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If the facts don’t fit the theory, change the facts! The scientists in charge of the climate satellite data produced by Remote Sensing Services (RSS) in California have decided to adjust their satellite data to increase the warming trend since 2000 and make that data more closely match the surface temperature data that NASA and NOAA have already altered to show that same warming trend.
Researchers from Remote Sensing Systems (RSS), based in California, have released a substantially revised version of their lower tropospheric temperature record. After correcting for problems caused by the decaying orbit of satellites, as well as other factors, they have produced a new record showing 36% faster warming since 1979 and nearly 140% faster (i.e. 2.4 times larger) warming since 1998. This is in comparison to the previous version 3 of the lower tropospheric temperature (TLT) data published in 2009.
How have they done this? They made several changes, the first two of which appear quite questionable. First, they addressed the “time of observation issue.” There is a belief among some climate scientists that the time temperature readings were taken can introduce an error in the long term trends.
To account for changes in observation times, the RSS group used a number of different approaches and models to try and estimate what the temperature would have been if the measurement time remained constant. This involves a combination of satellite observations (when different satellites captured temperatures in both morning and evening), the use of climate models to estimate how temperatures change in the atmosphere over the course of the day, and using reanalysis data that incorporates readings from surface observations, weather balloons and other instruments.
Depending on the time of the observation correction approach chosen, the resulting temperature trends between 1979 and 2016 ranged from as low as 0.13C per decade to as high as 0.22C per decade. The RSS group ultimately decided that the most reasonable set of parameters give a temperature trend of 0.17C. [emphasis mine]
I am puzzled by this, since satellites in orbit do not take readings at one particular time, but at a wide range of times. In fact, I would say that the number of readings, at all different times, would easily introduce enough randomness into the results that any error would be insignificant. Instead, these scientists have decided to adjust the raw data to add a warming trend of almost a tenth of a degree centigrade.
Next, they simply decided that the data coming from some satellites should be excluded.
The RSS group also used the presence of multiple satellites in recent years to test for “odd man out” behaviors, when three or more satellites are available and one differs substantially from the others. They decided not to use NOAA-18 used prior to 2009 because of this. AQUA was also not used after 2009, and NOAA-15 was excluded after 2011. This choice increased the 1979-2016 temperature trend by around 7% compared to leaving in satellites whose readings were identified as anomalous. [emphasis mine]
In other words, some satellites were giving them data that they didn’t like, so they simply decided they wouldn’t use that data.
I should note again that the more data you have, the more likely you will obtain a closer approximation of reality. Just because one satellite seems to be an outlier does not mean it is wrong. It could actually be capturing information that the other satellites are missing. By excluding this data, in order to increase the warming trend by 7%, these scientists are essentially cooking the books.
All of these corrections might be justified, but why should anyone believe them? The changes all move the data in one direction, to prove global warming, which has been the result of every single adjustment made by every single global warming scientist since they began adjusting the raw data about two decades ago. This just seems impossible, and instead suggests confirmation bias: Even if they are entirely sincere (which I increasingly doubt), their commitment to their global warming theories is causing them to adjust things always in the direction that will confirm their theories.
And why am I increasingly skeptical of their sincerity? Well, there is this ridiculous series of doomsday predictions from the global warming community, which is only a small sample of many other similar doomsday predictions. Every few years, beginning in the 1970s, they have told us we only have at most a decade before global warming was going to kill us all. Every single one of these predictions has proved to be laughably false. Even this week they did it again, predicting that we have only until 2020 to stop global warming or we will all be doomed.
I predict that come 2020, when this prediction proves false, the UN and these same climate scientists will suddenly tell us that we only have until 2025 to stop global warming, or we will all be doomed. And then they will do it again in 2030 when the 2025 prediction proves false. And again in 2030. And again in 2035. And again ad infinitum.
My skepticism is further reinforced by the complete predictability of everything these global warming scientists do. For example, in January climate scientist Roy Spencer (the project scientist for an actual climate satellite gathering this very data) made the following prediction about the RSS satellite data and the scientists in charge of it.
I expect there will soon be a revised TLT product from RSS which shows enhanced warming, too. Here’s what I’m predicting:
- 1) neither John Christy nor I will be asked to review the paper
- 2) it will quickly sail through peer review (our UAH V6 paper is still not in print nearly 1 year after submission)
- 3) it will have many authors, including climate model people and the usual model pundits (e.g. Santer), which will supposedly lend legitimacy to the new data adjustments.
Let’s see how many of my 3 predictions come true.
Spencer’s prediction was right on. They have revised their data to show enhanced warming, and done it without any review by scientists who might question their adjustments.
I increasingly despair that none of this can be fixed. In order to regain trust, what must really happen is a wholesale firing of everyone involved in these adjustments. This isn’t because all of them are dishonest, but because there is no way to know one from the other, and the only way anyone can ever trust this data again is for it to be reviewed and released by a completely different set of individuals.
Unfortunately, I simply do not see these wholesale firings happening. The adjustments will continue, the data will get increasingly corrupted, and we will drift farther and farther from really knowing what is going on.