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Thursday, February 18, 2016

Look at the squirrell! Dull deluded deniers moan about a single unused weather station

Sou | 5:15 PM Go to the first of 2 comments. Add a comment
Anthony Watts was sent a bunch of photos from a fan of his, Mark Albright (archived here). If you've been hanging around climate blogs for a few years you might recognise the name. Mark is listed as Research Meteorologist at the University of Washington, and hangs out with Cliff Mass, who flips and flops between acting like a full-on climate science denier and accepting that humans are changing the climate. Mark Albright got himself into the climate spotlight a few years ago, when he did something foolish with snow data. Given his preference for WUWT, and his past antics, I'd say he's just another science denier from the USA.

What Mark found was a poorly sited weather station in a park in Arizona: Picacho 8 SE. So he sent lots of photos to Anthony Watts. Anthony, in turn, for want of anything meaninful to write about, has filled his blog with the photos.

If you read the WUWT fine print, you'll see Anthony wrote this (my emphasis):
Picacho 8 SE is a COOP site, not part of USHCN, but it (along with others) is used as basis for the adjustments to the stations that have not been compromised. 
Okay, so it's not part of USHCN. And Anthony provides no evidence that this particular data has ever been used as the "basis for the adjustments to the stations that have not been compromised". He just makes the claim.

By the way, the official contiguous US national climate data (CONUS) is now US ClimDiv, not USHCN. On the NOAA website, USHCN national data stops at 2012:

Figure 1 | USHCN January to December annual data from 2000 to 2012 Source: NOAA

Whereas the ClimDiv data goes right the way through:

Figure 2 | US ClimDiv January to December annual data from 2000 to 2015 Source: NOAA

As the NOAA website explains:
National USHCN monthly temperature updates have been discontinued. The official CONUS temperature record is now based upon nClimDiv. USHCN data for January 1895 to August 2014 will remain available for historical comparison.



It should also be pointed out that the  Arizona, Picacho 8 SE weather station is not one of the stations used for working out global temperature changes. It's not listed in the 6020 or so list of stations that contribute to the final product for GISTemp.

You can see the raw data at Berkeley Earth, which would make one wonder what all the fuss is about:

Figure 3 | Picacho 8 SE raw monthly data, showing quality control fails. Source: Berkeley Earth

Why the fuss? It's a denier excuse for unsubstantiated denier claims


So what is all the fuss about? Well, Anthony claims that poorly sited stations result in "an inflated temperature trend". He has yet to prove that. In the USA at least, they don't appear to. Here is a chart of monthly temperature anomalies of the pristine US climate reference network with the US ClimDiv network.Click to enlarge as always:

Figure 4 | US CRN and US ClimDiv January to December annual data from 2000 to 2015 Source: NOAA

The two sources are almost indistinguishable. The pristine CRN data set is very slightly below the ClimDiv data back in 2006. However in 2014 and 2015, the larger ClimDiv annual anomaly is slightly cooler than the pristine data set.

That might be why Anthony has to refer to a non-peer-reviewed poster and press release rather than a published paper to make his claim. I'll believe he can get his work published when I see it in a journal. Having got it into the WUWT "record", all Anthony has to do is refer to his own "work" to continue to make his unsubstantiated claim.


An old denier trick


BTW - that's an old trick of deniers. On the very rare occasions that a science denier does bother to link to some so-called "evidence" of something, it's not to evidence at all. The link will take you to a denier blog, which will take you to another denier blog (if you're lucky), which will take you to another denier blog (if you are extra lucky, and inclined to persist). And if you haven't given up at that point, and if you are extremely fortunate, you might find a link to some actual science which will show the complete opposite to the deniers' claims.

Whether or not he is correct that the short record of station 26513, Picacho 8 SE in Arizona is used "as basis for the adjustments to the stations that have not been compromised" I don't know. Anthony doesn't provide any evidence that it is, It's had lots of changes in its short life (click the history links). In the NOAA database it's simply listed as part of the COOP database, not as part of any other database. Compare it with Seligman in Arizona, which is listed as part of the USHCN database.


Old vs new. New south central Arizona computations are cooler!


There's one more chart I found, which compares the old way of computing US data (Drd964x) with the current one (nClimDiv). This is a chart of temperatures for south central Arizona:

Figure 5 | Comparison of old method of computing climate data with the current method, for south central Arizona. Source: NCDC/NOAA
From the above chart the very old temperatures were running way too hot (see point 2 in the quote below), and the most recent temperatures were running a bit too hot, compared to the current method.

NOAA describes the old dataset this way:
Traditionally, climate division values have been computed using the monthly values for all of the Cooperative Observer Network (COOP) stations in each division are averaged to compute divisional monthly temperature and precipitation averages/totals. This is valid for values computed from 1931-2013. For the 1895-1930 period, statewide values were computed directly from stations within each state. Divisional values for this early period were computed using a regression technique against the statewide values (Guttman and Quayle, 1996). These values make up the Drd964x division dataset.

And the current nClimDiv dataset is described as:
The nClimDiv dataset is based on the GHCND dataset using a 5km gridded appoach. It is based on a similar station inventory as the Drd964x dataset however, new methodologies are used to compute temperature, precipitation, and drought for United States climate divisions. These new methodologies include the transition to a grid-based calculation, the inclusion of many more stations from the pre-1930s, and the use of NCEI's modern array of quality control algorithms. These have improved the data coverage and the quality of the dataset, while maintaining the current product stream.
If you go to the webpage and click on the "Current dataset (nClimDiv) tab, you can read more about the specific issues addressed in the newer dataset. For example:
The nClimDiv dataset is designed to address the following general issues inherent in the Drd964x dataset:
  1. For the Drd964x dataset, each divisional value from 1931-2013 is simply the arithmetic average of the station data within it, a computational practice that results in a bias when a division is spatially undersampled in a month (e.g., because some stations did not report) or is climatologically inhomogeneous in general (e.g., due to large variations in topography).
  2. For the Drd964x dataset, all divisional values before 1931 stem from state averages published by the U.S. Department of Agriculture (USDA) rather than from actual station observations, producing an artificial discontinuity in both the mean and variance for 1895-1930 (Guttman and Quayle, 1996).
  3. In the Drd964x dataset, many divisions experienced a systematic change in average station location and elevation during the 20th Century, resulting in spurious historical trends in some regions (Keim et al., 2003; Keim et al., 2005; Allard et al., 2009).
  4. Finally, none of the Drd964x dataset station-based temperature records contain adjustments for historical changes in observation time, station location, or temperature instrumentation, inhomogeneities which further bias temporal trends (Peterson et al., 1998).
The first (and most straightforward) improvement to the nClimDiv dataset involves updating the underlying network of stations, which now includes additional station records and contemporary bias adjustments (i.e., those used in the U.S. Historical Climatology Network version 2; Menne et al., 2009).
There's more on the website.

The short version of the above is that deniers are running out of denier memes so they are reverting to very old and outmoded and wrong ones - "ooh look, a squirrel!"


From the WUWT comments


Anthony Watts' climate conspiracy blog caters for the weird and wacky underworld. It's now inhabited only by utter nutters.

I expect Gordon Jeffrey Giles is referring to the people who put up the weather station at the Picacho Peak State Park:
February 17, 2016 at 9:29 am
Words escape me.
Wait…. IDIOTS comes to mind.

Marcus decides the park managers are in on the climate conspiracy:
February 17, 2016 at 9:42 am
They are not idiots, this is intentional …IMHO.

Marcus reiterates his conspiracy theory again and again (among 15 comments). (What a shame that the conspirators weren't able to get their weather station included in global datasets):
February 17, 2016 at 5:55 pm
…As I have always said, it is intentional, deliberate and has an agenda to fulfill ! 


Eric Slattery (@Technos_Eric) might not know that the weather station data isn't included in the USHCN dataset or in any global data set, and wrote:
February 17, 2016 at 9:32 am
Excellent post Anthony!
Bad data is worse than no data. Especially for this type of investigation where you’re looking at pretty sensitive (to change in outcome/trend) data. It typically leads to wrong conclusions and thinking. See it all the time in Clinical Data……

Bruce Cobb is another regular WUWT conspiracy theorist:
February 17, 2016 at 9:41 am
The more they can pre-cook the data, the less fudging they need to do afterwards. More efficient that way.

wendellwx57 thinks that most meteorologists and climatologists are in on some climate hoax:
February 17, 2016 at 9:45 am
Its time for the National Weather Service to break away from NOAA. I think that they would function better as a scientific organization if they weren’t under NOAA’s control and oversight. Its time for some of the nations meteorologists and climatologists (not all of them have been bought off or are bad) to quit catering to special interest groups, lobbyists, and government payoffs (grants for research) and to play quit playing politics with the weather. I long for the days of integrity and honesty from these folks to return.

CO2isLife wants something like the International Surface Temperature Initiative, or Berkeley Earth, or any of the sources listed on Nick Stokes website, or at realclimate.org or elsewhere. However I doubt he or she would know what to do with the data.
February 17, 2016 at 9:47 am
This is more reason for an Open Source Temperature Data Repository.

ristvan is another wacko climate conspiracy theorist, who wants to throw away data:
February 17, 2016 at 9:54 am
More evidence of NOAA ineptitude. The switch to state by state NClimDiv in 2014 swept in COOP stations such as this, contributing to NOAAs newest ‘official’ Arizona warming. ‘New and improved’ NClimDiv introduced or increased warming in all but 8 states. For CONUS, it increased the decadal warming rate from 0.088F to 0.135F. Another fine ‘sciency’ contribution from warmunist Tom Karl and his merry band of NOAA rogues. 

Resourceguy reckons that the Picacho State Park should have its funding cut because of where the weather station was installed:
February 17, 2016 at 10:24 am
There should be funding cuts associated with ineptitude, or expect more of the same laziness.

Oh, that's enough time wasted. Like I say, the deniers are in the doldrums. As the world heats up, the best they can come up with is a poorly sited weather station that isn't even part of any major climate data set.

2 comments:

Nick Stokes said...

Sou,
I don't think that station is currently used in nClimDiv either (which is a much larger set). The complete inventory of that is here, 294 Mb file, and the most recent month it appears is Feb 2014.

Sou said...

Thanks Nick. I'm not surprised to see that.