[waxman]

This graph actually carries a lot of intellectual weight for 2 reasons:

1) it is an apparently unbiased inquiry, which means a lot. The allegations against leading climate change scientists, whether they are valid or not, highlight an inescapable reality about the world of academic geologists (no matter how "inconvenient" of a truth it is): like many scientists, these people need to raise large amounts of funding for relatively boring projects (i.e. ice samples anyone?). But if they tie in their research to a hot (no pun), visible issue (as rendered by the media and politicians, regardless of its scientific merit), then BAM! It's a lot easier to get funding. Hence, climate scientists have a huge incentive to paint global warming as massive, urgent big problem, whether or not it actually is. Seeing data crunched by an amateur, who has the skills to process it, but not the incentives to skew it, means a lot.

2) Even though it only shows weather data from a single region, "global warming" would presumably be a global phenomenon that one could detect from basically any location (and if this is not the case, then the press needs to revise its doomsday scenarios about global warming necessarily flooding New York City and Shanghai, because if it's only occurring in some places, then we shouldn't use data gathered in Canada to predict catastrophe in East Asia.)

I'm not claiming to know the scientific truth about this issue one way or the other, but I do know that there are a lot of forces at play here besides science (funding incentives, politics, news media sensationalism, green energy business interests, etc.), and I think a return to the data is a great place to start unraveling this issue that is far more complex than Al Gore or his opposite Dick Cheney would have you believe.

[smcq]

That particular visualization wouldn't show an average global temperature increase until after the artic was quite dry.

As the author says, a picture is a story. His story is "at an extremely high level we have seasonal temperature fluctuation."

Your entire second point shows a complete misunderstanding of well, everything.

[ajross]

Item 2 is just wrong. Even something as (comparatively) well understood as an El Niño event causes wilding differing effects from region to region. Every time a scientist goes on TV to explain this stuff, they have to explain this very point: local measurements don't cut it, you have to look at and correlate very complicated global data sets. Apparently you didn't listen becuase of...

Item 1, which seems to me to be a completely unsubstantiated ad hominem. You could use that same argument to reject any science you don't want to hear.

[waxman]

You're incorrectly using the term "ad hominem." An ad hominem argument is when you try to invalidate an idea with an irrelevant personal attack. The problematic incentives facing climate change scientists are certainly relevant to their research. I'm not saying we should dismiss their data necessarily, but I am calling into question their motivations. Would we be skeptical of public health research on smoking funded by a tobacco company? I hope so. But just because they would have strong incentives to produce a particular outcome doesn't mean their science is wrong, but it could very well be biased. Same here.

[jbooth]

The scientific truth of the matter is that last month was the hottest on record: http://af.reuters.com/article/topNews/idAFJOE61O02C20100225

There is room for scientific doubt about whether this is caused by CO2 -- it's a greenhouse gas but correlation != causation and all that.

But if you conclude that the earth isn't actually warming, you're doing it wrong -- there's no doubt about that.

[babar]

1. You assume a (fairly) anonymous, amateur source based on a single data point is more unbiased than someone who has devoted most of their lives to collecting data? I totally agree with the movement to make scientific data more open, but I think you are really underestimating the motivations of most scientists.

2. Extrapolating from a single data set leads to huge biases in interpretation. There are too many uncontrolled variables to say anything meaningful beyond what the temperature in this city has averaged. I think the rate of change that people are worried about in overall temps would probably not even register on this graph clearly.

If you are going to criticize how science is done, you should probably learn more about how it is done.

And some basic statistics.