Real Climate Science

I started the day with Anthony Watts sending an E-Mail to an alarmist saying that I am worse than Michael Mann, because I use only raw, untampered  data.

Then Zeke stopped by and said that my objection to using anomalies was for a “different kind of anomaly.” All he wants me to do is to double count (I will explain this in a later post) lost rural station data via infilling and gridding, and lose any possibility of detecting the huge baseline shifts that have occurred.

Then Suarez bared his teeth.

You can’t make this stuff up.

2. Quality control: Continually adjusting a process to compensate for variations in its output. If the variations are within the control limits of a stable system (and all stable systems have variations) then tampering invariably makes things worse. Only a change in the system itself (and not any ad hoc adjustment) can reduce variation and improve quality. Urge to tamper (trying to do ‘one’s best,’ but actually messing around) springs from the naïve desire to do something anything to improve results without sufficiently understanding the system, and ruins an otherwise working process.

What is tampering? definition and meaning

He needs to be banned for life.

Intelligent scientists in legitimate professions understand that when working with large data sets, error distributions tend to be quite random – and the best way to deal with them is to assume that they average out to zero.

This understanding also provides a way to find if the error distribution is skewed, as would occur if there has been selective dropout of rural stations or if the data has been deliberately tampered with.

The approaches of using anomalies, gridding and infilling mask systematic changes to the data, and must be avoided when doing this sort of analysis.

If the data set is legitimate, then random dropout of monthly data or movement of stations will have very little effect. Some stations will get warmer, some will get cooler. Trying to “correct” for this opens the door to confirmation bias – or worse.

The fact that there are systematic adjustments cooling the past and warming the present seen in nearly every state and city, throws up a huge red flag that the adjustments are not legitimate. Why would anyone want to hide this information by using anomalies, gridding and infilling – which would be unnecessary in a legitimate data set anyway?

We know that there is no such thing as a government conspiracy, because the IRS was not targeting conservative groups – and they found lots of WMDs in Iraq.

Watergate did not happen, and that Gulf of Tonkin attack was totally real.

He’s hopelessly stubborn, worse than Mann at being able to admit mistakes IMHO.

Did NASA/NOAA Dramatically Alter U.S. Temperatures After 2000? – Hit & Run : Reason.com

My response ;

Dear Skeptic,

If rural station data is being progressively lost, then infilling and gridding will create a multiplied progressive warming bias. I would highly recommend that you stop doing that.

I am considered a heretic by some on both sides of the global warming debate, because I refuse to tamper with the raw US data.

I have already shown why you can’t detect baseline tampering using anomalies, and thus should not use them. I have also shown how infilling missing data massively biases the US data towards warming over the past 20 years.

Now I am going to show why gridding is unimportant. The graph below shows my ungridded USHCN final averages in blue, and gridded NCDC temperatures in red.

The slope is almost identical, and the offset is probably mainly due to NCDC’s extra co-op stations. Gridding is unimportant for US data, because the stations are fairly evenly spaced, by design.

On the other hand, the data tampering being done by USHCN is huge. People on both sides of the debate should quit focusing on meaningless precision in tampered data, and instead focus on the huge inaccuracy created by tampering.

With large data sets with a random distribution of error (like missing data) real scientists do not attempt to make corrections. As soon as corrections start being made, the door is opened to confirmation bias at best – and it gets worse from there.

Leave the data alone. You are falling for an old NOAA mind trick.

The use of anomalies in calculating temperature data allows NOAA/NASA to shift the baseline years undetected.

The graph below shows how NCDC tampers with the US temperature record, to create a non-existent warming trend.

Here is NCDC’s 1991 version of US temperatures in absolute temperatures.

 www1.ncdc.noaa.gov/pub/data/cmb/bams-sotc/climate-assessment-1981-1990.pdf

The next graph shows the NCDC 1991 version and 2014 version in absolute temperatures. They have cooled the past. This has nothing to do with station loss. It is about altering the data.

Now look what happens if I use temperature anomalies, as some people on both sides of the debate demand. As long as they cool all of the years during a baseline period (in this example 1951-1980 – the one used by NASA) by an approximately equal amount, most of the data tampering during that period is hidden.

The trick NCDC pulls is to stop cooling temperatures after the end of the baseline period. This allows them to create a huge fake warming in recent years, which is largely hidden using anomalies.

By using the anomaly method, the data tampering becomes invisible. Is it the goal to hide the tampering, or do they just not understand what they are doing?

Additionally, it is utterly absurd to believe that station loss since 1990 has selectively targeted warmer stations, and particularly doing so increasingly over time. That is statistically impossible.

Congress got to the bottom of the NASA Challenger scandal by bringing in outside experts from a wide range of disciplines.

With the climate scandal, they take a different approach. They insist that all experts are scandal insiders. Some skeptics have gotten sucked into their peer-review trap, which slows them down and makes them beholden to the very people behind the scam.

America is infested with very dumb people who claim Barack Obama was born in Kenya. And the first one of those birthers was Barack Obama in 1991

Born in Kenya and raised in Indonesia and Hawaii’