17 Year Global Warming

Katharine Hayhoe is an Associate Professor in the Public Administration program at Texas Tech University and Director of the Climate Science Center at Texas Tech. She is one of the most well-known climate scientists. She is included in the 2014 Time100 as a well-known scientist, and she is a lead author for the 2014 Third U.S. National Climate Assessment. 
Last month, Katherine Hayhoe sent out a tweet saying that other peoples' claim of NO global warming in the past 17 years "is a lie [that] just will not die". She then goes on to to show a graph of 17-year data with a positive slope (increase) of 0.5 to 0.6°C.
Dr. Sierra Rayne holds B.Sc. and Ph.D. degrees in Chemistry and a diploma in water engineering technology. He has authored over 100 peer-reviewed journal articles in chemistry and environmental science, as well as hundreds of technical reports, preprints, and articles for media outlets.
Dr. Rayne has recently taken issue with Dr.Hayhoe's claim that no global warming in the past seven years is a lie. He does this on the basis of statistical analysis of the data. His extensive explanation appears in the July 26 issue of American Thinker (http://www.americanthinker.com/blog/2014/07/rigorous_climate_science_is_now_lying.html).
Dr. Rayne says scientist should start using statistical tests when discussing data in public.  Otherwise, they are not illustrating rigorous science and are simply contributing to a poor understanding of science by the public audience.
To illustrate his point, Dr. Rayne plotted 17 randomly generated numbers. The trend line on the graph was down. If they had been global temperatures, it would have indicated a cooling effect. A second plot with 17 other randomly generated numbers showed a trend line increase (hypothetical global warming). A third plot of randomly generated numbers gave a shallow negative trend line; very slightly down. If three sets of randomly generated numbers can give such different trendlines when plotted, it is apparent that the trendlines from those three sets are not statistically significant. It is also obvious that Dr. Hayhoe's plot of 17 global temperatures is also not statistically significant.
Dr. Rayne goes on to explain that statistical significance is measured as a P value. In his first plot, the P value was 0.10. He says that In science the statistical P value must be 0.05, which is 95% certainty. He also says that in the case of issues such as climate change, whereby action would necessitate a near-complete alteration to our entire socio-economic and political structures and relationships, we should be demanding even higher statistical significance, such as a P value of 0.01 which is a 99% probability of the trend not being a result of chance.
I suppose we can excuse Dr. Hayhoe for her negligence in not considering the statistical significance of the trend line on her graph. I am also a scientist and would not have thought of it, but I have an excuse. I was initially trained in science 70 years ago and never took a course in statistical analysis. However, Dr. Hahoe's more recent training would likely have included statistics. If it did, she decided not to use it. Her error is especially egregious when one considers that she has called the global warming dissenters "liars".

Jerry Brown's False Predictions

The Wall Street Journal reported that California Gov. Jerry Brown had a three-day trade mission to Mexico, during which time he tried to tried to make a connection between global warming and immigration. He is quoted as saying, "“We can see how some are fearful of children walking across the border. What will they think when millions of people are driven north from the parched landscapes of a world degraded by intensifying climate change?”
This is typical of a hack politician like Jerry Brown. He is taking a real situation of illegal immigration at our southern borders and connecting it with a pie-in-the-sky theory of global warming. He has done so, because of the accepted disaster of global warming by many uninformed people, who conform to the Chicken Little Theory that the sky is falling.