UPDATES: See below
Let us continue our exploration of Fall, et al. the al. being played by Watts, Nielsen Gammon, Jones, Niyogi, Christy and Pielke Sr. Credit where credit is due of course, but Eli thinks that after he drives his combine harvester through their carrot patch they may not be so happy.
To his credit John N-G has been posting a lot on this, describing what he thinks is worthwhile about the paper. Here is how he differentiates between Fall, et al. and Menne, et al.
So Eli being a RTFR kinda bunny asked where the data was, and John pointed. Many thanks, and Eli went and got and extracted the Excel file with the results. Now to be honest, Eli was not looking for what he found, but what he found has implications both for Fall et al, and elsewhere (tho not so much for GISSTEMP). When Eli unzipped the Final List.xls he sorted it by Watts Rank (1-5, with 5 being the worst stations) and by location: Rural, Suburban and Urban.
Then, thanks to Gatesian logic, the Rabett compared the number of stations in each Watts Rank by location and count,
It was an ah choo moment, because clearly rural stations are relatively under-represented in categories 1 and 2, but relatively over represented in the worst three rankings.
The implication of this is that Fall and Co. (and Menne) can and should not simply compare results from categories with each other, but should first look and see how the rural, suburban and urban distributions vary within categories, and indeed they do. Let the bunnies look at this for a couple of categories (gets very Tamino like) starting with Category 2
and Rabett Labs sees pretty much the same thing for the trends in Tmin and Tman, with what looks like two classes of rural stations. This is equally clear in WR3. How about Watts Rank 4?
UPDATE: This was originally switched with Tmax for WR 3. John N-G pointed this out. The asymmetry between the urban and rural remains, but the suburban is more like the rural
UPDATE: Same as for above for WR4
Tmax for WR3
1. Fall, et al. fell off the carrot truck into the harvester because they did not correct for location bias which is a hoot and a half given how Watts and Pielke have gone on for centuries about the UHI, urban heat island effect, but this appears to be the RRE, the rural refrigerator effect.
2. If Eli compares the list of stations GISS uses with those used by Fall, et al., Fall appear to omit some urban and some airport stations although he was too foul to look at what was in the USHCN and what not
3. Without the RRE stations, trends in Tmean, Tmax and Tmin appear to match pretty well within Watts Ranks and across them and for rural, suburban and urban stations (Eyeball Stats).
4. The RRE stations appear to have pretty damn close to zero trends in Tmean, Tmax and Tmin.
5. What differentiates the RRE stations is not clear to Eli. Probably requires digging deep into the metadata.
6. There is at least one paper in there. Please acknowledge Rabett Labs, E. Rabett Prop.
7. If you want a copy of the Excel spreadsheet, put a note in the comments
UPDATE: John N-G points out that for determining a US wide trend proper area weighting has to be used. True enough, but to average something, it helps to average apples, not apples and pears.