Jon Brooke (16:27:40) :

“My suspicion is that far from this station being one chosen at random, it is actually the “worst” that Mr Watts could find,”

Have you actually taken the trouble to read back through this whole thread? It doesn’t look like you have otherwise you’d kno wthat it is Willis Eschenbach who has done the anlysis for Darwin and not Anthony Watts. You would also have noticed

KevinUK (10:56:57) :

“Willis,

With vjones’s help and with the aid of EMSmith’s excellent documentation, I’ve been carrying out my own analysis of the NOAA GHCN data. My first step was to reproduce you excellent analysis for Darwin (unlike the Team who think that ‘there’s nothing to see here, move on’). I’ve therefore been applying the scientiic method and have attempted to falsify your analysis. I’m sorry (actually I’m glad) to say that I failed! I’ve reproduced your charts and results almost 100% and have documented my efforts on vjones blog ‘diggingintheclay‘. You can read the thread in which I reproduce your analysis by clicking on the link below.

Reproducing Willis Eschenbach’s WUWT Darwin analysis

As I’m sure you already know and appreciate science progresses by ’standing on the shoulders of giants’ so I’ve taken the liberty of further extending you excellent analysis for Darwin to all the WMO stations in the NOAA GHCN dataset.

Specifically I’ve attempted to answer the question posed by others on your original Darwin thread as to whether or not Darwin is a special case or not?
Well judge for yourself by clicking on the link below which documents my extension of your analysis to include the whole NOAA GHCN dataset.

Physically unjustifiable NOAA GHCN adjustments

The following is an excerpt from the thread

“In total, I have found 194 instances of WMO stations where “cooling” has been turned into “warming” by virtue of the adjustments made by NOAA to the raw data. As can be seen from the following “Cooling turned into warming” table (Table 1) below, which lists the Top 30 WMO station on the “cooling to warming” list, Darwin is ranked in only 26th place! The list is sorted by the absolute difference in the magnitude of the raw to adjusted slopes i.e. the list is ranked so that the worst case of “cooling” converted to significant “warming” comes first, followed by the next worse etc.
It’s clear from looking at the list that Darwin is certainly not “just a special case” and that in fact that there are many other cases of WMO stations where (as with Darwin) NOAA have performed physically unjustifiable adjustments to the raw data. As can been seen from Table 1 many of these adjustments result in trend slopes which are greater than the IPCC’s claimed 0.6 deg. C/century warming during the 20th century said by the IPCC to be caused by man’s emissions of CO2 through the burning of fossil fuels.
”

“Personally I’m unconvinced, but if you think that this analysis could be applied to other stations, lets see them”

So click on the links above and you’ll be able to ‘see the anlysis applie dto other stations’ and hopefully then you will be convinced that the adjustments NOAA make to the raw data for many stations whether they result in ‘cooling turned into warming’ or ‘warming turned into coooling’ are just not physically justifiable. Even NOAA have now admitted that this is the case and are in the process of correcting their adjustment algorithms.

There are several dozen stations where I have looked into the matter graphically, using data from a number of sources and stages of adjustment.

Because I live in Oz, I have used Oz data because there is less chance that it has gone through the overseas sausage machines.

There was an earlier post where a distribution was given, to show that as many adjustments were downwards as upwards. The place to go looking is on the limbs of the bell curve and Darwin is one of these. Not the worst, just one. Another is Coonabarabran, buts its early data was used by the adjusters even though our own BOM has deleted the temperatures pre-1950 on grounds of poor quality. Because I could not identify many Australian stations in the outliers, I did not proceed further.

There is a problem with supporting data. It is very hard to find for a particular station from another country, whether it has home country adjustments before it goes into GISS etc for more. The Oz data are being refined all the time, but GISS probably cannot tell you if they are using BOM refined version 1, 2, 5, 10 or 20; or when they started using a version, or when they stopped and changed to another, or whether they deleted the first try and substituted the next or latest …

Let’s call a spade a spade. The GISS and HadCRU and NOAA data sets are an untidy mess of record keeping, including some adjustments that any prudent scientist would have to regard as prima facie evidence of unjustified fiddling.
Darwin is but one. It takes only one to establish a principle.

Einstein: “No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”

I’m the one who essentially trusts the existing analysis, remember?

It’s you who is trying to convince the world that the data is bad. So why don’t *you* select a few stations? My suspicion is that far from this station being one chosen at random, it is actually the “worst” that Mr Watts could find, and even in this case his analysis is far from convincing – he derides the modifications made to the data by others but has applied his own modifications instead and asks that people accept them at face value.

Personally I’m unconvinced, but if you think that this analysis could be applied to other stations, lets see them.

Why don’y you select a few stations and do some analysis for yourself and show it here? If you lack the skills to do that, you probably lack the understanding to comment as you did.

Not sure how much time you have for this, but maybe you could do a similar analysis on a RANDOM sample of other stations world wide.

I see loads of people saying, “wow, that just shows the whole thing is corrupt” but the raw data is there for anyone to look at. Lets see some more widescale alternative analysis, not just a cherry picked one to make a point.

The first thing that strikes me is that you put up a graph from the IPCC from about 1920 and then the GHCN graph from about 1890 and say “they look nothing like each other” without pointing out the different date ranges.

But if you compare the GHCN graph from 1920 onwards, actually, it does look remarkably like the other graph.

Of course I can see that there does look to have been a significant drop in temperature before this date (and I haven’t looked for an explanation for that – maybe another discussion), but your point seems to be that the data have been (mal)adjusted, whereas I find it hard to see what you claim is blatantly obvious.

The world is heading into a full blown Ice Age and ‘Al Gore’ and His cohorts are trying to mislead the population to save them from the Fear of a slow Death.

Tell everyone that the World is warming to hide them from the truth.

When you freeze peacefully in your bed at night you won’t know you have been protected from the ” Peril’s of Global Warming”

Try Florida – Had their coldest Winter ever I believe. Bring your ski’s

Poor old OZ – Very hot summer but ” Snowed to down to 1000M in mid January.

Very odd – a very HOT Summer with “snow” . Maybe someone can explain.

I can’t???

Mapping global warming

The main conclusion reached in the thread is that global warming is hardly global and that based on the evidence shown in the colour coded trend maps presente din the thread, ‘global warming’ is not global but is in fact largely NH winter warming. I’ve stated that given what the maps show, it’s hard to see how CO2 could be the cause of this warming unless the demon CO2 is happy to allow notable exceptions while being choosey in selectively warming parts of the planet while allowing other parts to cool at the same time.

I’ve suggested that Western Australians apply for a rebate on their carbon taxes and have also recommended where us ‘pommies’ should all go if we want a good tan this summer.

Regards

KevinUK

The impulse to keep precise records did not occur right away.

Wasn’t it about the Civil War before we start seeing actual measurements on a standardized, precise thermometer recorded in a systematic way?

And then the SAMPLE set consists only of a few large European cities. The existence of a large number of measurements distributed throughout the Earth did not occur until around World War II during the big push for aviation.

I am not saying that people did not have thermometers.

That is a very different question from someone keeping regular, consistent, temperature measurements in a reliable record.

And that pretty much needs to be daily. For example, if you have a temperature measurement for Amsterdam on May 20, 1910, but in South Africa you have only a temperature measurement on May 31, 1910, how useful is that for comparison?

Measurements really would need to be on the same day in different cities throughout the world to have much value as a set of RECORDS.

People playing with thermometers is very different from keeping reliable, precise, and usable records.