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Climate4You Update

Dear Jennifer,

Please find below a link which will take you directly to a monthly newsletter (ca. 1.5 MB) with global meteorological information updated to June 2012:

All temperatures in this newsletter are shown in degrees Celsius.

Previous issues (since March 2009) of this newsletter, diagrams and additional material are available for download on

All the best, yours sincerely,
Ole Humlum
Professor of Physical Geography
University of Oslo, Norway

PS The following chart from the update shows the change in ocean heat content for the top 700 metres since January 1955 from the National Oceanographic Data Center:


77 Responses to “Climate4You Update”

Pages: « 1 [2] Show All

  1. Comment from: toby

    there are few truer statements than the famous”lies, damn lies and statistics”. It doesnt matter which side of the fence you sit on, people abuse data and frequently completely subconsciously.
    When it comes to variability I found some of the past newspaper articles linked to by chris G on an earlier post very enlightening, and if you really want to see evidence of past weather events, then check out the amazing events that have been documented over the last few thousand years!

    the correlation between co2 and temp is not one that can be easily seen in a chart of temp and emissions…as climate4you data makes pretty clear…as does a look at a temp chart from 1880-2012 with co2. as many times when co2 climbs that temp falls…and couple that with strong evidence from proxy data that co2 lags temp increases…then you need to rewrite history to find co2 as a blatant culprit.

    Mention this fact on a warmer blog and you get shot down for ignoring PETM….this may be an example of co2 leading warming…but it should be abundantly clear that negative feedback effects dominate climate, otherwise we would be in a far more chaotic state!

  2. Comment from: bazza

    The comparison of 1951-80 and 2006 to 2011 illustrated that there had been a very large increase in the area of the globe impacted by extreme temperatures. ( extreme is defined here as a way out 3 SD for the stats fans). Now La NInas are the major regular contributor to cool periods in the short term as far as I know. So from 1951-80 they averaged about one in four years as you would expect over a period of that length. From 2006 to 2011 cooling La Ninas were about twice as frequent so you might expect fewer extremes other things being equal. They most clearly are not. The definition of extreme is about a 1 in a thousand probability. Extreme heat anomalies covered less than 0.2% of the globe over the period from 1951-80. But 2006 to 2011 extremes covered from 4-13%. Those are the facts – your beliefs are another matter. Apologies for the repetition to those who got it the first time but as the rest of the article showed, increasing variability, not just an increase in the means would be needed to get that big and alarming a change.

  3. Comment from: Robert

    Can someone tell the guy that the years from the fifties to the end of the seventies were part of a mid-century cooling we all know about and discuss frequently? Neg PDO (interesting influence, if still poorly understood), Global Cooling scare and massive ice in the Arctic by the 70s. The fifty years before that were a totally different story. Global Warming scares, documented low-ice minima in the Arctic in the early1920s, dustbowl conditions in the thirties in both US and Oz, half a century of rain deficit in most of Oz after the Fed drought, in spite of some ruinous floods and cold waves (for variability!)…

    For hardcore fans of variability and extremes, two of the three most lethal weather disasters in recorded human history occurred in the 1930s – floods in China!

    Lastly, the nature of the 2009 El Nino was completely different to those that came before, in that period after the late seventies. Same with La Nina. If we can’t see reality for superficial stats and ill understood influences expressed as simplistic mechanisms and levers, then we will end up believing any old trash.

    I, too, apologise for any repetition.

  4. Comment from: Debbie

    Did you also happen to notice that one of the few actual comments Bazza made about the Climate4You work was:
    climate changes a bit slower than weather,
    Followed by a rebuttal to my question about timeframes that pointed out that even Cohers knows that 10 years is not long enough (re the info on pp22-23 of Climate4You update)
    Now apparently, the period between 2006 to 2011, which according to my maths is 5 YEARS is indicative of a:
    a very large increase in the area of the globe impacted by extreme temperatures.
    Not only that:
    From 2006 to 2011 cooling La Ninas were about twice as frequent so you might expect fewer extremes other things being equal. They most clearly are not.
    And amazingly a 5YEAR timeframe is also now enough to make this statement:
    But 2006 to 2011 extremes covered from 4-13%.
    All of these are compared to a 29 year timeframe 51 – 80
    By Bazza’s own (rather vague) defintion of weather versus climate….wouldn’t a 5 year timeframe be just weather and also just commenting on wiggles?
    It appears Bazza accepts it is for OK for Hansen to use and draw conclusions from a 5 YEAR timeframe but it’s not OK for Humlum to use a 10 year timeframe?
    Perhaps he is correct and it is is all about that ‘other matter’?

  5. Comment from: Debbie

    It appears that the increase in extreme events is not actually materialising in our part of the world?
    Or indeed anywhere else?

  6. Comment from: Luke

    Debs – as an exercise look up what the IPCC says about storminess. Report back.

  7. Comment from: Debbie

    IPPC – different – I know.
    Is there something wrong with the observations of Climate4You and other observations that have been linked here?
    Is their methodology faulty?
    Have they incorrectly observed/recorded the evidence?
    And… what is an acceptable timeframe to observe climate as opposed to weather?
    So far it appears that there isn’t one….it just depends on whom is making the observations.
    Apparently it’s invalid for Humlum to make observatory comments on a decade of data (10 years) because it simply isn’t long enough…. but others are allowed to make far reaching comments about the climate using data in a 5 year timeframe….and:

    Those are the facts – your beliefs are another matter.

    Also Luke,
    Trying to globally average out the incidence of highly variable weather (like storms) ?
    Ummm….I know that it is possible to come up with a figure….but good luck with that one!
    It proves absolutely nothing USEFUL about the weather or the climate.
    It is, however, an interesting exercise in statistics.

  8. Comment from: bazza

    Were I to be shooting crap and an exceptional number of sixes kept coming up, would I a) crap out, b) get the dice checked, or c) play on and check the stats after another hundred rolls?

  9. Comment from: toby

    check for loaded dice…or loaded data?

  10. Comment from: Debbie

    ROFL! :-)
    Very clever Toby.
    I know you hate me asking questions….sorry.
    But was that you trying to justify why the 5 YEAR timeframe is now acceptable when commenting on climate statistical correlations and trends? Even when it is presented as a comparison to a 29 year timeframe?
    If it was….I would respectfully suggest you justify with evidence.
    An analogy with a crap game is ….well….. pretty crap really.
    You did say a few days ago that ‘even Cohers knows that 10 years is not long enough’.
    Maybe you might like to offer an acceptable, definitive timeframe that allows weather and weather wiggles to morph into climate… or…. does that just change according to something else perhaps?
    Just in case you decide to ask me my THOUGHTS…..I would say that using a 5 year timeframe and comparing it to data from a 29 year timeframe is simply NOT a statiscally valid exercise.
    Therefore unlike the extrapolation exercise on SLR….which at least followed a clearly stated methodology…this one would tempt me to borrow from Jen’s terminology:
    ‘pretty stupid’.

  11. Comment from: bazza

    Deb, try and think about extremes as being a bit about weather. Keep working on your questions and comebacks- Toby would not mind if you used that one about “lies, damn lies etc” next time you want to rebut a stat. Then of course you could use the one about all the worlds temperature records being doctored like the dice .Loved your work in your review of the Climate of the Nation – full of insights to be sure. Happy to respond any time you ask a considered question that seeks to advance a discussion. Still waiting.

  12. Comment from: Debbie

    Your point was?

  13. Comment from: toby

    Well the reality is that stats can be manipulated as both sides have shown to their detriment….it was an attempted joke as much as anything…thx for getting it Deb!
    It does not seem unreasonable to me to be somewhat sceptical about such a significant shift to extreme ( 3 sd’s…that is significant, but i am no stats expert) anomalies. We do know they have played around with station data and sites ( maybe for good reason….maybe not) but I would certainly wonder how big the error factor is in their data and if these anomalies lie within or outside these error factors?
    this point can be made in relation to a “global mean” as well in that the errorbar in creating this “mean” from memory is +-2f….but we are talking about a warming of 1.5f……in other words the data is telling us nothing?
    I still think the fact that your warm period is quite considerably warmer than the cool base period means it is highly likely that there will be higher highs….and potentially much higher highs from a known cool period… you say this is weather…..and over 5 years that is what you are talking about…but maybe over 30 years you can talk about climate… does the 1915-45 warm period relate to your 2006-11 period..or better still the 1980-2010 period so that we are comparing similar climatic time frames?……if the area suffering from extreme heat anomalies is lower then it would potentially support many of our comments here…if not it would support you?

    Rob’s point at 10.31 makes some interesting responses to you I thought?

  14. Comment from: Debbie

    BTW Bazza,
    I have no idea what you are ‘still waiting’ for.
    But I am definitely still waiting for you to
    a) keep your deal and
    b) please answer my question/s re the Climate4You work.
    I am still finding most of what you write to be about criticising others rather than an attempt to advance a discussion.

  15. Comment from: bazza

    Deb, check out the quadratic, check out how many times he mentions the recent run of La Ninas, check out if he has form as unbiased commentator. Check out Norwegian dependency on oil revenue. Dont worry about the data – it comes from reliable sources. His SLR extrap. was seen by you and Jen as OTT – it only takes one. His collection of graphs simply panders to cherry pickers and seduces the innocent.

  16. Comment from: toby

    Bazza I found only one comment that you can be referring to on climate of a nation and it related to a a very unscientific statement from our friend Luke;
    “No there’s only one possible cause for recent warming unless you believe in fairies “
    To which I suggested it is well known that the following have also contributed in varying degrees;
    sun, land clearing, land use, urban heat effect.
    and that a 1 % change in cloud cover is also potentially sufficient to have caused the warming.

    truth hurts huh?

    And you say above “His SLR extrap. was seen by you and Jen as OTT – it only takes one.”…so one use of poor stats/ data and that is enough to dismiss everything……and yet you are happy to quote the likes of hansen and mann, IPCC and any other well known warmist with a media profile….heaven help us!! you hypocrite!!!!

  17. Comment from: Debbie

    So Bazza,
    In the interest of discussing the evidence without the rest can I just paraphrase that answer to make sure we are on the same page? Please correct me if I have missed something.
    You think the data is perfectly fine but you are not fine with the way the data has been presented?
    So, you do have an objection to the methodology in relation to a focus (or lack of) on recent La Ninas and/or quadratics?
    You also seem to have a question about motives and Nationality? I question the relevance of that.
    I think the fact that I can’t see a useful/ valuable reason for the SLR projection doesn’t mean that the whole report should be dismissed, but you seem to think it should?
    So if those are correct ‘assumptions’, can you now please explain the fault in the methodology in relation to the stated context (or terms of reference if you prefer that terminology) in this Climate4You update?
    I’m not claiming that this report is anything other than what it is, which is an update of previous modelling, plus a few extrapolations based on clearly outlined methods.
    I am truly interested to know why you obviously strongly object to what is reported based on evidence.
    The cherry picking accusation is a total furphy (IMHO) if we are discussing statistical analysis.
    That is actually what all stat analysis does by its very nature, especially in projective work.
    That is paricularly true if we are trying to extrapolate trends and patterns in such an uncooperative beast that we call weather and/or climate.
    What needs to be clear is the methodology and the terms of reference.
    (IMHO) as always.

  18. Comment from: Luke

    “Truth hurts” exclaims Toby – so does drongoism

    sun – nope
    land clearing, land use – nope – in general makes the surface brighter – cooler
    UHI – nope – laternative lines of evidence – satellite, ocean, BEST etc

    Cloud cover – – net cooling!?

    Aerosols is your best bet for major change and you left it out – partially explains hiatus in warming

  19. Comment from: Debbie

    Did you actually read that Joel Norris paper that you have linked?
    I cannot see how it has disproved what Toby pointed out.
    In particular the cloud cover point.
    I don’t have any objection to this report as far as its ‘terms of reference’ are concerned, nor do I object ‘in principle’ to the MOST of methods that are clearly outlined.
    I draw your attention to pp 10 – 33 and particularly the conclusions on page 33.
    How does his observations differ from Toby’s basic point?
    Then look from pp 34- 60.
    I do question the validity/purpose of using different timeframes (which will radically alter ranges in stats)….but, for the purpose of this particular comment, will let that slide at the moment.
    The most important pages to note are his conclusions on pp59-60.
    How do these conclusions differ to Toby’s point?
    I will particularly note dot points 4 and 5 in the Norris paper pp 59-60.
    + there is not yet enough information available to attribute cloud trends to AGW
    + multidecadal reliable observations of the upper atmosphere over the ocean are not available.
    I also draw your attention to the number of times that Norris points out that the uncertainties outweigh any ‘settled’ answering of his opening questions.

    The question I am asking YOU is: in what way has this particular report DISPROVED Toby’s point?
    Because you have used it to claim this:

    sun – nope
    land clearing, land use – nope – in general makes the surface brighter – cooler
    UHI – nope – laternative lines of evidence – satellite, ocean, BEST etc
    Cloud cover… cooling!?
    If I sent Norris your comment…do you think he would agree with you that his report disproves Toby’s point?
    I will also note that Toby did not comment on Aerosols….but they are discussed in this report….but not relevant to your treatment of Toby’s argument.
    His point was basically….the ‘other’ variables have much more likelihood of affecting temp than AGW.
    He also DID NOT say a 1% INCREASE in cloud cover….he said a 1% CHANGE!

  20. Comment from: Luke

    Did you read the conclusion Debs – cloud cover since 1952 a net cooling effect. JEEEEEEEEEEZZZZZZZZZZZZZZ !

    Debs if you spent more time doing a modicum of elementary reading instead of opining out of your butt here you would know that aerosols are currently thought to be a major cause in the slow down in warming.

    Something about best bets and ask what the current practitioners think first – as a minimum courtesy.

  21. Comment from: Debbie

    ZZZZZZZZZZZ indeed Luke.
    So a 1% CHANGE in cloud cover either up or down for WHATEVER REASON?
    Your aerosols point is completely irrelevant in the context of your dismissal of Toby’s point.
    Just so we get this straight however.
    Would a 1% CHANGE up or down in cloud cover (disregarding the rest of the ‘others’ ) outweigh the statistical significance of what is THOUGHT to be the influence of areosols?
    Which is relevant to Toby’s point.

  22. Comment from: Debbie

    And further Luke,
    I was very, very careful to point out that I do NOT object to Norris’ work.
    I objected strongly to the way YOU chose to use it.
    He was careful to point out his terms of reference and his methods.
    There is nothing in there that DISPROVES what Toby pointed out.

  23. Comment from: bazza

    I have been moderated out, like was it Groucho said he would not want to join a club that would accept him ! I would have asked Debbie for the meaning of: “The cherry picking accusation is a total furphy (IMHO) if we are discussing statistical analysis. That is actually what all stat analysis does by its very nature, especially in projective work.”
    Now I know.

  24. Comment from: Debbie

    I am not sure I have interpreted your question correctly or even if there is any point in my attempt to answer it…..but here goes.
    I also qualified, very importantly:
    That is paricularly true if we are trying to extrapolate trends and patterns in such an uncooperative beast that we call weather and/or climate.
    IMHO Bazza,
    AND as an over riding qualifier I accept absolutely that what some would call ‘both sides’ have continually accused the other of ‘cherrypicking’….I actually agree that cherrypicking occurs (on both sides) but that in and of itself, it is NOT a valid complaint.
    Statistical analysis, especially projective work, is primarily an attempt to look for trends and patterns (or I guess in the work we’re discussing the terminology is better known as a ‘signal’) and use these calculations as a ‘tool’ to help us understand the world around us and also an attempt to help us make informed decisions about the benefits/disadvantages of ‘adjusting’ any inputs.
    What we attempt to do is model or extrapolate different ‘assumptions’ about various inputs that I guess can be (very) simply described as …..if everything else remains ‘equal’ or ‘basically unchanged’, what is the likely influence on the whole of a change in factor X?
    In economic projective modelling this can be a very useful exercise.
    It is also very useful in modelling ‘outcomes’ in numerous other professions….including climate science of course.
    In my personal business (Agriculture) we can easily see the advantages of using such a tool.
    We can factor in a ‘range’ of prices for our various commodities….a ‘range’ of different water allocations in relation to our planting windows…..a range of weather forecasts and rainfall forecasts….a range of varying prices in our input costs….and that can become ever more intricate and complicated and it has also become even ‘higher powered’ with new technologies and programming.
    All we then have to do is change one of those ‘inputs’ in those models to examine how that particular change could affect the whole picture.
    A simple example in my business would be to change the market price of wheat.
    If nothing else changes, that particular change either up or down will have a demonstrable effect on the whole business model.
    However….that one particular answer is ‘assuming’ that other equally important or even more significant variables like yield, the price of fertiliser/fuel, water availability, summer rainfall events, R&M costs, the market prices of the many other commodities we produce, interest rates, water quality etc etc etc etc ad infinitum ….will remain basically unchanged.
    That’s why I think the ‘cherrypicking’ argument….no matter what ‘side’ or what our ‘belief’ may be… is really a bit of a furphy.
    If we’re trying to focus on the significance of one ‘input’ then of course that input is the one we ‘adjust’ in the modelling.
    That can also be described as ‘cherrypicking’.
    The rest of my POV about the AGW debate is based more on the fact that this type of work is called ‘science’ and that it is ‘settled’ and that it can be used effectively as a primary decision making tool.
    I do not believe that to be the case and I have seen no evidence in the form of ‘measureable outcomes or results’ that would cause me to re evaluate.
    To me….that particular mindset/standpoint and the huge media/political argument it has created…. is part of the problem rather than part of of any practical solution.

  25. Comment from: bazza

    Debbie, I asked about your claim “The cherry picking accusation is a total furphy (IMHO) if we are discussing statistical analysis. That is actually what all stat analysis does by its very nature, especially in projective work.” You tried to justify it, I think, using your experience with what-if changes to budgets that excude uncertainty as you would expect. There is absolutely zero relevance to statistical inference .

  26. Comment from: Debbie

    Is that right Bazza?
    Zero relevance?
    To what in particular?
    Projective modelling?….or is it now ‘statistical inference’ ?
    I thought you wanted an explanation (or the meaning) of my comment about ‘cherry picking’ being bit of a furphy when we discuss projective modelling? (summarised version of original comment)
    I admit I was a bit unclear about what you asked….maybe you might try to ask questions in a less obtuse manner and minus the veiled, smarmy, personal insults?
    BTW…I don’t know why you got moderated as I didn’t see the comment….but I can easily guess on the evidence of past performance.
    But, nonetheless, as a further comment on your comments.
    (IMHO) as always….
    It doesn’t matter whether it’s to do with budgets or climate or weather or education or health or mining or insurance or hydrology or whatever else you care to name …’s still essentially a ‘what if’ exercise and it does exclude variability (or uncertainty as used by you) of other changes in other inputs as it examines the ‘what if’ proposition or looks for a particular ‘signal’.
    Are you now claiming that AGW projective modelling is NOT a ‘what if’ exercise that excludes uncertainties?
    You see Bazza….in principle I don’t have a problem with that….my very, very strong objection is the highly inappropriate political hijacking of this work….including the claims that it is ‘science’, that it is ‘settled’ and that it is a primary policy making tool that we should just ‘trust’ because it is all about ‘higher level principles’ or ‘the greatest moral challenge of out time’ or ‘ to protect future generations’ or ‘to mitigate the fact that climate changes’ or to protect us from ‘immiment catastrophic risk’ or ‘to protect the environment’ or to stop people getting cranky in traffic jams or to manage bush fire risk or the risk of houses falling into the ocean next century sometime or etc etc etc….
    That’s why I have no problem in principle with the Climate4You work or the Joel Norris work that Luke linked or Jen and Abbot’s paper and numerous others.
    They’re all fine if they clearly state the context and have a clearly stated methodolgy….even the majority of the AGW modelling that I have seen is fine as a statistical exercise. (and I realise that there is an exponential increase of such work….mainly because of aforementioned objection and one single person has little hope of reading a significant % of that!)
    But…I’m confident this comment is further proof of some type of personality fault on my part Bazza and that I’m doomed in some manner that I either simply don’t understand or that I don’t care enough about.

  27. Comment from: toby

    You were moderated out, bazza?..what here by Jen?

    is that why we have not seen a response to most of the points raised here? has the 1980-2010 period been compared with a similar warm period?
    is it not true to suggest your 5 year time frame is “weather” and you are comparing it to climate of a 30 year period?

    if watty is correct your anomalies will be a function of loaded data……

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