Guest Post by Willis Eschenbach
[See Addendum at the bottom.] [See Second Addendum at the bottom]
I got to thinking about the distribution of the so-called “global” warming. I’d heard that a good chunk of it was due to increasing nighttime minimum temperatures. So I grabbed the Berkeley Earth land-only temperature dataset. It has its problems, and I suspect the overall warming trend is exaggerated, but at least it is internally complete and consistent. I wanted to know both where and when the warming is strongest, and where and when it is weakest. I used the post-1900 data because prior to that the error bars get pretty wide, but the choice of starting point doesn’t make much difference.
For my first subdivision in time and space, I looked at the daytime maximum and the nighttime minimum temperatures by hemisphere. Figure 1 shows the result:
This shows that as a hemispheric average, the nighttime minimum temperatures are rising faster than the daytime maximums, and that the northern hemisphere nights are warming the fastest of the four groups.
(I note in passing that while both the northern and southern hemisphere daytime temperatures dropped strongly from about 1945 to 1975, the corresponding drop in the nighttime temperatures is nowhere near as large. No idea why … always more questions than answers, gotta love that, but I digress …)
However, that wasn’t quite what I was looking for. I wanted to know more details about exactly where and when the warming was going on. So I made a couple of movies. Since the fastest warming is in the night-time, here are the century-plus nighttime minimum temperature trends, on a 1°x1° gridcell basis:
This is what I was looking for, the details of the location and timing of the warming. The Northern Hemisphere nighttime temperatures are increasing the most during the winter in Siberia and Canada. And similarly, in the Southern Hemisphere the nighttime warming is greatest in the winter, although it is more evenly distributed spatially. Meanwhile, there is little trend change month-over-month in the tropics.
Now, call me crazy, but I don’t recall anyone ever saying “Boy, I sure wish that the February nights in the Yukon were colder” …
What about the daytime maximum temperatures? Figure 3 below shows the days:
Curiously, or perhaps not curiously, this daytime view shows the same pattern as the nighttime temperatures. The warming is concentrated in the extratropics in the winter.
Conclusions? Well, the most obvious conclusion is that the “global” warming is not global at all. Instead, it is strongest at night in the winter in Siberia and Canada. I’m pretty sure the poor people in Murmansk are not complaining about that …
In addition, there are large regions of the earth where for one or more months of the year, over more than a century the temperatures have actually cooled … the entire southeastern US, for example, is now colder in January than it was a century ago, both during the day and at night. If nothing else, this highlights the complex nature of the climate.
That’s what I see so far, but there’s much more to learn in the movies …
Clear weather today. I’m off to build an outdoor viewing tower so our cat can survey its domain … got to take my shirt off and saw up some wood in the sunshine, we melanin-deficient folks need to get our Vitamin D.
Best wishes to you all, whether you are in sunshine or rain,
Addendum: I was accused in the comments of suffering from hypo-Europhilia, as evidenced by my Pacific-centered movies. Hey, I’m a tropical South Pacific boy, guilty as charged, so here’s the new movie:
Second Addendum: A commenter asked how well the climate models do at reproducing the patterns shown above. Here are a comparison of four different months (Feb, May, Aug, Nov) of one single GISS-E2-R model run from the KNMI dataset:
I don’t find the agreement particularly compelling, but YMMV.
Data: I got the Berkeley Earth temperature data from the marvelous KNMI site. Click the link entitled e.g. “1833-now: Berkeley 1°” and look down at the bottom of the resulting page for the gridded NetCDF dataset.
PS: I am reliably informed that it is no longer politically correct to refer to so-called “white” people as being “melanin-deficient”, as it implies that something is wrong with them. The new politically approved term is “melanin-challenged”.
My Usual Request: If you disagree with me or anyone, please quote the exact words you disagree with. I can defend my own words. I cannot defend someone else’s interpretation of my words.
My Other Request: If you think that e.g. I’m using the wrong method on the wrong dataset, please educate me and others by demonstrating the proper use of the right method on the right dataset. Simply claiming I’m wrong doesn’t advance the discussion.