Henry’s Pool Tables on Global Warming/Cooling
February 21, 2013 in climate change
henryspooltableNEWa (click to follow link)
referring to my results reported in the tables above:
I took a random sample of weather stations that had daily data. I looked at daily maximum and minimum temperatures and the mean temperature for the day. In this respect random means any place on earth, with a weather station with complete or almost complete daily data, subject to the given sampling procedure decided upon and given in 2) below.
I made sure the sample was globally representative (most data sets aren’t!!!) ……
a) The amount of weather stations taken from the NH must be equal to the amount weather stations taken from the SH
b) The sample must balance by latitude (as close to zero as possible)
c)The sample must also balance 70/30 in or at sea/ inland
d) longitude does not matter, as in the end we are looking at the change in average yearly temps. which includes the effect of seasonal shifts and irradiation + earth rotates once every 24 hours. So balancing on longitude is not required.
e) all continents included (unfortunately I could not get reliable daily data going back 38 years from Antarctica,so there always is this question mark about that, knowing that you never can get a “perfect” sample
f) I made a special provision for months with missing data, not to put in a long term average, as usual in stats, but to rather take the average of that particular month’s preceding year and year after. This is because we are studying the changing weather patterns over time.
As an example here you can see the annual average temperatures for New York JFK:
You can copy and paste the results of the first 4 columns in excel.
Note that in this particular case you will have to go into the months of the years 2002 and 2005 to see in which months data are missing and from there apply the correction as indicated by me + determine the average temperature for 2002 and 2005 from all twelve months of the year.
I determined at all stations the average change in temp. per annum from the average temperature recorded, over the period indicated (least square fits, i.e. the figure reported in the tables is the value before the x).
the end results on the bottom of the first table (on maximum temperatures),
clearly showed a drop in the speed of warming that started around 40 years ago, and continued to drop every other period I looked//…
I did a linear fit, on those 4 results for the drop in the speed of global maximum temps,
ended up with y=0.0016x -0.0281, with r2=0.98
At that stage I was sure to know that I had hooked a fish:
I was at least 95% sure (max) temperatures were falling.
On same maxima data, a polynomial fit, of 2nd order, i.e. a quadratic function gave me,
That is very high, showing a natural relationship, like the trajectory of somebody throwing a ball…
ergo: the final curve for maxima must probably be something like a sine wave fit, with another curve happening, somewhere on the bottom…
Now, I simply cannot be clearer about this. The only bias might have been that I selected stations with complete or near complete daily data. But even that in itself would not affect randomness in my understanding of probability theory.
Either way, you could also compare my results (in the means table) with that of Dr. Spencers, or even that reported by others and you will find same or similar results for the change in the global mean temperature.
The proposed mechanism for AGW implies that more GHG would cause a delay in radiation being able to escape from earth, which then causes a delay in cooling, from earth to space, resulting in a warming effect. It followed naturally, that if more carbon dioxide (CO2) or more water (H2O) or more other GHG’s were to be blamed for extra warming we should see minimum temperatures (minima) rising faster, pushing up the average temperature (means) on earth. I found / you will find that if we take the speed of warming over the longest period (i.e. from 1973/1974) for which we have very reliable records, we find the results of the speed of warming, maxima : means: minima at 0.034 : 0.012 : 0.004 in degrees C/annum. That is ca. 8:3:1. So it was maxima pushing up minima and means and not the other way around. Anyone can duplicate this experiment and check this trend in their own backyard or at the weather station nearest to you. In addition, I find the following trends in minimum temperature records over time: 0.004K/annum (from 1974), 0.007K/annum (from 1980), 0.004K/annum (from 1990) and -0.009K/annum (from 2000). Putting these values out against the time periods indicated, i.e. 40, 34, 24 and 14 years respectively, you get the acceleration/deceleration of warming. I was astonished to find an absolute perfect curve, a quadratic function, with Rsquare=1. That means 100% correlation. If there were any man made warming at all, one would expect to see some chaos in that curve…..(i.e. somewhat less than 100% correlation). Note that the theory of AGW implies rising minimum temperatures, pushing up the mean average temperature. See graph at just below the minima table!
henryspooltableNEWa (click to follow link)