This is the 2009 anomaly map measured against the default 1951-1980 benchmark. How much of those colors represent bias from the baseline? How much represent the benchmark period being cold? My suggestion:
So, what we find is that several of the persistent patterns in the anomaly maps seem to be artifacts of the baseline years chosen:
In particular, those persistent Hot Hot Hot Arctic temperatures. Here we can see that there is a consistent warming contributed to the area north of Alaska and the north of Siberia. Gee, Siberia being warm, where have I heard that one before?
In Antarctica, we have both the “Warm Peninsula” and that persistent odd cold patch that keeps showing up.
The warm central Pacific patch looks like it has a precursor as does the warm spot in the middle south of Africa along with Madagascar and the ocean south of it.
In my opinion, many of the persistent “odd” features of the anomaly maps I’ve looked at over the last couple of years can be explained by the peculiarities of the baseline chosen by GISS for their default.
Benchmarking The Baseline
I had set out to measure any bias that might be in the GIStemp “baseline” interval of 1951 to 1980 a couple of days ago and ran into an odd bug (where the world’s oceans turned blood red and GISS stated they were 9999 degrees) that took a day or so to explore. Ok, now it’s time to get back to my original track.
Basically, the question is: To what extent is there evidence that the “baseline” interval has bias in it?
This is not as easy to answer as you might think. Against what do you measure the baseline measurement? Where is your ‘gold standard’ or your ‘platinum meter’ or your ‘caesium clock’ for global temperatures against which to measure your ‘standard’ ?
Ok, we’ll have to ‘make one up’. While it isn’t an ideal choice, the best I can think of for this test is just to use the total temperature history in GIStemp. While we know the start date of 1880 is a bit of a “cherry pick” for warming (the world was warmer in 1720 than in 1880 and was just coming out of the Little Ice Age when GIStemp starts the series) it also includes roughly a full half cycle of temperatures. To use from 1720 to 2009 would put 2 ‘high’ ends in with only one cold middle. So I’ve chosen to use the entire life span of the data.
Even this ‘has issues’ in that the data are geographically sparse in the early years. GIStemp uses what it has to ‘fill in’ some boxes. Part of what we will be seeing is in the ‘unadjusted’ data and part of it is the effect of GIStemp adjustments and fill in. But this is a valid thing to do, since it is what GIStemp does when it makes the maps we look at.
Finally, if we compare the baseline to the whole data, we get one view (what those years looked like) but if we invert that image, by measuring ‘all data’ against the baseline we see how that baseline would contribute to the bias of any given year as compared to the total of all data. That is what was done in the above graph.
OK, So What Does The 1951-1980 Interval vs All Data Look Like?
This is the more normal view. What those 1951-1980 years look like in comparison to All Data. And they do look cold in general, but with a couple of slightly warmish spots.
It all looks a bit cold to me, except for that one really hot spot in Antarctica. Oddly, right next to is a Very Cold Antarctic Peninsula. That cold baseline goes a long way toward explaining the “hot peninsula” stories of the last few decades.
For folks wanting to see if the 1961-1990 baseline used by other temperature series, like HadCrut, has a similar bias, here is that baseline compared to ‘all data’. First for the ‘unadjusted’ data (as used by those other codes) then for the GISS processed version.
This graph is the ‘as re-imagined by GISS’ data:
In it, we see a bit more of the Antarctic (due to GISS adding SCAR data) and again the arctic blues are a bit more enhanced. That same Arctic spot that was deep red for the default GISS interval is now blue. I wonder if that is a flaky station or a place with wide swings of “30 year weather”?
What 2009 vs All Data Looks Like If You Use
the “Unadjusted” Input Data?
For what it’s worth, I was going to make a “2009 vs All Data” map using the ‘unadjusted data’, that GIStemp uses as input, to see how much of the “anomaly” was baseline, how much was GISS processing, and how much was in the “unadjusted” data. But when you try to do that you get this message;
Surface Temperature Analysis: Maps
I cannot construct a plot from your input. GHCN unadjusted plots only available through 1999
So one is left to wonder what they use for GHCN data input if they do not have any “unadjusted” data after 1999. Are the current GISS maps based on “unadjusted” through 1999 and adjusted afterwards? One hopes not. Yet it simply is not known. The documentation says it uses “unadjusted”, but this interface to the actual product being run can’t find it for 2000 – 2009. OK, we have a big “Dig Here!”, but I’m doing other things right now, so this one will need to wait; or fall to someone else to figure out.
The “unadjusted” data file downloaded from NCDC has data through 2009, so what GISS has done to lose those years data in their Anomaly Map product is, er, an open issue…
So the best I can do is this 1951-1980 vs All Data GHCN ‘unadjusted’ graph. (But that leaves me wondering where that 2009 ‘unadjusted’ data came from… )
It looks generally more “muted” than the GISS processed version. This implies to me that a fair degree of what we see in the anomaly maps for today comes directly from how GIStemp processes the “unadjusted” data that it uses to make the baseline period.
The Default 1951-1980 Baseline By Decades
So is there any particular part of that baseline that looks like it “stands out” as not a typical period of time? I’m going to look at it ‘by decades’. Single years probably don’t do that much to bias a 30 year span, and “by decades” ought to show up where there is any issue. Other folks can dig into the individual decades if they wish and see if any particular years are spectacular or not using the GISS web site.
Looks a bit cold to me, but not too bad. Looks like we get our cold Siberia and our cold Antarctic Peninsula from here. Also that cold spot near South American coastal Ecuador looks like it influences the present as well.
Well, quite a bit of cold. That North of Siberia Arctic is “way cold” and likely to provide bias for decades to come.
A continued cold Arctic. OK, looks like a pretty good “cherry pick” (accidental or otherwise) for a very cold time in the Arctic. We also see that ‘hot patch’ in Antarctica. In the other two decades, that patch is NULL, so we now know that this single decade (and perhaps even a subset of it) contributes all that “hot spot” to the baseline and that explains that particular “cool” feature in our present maps vs this baseline.
Scanning back over these three maps, we also see a persistent cold spot in the central / southern area of Africa.
In general, it looks to me like 30 years is just too short a time period to use as a baseline, especially given the sparse data, limited coverage, and data dropouts of those early years. Artifacts of that sparse data and short time period “bleed through” into the present anomaly maps and bias the perception of those maps.
Isn’t That Just Showing The Arctic Has Warmed?
For the inevitable complaint that I’m just showing that the arctic has warmed since 1950, we can look at this graph. This is the period from 1931 to 1940 measured against ‘all data’. It, as you can see, has a very warm Arctic. So at the end of the day I’m left to conclude that a significant part of our present “Hot Arctic” is a result of comparing it to an abnormally cold period in the baseline interval.
For Boballab: 1931 start, 60 years duration
Your wish is my command:
If you open two copies of this page, you can compare this version with the one at the very top of the page. Both are calendar year 2009, but the top one is the default baseline while this is the “boballab” suggested baseline of 1931 for 60 years. (FWIW, I liked the 70 duration graph better, but this one has some interesting features too).
OK, what I noticed is that “baselines matter” in that there is an overall ‘cooling’ of the map. Not dramatic, but hey, if we’re supposed to panic over 10/100 C then I think 5/100 C is significant! (Top map is 0.68 this one is 0.63 in the upper right corner).
Most dramatic is that odd patch to the west of the Antarctic Peninsula. It has entirely changed color. Specifics of baseline matter, especially in places with sparse data. Regional effects DO show up based on the baseline.
Lesser drama, but still very interesting: Africa inland on the side near Madagascar gets a white blob. The cool area in North America stretches slightly further south. Siberia cools off. French Polynesia gets a bit of cooling as does southern Alaska.
It’s like one of those “what’s different in these two pictures” games. Subtile changes, but very real. So: “baseline matters” and longer is better.