From Alan at Appinsys, who emails that he was inspired by this story on WUWT: A spot check on NOAA’s “hottest so far” presser
“NOAA: June, April to June, and Year-to-Date Global Temperatures are Warmest on Record”
The following figure from NOAA shows the temperature anomaly of January – June 2010 compared to the 1971-2000 base period for 5×5 degree grids [http://www.noaanews.noaa.gov/stories2010/20100715_globalstats.html]
The problem with the above map: data quality and data manipulation.
The following sections provide some spot checks on the areas of the world exhibiting the most warming according to NOAA. The gridded historical data graphs shown in these sections are from the Hadley CRUTEM3 database for January – June. (CRUTEM3 uses a 1961-1990 base period whereas the NOAA data above is for a 1971-2000 base period. This simply shifts the anomalies on the vertical scale, but does not affect the relative trends.)
It is clear from the following sections that NOAA performs manipulations to create false impressions from the data, including assigning temperature increases were there is zero data.
Spot Check – Northern Africa
It is apparently much hotter than usual in the Sahara. But where is the data? Several of the 5×5 degree grids have zero stations (indicated by the black arrows). Many of the others have one station with very limited historical data. There seems to be an inverse correlation between the number of stations and warming – more stations in a 5×5 degree grid and less warming is observed.
The map figure above shows the location of stations in the NOAA GHCN database (blue G or green B icons) and the red 5×5 icon indicates whether data exists in the Hadley CRUTEM3 database – a 5×5 degree gridded database used by IPCC (plotted at http://www.appinsys.com/GlobalWarming/climate.aspx). The grid lines are 5×5 degree grids.
In many of the 5×5 degree grids showing 4 degrees warming according to the NOAA map, there are only one or two stations. The figure below shows some of the “hot-spots” in the NOAA map displaying January – June average temperature anomaly from the Hadley CRUTEM3 database for 1900 – 2009. In no cases is the warming close to what NOAA indicates.
There is a severe problem with lack of historical data in Africa as well as lack of coverage and gaps in the data. NOAA’s algorithms spread the low quality data across areas that have no data as well as showing warming that isn’t really there.
One must really question the NOAA data when even the areas with many stations seem misrepresented. The following figure shows the area of eastern Turkey which has many stations and shows no warming in Jan-Jun through 2009, but suddenly according to NOAA has 4 degrees in 2010.
Spot Check – Greenland
It is apparently much hotter than usual in Greenland. But where is the data? Most of the 5×5 degree grids have zero stations (only some of which are indicated by the black arrows). Most of the grids with data have one station. The two hottest spots on the NOAA Greenland area show 5 degrees warming and have no data.
Some of the Greenland stations have long-term data. The figure below shows some of the “hot-spots” (that actually have data) in the NOAA map displaying January – June average temperature anomaly from the Hadley CRUTEM3 database for 1900 – 2009.
Spot Check – Canada
It is apparently much hotter than usual in Greenland. But where is the data? Most of the 5×5 degree grids have zero stations (only some of which are indicated by the black arrows). Most of the grids with data
Historical Context
Many parts of the world do not have data for the first half of the 20th century. Without this historical context it is easy to create misleading impressions.
Northern Africa: A lack of historical context. The warming of 1 – 2 degrees since the base period is without historical perspective. This lack of history gives the false impression that the warming is significant.
Greenland: The historical context shows that warming and cooling by several degrees is not without precedent. Recent warming is less than the 1930s. The statement of warming since the 1980s gives the false impression that this is unprecedented.
Canada: Many stations in northern Canada are no longer maintained in the GHCN or CRUTEM3 databases. Warming has been 4 degrees over the last 40 years according to NOAA. The historical context shows similar warming in the 1930s (graph shown previously).
Recent warming in Canada correlates to the El Nino Southern Oscillation (ENSO). The following figure compares the Jan-June temperature graph shown previously for northern Canada with the multivariate ENSO index (from http://www.esrl.noaa.gov/psd/people/klaus.wolter/MEI/).
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Go easy on NOAA folks. They know that climate is complex and requires numerous mathematical tricks to make it understandable.
i don’t find it surprising that they’ve used imaginary numbers:)
Once again why is a 30 year average used for the baseline? Naturally it’s going to skew the data just like it will 30 years from now when the earth will begin to cool at an alarming rate because the previous 30 years were warmer than the previous 30 year period before that. Folks this is all about getting research money from the government. 30 years from now scientists will be trying to get research money to figure out why the temperatures have become dramatically cooler than the previous 30 year period.
If you want to know whether or how the climate is changing, you have to plot anomalies – i.e. the amount and sign of change (in this case, of temperature). In order to do that you have to have a baseline to compare the current figures against. It doesn’t actually matter what baseline you choose – you’ll still see the trend (i.e. whether it’s rising, steady or falling) whatever you choose as a baseline. The choice of baseline doesn’t ‘skew’ the data at all. It’s arbitrary.
All of the red dots in and around New Zealand are clearly smaller than a 1°C dot – most of them substantially smaller. Anyone can see that. The nearest 2°C dot is somewhere around Tibet. Look again.
The NOAH area averaging algorithm is statistically dreadful. There are large swaths with no records which are filled in by interpolation. Or a single station can cover 90,000 square miles. Plus there is no historical data for the oceans until very recently. Readings from ships hundreds of miles apart do not constitute a temperature station.
This is well known in the field, but NOAH has always ignored the resulting uncertainties, which are huge. They used to report the global temperature in thousands of a degree, which I jumped on them for 15 year ago and they quit, or I think they did. My view is that it is not accurate to even a tenth of a degree, perhaps not to an entire degree. This easily explains why these surface statistical models (for that is all they are) do not agree with the satellite readings.
However, there is no reasonable interpolation algorithm in this context that gives higher values on interpolation than are found in the actual data. There may be a Data Quality Act issue here. Someone should file a formal complaint.
Icarus says:
July 17, 2010 at 7:30 pm
“[…]location doesn’t seem to have any bearing at all on the anomaly for June 2010. Why should it? Is the author arguing that it couldn’t possibly have been 4C above average in the Sahara last month just because it wasn’t 4C above average in the same place in Jan-Jun 2009? Doesn’t seem to me to hold water.”
So you are defending inventing data where none was measured?
According to satellites (UAH), http://vortex.nsstc.uah.edu/data/msu/t2lt/uahncdc.lt
Both June and first half of 1998 was varmer than 2010
Mean global temp anomaly:
Jan-June 2010 = + 0,56 deg C
Jan-June 1998 = + 0,64 deg C
June 2010 +0,44
June 1998 +0,57
Icarus says:{July 18, 2010 at 8:26 am}
“If you want to know whether or how the climate is changing, you have to plot anomalies – i.e. the amount and sign of change (in this case, of temperature). In order to do that you have to have a baseline to compare the current figures against. It doesn’t actually matter what baseline you choose – you’ll still see the trend (i.e. whether it’s rising, steady or falling) whatever you choose as a baseline. The choice of baseline doesn’t ‘skew’ the data at all. It’s arbitrary.”
However, in the first chart NOAA is not showing a trend it is showing a specific temperature anomaly against a particular base period. So it does matter in this case. It doesn’t matter if June 2010 is X number of degrees above or below an arbitrary base line. Change the base line and the June 2010 temp anomaly goes up or down accordingly.
Dirk H: You rather evaded the issue there. How do Jan – Jun 2009 temperatures cast doubt on June 2010 temperatures?
To answer your question though, temperature anomalies generally pertain over a large area, which is why some extrapolation and interpolation is justifiable. If you have a 1°C anomaly at two different stations 300 miles apart for June 2010, it’s unlikely that a point in between these two stations will have had a dramatically different anomaly for that month. This is a matter of observation, rather than ‘inventing’ data. Clearly there are many parts of the world where good weather records are closely spaced, so this observation would seem to be reliable. It makes sense if you think about it – heat waves or cold spells generally cover large areas, many hundreds of miles across, not just a few miles.
Tom in Florida wrote:
I take your point. However, they do have to measure the anomaly against *something*. What would you choose, and why?
If you look at the map. What’s basically Louisiana (though obviously covers other styates, show what looks like either an increase of 3 or 4 degrees.
Yet when you punch in Louisiana on NOAA’s climate at a glance. Since 1895 the trend has been a negative (-) .01F/decade. Looking at the region. Year to date is a whopping .04/decade. And this year is below the mean.
Which math are they using?
danbo wrote:
The map doesn’t use 1895 as a baseline, it uses 1971 – 2000. That’s probably the mistake you’re making.
Icarus says:
July 18, 2010 at 2:34 pm
“[…]anomaly for that month. This is a matter of observation, rather than ‘inventing’ data. Clearly there are many parts of the world where good weather records are closely spaced, so this observation would seem to be reliable. ”
Bollocks. It’s Hansen pseudoscience.
DirkH says:
July 18, 2010 at 3:40 pm
“Bollocks. It’s Hansen pseudoscience.”
And i know i won’t convince you, Icarus, because you’re one of Hansen’s stooges, but let’s just show your fanastical thinking for what it is by mentioning the Bolivia Effect:
http://chiefio.wordpress.com/2010/01/08/ghcn-gistemp-interactions-the-bolivia-effect/
just as a service for people who drop by accidentally and don’t know about what kind of magical fantastical mockery of science that Hansen does there with GISTEMP we’re talking.
The mistake seems to be else where. The numbers for the last six months, (according to NOAA) a little more than a degree below normal. I guess climate didn’t exist before 1971. “Ever” only goes back to 1971.
Icarus says:{July 18, 2010 at 2:40 pm}
“I take your point. However, they do have to measure the anomaly against *something*. What would you choose, and why?”
I certainly wouldn’t attempt to say any single month is X or Y degrees different than an arbitrary base line. I wouldn’t bother to report about calendar monthly anomalies at all. In fact I wouldn’t bother with global average temperatures at all either. I would accept the fact that climate changes and that adaptation is the best way to deal with it.
I don’t suppose this map and the timeframe the “analysis” picks has anything to do with the next climate-junko-fest, which is coming up shortly, somewhere nice and warm (with the aircon tuned off) like Cancun?
And anyone who states that it does not matter what baseline period you use for your anomaly calculation is a complete buffoon. Try taking the 1930s as your baseline and see what a difference that makes.
All of the red dots in and around New Zealand are clearly smaller than a 1°C dot – most of them substantially smaller. Anyone can see that. The nearest 2°C dot is somewhere around Tibet. Look again.
I looked again. Now, instead of thinking the map was wrong I just don’t know how to read it at all.
I can’t tell what sized dot is used over the South Island of NZ. I had assumed that each dot size went up in 1°C units. Apparently not. Apparently we are meant to try and read the size of the dots off a non-linear scale at the bottom. Mental!
Humans are shockingly poor at reading non-linear scales like this because people count by area of dots, not radius. So a dot twice as big looks four times as big. To use intermediate size dots on top is just crazy.
I teach Maths. I would fail this graph if it was presented by a 14 year old. It is totally and utterly useless (except perhaps as a propaganda tool). It is both misleading at first impression and unable to be read accurately with closer inspection.
Mooloo wrote:
I wouldn’t say it’s *completely* useless. It was clear to me, for example, that the area around New Zealand saw less than 1°C anomaly and that there was a more than 3°C anomaly in much of central Asia. As an overall impression for the whole planet it’s not *that* bad.
An alternative way to present the data which is used in more detailed reports (rather than ones intended for the popular media) is the kind of graph where the grid squares are colour-coded (different colours for each °C of warming/cooling). Those are probably better if you want to get a more precise figure for a particular area, but perhaps not so good if you want a quick overall impression of warming vs cooling.
What kind of graph would you choose to give an at-a-glance impression of anomalies, given your expertise in this area?
Tom in Florida wrote:
Well how would you know how to adapt if you didn’t know how (or even whether) it was changing?
The honest way to present these grid estimates is with vertical bars. There is a fun book entitled “How to Lie with Statistics” that specifically address using misleading non-linear graphics like this. Written in the 1950’s, it is still in print, for obvious reasons.
But the underlying fallacy is simply taking these rough estimates as in any way accurate. The complex area averaging method is full of well known problems, yet the estimates are taken as accurate by the advocates. They are not accurate. You cannot derive an accurate estimate of global atmospheric temperatures from the existing historical record. The data is simply not representative and no amount of extrapolation and interpolation can make it so.
The “hottest June on record” story is currently the headline story on CNN dot com…..in their other top stories they report on the deadly freeze gripping Argentina. You gotta love the irony factor.
http://www.cnn.com/2010/WORLD/americas/07/19/argentina.cold.snap/index.html?hpt=T2
Icarus says:{July 19, 2010 at 4:42 am}
“Well how would you know how to adapt if you didn’t know how (or even whether) it was changing?”
Humans have already adapted to the wide variety of climates that exist on our planet. We live in cold, hot and everything in between. Keep in mind that annual temperature swings are greater than any proven, predicted or modeled change in “average world temperature”. For that matter, so are daily temperature swings. It doesn’t matter if the climate changes to warmer or colder. I can heat my house to 72 F in winter, and cool it to 72 F in summer if I so desire. We have the technology to handle it either way. The real issue is can we do it cleaner and more efficiently. Clean water and air are much more important than trying to manage a mythical average world temperature.
There are three of scenarios we can do nothing about.
First would be a large, rapid and unpredicted change in our Sun (very unlikely).
Second would be a major hit by anything from space (very probable).
Third would be the return of glaciation due to orbital parameters (will most likely happen).
Will current plans for spending vast amounts of time, money and resources on climate change help us in any way prior to any of these three scenarios happening? NO.
Will redirecting these vast amounts of time, money and resources to reducing real air and water pollution help us in any way prior to any of these three scenarios happening? YES.
So I go back to my original statement that “I wouldn’t bother to report about calendar monthly anomalies at all. In fact I wouldn’t bother with global average temperatures at all either.”
“In most endeavors, accurately predicting the course of an incredibly complicated phenomenon such as global climate — and doing so over a 30-year period — would build considerable credibility. But not in this case. The debate over global warming has become mostly political, not scientific, and in a political debate actual facts, data and expertise can be of sadly little consequence. In fact, as the science becomes more and more solid, and as the Earth gets warmer and warmer, many of those who desperately need to deny what’s happening have abandoned the pretense of science and begun to seek shelter behind bizarre conspiracy theories.”
Even warmest six months on record can’t puncture denialists’ fantasy
I am of the opinion the merging (via http://www.ncdc.noaa.gov/oa/climate/research/Smith-Reynolds-dataset-2005.pdf )of the Land and SST datasets gives a significant warming bias…based anomaly dot map changes…