Cooling The Past In Bolivia
By Paul Homewood
Eliza suggested I looked at some of the temperature records for Bolivia, as it shares a border with Paraguay.
One station she suggested was Santa Cruz.
As with all of the Paraguayan stations, we find that a substantial, artificial warming trend has been introduced. What is also significant is that we see the same sharp drop in temperatures in the 1970’s, which we had in Paraguay, and which the GHCN algorithm assumed could not be right.
It is also worth noting the large gap in readings beginning in the 1990’s. It is questionable how reliable any comparisons now can be with the previous data. Nevertheless, GHCN assume that the last few years must be warmer than the actual data says.
We can also check out the other Bolivian stations.
ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/v3/products/stnplots/3/
At every station, bar one, we find the same pattern as Santa Cruz. The past is cooled and the present warmed.
Also, again, we find the marked cooling in the 1970’s.
The only station to which slightly bucks the trend is La Paz, with temperatures adjusted down slightly in recent years. But even here the sharp cooling trend shown on the actual data is moderated after all adjustments. Given how much the city has expanded in the last half century, any trends here are likely to be worthless anyway.
In every case, the data in the last couple of decades is so sparse as to make any conclusions on temperature trends pretty meaningless, but none of this stops GISS from declaring that temperatures in this part of the world were a degree higher last year than the 1951-80 average.
Despite these huge holes in the temperature record, GHCN still manage to come to the conclusion that, in every case but one, temperatures measured in the last decade have been underestimated.
It seems it is not just the Paraguayans who do not know how to read thermometers.
NOT A LOT OF PEOPLE KNOW THAT 
And they call this Climate Science?
Are there any genuine data series in South America at all?
Are there any data series in the whole world that haven’t been corrupted?
A C Osborn January 30, 2015 7:31 pm
“And they call this Climate Science?”
This is called Climate Non-Science, made from 97% Climate Incompetence!
“Are there any genuine data series in South America at all?”
Even a local guess is far more correct than any computer “correction”.
If the guess is the best you have, then only that is the best measurement at that time and place. Everything else must be a worse guess. If you have no guess, such, is still part of the best data set you will ever have. Proper statics need never adjust any measurement. any dropout decreases both the sum and the divisor, for the average of “measurement”.
Error bars always need to increase for such dropout. Climate Clown homogenization is adding sawdust to the peanut butter..
Reblogged this on Globalcooler's Weblog.
Hello Mr Homewood La Paz is 14000 feet high (El Alto Airport anyway). There not worried about AGW there LOL. Well that confirms that one (Bolivia as well) anyway.LOL. As an aside my father spent 1962 to 1965 in Bolivia fixing the Stevenson boxes/measurements/readings methods/ thermometres ect there for the WMO, with the Bolivian Met Service so presumably from that time onwards there should be no adjustments. Idem for Paraguay from 1966 to 1977. You might have a look at Northern Argentina, Salta, Clorinda, Formosa, Corrientes, Resistensia, Posadas. In Brazil, Foz de Iguazu, Curitiba, ect although my father had nothing to do with the Meteorological services there and presumably, ther should be no problems as they are more advanced countries. In any case we cannot blame eitherthe Paraguayns or Bolivian met servicesas the raw data is most like correct. As I recall here in Paraguay (and in Bolivia) there were no real problems with measurements BEFORE 1962 or After.
Using the new HadISD database, I plotted the temps for Cobija. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000005368648461.
Here is the plot:
Using the new HadISD database, I plotted the temps for Riberalta. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000001356617265.
Here is the plot:
Using the new HadISD database, I plotted the temps for Rurrenabaque. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000000595914272.
Here is the plot:
Using the new HadISD database, I plotted the temps for San Borja. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000004418011531 .
Here is the plot:
Using the new HadISD database, I plotted the temps for Concepción. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000002308572097.
Here is the plot:
Using the new HadISD database, I plotted the temps for La Paz/Alto. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000001264765216.
Here is the plot:
Using the new HadISD database, I plotted the temps for Cochabamba. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000002608985467.
Here is the plot:
Using the new HadISD database, I plotted the temps for Santa Cruz/El Trompo. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000010263140210.
Here is the plot:
Using the new HadISD database, I plotted the temps for Robore. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000001545356757.
Here is the plot:
Using the new HadISD database, I plotted the temps for Sucre. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000000289373890.
Here is the plot:
Using the new HadISD database, I plotted the temps for Puerto Suarez. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000005221303444.
Here is the plot:
Using the new HadISD database, I plotted the temps for Camiri. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as -0.000000027766814.
Here is the plot:
Using the new HadISD database, I plotted the temps for Yacuiba. Using the @slope function in Quattro Pro X5, I calculated the slope of a simple linear regression without interpolation as 0.000002608147645.
Here is the plot:
As before, all of these stations appear to be at airports, hence they are in the HadISD database. Trinidad was not in the data base. All of the stations passed “final filtering” for quality control, with the exception of Cobija and Concepción, which failed. Although, these stations have been (presumably) adjusted as part of the QC process, they have not been adjusted for break_points.
As can be observed, the data for the 1990s is clearly available and quality controlled. As before, the HadISD database consists of hourly or quasi-hourly observations, so the sampling is much better than with min-max thermometers. I calculated the slopes without interpolating for missing observations. There does not seem to be any climate change in Bolivia, based on these weather stations, which, since they were presumably used for aviation, would have been maintained and calibrated pretty continuously. I don’t see how the GISS adjustments are justified.
I hope this is helpful. If I have the time, I will continue to post plots from the HadISD database (for those stations that are in the database), if you do any more South American observations, unless you would rather I didn’t.
Phil, I notice that they do not have 2014 values, which would have been helpful in the “Hottest Year” debate.
As of right now, the HadISD database ends at Dec 31, 2013. At some point, they would be updating it, but that is all that is available now. I imagine it would take some time to do so, as it is barely a month since the year ended. Nevertheless, what is remarkable is the lack of any warming over the last forty years. Supposedly, the 70s were cold, followed by considerable warming during the 90s and then the “Pause.”
So you would expect to see the data in the form of an “S” curve, with perhaps 2014 at the warmest end. However, the lack of ANY trend over the last 40 years or so is a surprise and it is such a surprise that I think it debunks the 2014 as “hottest” year, even without 2014 data.
What you see is about as flat as a tabletop. 2014 would have to be a book at the end of the tabletop and that would raise questions of credibility. With the exception of La Paz/Alto, ALL of the GISS adjusted plots show a warming trend for the period covered by HadISD (1973-2013), which is about the rightmost 60% of each GISS graph. HadISD is showing no trend at all ending with 2013 for every single one of these stations. One year cannot make a trend. I think the HadISD database is in significant conflict with the warming claimed by GISS.
Also, the HadISD database covers enough time (more than 30 years), that you can argue it is showing “climate” and not “weather.” The argument that 2014 is the “hottest” year would be easily dismissed as “weather,” were it not for the long warming trend claimed by GISS. By debunking the warming trend over the last 40 years, the claim that 2014 as the “hottest” year is significant can be dismissed as just “weather,” if it exists at all.
Good God,
Can we finally throw folk in jail, for deliberate fraud, against the people and governments of the US, GB, EU, and AU? Will the funding for such alleged “fraud” immediately cease until such is decided by a court of, each political unit? Will so called “science” ever recover? Must we close all so called institutions of higher learning until all hard science curriculum has been audited by disinterested parties, for scientific discipline and rigor?
Call me pissed!!!
This is the kind of stuff we really need to hammer the alarmists with. I can’t tell you how many times I have heard defenders of the surface station records saying that atmospheric temperatures don’t matter, only surface temperatrues. This sort of detail helps to show that while that may or may not be true, only satallite records can be trusted.
Off Topic, what is with the Longitude and Latitude being switched from the international standard. Typicaly latitude is listed first, and longitude listed second, but these records are switched. Kind of goofed me up when trying to see it on a map.
The ‘Surface’ temperatures are NOT the temperature of the surface! They are the temperature of the ATMOSPHERE a couple of metres off the ground.
Paul,
GHCNv3 included many adjustments (that increased warming) as compared to version 2.
If you did your same analysis using GHCNv2, I believe you would find the results would show even more extreme adjustments, often turning cooling into warming.
The GISS data has been totally corrupted and is unfit for scientific use, since the historical temperatures change every month. This makes replication near impossible. Conclusions drawn for data used in a paper one month could be totally reversed several months later. Valid conclusions based the currently available data, could be dismissed out of hand with an improper “That was using old data”. This is a total corruption of the scientific method.
NASA’s satellites have documented over 12C of UHI over Providence, RI: http://www.nasa.gov/topics/earth/features/heat-island-sprawl.html
This level of UHI was obviously not present over a century ago. Adjustments made to the raw data have not properly corrected for this UHI. In fact, the adjustments are backwards for this, as the adjustments have cooled the past and warmed the present.
The data has been adjusted so often and by so many different groups, does anyone even know what the actual annual-mean measured (raw) temperature was in Providence, RI?
There has surely been warming since the Little Ice Age ended, but the warming has just as surely been exaggerated by incorrect adjustments to the data.
Paul, ,Manic Bean Counter is having a go at ThenThereisPhysics over his rebuttal of your first Paraguay post. Tallbloke is showing it on his site. It would be great if it could all get highlighted over on WUWT to get greater internet exposure.
And don’t forget the fairly recent and “unprecedented” cold spells: https://theextinctionprotocol.wordpress.com/2010/12/12/6-million-marine-animals-die-in-winter-freeze-in-bolivia/
And last winter (May 26): http://www.rpp.com.pe/2014-05-26-tres-personas-mueren-debido-a-ola-de-frio-en-bolivia-noticia_694972.html
–AGF