Guest essay by John Mauer
One aspect of the science of global warming is the measurement of temperature on a local basis. This is followed by placing the data on a worldwide grid and extrapolating to areas that don’t have data. The local measurement site in the northwest corner of Connecticut is in Falls Village, near the old hydroelectric powerhouse:
The data from that site appears to start in 1916 according to NASA records; it shows intermittent warming of about 0.5 degrees C over the last 100 years. However, NASA recently decided to modify that data in a direct display of political convenience to exaggerate the rate of warming, that is, making the current period appear to show increased warming. What follows is a look at the data record as given on the site for NASA Goddard Institute of Space Studies (GISS), a look at alternate facts.
The temperature data for a given station (site) appears as monthly averages of temperature. The actual data from each measurement (daily?) is not present. The calculation of an annual temperature is specified by GISS. A reasonable summary includes several steps.
Although the data set is not labeled, these measurements are presumably min/max measurements. The monthly numbers include the average of at least 20 measurements of temperature for each month. Then the monthly averages are combined to get a seasonal mean (quarters) starting with December. Then these four quarters are averaged to get an annual mean.
The entire data set is also subjected to composite error correction by calculating the differences of each data point from its monthly mean (the monthly anomaly). Then the seasonal correction is the average of the appropriate monthly corrections and the yearly correction the average of the seasonal corrections. The net of these corrections is added to the average. The result is an annual “temperature” which is a measure of the energy in the atmosphere coupled with any direct radiation impingement.
The plot of 101 years of temperatures in Falls Village is shown above. Although there is routinely a great deal of variation from year to year, several trends can be separated from the plot. A small, but noticeable increase occurs from 1916 through about 1950. Then, the temperature decreases until 1972 with much less volatility. Then, the temperature increases again until roughly 1998 when it holds steady until the present. However, the present volatility is very high.
The El Nino (a change in ocean currents with corresponding atmospheric changes) in 1998 and 2016 is very visible, but not unique in Falls Village. (Please note the Wikipedia editing on the subject of climate change is tightly controlled by a small group of political advocates.)
Sometime in the last few years, just before the Paris Conference on Climate Change, GISS decided to modify the temperature data to account for perceived faults in its representation of atmospheric energy. While the reasons for change are many, the main reason given appeared to be urban sprawl into the measurement sites. They said, “GISS does make an adjustment to deal with potential artifacts associated with urban heat islands, whereby the long-term regional trend derived from rural stations is used instead of the trends from urban centers in the analysis.” Falls Village is a small rural town of approximately 1100 people, mostly farm land.
The plot of all the changes to the raw temperature data from Falls Village is shown above. First, of course, several sections of data are ignored presumably because of some flaw in the collection of data or equipment malfunctions. Second, almost all of the temperatures before 1998 are reduced by 0.6 to 1.2 degrees C which makes the current temperatures look artificially higher. Curiously, this tends to fit the narrative of no pause in global warming that was touted by GISS.
Link: https://data.giss.nasa.gov/cgi-bin/gistemp/stdata_show.cgi?id=425000626580&ds=5&dt=1
Further, if the reasoning of GISS is taken at face value, the apparent temperatures of New York City would be affected. Falls Village (actually the Town of Canaan, Connecticut) is about two hours outside of the City and is part of an expanded weekend community.
http://di2.nu/foia/foia2011/mail/0506.txt
(4) CLIMATE CHANGE SCIENCE: TIME FOR TEAM “B”?
The American Enterprise Institute, 15 February 2005
Anyone with even a basic view of statistics knows that taking averages of averages etc and then trying to derive even more data from that result is a fools errand. Remember the definition of statistics – “an attempt to derive meaning where there is none.” In general the more manipulation done to historical data the more useless it becomes. In other words, the error bar gets so large that ALL the data is useless.
As far as the GISS manipulations go I’d be very surprised if anyone with a statistical background ever reviewed and approved this approach.
I’ve just sampled a few stations in Aus a few times but the mean of half hour readings usually comes out over a degree (C) different (more or less) than the mean of the official min and max (which is usually half a degree or more greater the the highest half hour reading shown because of a short spike). It shows how off the use of the mean of min and max readings of thermometer for a day is for a guess at how the thermal energy of a hundred cubic kilometers of air changes (especially since its not the same air the next day). Homogenizing the data using a method developed for real intensive properties is not real science.
It is not real science but it provides the right answer for the customer funding the research. I find it amazing that despite the immense amount of money being spent based on these over processed observations, nobody has carried out a formal validation of them. I doubt if any of them would even meet basic quality standards. A rather slap dash approach to processing large numbers of data points is forgivable in an undergraduate project with insufficient research, but for multiple government agencies with funding in the multiple millions to not bother to validate and provide result documentation of that testing is very close to malfeasance. Each site should have a ‘quality record’ that provides supportable reasoning for each and every ‘homogenization’ change to data and that change signed off by an accountable person. The original data for that site must be kept as well as the homogenized (invented?) data to allow replication of the claimed to be justified changes.
If an accountant did what NASA/NOAA/Hadley Centre do to meteorological observations, to a company sales figures it would be criminal.
East coast. Pullitzer Price for fiction.
http://www.goodreads.com/book/show/7354.The_Shipping_News
In business you don’t duplicate. Profit margin is too important. Well so are my tax dollars. Trump the businessman is doing what should have been done the very first time another agency got into the temperature business. He is minding my money. About friggin time. I don’t care who does what as much as I care that several tax funded agencies are doing essentially the same $&@ur momisugly#%damn what!