Chiefio asks: why does GISS make us see red?

The empty ocean goes infinite hot on a null anomaly

What to make of THIS bizarre anomaly map?

What Have I Done?

I was exploring another example of The Bolivia Effect where an empty area became quite “hot” when the data were missing (Panama, posting soon) and that led to another couple of changed baselines that led to more ‘interesting red’ (1980 vs 1951-1980 baseline). I’m doing these examinations with a 250 km ’spread’ as that tells me more about where the thermometers are located. The above graph, if done instead with a 1200 km spread or smoothing, has the white spread out to sea 1200 km with smaller infinite red blobs in the middles of the oceans.

I thought it would be ‘interesting’ to step through parts of the baseline bit by bit to find out where it was “hot” and “cold”. (Thinking of breaking it into decades…. still to be tried…) When I thought:

Well, you always need a baseline benchmark, even if you are ‘benchmarking the baseline’, so why not start with the “NULL” case of baseline equal to report period? It ought to be a simple all white land area with grey oceans for missing data.

Well, I was “A bit surprised” when I got a blood red ocean everywhere on the planet.

You can try it yourself at the NASA / GISS web site map making page.

In all fairness, the land does stay white (no anomaly against itself) and that’s a very good thing. But that Ocean!

ALL the ocean area with no data goes blood red and the scale shows it to be up to ‘9999′ degrees C of anomaly.

“Houston, I think you have a problem”…

Why Don’t I Look In The Code

Well, the code NASA GISS publishes and says is what they run, is not this code that they are running.

Yes, they are not publishing the real code. In the real code running on the GISS web page to make these anomaly maps, you can change the baseline and you can change the “spread” of each cell. (Thus the web page that lets you make these “what if” anomaly maps). In the code they publish, the “reach” of that spread is hard coded at 1200 km and the baseline period is hard coded at 1951-1980.

So I simply can not do any debugging on this issue, because the code that produces these maps is not available.

But what I can say is pretty simple:

If a map with no areas of unusual warmth (by definition with the baseline = report period) has this happen; something is wrong.

I’d further speculate that that something could easily be what causes The Bolivia Effect where areas that are lacking in current data get rosy red blobs. Just done on a spectacular scale.

Further, I’d speculate that this might go a long way toward explaining the perpetual bright red in the Arctic (where there are no thermometers so no thermometer data). This “anomaly map” includes the HadCRUT SST anomaly map for ocean temperatures. The striking thing about this one is that those two bands of red at each pole sure look a lot like the ‘persistent polar warming’ we’ve been told to be so worried about. One can only wonder if there is some “bleed through” of these hypothetical warm spots when the ‘null data’ cells are averaged in with the ‘real data cells’ when making non-edge case maps. But without the code, it can only be a wonder:

With 250 km ‘spread’ and HadCRUT SST anomalies we get bright red poles

The default 1200 km present date map for comparison:

GIS Anomaly Map for November 2009

I’m surprised nobody ever tried this particular ‘limit case’ before. Then again, experienced software developers know to test the ‘limit cases’ even if they do seem bizarre, since that’s where the most bugs live. And this sure looks like a bug to me.

A very hot bug…