This forum is about wrong numbers in science, politics and the media. It respects good science and good English.
The modeler is not worried about the inaccuracy short term of his models. Long term they should be fine...
Yet another reason to wonder if I am stuck in the matrix. A complete loss of rational thought in "scientists".
I downloaded the BEST Quality Controlled data set, imported it and plotted.
chart an overall look at it.
I have run all 40000 stations. Paging through them gives lots of flat temperature profile. Lots of sinusoids. I suspect that if I were to merely reflect the data for each locations data around any arbitrary axis, I will get a reasonable "guess" for what happens in the future.
(In the image above, the darkness of the point ranges from 128 to 0, 0 being black, 128 being half way between black and white. 0 represents the temperature reported by the most stations over the entire range. I.E. the dark band is the temperatures most reported).
1 pixel of width is 1 month.
1 pixel of height is 0.2K
Each data point is 2px x 2px. If I make them smaller than this, it is really hard to see anything.
The decimal notation for dates is the BEST convention.
It is amusing to see the poor prediction of the global warming trend against observation by climate models, particularly as the pro-AGW side is fond of the outrageous assertion that climate change is as certain as gravity, which implies that climate change models are as accurate as celestial mechanics. [Celestial mechanics is based on gravity and is accurate to a substantial number of decimal places].
However there is another validation issue associated with climate computer models, which tends to get covered up, and I think only a few people are aware of it. If you've not heard of this particular issue before Brad, you'll think that you're even more deeply embedded in "The Matrix". It actually relates to something you've raised a number of times in this forum, the idea of anomaly temperature plotting.
When anomaly temperature plotting has been discussed in this forum, it tends to be discussed around JEB's idea of 'chartmanship', or the practice of misleading people through presentational tricks in graph plotting. But there is another reason why the climate science community prefers anomaly temperature plotting, and it may be the main reason they prefer it, is that climate models don't look very good when the output is presented in the non-anomaly temperature form.
The issue is described in this post in 2009 from "The Blackboard" blog:
Basically, model simulations don't match the average temperature of the Earth very well, and can be up to a few deg C out. The discrepancy seems to be higher than the few tenths of a degree that they expected the world to be very nervous about. The climate modellers presumably are treating this discrepancy as being some sort of 'systematic error' which doesn't change with time. But if this error varies with time, rather like a 'baseline drift', it might even be part of their claimed warming trend. According to the blogger, Lucia, the issue is covered up by modellers in presentational material because it is regarded as too 'confusing'.
I can't imagine a person doing validation work in industry on some computer program which predicts temperatures covering up the fact that the observed target temperature isn't well predicted.
On the subject of validation of climate models, I noticed an interesting post on the "Climate Skeptic" blog a few days ago, which updates a simple model originally devised in 2007 for reproducing the global average temperature anomaly since 1870:
My guess at the background to this is that in the mid-00s, the AGWers were keen on a line of argument that as complex climate models could 'postdict' the past, they must be able to predict the future. There was a BBC documentary in 2006 which featured a presenter called Paul Rose (I think the documentary, for anybody interested, was this one: http://docuwiki.net/index.php?title=Meltdown:_A_Global_Warming_Journey ), where Rose was initially portrayed as a sceptic, but after talking to various experts was converted to the cause, and was particularly convinced by climate models being able to produce a fairly good match to historical temperature data. In response to this line of argument some AGW sceptic bloggers pointed out that they could get good matches to historical data using much simpler approaches, and at no expense to the public.
The Climate Skeptic blog model is actually showing pretty good predictive behaviour for the six years following on from 2007, up to mid-2013, and is outperforming the 'professional' climate models. The model predicts that global cooling will occur over the next twenty years.