Monday, August 1, 2022

Claim: A new bombshell report found that 96% of ConUS NOAA temperature is corrupted (false)

Anthony Watts has a new report on US temperature stations. He had 2 pinned posts - the announcement here and a 1hr Heartland video presentation here. The subheading to the announcement reads:

"Official NOAA temperature stations produce corrupted data due to purposeful placement in man-made hot spots
Nationwide study follows up widespread corruption and heat biases found at NOAA stations in 2009, and the heat-bias distortion problem is even worse now"

Dramatic stuff. As Victor Venema pointed out, it is the tenth anniversary of another dramatic announcement, when Anthony said he was suspending everything to rush out a paper on the bad siting of stations. The paper still has not appeared.

In this post, I'll comment briefly on the report, but mainly will discuss the more complete refutation, which is that the resulting ClimDiv US average is very close indeed to that derived from the independent purpose-built network USCRN.

The report.

It is mainly taken up with photos of various sites that WUWT observers found fault with. But the bare statistics are that they looked at 128 stations, out of a total of well over 10,000 that are currently being used, and found 5 that they deemed satisfactory. That gave rise to the headline claim "MEDIA ADVISORY: 96% OF U.S. CLIMATE DATA IS CORRUPTED".

The report is a sequel to an earlier similar study in 2009 which has been fairly central to WUWT's operations. But, aside from the question of whether the stations sighted were really as bad as they claim, there is a further question of whether they are representative. On the face of it, no. The earlier report was in the days of USHCN (pre-ClimDiv), which was a set of 1218 stations from which the national average was derived. This time, 80 of the sample were from that set, leaving only 48 from the remaining 10000+ stations. That might not be so bad, were it not that there is a history, much discussed in the report, of those stations in the earlier report. There is plenty of scope for that to be a biased sample, and there is nothing in the report to show how bias was avoided. However, this is not the main reason for doubting the report.

Comparison with USCRN

USCRN is a network since about 2005 which has about 115 stations in the continental US (conUS) built in an array intended to be representative for the region, including an avoidance of urban activity. WUWT generally thinks well of this (as do we all). The announcement said:
"“By contrast, NOAA operates a state-of-the-art surface temperature network called the U.S. Climate Reference Network,” Watts said. “It is free of localized heat biases by design, but the data it produces is never mentioned in monthly or yearly climate reports published by NOAA for public consumption."

Given that fondness, it was natural that people should ask how ClimDiv, from the supposedly corrupted stations, compared with USCRN. Well, that is interesting. There is a very close match, as the NOAA Temperature Index page shows:

You can see little bits of blue (ClimDiv) peeping out from behind the USCRN, but mostly they totally run together. This may be a bit clearer with the annual data:

Now this comparison is not made anywhere in the report or associated writings. The monthly plot is even featured on the front page (right panel) of WUWT, but the ClimDiv part has been removed.

What is hinted in the report is that the correspondence was achieved by unstated adjustments. Here is Anthony's response to my posting the plot:

"They use the USCRN data to ADJUST nClimDiv data to closely match. And there is only 17 years of it, which means the past century of data is still as useless and corrupted as ever."

The rest of this post is mainly discussing that. No evidence is given, of course, and it's wrong. But it's also absurd. The heading quoted above says that NOAA is deliberately biasing the stations to inflate warming, and yet, the explanation goes, after all that they throw out that effort and adjust to the USCRN.

As for the 17 years, the survey itself was in 2022. It tells about current conditions, and if they are so bad, it is now that they bad results should be appearing. Faults of more than 17 years ago will not be illuminated by scrutinising current stations.

Is the averaging process adjusted?

I do my own calculations here. I described two years ago how I used the monthly average station data provided by both USCRN and GHCN (proxy for ClimDiv) to emulate the NOAA calculations. The one-month calculation, with comparative maps, is here, and the time series calculation is here. The key graph which corresponds to the NOAA monthly graphs, is here. Note that my results are in °C, while NOAA's are in °F.

In the legend, USCRN and CLIMDIV are my rendering of the NOAA data as in the earlier plots. MoyCRN is my calculation of the average from the station USCRN data. GHCN_u is the calculation using the ConUS GHCN V4 unadjusted station data, and GHCN_a uses GHCN V4 adjusted data.

And they all move along together, whether derived from USCRN, ClimDiv/GHCN, calculated by NOAA or me, and whether or not adjusted with GHCN. Again the different behaviour is a bit clearer with a 12 month running mean plot:

So is the station data rigged?

Presumably that would be the claim. It isn't, of course, and as said above it would be completely pointless to do so. But it actually can't be. All the daily data is available within a few days at most of being read. It would be quite impractical to adjust the ClimDiv on even that timescale to match USCRN which would probably be not yet available. And of course the posted daily data comes from data which is mostly posted promptly hourly.

Plus the ClimDiv comes from 10000 or so different operators. They can't all be in the conspiracy, and they can see what is happening to their data. The conspiracy notion is ridiculous.

What if ClimDiv and USCRN were both wrong?

I pushed this line of argument, and this is where it tended to come down to. Don't trust any of 'em. But the causes of error would be quite different - supposedly various bad siting issues for ClimDiv (of many kinds)

Update - difference plot and trend

Prompted by comments, I have plotted the difference USCRN-ClimDiv. Note that the range is much less than the earlier plots. 

Now there is structure to the difference, and a statistically significant upward trend, as Mark B noted in comments. However, it does not indicate "corrupted data due to purposeful placement in man-made hot spots". It goes the other way - ClimDiv is warming more slowly than USCRN!

Appendix - calculation method

I'll give a quick summary of my spatial averaging method here; more details are in my earlier post. It is much less elaborate than NOAA's, but I think quite accurate. I create a fine grid - 20km is a good compromise, 10 km takes longer. Many cells have no station data, especially of course with USCRN. Then I apply the principle that stations without data are assigned a temperature equal to the average of the neighbours. Of course, the neighbours may also be unknown, but I can write down a large sparse matrix expressing these relations, and solve it (conjugate gradients). This is equivalent to solving the Laplace equation fixed at cells with data.

A test of the method is whether it can give spatial maps like those of NOAA. It can - I did that in my earlier post. Here is my comparison for January 2020:

Of course, another test is the good congruence of the time series above.


  1. Roy’s trick looks cooler:

  2. What Watts does have going for him is physical proof of poorly placed stations in the report (pictures) and his study from 2011. So something here is not right. Yes, it all looks the same at the very end, but pictures don't lie?

    1. Well, pictures of some stations, which he says were poorly placed, some time in the past. 128 out of about 10000, so there is ample scope for cherry-picking. But physical proof? It's all subjective. Asphalt? Don't like the look of that. Building nearby? You can write those things down, but do they really affect the measured temperature? There is no physical proof of that, except the end result, which says they don't.

    2. Hey Walter! A better scientific study would be not to say "huh these temperature sites look fishy" and just stop there, but to actually *test* whether or not the "questionable" part of the siting makes a difference. "Here is a question" isn't usually publication-worthy in and of itself: you need to do the work to provide an answer. Quantify the degree to which the "poor siting" actually makes a difference, if it does at all.

      If you *don't* do that work, then no, you don't have physical proof of poorly placed stations.

      My *loose* understanding is that other scientists have already done this work, and shown that most problems (like asphalt being put in near a station) are easily adjusted for; they present as a one-time step-change in the temperature anomaly that can be identified and then adjusted for.

  3. He did include in his report the effect that poor station siting has on the trend over time from 1979 to 2008. The effect was almost double when compared to stations that were properly sited. He also cited in his references (#32) Fall et al. 2011, of which he was also an author, but you and Nick didn't address that.

    1. What I am doing is preliminary, but I am currently exploring the impact of poor station siting on temperature distribution for a single month. My findings suggest that inadequate placement reduces variability in the daily diurnal cycle, consequently affecting variability in the daily average, the monthly average, and ultimately the annual average. Station B (green) is placed on a sidewalk; I know this because I have visited the station.

  4. Walter,
    "He also cited in his references (#32) Fall et al. 2011, of which he was also an author, but you and Nick didn't address that."

    Who else didn't address it is WUWT, in the 2022 article on the report, or the report itself. Yes, there is a footnote 32 in the "bombshell" report, but what it says is:

    "After an extensive peer-reviewed process, the Surface Stations project authors published a 2011 report coming to a very different conclusion than the NCDC authors.32 The paper incorporated comprehensive data analysis from both well-sited and poorly-sited stations, using a larger sample size of stations than NCDC’s 2010 report, while remaining true to the NCDC’s rating approach. The 2011 paper concluded, “According to the best-sited stations, the diurnal temperature range (DTR) in the lower 48 states has no century-scale trend.”33"

    Not a difference in trend of temperature, but a difference in trend of diurnal range. Weak tea. The Fall et al Fig 4 showed that the adjusted Tavg showed no trend difference at all with CRN rating. For TMAX, CRN class 1/2 showed the highest trend, balanced by a low trend for Tmin.

  5. Nick, do you have an email? I need to talk to you about something serious, regarding safety.