Northern Hemisphere UHI CRUTem3

This article describes another way to look at the northern hemisphere CRUTem3 data studied by Dr. Roy Spencer in the WUWT article here:

Dr. Spencer identifies a spurious Urban Heat Island (UHI) influence of about 0.13°C per 39 years based on using 3 population density classes out of a possible 5.  He shows that this results in a UHI caused overstatement of the temperature trend by about 15% as he describes in the paragraph below:

The CRUTem3 temperature linear trend is about 15% warmer than the lowest population class temperature trend. But if we extrapolate the results in the first plot above to near-zero population density (0.1 persons per sq. km), we get a 30% overestimate of temperature trends from CRUTem3.

In Spencer’s chart below, he shows about 0.13°C over 39 years or about 0.0033°C per year exaggeration in the CRUTemp3 record caused by UHI:

The chart above shows spurious UHI content of about 0.0033°C per year (chart by Dr. Roy Spencer)

I used a method to remove cyclical signals from the entire dataset.  It is a technique I developed to minimize the least squares error by using a dual signal cyclical and exponential model of the temperatures (or anything else).  You could argue I have too many degrees of freedom to play with when I curve fit it, and you would be right, but the chart below represents a model with the least error that I could generate.  Other combinations work reasonably well too, but have more error than this one.

The section of the NH temperature dataset that Dr. Spencer chose to analyze from 1973 to 2011 is on one of the repeating sawtooth steeper areas of the temperature curve.  1973 was near the bottom of one of the last cooling cycles, right around the time of “the next ice age” scary news stories of the day.  This section of the curve also coincides with the steepest part of the sine components that fit well in my analysis.  So I would argue that this is much steeper than the long term trend and that Dr. Roy’s analysis therefore underestimates UHI.

As I show in the chart below, the section of the curve that Spencer analyzes is increasing at about 0.0163°C per year, of which 0.0033°C is UHI.  On my chart, that is about 20%; he uses 15% as a linear fit.  But the long term trend after removing cyclical items is only 0.0066°C per year.  So the UHI component is 50% of the long term trend (click to enlarge).

Dr. Spencer goes on to say that if more population classes were used, the amount of UHI increases dramatically, but since there are fewer items in each class, the data is statistically less reliable.

The conclusion I am pointing out here is that even without using more classes, I get a UHI contribution 2.5x higher since my divisor (slope) is lower comparing long term versus short term.  Using the paragraph above, if Spencer was able to get from 15% UHI influence to 30% UHI (2x) by extrapolating toward zero population (at 0.1 people per km^2), AND if I can get from 20% to 50% UHI (2.5x) by comparing the short term versus long term, is it possible that UHI in fact accounts for ALL or MORE than 100% of the observed increase in NH CRUTem3 data?

Summary / calculations:

0.0033°C/yr UHI Spencer basis * 2.5 LT.vs.ST * (2x extrapolation to zero population)=0.0165°C/yr.

The long term slope is only 0.0066°C per year, the short term slope is only 0.0163°C/yr.

Has Dr. Spencer found UHI accounting for more than 100% of the total measured increase?  It looks possible.

Now start adding classes which adds another very steep multiplier.  How important is UHI at much more than 100% of total influence?  Probably worth looking into!

Comments welcome.

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Posted by on March 31, 2012 in Climate


Contiguous U.S. Temperature March 1895-2011

March 1910 is the hottest ever in the Contiguous US:

But if you remove the cyclical elements, the trend drops to almost zero: (0.127°F/Century)

h/t to Steve Goddard

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Posted by on March 21, 2012 in Climate


Luling, TX temperature deconstruction

See, the trend IS up.  At 0.04°F per century.  Long cycle at 109 years.

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Posted by on February 17, 2012 in Climate


Envisat Sea Level Deconstruction with 2 Waves

So much for sea level rise.  Going DOWN…

I thought I would have even more fun and try the best fit of two sine waves, trend, and acceleration.  After removing seasonal signals and the 25 year signal, the trend is down slightly, and the acceleration factor is also slightly negative.  The main effect is the Wave2 signal.

If the cycle should continue, you can expect a minimum around 2021 of 0.455mm, about 30mm lower than now.  And once again, I thought I would extend this out a few years and chart it, purely for entertainment purposes.


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Posted by on February 8, 2012 in Climate


UAH Global Temperature Deconstruction as of Dec 2011

UAH Global.  The trend is substantially lower once cyclical component is removed.  Click for larger image.

And for even more fun, another projection to 2100…  Any good alarmist will show something that accelerates, right?  And alarming it is indeed, a whopping 0.8°C.  And before you ask, yes, I’m quite sure the “Accel” parameter is accurate to 9 places  🙂

(quietly removes alarmist hat)

I’ve done dozens of these little exercises, using different techniques and datasets, and they seem to all point to cooling until 2028, ±.  This one says 2025.  But this is a projection, not a prediction, or whatever those guys call it…

UPDATE: I thought I had the January data but didn’t… Here is a chart with it.  Trend drops to 0.41°C per century.


Posted by on February 3, 2012 in Climate


Sea Level Deconstruction

The latest Sea Level data from the University of Colorado

This is a response to Willis Eschenbach’s post at WUWT, .  I thought I would check whether sea level rise is accelerating, or decelerating.  This is pretty easy to test.  I also superimposed the best fit sine wave to capture any longer term cyclical behavior.

I was unable to model anything that would allow best fit using an accelerating parameter on an exponential function.  Deceleration did improve the least squares error, with or without the sine wave.  The factors are shown in the chart below (click to enlarge):

Note that the recent data shows obvious deceleration, as the best fit sine wave and -acceleration factors both show.  Note also that the best fit trend is only 2.24mm/year, well under Hansen’s estimates.  The rest of the total impact is a cyclical element with an amplitude of 7.04mm and a 25.3 year wavelength (of the last cycle at least).  You can see that the residuals are well centered around zero.

And since Hansen is so willing to make projections of things that are NOT in the data, I’m going to take the liberty of doing all those things Willis tells us not to do in the following chart – project these same factors over the next 88 years to 2100:

So there you have it… Declining sea levels until 2019, then rising again to 2033, and pretty much down hill from there.  Hmmm…  If my projection is based on actual data, does that make mine more credible than those a “real” climate scientist?


Update 2013/11/30:


Acceleration is still negative in 2013 after removing the main cyclical component.  Recovery from the 2011 sea level blip cut the acceleration in half.


Update 2014/12/07:  Reader @AGrinstead thinks that more recent data will change the outcome:

AslakGrinstad 2014-12-07 23_07_44-Twitter _ Notifications

He’s right.  More recent data makes the deceleration even more clear than before.

2014-12-07 22_54_47-Microsoft Excel - SineWaveSolver20141207SeaLevel.xls

This drops the date for zero sea level rise by a few decades:

2014-12-07 22_59_54-Microsoft Excel - SineWaveSolver20141207SeaLevel Chart 2.xls


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Posted by on January 30, 2012 in Climate


HadSST2gl Sea Surface Temperature Deconstruction

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Posted by on January 29, 2012 in Climate