OK, I couldn’t Resist
This graph has the monthly trend lines from 1986 to date. Notice in particular how drastic some trends are. Like November, for instance. ( You can click on the graph to get a much larger and readable version).
I can’t help but think that this is something of a “Jumping The Shark” graph. The drastic and extreme change of trends, especially in some months, along with the divergence between months, just looks crazy. Yet that’s what is in the data. There is no adjustment, homogenizing, filling in, UHI adjustment, etc. done by me. This is the straight GHCN “Unadjusted” data set. It is converted to anomalies by having each thermometer compared only to itself, and for each month being compared only to itself. There is no seasonal averaging nor any kind of blending done. Simple, direct “self to self” comparisons for each thermometers in each month.
Compare with the graph of the data prior to 1986. In this graph there is a minor warming of winter months as we rise out of The Little Ice Age, but substantially no warming happening in Summer. A very natural state of affairs.
That is just a crazy change of trend between these two graphs. Notice that I’ve stretched the vertical size of the second graph so that what little divergence there is within those trend lines would be more visible.. This change of trend between the graphs happens well after CO2 has had plenty of time for “effect”, yet could not warm the summers prior to 1986. It looks very non-physical.
I’ve chosen to make this segment break in 1986 for this graph as that is when a lot of the newer “duplicate number” or “modification history” flags first start to show in the data (the older series overlap, then exit with The Great Dying Of Thermometers that starts in 1990 in a big way.)
The nature of these graphs, and how they are made, is discussed in the posting of yesterday, here:
That posting has the graph entire from start to end, along with trend lines for the data as a composite from start to end, so you can compare the two segments with the total by using the graphs in both postings.
I suppose one could try to claim that a 24 year segment was just too short to give a valid trend, but then one would have to explain why a 30 year segment is long enough to define “climate”… and why it’s usable for defining “climate change” but not usable for showing how atypical the present segment of the data looks when presented.
IMHO, these two graphs highlight a significant “brokenness” in the GHCN data series.
Update: This Just In
From Verity Jones I’ve been handed an early peek at a “Pivot Chart” she has started. This is just the first 50 or so lines done, but it shows how the data suddenly change in 1986 or so with the change of the “modification history number” AKA “Duplicate Number”. 50 down, only 6800 to go…
Down the left side are the Station IDs, across is ‘years’. A colored box shows where there is data. If I understand what this says correctly, it is showing “The Splice” where one set of stations lead in, we get a different set (mostly) in the ‘cold period’ from 1951 to about 1980 ish, then a swap is made about 1986-1990 to yet another set.
“A Splice is a terrible thing to waste.”…
Exactly what the change is that happens at that moment in time is yet to be determined.