And we can. The chart below shows the statewide average annual temperature since 1895, overlaid with a linear trend line. The increase is only about a degree, but it's quite clear.
(Click for larger chart)
Now, folks who don't believe in global warming will probably look at the chart above and say it doesn't prove anything. That the relatively small increase it shows could be due to the "heat island" effect, bad temperature stations, the sun, or perhaps even astrology, as the rather conservative South Dakota legislature seems to believe. But, with the exception of astrology, we have enough data to examine those possibilities. Climate models predict that human-caused temperature increases in Wisconsin should be seen mostly in the winter, but biased temperature measurements or changes in solar output should affect all four seasons more or less equally. As you can see from the next chart, almost all the warming in Wisconsin has indeed occurred during the winter, exactly as one would expect from anthropomorphic global warming.
(Click for larger chart)
While a one-degree increase in average yearly Wisconsin temperature over a hundred years isn't much, the three-degree winter increase, which has occurred mostly in the past thirty years, is a significant and noticeable change!
So, is this the final nail in the coffin of Wisconsin global warming deniers? Unfortunately, no. Their beliefs are based on ideology, not science or data. No amount of evidence will change their minds because they simply ignore or distort anything that doesn't fit their preconceived notions.
The data I used in the charts came from the Wisconsin State Climatology Office. It's a great resource for looking at local climate issues and concerns.
2 comments:
"The increase is only about a degree, but it's quite clear."
I disagree, that could easily be a linear trend given the large fluctuations in temperature. Also, what are the error bars on that graph. A 2 sigma error bar would likely swamp any signal that you might think is there.
This further begs the question of why you use a linear fit at all. The graph clearly is non-linear. The chi square must be huge. Try a periodic function next time.
I don't disagree with your points, but they're rather meaningless to the vast majority of readers. Even someone with a limited mathematical background can look at the data, see the trends, and understand how I derived them. That's my goal.
Some additional points: The Wisconsin data is consistent with the rest of Midwest. The same general patterns hold. Check it yourself. While using a larger geographical data set would yield more statistical significance, I was writing about Wisconsin, so I just used Wisconsin data.
Had the Wisconsin data been anomalous, I wouldn't have written this post. Had my admittedly simplistic analysis not matched both the broader trends and the climate models, I wouldn't have written this post. But everything is consistent, and my post accurately states the trends, even if they aren't derived as rigorously as perhaps we would prefer.
Sometimes simple is better...
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