Posted on 01/24/2015 12:12:21 PM PST by Ernest_at_the_Beach
It was bound to happen eventually. We could see it coming – a feeding frenzy from “really, it is still getting warmer” to “we told you so: this is proof positive that the science is settled and we will all boil or fry!” The latest numbers are in and they show the “hottest” year since temperature data has become available depending on which data you look at.
The cheerleader this time around seems to have been AP science correspondent Seth Borenstein. Various versions of his essay on the topic have permeated most of America’s newspapers including my own hometown Canadian paper. In his articles, e.g. here and here, he throws enormous numbers at us involving probabilities actually calculated (and checked!) by real statisticians which purport to show that the temperatures are still rising and spiraling out of control:
Nine of the 10 hottest years in NOAA global records have occurred since 2000. The odds of this happening at random are about 650 million to 1, according to University of South Carolina statistician John Grego. Two other statisticians confirmed his calculations.
I was duly impressed by this and other numbers in Seth’s article and asked myself what else of this extremely unlikely nature might one find in the NOAA data. With a little bit of searching I was able to locate an interesting tidbit that they clearly missed. If we wind the clock back to 1945 and look back at the previous temperatures, we notice that they also rose somewhat rapidly and new “hot” records were created. In fact, the graphic below shows that the highest 8 temperatures of the 65 year series to that point in time all belonged to the years 1937 to 1944 Furthermore, in that span of eight years, five of these were each a new record! How unlikely is that?
Using the techniques of the AP statisticians, a simple calculation indicates that the chance of all eight years being the highest is 1 in 5047381560 – almost 9 times as unlikely as what occurred in the most recent years! Not to mention the five records…
By now, most of the readers will be mumbling “Nonsense, all these probabilities are meaningless and irrelevant to real-world temperature series” … and they would be absolutely correct! The above calculations were done under the assumption that the temperatures from any one year are all independent of the temperature for any other year. If that were genuinely the case in the real world, a plot of the NOAA series would look like the gray curve in the plot shown below which was done by randomly re-ordering the actual temperatures (in red) from the NOAA data.
For a variety of physical reasons, measured real-world global temperatures have a strong statistical persistence. They do not jump up and down erratically by large amounts and they are strongly auto-correlated over a considerable period of time due to this property. Annual changes are relatively small and when the series has reached a particular level, it may tend to stay around that level for a period of years. If the initial level is a record high then subsequent levels will also be similarly high even if the cause for the initial warming is reduced or disappears. For that reason, making the assumption that yearly temperatures are “independent” leads to probability calculation results which can bear absolutely no relationship to reality. Mr. Borenstein (along with some of the climate scientists he quoted) was unable to understand this and touted them as having enormous importance. The statisticians would probably have indicated what assumptions they had made to him, but he would very likely not have recognized the impact of those assumptions.
How would I have considered the problem of modelling the behaviour of the temperature series? My starting point would be to first look at the behaviour of the changes from year to year rather than the original temperatures themselves to see what information that might provide.
Plot the annual difference series:
![change-time-series[1]](https://wattsupwiththat.files.wordpress.com/2015/01/change-time-series1.jpeg)
Make a histogram:
Calculate some statistics:
Mean = 0.006 = (Temp_2014 – Temp_1880)/134
Median = 0.015
SD = 0.098
# Positive = 71, # Negative = 59, # Equal to 0 = 4
Autocorrelations: Lag1 = -0.225, Lag2 = -0.196, Lag3 = -0.114, Lag4 = 0.217
The autocorrelations could use some further looking into, however, the plots indicate that it might not be unreasonable to assume that the annual changes are independent of each other and of the initial temperature. Now, one can examine the structure of the waiting time from one record year to the next. This can be done with a Monte Carlo procedure using the observed set of 134 changes as a “population” of values to estimate the probability distribution of that waiting time. In that procedure, we randomly sample the change population (with replacement) and continue until the cumulative total of the selected values is greater than zero for the first time. The number of values selected is the number of years it has taken to set a new record and the total can also tell us the amount by which the record would be broken. This is repeated a very large number of times (in this case, 10000) to complete the estimation process.
The results are interesting. The probability of a new record in the year following a record temperature will obviously be the probability that the change between the two years is positive (71 / 134 = 0.530). A run of three or more consecutive record years would then occur about 28% of the time and a run of four or more about 15% of the time given an initial record year.
The first ten values of the probability distribution of the waiting time for a return to a new record as estimated by the Monte Carlo procedure look like this:
Years Probability
1 …….. 0.520
2 …….. 0.140
3 …….. 0.064
4 …….. 0.039
5 …….. 0.027
6 …….. 0.022
7 …….. 0.016
8 …….. 0.012
9 …….. 0.012
10…….. 0.009
Note the rapid drop in the probabilities. After the occurrence of a global record, the next annual temperature is also reasonably likely to be a record, however when the temperature series drops down, it can often take a very long time for it to return to the record level. The probability that it will take at least 5 years is 0.24, at least 18 years is 0.10 and for 45 years or more it is 0.05. The longest return time in the 10000 trial MC procedure was 1661 years! This is due to the persistence characteristics inherent in the model similar to those of a simple random walk or to a Wiener process. However, unlike these stochastic processes, the temperature changes contain a positive “drift” of about 0.6 degrees per century due to the fact that the mean change is not zero thus guaranteeing a somewhat shorter return time to a new record. A duplication of the same MC analysis using changes taken from a normal distribution with mean equal to zero (i.e. no “warming drift”) and standard deviation equal to that of the observed changes produce results very similar to the one above.
The following graph shows the probabilities that the wait for a new record will be a given number of years or longer.
This shows the distribution of the amount by which the old record would be exceeded:
For a more complete analysis of the situation, one would need to take into account the relationships within the change sequence as well as the possible correlation between the current temperature and the subsequent change to the next year (correlation = -0.116). The latter could be a partial result of the autocorrelation in the changes or an indication of negative feedbacks in the earth system itself.
Despite these caveats, it should be very clear that the probabilities calculated for the propaganda campaign to hype the latest record warming are pure nonsense with no relationship to reality. The behaviour of the global temperature series from NOAA in the 21st century is probabilistically unremarkable and consistent with the persistence characteristics of the temperature record as observed in the previous century. Assertions such as “the warmest x of y years were in the recent past” or “there were z records set” when the temperatures had already reached their pre-2000s starting level as providing evidence of the continuation of previous warming are false and show a lack of understanding of the character of the underlying situation. Any claims of an end to the “hiatus” based on a posited 0.04 C increase (which is smaller than the statistical uncertainty of the measurement process) are merely unscientifically motivated assertions with no substantive support. That these claims also come from some noted climate scientists indicates that their science takes a back seat to their activism and reduces their credibility on other matters as a result.
I might add that this time around I was pleased to see some climate scientists who were willing to publicly question the validity of the propaganda probabilities in social media such as Twitter. As well, the (sometimes reluctant) admissions that the 2014 records of other temperature agencies are in a “statistical tie” with their earlier records seems to be a positive step towards a more honest future discussion of the world of climate science.
The NOAA annual data and monthly data can be downloaded from the linked locations.
Science - any science - is NEVER settled.
Scientific method definition:
The principles and empirical processes of discovery and demonstration considered characteristic of or necessary for scientific investigation, generally involving the observation of phenomena, the formulation of a hypothesis concerning the phenomena, experimentation to demonstrate the truth or falseness of the hypothesis, and a conclusion that validates or modifies the hypothesis.
The “climate change” people have NEVER demonstrated the truth or falseness of their basic hypothesis with reliable collection of measured data applied in a consistent and objective manner. Of course their conclusions are skewed.
I like how they massage the data rather than use the actual information.
When you have to manipulate the data to produce a result you want rather than the actual result, you aren’t engaged in science.
Yep!
Yup.
Gotta double down on the hockey stick!
The left is disingenuous. That is all you need you know.
BLA BLA BLA, we’re all going to die Eventually.
If last year was so hot, why did it take until late June for the last ice bergs to melt on Lake Michigan?
[[“we told you so: this is proof positive that the science is settled and we will all boil or fry!”]]
tHE ‘SCIENTISTS’ ARE CROWING ABOUT this stating snide remarks like “Now we can finally put to rest those ‘non-scientific’ blog sites that claim there hasn’t been any warming for 18 years” and “These unscientific blogs have been reporting propaganda and lies for years now,” etc-
I’d like to ask these ‘scientists’ how just 0.04% of our atmosphere can possibly be causing global climate change (that is the TOTAL Amount of CO2- both natural and man made in our atmosphere- Man’s contribution of CO2 is just 3.4% of that 0.04% which works out to man contributing the ‘shocking’, WHOPPING amount of CO2 to the atmosphere of just 0.0037% 3.4% of 0.04% = 0.0037% or thereabouts)
Of that piddly 0.04% TOTAL AMOSPHERIC CO2, only a tiny insignificant fraction of the earth’s escaping heat gets absorbed and ‘back radiated’ towards earth-
the VAST majority of radiated heat goes right on out into space- meaning that what tiny fraction does actually make it’s way back to earth gets swamped by overwhelming about of cooler temps and the heat gets cooled- there is no way this side of Heck that such a small amount of heat being back radiated can possibly be causing global climate change- only a tiny fraction of the escaping heat, perhaps about 10% makes it’s way back to earth- and only a tiny fraction of escaping heat even gets absorbed by CO2 in the first place because there simply isn’t hardly ANY CO2 in our atmosphere - 0.04% to be exact, and there is no way in heck that man is, in the words of these global warming LIARS, “Almost entirely responsible for global climate change” When man’s contribution of CO2 to the TOTAL Atmospheric Volume is only 0.0037%.
If someone dumps a vial of water into the ocean that is only 0.0037% of the total oceanic volume, will it cause global flooding?
[[The “climate change” people have NEVER demonstrated the truth or falseness of their basic hypothesis]]
Because they KNOWE it is a lie and isn’t supported by either the science OR the math- man is only responsible for just 0.0037% of the Total Volume of the Atmosphere (this is different than the % of total atmospheric
CO2 which I explained in post above)- They KNOW that if they start trotting out the numbers, EVERYONE will discover what LIARS they are
[[The left is disingenuous. That is all you need you know.]]
All you need to know is that this LIE- this scam- IS going to become law and the ‘ne truth’ in the very near future, and we are ALL going pay a heavy heavy price for it while those perpetrating the LIE will become richer than their wildest dreams
Their laws are immaterial to the future. If the choice is freeze to death or obey some stupid Oligarchy law, the Oligarchy will be erradicated over night.
Because they are lying. It was one of the top 5 coldest years since accurate satellite temps have been recorded. That is why they commit fraud by ignoring the sat temps.
What the heck is the “Global Temperature”???
Where is it measured?
Morons! We are on the mercy of Sun, energy coming from sun, sunspot cycles cause fluctuations.
Humans have as much effect on “global temperature” as Obama peeing in the ocean causing global flood.
So what do these lunes want falling mean temps and Global glaciation?
The Mob. Didn't I see a line on that event listed in Vegas? The fix was in.
"And what about those 97% of scientists who agree? Well, what they all agree on is that if their government climate funding goes away, their careers will end."
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