Annual Temperature Plots - Puerto Casado

This site was selected because Kevin Cowtan produced the NOAA Paraguay data video (which was also used to advertise the Climate Change Denial course). Here, Kevin uses an older version of the software (but with a higher quality map) to examine the data. I suggest that you follow along using my program and try to recreate the same plots.

BTW - all the images on this page can be zoomed by simply using the mouse wheel or double clicking.

Video | Just the station | An obvious station move | Surrounding sites - Concordia | Analysis similar to the video | Berkeley Earth data | Regional Comparison | Discussion


This page is a response to Kevin Cowtan's NOAA Paraguay data video, which is a response to an article, which is a response to new data adjustments.

Just the station

Before starting a complex analysis, here is just the station data for Puerto Casado (the green dot on the map).
The 2 images below are of the same temperature record - the red is raw, the blue is "adjusted". The only difference between the images are the end point of the trend lines - 2000 on the left and 1966 on the right. The video makes a real big deal about a descending spike in 1970 - you can see it in the red trace below.
You can also see, of course, that discussing just the 1970 spike that was removed is just misdirection - it is the change in the trend line (cooling to warming!) that is important! Actually, the second plot shows that the slope of the 1951 to 1966 data is identical - it is the 2C drop (adjustment) in the early data that is important. Sometimes this sort of thing is because the station moves to another location. However, in this case, perhaps not - notice that the raw data is continuous from 1966 to 1980. With a station move, the change occurs in a single year (or two). In addition, they have removed 4 years of data and adjusted an additional 4 (8 total)! Very suspicious.

It is curious that in the video Kevin compared the raw and adjusted anomalies (computed for a base period of 1961 to 1990) rather than looking at the actual temperatures. As you can see in the plot above, the actual temperatures from 2003 to 20014 are identical before and after the "adjustments". As far as trendlines go, this has no effect. However, when looking at adjustments, this makes a major 2C "adjustment" look like only half that amount. In other words - it looks like no big deal. In fact, it misleadingly implies that part of the record was adjusted up .. and that part was adjusted down. (Looks fair - doesn't it!)

So, the bottom line is - when looking at adjustments to a single station, use the temperatures, not the anomalies.

An obvious station move

As I said above, a large temperature change due to a change in station location is usually pretty obvious, and it typically shows a transition within single month (which can become one or two years in annualized data like this). For instance, Salto, Uruguay has a pretty obvious station move - a one- to two-year fast change in temperature. In this case, moving the station average so that the two half's agree makes a lot of sense. However, changing the slope of the line - from -1.179C/decade to -0.423 - does not make obvious sense. If you had the raw daily data, this might be completely obvious .. but from this vantage point ???
At the bottom of this page is an image (with links) showing that the Salto data needed to be adjusted 7 times - not just one.

Surrounding sites

Like in the video, I zoomed out and selected a region. I tried to select similar regions for both the adjusted and raw datasets. When doing this (and switching between datasets), I saw that there are more sites in the raw dataset, and the extras are probably a lot less reliable. As a result, I adjusted the selection so that both collections contained exactly the same stations. (It was while doing this that I spotted Salto - above.)

I also inspected a number of stations and didn't see any difference between Paraguay and the surrounding areas. It appears that northern Argentina also had the same weird data patterns. Closer analysis shows that a lot of stations in that area have missing data. As a result, the surrounding stations can not be used to remove those readings.

In fact, the data indicates that more research is appropriate.


Almost next door to Salto, Uruguay is Concordia AER, Argentina - they are both at an altitude of about 48 meters and located on opposite sides of the Uruguay River.
The Concordia data was adjusted to make it colder in the past - suspicious, but not necessarily a problem.
However, it becomes more interesting when it is compared to Salto,
In the raw data, notice the lack of temperature change for Concordia - the trend is 0.014C/decade and never changes. Very steady. No sign of any forcing. No indication of a station problem. However, the adjacent Salto loses 3C in twenty years. Clearly, something is not right. (Remember, you have to zoom the map way in to see both stations - they are very close - what ever that means on a map at this scale.)

In the adjusted data, at the beginning Salto is now about 1.5C warmer than Concordia which is just on the other side of the river.

Analysis similar to the video

I preformed the same type of analysis as shown in the video and because I was doing an actual temperature (not an anomaly) the related purple stations must also be deselected (turned red). I tried to select the same stations for both datasets, got 39 and 41, and could not find the 2 extra stations. They are probably directly under another. At any rate, I used the following stations (green means selected).
These are the plots
As you can see, Paraguay makes almost no difference after 1985. Since the number of stations drops off quickly before 1951, I am not displaying the older data. You have access to the software, so you can generate those plots yourself.

That's interesting, there appears to be extreme cooling after around 1995. Including Paraguay does not seem to make any effect.

If anyone ever wanted evidence for a pause - here it is. And this time, the adjustments made it cool faster.

Of course, your results will vary because you will probably pick different "near" stations than anyone else. But this type of analysis is fun and you will learn to use the tool.

Note: don't pick any sites in Chile - it's on the other side of the Andes.

Sites in the video

Well, above I followed the general procedure in the video and got different results. Since he doesn't specifically list the selected sites, I tried to match the dots. His map appears to match the 7 stations selected below.
Note that ROBORE only appears in the raw data. Therefore, some comparisions using it are invalid.

I went through and compared all 6 other sites used in the video. Based on what I saw,

That's enough analysis to know that the video is nonsense and that my analysis, using 27 (raw) and 30 (adj) stations outside Paraguay, is better than his using only 7.

Specifically, he claims that the 7 justify all the adjustments to the Paraguay data - but the larger number indicates that the adjustments are bogus. But you have access to the software - make up your own mind.

Berkeley Earth data

Berkeley Lab (Lawrence Berkeley National Laboratory) provides support data for all the climatology stations - more than 40,000 sites.

What I found most interesting is that the GHCN adjusted data is completely missing 4 years of data (there is a clear gap), and that the Berkeley Earth data does not have a gap.

Above, I used Salto as an example of an obvious station move. According to Berkeley Earth, the Salto data needed to be adjusted 7 times! Also notice that the GHCN and Berkeley Earth final results are quite different.

In the Berkeley Earth plots, the vertical lines with red markers are supposed to indicate documented station moves, the black markers represent undocumented anomalies identified because the data just looks wrong.

By the way - the Berkeley Earth adjustment changed Concordia from -0.06C/Century to +1.16C/Century

Regional Comparison

The main claim in the video is that the spike in 1970 is not found in the surrounding stations. So .. here is a map and the results .. with Paraguay removed. I have used the raw, unadjusted data.
I think the 1970 decrease is there .. and is perhaps real!

But I'll let you decide. (What do I know?)

(Compare the plots above with 2:36 in the video.


The take away from this page is not that I have proven anything one way or the other. Instead, I have shown one way to use the tool and external data to evaluate discussions you might see in the press. There is clearly no one correct answer.

Related discussion on the MOOC (requires a login to read)

Author: Robert Clemenzi
URL: http:// / Science_Facts / Annual_Temperature_Plots / Puerto_Casado.html