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Models get the core assumptions wrong– – the hot spot is missing
Posted By Joanne Nova On May 24, 2012 @ 2:00 am In Global Warming,Student Resouce | Comments Disabled
This is part of a series that Tony Cox and I are doing that references the most important points and papers, as a definitive resource about the evidence. The missing hotspot is not just another flaw in the theory, it proves the models are wrong: not just “unverified”, not just “uncertain”, but failed. Apologies to those who feel I harp on about this! This is a condensed review, squishing years of a scientific battleground down to it’s bare bones… — Jo
It is not well known that even the IPCC agrees that the direct effects of CO2 will only increase world temperatures by 1.2°C. All of the projections above that (3.3°C , 6°C etc) come from model projections based on assumptions of what water vapor and clouds will do (these are the feedback effects of the original 1.2°C).[i] Are the feedbacks correct?
If the IPCC models are right about the feedbacks, we would see a hot spot 10km above the tropics. The theory is that with more heat, more water will evaporate and rise, keeping relative humidity constant at all heights in the troposphere. The point has been conclusively tested with 28 million weather balloons since 1959.[ii]
Figure 7. Based on Figures 2 and 3, page 13 of McKitrick et al.
Douglass et al [v] compared models with observations and officially pointed out the discrepancy in 2007. The paper was rebutted by Santer et al [vi], but the Santer paper did not contain new observations, instead it “found more uncertainties” in model projections and in radiosonde results, which widened the error bars until they overlapped. Santer et al strangely used a truncated dataset, ending in 1999, even though more recent data was available.
McKitrick, McIntyre, Herman[vii] – (2010) used the same datasets, but included newer data, extending the analysis, and used a more sophisticated statistical technique to show that the models all predict warming in the low to mid troposphere, and that their predictions are about 4 times higher and outside the error bars of what the weather balloons and satellites measure. They answered the critics, with corrections in 2011, and the results became even stronger.[viii] All observational trends were now significantly below the average model trend.
Christie et al [ix] also showed the observations didn’t fit the model predictions. They developed the Scaling Ratio – a ratio of the atmospheric trend to the surface trend. This neatly removes the effects of El Nino variations from year to year. They showed that global climate models predict a scaling ratio of 1.4 ±0.8. (i.e. the atmosphere should warm 40% faster than the surface). Instead the scaling ratio for real world data was 0.8 ± 0.3 (i.e. the atmosphere was probably not even warming as fast as the surface.) Fu et al[x] replicated the approach, largely coming to the same conclusion.
Not only are the model predictions exaggerated and feedback assumptions the wrong sign (positive, rather than negative), the small amount of recent warming was likely due to a natural climate shift in 1977 (McKitrick[xi]). This climate shift has been noted by many other researchers (Stockwell[xii] ) and implies man-made global warming is playing an even smaller role then predicted by the models.
The core assumptions of the IPCC favoured models are not supported by empirical measurements.
Miskolczi developed a theoretical explanation for the absence of a tropical hot-spot in 2004, postulating that the production of entropy would already be maximized, therefore, an increase in one greenhouse gas will be matched by a decrease in another (namely water vapor) so that the efficiency of radiation leaving the Earth will not be changed[xiv] ,[xv]. He estimates that the greenhouse effect as shown by the atmospheric optical depth has not changed in 61 years (he used estimations of greenhouse gas concentrations, and radiosonde recordings of temperature and humidity).[xiii] Other studies by Paltridge et al 2009 [xvi] have shown that water vapor levels have dropped as CO2 levels have risen. Miskolczi’s 2010 work has not been challenged to date at a peer-reviewed level.
[v] Douglass, D.H., J.R. Christy, B.D. Pearson, and S.F. Singer. (2007). A comparison of tropical temperature trends with model predictions. International Journal of Climatology, Volume 28, Issue 13, pp. 1693-1701, December 2007. [Abstract] [PDF]
[vi] Santer, 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: 1703–1722. doi: 10.1002/joc.1756 [Abstract] [PDF]
[vii] McKitrick, R., S. McIntyre, and C. Herman, (2010), Panel and multivariate methods for tests of trend equivalence in climate data series. Atmospheric Science Letters, 11: 270–277. doi: 10.1002/asl.290 [PDF] [Discussion on JoNova]
[viii] McKitrick, R., McIntyre, S., and Herman, C. (2011) Corrigendum to Panel and multivariate methods for tests of trend equivalence in climate data series, Atmospheric Science Letters, Vol. 11, Issue 4, 270–277. [Abstract]
[ix] Christy J.R., Herman, B., Pielke, Sr., R, 3, Klotzbach, P., McNide, R.T., Hnilo J.J., Spencer R.W., Chase, T. and Douglass, D: (2010) What Do Observational Datasets Say about Modeled Tropospheric Temperature Trends since 1979? Remote Sensing 2010, 2, 2148-2169; doi:10.3390/rs2092148 [PDF]
[x] Fu, Q, Manabe, S., and Johanson, C. (2011) On the warming in the tropical upper troposphere: Models vs observations, Geophysical Research Letters, Vol. 38, L15704, doi:10.1029/2011GL048101, 2011 [PDF] [Discussion]
[xi] McKitrick, R. and Vogelsang, T. J. (2011), Multivariate trend comparisons between autocorrelated climate series with general trend regressors, Department of Economics, University of Guelph. [ PDF]
[xiii] Miskolczi, Ferenc M. and Mlynczak, M. (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–December 2004, pp. 209–251 [PDF]
[xiv] Miskolczi, Ferenc M. (2007) Greenhouse effect in semi-transparent planetary atmospheres. Idojaras Quarterly Journal of the Hungarian Meteorological Service Vol. 111, No. 1, January–March 2007, pp. 1–40 [PDF]
[xv] Miskolczi, Ferenc M. (2010), The Stable Stationary Value of the Earth’s Global Average Atmospheric Planck-Weighted Greenhouse-Gas Optical Thickness. Energy & Environment Vol. 21, No. 4, 2010 pp 243-263 [PDF and Discussion]
[xvi] Paltridge, G., Arking, A., Pook, M., 2009. Trends in middle- and upper-level tropospheric humidity from NCEP reanalysis data. Theoretical and Applied Climatology, Volume 98, Numbers 3-4, pp. 351-35). [PDF]
PS: Thanks to a generous soul in Adelaide. Another letter is on the way to thank you (your first letter arrived just fine, but my reply appears to have gone missing.) Merci! Cheers, Jo
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