Pass 1: How to read the graph

This graph’s basic data are temperature anomaly, not temperature, but difference in observed temperature averaged out over a month, using a baseline of 1961-1990. Global warming was already underway for this period, but it still works as a baseline. Anyway notice the scale shown at the beginning of the presentation.

The Graph shows the temperature anomaly across latitude, using a circle meant to represent the earth, so the north pole is on top, the south pole on the bottom, the equator half way between, etc.

The height of the graph’s bars, as well as their color, show the anomaly, but the beginning of the graphic shows you how far out, in standard deviations, the values are.

The Graphic display starts at 1900. The values are shown for each month, but they are 12 month moving average values, otherwise this graphic would give you a seizure.

So watch the first 20 seconds or so as many times as you need to, to fully understand these details.

Pass 2: It is getting warmer and weirder

On the first pass, just note that as the earth gets warmer, at sea and on land (see the two graphics at the bottom). Notice that the variation from year to year as well as the increase in temperature really takes off in the 1980s. Notice that the surface warmth values increase dramtically starting in the 1990s. Notice that things get really wild over just the last ten years or less.

Pass 3: Ends and middles

On your third pass, and this may take a few passes, notice the difference between the equatorial, temperate, and polar regions, as well as the difference between the two poles.

Consider that the increased warming in arctic regions compared to other regions affects many aspects of our weather.

Consider that the increases in temperate and tropical regions means that over some periods of time an increasingly lager area of the earth becomes uninhabitable without air conditioning.

Notice that the northern and southern hemisphere don’t have the same exact pattern.

What else did you see?

[click on the graphic to get to a larger version]

Just to be clear on how to read the graph … the red dot is not anywhere in particular on the horizontal scale. The X and Y axis simply plot global average temperatures estimated for 1895 to 1933, a series of years that has 1914, a century ago, in the middle of it. This early sequence of data is meant to represent “pre-industrial” temperatures, and here that is compared using the single red to today, positioned correctly on the vertical scale (of temperature). Note, however, that 1895 to 1933 is not really pre-industrial. Human produced greenhouse gases were already being added to the atmosphere by then, though not to the same degree as more recent decades.

You will hear people say that even if 2014 is the warmest year on record, that it is not statistically significantly warmer than the next warmest year. That is absurd. One would have to have a very poor understanding of how statistics works to make such a statement non-ironically. But to make the point even more clear than I might if I explained why that is a dumb thing to say, statistically, I produced this graph which shows that today it is much warmer than it was not so long ago.

ADDED: A question has been raised as to whether or not I chose the proper scale on the Y-axis. I did. My intention was to show variation and average temperatures for several decades near the beginning of the industrial period, centering on 100 years ago, and to put the current year in context of that. This graph does that nicely, with no strangeness about axes other than the carefully explained fact that the clearly labeled 2014 datum is not scaled to the time scale on the bottom. The nature and variation of the entire instrumental curve is readily available and there are dozens of graphs here on this blog and elsewhere that show this (I placed one at the top of the post for your convenience). The point of this graph was to remove the ascending values and obviate the rather absurd question of statistical difference between the highest and second highest ranked years. As explained.

But the Y-axis problem emerges as a more general climate science denial meme (other than, and beyond, the relatively valid and honest question of how to best scale the Y-axis on a graph like this). And in relation to that, I’ve made a NEW ENTRY IN MY FAQ. Please have a look. There are some fun graphs.

Added:

To demonstrate two ways in which people get this wrong. First, an actual scientist type person simply believing (incorrectly) that all scales must start at zero (maybe they do in his field), and second, a climate science denialist actually arguing that the joke graph shown in the tweet is the best way to show global temperature change.

You might have to click on the pic to be able to read it:

It is a major contribution showing the relationship between climate sensitivity and climate change in the future depending on various important factors. The graphic I made from it is here (click on it to get the big giant version):

You’ll notice I left only one sensitivity + aerosol forcing line on it because in my talk I’ll use that as the most likely. Some of you might find it helpful.