When Secretariat defeated the field in the 1973 Belmont by 25 lengths, even contemporary climate scientists did not dispute that Secretariat ran faster than the other horses. --Steve McIntyre
That Secretariat was a very fast horse is about all you can get universal agreement with climate scientists in the field of metrics. When it comes to measurements of the earth's temperature, which, of course, is their field, the actual data is often tweaked until it agrees with their global warming hypothesis (the exact opposite of how science should be conducted; more on that topic here).
Unfortunately, I have two new examples of climate scientists moving the goalposts from the back of the end zone to the 12-yard line.
Let's begin with a discovery I made over at NASA's climate website.
On April 2, 2013, I wrote a brief post about Dr. Hansen's retirement from NASA. It included a screenshot of Hansen's temperature forecast versus actual earth temperatures to that time (reproduced immediately below):
I was working on a different project yesterday and went back to the NASA original source. Instantly, my eyes registered something was off. That version is below.
So, I asked my artist friend, Karen Ryno, to put the 2013 and 2016 versions (they are supposed to be the same up to 2012, data is added at the end of each year) side by side. It is below.
I suspect they made the January 20, 2016, change because Hansen's 1988 forecast was embarrassingly bad when compared with the actual temperature values. So, they substituted temperature numbers that were more, shall we say, convenient.
I give credit for NASA pointing out their change. If you cannot read the small print at the bottom of the graph above, it says, "Update of Fig. 3(a) in Hansen,
But, is raising the recent temperatures on a graph designed to validate a 1988 forecast scientifically valid? I say, emphatically, no!
Suppose in 1725, a climate scientist said that, due to global cooling, the average high temperature March of the year 1750 in Berlin would be 12°. Let's say it turned out that March, 1750, was extremely warm, compared to the forecast, with an average high of 50°F. The climate scientist making the forecast (given what is apparently ethical in today's climate science) says, Wait a minute, I meant the March, 1750, forecast in degrees Celsius! My forecast of 12° nearly matched the Celsius high of 10°C! [the Celsius temperature scale was invented in 1744].
Here is another example: Suppose you made a Vegas sports book bet on the outcome of a Kansas City Chiefs - Denver Broncos game the day before it was played. Would the sports book allow you to change your wager at the end of the third quarter as the game was in progress? Of course not. A bet (a form of "forecast") is based on what was known to the parties at the time the bet was made.
In order to be valid, temperature forecasts must be compared to the unmodified temperature scale that was being used at the time the forecast was made. Hansen's forecast must be compared to Hansen's temperature data metric (original GISTEMP) from 1988. Of course, that data is no longer produced. Like in the Soviet Union, inconvenient climate data is erased or discontinued. [Side issue, this is why climate realists will not take bets with people like Bill Nye; the metrics get changed over time, always showing recent years to be warmer.]
Here is a second example example of changing goalposts. Over at Climate Audit, the invaluable Steve McIntyre has a case involving comparisons to climate computer models.
The issue in question began over at climate scientist Dr. Judy Curry's blog in a post titled, "Comparing Models with Observations." Judy was asking questions about various climate models and how they performed when compared to earth's actual temperatures when plotted on graphs. Just go over to the green link to see her comments and concerns...I'll wait.
Are you back? Great! As you know, Judy asked this question about the sets of graphs purporting to show the same comparison.
With regards to John Christy’s figure, he is the author of one of the main observational data sets used in the comparison. I don’t know the source of the time series that Gavin provided, but the observations in gavin’s figure vs Christy’s figure do not look similar in terms of time variation. I have no idea how to explain this.
So, Steve McIntyre took up Judy's question and compared the effects of the different baselines used and found that it made a real difference as to how well the climate models fared (short answer: poorly).
One of the figures originally in question is below and its author/original use is Dr. Roy Spencer, here.
Over 95% of the Climate Models Agree: The Observations [green and blue lines] Must Be Wrong is a sarcastic comment about the climate science culture of manipulating temperatures to make them agree with the hypothesis of a rapidly/catastrophically warming earth.
McIntyre demonstrates at his site that by manipulating the "base period" (the solid horizontal line at 0.0 in the graph above) and by changing the averaging technique, it makes the climate forecasts appear better than they actually were. The difference is shown in McIntyre's figure below:
I'd love to be able to tell you this is an exception to the rule in climate 'science' but it is not. Unlike [good] science, in climate science when the data does not agree with the hypothesis, sadly, it is the data that is changed.