As a scientist, I rely sometimes on models to predict outcomes so that I can measure outcomes against expectations. However, I know enough from the experiments I did and those done by students in lab to know that with great frequency things happen that I did not expect. As I mentioned many times elsewhere and on this blog, I like to look at the data myself, and so when a coworker showed me the real-time data reporting on weather and environmental activity in the atmosphere last fall, I was understandably intrigued. I found the data to be very illuminating and in some cases quite contradictory both to the models as well as the conclusions drawn by others. Since this tool shows real time data on climate, I found a few things very interesting.
The scale isn't intuitive, and in some cases is misleading. Scientists use graphs all the time, but when they use graphs with funny or arbitrary scales, it obfuscates the data to the standard user. When I see a graph, I expect it to start at zero so that I can compare things properly. Not all of the graphs do. When they do, sometimes they use a sliding scale where you see more of the numbers at the bottom than at the top (1,2,3,4,5...) and then near the bottom the space between them expands to change the perspective (15,25,35...), which gives a different impression to those untrained to read the graphs. It's deceptive. It's dishonest. It's pseudoscience. It's COMMON.
Some of the most interesting sources of information are never even really discussed. I noticed some strange behavior in equatorial Africa and in the northern part of Australia, but you won't hear about those places on the news or in reports. You hear about the West, as if that's the only interesting part, but now that we can explore the Heart of Darkness, I think it behooves greater interest as to what's actually happening there, because nobody really knows. Unfortunately, nobody really seems very interested either.
There's simply too much data to analyze, store, and for which to account, even in a model. I doubt very much anyone is capturing all the relevant data, because we probably don't know which pieces of data actually matter. Even if we did, where would we store it, and who would pour over it for the next 30 years of their life? The models cannot include all the data, because it would take too much time to program it, and because we can't provide enough, and the researchers are biased anyway, so the data that makes the cut will probably corroborate the programmer's preconceived bias.
Take a look at it for yourself. Below is a significantly long tutorial (12 minutes) I uploaded tonight to show you what I saw the first time I was able to record it. More will follow, including discussions on Australia, Africa, and the influence of the Sahara on "climate" because that can't be ignored either, no matter what the political agenda.
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