McShane and Abraham Wyner attempted to replicate Michael Mann\u2019s infamous hockeystick using Mann\u2019s own data. The hockeystick first appeared in Mann\u2019s 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 \u201cunprecedented\u201d. The hockeystick is based on dendro-climatic proxies or tree-rings which supposedly provide evidence for past temperatures. <\/p>\n\n\n\n

Mann\u2019s hockeystick shows basically flat temperature until the 20th<\/sup>\u00a0C and then a sudden and rapid increase.Mann\u2019s 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 \u201ctemperature\u201d trend to what thermometers show suggesting those trees don\u2019t make a good or accurate alternative to thermometers.<\/p>\n\n\n\n

McShane &Wyner tried to create the same graph from the same data, but, as Figure 5 above shows, could not. They conclude:<\/p>\n\n\n\n

\u201cUsing 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%.\u201d[page 37]<\/em><\/p>\n\n\n\n

So, even using Mann\u2019s dubious data and employing a variety of statistical methods, McShane & Wyner\u2019s 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\u00a0not<\/em>\u00a0the 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<\/sub>\u00a0was supposedly low.<\/p>\n\n\n\n

The paper correctly describes the importance of the hockeystick not only to global warming but also Green policies:<\/p>\n\n\n\n

\u00a0\u201cthe 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.\u201d [page 2]<\/em><\/p>\n\n\n\n

It would seem the hearts and minds have been won with false promises.<\/p>\n\n\n\n

In recognition of the importance of McShane & Wyner\u2019s paper it was published as an edition discussion piece in\u00a0Annals of Applied Statistics25<\/sup>\u00a0<\/em>As well as\u00a0<\/em>the original paper 15 discussion papers were included in the edition.<\/p>\n\n\n\n

Two salient points emerge from this discussion. The first is noted in McIntyre and McKitrick\u2019s comment where they say:<\/p>\n\n\n\n

McShane & Wyner\u2019s results are, in a sense, a best case as they assume that the quality of the data set is satisfactory [page 4]<\/em><\/p>\n\n\n\n

In fact, as noted, the data was not satisfactory. The significance of this is that the \u2018science\u2019 of the hockeystick is the data; the data is the proxy for the climatic processes which are analysed in McShane & Wyner\u2019s statistical overview.<\/p>\n\n\n\n

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\u2019s statistical justification for the hockeystick. As this stage therefore their view on the hockeystick is definitive.<\/p>\n\n\n\n

6      McKitrick, McIntyre, Herman26<\/sup> – The hot spot is really missing<\/h3>\n\n\n\n

Figure 7. Based on Figures 2 and 3, page 13 of McKitrick et al.<\/p>\n\n\n\n

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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.<\/p>\n\n\n\n

Douglass et al\u00a027<\/sup>\u00a0pointed 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.<\/p>\n\n\n\n

As a result Santer et al [2008]\u00a028<\/sup>\u00a0claimed 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.<\/p>\n\n\n\n

Christy et al [2010]\u00a029<\/sup>\u00a0responded 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\u00a0\u00b10.8 [i.e. the atmosphere should warm 40% faster than the surface]. In reality the observations showed a scaling ratio of\u00a00.8\u00a0\u00b1 0.3\u00a0[i.e. the atmosphere was not warming as fast as the surface].<\/p>\n\n\n\n

McKitrick et al [2010] 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\u00a0higher<\/em>\u00a0and outside the error bars of the weather balloons and satellites measurements [see Figure 7].<\/p>\n\n\n\n

McKitrick et al\u2019s findings have been replicated by Fu et al\u00a030<\/sup>\u00a0who 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\u00a031<\/sup>\u00a0not 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\u00a032<\/sup>\u00a0and 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\u00a0CO2<\/sub>, which would change the optical depth, are not heating in the way predicted by AGW.<\/p>\n\n\n\n

7 Anagnostopoulos, G. G., Koutsoyiannis, D., Christofides, A., Efstratiadis, A. & Mamassis, N. The only thing certain is the models are wrong.<\/strong><\/p>\n\n\n\n

If McKitrick et al shows that the IPCC global computer models can\u2019t model the present and therefore the future, Professor Demetrius Koutsoyiannis and his team show those models can\u2019t even model the past.<\/p>\n\n\n\n

Koutsoyiannis is one of the world\u2019s 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 this uncertainty.<\/p>\n\n\n\n

In his 2008 paper Koutsoyiannis33<\/sup>\u00a0compared 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\u00a0CO2<\/sub>, then the model should be able to match past known data.<\/p>\n\n\n\n

Koutsoyiannis\u2019s 2008 paper has not had a peer reviewed rebuttal but was subject to a critique at Real Climate by Gavin Schmidt.34<\/sup>\u00a0Schmidt\u2019s criticism was 4-fold; that\u00a0Koutsoyiannis uses a regional comparison, few models, real temperatures not anomalies and too short a time period.Each of Schmidt\u2019s 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.<\/p>\n\n\n\n

In 2008 Koutsoyiannis found that while the models had some success with the monthly data all the models were \u201cirrelevant with reality\u201d at the 30 year climate scale.<\/p>\n\n\n\n

Koutsoyiannis\u2019s 201035<\/sup>\u00a0paper \u201cis a continuation and expansion of Koutsoyiannis 2008\u201d. 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.<\/p>\n\n\n\n

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.<\/p>\n\n\n\n

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.<\/p>\n\n\n\n

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Conclusion<\/h1>\n\n\n\n

The global warming models amplify CO2<\/sub>\u2019s effect by 3 \u2013 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\u00a0CO2\u00a0<\/sub>are exaggerated by at least 3C.<\/p>\n\n\n\n

<\/a><\/a><\/a><\/a><\/a><\/a><\/a>Figure 8 Climate Sensitivity Comparison<\/p>\n\n\n\n

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The Hansen36<\/sup>\u00a0point of 1.2\u00baC in Figure 8 is a non-feedback calculation for the temperature increase from a doubling of\u00a0CO2<\/sub>. 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\u00a0CO2<\/sub>.<\/p>\n\n\n\n

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\u00a0CO2<\/sub>\u00a0has already occurred.\u00a0CO2\u00a0<\/sub>atmospheric concentrations have risen approximately 40% since 1900. Any temperature increase due to the increase in\u00a0CO2\u00a0<\/sub>during this period would have already occurred.<\/p>\n\n\n\n

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\u00a0CO2\u00a0<\/sub>temperature response is not delayed. This aspect of climate sensitivity has been independently confirmed in the Beenstock and Reingewertz analysis.37<\/sup>\u00a0Beenstock finds that any effect\u00a0CO2\u00a0<\/sub>increase has on temperature is temporary and not related to the absolute level of\u00a0CO2.<\/sub><\/p>\n\n\n\n

The global warming predictions are contradicted by past, present and future data. Feynman\u2019s maxim applies and the vast funding which is now being directed to \u2018solving\u2019 global warming should be redirected to hypothesis which are consistent with empirical data and confirmed by observable evidence.<\/p>\n\n\n\n

References<\/h1>\n\n\n\n

1.\u00a0\u00a0\u00a0\u00a0\u00a0Cox, Anthony and David Stockwell [2011]. The Drum; [Discussion<\/a>]<\/p>\n\n\n\n

2.\u00a0\u00a0\u00a0\u00a0\u00a0Nova, Jo, Anthony Cox and Anton Lang [2011]. We can lower Australian CO2 emissions by…(wait for it) building new coal plants!, JoNova blog. [Discussion<\/a>]<\/p>\n\n\n\n

3.\u00a0\u00a0\u00a0\u00a0\u00a0Seabrook, Andrea [2007]. Gore Takes Global Warming Message to Congress,\u00a0NPR [Discussion<\/a>]<\/p>\n\n\n\n

4.\u00a0\u00a0\u00a0\u00a0\u00a0Anderegg, William R. L., James W. Prall,\u00a0<\/a>Jacob Harold\u00a0<\/a>and Stephen H. Schneider\u00a0<\/a>[2010]. Expert credibility in climate change, PNAS, 10.1073 [PDF<\/a>]<\/p>\n\n\n\n

5.\u00a0\u00a0\u00a0\u00a0\u00a0Andrews, Timothy and Piers M. Foster. [2008] CO2 Forcing Induces Semi-direct Effects with Consequences for Climate Feedback Interpretations, School of Earth and Environment, University of Leeds [PDF<\/a>]<\/p>\n\n\n\n

6.\u00a0\u00a0\u00a0\u00a0\u00a0Wielicki, Bruce A, Takmeng Wong, Richard P Allan, Anthony Slingo, Heffery T Kiehl, Brian J Soden, C T Gordon, Alvin J Miller, Shi-Keng Yang, David A Randall, Franklin Robertson, Joel Susskind, Herbert Jacobowitz [2002] Evidence for Large Decadal Variability in the Tropical Mean Radiative Energy Budget, Science, Vol 295 no. 5556 pp 841-844, [Abstract<\/a>] [Discussion Watts Up With That<\/a>]<\/p>\n\n\n\n

7.\u00a0\u00a0\u00a0\u00a0\u00a0Lindzen, R. S. and Y.-S. Choi [2009], On the determination of climate feedbacks from ERBE data, Geophys. Res. Lett., 36, L16705, doi:10.1029\/2009GL039628.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0[Abstract<\/a>], [PDF<\/a>] [Discussion<\/a>]<\/p>\n\n\n\n

8.\u00a0\u00a0\u00a0\u00a0\u00a0Lindzen, R. and Yong-Sang Choi, [2011] On the Observational Determination of Climate Sensitivity and Its Implications, Asia-Pacific J. Atmos. Sci., 47(4), 377-390, 2011 [PDF<\/a>]<\/p>\n\n\n\n

9.\u00a0\u00a0\u00a0\u00a0\u00a0Spencer, R.W., W.D. Braswell, J.R. Christy, J. Hnilo, [2007]. Cloud and radiation budget changes associated with tropical intraseasonal oscillations. Geophysical Research Letters, 34, L15707, doi:10.1029\/2007\/GL029698. [PDF<\/a>] [Discussion<\/a>]<\/p>\n\n\n\n

10.\u00a0\u00a0Spencer, R., and W.D. Braswell. [2008]. Potential biases in feedback diagnosis from observations data: a simple model demonstration. Journal of Climate, 21, 5624-5628. [PDF<\/a>]<\/p>\n\n\n\n

11.\u00a0\u00a0Spencer, Roy W. and William D. Braswell [2010], On the diagnosis of radiative feedback in the presence of unknown radiative forcing. Journal of Geophysical research, vol. 115\u00a0D16109,\u00a0doi:10.1029\/2009JD013371,. [PDF<\/a>]<\/p>\n\n\n\n

12.\u00a0\u00a0The Climate Process Team on Low-Latitude Cloud Feedbacks on Climate Sensitivity [cloud CPT], 2011, [Newsletter<\/a>]<\/p>\n\n\n\n

13.\u00a0\u00a0Allan, R [2011] Combining satellite data and models to estimate cloud radiative effects at the surface and in the atmosphere. University of Reading [Abstract<\/a>] [Discussion<\/a>]<\/p>\n\n\n\n

14.\u00a0\u00a0Spencer, R. W.; W.D. Braswell, [2011] On the Misdiagnosis of Climate Feedbacks from Variations in Earth\u2019s Radiant Energy Balance, Remote Sens. 2011, 3, 1603-1613. [PDF<\/a>]<\/p>\n\n\n\n

15.\u00a0\u00a0von Schuckmann, K., F. Gaillard and P.-Y. Le Traon [2009] Global hydrographic variability patterns during 2003-2008. J. Geophys. Res., 114, C09007, doi:10.1029\/2008JC005237 [Abstract<\/a>] [Discussion<\/a>]<\/p>\n\n\n\n

16.\u00a0\u00a0Meehl, Gerald A., Julie M. Arblaster, John T. Fasullo, Aixue Hu and Kevin E. Trenberth [2011] Model-based evidence of deep-ocean heat uptake during surface-temperature hiatus periods. Nature Climate Change doi:10.1038\/nclimate1229 [Letter<\/a>]<\/p>\n\n\n\n

17.\u00a0\u00a0Ablain, M., A. Cazenave, G. Valladeau and S. Guinehut [2009] A new assessment of global mean sea level from altimeters highlights a reduction of global trend from 2005 to 2008: M. Ablain, A. Cazenave, G. Valladeau and S. Guinehut Ocean Sci. Discuss., 6, 31\u201356, [PDF<\/a>]<\/p>\n\n\n\n

18.\u00a0\u00a0Cazenave, A., K. Dominh, S. Guinehut, E. Berthier, W. Llovel, G. Ramillien, M. Ablain, G. Larnicol. Sea level budget over 2003-2008 [2009] A reevaluation from GRACE space gravimetry, satellite altimetry and ARGO: Author manuscript, published in “Global and Planetary Change 65, 1-2 (2009) 83-88”
DOI : 10.1016\/j.gloplacha.2008.10.004 [PDF<\/a>]<\/p>\n\n\n\n

19.\u00a0\u00a0Knox, R. S. and D. H. Douglass [2010] Recent energy balance of Earth: R. S. Knox and D. H. Douglass International Journal of Geosciences, 2010, vol. 1, no. 3 (November) \u2013 In press doi:10.4236\/ijg2010.00000 Published Online 2010 [PDF<\/a>]<\/p>\n\n\n\n

20.\u00a0\u00a0Miskolczi, Ferenc M. [2007] Greenhouse effect in semi-transparent planetary atmospheres. Idojaras Quarterly Journal of the Hungarian Meteorological Service Vol. 111, No. 1, January\u2013March 2007, pp. 1\u201340 [PDF<\/a>]<\/p>\n\n\n\n

21.\u00a0\u00a0Miskolczi, Ferenc M. [2010] The Stable Stationary Value of the Earth\u2019s Global Average Atmospheric Planck-Weighted Greenhouse-Gas Optical Thickness. Energy & Environment Vol. 21, No. 4, 2010 pp 243-263 [PDF and Discussion<\/a>]<\/p>\n\n\n\n

22.\u00a0\u00a0Miskolczi, Ferenc M. and Martin G. Mlynczak [2004] The greenhouse effect and the spectral decomposition of the clear-sky terrestrial radiation. Idojaras Quarterly Journal of the Hungarian Meteorological Service Vol. 108, No. 4, October\u2013December 2004, pp. 209\u2013251 [PDF<\/a>]<\/p>\n\n\n\n

23.\u00a0\u00a0Paltridge, Garth, Albert Arking and Michael Pook [2009] Trends in middle- and upper \u2013level tropospheric humidity from NCEP reanalysis data, Theor Appl Climatol (2009) 98:351\u2013359 DOI 10.1007\/s00704-009-0117-x [PDF<\/a>]<\/p>\n\n\n\n

24.\u00a0\u00a0McShane, Blakely B. and Abraham J. Wyner [2010] A Statistical Analysis of Multiple Temperature Proxies: Are Reconstructions of Surface Temperatures Over the Last 1000 Years Reliable? The Annals of Applied Statistics 2011, Vol. 5, No. 1, 5\u201344 DOI: 10.1214\/10-AOAS398 [PDF<\/a>]<\/p>\n\n\n\n

25.\u00a0\u00a0Watts, Anthony 2010 Watts Up With That [Discussion<\/a>]<\/p>\n\n\n\n

26.\u00a0\u00a0McKitrick, R., S. McIntyre, and C. Herman, [2010], Panel and multivariate methods for tests of trend equivalence in climate data series. Atmospheric Science Letters, 11: 270\u2013277. doi: 10.1002\/asl.290 [PDF<\/a>]<\/p>\n\n\n\n

27.\u00a0\u00a0Douglass, David H., John R. Christy, Benjamin D. Pearson, S. Fred Singer [2007] A Comparison of tropical temperature trends with model predictions, Int. J. Climatol.(2007) Published online in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002\/joc.1651 [PDF<\/a>]<\/p>\n\n\n\n

28.\u00a0\u00a0Santer, B. D., P. W. Thorne, L. Haimberger, K. E Taylor, T. M Wigley,. L. Lanzante, J. R. Solomon, M. Free, P. J Gleckler, P. D. Jones, T. R Karl, S. A. Klein, C. Mears, D. Nychka, G. A. Schmidt, S. C. Sherwood and F. J. Wentz [2008], Consistency of modelled and observed temperature trends in the tropical troposphere. International Journal of Climatology, 28: 1703\u20131722. doi: 10.1002\/joc.1756 [Abstract<\/a>]<\/p>\n\n\n\n

29.\u00a0\u00a0Christy J.R., B. Herman, R. Pielke, Sr., P. Klotzbach, R.T. McNide, J.J. Hnilo, R.W.Spencer, T. Chase, and D.Douglass: (2010), What Do Observational Datasets Say about Modeled Tropospheric Temperature Trends since 1979? Remote Sensing 2010, 2, 2148-2169; doi:10.3390\/rs2092148 [PDF<\/a>]<\/p>\n\n\n\n

30.\u00a0\u00a0Fu, Q; S.Manabe, and C. Johanson [2011], On the warming in the tropical upper troposphere: Models vs observations, Geophysical Research Letters, Vol. 38, L15704, doi:10.1029\/2011GL048101, 2011 [PDF<\/a>] [Discussion<\/a>]<\/p>\n\n\n\n

31.\u00a0\u00a0McKitrick, Ross and Timothy J. Vogelsang [2011], Multivariate trend comparisons between autocorrelated climate series with general trend regressors, Department of Economics, University of Guelph. [Discussion paper PDF<\/a>]<\/p>\n\n\n\n

32.\u00a0\u00a0Stockwell, David R. B. and Anthony Cox, [2009], Structural break models of climatic regime-shifts: claims and forecasts, Cornell University Library, arXiv10907.1650 [2009] [PDF<\/a>]<\/p>\n\n\n\n

33.\u00a0\u00a0Koutsoyiannis, D., N. Mamassis, A. Christofides, A. Efstratiadis, S.M. Papalexiou [2008], Assessment of the reliability of climate predictions based on comparisons with historical time series, European Geosciences Union General Assembly 2008 Vienna, Austria, 13 18 April 2008 Session IS23: Climatic and hydrological perspectives on long term changes [PDF and Presentation<\/a>]<\/p>\n\n\n\n

34.\u00a0\u00a0Real Climate [2008] [Discussion<\/a>]<\/p>\n\n\n\n

35.\u00a0\u00a0Anagnostopoulos, G. G., D. Koutsoyiannis, A. Christofides, A. Efstratiadis, and N. Mamassis, [2010] ‘A comparison of local and aggregated climate model outputs with observed data’, Hydrological Sciences Journal, 55: 7, 1094 \u2014 1110 [PDF]<\/a><\/p>\n\n\n\n

36.\u00a0\u00a0Hansen J., A. Lacis, D. Rind, G. Russell, P. Stone, I. Fung, R. Ruedy and J. Lerner, [1984] Climate sensitivity: Analysis of feedback mechanisms. In Climate Processes and Climate Sensitivity, AGU Geophysical Monograph 29, Maurice Ewing Vol. 5. J.E. Hansen and T. Takahashi, Eds. American Geophysical Union, pp. 130-163 [Abstract with PDF attached<\/a>]<\/p>\n\n\n\n

37.\u00a0\u00a0Beenstock, Michael and Yaniv Reingenertz [2009] Polynomial Cointegration Tests of the Anthropogenic Theory of Global Warming Department of Economics, The Hebrew University, Mount Scopus, Israel. [PDF<\/a>]<\/p>\n\n\n\n

<\/a><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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