For the entire month of January we heard it -- the exceptionally cold temperatures in the Northeast and South proved that global warming is a hoax.
My answer (see previous post below) and every good scientist's answer to that nonsense was the same: Wait for the data. What you see outside your window is one data point for one day. Wait until the end of the month and year and see if the impressions bear out.
The facts are in now, and they show clearly that there was no significant drop in temperatures in the U.S. over the month of January. In fact, even in some cities that thought they were unseasonably cold, it turns out that the temperatures were near normal. The national average temperature was only 0.1℉ below normal, 30.3℉ instead of the normal 30.4℉. In fact, the more significant statistic is that January's rainfall was .9 inches below average, making it the fifth driest January on record -- an observation that goes along with climate change models, rather than against them.
Say what? That can't be possible, you may say. Don't you remember the blizzards, the ice storms, the closed airports? Impossible!
No, possible -- and the truth. Because while the East Coast and South endured unseasonably low temperatures and some increase in precipitation, in the West the temperatures were above normal and very, very dry. The above normal temperatures in the West made up for the Eastern lows, and what we got was a very slight (0.1 degree) drop below historic averages.
The data is in. And it says there was no record cooling in the U.S. last month. Sorry, naysayers.
Remember what an average is. An average takes into account all measurements, not just the ones outside our windows. And this is crucial to understanding climate change, because climatologists are not saying the temperature of the planet will rise every single day, every single place. What they are saying is that the average temperature will rise. January's observations are consistent with that prediction.
It is worth going into this a little more deeply. In general, an average, or more precisely, a statistical mean is the number that is in the middle of any set of measurements. (Technically the middle number in a set of data is called the median, but in most randomly distributed systems the mean and the median turn out to be close to the same thing, so we can be a little loose in our talk and say "the average" when we mean "the statistical median." Ok, enough shop talk.)
For example, if a basketball player has an average score of 15 points per game, that means half the time he will score above 15 points, and half the time he will score below 15. In the same way, if the climate is warming, we expect the average global temperature to gradually rise over time, but that still means monthly averages should fall below the historic mean fairly often, and probably close to half the time. (Unlike with the basketball player, however, it will be slightly less than half the time. In order for the average temperature to rise, new temperatures must hit above the average more times than not.)
Thus, months like January should happen sometimes, and are expected under the climate change model.