Hotness is in the eye of the beholder

I’ve mentioned before how chosen color schemes greatly influence how people see surface temperature data. Frank points out that sea surface temperature presentations suffer from the same problem. – Anthony

Guest post by Frank Lansner

This is no news – but still needs to be told. NOAA can in many contexts come up with the hottest temperatures available. Here we take a look at the European Sea Surface Temperatures as of 3 may 2010.

NOAA vs. UNISYS, SST, Europe. When I look at this compare, again and again I have to check if these SST are from the very same date, 3 may 2010. But they are. Differences are immense to an extend where it hardly makes sense to look after the European SST?
NOAA is hotter than UNISYS in for example these waters:

The Baltic Sea, The North Sea, The Caspian Sea,

And in addition,

The Black Sea has NOAA Approx. 3,5 K warmer than UNISYS, and

The NOAA hotspot area” North of Scandinavia: NOAA Approx. 4 – 6 K warmer than UNISYS .

Is there a valid sound simple explanation for these great differences?

In addition NOAA uses a colour scheme that makes Europe look as if surrounded by burning lava. It’s quite a difference to the impression you get when looking at the UNISYS graphic.
So which graphic is correct? For the Baltic, here’s what the “jury” says, SMHI (From Sweden) has an updated SST for the Baltic Sea from exactly 3 may 2010:

The 3 graphics agree reasonably for the Northern Baltic Sea, but for the rest of the Baltic Sea, SMHI shows in average around – 1,5 degrees Celsius anomaly. Both UNISYS and NOAA show too warm temperatures, but NOAA far worse than UNISYS. So, NOAA is around 2 K warmer in this area than SMHI – the best estimate.
Europe is not the only area where NOAA has warmer temperatures than UNISYS. NOAA appears markedly warmer than UNISYS on the Northern Hemisphere – but a little colder than UNISYS in areas of the Southern Hemisphere:

Link to the daily UNISYS SST:
http://weather.unisys.com/surface/sst_anom.html

Link to NOAA SST – use “FULL GLOBAL” to see all:
http://www.osdpd.noaa.gov/PSB/EPS/SST/climo.html

Link to SMHI detailed SST for Baltic + Danish waters:
http://www.smhi.se/polarview/

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94 thoughts on “Hotness is in the eye of the beholder

  1. This is called “selling your deal” – any good presenter using a map representation of data will choose color schemes to emphasize the desired point. You may not agree with their point of view but the pro-AGW people are not stupid . The fully know what they are doing with the color schemes chosen. This technique is used all the time in the presentation of geophysical / geological data (my area of expertise). Of course, if you are used to looking at data presented in this way, you can see past the color scheme & see what the data is truly telling you. The problem is the general public does not fall into that category and can be easily mis-led by the color scheme

  2. And you still don’t understand differing baselines.

    REPLY:
    Rat Boy, we understand differing baselines just fine, the issue is the color presentation. -A

  3. “Differences are immense to an extend”? Did you mean extent?

    When one sees certain typos as that, one wonders if there was any scrutinizing of the claim made in the story. Just saying because anyone can write a piece these days (and they do).

  4. P.S. Are color blind people more apt to be skeptics? Curious because I am color blind.

  5. The usual confusion between ‘anomaly’ and ‘temperature’. If there is no confusion the the maps should not be labeled SST, but SSTa or some such, as the SMHI does. If the baselines are different, the anomalies will be different, and color scales may not mean the same thing even if red = 4 degrees for both.

  6. Interesting.

    Just looking at the color distribution shows a huge difference in presentation. NOAA uses a two-tone color scheme — hot or cold. And of course the colors chosen for hot have a much greater impact.

    Now, look at the UNISYS color scheme — it’s what I call a Goldilocks scheme. The strongest colors are reserved for the extremes, greater or less than 2, while the mid-range has the more subdued colors, so that most of the water temps are “just right”. And, of course, it is far less dramatic.

    As for the other differences — I’ll leave that to someone with a stronger stomach.

  7. Completely OT–but I just watched the Discovery Channel’s special on “The Volcano That Stopped the World”. Great show–especially the passionate explanations by the geologists–until they HAD to bring AGW into the mix.

    Their speculative claim: That anthropogenic global warming is increasing the likelihood of sub-glacial volcanoes (like many in Iceland) erupting–due to the melting of the glacial mass, effectively removing the ‘lid’ from such volcanoes. They call it something like ‘unloading’. They were also kind enough to blame human’s CO2 emissions.

    I didn’t check to see if Al “Manbearpig” Gore was funding the show, but I can’t help but ask the obvious about this claim:
    1. What proof is there that humans are definitively warming the planet? (Other than UHI)
    2. What proof is there that human activity is causing the reduction in glacial ice sheets? (Reminder–we’re talking about continental-type or land-based glaciers, not sea ice here.)
    3. What proof is there that–whatever the cause of the reduction–reduction in glacial mass above a volcano can serve as a ‘trigger’ for volcanoes of the Icelandic ilk?
    4. Why did they have to put that shameless plug for emissions reduction into the show?

    Oh–I just figured it out. We can blame the Icelandic government, which has obviously told the producers of the show that Icelandic-lava-fueled geothermal energy can be used INSTEAD of fossil-fuel based energy. Now it makes sense.

    Actually, I welcome the scientific arguments supporting their claim. It is an interesting one. If it’s well-documented, then I’ll apologize with foot-in-mouth.

  8. We experience daily changes in temperature far in excess of the anomalies shown without much discomfort. This fixation on “temperature” is quite meaningless but a handy distraction from trying to explain the physics of the atmosphere which, it appears, nobody understands.

    If the physics of the atmosphere were understood we would be inundated with daily tutorials explaining how and why it WILL get warmer. Instead of tutorials we get daily threats.

  9. Yes, the colours are used differently, but the changed are more then just use of colours.

    See the black sea. For UNISYS its around -1 K or less, for NOAA its above +2 K in anomaly.

    When you take your time you will see that this is more than the (very effectfull) colour use.

    Joanne Nova presented me for a graphic she made for 3 may where it becomes obvious that also the whole Mediterranean appears more than 1 K to hot in the NOAA.

    Leif Svalgaard: you write: “The usual confusion between ‘anomaly’ and ‘temperature’.”
    UNISYS describes their plot: “Sea Surface Temperature Anomaly Plot ”
    NOAA describes their plot:”SST Anomaly (degrees C)”
    And then Leif, you also mention the obvious , that the colour use is different, but I would not have posted this if it was only a color use issue. Its far from that, please take your time and look more carefully.

  10. Wrt color schemes: The NOAA color schemes strikes me as the more honest. Using light blue for anomalies up to +1 and green for up to +3 is downright deceptive. Shades of blue for all -ve and yellow/orange/red for all +ve is much more natural.

    Wrt baselines: Frank L certainly gives the impression he does not understand this subtlety. I’m sure AW does, but he was remiss in not dismissing that part in his intro to the original post.

  11. Claiming that the Baltic is warmer than normal is utterly absurd. We have just come through the coldest winter in a generation, and ice-cover in the Baltic was the worst since 1985. The last ice in the Bay of Riga and Gulf of Finland only melted about a week ago and the Gulf of Bothnia is still ice-covered, and expected to remain so for most of May. I live near the Baltic coast, and the spring is unusually late this year because of the cooling effect of the sea.
    NOAA is either negligent or deliberately misleading.

    Pekke: Water temperature is measured, but the anomaly map which is satellite based probably includes meltwater on top of the ice. Melting ice is always at zero degrees centigrade. Notice the positive anomaly in the northwestern gulf of Bothnia. There is a large lead there at the moment and water up there is very nearly fresh, so it is at its densest at 4 degrees centigrade. On the finnish side where there is still ice the temperature is around zero.

  12. The color scheme fussing is silly. My own area is computational fluid dynamics, and the NOAA style scheme has been standard for at least 30 years. It’s even there as one of the standard palettes (heat.colors) offered by R, a stats package which has nothing to do with climate science.

    Yes, it makes higher temperatures look hotter. It’s meant to. It communicates something to the reader.

    And Leif and Rattus are right. If you’re doing these comparisons you should at least acknowledge the difference in anomaly bases.

  13. All publications from NOAA with particulars about the climate are showing more than substantial differences with independent scientific institutes and their measurements .
    Who is in charge of NOAA publications on the internet and is this a deliberate attempt to influence public opinion in order to push the AGW – cap and trade agenda ?
    Situation in the USA is under Obama rule getting worse than in Russia during the recent 50 years !

  14. Both colour schemes are poor in my opinion.
    A much better way is to use white as the neutral temp anomaly (-0.5 to 0.5) then take it from their. The BOM use this for their enso sst updates and it seems to work much better.

  15. The NOAA colour scheme is of course based on the childrens bath water temp strip. Red means you are going to burn and injure your children and isn’t that exactly the message they want mum’s and dad’s to believe;

    Cheers

  16. The NESDIS dataset uses only nighttime SST data. Why? The answer lies within the description of the data.
    http://coralreefwatch.noaa.gov/satellite/methodology/methodology.html#sst
    “Nighttime-only satellite SST observations are used to eliminate diel variation caused by solar heating at the sea surface (primarily at the “skin” interface, 10-20 um) during the day and to avoid contamination from solar glare. Compared with daytime SST and day-night blended SST, nighttime SST provides more conservative and stable estimate of thermal stress conducive to coral bleaching.”

    Discussed the “hotness” of NESDIS “coral reef watch” SST data in this post:
    http://bobtisdale.blogspot.com/2009/09/note-about-sst-anomaly-maps.html

    The NESDIS webpage also cautions users about high latitudes of the “Coral Reef Watch” SST dataset: “Note that these anomalies are somewhat less reliable at high latitudes where more persistent clouds limit the amount of satellite data available for deriving both accurate SST analysis field and climatologies.” They do not go to the same lengths as other datasets to make corrections at high latitudes.

  17. AGW “real estate” is no different from “real” real estate. To make a sale, sell the sizzle, not the steak. ;-0

  18. Something very strange going on. NOAA has a positive relative anomaly north of Lappland and in the Black Sea. UNISYS has a negative relative anomaly in these places. Yet they agree in the Tyrrhenian Sea which is around zero/plus one on both scales.

    Not just the colour bias, which I think does verge on propaganda in NOAA’s case.

  19. gary says: “P.S. Are color blind people more apt to be skeptics? Curious because I am color blind.

    I’d guess yes, but not for the reason you suggest. If you are colour blind, you will be much more aware that people can see the same “data” and view it quite differently. You will also be very aware that your perception of something is subtly different from those with three colour vision, so you will not be so easily deluded that data is the same as your perception of the data.

    All in all, I would suggest someone with colour blindness is much less likely to assume “the consensus” is correct and much more likely to be aware that someone’s perception of e.g. a cause behind a warming century is merely a false perception based on a lack of data.

  20. This is a bit of a mess. Can you clear up which are actual temps and which are anomalies, thanks.

  21. “Bruce of Newcastle says:
    May 7, 2010 at 2:45 am
    Something very strange going on. NOAA has a positive relative anomaly north of Lappland and in the Black Sea. UNISYS has a negative relative anomaly in these places. Yet they agree in the Tyrrhenian Sea which is around zero/plus one on both scales.

    Not just the colour bias, which I think does verge on propaganda in NOAA’s case.”

    The NOAA hotspot North of Lapland for example has been there fore ages, its a real difference in data. Also, it has nothing to do with colour scheme nor night temperatures as Bob Tisdale suggests, and the same goes for several other areas. No way is the Baltic over night suddenly warmer than normal end then in day time colder. Not realistic.
    I think its perfect that we are open minded – a good scientific vertue – but we should not end up defending NOAA data when no arguments really support it. (But the info about night vs. day measuring itself is appreciated!)

  22. “HR says:
    May 7, 2010 at 3:29 am
    This is a bit of a mess. Can you clear up which are actual temps and which are anomalies, thanks.”

    All graphics shows ANOMALIES and are therefore comparable – when you of course consider the color legends.
    And NOAA anomalies are far often more hot than UNISYS than the opposite.

  23. Nick Stokes says:(May 6, 2010 at 11:45 pm)
    “And Leif and Rattus are right. If you’re doing these comparisons you should at least acknowledge the difference in anomaly bases.”

    So the question I have is this:
    Why do different groups use different baselines?
    Is it because:
    a. They do not want their results easily compared to someone else
    b. They are arrogant and believe only their results show something special
    c. They have access to different data and do not want to share
    d. No one can agree on a standard baseline for each type of anomaly chart
    e. They want to deceive
    f. Some other reason

  24. Laying the colors aside: This is not the 1st time NOAA has been presenting data that the locals shake their heads over.
    Behavior is compelling evidence, and there is a pattern.

  25. Frank,
    Half of you all have dropped the hint – but let me spell this out:
    The baselines appear to be different. It is not enough to say “anomaly” but “anomaly from 19xx to 19yy average” as a baseline.
    Other differences – like night vs. day time measurements, have also to be looked at.
    On the proper color I have to agree with RobJM as this would help tremendously identifying the maps as anomalies and not temp.

  26. This just highlights the whole sad anomaly fiasco.
    The way it is now everybody can have their own movable baseline.
    This is what makes the anomaly so confusing and deceptive.

    I say go strictly with K units or use some universally agreed standard temperature and pressure like 25 C and 760 mmHg etc.

    It is like changing par on your golf score.
    If you normally shoot in the 90s you could say “Hey I’m only +15 today.”
    The answer is “No you slug you were 33 over par meaning you shot a 105. So shut up and quit trying to embarrass yourself and everybody around you.”

  27. “we understand differing baselines just fine, the issue is the color presentation. -A”

    Reading the article, the author more than once directly compares anomaly readings from the different maps. So this article is not just about color presentation. It is saying the data sets are actually inconsistent with each other.

    The word ‘baseline’ doesn’t appear once in the article.

    So for the readers who aren’t familiar with these particular data, could you tell us what the baselines are for the three different maps?

    For SMHI I see this, “15-year reanalysis using HIROMB for the period 1990-2004”
    On a quick look, I couldn’t find the baseline for the other two.

  28. I agree. Use absolute temps and all should agree to use a standard color scheme. Afterall, THEY are asking US to do far more agreeing to do this or that. Seems a small price to pay to win over our cooperation.

  29. Anthony/Frank,

    You guys are getting more desperate by the minute complaining about the colour schemes on the NOAA maps. In any event, the NOAA colour scheme is far easier to make sense of to the non-expert with yellow to red showing warmer and blue to purple showing cooler. Since when has green or even blue ever represented warmer than a baseline? Does the hot tap in your bathroom have green or blue above it??????? Does a children’s temperature thermomoter show warm as green or blue? of course not. As a non-expert in this field I cannot make any sense of the UNISYS colour scheme.

    REPLY: Yeah sure, whatever.

  30. Yes, without a common baseline, anomalies become almost meaningless — especially if one is interested in the science of changing conditions (I fear to say the dreaded phrase “climate change”) and comparing one method of measurement to another. Perhaps it is time to do away “anomalies”? Are they really more useful than actual temperatures if anyone can cherry-pick? Of course, there is outright lying re the “actual temperatures”. NOAA anyone?

    I wish Leif would apologize to Frank. The former is usually exact in relationship to the current science, so many of us notice his posts in particular. And Frank Lansner has consistently offered some of the finest posts on WUWT for my money.

    Both NOAA and UNISYS measure anomalies. I check UNISYS daily; the chart is both informative and absolutely beautiful. A morning feast for the eyes.

  31. Tom in Florida says:

    “Why do different groups use different baselines?”

    If your dataset starts more recently than somebody else’s, then you can’t use the baseline used by the older datasets. Meaning, when RSS and UAH first started publishing their numbers, they simply couldn’t use the baselines normally used by GISS or CRU, because there are no satellite data for 1950. On the other hand, should we expect GISS and CRU to start using a new baseline every single time a new satellite record comes into being? This would also cause confusion, as then GISS publications from 1990, 2000, 2020 would be on different baselines from each other.

    So it’s just best to take note of what baseline any given dataset is using, and if you want to make things directly comparable, add or subtract the necessary offset, before continuing. That’s easy enough to do.

    In any event, the article above is very remiss for not telling the reader what the baselines are.

  32. Carrot Eater:

    “So for the readers who aren’t familiar with these particular data, could you tell us what the baselines are for the three different maps?

    For SMHI I see this, “15-year reanalysis using HIROMB for the period 1990-2004″
    On a quick look, I couldn’t find the baseline for the other two.”

    My point exactly. What are they comparing these temps to.. winter of 1974 or 1800 when the Little Ice Age ended? In both cases, of course it’s warmer. But to not include a reference to their baselines doesn’t make their maps any more scientific than musing over the taste of your morning coffee..

  33. “husten says:
    May 7, 2010 at 5:58 am
    Frank,
    Half of you all have dropped the hint – but let me spell this out:
    The baselines appear to be different. It is not enough to say “anomaly” but “anomaly from 19xx to 19yy average” as a baseline.”

    Husten, this is 100% correct, and thankyou for writing. But if you look at the compare for the whole world, the 3´rd graphic above, you will see, that on the southern hemisphere, NOAA is in fact a little colder than UNISYS as I write in tha article. And we cant have a baseline doing one thing in the NH and another in the SH, see?

    Please take a close look:

    The overall differences between NOAA and UNISYS are not thaaat big in the overall picture, but here are features specific places on the globe where NOAA just differ wildly from UNISYS within specific regions. Take a look at the central North Pacific, the blue oval.

    Around the blue oval the NOAA and UNISYS are pretty much shoing the same, but IN the oval, things goes bananas. These issues are clearly NOT baseline issues .
    And the examples i have given for Europe where sea areas are 1,2,3,4,5,6 K warmer than UNISYS cannot be baseline issues either.

    Just ONE glimpse at the NOAA North Scandinavian hotspot – that has been there for years – tells you that there are some data issues that really needs attention, and that has nothing to do with small differences in baselines nor colore schemes etc.

    The Black sea, NOAA´s Black sea is over 3 K warmer than UNISYS. If such a thing was a baseline issue, i would very very much like to know what years their baseline was taken from :-) – perhaps year 9000 b.c. – 8900 -b.c. ?

    K.R. Frank

  34. Don’t we have a STANAG to cover this type of confusion so that we use the same colors to represent the same data? I thought everything and anything was covered by a STANAG. The Chinese didn’t call us a Paper Tiger for nothing.

  35. No credible baseline can explain the NOAA map. For example the sea south of Åland is shown as being warmer than normal and the Gulf of Finland as being colder than normal. The actual water temperature was about 3 degrees centigrade in both areas on May 3 (http://www.smhi.se/oceanografi/istjanst/produkter/arkiv/sstchart/sstchart_20100503.pdf).
    This means that the NOAA baseline must have warmer temperatures in the Gulf of Finland than in the Northern Baltic, a situation that simply does not occur in spring.
    Incidentally differences between daytime and nighttime water temperatures in the Baltic is negligible this time of year.

  36. Frank Lansner says:
    May 7, 2010 at 3:35 am
    ….
    All graphics shows ANOMALIES and are therefore comparable – when you of course consider the color legends.
    And NOAA anomalies are far often more hot than UNISYS than the opposite.

    There are substantial differences in the reported anomalies for areas like the Black Sea, Faroe Is., and N. of upper Norway. Either NOAA and UNISYS are using different data, or else they are using dramatically different reference periods to compute their anomalies. Some commenters have suggested that the latter is the case, but they have provided no actual information about the nature of the differences.

    As for the color schemes, I don’t like either. NOAA reasonably uses yellow for neutral (or just above neutral), but then makes no use of green, and uses black for both -4 and land. Green would be a good alternative color for neutral. INSYS has even green way up at 1.75, and so fails to exploit the red region. The shades of magenta are also hard to distinguish.

    gary says:
    May 6, 2010 at 9:59 pm
    P.S. Are color blind people more apt to be skeptics? Curious because I am color blind.

    Perhaps NOAA is trying to accommodate common RG colorblindness (10% of males?) by not using green. Even so, there must be a better way to do the blue end of the color scheme. Perhaps there is some way brightness could be used to distinguish greens from reds without giving up on green altogether.

    But if yellow = R+G, does this register as R+R if you’re RG colorblind?

    Using light gray for land rather than black (which is also in the color scale) would be a help.

  37. The NSDIS baseline seems to be based on the dataset here:

    http://www.osdpd.noaa.gov/ml/ocean/sst/monthly_mean_sst.html

    That means it comprises 1984-1998, except for a hiatus june 1991 – march 1992, which was deleted because of Mount Pinatubo cooling. Looking at the data suggests an explanation for the weird permanent “hot-spot” north of Norway. For some reason this area is missing in most of the monthly maps, so presumably in this are the anomaly is calculated on a much smaller dataset, or simply interpolated.

  38. The NOAA baseline must be after 1972 or 1979, since this is the starting point of the measurements, i believe. But in the decription I have not found it, perhaps missed it:
    http://coralreefwatch.noaa.gov/satellite/methodology/methodology.html#ssta

    This means, that NOAA has rather recent baseline years, hot baseline years, and baseline is not helping to explain the very hot specific areas here and there on the North Hemisphere.

    And as i said, baseline differences (especially when NOAA uses warmer years) can only explain a fraction of these odd warm features.
    The pearl above all is the NOAA hotspot north of Scandinavia up to 6 K over UNISYS, any baseline issues could only explain a few % hereof.

  39. “And as i said, baseline differences (especially when NOAA uses warmer years) can only explain a fraction of these odd warm features.”

    Since you wrote the article, it’d be helpful if you actually completed the circle and chased down what the baselines actually are, so that we can compare apples to apples, instead of guessing about it.

    If any difference remains, then we move on to what the data sources are. Are they using different sources, or is it the same source with different processing? Is this all satellite data? Is there any model re-analysis in there?

    Anomaly data for a specific day is in itself interesting. Is the baseline all May 3rds within the baseline? All May days within the baseline?

  40. Nick Stokes says:
    May 6, 2010 at 11:45 pm

    The color scheme fussing is silly. My own area is computational fluid dynamics, and the NOAA style scheme has been standard for at least 30 years. It’s even there as one of the standard palettes (heat.colors) offered by R, a stats package which has nothing to do with climate science.

    Yes, it makes higher temperatures look hotter. It’s meant to. It communicates something to the reader.

    And Leif and Rattus are right. If you’re doing these comparisons you should at least acknowledge the difference in anomaly bases.

    All beside the point. Well, maybe not. To reiterate what you said:

    “It communicates something to the reader.”

    Yes, it does. It communicates, to use the phrase in the original article, you are all going to die in a burning pool of larva.

    It’s akin to the little brother holding his snot covered finger 1 inch from his sisters face and calmly repeating “I’m not touching you; I’m not touching you; I’m not touching you…”.

    All too often the scientific comeback is that it’s not their fault you (the general public) don’t understand. Actually, yes, it is the scientists fault.

    But it goes beyond ‘fault’ – it comes down to complete lies. A lie of omission is still a lie and is very easy for scientists to do, deliberately or otherwise, because the audience is not a specialist in that field; they cannot ask the correct questions to determine if an omission has been made. Luckily, science is science. Those whose scientific background is in another field which relies on the same techniques can intelligently ask those questions because they can identify flaws in reasoning, even if they may not understand fully the subject matter. This is where the (climate) ‘scientific’ comeback is – “well, you aren’t a climate scientist…”.

  41. “carrot eater says:
    […]
    If your dataset starts more recently than somebody else’s, then you can’t use the baseline used by the older datasets. ”

    Why not?

  42. Hi Carrot eater!

    Promise me one thing: Its fine and good that you want all relevant questions answered, but: Please don’t overlook 6 K difference in anomaly because you focus on baseline issues that might explain 0,1K ok? Promise? Because then my bringing these fatal data issues to you guys will fall on the floor, and NOAA should not get away with this so easy.

    And then one more time: I can’t find the baseline years.
    But if you then say: “FINE, no baseline years written by NOAA, then lets forget a 6 K anomaly North of Scandinavia!” i will be surprised.

    The satellite data from used by NOAA and UNISYS are likely from the satellite years and thus comparable. And don’t forget that NOAA’s world map is in fact older in the Southan hemisphere than UNISYS as i write above in the comments.
    Therefore, the baseline cannot be that different between UNISYS and NOAA.

    What we look at here is Freak data limited to specific areas. These freak-warm specific areas cannot be explained by a baseline issue, even though it would be good to know the baselines.

  43. correction, went too fast:
    “And don’t forget that NOAA’s world map is in fact colder in the Southern hemisphere than UNISYS as i wrote above in the comments.
    Therefore, the baseline cannot be that different between UNISYS and NOAA.”

  44. Sorry if this is Off Topic, but:

    It occurs to me that agricultural land usage could be a useful calibrator of these allegedly foolproof satellite-measured time series. (After all, what greater contrast could there be between the overzealous climatologist who never goes outdoors, and a pragmatic no-nonsense farmer.)

    Is anybody aware of data showing “crop range” – the lands where farmers think they get optimum yields over the years? Such data would of course be subject to other influences such as market price, new strains, etc., but intelligently treated and filtered might contain a useful climate signal.

  45. Frank,

    “Please don’t overlook 6 K difference in anomaly because you focus on baseline issues that might explain 0,1K ok?”

    Until somebody (hopefully you, since you’re the one who raised the point) actually goes and puts the two datasets on the same baseline, none of us know whether the difference due to different baselines is 0.1 K or 3 K or what. Keep in mind that the difference in baselines will be a function of both location and probably also day, if not week or something like that.

    So until you do that legwork, it’ll be difficult to know what we’re looking at, if anything. If these were the more familiar land station datasets, somebody else would have done it by now. But these are data I’m not familiar with, and I doubt I’m the only one.

    Hand-waving about the baselines is not sufficient here. Please first do the math. Then we’ll see what difference is left, and why that might be.

  46. Carrot eater, both datasets are from the Satellite years so your viewpoints about how these data could just explain 6 K in difference due to different years are nonsense to me, i’m sorry.
    Look, call it “hand waving” or what you want, say that i don’t do my math because NOAA doesn’t show what exact satellite years they use or whatever.

    I think most people can see a problem over Scandinavia, even though one set might not use exactly the same years between 1979 – today as the other:

    Over and out, Carrot Eater.

  47. ?????

    It has been stated time and time again that we can expect a 1°C increase for a doubling of CO2 without feedbacks in our atmosphere based on the general acceptance of Fourier’s law. I do not have any problem understanding the concept of filling a sealed glass chamber with varied levels of different gases and comparing the various energy levels maintained by different gases in the sealed system at equilibrium due to varied input levels of outside radiation.

    There is the control of the outside chamber’s reflective properties of the glass, there is the inside chamber’s reflective properties of the glass and there is the heat energy that is stored by the glass itself. As the chamber is the same, Fourier’s experiments show the different potentials for energy storage among gases(period).

    QUESTION: (Not a rhetorical one)

    How is it that we can apply Fourier’s law to earth’s atmosphere which is neither a sealed glass chamber nor at equilibrium regarding CO2?

    If this were face to face I would stop there and eagerly wait for an explanation. However, I think that leaving the above honest question on a thread, some might think that in spite of my previous declaration I was presenting a rhetorical question. It is my understanding during the course of my readings that Dr. Lindzen and others have said things along the lines of Fourier’s law regarding the expected one degree Celsius increase in response to a doubling of CO2 in the absence of other forcings, and I just can’t wrap my head around it.

    Somebody please explain to me the concepts that I am missing that are understood by people like Dr. Lindzen who say that we can expect a 1°C response to a doubling of CO2 in our atmosphere in the absence of equilibrium, a sealed environment & any other forcings?

  48. Personally, I think the NOAA color scale is better. It is easy to see where has a positive anomaly and where has a negative anomaly.

    The unisys color scale has blue/cyan color to represent positive anomalies which is unconventional and maybe a little bit misleading…

  49. Frank,

    “Carrot eater, both datasets are from the Satellite years ”

    I have no idea how much that limits the possible differences at any given location, on any given day. Keep in mind that we’re looking at specific locations on (presumably) specific days. The variability in this is higher than in, say, studies of variability in the annual global mean.

    Maybe there is some underlying difference in the data sets, or how they were processed. Maybe there’s some weird software glitch somewhere. After all, I have no idea where the numbers are coming from. But until you put the numbers on an equal footing, we can not begin to think about that.

  50. Paul says:
    May 7, 2010 at 9:45 am
    “QUESTION: (Not a rhetorical one)
    How is it that we can apply Fourier’s law to earth’s atmosphere which is neither a sealed glass chamber nor at equilibrium regarding CO2?”

    Short answer, you can apply the ‘law’, but the calculated results will be inexact.

    There are many ‘laws’ of physics which require conditions to be applied which are not easily found in nature, and the answers will be incorrect. Because many climate processes are sensitive to initial condition, even slight errors multiply quickly and end up producing nonsense results.

  51. “Maybe there is some underlying difference in the data sets, or how they were processed. Maybe there’s some weird software glitch somewhere. After all, I have no idea where the numbers are coming from. But until you put the numbers on an equal footing, we can not begin to think about that.”

    Then you can agree that NOAA, UNISYS, SST maps are pretty much useless for anything.

  52. personally I think NOAA ‘s color scale is trash. How many colors of red are there ?NOAA cooler colors are still yellow and green,Which I HATE Ithink UNISYS give most accurate reading.

  53. Andy Krause says:
    May 7, 2010 at 10:50 am

    “Then you can agree that NOAA, UNISYS, SST maps are pretty much useless for anything.”

    No, they’re potentially very useful, provided you know what is being shown. But this article is an attempt to use them, without knowing what is being shown. That’s the problem.

    terry46 says:
    May 7, 2010 at 10:55 am

    “personally I think NOAA ‘s color scale is trash. How many colors of red are there ?NOAA cooler colors are still yellow and green,Which I HATE Ithink UNISYS give most accurate reading.”

    Huh? The NOAA map above doesn’t even use green. Yellow is on the positive side, as would seem reasonable to me. Maybe you’re talking about a different graph?

    It’s the infosys colorbar that’s a bit strange, if anything, with a shade of blue actually turning up on the positive side.

  54. terry46 says:

    Terry, there are no greens on the NOAA map for you to hate. What’s more, if you look closely you will see that yellow only represents warmer than the baseline–not cooler. It is one thing for to be sceptical about NOAA material but all this fuss about colour schemes has reached a new low for the sceptics and shows desperation.

  55. Carot Eater: you write: “Keep in mind that we’re looking at specific locations on (presumably) specific days.”

    If the base period was 1 day, 1 week or maybe 1 month one could image quite large anomalies, but we are normally talking about base periods of many years, often decades when NOAA make a base period. An area like the one North of Scandinavia cannot possible quite lokaly deviate with 6 K for many years and thereby give this NOAA hotspot North of scandinavia for years now. Its really just out of the question, no more no less. A little decimal deviation is possible.

    And that NOAA makes the error and not show clearly the base period, does not mean that we cannot tell the obvious about their hotspot. Because an giraf stands on a mouse, we can still tell that the giraf has a long throat :-)

    Anyway, BRIAN D, found a similar NOAA SST graphic, with a baseperiod: 1982-96.
    so far so good.

  56. Frank:

    A baseline may be listed as several years, but you have to also check what periods within those years are being used. For land surface data, if I’m going to find the anomaly for the month of May, I will subtract out the average of all Mays in my reference set; not the entire reference set.

    That’s why I’m wondering how the daily anomaly is being calculated, because I have no idea. For May 3, are they subtracting the average of all May 3rds in the period 198x to 199y, or all days in May over that span, or all days in the first week of May? I don’t know, but it’s the sort of thing I’d want to know before I started working with these numbers. Looks like it’s discussed here: http://coralreefwatch.noaa.gov/satellite/methodology/methodology.html#ssta

    Are you saying that exact same red spot north of Scandinavia is there every single day, over the course of several years? If so, that would be interesting to look at. But you’re only here showing one day.

    But for your point about any apparent disconnect between the data sets: I’m sorry, but you simply have to put everything on the same basis first. If you are going to use a data set, you should first know what it is. Once you know what it is, then assuming you can download the data, then it’d be pretty simple to put it on the same basis for whichever part of the map you care about.

    Failing that, you could download the data for a given grid box, in the three different data sets, and plot the trends over time. If the trends are parallel but simply offset from each other, then it was just a baseline issue. If not, then something else is up. Maybe the sets really do disagree, I have no idea. But you have to do more to show that.

    You can say until you’re blue in the face that you don’t actually know the difference due to the baselines, but that you’re sure it’s small, but that just isn’t acceptable. If somebody is going to compare individual anomaly values from CRU and GISS, they must put them on an equal basis first. Same thing here.

  57. You can’t compare two anomaly maps with different baselines- at least not in the way you’re doing it.

    Look at it this way. Say the Noaa baseline is zero degrees. An area where the temp ranges from -0.25 to +0.25 degrees plots as part positive anomaly (+o.25) , part negative anomaly (-0.25).

    Now say the unisys baseline is 1 degree. Those same temperatures would plot as anomalies of -1.25 and -0.75: all negative.

    And it looks like NOAA uses a finer grid- so little hot spots on the NOAA map would be “averaged out” in the unisys map.

    The temps north of sweden/norway seem different between the two (there’s a wider range of temps in the NOAA version)- maybe that has to do with different ways they handles sea ice?

    But in the rest of the world, the two maps look pretty consistent to me.

  58. “And it looks like NOAA uses a finer grid”

    If so, that’s something to keep in mind.

    “maybe that has to do with different ways they handles sea ice?”

    If sea ice were an issue between the two sets, wouldn’t that show up over a larger area in the Arctic?

  59. Pyromancer76 says:
    May 7, 2010 at 6:40 am
    I wish Leif would apologize to Frank.
    I don’t think any is necessary [but if so, will gladly give one]. My small complaint was about the fuzziness in using ‘SST’ for what is ‘SST anomaly’. With different baselines, one gets maps that cannot be compared at a glance [which is what such maps were supposed to be useful for]. One can always by analysis of the numbers extract information from the maps, and Frank is correct that they don’t compute, but one should not have to do that. ‘At a glance’ is a powerful tool.

  60. Tom,
    “Why do different groups use different baselines?”
    For good historical reasons. Anomalies are used basically to take out effects due to local siting. You need a reasonable time to estimate that – thirty years is conventional. You want to make sure that as many as possible of your sites have data in that period, so you choose the most recent thirty years. Well, almost – people also like to go for calendar decades.

    Once chosen, you accumulate a whole lot of data and published plots expressed relative to that anomaly base. There’s a big cost in changing, and no reason. So it stays, for the same sort of reason the US sticks with F.

    So GISS, which started Gistemp in the ’80’s, use 1951-80. CRU, which formalised in the ’90’s, use 1961-90. Satellite data people use a period since 1979, because that’s where they have data.

  61. So, I’m really curious how one would resolve the discrepancy. Obviously the NOAA and UNISYS are using different software, as is the Swedish outfit. This could reasonably mean that they use different modelling algorithms. In such a case, how would one go about doing an apples-to-apples comparison?

  62. Nick Stokes says:
    May 6, 2010 at 11:45 pm

    “The color scheme fussing is silly. My own area is computational fluid dynamics, and the NOAA style scheme has been standard for at least 30 years. It’s even there as one of the standard palettes (heat.colors) offered by R, a stats package which has nothing to do with climate science.

    “Yes, it makes higher temperatures look hotter. It’s meant to. It communicates something to the reader.”

    You neglected to tell us exactly what you thought it communicated (and was meant to communicate) to the reader. A dishonest distortion of reality intended to deceive the general public, no?

    [A, I think the warmist trolls doth protest far too much on this post, and it shows that, far from what they are saying about us being desperate, it must really be of some significance to them in revealing yet more of the inherent dishonesty of their side of the AGW argument.]

  63. Hi Carot eater, yes the hotspot is in fact a rather famous NOAA feature, i havent invented it,

    Here January 2010:

    July 2009:

    Feb 2009:

    Aug 2008:

    April 2008:

    nov 2007:

    Mar 2007:

    Apr 2006:

    nov 2005:

    feb 2004:

    feb 2002:

    apr 2000:

    etc.

    But, C.Eater, you are missing the point:
    Its the BASE period that is many years long and there fore cannot hold a very local super heated area. You cant have for exampple the state of New York 6 degrees hotter than the neighboring states for many years, its just not possible.

    Therefore, the POINT:
    We are comparing UNISYS and NOAA. There is a huge difference for a nunmber of Sea areas between those two for the very same day. If this where due to different baselines, then the baselines over manye years on quite local areas should have deviated srtongly without neigboring areas affected. Its just not possible.

    The baselines made over many years cannot explain huge temperature differences for local areas, mostly different baselines can explain differences on global scale or at least hemispherical. Not for instance the hot spot North of Scandinavia.

    Or that is, yes, the baseline data can explain this is huge local difference if the baseline holds the error im looking for.

  64. Hi Chris V!

    you write:
    “The temps north of sweden/norway seem different between the two (there’s a wider range of temps in the NOAA version)- maybe that has to do with different ways they handles sea ice?”

    There has been no sea ice there since 1979, the sattelites, so i think not :-)

    And, yes, baseline is important, but important to explain global scale differences – or perhaps hemispherical. Certainly not those small specific areas i have pointed out as I explained to carot eater above.
    K.R. Frank

  65. Anu says:
    May 7, 2010 at 6:42 am

    “Hot is hot – I don’t think the color schemes really matter:
    “…”

    A novel form of hand-waving, for sure. You really are anxious to distract from the significance of this post, aren’t you?

  66. “carrot eater says:
    May 7, 2010 at 11:27 am
    Andy Krause says:
    May 7, 2010 at 10:50 am

    “Then you can agree that NOAA, UNISYS, SST maps are pretty much useless for anything.”

    No, they’re potentially very useful, provided you know what is being shown.”

    – Exactly, to extremely different suggestions to what the SST anomaly is…
    So if you want to know if its hot in Scandinavia you have to confront to datasets, then dig up some references not available etceetc.

    No its a mess to have so big differences, it makes your impression completely random. You can just as well try to look in a crystal bowl.

  67. Tenuc says:
    May 7, 2010 at 10:29 am

    Short answer, you can apply the ‘law’, but the calculated results will be inexact.

    There are many ‘laws’ of physics which require conditions to be applied which are not easily found in nature, and the answers will be incorrect.

    Tenuc, on this issue I tend towards your “and the answers will be incorrect” but because minds such as Lindzen state with what seems to me certainty it warps my mind to figure out how they reach these conclusions.

  68. I’ll state my bias up front. I have been retired from Unisys for years, and at one time worked for several years on Univac/Unisys weather software contracts for the USAF. Some years prior to that I wrote weather software for the USAF as a Blue Suiter.
    Unisys has been in the Weather Software business for decades and you can see much of the output on their weather website. As near as I can tell, the data to be plotted is pulled directly from standard weather communications circuits as common observational data.
    I would expect Unisys to have no interest in warming or cooling, but only in selling software. I suspect that if Anthony has any questions about the massaging of data prior to or during plots, Unisys would probably gladly answer reasonable questions by phone, and be happy about the exposure.

  69. “You neglected to tell us exactly what you thought it communicated”

    It communicates exactly what it’s meant to communicate – the distribution of temperature. In CFD we use the same color scheme for the inside of a furnace or a refrigerator. Using warm and cool colors means you don’t have to keep looking at the legend to work out what’s what. And you use a big spread of colors just for clarity.

    I don’t know what kind of offence you think NOAA is committing by trying to tell you about SST’s. But if they are going to do it, there’s no point in making it harder for the reader with wishy-washy colors.

  70. Frank:
    If the red spot north of Scandinavia is that persistent, well.. it has to go away at some point. Show some plots during the baseline period, if you’ve worked out what it is yet. A place can’t permanently be at +4 C or whatever it is, unless they’ve made some math error.

    I wonder if it used to have the white mask, for sea ice, and now it doesn’t? That could throw something off.

    As for everything else: I have no idea why you resist doing your readers the basic service of making your comparison of apples to apples. Instead of telling us why we can manage to compare apples to oranges, please just give the apples to apples. It should not be hard. And again, to use a data source, you should probably know what it is. Not knowing the baseline is not knowing what it is.

    You do realise that each grid box will have its own separate baseline?

  71. Nick Stokes says,

    “But if they are going to do it, there’s no point in making it harder for the reader with wishy-washy colors.”

    What are you selling Nick?? Electric washing machines, Furnaces, TimeShares?? These anomaly maps are supposed to transmit information not emotion. Y’all AGW apologists are a HOOT!

  72. Frank:

    I’ve poked around a bit. Curious. Could be worth emailing somebody at NOAA, for help.

    First, that hot spot is indeed fairly persistent in recent years. Though here, it got frost-bitten:

    which somehow came from these absolute temperatures

    The NOAA baseline is interesting. They interpolate between monthly baselines to get a baseline for a specific day, for any grid location. Anyway, 1985-1993, except 1991-1992.

    I can’t figure out how to make trend maps, or download the gridded data, which would make this all much easier. One could probably ask for help on that.

    Without downloading the gridded data, one is stuck eyeballing things. But with some diligence, you could check the math and see where that hotspot is coming from.

    The anomalies during the baseline period are here
    http://www.osdpd.noaa.gov/ml/ocean/sst/monthly_mean_sst_anom.html
    And the absolute temperatures during the baseline period here
    http://www.osdpd.noaa.gov/ml/ocean/sst/monthly_mean_sst.html

    Throughout the baseline period, it looks like there’s a sea ice mask around that patch of ocean north of Scandinavia. Or near it, at least. So during the baseline, you get neither absolute SST nor anomaly at that spot, for much if not all of the time. If I’m looking at the right spot.

    How can you find an anomaly when there is no data in the baseline period? I’m puzzled. Here’s an example May month from the baseline period:

    See that white area with no data, north of Finland?

    Now, looking at the absolute temps for May 3,

    and the anomalies for May 3,

    Because they changed the map view, it’s hard to compare, but it does look like they are computing anomalies for a bit of ocean where there was little or no data, during the baseline period. So if nothing else, it’d be worth asking them what is going on there.

    Finally, UNISYS seems pretty difficult to use. I can’t find any description of the data source, or baseline, or anything. Seems like they want you to pay for stuff; I hope you don’t have to pay for such basic information.

  73. I made an experiment about 6 years ago using a graph from MSU Chanel 2 that shows the warming trend 1979-2002 and shifting the color registers in Photoshop and setting the zero degree in blue, leaving purple and violets to show warming. The visual impact is completely amazing. In the original graph you’d think that Earth was set on fire, and in the modified graph the warming is confined to Siberia. Take a look at:

    Original graph

    Modified graph

    The visual impact of reds and yellows –associated with fire and heat –is 90% of the effect sought by the alarmists.

  74. Kuhnkat,
    Here is a collection of CFD videos from Fluent. They’re mostly about bits of machinery. They’re actually fun to watch. But they are, like NOAA, trying to present info in an easily understood way. They aren’t trying to make any point about the hotness of things. And almost every one uses a color scheme like the NOAA one.

  75. Carot eater: As a Scandinave, im quite surpriced to hear that there has been ice just North of scandinavia back in the 1980´ies – have never heard of such ice in that period, probably my mistake.
    Im sure this is how NOAA every year can claim that these waters are4-5 degrees warmer than “normal” while UNISYS ssays they are slightly colder than normal.

    But if true, we can actually expect those waters to freeze over now when it gets colder? Interesting!

    A very local difference can be explained by ice in the baseperiod – but im still puzzled how so many very local differences between NOAA and UNISYS all the local areas where there are no ice. Can you really have 2 baseline periods (for NOAA and UNISYS) that for many years has some small local areas so quite different in temperature?

    Can the Black sea in many years of NOAA baselin really be 3-3,5 K colder than all the years of the UNISYS basline period??

    well if so, then there should allways be this 3-3,5 difference between NOAA and UNISYS in the black sea.

    But there is not in the little test i made, here compare 1 january 2000 NOAA has black sea around +0,5K UNISYS has + 0 approx. At least nothing like 3-3,5 in difference.


    For UNISYS archived animaly charts, see files with the text “anomaly”:
    http://weather.unisys.com/archive/sst/

    So did UNISYS change baseline underway ? ?
    Or there was one reader that sais that SST can shift dramtically from day to day. But for 6 may 2010 we still have a difference between NOAA and UNISYS in the black sea of 3-3,5 K, sp that not it.

    This is indeed a “long haired” issue, but Carrot Eater, even though i personally has not spent weeks weeks and week alone on this issue without help from you WUWT readers, i just dont agree that i should not have shown you guys these differnces. They are relevant in any case since users of UNISYS and NOAA simply has a right to know that there are these big differences.

    By posting at WUWT, its definetely often the input from the readers i read myself even though we have not 100% uncovered whats going on with these huge differences.

    If you only want to read material by scientists that has spent way more time on the issues that I have available, then there are places where only such material are published.

  76. Nick Stokes says:(May 7, 2010 at 1:04 pm)
    “Once chosen, you accumulate a whole lot of data and published plots expressed relative to that anomaly base. There’s a big cost in changing, and no reason”

    So your answer is (from my list of choices):
    c. They have access to different data and do not want to share
    d. No one can agree on a standard baseline for each type of anomaly chart

    “So it stays, for the same sort of reason the US sticks with F.”

    I have to disagree with this one. For the US to change to C from F would involve changing the way everyone thinks not just cost. People think in F not C and it would take several generations for it to become ingrained in our culture. Not so with difference anomaly baselines.

    “So GISS, which started Gistemp in the ’80′s, use 1951-80. CRU, which formalised in the ’90′s, use 1961-90. Satellite data people use a period since 1979, because that’s where they have data.”

    So again, it is (from my list of choices) :
    c. They have access to different data and do not want to share
    d. No one can agree on a standard baseline for each type of anomaly chart

    with a large dose of:
    b. They are arrogant and believe only their results show something special

  77. Mr Stokes
    You say that NOAA is innocent – I’ll stand with you on that. You say that skeptics paint the whole organization as a conspiracy dump – no support for you there.

    We should question the color scheme use at NOAA because the establishment won’t.

    Look at the NOAA scheme yourself , they start using a gradation of yellow, tending towards orange and red for all positive anomalies. Then they use a *different* color family from the other end of the spectrum, abruptly, for all negative values.

    Why?

    Why did they skip the in-between range of green colors? Please remember, we are just talking about colors now, and not of any connotations as yet.

    Look at your CFD diesel engine animation – they have a smooth transiting green range in between blue and yellow. The Unisys map has the same transition.

    Look at the NOAA color scale from 0 to 1.5 (anomaly). Can you tell the difference? I cannot. Can you tell the difference, visually, between 1.5 and 2.5? I cannot – these are represented by two very close shades of yellow. This is because they took the yellow-red part of the spectrum, stretched it out to represent one whole half of the entire anomaly range.

    This only means, the color scale used is not actually good for conveying information about the anomaly fluctuations/changes of 0.5 which the map purports to depict. On the other hand, the color scale is very good in a binary/dichotomous manner – increased anomaly versus decreased anomaly – you can clearly catch that visually by looking at the NOAA map. The is because of the color family jump in the scale. There is a threshold effect at the ‘0’ point.

    Representationally,
    Yellow-orange-red belongs to the ‘hot’ end of the spectrum. They all convey a visual impression of warmth, do you agree? Why is a +0.5 anomaly represented by a hot color, when just 1 K away, there is a temperature point, -0.5, represented by blue, a ‘cool color’? Is this appropriate?

    It is appropriate only if we believe all positive anomalies, irrespective of their amount, have a different meaning, which needs to be highlighted by a different color.

  78. Apparently the NOAA has never heard of Roy G Biv:

    Red
    Orange
    Yellow
    Green
    Blue
    Indigo
    Violet

  79. The NOAA SSTa maps are color-coded mainly to highlight positive vs negative anomalies, just as I wrote, in bimodal fashion. This probably has meaning in coral reef research.

  80. Tom in Florida

    “with a large dose of:
    b. They are arrogant and believe only their results show something specia”

    This doesn’t make any sense. GISS could change their baseline to match CRU’s tomorrow, and the results shouldn’t show anything more or less special. It’d just nudge the absolute value of the anomalies down to match CRU’s.

    Look, if everybody used the same baseline for a given sort of chart, then everybody would also have to change their own baselines every so often, as new groups or measurements came into existence to make new versions of those charts. You simply can’t win, in terms of simplicity.

    So just do what everybody does now – know what it is that you’re looking at, especially if you’re doing something like the above where you are directly comparing anomaly numbers. Happily, when it comes to trends, none of this matters.

  81. Shub

    “Representationally,
    Yellow-orange-red belongs to the ‘hot’ end of the spectrum. They all convey a visual impression of warmth, do you agree? Why is a +0.5 anomaly represented by a hot color, when just 1 K away, there is a temperature point, -0.5, represented by blue, a ‘cool color’? Is this appropriate?”

    ? Of course it’s appropriate. So long as it’s pretty much symmetric. The color at +0.5 should be as ‘warm’ as the color at -0.5 is ‘cold’.

    What would be a bad colorbar is one that isn’t even centered in a reasonable way (the unisys one where blue appears on the positive side), or one where the color gradients were different on either side of zero: for example, if +4 were red, but -4 were just light blue, instead of purple.

    As for your complaint about distinguishing things: yes, a colorbar without green is one that gives up some scope for visual resolution – if you used greens, then you wouldn’t have to use fine shades of other colors to portray differences. You could use green, you could not. I guess you could use light green for the first bin above 0, and dark green for the first bin below zero, if you really wanted green.

    In any case, this is all rather boring. When you see a chart, look at the scale, so you know what you’re looking at. And then look for the definition of the baseline, so you know what you’re looking at.

  82. Frank:

    Mind you, I’m not saying the hotspot is there because it’s usually 5 C there, and they are subtracting a null to get an anomaly of +5. If they were, that’s quite an error. But it’s something to ask after. At the very least, I’d ask how to download the gridded data (hopefully it’s possible!); once you do that, you can resolve all these things for yourself, as you can reproduce the anomaly calculation yourself. Just keep in mind that every location has a different baseline, and not only that, but each of the 365 days of the year has its own baseline (somewhat crudely interpolated).

    You can only get so far staring at maps and colorbars; at this point you need tabulated numbers.

    As for UNISYS: after a reasonable look around the webpage, I could not find information about what they were plotting – the data source, or the baseline. Is the baseline also interpolated from monthly averages to the day? Who knows.

    I assume UNISYS does not have its own private commercial weather satellite, so presumably they are getting it from somewhere else. So simply I would not use their map in this way before asking them what the map was. You have to know what it is.

  83. carot eater
    One can ‘complain’ only if there is scope to ‘complain’. Thanks for acknowledging (grudgingly) that green could have been used.

    The anomaly color scheme is designed to display and convey bimodal information – NOAA says this on its website itself. Their color scheme is *not* suitable to display a range of values

    The Unisys one is better in that respect. Yes, we can point out that the Unisys color for -7.5 is the same as its color for +4.5. But atleast it has a differential display for the middle range of anomalies.

    Why would a colorbar with blue for positive values be a bad ‘centring’?

  84. Carot eater, I think most of the problem is that NOAA for some reason has picked just 7 years (1985-91 + 1993) for their baseline.

    On this SST NOAA world map,

    they use 1982-96 as baseline and, their differences compared to UNISYS is mostly gone, compare with UNISYS:

    So when NOAA uses more years, they start to resemble UNISYS. This does speak for the quality of UNISYS.
    The Black sea anomaly for example now are practically the same. A difference of 3 K is gone.

  85. carrot eater says:(May 8, 2010 at 5:56 am)

    quoting me: “Tom in Florida:“with a large dose of:
    b. They are arrogant and believe only their results show something special”

    You say: “This doesn’t make any sense. GISS could change their baseline to match CRU’s tomorrow, and the results shouldn’t show anything more or less special. It’d just nudge the absolute value of the anomalies down to match CRU’s.”

    I don’t mean to say the baseline change will show anything special but rather it would make it easier for the average person to understand. Just the fact that GISS won’t change their baseline to CRU’s and vice versa kind of makes my point.

    “So just do what everybody does now – know what it is that you’re looking at, especially if you’re doing something like the above where you are directly comparing anomaly numbers. Happily, when it comes to trends, none of this matters.”

    No problem with that but everybody does not know what it is they are looking at, reading the posts here is evidence of that, and that is my point. It seems to me that the baselines need to be clearly defined, and made plainly clear and obvious to a even a casual reader on all anomaly charts. It can’t be that hard to do!
    I have learned, through reading this blog, to always look for the baseline. But it also seems to me that certain baselines are chosen to fit the argument being presented. I sometimes get the feeling that the creator of the chart is hoping that most people won’t notice a different baseline. And that keeps the old saying “figures lie and liars figure” popping in my brain.

  86. I have attached below an email from John Sapper at NOAA regarding reliability of the SST data in polar regions:

    —–Original Message—–
    From: John Sapper [mailto:John.Sapper@noaa.gov]
    Sent: Thursday, March 05, 2009 1:17 PM
    To: Nieuwenhuis, Fred
    Subject: Re: SST Anomaly charts

    Hi Fred,

    I should probably put a disclaimer on these images about the data not
    being reliable outside the 70 North to 70 South latitude range.
    I don’t think it is a sensor issue. Only that the data are very sparse
    in polar regions.

    Cheers,

    John

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