Satellite Temperatures and El Niño

Bill Illis says:
May 14, 2010 at 5:07 pm “When I run the regressions on the different temperature series over the entire time periods available, I get more-or-less the same response to the ENSO.”
How do you determine which is the dependent variable?
If ENSO causes heat, where does it come from?

It is an obvious FACT that what the Satellite data calls Surface Temperature is not.
Apart form a small area of the west the Northern Hemisphere has had it’s coldest Ground based Temperatures for many years and has broken many records. The Northern Sea temperatures as measured by Argo Bouys do not show the Seas warmer now than in the past 10 years.
Yet dispite all this REAL evidence we still have Satellite Global Surface Temperature Anomalies the highest ever and not only that all the PLUS anomalies are shown in the Northern Hemisphere.
It is definitely a case of 2 (Ground) + 2 (Sea) does not equal 4.

Wren
re “Do you have a specific null hypothesis in mind?”.
Try:
1) Average temperature rate of rise since the last ice age will continue.
2) Average temperature rate of rise, over all data since 1850, will continue.
3) Pacific Decadal Oscillations superimposed on the average temperature trend will continue.
Check out Don Easterbrook’s AGU paper on potential global cooling He projects Pacific Decadal Oscillations (PDO) dominating temperature trends through 2100.

The recurring climate cycles clearly show that natural climatic warming and cooling have occurred many times, long before increases in anthropogenic atmospheric CO2 levels. The Medieval Warm Period and Little Ice Age are well known examples of such climate changes, but in addition, at least 23 periods of climatic warming and cooling have occurred in the past 500 years. Each period of warming or cooling lasted about 25-30 years (average 27 years). Two cycles of global warming and two of global cooling have occurred during the past century, and the global cooling that has occurred since 1998 is exactly in phase with the long term pattern. Global cooling occurred from 1880 to ~1915; global warming occurred from ~1915 to ~1945; global cooling occurred from ~1945-1977;, global warming occurred from 1977 to 1998; and global cooling has occurred since 1998. All of these global climate changes show exceptionally good correlation with solar variation since the Little Ice Age 400 years ago.
The IPCC predicted global warming of 0.6° C (1° F) by 2011 and 1.2° C (2° F) by 2038, whereas Easterbrook (2001) predicted the beginning of global cooling by 2007 (± 3-5 yrs) and cooling of about 0.3-0.5° C until ~2035. The predicted cooling seems to have already begun. Recent measurements of global temperatures suggest a gradual cooling trend since 1998 and 2007-2008 was a year of sharp global cooling. The cooling trend will likely continue as the sun enters a cycle of lower irradiance and the Pacific Ocean changed from its warm mode to its cool mode. . . .
The announcement by NASA that the Pacific Decadal Oscillation (PDO) had shifted to its cool phase is right on schedule as predicted by past climate and PDO changes (Easterbrook, 2001, 2006, 2007) and coincides with recent solar variations. The PDO typically lasts 25-30 years, virtually assuring several decades of global cooling. The IPCC predictions of global temperatures 1° F warmer by 2011, 2° F warmer by 2038, and 10° F by 2100 stand little chance of being correct. “Global warming” (i.e., the warming since 1977) is over! . . .
The good news is that global warming (i.e., the 1977-1998 warming) is over and atmospheric CO2 is not a vital issue. The bad news is that cold conditions kill more people than warm conditions, so we are in for bigger problems than we might have experienced if global warming had continued. Mortality data from 1979-2002 death certificate records show twice as many deaths directly from extreme cold than for deaths from extreme heat, 8 times as many deaths as those from floods, and 30 times as many as from hurricanes. The number of deaths indirectly related to cold is many times worse.

The challenge to AGW is to show significant variations CAUSED BY anthropogenic effects that are significantly different from Easterbrook etc.
Global Warming Models have not included the PDO and other natural cycles. Consequently, they cannot differentiate between natural weather “noise” and anthropogenic causes.
e.g. See Credibility of climate predictions revisited G. G. Anagnostopoulos, D. Koutsoyiannis, A. Efstratiadis, A. Christofides, and N. Mamassis; Department of Water Resources and Environmental Engineering, National Technical University of Athens, (www.itia.ntua.gr)
European Geosciences Union General Assembly 2009, Vienna, Austria, 19‐24 April 2009

The performance of the models at local scale at 55 stations worldwide (in addition to the 8 stations used in Koutsoyiannis et al., 2008) is poor regarding all statistical indicators at the seasonal, annual and climatic time scales. In most cases the observed variability metrics (standard deviation and Hurst coefficient) are underestimated.
• The performance of the models (both the TAR and AR4 ones) at a large spatial scale,
i.e. the contiguous USA, is even worse.
• None of the examined models reproduces the over‐year fluctuations of the areal
temperature of USA (gradual increase before 1940, falling trend until the early 1970’s,
slight upward trend thereafter); most overestimate the annual mean (by up to
4°C) and predict a rise more intense than reality during the later 20th century.
• On the climatic scale, the model whose results for temperature are closest to reality
(PCM‐20C3M) has an efficiency of 0.05, virtually equivalent to an elementary
prediction based on the historical mean; its predictive capacity against other indicators
(e.g. maximum and minimum monthly temperature) is worse.
• The predictive capacity of GCMs against the areal precipitation is even poorer
(overestimation by about 100 to 300 mm). All efficiency values at all time scales are
strongly negative, while correlations vary from negative to slightly positive.
• Contrary to the common practice of climate modellers and IPCC, here comparisons are made in terms of actual values and not departures from means (“anomalies”). The
enormous differences from reality (up to 6°C in minimum temperature and 300 mm in
annual precipitation) would have been concealed if departures from mean had been
taken.
20. Conclusions
Could models, which consistently err by several degrees in the 20th century, be trusted for their future predictions of decadal trends that are much lower than this error?

See further details in their numerous publications.
See also: Validity of Climate Change Forecasting for Public Policy Decision Making
Green, Kesten C, Armstrong, J. Scott and Soon, Willie, 20. February 2009
and International Journal of Forecasting 25 (2009) 826–832

. . .We used the U.K. Met Office Hadley Centre’s annual average thermometer data from 1850 through 2007 to examine the performance of the benchmark method. The accuracy of forecasts from the benchmark is such that even perfect forecasts would be unlikely to help policymakers. For example, mean absolute errors for 20- and 50-year horizons were 0.18°C and 0.24°C. . . . Again using the IPCC warming rate for our demonstration, we projected the rate successively over a period analogous to that envisaged in their scenario of exponential CO2 growth—the years 1851 to 1975. The errors from the projections were more than seven times greater than the errors from the benchmark method. Relative errors were larger for longer forecast horizons. Our validation exercise illustrates the importance of determining whether it is possible to obtain forecasts that are more useful than those from a simple benchmark before making expensive policy decisions. . . .

We look forward to anyone providing counter studies that include these effects and still provide statistically clear evidence for anthropogenic global warming.