There is a new report on global climate change this week that addresses many of the claims being raised against the theory by critics. Despite the overwhelming agreement of the scientific community, people continue to cite anecdotal observations of cool temperatures to refute predictions. The new report crunches the climate numbers and concludes that there is less than 1 chance in 100,000 that global average temperature over the past 60 years would have been as high without human-caused greenhouse gas emissions.

The research published in Climate Risk Management by Philip Kokica, Steven Crimpc, and Mark Howdend is reportedly the first to quantify the probability of historical changes in global temperatures. They directly address the arguments promulgated by climate change critics:

December 2013 was the 346th consecutive month where global land and ocean average surface temperature exceeded the 20th century monthly average, with February 1985 the last time mean temperature fell below this value. Even given these and other extraordinary statistics, public acceptance of human induced climate change and confidence in the supporting science has declined since 2007. The degree of uncertainty as to whether observed climate changes are due to human activity or are part of natural systems fluctuations remains a major stumbling block to effective adaptation action and risk management. Previous approaches to attribute change include qualitative expert-assessment approaches such as used in IPCC reports and use of ‘fingerprinting’ methods based on global climate models. Here we develop an alternative approach which provides a rigorous probabilistic statistical assessment of the link between observed climate changes and human activities in a way that can inform formal climate risk assessment. We construct and validate a time series model of anomalous global temperatures to June 2010, using rates of greenhouse gas (GHG) emissions, as well as other causal factors including solar radiation, volcanic forcing and the El Niño Southern Oscillation. When the effect of GHGs is removed, bootstrap simulation of the model reveals that there is less than a one in one hundred thousand chance of observing an unbroken sequence of 304 months (our analysis extends to June 2010) with mean surface temperature exceeding the 20th century average. We also show that one would expect a far greater number of short periods of falling global temperatures (as observed since 1998) if climate change was not occurring. This approach to assessing probabilities of human influence on global temperature could be transferred to other climate variables and extremes allowing enhanced formal risk assessment of climate change.

They note that July 2014 was the 353rd consecutive month in which global land and ocean average surface temperature exceeded the 20th-century monthly average. Notably, anyone born after February 1985 has not lived a single month where the global temperature was below the long-term average for that month. Their analysis put the probability of getting the same run of “warmer-than-average months without the human influence was less than 1 chance in 100,000.”

We identified periods of declining temperature by using a moving 10-year window (1950 to 1959, 1951 to 1960, 1952 to 1961, etc.) through the entire 60-year record. We identified 11 such short time periods where global temperatures declined.

Our analysis showed that in the absence of human-caused greenhouse gas emissions, there would have been more than twice as many periods of short-term cooling than are found in the observed data.

It is an interesting paper that I recommend to you. I am obviously already sold on the concept of climate change and strongly disagree with those fighting efforts to control the pollution linked to the change. However, we can have a civil discourse on the subject and I believe that this is a credible report worthy of inclusion in that ongoing debate.