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SciTech Birth Day: February 11
SciTech Impact Areas
01. Climate Change
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35. Dark Matters
36. Cosmology
37. Energy Storage
38. Virtual/Augmented Reality
39. Space Exploration
40. Impact Event
02. Alternative Energy
03. Computer Power
04. Nanotechnology
05. Stem Cells
06. Communications
07. Hydrocarbon Use
08. Clean Transportation
09. Online Information
10. DNA Decoding
11. Cell Biology
12. Photonics
13. Proteomics
14. Quantum Physics
15. Genetic Modification
16. Degrading Oceans
17. Robotics
18. Nanomedicine
19. Neuroscience
20. Extending Lifespan
21. Overpopulation
22. Scientific Instruments
23. Synthetic Biology
24. Nuclear Physics
25. Artificial Intelligence
26. Body Implants
27. Major Disease Cures
28. Water Shortage
29. Species Loss
30. Brain Enhancement
31. Origin of Life
32. Sensor Technology
33. Pandemics
34. Exogenous Life
35. Dark Matters
36. Cosmology
37. Energy Storage
38. Virtual/Augmented Reality
39. Space Exploration
40. Impact Event
Impact Areas listed in order of ranking

Doubling down on climate change prediction
For many years, decades really, climatologists, meteorologists, ecologists and other scientists have labored to produce hundreds of reports, studies, books that detail their own field’s view of what’s happening to the Earth’s climate. Thousands of scientists, several decades of work, googolplexes of data, unending discussion and debate – in the end, however, a rather simple consensus: Greenhouse gas levels in the atmosphere are rising, among them man-made CO2, and with them the Earth’s average yearly temperature is rising. It’s called, of course, global warming, and to some extent man-made (anthropocentric) global warming (AGW).
Apparently the consensus hasn’t been enough.
In a few short weeks, since the boneless conference in Copenhagen in January, it seems like the mood for doing something about climate change is turning sour. It isn’t a monumental PR flop, quite yet; but the questionable scientific behavior surrounding “e-mailGate” and “glacierGate” added to the heavily subsidized attacks on science and scientists, have made doubts and ducking responsibility almost respectable. Certainly this is true in the United States and Britain, probably less so but growing elsewhere. Besides, if you’re a policy maker, it’s obviously less expensive and safer (politically) to do nothing now. Anyway, the scientists could be wrong.
Of course the scientists could be wrong. As most people know, forecasting the weather is difficult. Forecasting climate is even more difficult. Forecasting major changes in climate in increments of decades…well, that’s really difficult. That’s why climate scientists and those whose fields are directly involved, look at the decades of data, debate and spar over details, check and recheck their assumptions and almost all of them draw the same conclusion: global warming is happening and carbon dioxide of human creation is a key component. No matter. The public is not ‘getting it.’ Soon, if they haven’t already (like the craven cave-dwellers in the U.S. Congress) the politicians will not ‘get it.’
What’s a climate scientist to do? They can’t hand the public and politicians anything like 100% certainty. They know there will always be a margin for error. There will be disagreements among scientists. There will be screw-ups, and woefully, false data. There can always be discoveries that change the whole conclusion about global warming. Heck, one not so fine morning the Sun may not come up (unforeseen dynamics in the Sun’s fusion process, and it just goes poof); but not bloody likely. So, what are climate scientists to do?
Why, double down, of course. That’s the gamblers’ expression: If you’re losing big, double your bet and go for the big win. In blackjack, you do this if the odds (from the first two cards) are in your favor. In the global warming PR game (and this part of it is a game), it means scientists should take the models they use now for predicting the course of global warming – and make them bigger, better, and more comprehensive.
Alternative futures for a warming world
Got that? Especially the part about RCPs? It means that not only will these climate models, for the first time really, include feed-back from what is actually happening in the climate, but also the effects of human decision making. The new models should not only include new types of information, but the predictions they produce should be much more fine-grained to include the impact of global warming on natural resources, human health, coastal infrastructure, ecosystems and other sectors. Finally, the new approach means that the models will provide a framework in which scientists can perform their research…(unstated) so it can have the most bang for the buck. In short, make predictions that will influence policy makers to do something.
I suppose many scientists thought that’s what they’ve been doing all along.
Is there a risk this is going to generate more scenarios for people not to believe in?
Other scientist will immediately bristle and say “We got into trouble by trying to stack the data for the best argument. This is just increasing the risk.”
More risk, more visibility, and bigger stakes: If this doesn’t all add up to doubling down on the science, what does?