The methodology of the article is peculiar. First, why only analyze the U.S.? Even though the U.S. has more stations than any other single country, its surface area is only 2% that of Earth.
More importantly, why pick only one rural and one urban station from each state? What was the criteria used to pick each state's stations? Was it random? The article does not clarify, so it lends itself to accusations of cherry-picking.
It's fairly easy to verify Long's claims with GHCN Processor. A quick verification takes perhaps 10 minutes if you're familiar with the tool's options.
First, we can get rural and urban temperature anomaly series for the U.S. from the adjusted data, with the following commands, respectively:
ghcnp -include "country eq 'UNITED STATES OF AMERICA' && population_type eq 'R'" -reg -o /tmp/us-rural.csv
ghcnp -include "country eq 'UNITED STATES OF AMERICA' && population_type eq 'U'" -reg -o /tmp/us-urban.csv
GHCN Processor informs us that it processed 867 rural stations, and 117 urban stations. That's plenty more than the article analyzes. Let's take a look at a graph of both series.
This is still consistent with Long's claims. What we want to confirm is whether the rural trend is significantly less steep in the raw unadjusted data. To get rural and urban series from the unadjusted data file, I used the following commands, respectively:
ghcnp -dt mean -include "country eq 'UNITED STATES OF AMERICA' && population_type eq 'R'" -reg -o /tmp/us-rural-raw.csv
ghcnp -dt mean -include "country eq 'UNITED STATES OF AMERICA' && population_type eq 'U'" -reg -o /tmp/us-urban-raw.csv
In this case, the tool informs us that 1046 rural stations have been analyzed, compared to 392 urban stations. A graph of the series follows.
To be thorough, let's also get 12-year running averages of the unadjusted series. That's what the article does.
This graph is very different to Figure 6 from Long's article, and it doesn't support Long's conclusions by any stretch of the imagination. It's also clear that while Long's urban trend is roughly correct, the 48 rural stations he picked are not representative of the 1046 stations GHCN Processor retrieves out of the raw data file. Why they are not representative can only be speculated upon, but I have some ideas.
The divergence between urban and rural stations that exists prior to the reference period (1950 to 1981) might be something that needs to be looked into further, but it's not too surprising. The farther back you go, the fewer the number of stations that report. There's simply more error in older data.
In comments, steven suggests that GHCN v2 population assessments are old and may no longer be applicable. For example, a station might be near a town that used to have less than 10,000 people, and classified as 'R', but then the town grew.
Intuitively, it doesn't seem likely that this would be sufficient to explain away the findings, and it certainly doesn't address Dr. Long's choice of only 48 rural stations in the U.S. But I try to keep an open mind about these types of arguments, within reason.
Fully addressing steven's objection would take substantial work, but we can do the next best thing. Steven indicates that population density is what really matters. Let's take a look at a population density map of the United States (from Wikimedia):
Here's another such map. A portion of the U.S. (basically, the mid-west) has considerably lower population density than the rest of the country. Let's define this low-density region as that bounded by longitudes -95° and -115°, which excludes California. A longitude map of the US can be found here.
A typical rural station in the low-density region should not be as likely to be near an urban area as a rural station in high-density areas of the U.S. Additionally, the population density around the station should be lower for rural stations in the low-density region, in average. Does that make sense?
With GHCN Processor we can easily obtain an unadjusted temperature anomaly series only for rural stations in the low-density region, as follows.
ghcnp -dt mean -include "country eq 'UNITED STATES OF AMERICA' && population_type eq 'R' && longitude < -95 && longitude > -115" -reg -o /tmp/us-really-rural-raw.csv
I've calculated 12-year running averages of the rural low-density series, and plotted it along with the full-rural series.
Things haven't really changed, have they?
There seems to be somewhat of an offset between both station sets, which is interesting to some extent. Apparently, "really rural" stations were warm relative to all rural stations during the baseline period (1950 to 1981.)
BTW, there are 432 "really rural" stations in the unadjusted data file.