AcuuWeather meteorologist Joe Bastardi has a question about two datasets and asks: If it is darn warm, how come there is so much sea ice?
Bastardi asks a simple question: how can we have above normal temperatures in the Arctic and the Antarctic and continue to add to the global sea ice trend? After all we’ve been told by media stories that both the Arctic and the Antarctic continue to melt at a frenetic pace. But it looks like this year we’ll see another Arctic recovery as we’ve seen in 2008 and 2009.
Bastardi also wonders about something we routinely ask about here at WUWT: data adjustments. GISS seems to be stuck with Arctic positive anomaly, yet the sea ice isn’t cooperating. Of course just having a positive temperature anomaly doesn’t guarantee melt, but members of the public who are less discerning, who look at red hot color presentations like GISS puts out, usually can’t tell the difference.
For reference here are the images Joe uses in his presentation. I’m going to help out a bit too with some simple comparisons.
First The GISS Dec-Feb 2010 Global Surface Anomaly as Joe presents it in his video:
Note that in the warmest places in the Arctic according to GISS, there are few if any land thermometers:
Above: map of GHCN2 land stations (thanks to commenter Carrick at Lucia’s)
Note the cross section of the GISS data, most of the warmth is at the Arctic where there are no thermometers. The Antarctic comes in a close second, though it has a few thermometers at bases on the perimeter of the continent plus a couple at and near the center. Note the flat plateaus are each pole.
The effects of interpolation become clearer when you do a 250 km map instead of 1200 km:
All of the sudden, the hot Arctic disappears. It disappears because there are no thermometers there as demonstrated by the cross section image which stops at about 80N.
Interestingly, the global surface anomaly also drops, from 0.80°C at 1200km of interpolation to 0.77°C with an interpolation of 250km.
One of the things that I and many other people criticize GISS for is the use of the 1951-1980 base period which they adopted as their “standard” base period. That period encompasses a lot of cool years, so anomalies plotted against that base period will tend to look warmer.
This famous GISS graph of surface temperatures from weather stations, shown worldwide in media outlets, is based on the 1951-1980 period:
Uncertainty bars (95% confidence limits) are shown for both the annual and five-year means, account only for incomplete spatial sampling of data.”]
GISS doesn’t provide a utility to replot the graph above with a different base period on their webpage here http://data.giss.nasa.gov/gistemp/graphs/ but I can demonstrate what would happen to the GISS global maps using a different base period by using their plot selector here http://data.giss.nasa.gov/gistemp/maps/
Watch what happens when we use the same base period as the UAH satellite data, which is 1979-2009. The 1200km interpolated global temperature anomaly for Dec-Jan-Feb 2010 drops more than half to 0.38°C from 0.80°C. That number is not so alarming now is it? As for the graphic, the flaming red is still there in the same places because the anomaly map colors always stay the same, no matter what the absolute temperature scale is. In the first map with the 1951-1980 base period, the max positive anomaly was 6.4°C for 1200km and 8.8°C for 250km, while in the one below with the 1979-2009 base period the max positive anomaly of 7.1C If colors were assigned to absolute temperatures, this map would look cooler than it’s counterpart with the 1951-1980 base period.
And here’s the 250km presentation, note that the global surface temp drops to 0.34°C
So it is clear, with the GISS anomaly presentation, you can look at it many different ways, and get many different answers. Who decides then which maps and graphs with what base periods and interpolations get sent out in press releases? Jim? Gavin?, Reto? Consensus over coffee at Monks?
The answer as to what base period GISS chooses in temperature anomaly maps to present to the public is easily answered by looking at their main page here: http://data.giss.nasa.gov/gistemp/
Here’s a thumbnail of the page, and the full size version of the second graph from the top, note the caption on the top of the graph:
Clearly, they prefer the base period of 1951-1980 as the default base period for the public presentation [as well as 1200 km smoothing] and by choosing that, the GISS results look a lot more alarming than they might be if a different base period was used, such as the 1979-2009 period used by UAH and RSS.
Anomalies can show anything you want based of choosing the base period. For example, a simple thought experiment. I could choose a base period from 11,000 years ago, during the last ice age, and plot maps and graphs of today’s temperatures against that base period. Would we see red? You betcha.
Here’s a graph that shows reconstructed northern hemisphere temps at the end of the last ice age 11k years ago, they were about 4.5°C cooler than today. Granted it’s not a global temp, but close enough for government work.
So if I used a 30 year slice of temperature 11,000 years before the present as a baseline period, our GISTEMP map would look something like this:
Obviously the map above is not an accurate representation, just a visual guesstimate. The more excitable who frequent here will likely cry foul at my abuse of the image. But it does illustrate how choices of colors and baseline periods can have a distinct effect on the final visual. Using a cold baseline period in the past (in this case 4.5°C globally cooler than the present) makes the present look broiling hot.
Anomalies are all about the starting choices made by people. Nature doesn’t give a hoot about anomalies. Generally, people don’t either. Imagine if your local TV weather forecaster gave tomorrow’s forecast in anomalies rather than absolute temperatures. He might say something like:
It’s going to be a hot one folks! Tomorrow we’ll have a high temperature that is 0.8C warmer than the 1951-1980 historical baseline for this city. Dress accordingly.
Useful isn’t it? Even more useful if he’s the weatherman in Svalbaard and people anticipating a heat wave go out in shorts and tank tops in mid February.
While anomalies are fine for illustrating many things, including temperature, bear in mind it’s all about the starting conditions chosen by the individuals doing the analysis. It’s all about choosing a baseline “normal”, which is subjective.
So when Joe Bastardi looks at the GISS map of the world, sees red, and wonders why we have a growing ice presence, the answer is in the choice of baseline and the choice of colors used to calculate and represent the anomaly.
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
HumanityRules (22:46:58) :
I think that this was well written and should have elucidated some ideas for people who haven’t clued in to how charts are designed to make a point. The colours you have just admitted are important. However, trends are also important but the idea was that the trends are chosen… did you miss that?
Bastardi asks a simple question: how can we have above normal temperatures in the Arctic and the Antarctic and continue to add to the global sea ice trend?
And how can the dmi 80N be running at 1958-2002 baseline average all winter long and GISS be running a hot anomaly up there?
http://ocean.dmi.dk/arctic/meant80n.uk.php
GISS has fallen into a crater of imaginary magma.
This IS weak. I agree.
What is the point of the bit where he is going on at great length about the locations of thermometers. I really couldn’t figure out what he was trying to get at here. We have a perfectly accurate map of the `blob anomaly’ from satellite measurements which conforms to the shape above. So … ? Is he trying to claim some weird quantum effect whereby temperatures are not actually real unless someone whips out a thermometer?
And all the complaining about the choice of colours in the graph just seems like petty whining, and I’m an AGW skeptic! Does anyone here actually have trouble understanding the graph? The choice of red for hot and blue for cold is pretty usual isn’t it. I personally would find it very annoying if the colours were used the other way around.
The map is a map of an anomaly – a difference from average. It doesn’t pretend to be anything else. The red areas are experiencing above average temperatures for the time of year. The blue areas below. It isn’t rocket science. Which 30 year period you use as the baseline actually makes precious little difference to what the graph looks like. It might shift the colour bands just slightly, but it certainly won’t make the blob go away.
That is because the areas under the blob anomaly really ARE experiencing above average temperatures just as the areas which are blue on the map did indeed experience a colder than usual winter. The map is using honest data and displays a real effect.
A colour map of absolute temperatures wouldn’t tell us the same thing. You wouldn’t be able to look at it and see, for example, that yes indeed Europe and the continental US did have a colder than usual winter.
Surely anyone with a brain knows that above average for the north pole in winter just means it won’t freeze your balls off quite as fast as usual. Only idiots will imagine boiling hot arctic seas because of some red on a map, and who cares what idiots think.
This just seems … silly. I’d prefer to save my ammunition for situations where the data is not honest and where it is dishonestly displayed. I have no complaints with this map.
I fear we have a divergence problem. Best to employ Mike’s Nature Trick to “hide the decline”
All of the ice, snow and cold is due to unprecedented warming. The climate models predicted that it would get colder while it got warmer, and that snow in Florida was an inevitable consequence of the expanding tropics.
If it warms up about four more degrees as forecast by The Met office, we will no doubt have an ice age.
I would suspect that if their alleged AGW hypothesis had any validity the data would hold up at different resolution granularities.
It’s an excellent discovery that it falls apart. The questions have to do with why and how come and what the heck were they thinking?
Clearly scaling the data invents data to fill in in-between. While I’m not a statistics expert by any means it’s clear to me as a computer scientist and a systems scientist that you’d get bogus data when scaling. I do a lot of work with video compression and decompression codecs and this data issue a problem that is similar with scaling of images on decompression depending on the compression ratio. The higher the initial compression ratio the more resolution loss, data drops, distorted data, and importantly pixelation of data across vast areas of the imagery, not to mention the most horrific effect, the creation of data that was never there in the first place!
The climate data is similar to the decompression problem when the initial compression is high… the climate data is starting with incomplete data (no initial compression just a sparse set of geographic data spread across vast areas of a map of the Earth) and they are trying to build a complete image. Ha. Not possible. Just try compressing a video from Blue Ray HD1080P Resolution down to the amount of data that the climate folks are getting (in the above images from the article) and you have a major loss of information. Now take that chopped up data with high distortion (low numbers of data points) and attempt to construct the HD1080P image again. Not going to happen as there just isn’t enough data to even get a partial image let alone a 320p or 480p standard tv image let along a HD720p or HD1080p image! So the entire process that the climate scientists supporting the alleged AGW hypothesis is UTTERLY flawed from the get go. They just do not have enough data to construct a global image of climate without INVENTING DATA on the fly with their algorithms.
In layman’s terms, the climate data sucks. They don’t have enough stations to support the wild claims that they allege with their alleged AGW hypothesis. Epic failure on their part. Not only that, but a new angle from computer science image decompression falsifies their conclusions since information science teaches us that what you’ll end up with is INVENTED DATA not data from the original image (which in this case is the original temperatures in the many missing grid places).
In other words, an EPIC FAILURE of the alleged AGW hypothesis.
Thanks for the fantastic article. I hope that this comment gives someone another tool to do further analysis. I’m available to offer computer science or systems science expertise in this.
Now back to writing that high quality advanced video compression algorithm.
Oh, before I go it’s funny that Sharp has a new set of LCD TVs that actually add a yellow pixel to the set of Red, Blue and Green to achieve – they allege – better color. The cameras will also need this extra pixel color. So the computer and entrainment business are well aware of data pixel resolution issues but somehow climate science is still working in the bronze age of data measurements.
“The effects of interpolation become clearer when you do a 250 km map instead of 1200 km”.
Maybe that’s “The effects of interPOLARation …”.
New word to describe their desired outcome as a result of their alleged AGW hypothesis agenda bias… oh, pardon me, their mistaken process and erroneous outcome. [:)]
Does the grid matches with station data?
look at this one near north pole:
http://data.giss.nasa.gov/cgi-bin/gistemp/gistemp_station.py?id=431043120000&data_set=1&num_neighbors=2
Maybe the Arctic sea ice ‘recovered’ to some extent because it is winter.
Also there was this peculiar temperature anomaly distribution associated with a record low NAO index.
Likely all Arctic sea ice older than two or three years will be gone by September 2010. Because that, in reality, is the trend.
http://nsidc.org/images/arcticseaicenews/20091005_Figure5_thumb.png
Oh, while it might be technically correct to call it interpolation, with the amount of “interpolation” they are getting it’s more appropriate to call it fabricating the data. Whether that “fabrication” is fraudulent or not is a subject of a different investigation, as has been going on for some time.
Regardless, they fabricated climate data. They made it up. The proof was shown above.
If the alleged AGW hypothesis and the alleged science it rests upon is what passes as science I’d prefer to believe superman is real.
Pat – re Government’s withholding the dat.
New Zealand has all its data online at the MIWA site — you have to register but its free and anyone can do it. I believe Canada also has it online.
The anomaly vs ice debate becomes even more interesting when you look at the maps of where the “hot” anomaly is supposed to be and the current ice extent
http://nsidc.org/data/seaice_index/images/daily_images/N_daily_extent_hires.png
There is a bit on the eastern seaboard of Canada that is below the long term average, but most of the rest is just packed with ice.
Joe Joe Joe, you obviously don’t understand the science when you say;
‘If it is darn warm, how come there is so much sea ice?’
Look, its very simple. Very simple indeed. In fact its so simple I don’t know why you don’t understand. In fact it’s far too simple for me to waste my time having to tell you how ice can readily form even in an unprecedented heatwave.
Tell you what, rather than me having to embarass you by having to explain something so simple in public why dont you read AR5? Its all there. Believe every word written as its peer reviewed. Then you will see how simple the explanation is. Now, do you need help with any other problems?
tonyb
On first look there does appear to be significant inverse correlation between number of stations and alleged anomaly. I would hypothesize their fudge factor is incorrect.
Slightly OT, but today’s Times of London carries a story from the National Trust which claims a slightly hotter UK climate will see roses along with the traditional English garden depart forever and used paintings imagining a hot future to demonstrate!
Roses and other ‘traditional’ English flora flourish in many tropical and sub-tropical climes, but this is, of course, ignored by the National Trust which largely exists courstesy of the British taxpayer.
The “climate wars” is like a temperature “see-saw” with warmers and skeptics on each end.[warmers at the left]
Warmers want “their end to fall” to show an upward slope of the see-saw.[r to l]
Skeptics want “their end to fall” to show a downward or flat slope.
The trouble is ,none can really say where the fulcum is,what is earths NORMAL temperature.
Truth is there is a Natural Cycle of the “temperature” determined by Solar,orbit,comet,etc. that can never be influenced by man,or Mann.
A snail crossing the road of time does not know when a roadroller is coming
Obviously the satellite measurements were checked. They show distinctive cooling in the Arctic. Don’t they?
I have a question related to the GHCN2 land stations map. How come Turkey stands out as having an unusually dense network of surface stations in comparison with the much wealthier nations of Western Europe? In fact, it appears that Turkey is on par with Japan, the Eastern US, and Eastern Australia in terms of surface station coverage density. That seems quite remarkable.
Jay Currie (23:22:49) : I have wondered about the GISS and others use of baseline anomalies for a while. It struck me that you could do an anomaly calculation by adding a given station to itself.
I call that “selfing” after the botany ‘self fertilization’ jargon. I use a process that only compares the same months to themselves and that only compares the same thermometer with itself. So you start a thermometer at some point in it’s life ( say 1920 ) and that first December is a “zero” anomaly relative to itself. In 1921 you compare Dec 21 to Dec 20 and get the “delta” as the anomaly. In 1922 you compare to 21. Etc. So far this is much like First Differences. But if 1923 and 1924 were “missing data” F.D. would reset and take another zero ( also, the FD I’ve seen use an annual average and that “has issues” with missing months…) What I do is simply hold onto that 1922 value until I DO get a new valid December number. This preserves real trends better through data dropouts. All data past that first year are used and all dropouts (except a final ending one) are eventually “spanned” and the “delta” makes it into the file for further use.
So far it’s worked rather well. (It reproduced the National Geographic temperature graph from the 1970’s fairly well – modulo the different coverage areas of N.Hemisphere vs N. America)
In ‘running charts’ on various countries, I do not get a smooth or even a sin wave rising CO2 ‘signature’. Instead I find a lot of “hockey sticks” (often with a pivot / heel at 1990 ) and some very flat countries. Interestingly, some countries seem to have a manufactured “Dip” in the 1951-1980 baseline via adding and removing thermometers… The thermometer count line is symmetrical with the temperature “dip”.
So Korea is fairly flat:
http://chiefio.files.wordpress.com/2010/03/rokorea_hair.png
More Asia here:
http://chiefio.wordpress.com/2010/03/22/asia-a-gaggle-of-graphs/
From the Pacific Basin set we have Singapore with a nice “Hockey Stick”:
http://chiefio.files.wordpress.com/2010/03/singapore_full_hair.png
And in South America we have Uruguay where the “baseline” tops are about -1 C (lower than the before or after that touch 0 regularly) and has onset with thermometer count change:
http://chiefio.files.wordpress.com/2010/03/uruguay_full_hair.png
More South American graphs here:
http://chiefio.wordpress.com/2010/03/17/south-america-hockey-in-the-jungle/
And the rest of the Pacific Basin here:
http://chiefio.wordpress.com/2010/03/18/pacific-basin-the-australian-hockey-league/
I’ve seen enough cases where the “baseline” drops 1/2 C to 1 C just as thermometer count changes, then pops back up on another thermometer count change to suspect that the baseline may be ‘selected’ because it was cooler, but may have been ‘helped along’ (especially in some warmer places…) but a bit of thermometer selective listening skills…
Notice that very few to none of the common shapes in these graphs matches the expected smooth rise over time from “CO2 warming” nor the “cyclical ripple on the rise” from natural cycles on top of CO2 warming. They just look very “cooked” with common step function jumps at about 1980 and 1991 or so.
Oh, and on GIStemp: Realize they also use stations like Eureka Canada (that warm spot way up north) to “warm” 1200 km in all directions. So dropping a station 1000 km away on a glacier and putting in Eureka data instead can make for nice warming… IMHO. (Even if it’s “supposed” to be corrected, the correction is not perfect). Between a “cooked” baseline and broiled in-fill, GIStemp makes a roasted arctic when no such thing is happening.
‘So when Joe Bastardi looks at the GISS map of the world, sees red, and wonders why we have a growing ice presence, the answer is in the choice of baseline and the choice of colors used to calculate and represent the anomaly.’
If the color coding where used to highlight the Holocene Optimum, Roman Optimum and MWP anomalies, wouldn’t it show less “Redness” as we proceed into present time?
OT – Interesting post on the Register about the guy leading the CRU investigation: http://www.theregister.co.uk/2010/03/24/climategate_oxburgh_globe/
Well, I got to wondering just what temperature sensors we do have in the Arctic. It seemed to me that reaching out to 250 km, Hansen couldn’t be covering that much above 80°N … and it turns out he’s not.
Figure W1. Coverage of the area north of 80°N, showing 250 km radius areas around ground temperature stations.
Here’s your two miscellaneous factoids for today. A 1200 km radius circle is about the same size as the 80° N circle shown in the figure. It encompasses an area about three times the size of Alaska … and GISS is claiming that one single solitary temperature station is representative of that whole area.
Not.
OT: Predictably depressing UK government response to this petition:
“We the undersigned petition the Prime Minister to suspend the Climate Research Unit at the University of East Anglia from preparation of any Government Climate Statistics until the various allegations have been fully investigated by an independent body.”
Government response:
“The Government believes that all these allegations should be investigated transparently.
An independent review is currently examining the scientific conduct of the Climatic Research Unit (CRU) and is due to report its findings later in the spring. More information on the review can be found at: http://www.cce-review.org/. The University of East Anglia also recently announced that there will be a separate review to examine the CRU’s key scientific publications. The findings of both these reviews will be made public.
The House of Commons Select Committee on Science and Technology is also investigating the matter. On 1 March the Select Committee heard evidence from a wide range of contributors, including Professor Jones, who has temporarily stepped down from his post as Director of CRU.
CRU’s analysis of temperature records is not funded by, prepared for, or published by the Government. The resulting outputs are not Government statistics.
Our confidence that the Earth is warming is taken from multiple sources of evidence and not only the HadCRUT temperature record, which CRU scientists contribute to. The same warming trend is seen in two independent analyses carried out in the United States, by the National Oceanic and Atmospheric Administration (NOAA) and the Goddard Institute of Space Studies at the National Aeronautics and Space Administration (NASA). These analyses draw on the same pool of temperature data as HadCRUT, but use different methodologies to produce analyses of temperature change through time. Further evidence of this warming is found in data from instruments on satellites, and in trends of declining arctic sea ice and rising sea levels.
Science is giving us an increasingly clear picture of the risks we face from climate change. With more research, we can better understand those risks, and how to manage them. That is why the Government funds a number of institutions, including the University of East Anglia, to carry out research into climate change science.”
http://www.number10.gov.uk/Page22924
Anthony: The Zonal Means Plots above are somewhat deceiving because they have different temperature scales. A quick glance at the two plots show that the 1200km smoothing actually lowered the peak temperature at ~81N by about 1.3 Deg C. And as you’re aware, the area of the Arctic North of 81N represents very little of the Global Surface area–on the order of 1.5 to 2%–though it does have a much greater visual effect due to the projection used by GISS for their maps. The real curiosity in the two datasets is how the 1200km smoothing turns the zonal mean temperature anomalies of mid-latitudes of the Northern Hemisphere from negative to positive. Refer to the comparison graph of the two zonal mean datasets:
http://i40.tinypic.com/f4ldvd.png
Let’s also not forget that the Mercator projection skews area the further you go to the poles. If we looked at a polar projection, the visual torch basically goes away.
UK Government response to CRU petition
I’ve just received the response from the government on the CRU petition. http://www.number10.gov.uk/Page22924
Our confidence that the Earth is warming is taken from multiple sources of evidence and not only the HadCRUT temperature record, which CRU scientists contribute to. The same warming trend is seen in two independent analyses carried out in the United States, by the National Oceanic and Atmospheric Administration (NOAA) and the Goddard Institute of Space Studies at the National Aeronautics and Space Administration (NASA). These analyses draw on the same pool of temperature data as HadCRUT, but use different methodologies to produce analyses of temperature change through time. Further evidence of this warming is found in data from instruments on satellites, and in trends of declining arctic sea ice and rising sea levels.
So that’s all sorted then!