I met Ken while on my Australian tour, he’s been doing some fine work.
Via Andrew Bolt
Retired school principal Kenskingdom was alarmed by this Bureau of Meteorology graph, showing a strong warming trend for Victoria, Australia:
He checked the data from which the trend, and found it had first been adjusted and turned into “high quality” data. As a BOM spokesman assured him:
On the issue of adjustments you find that these have a near zero impact on the all Australian temperature because these tend to be equally positive and negative across the network (as would be expected given they are adjustments for random station changes).
Actually, no, though. You see, Kenskingdom discovered that the adjustments served to exaggerate Victoria’s warming remarkably:
Kenskingdom goes through the individual stations for you and concludes:
There is a distinct warming trend in Victoria since the 1960s, which has been especially marked in the last 15 years.
The first half of the record shows a cooling trend. BOM’s adjustments have attempted to remove this.
2007, not 2009, was the warmest year in the past 100 years.
Three stations identified as urban in 1996 have been included.
Many stations’ data have been arbitrarily adjusted to cool earlier years
Only one station has had its trend reduced. Two are essentially unchanged.
Ten of Victoria’s 13 stations have been adjusted to increase the warming trend, to the extent that there is a warming bias of at least 133%, more likely 143%.
These adjustments, and the Australian temperature record to which they contribute, are plainly not to be trusted.
Is someone collating all the sites that show questionable adjustment/corrections like Victoria, including countries/regions as a whole? I know one of the blogs has shown analyses of regions – essentially that is what the site does, review the IPCC regional sites and provide alternate views.
Plus, is there work that details and audits why the IPCC “natural” cycle (i.e. without CO2 forcing) is a cooling trend?
*sigh* what else is new? We know that global warming has been “man made” for quite some time and he is just discovered (again) how man makes it.
I got your “quality data” right here.
That looks like it could be a single station move around 1960. Station histories for Australian stations are available somewhere from the BoM, why not just look at them to see what prompted the BoM to do that, before you decide what is to be trusted or not?
In any case, it’s the period since the 1960s that we’re really looking at, when we’re talking about the AGW period… before that, greenhouse gas forcing was not dominant.
I get the feeling from reading about all the warm bias that has gone into the global average temperature calculations that if it were an honest calculation it would come out to just about what to expect (from simple physics) from the increased CO2 minus absent positive feedbacks. Given the exponentially decreasing capacity of additional CO2 to cause surface warming it would appear that we’re looking at maybe 1.5C of global average temperature increase over the next 100 years and this is disproportionately occurring in the night time low temperatures in the winter in high northern latitudes where it, in fact, is a welcome happenstance that merely serves to lengthen growing seasons and extend northward the boundaries of arable land and possibly even reliably open up a northwest summertime passage in the arctic which would be a boon to intercontinental shipping. Add on the benefits to plant growth rates from increased atmospheric CO2 and reduction in water requirements for same(which are global benefits) and it looks like a pretty solid conclusion that we should be thankful for rather than fearful of anthropogenic global warming.
That’s standard M.O. They always adjust and always downward in earlier times and/or upward in later times. So, yep, it is probably as many adjustments up and down,(I bet you’d find nearby stations with more recent temps adjusted upwards) but always in the same manner as it relates to time.
Down under and in the USA, how are these “adjustments” justified?
In science (and I have 30 years in science and engineering), adjusting old data is considered cheating unless some instrument malfunction can be proven.
Great work by Ken Stewart here. The Vic region is my home turf- finally a nice detailed look at the BOM temperature adjustments.
As far as I know, New Zealands’ NIWA still refuses to release information regarding the reasons for their own warming adjustments (update?). Looking at these graphs, I wonder now how the BOM is going to react.
Thanks Anthony, it was great to meet you in Emerald. I’m going away for a few days and won’t be able to post comments, but thanks.
carrot eater :
Obviously you have not bothered to read my posts. I have looked at the raw data and adjusted data for 93 out of the 100 High Quality stations, and the vast majority have been warmed. The average for those 93 is approximately 33%. BOM says they have adjusted to correct for discontinuities so the adjustments should be random and average to neutral. Only a few of the stations’ metadata is available in digital form yet.
Ken
Sorry, that should have been “The average for those 93 is approximately 33% extra warming above the raw trend.”
Ken
James Sexton,
I can’t speak to Australia itself, but when you use unadjusted data from around the globe, you get pretty much the same results as what GISS, CRU and NOAA get using their adjusted figures.
So it’s actually quite true that taken globally, the adjustments cancel out, and have no real bearing on the global trend. This has been painstakingly shown by Zeke at Lucia’s, among several others in recent months. That’s what you have to do when you want to see what effect adjustments have on the overall result – instead of picking out stations one by one and looking at their graphs, you have to actually recalculate the overall result using the adjusted and unadjusted data sets, and see what difference it makes.
Incidentally, for whatever it’s worth, the exact adjustments made here by the BoM are not adopted by either NOAA or GISS. CRU may or may not; they sometimes adopt the adjustments suggested by the providing countries, I think.
I was wondering what Climate Science students use for textbooks. I think I found the answer here:
http://www.amazon.com/How-Lie-Statistics-Darrell-Huff/dp/0393310728/ref=sr_1_1?ie=UTF8&s=books&qid=1278009721&sr=1-1
It is now called helping the data, smoothing or cleaning the info.
Who doesn’t want a refurbished data set?
Funny how Gavin last year predicted 2010 would be the warmest year yet and it turns out that GISS is churning out warmest months after warmest months. Either Gavin is truly an amazing oracle when it comes to season’s weather and the Met Office should grab him PDQ, or he had advanced knowledge of GISS strategy…
This is IMO no luck that all AGW supporting weather offices are relaying the GISS stuff.
Sounds to me like “The Sting”: you never can lose when you already know the answer…
Notice how the “adjustments” always seem to be matching the same pattern of correction.
This will not stop until there is a planet wide movement to jail all of the “fraudulent adjusters’ who attempt to call themselves ‘scientists’.
The sooner we jail the perps…the sooner we can get back to doing real science!
Or is ‘science’ all a facade? and may have been a super scam all along?
It just amazes me how the obviously cyclical variations in temperature are so frequently smoothed out to produce a more straightforward warming trend.
The graphs shown have a different y-axis. The Bureau of Meteorology graph uses a mean temperature anomaly based on a 1961-1990 base and the “comparison” graph is unlabeled. From 1960 to the present time both graphs are in agreement and cover the period of time showing the most dramatic increase in global temperature known by many to be the “blade of the hockey stick”.
Prior to 1960 the graphs start to diverge and the Bureau’s temperatures are noticeably cooler back to 1915. Whether the cooler adjustments were correctly applied or done in error would be best judged by reading the Bureau of Meteorology article (peer reviewed?) accompanying the graph. Who can tell, maybe all those old thermometers were poorly placed.
You’re half right. It’s the period since the 1960’s when we’re talking about the AGW period. Where you’re wrong is the lack of interest in the prior period. If it was as warm 100 years ago as it is today then there we could conclude that there is no such thing as AGW. The temperature trends before 1960 are what’s called “control data” i.e. data where the variable of interest is isolated. Without being able to isolate the CO2 variable we we’re simply not doing any valid science.
carrot eater says
Missed the point again rabbet.
No wonder climate science has lost the trust of most informed people. The Victoria ‘warmed period’ is just one of a series of published blunders, or worse, and is perhaps an indication of how many people have a vested interest in CAGW being true.
We need some real scientists doing real science so that we can start on the long and complex road to understanding our chaotic climate and how it is affected by changes in solar activity. What we have at the moment is cargo cult climate science where belief, rather than evidence, drives the agenda.
Jay: The justification seems to be: The ends justify the means.
Carrot Eater says:
“In any case, it’s the period since the 1960s that we’re really looking at, when we’re talking about the AGW period… before that, greenhouse gas forcing was not dominant.
Uhhmmmm – no.
We don’t cherry pick the data that suits our particular beliefs and preferences.
We don’t cherry pick the starting points or the ending points to suit our desires.
We don’t adjust the data to suit our particular perspectives.
We don’t make unsupported declarations about “green house gas forcings”.
We don’t make unsupported declarations about when the unsupported “green house gas forcings” were or were not “dominant”.
We record the raw data. We plot the raw data. We examine the results for trends. We risk hypothesis, based on the data. If it stands against all challenges, it might become theory.
“Funny how Gavin last year predicted 2010 would be the warmest year yet and it turns out that GISS is churning out warmest months after warmest months.”
Or it’s as simple as knowing there was an El Nino coming on.
If the adjustments cancel out globally, then what is the justification for adjusting?
One can easily go cherry-pick stations to manufacture a chilling plunge into a cold period.
In fact, that is what I expect will happen by the alarmists when their warming scares go belly up.
Jay Cech says:
July 1, 2010 at 11:12 am
Down under and in the USA, how are these “adjustments” justified?
In science (and I have 30 years in science and engineering), adjusting old data is considered cheating unless some instrument malfunction can be proven.
____________________________________________________________________
Yes and that is why all the “Climate Scientists” are fighting against FOI requests and having their data looked at. Why data and methods are not included with submission of articles to “peer reviewed journals” Why within “Climate Science” publishing articles without the data and methods is considered the “norm” to quote Mr. Jones at the Parliamentary inquiry.
The big lie:
If this were true then there’s no need to homogenize the data. Why bother making the adjustments if they have “near zero impact”?
I think the truth is that anthropogenic global warming of a tenth of a degree per decade is “near zero” in and of itself. So the “impact” can be said to be near zero or, in other words, within a tenth of a degree per decade of zero.
rbateman
“If the adjustments cancel out globally, then what is the justification for adjusting?”
You didn’t necessarily know this would be the case, before you started going about doing the adjustments. You just knew you had a bunch of data with station moves, instrument changes, etc, etc. If the changes due to these were truly random, you could not bother making the adjustments, if all you cared about was the global mean. But it made sense for somebody to start doing adjustments, to check.
Also, it can matter on the regional scale, and it certainly matters on the scale of the individual station. When it’s interesting to look at an individual station like that above, to get an idea of the record of a very particular location, you might as well somehow correct for things like station moves. Then, in some regions, it may be possible that the disruptions weren’t random; this is the case in the United States. A whole bunch of stations all changed their observation time and instrument type over a decade, so a lot of stations have a change in the same direction at the same time. Those won’t cancel out.
Is this “warming” just in Victoria? Friends living near Sydney are complaining that this winter is the coldest since a cold spell in the 1960s, and another cold spell in the 1930s.
Looks exactly as Swiss homogenized temperatures. All raw trends have been exaggerated. Raw data fits nicely with rural stations in nearby countries.
http://noconsensus.files.wordpress.com/2009/12/v2zki81.png
Gail
“Why data and methods are not included with submission of articles to “peer reviewed journals” ”
The methods used by both GISS and NOAA are available to all, and have been pretty much since inception. The source data they use have been available to all for years. The code GISS uses has been available to all for some years now; NOAA’s code for the new USHCN is now available, and NOAA’s code for the new GHCN will be available once they launch it.
Instead of talking conspiracy theories or picking out individual stations and complaining you don’t understand an adjustment, one could actually do some analysis, and take the openly available unadjusted data, and see what you get. As I’ve mentioned, Zeke at Lucia’s, among several others, have now done this. And they get results consistent with GISS, NOAA and CRU.
Carrot eater, sure an El-Nino coming… Let’s consider the recent post about La Nina on this blog and the highlighted difference between modelling 6 months earlier and the reality. As I said Gavin is an oracle… a stinguy one! Too bad he never predicted temps would cool down when they did…
If Australia and New Zealand are in the southern hemisphere they are not supposed to follow the same fate as nothern first worlders, unless they do it by imitation.
Sure that they have built many Gaia churches, all of them with a sculpture of “El Gordo” to be kissed and XXX massaged as HE likes to.
This technique is well rehearsed. First, you reduce or even eliminate initial sites, retaining only those with a pronounced cooling bias, thereby depressing the origin of your desired trend. Second, you “adjust” subsequent data upward by various obscurantist means, concentrating on UHI and other temperature-enhancing effects as your spurious time-series nears its end. Interim data may be skewed up or down, subtly favoring a long-term rising tendency.
Having thus constructed an ostensibly plausible but in fact blatantly rigged linear progression, climate hysterics plaster their reports with all manner of extraneous rationales, bleats and squeaks extrapolating from nonsensical particulars such as melting Himalayan glaciers to portend humanity’s literal extinction by c. AD 2100.
From this, nothing will deter junk-science cultists– nothing. Grant monies, in-group power-and-privilege, mask an underlying nihilism that rejects post-Enlightenment industrial/technological civilization in toto. On published record, death-eating Luddite sociopaths such as Paul Ehrlich, John Holder, Keith Farnish seek explicitly to “pastoralize” all modern cultures, regressing modern amenities to pre-medieval times.
Radical extremists uniformly celebrate this depraved worldview, which can only originate in a deep-seated psychological need to Rule or Ruin everything such wreckers touch. The fact that global elites cavalierly endorse such theses, entailing human mega-deaths, bodes ill for optimism as the Western world has known it since the Renaissance.
carrot eater says:
July 1, 2010 at 11:47 am
James Sexton,
“I can’t speak to Australia itself, but when you use unadjusted data from around the globe, you get pretty much the same results as what GISS, CRU and NOAA get using their adjusted figures.
So it’s actually quite true that taken globally, the adjustments cancel out, and have no real bearing on the global trend. …..”
I’ve heard that often. The only problem I have with the statement is, each and every station I’ve ever seen adjusted is always lower in the earlier years or higher in the later years and often both. I’m sure there are exceptions, but to have me believe this doesn’t effect the overall trend is silly. If it doesn’t effect the trend, why do it at all? One could state that this is only one station, but then we’d be ignoring the other stations this web site has brought to our attention. Australia, in fact, seems to be replete with over-adjusted sites. Darwin come to mind for some reason. I also recall a station or 2 in N.Z. that were obviously over-adjusted. You can say this doesn’t effect the overall global trend, but if they can’t get entire continents correct, what cause is there to believe their estimates for the rest of the globe are correct? I’ll list a few issues regarding our trend, you tell me if this lends to their credibility or not. As this case shows and Kenskingdom points out, not only this weather station but many others are in error. This should invalidate Australia’s alleged trend. Africa has so few stations and lack of continuity in the data, no one can say one way or the other that its warmer or cooler with any certainty. We know in the western hemisphere there is only on station north of the arctic circle that gets extrapolated to other parts of the arctic, regardless of currents, both wind and sea and gives us useless trend. Oddly enough, South America has a bit of the same problem in Bolivia as the Arctic has and some of the same problems with data continuity as Africa has, it has the worst of both worlds and again, no one can say whether its warmer or cooler there. Asia? The two largest countries in the largest continent have their own data integrity problems, which I’m sure you’re familiar with. China and their moving stations and Russia with the altered temps to ensure more rations. Now, where were we? Oh yeah, the validity of the overall global trend. Carrot eater, I appreciate your idealism, I really do, but you’re being fed something more than a carrot and it extends beyond the credible.
TomRude says:
July 1, 2010 at 1:15 pm
See this:
http://weather.unisys.com/surface/sst_anom.gif
There are some warm left in australian seas. Say good bye to them.
As George Carlin said, “the earth is not going anywhere, we are (in this case YOU), so pack your s*..s up folks”, and brace among yourselves for not to die as frozen penguins!
John Blake:
death-eating Luddite sociopaths such as Paul Ehrlich, John Holder, Keith Farnish seek explicitly to “pastoralize” all modern cultures, regressing modern amenities to pre-medieval times….
Kind of, because those post “modern cultures”will disappear, while leaving no carbon footprint at all, and old cultures, thanks God, will survive.
CE, if the adjustments balance out globally, then where are the downward adjustments located? On WUWT, I’ve seen upwards adjustments in Australia, New Zealand, and the USA. Are there any downward adjustments in populated areas.
carrot eater
This is the graph you must be talking about re; zeke/lucia
http://rankexploits.com/musings/wp-content/uploads/2010/03/Picture-112.png
The adjusted and unadjusted data are significantly different by up to a few tenths of a degree but probably doesn’t effect the trend. Speaking of the trend, there is none. The mother of all El Nino’s in 1998 sticks out like a sore thumb as a step change but for the 100 years before that there is no trend and once the massive El Nino gets a chance to average out of the picture there won’t be any step change to see either.
Thanks for the link. Essentially no warming trend in in the U.S. from 1900 to 1997 and if it wasn’t for the largest El Nino on record in 1998 and its aftermath there wouldn’t have been any warming in the last 12 years either.
For those asking whether this is just for Victoria, just spend a few minutes at Ken’s site… he has done this for each state and territory and the results are similar.
Carrot Eater: You might not be aware that Australia is an island surrounded by a bit of water infested with a few nasties like sharks (aka the man in the grey suit), crocs and octopii that will kill you as soon as look at you… but I digress.
Given that we are reasonably far removed from all neighbouring countries, what possible justification could you have for suggesting that adjustments to temperature records in Australia are linked to those in the rest of the world?
These records should be quite independent from all neighbouring country records. The fact that Ken has shown that the Aussie records are inexplicably biased with a warming adjustment stands by itself. It is an analysis of the Aussie records… not GISS, CRU or whomever else. He is demonstrating without doubt that there are issues that need to be addressed in Australia by the BoM, which makes statements month after month stating record warm this, or record dry that, in order to support the politicians that put the pay in their pockets.
The other major institution for studying climate science in Australia just appointed a MacQuarie banker with no science background as their chairman:
http://news.smh.com.au/breaking-news-national/banker-lawyer-sailor–csiro-boss-20100621-yr5v.html
He himself stated:
“I’m staring at a sea of faces who are probably asking: ‘Who is this guy who has no scientific pedigree at all, what’s he going to do with us and what’s he going to do with this organisation?'”, Mr McKeon said.
Gee maybe there is a slight conflict of interests here?
GISS and USHCN v2 redux.
The adjustment code used is publicly available, of course, but not a hint of all the code discarded because it didn’t produce the desired result.
Pure coincidence that in the early 20th Century, people in Australia were misreading their thermometers (or is that thermometres?) in the same direction and by the same amount that people in the States were.
Indisputable proof of Dr Mann’s teleconnection hypothesis, I’d say.
“GISS and USHCN v2 redux.
The adjustment code used is publicly available, of course, but not a hint of all the code discarded because it didn’t produce the desired result.”
The unadjusted data give you the same result, globally.
So it’s actually quite true that taken globally, the adjustments cancel out, and have no real bearing on the global trend.
I think you are running into the conundrum known as Simpson’s Paradox. (Wikipedia explains it pretty well.)
Basically because the bulk of the temperatures are concentrated in a couple of places (especially the US) the straight average of adjustments might be small. They might cancel out if all are weighted equally important.
But the spots of concern, like Victoria, have far greater effects internationally because they “cover” a far greater part of the world.
If you “fix” New Zealand (as NIWA has) then you get to “fix” a huge chunk of the Southern Pacific too.
Tag the ridiculous adjustments onto the ridiculous gridding and you can have an amazing effect on “global temperature”, all while “cancelling out”.
Meanwhile, in this alarmingly warm 2010, the cold is causing problems for the homeless and elderly.
“SOME people fear death the way the homeless fear the cold.
With Sydney’s minimum temperatures dipping towards record lows, cold and death can be pretty much the same thing for many of the thousand or so people estimated to be sleeping rough each night.
The director of the St Vincent’s Hospital Emergency Department, Gordian Fulde, said the cold snap was cutting through the homeless like a silent disease.
Nobody has died on the streets yet, although Associate Professor Fulde said the hospital had been busy since the weekend issuing death certificates for people who had died in their homes, probably from the cold.”
http://www.smh.com.au/sport/golf/elin-la….00701-znea.html
I’m obviously having trouble with the “chain of custody” here.
a) A local weather station (auto or manual) and its local management.
b) A national aggregator (BoM in this instance)
c) BoM to NOAA (GHCN) and likely CRU
d) GISS from GHCN
“adjustments made here by the BoM are not adopted by either NOAA or GISS”
But GISS uses GHCN as its main source and GHCN gets its “raw” data from BoM (in this instance).
“but when you use unadjusted data from around the globe , you get pretty much the same results as what GISS, CRU and NOAA get using their adjusted figures.”
I’m not suggesting here that “the results” are wrong but if the chain outlined above is anywhere near correct then where exactly are you obtaining “raw” data that would back that conclusion? Everybody in the chain bar the local source (one hopes) has “adjusted” the data. Blind adjustments in the case of NOAA and GISS.
Corrected link, although Tiger is certainly getting the cold shoulder from his wife 🙂
http://www.smh.com.au/nsw/homelessness-on-the-rise-in-a-citys-cold-heart-20100701-zqr1.html
Thanks Mooloo and Carrot Eater, think I may of learned something today. One thing I have struggled to get my head around is that when you look at adjustment data there is a clear trend that exaggerates warming when one would expect dampening in order to compensate for UHI, yet when you grid it the final result is negligible. How to resolve this apparent contradiction instead of just selecting the dataset that supports my personal bias on this issue and ignoring the database that doesn’t fit my world view? I asked Anthony about this in Ballarat, Australia, but my understanding of the problem was not deepened by our brief exchange. Simpson’s paradox is very interesting, I wonder if it actually applies in this case. If I had spare time, I’d like to pull the data apart, look at some open-source attempts to reconstruct anomaly data and try and puzzle it out.
carrot eater says:
July 1, 2010 at 4:09 pm
“GISS and USHCN v2 redux.
The adjustment code used is publicly available, of course, but not a hint of all the code discarded because it didn’t produce the desired result.”
The unadjusted data give you the same result, globally.
—…—…—
False. And false. Hansen (GISS) fought for years to avoid releasing ANY data even under repeated FOIA lawsuits. They still hide raw data. They still hide their conversions and their code, but have released “some” code. Under protest. We don’t know how they refuse to release, nor whether what is released is actually used.
False. NOWHERE have even 20% of raw data been adjusted “downwards” – EVERY rural site checked worldwide (US, UK, Canada, NZ, and (here) Australia has reported raw data adjusted upwards (recently) or raw data (original/pre-1970) adjusted downwards in ratios of 8 to 1 to 15 to one. Russia rejects the GISS data completely and reports a cooling trend that continues unabated in their Arctic and Siberia areas.
Ah yes similar to what they did with Brisbane:
http://globalwarmingskeptics.info/forums/thread-188-post-3121.html#pid3121
Anything to mislead the masses is code for political action.
Enneagram–
Perhaps an inverse “social Darwinism” (Herbert Spencer) will eventually regress global cultures to their reproductive roots (given developed countries’ birth-rates considerably below the required 21 per 1,000, this had better happen soon), but meantime at what price? Absent objective or even rational constraints, authoritarian Welfare States pursue demeaning, wastrel policies as if there literally were no tomorrow.
Absent the 1,500-year Younger Dryas “cold shock” completed c. BC 7300, our current Holocene Interglacial Epoch would likely have ended about AD 450, coincident with the Fall of Rome. Now as Earth enters on a 70-year “dead sun” Maunder Minimum similar to that of 1645 – 1715, quite probably preceding a resurgent 102,000-year Pleistocene Ice Time, Climate Cultists’ decades-long sabotage of global energy economies will soon bear very bitter fruit.
In other unrelated news:
http://www.theaustralian.com.au/politics/gillard-slashes-mining-super-profits-tax-rate-to-30pc-to-end-war-with-resources-giants/story-e6frgczf-1225886962498
The Australian Government seems to be nearing a compromise on the new controversial mining tax. The number of resource industries to be taxed has been reduced to the following:
Coal, oil, gas and iron ore.
Anyone other than me see something interesting here? Basically the three fossil fuels and iron ore. Effectively the Australian Government is now angling for a direct carbon tax but on industry profits rather than a per tonne basis.
carrot eater says: July 1, 2010 at 4:09 pm
The unadjusted data give you the same result, globally.
Then why is it adjusted?
carrot eater says:
July 1, 2010 at 12:54 pm
rbateman
“If the adjustments cancel out globally, then what is the justification for adjusting?”
You didn’t necessarily know this would be the case, before you started going about doing the adjustments…..
______________________________________________________________________
“adjustments” should not be done period.
On the one hand we are told that “station moves, instrument changes…” require “adjustments” to the data for individual stations. On the other hand we are told that “homogenizing” the data by making up “adjustments” from stations up to 1200 km away or infilling data from surrounding areas to manufacture data for areas with no data is perfectly alright.
And yes I have done an analysis for my home state.
This is what I found:
I live in North Carolina and here is a quick look at my state. It is VERY interesting.
There is nothing closer to the mountains than Chapel Hill which is just west of Raleigh. All the areas with longitudes further west are also further south and that puts them on the seacoast. Chapel Hill is on the plains. Seems the mountain areas are no longer part of the record, imagine that.
I also found that at Wunderground the Moncure NC station is no longer available, it flips you to the new Sanford NC airport. It was available the last time I looked. Asheville NC is the big city in the mountains, home of the Biltmore Estate (1895) Its weather station now only goes back to 2005 at the AIRPORT of course. The site also directs you to the “nearby” (80 miles) city of Greenville (downtown) which only goes back to 1970. That site has been declared “unofficial” The “official” station is now the Greenville/Spartanburg, South Carolina (Airport)
Here is a quick look at the only city & close by airport listed for North Carolina. The city is on the North Carolina/Virgina border and right on the ocean. Take a look at the city vs the airport! Norfolk City and
Norfolk International Airport
The Raleigh North Carolina area is in the piedmont area of North Carolina. It is far from both the mountains and the sea coast. Here is an Elevation map and North Carolina map of cities
North to south thru the middle of the state
North – Raleigh NC
Large city in the middle of NC – Fayetteville NC
South – Lumberton NC
Coastal Cities:
North – Elisabeth City
South – Wilmington NC
Rural
North – Louisburg
North – Louisburg
South – Southport
South – Southport
Here is the raw 1856 to current Atlantic Multidecadal Oscillation Amazing how the temperatures follow the Atlantic ocean oscillation as long as the weather station is not sitting at an airport isn’t it?
Oh and one other thing. As a farmer I pay close attention to the weather. At Wunderground the temperatures of the day are always adjusted up when I look at the previous day’s information. When you get up at dawn each day and check the weather it becomes pretty darn obvious the data is “adjusted” when the freezing morning weather from yesterday, that left ice on the livestock tanks, is reported the next day as a “minimum temperature” that was above freezing.
And some prominent commenters are playing up the alleged increase in global temperature this spring and sweeping under the rug last northern hemisphere’s colder than normal winter.
This post is evidence that confirms my suspicions that one can’t rely on reports that temperatures are “warmer” this spring world-wide.
The global carbon taxers are desperate and more willing to manipulate the data than ever.
“On the issue of adjustments you find that these have a near zero impact on the all Australian temperature because these tend to be equally positive and negative across the network (as would be expected given they are adjustments for random station changes).”
Do they send their data to JH for homogenization?
carrot eater says: “If the changes due to these were truly random, you could not bother making the adjustments, if all you cared about was the global mean. But it made sense for somebody to start doing adjustments, to check.”
True. But if that is the case, assessments of aggregate temperature trends should just use the unadjusted data.
The only sensible use of an aggregate of adjusted data would be to demonstrate no statistical bias in the adjustments (when taken in aggregate).
On that logic, the approach of GISS and others still appears to be incorrect. They are using the wrong data. And my guess is that it would probably be quite simple for them to substitute unadjusted data into their methods (or to turn-off the adjustment steps if it is embedded in their code).
It would make sense for somebody to step into the “gap in the market” to publish an aggregate of the unadjusted data. It would also be interesting to see whether the other producers agree with the new series …. or more to the point, their reasoning if they have any issues with it.
Shows the importance of open source raw data with transparent reporting on weather station issues both now and in the past.
Jordan:
You perhaps don’t realise it, but for everywhere except the US, GISS takes as its input the unadjusted data. It then applies only one adjustment*, and that is to impose on ‘urban’ stations the trend of its ‘rural’ neighbors. That is the only adjustment that GISS itself does. ‘Urban’ and ‘rural’ are currently identified by how bright the areas are at night in satellite images; you can argue whether that’s the best way.
Here you can see the effect of not doing that adjustment, vs doing that adjustment:
http://clearclimatecode.org/gistemp-urban-adjustment/
Keep in mind that for this graph, for a small section of the global land mass (the US 48), the ‘no adjustment’ series does include adjustments previously made by NOAA. For the entire rest of the world, there is no adjustment at all at any point, in the ‘no adjustment’ series. *Well, OK, with the exception of 2 oddball stations, St. Helena and Lihue.
“True. But if that is the case, assessments of aggregate temperature trends should just use the unadjusted data.”
Why? The adjustments are done for a reason – to remove spurious issues from the raw data that are not related to climate. For GISS, the attempt is to remove UHI. For NOAA, the attempt is to remove the effect of station moves, etc, and the new method they’re currently testing may (or may not) also be effective for UHI (we shall see when it’s released). So if you think your adjustments are done well, then it makes perfect sense to publish the overall results with them in there.
It just so happens that the adjustments have little effect on the overall result (as copiously documented by Zeke at Lucia’s, among others), looking globally, and that’s partially due to some of the spurious issues being random in their effect (for NOAA), and in the case of GISS, it’s because the original raw dataset simply doesn’t have a ton of urban stations that warmed much more quickly than their rural neighbors.
Note the obfuscation in carrot eater’s definition of what “raw” data is.
Unadjusted is not raw.
DR:
‘unadjusted’ is simply the raw daily or hourly data, converted into monthly means.
RACook
“False. And false. Hansen (GISS) fought for years to avoid releasing ANY data even under repeated FOIA lawsuits. They still hide raw data. They still hide their conversions and their code, but have released “some” code. Under protest. We don’t know how they refuse to release, nor whether what is released is actually used.”
None of your response is based in any reality.
People have taken GISS’s published code, run it for themselves, and recovered the same results as GISS’s published results.
People (clear climate code) have taken GISS’s published code, read through it line by line, found a couple minor errors, translated into a different platform and made it easier to read, and.. recovered the same results as GISS’s published results.
People have taken the unadjusted data, written their own code from scratch that uses slightly different methods, and gotten about the same results (Zeke at the Blackboard, Tamino, Chad at http://treesfortheforest.wordpress.com/2010/05/19/better-late-than-never/, Nick Stokes).
People have even taken an entirely different source of unadjusted data (daily temperature means, instead of monthly temperature means), and gotten about the same result (http://rhinohide.wordpress.com/2010/06/29/gistemp-with-gsod-round-2/)
I’m sorry, but there’s simply no conspiracy here.
Oh, by the way: As for the claims of Watts, d’Aleo and EM Smith that global warming is at least in some part an artifact of an intentional station drop-off at 1990 – that claim has already been comprehensively refuted by several people, but Ron’s work at http://rhinohide.wordpress.com/2010/06/29/gistemp-with-gsod-round-2/ takes it one step further, by using a different source data set that has no station dropoff at 1990. His source set has a high number of stations since 1973. His analysis is still preliminary, but the station drop-off conspiracy meme is as dead as can be.
I can tell you one thing, raw or not, it’s COLD in Sydney’s inner west! No question! A 61 year cold low record for June. There is no conspiracy there. Shame I am gassing myself on CO emissions because, in Australia, it’s always warm (No need for flued gas heatring, just vent into the living space. So 1950’s).
Until it was so clearly demonstrated in the commentary chain for this post, I had not realized eating carrots could lead to such severe myopia…….. and cognitive suspension of reality.
It’s Just Weather: 55F and raining, here in western Washington state. 12F (7C) below ‘normal’, as has been most of the last month and much of the spring. Our Global Warming/Carbon Tax Governor, Christine Gregoire, is petitioning the O’blame-a administration for ‘federal disaster relief aid’ because the winter and spring have been so ‘unusually cold and wet’, causing about 40% of the fruit crops to fail. Late frosts combined with continual cold rains caused poor pollination and fruit development. Note that both ‘correlation’ and ‘causation’ are established firmly.
Do you suppose Governor Gregoire is a carrot eater also?
Mac the Knife says:
July 2, 2010 at 8:51 am
Until it was so clearly demonstrated in the commentary chain for this post, I had not realized eating carrots could lead to such severe myopia…….. and cognitive suspension of reality.
Do you suppose Governor Gregoire is a carrot eater also?
_______________________________________________________________
I do not know but I think Rabett is.
It’s been comprehensively shown by several independent workers that the results of GISS and NCDC can be replicated, both using GISS code as well as written-from-scratch code, using both GISS algorithms as well as independent algorithms, using completely unadjusted data, and even using a completely different data set.
There is no conspiracy in any allegedly hidden code, there is no conspiracy in the adjustments, there is no conspiracy to drop stations to artificially bring about a rise in temperatures. No, no and no.
Your response to that is to note that it happens to be cold right now wherever you happen to live, and then accuse me of myopia?
Interesting.
I think carroteater has the best of this lot. As a skeptic, I question, challenge, prod and poke at, but ultimately go with the evidence.
So it appears that the several conspiracy theories just don’t hold up. And it’s pretty low to reply to reasoned discussion with the ‘myopia’ line!
Does the raw or ‘High Quality” data from this data set go to GHCN?
What is the case for other records sent to GHCN outside the U.S.?
DR:
It should always be the raw that is sent for the GHCN. I always have trouble finding my way around the Aussie BoM website, but you should be able to confirm that for yourself if you can manage to find the raw data on the Aussie page, and then compare it to v2.mean.
The GHCN specifies that it only picks up data if it can find the unadjusted version. NOAA then does its own adjustments. I think CRU is a bit different in this regard, and has accepted data that has already been adjusted by the providing country.
Somewhere on the BoM page, you should also be able to find station histories, which would give the reasoning behind the various adjustments for the stations in Victoria. Somewhere.. I know I’ve seen these for Australia, but never know what to click to find them.
OK. All of you fools. On both sides. Listen up! You can chit your chat for whatever you “think” is happening re: global climate. If you think humans are causing it, I pity you. If you think you can change it, I pity you even more. If the Earth is warming, its because of the Sun. If the Earth is cooling, its because of the Sun. God help us if any of you think there is a political solution (oxymoron) to this. This might be too religious for some of you!
[REPLY – We have some Sun Worshipers around here. But we also have our share of Sea Witches. And land use or “dirty snow” (etc.) may well account for some of it. We know the heat comes from the sun, but there is quite some dispute over whether the changes in TSI (or UV or whatever) are enough to account for the temperature change. It’s all in the delta, or lack thereof. (And we don’t even really know how great that change has been, considering the pitiful state of the historical records and the climate stations, themselves.) ~ Evan]
carrot eater says:
Oh, by the way: As for the claims of Watts, d’Aleo and EM Smith that global warming is at least in some part an artifact of an intentional station drop-off at 1990 – that claim has already been comprehensively refuted by several people,
No, it hasn’t. Folks have done a rather crude comparison of bulk station averages at one span of time and asserted that means they stay the same in other periods of time. They don’t. Take stations in a cold excursion in cold places (such as a cold PDO) and you get cold results. That’s the “baseline”. Then change to warmer stations in warmer places during the warm phase of the PDO, that’s the “warming”, now repeat endlessly that it will stay warmer, even as the snows fall…
The “problem” is that the range of a station at, for example, Reno will have a greater downward run during a cold time than during a warm time. And SFO will never have that kind of excursion to the low side. Have Reno “in” during the cold, then out during the next cold with SFO instead, and you can never recapture that low excursion.
And all the hand waving about gross averages will never ever find that fact. Nor do they prove anything.
Oh, and do remember that GIStemp uses one set of thermometer in the baseline and a completely different (AND warmer due to the dropped stations…) set in the ‘present’ for creation of the grid/box anomalies. It is NOT station to self anomaly creation. So don’t waste your time bleating about how ‘anomalies will save you’ as you are not using proper anomalies.
I normally just ignore C.eater as a waste of time, but a direct claim about me was made.
Oh, one other point, I’m working on an interesting example of the impact of The Great Dying of thermometers. I’ve found a source from some data on stations that were left out. Comparison with stations that were kept shows the left out stations NOT warming while the kept ones do. That will not show up in the analysis done by other folks when they do “kept & tossed up to 1990 vs Kept Only” after as the after 1990 data for the tossed are not there for comparison. I can’t yet say WHY they diverge, but they do. (At this point I’m suspecting either a coincident equipment change or a change of processing, but there are other possibilities). The bottom line, though, is that I have in hand example cases of “kept” rising in a 1990 hockey stick and tossed from nearby not rising so.
So you can claim to have proved a negative all you want. I’ll stick with the existence proof I have in hand. (And no, I’ve not published it yet. It takes a fair amount of work to hand transcribe the data from the forms and make a comparison, one station at a time. If only I had some Big Oil Money I could hire clerks and go a lot faster, but such massive funding is just like the rest of the warmers claims. Nowhere to be seen in the real world.)
EM Smith
You’re wrong on pretty much every count.
“No, it hasn’t. Folks have done a rather crude comparison of bulk station averages at one span of time and asserted that means they stay the same in other periods of time. They don’t. Take stations in a cold excursion in cold places (such as a cold PDO) and you get cold results. That’s the “baseline”. Then change to warmer stations in warmer places during the warm phase of the PDO, that’s the “warming”, now repeat endlessly that it will stay warmer, even as the snows fall…”
I don’t think quite grasp all the work that has been done. People have made temperature histories using only those stations that are continuous through the drop-off period you were so worried about. Using only those continuous stations, you still get the same result. What does that tell you, EM Smith? No switching of stations. Same result. As for the ones that did drop at 1990? Up to that point, also the same result. You want to tell me that those two subsets tracked each other fine until 1990, and then suddenly diverged when nobody was looking? What evidence do you have for that?
But in case you were worried about what those stations did, when nobody was looking, people have even used non-GHCN data sources (GSOD and ISH) that don’t have the 1990 station drop-off at all – data sources with a large station count through that whole period .. again, same result; nothing weird happens at 1990. What does that tell you?
And for the nth time, ‘cold’ and ‘warm’ don’t matter in the calculation you’re talking about. Only ‘cooling’ and ‘warming’ do. The offset used when combining stations completely eliminates any memory of what was ‘warm’ and ‘cold’.
“Oh, and do remember that GIStemp uses one set of thermometer in the baseline and a completely different (AND warmer due to the dropped stations…) set in the ‘present’ for creation of the grid/box anomalies. It is NOT station to self anomaly creation. So don’t waste your time bleating about how ‘anomalies will save you’ as you are not using proper anomalies.”
And you still don’t understand how GISTemp calculates anomalies, and it appears that a lot of your difficulties stem from that. On your website, you recently tried to work out a toy example of how GISS does it, and got it horrifically wrong. That was here,
http://chiefio.wordpress.com/2010/03/14/why-temperatures-matter-vs-anomalies/#comment-3881
You can see how the method actually works (and yes, the published paper and the code both do the same thing) here
http://rankexploits.com/musings/2010/not-so-spherical-cows-more-toy-problems/
at comments 38192 and 38195
When you actually understand how the RSM works, you can implement it and get results consistent with the CAM. Did you ever stop to consider that only GISS uses the RSM, but they still track CRU and NOAA anyway?
And also, by the way, I don’t think ‘baseline’ has the significance in the RSM (GISS’s method) you think it does. When combining stations, you use the entire period of overlap, not a fixed baseline.
Carrot Eater
It is quite one thing to replicate (repeating analyses to get the same result) and undertaking a forensic examination to understand where problems might lie and if they can cause a significant effect. I can dredge up the old “If you do what you’ve always done, you’ll get what you always got”
Remind me – what are we talking about in terms of warming – 0.6-0.8 deg C? So something that causes >0.1degC difference on average must be taken seriously (see here). Most people are looking at current temperatures, and they are looking at averaged temperatures (yes I know – spatially weighted). It turns out the difference is in the older temperatures, and when the spatial distribution of this is examined the differences are even greater (see here) – there is a big difference with lattitude. Don’t even get me started on adjustments.
Now that is where the warm and cold come in as different latitudes respond differently to the natural cycles in the climate (if you plot the GISS numbers here) “Cold” places (altitude as well as lattitude) show greater natural variation in temperature than “warm” ones in terms of amplitude. If we have been warming for a long time with cold stations present they will provide a large amplitude positive anomaly, then if we drop them as we start to cool this can have an effect of bias as ‘warm’ stations have a smaller amplitude variation and therefore anomaly. This is a concern.
And talking of anomalies, in the example you referenced, E.M.Smith was taking the trouble to answer the question “..what does an anomlily mean in layman terms?” [sic]. He did so simply and not ‘how GISS does it’. As for his understanding of it, do you think that with all the disucssions that have gone on that he really misunderstands it (still, if he ever did), or that perhaps he has been unclear or misinterpreted in what he has said about it and has just not been bothered to counter the ad homs tossed in his direction? He is clearly someone who has all the necessary skills and intelligence to do so and is not so concerned about what others think that he wastes time on such distractions.
Doesn’t it concern you just a little that we’ve had all these stories (with photos and eyewitness evidence) of ice melt in the arctic in the past and that we might be spending billions on something that is natural and cyclical?
“So something that causes >0.1degC difference on average must be taken seriously”
I have no idea what that graph is, seeing as it doesn’t have a descriptive title or caption. What are you trying to show?
“Don’t even get me started on adjustments.”
Go ahead, start on them. They have little effect on the global mean.
“If we have been warming for a long time with cold stations present they will provide a large amplitude positive anomaly, then if we drop them as we start to cool this can have an effect of bias as ‘warm’ stations have a smaller amplitude variation and therefore anomaly. This is a concern.”
In case you haven’t noticed, a multitude of bloggers have built up a temperature record using only continuous stations. No dropping of stations. On top of that, there are now a couple analyses that use a more complete set of stations, again with no drop-off in numbers at 1990. The results are consistent with the published ones.
The way you could get a bias through station drop is if you lost stations that had markedly different trends from their neighbors in the same grid box. But after doing analysis with data sets that don’t have station drop, and you get the same thing.. what does that tell you?
But at least your description is getting better than where it started, which was the naive idea that dropping cold stations makes it appear warmer, just because they were cold, informed by endless series of irrelevant graphs showing absolute temperatures averaged together.
“And talking of anomalies, in the example you referenced, E.M.Smith was taking the trouble to answer the question “..what does an anomlily mean in layman terms?” [sic]. He did so simply and not ‘how GISS does it’.”
Whatever he was trying to show, it does not correspond to what anybody does. What he did was nonsensical. So no, it was not a simple demonstration of what anomalies are.
“As for his understanding of it, do you think that with all the disucssions that have gone on that he really misunderstands it (still, if he ever did), or that perhaps he has been unclear or misinterpreted in what he has said about it and has just not been bothered to counter the ad homs tossed in his direction? He is clearly someone who has all the necessary skills and intelligence to do so and is not so concerned about what others think that he wastes time on such distractions.”
I have seen no evidence that he understood how GISS does it. He continually says GISS is somehow not ‘saved’ by anomalies because it doesn’t calculate anomalies at each station against itself. He’s never (that I’ve seen) explained how GISS actually does do it, or how he thinks that leaves it prone to not being ‘saved’. If he has ever clearly explained his thinking on this, please point it out. The reference station method is really not that difficult. On the other hand, he’s claimed that the GISS code doesn’t do what’s in the papers, when it very much does. And anyway, CRU and NOAA use roughly the same data source, but not the RSM, and still get consistent results… what does that tell you about the RSM vs the CAM, and whether it matters here?
And he might waste a little less time if he actually looked at the work done by others. Those aren’t distractions.
As for ad homs, you might consider the contents of this:
http://wattsupwiththat.com/2010/01/26/new-paper-on-surface-temperature-records/
I wonder if the authors still stand by the accusations made therein. They have not stood up.