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Comments 72351 to 72400:

  1. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Norman, is that seriously the best you can come up with? That there were some prior events considered 'extreme' is not news to you, me, James Powell or anyone else. Additionally, cherry-picked news articles can hardly be considered credible enough to faithfully place weather events into their proper climatological context (usually kinda turns the readers off...). I'm sure the newspapers from Russia, Pakistan or other places would have been suitably apocalyptic in their prognosis of the relevant extreme events! What is more interesting is when data is placed into a climatological context, such as Peterson et al, or many other papers including Rosenzweig (outdated with regard to recent extremes by virtue of being published in 2001, but hardly supporting your case anyway). By the way, in Peterson et al fig 16, the smoothed line is most likely a moving average or other smoothing function so that you can see the trend over the noise. Is that the worst criticism you have of that paper, seriously? I'll echo michael sweet's request at #223.
  2. Visual depictions of Sea Level Rise
    adelady, thank you ... I'll have to think about the explanation.
  3. Ocean Heat Poised To Come Back And Haunt Us?
    Ummm, this paper shows how a hiatus in global warming can be totally consistent to climate models... ...but I seriously doubt that the 2000s were a hiatus decade, because: 1)Temperatures do not flattened: 2) As is evident in this NINO 3.4 timeseries, ENSO was either neutral or moderate El Niño for most of past decade. The only significant La Niñas were in 2007-2008 and 2010-2011. This is consistent with the previous graph, that shows continuing warming except for a small hiatus in 2008-2009. Certainly a 2-year cooling or flattening is not a warming hiatus decade, is just a minor yearly fluctuaction. The warming pattern is different that the pattern of figure 4: Showing strong warming in the Arctic, unlike figure 4, that shows strong cooling. So is an interesting article, but it could explain some possible warming hiatus decade in the future, not in the present.
  4. Ocean Heat Poised To Come Back And Haunt Us?
    Re #1. Roughly decadal or perhaps roughly 11 years? http://www.woodfortrees.org/plot/sidc-ssn/from:1960 It is perhaps coincidence that the period where this whole haitus thingy starts (~2002) happens to be around the maximum of solar cycle 23, since which we've seen a significant drop to the solar minimum of 2009.
  5. Correction to the True Cost of Coal Power - MMN11
    Not. all. economists, Michael.
  6. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Norman, Your list includes many newspaper headlines. I recall last fall when deniers trumpeted a headline stating England was having the coldest winter in 350 years. It did not pan out that way. Dr. Masters has researched his list and when he says it was the worst flood in Pakistan in 500 years that is believable. The newspaper headlines you quote are not vetted and not believable. Please provide a peer reviewed list of disasters. I will note that last year there were 19 countries with all time highest temperatures and none with all time lows. How does that list count for extreme weather? Top that, if you can.
  7. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Norman#219: Nice article you've cited: Human activities are causing the augmentation of the natural atmospheric greenhouse effect. Future climate models (which should not be accepted uncritically) predict that anthropogenic forcing will bring about changes in the magnitude and frequency of all key components and natural cycles of the climate system. Climate change will gradually (and, at some point, maybe even abruptly) affect regional and global food production. Warming temperatures and a greater incidence and intensity of extreme weather events may lead to significant reductions in crop yields. --emphasis added Given that this was in 2001, perhaps those projections are coming home to roost. Oops, that was a short compilation of news events.
  8. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Daniel Bailey @220 I am not actually allied to the c3 website and I do not agree with their thoughts on Skeptical Science. I like this web site and it contains a vast amount of useful information. I like the strict moderation to keep things on topic. I just saw the list of items on this page and clicked on several to see they were newpaper items. I do not know how else one can determine extreme weather events since they do not always leave evidence that can be analyzed later. I do not want to disappoint and will steer clear of c3 or other type blogs for gathering evidence of the point I am trying to make. That weather may not be getting more extreme as the globe warms.
  9. Ocean Heat Poised To Come Back And Haunt Us?
    Rob Painting @#6 The NODC datasets for ocean heat content to 700m and to 2000m are divided up into contributions for the northern and southern hemispheres. They are at ftp://ftp.nodc.noaa.gov/pub/data.nodc/woa/DATA_ANALYSIS/3M_HEAT_CONTENT/DATA/basin/yearly/h22-w0-2000m.dat and h22-w0-700m.dat. Shouldn't they also show that the heating of the deep ocean is more pronounced in the southern hemisphere? I haven't plotted those data, and I don't have any feeling for what the coverage of the measurement grid is in the lower southern ocean.
  10. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    To tack onto muoncounter's able comment above: I would not trust any information from a site such as c3 (given its history) in any fashion, to the point of even checking what the time of day was compared to that shown on the website. No compilation of news events, no matter how lengthy, should be relied upon with any form of scientific accuracy. There is simply no context to base any kind of assessment. It is simply a cacophony of anecdotal events in tabular form, listed with the presumption by the reader that it is not only complete but accurate as well. At best, one may consider it interesting in the same sense that one finds supermarket tabloids interesting. Honestly, it is difficult to even know how to respond to you Norman, without it sounding cross. You continually cherry-pick, use anecdotal references interchangeably with scientific ones and preferentially cite denialist websites preferentially over scientific ones. This latest site you ally yourself with has this post:
    "SkepticalScience.com: The 'SS' Global Warming Propaganda & Lie Machine Exposed - Fundamentally Evil"
    Seriously? Since you, by extension/virtue of your reliance upon c3, maintain that Skeptical Science is "Fundamentally Evil", then why are you here? I, for one, no longer believe your protestations of 'just looking for the truth' (paraphrased). It can no longer be construed as innocent mistake your predilection for frequenting & citing such websites as c3. Indeed, I am personally quite offended by this most recent tack you have taken. It was a mis-step; you have over-played your hand. And I am very disappointed.
  11. Correction to the True Cost of Coal Power - MMN11
    It is amazing how economists wil devalue the lives of our children (and ourselves if you are less that 60).
  12. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Daniel Bailey, Here is a link to a peer-reviewed article that shows similar patterns to the c3 website. Look at Table 1 of the link. Severe droughts and severe floods from 1977 to 1998. Many samples of such events taking place. It does not seem to be as alarming as James Powell feels it is. Peer Reviewed article with list of weather extremes.
  13. Ocean Heat Poised To Come Back And Haunt Us?
    I am still curious about the physical systems that draw warmth down to the depths. As per my question a couple of weeks ago, how, when the physical processes are so little known, are we able to ascertain mixing rates in order to determine, for example, that oceanic thermal lag takes about 30 - 40 years to reach equilibrium with changes in forcing (Equilibrium Climate Sensitivity)? Also, I read about the 30 - 40 year lag, but also that ocean turnover takes 100s of years - and that these are not to be confused. But it is confusing. Why is the centennial turnover rate not a factor in ECS, and how does one make these distinctions when the physical processes of vertical mixing are so little understood? (At least, I have not found much in the literature or elsewhere that suggests we know more than a little about where and how vertical mixing takes place. I have enquired before, but no luck with recommendations so far)
  14. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Okay, so in spite of my better judgement, I clicked a few of these - and there was good old Steve G, Prince of CherryPickerville. Including the infamous picture of USS Skate, supposedly at the 'ice-free' North Pole. That's the problem with a 'source' like C3: there is no vetting of the material cited, which leaves those gullible enough to take it on face value thinking, 'wow, that's a lot of information - must mean something.' We've had another player - friend PT - who operated the same way. It's also a Faux News tactic - 'people are saying that global warming is ... ', when the 'people' saying those things are the Faux News on-air talking heads. Repeat it often enough and it must be true, no? In addition, Norman: please note that many of these headlines are reports of disaster - bridge collapse, 400 dead, etc. You've specifically disputed the use of disaster counts as meaningful - yet here they are being used by you.
  15. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    [ response to deleted snipped ] The topic of this Thread is "Extreme weather and Climate Change". Finding a large sample of past extreme weather events that compare to those in James Powell's ebook should not be considered off-topic or extraneous. It is what the topic is about. The topic is Global Warming causing climate to shift in such a way that more extreme weather will be the result. If it can be clearly demonstrated that extreme weather events are not exceptional for these last few years (by showing large lists of past extreme weather events that are very similar to the ones brought up today), then that would seem a valid position to consider.
  16. Models are unreliable
    DB, I appreciate your response. In fact, I have already pointed out the fact that anomalies rather than absolute temperatures are used for the reasons stated by NOAA. My problem was that I was not sufficiently confident of my facts regarding the models to say for certain that the raw data output does not appear in the form of absolute temperature. It certainly wouldn't make sense for it to do so given that the global temperature datasets are presented as anomalies, but I wanted to check up first. Thanks, Paul
    Response:

    [DB] Apologies; I didn't mean to imply that you hadn't.  My intent was to provide you with a sourced, concise reference.  Sphaerica gives some good links to resources on models here.

  17. Ocean Heat Poised To Come Back And Haunt Us?
    Karamanski - without going into technical detail - think of how heat is lost by the human body when you sweat, the evaporation of moisture takes heat with it, cooling the skin. In much the same way, the same thing occurs over the surface of the Earth. Consider how much cooler local temperatures are in tropical forests (with lots of moisture) compared to dry regions of the world at similar latitudes. I'll track down some papers for you - if you're genuinely interested (I do remember a very recent one about forests and water recycling cooling the Earth surface). As for the PDO, AFAIK I don't think an actual mechanism has been discovered. So whether it can be responsible for anything is moot.
  18. Ocean Heat Poised To Come Back And Haunt Us?
    Karamanski, I assumed (anyone can correct me if I'm wrong) that it is a result of increased evapotranspiration/Latent heat. The added water on land gets less energy put into heat/temperature, because it goes instead into evaporating at least some of the additional water (which requires a substantial amount of energy -- 600 times more to evaporate water than to raise it 1˚C).
  19. Ocean Heat Poised To Come Back And Haunt Us?
    It doesn't make any sense how more rain over land would cool global surface temperatures during La Nina and how less rainfall over land would warm global surface temperatures during El Nino. I was also wondering what cycle governs when hiatus periods occur. Is it the Pacific Decadal Oscillation, or increased frequency of La Ninas?
  20. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Daniel Bailey @214, I would hope that linking this sight does not undermine my credibility. Someone took the time (which would be a daunting task to compile) and gathered newpaper clippings of extreme weather events in the past. If one ignores the opinion of the author of the sight and concentrates only on the actual data (Newpaper clippings from around the world on extreme weather events) you get a historical perspective on severe weather events in number, intensity, and time frame. If you would insert Jeff Masters 2010-2011 weather compilation into this long list would it still stand out as something not seen since 1816? When looking at the whole globe, it would appear that somewhere they are experiencing extreme weather quite often. Look at some of the headlines in the long list of extreme event. Here is a sample: "1976: Worst Drought In England And Wales For 500 Years" "1951: Mississippi River Reaches Highest Level For 107 Years" "1951: 100 Degree Heatwave Lasts For 7 Weeks In Texas" "1952: Scientist Says Both Polar Ice Caps Melting At Alarming Rate" "1977: Worst Drought In California History - Year 2" "1977: Antarctica Iceberg Is 45 Miles Long & 25 Miles Wide"
  21. Models are unreliable
    With reference to my post above, I've now been given a link to the article it is apparently based on. It's from lucia at The Blackboard Has anyone come across this before?
  22. Ocean Heat Poised To Come Back And Haunt Us?
    Critical Mass - See Sutton & Roemmich (2011). Based on the observations, they indicate that most of the ocean warming is occurring below about 35°S. Not so co-incidentally the model used by Meehl (2011) indicates that is where most of the heat uptake to the deep oceans is occurring too, although I don't mention that in the post.
  23. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    213, Norman, Wow. That's just amazing. You (and your source) have proven that there have been extreme weather events prior to the advent of AGW, therefore AGW must not be affecting extreme weather events. Well done! Fantastic! Well, I'll certainly sleep easier tonight.
  24. Ocean Heat Poised To Come Back And Haunt Us?
    FundME - For the warm-coloured regions (in figure 4) - think of what happens when you pull the plug from the bathtub - you get this rotating mass of water as it disappears down the plughole. Those warm-coloured regions are gyres - rotating masses of water, and these are affected by wind speed. Increase wind speed and more heat is driven down into the deep. It's whole lot more complex than that of course, but that's the broad picture. Remember too, that the cool water brought to the surface during La Nina or La Nina-like periods, allows it to be warmed by the sun (that's how the ocean are warmed). So that surface layer, even though it is causing cooler global surface temperatures, is steadily gaining heat. These two processes are operating at the same time. Is that any clearer?
  25. Ocean Heat Poised To Come Back And Haunt Us?
    Joshag - Nice work there. I've not seen any observation-based studies which look at this issue, so I'll see if I can get a reply from some of the experts working on this. It does seem to support the decadal trends seen in the climate model though.
  26. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Norman, why is it in your desire to prosecute your agenda (and it is patently obvious you have one) you first frequent the denialist and dissembling websites for ammunition rather than relying upon the science and the scientific method themselves? A hint: The words "Gore 'Lie-A-Thon' " on the top of your linked source should have been a tipoff of bias. And a very typical page at c3. Reliance upon this type of "source" undermines your credibility severely.
  27. Models are unreliable
    A blogger has just posted an objection to climate models that I haven't come across before. Hopefully someone here knows more about it than me. The claim is that: "By concentrating on anomalies they (scientists) hide the fact that the models get the absolute global temperatures wrong by as much as 2C." I was under the impression that temperature anomalies are used because they correlate well over large distances, whereas absolute temperature doesn't. This sounds like the type of argument that McKitrick and Essex might have used. Any ideas, anyone? Thanks, Paul
    Response:

    [DB] "By concentrating on anomalies they (scientists) hide the fact that the models get the absolute global temperatures wrong by as much as 2C."

    The key word in your quote is "hide".  Your blogger is operating under the premise that there is a conspiracy, therefore ____________ is true.  This is a blatant obfuscation, easily proven wrong.

    From the NOAA page:

    1. Why use temperature anomalies (departure from average) and not absolute temperature measurements?

      Absolute estimates of global average surface temperature are difficult to compile for several reasons. Some regions have few temperature measurement stations (e.g., the Sahara Desert) and interpolation must be made over large, data-sparse regions. In mountainous areas, most observations come from the inhabited valleys, so the effect of elevation on a region’s average temperature must be considered as well. For example, a summer month over an area may be cooler than average, both at a mountain top and in a nearby valley, but the absolute temperatures will be quite different at the two locations. The use of anomalies in this case will show that temperatures for both locations were below average.

      Using reference values computed on smaller [more local] scales over the same time period establishes a baseline from which anomalies are calculated. This effectively normalizes the data so they can be compared and combined to more accurately represent temperature patterns with respect to what is normal for different places within a region.

      For these reasons, large-area summaries incorporate anomalies, not the temperature itself. Anomalies more accurately describe climate variability over larger areas than absolute temperatures do, and they give a frame of reference that allows more meaningful comparisons between locations and more accurate calculations of temperature trends.

    NASA has a nice synopsis on models, here.

  28. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    michael sweet @212 It appears someone has already compiled a list of what I have been looking for. This person took extreme weather events from the 1950's, 60's and 70's and put them on a list. I will link you to this webpage and you can see what you make of it. List of some extreme weather events.
  29. Philippe Chantreau at 06:38 AM on 16 October 2011
    Continued Lower Atmosphere Warming
    Of course muon, that's the way it will inevitably be represented by some. There is nothing anyone can do about that. The attentive reader who wants to know will notice that Dr P in fact showed nothing. Sure he showed that there is no warming "trend" since 2002 but also readily acknowledged this was meaningless because no trend, or lack thereof, can be establish over that time period. Then when asked by why he would devote so much attention to a meaningless trend, he was rather evasive. I must say I found that whole exchange rather surprising considering Dr P's background. We had countless occurrences on this site of people arguing about meaningless short term "trends", I recall there were threads devoted to the explanations of why short term says really nothing. I do not remember any respectable scientist with a deep understanding of noisy time series making that same argument.
  30. Visual depictions of Sea Level Rise
    shibui Try this one.
  31. Visual depictions of Sea Level Rise
    According to Steven Goddard at Real Science, the Envisat data is showing a drop in sea levels.Does anybody have any information on this?
  32. Continued Lower Atmosphere Warming
    DM#60: "it is not unreasonable to expect the same from the skeptics" There are 'skeptic' circles with a far shallower understanding of the foundations of this bridge. I'll go out on a limb and make a devil's advocate speculation: In those circles, this exchange will be played as 'Dr. P showed that warming really did stop and they couldn't show that to be false.' Of course, the other hypothesis could be that there will be universal acceptance within the 'skeptic' world that it cannot be proven that warming stopped. Anyone care to give odds on which hypothesis will win out?
  33. Continued Lower Atmosphere Warming
    Dikran, that was a great explanation of power!
  34. Ocean Heat Poised To Come Back And Haunt Us?
    Rob Painting might care to comment on this quotation by Berenyi Peter on a prior thread. It poses an interesting theory about how the overturning is mechanicaly driven: Quote: (-Very long quotation snipped-). unquote I believe the forties and fifties south latitudes are not well measured and therefore the extnt of heat sequestration or loss to space is largely unknown.
    Response:

    [DB] Please provide a link plus an explanation of why it is relevant to this thread.  Long quotations are considered poor etiquette and are frowned upon.  Thanks!

  35. Dikran Marsupial at 01:47 AM on 16 October 2011
    Continued Lower Atmosphere Warming
    Here is another way in which Prof. Pielke could demonstrate that the post-2002 trend is interesting, rather than just a likely artifact from looking at a noisy time series over too short a timespan. Rather than basing the argument on the failure to reject a null hypothesis, he could instead reframe it so that he was arguing for an alternative hypothesis, for instance H1: The rate of warming has diminished since 2002 And then see if he could reject the null hypothesis H0: The rate of warming has remained constant throughout He is then back in the normal statistical hypothesis testing setting, where he has to show that the observed trend is inconsistent with H0. This is straightforward, if you detrend the data, assumung a constant linear trend over the entire time series, H0 can be rejected if the residual trend from 2002-present is statistically negative. Now if we are going to talk about bridge-building, then I would say that I have built my side well over half way. I have listened to Prof. Pielkes argument, but I have seen what I consider to be a fatal flaw. I have pointed out this flaw, and remained patient and civil when my criticism has been repeatedly ignored (which is a rather disprepectful thing to do). I have now explained why the criticism in some detail to show why it is important, and even suggested two ways in which Prof. Pielke could strengthen his argument to the point where I would accept it. The latter certainly goes well beyond duty; the onus was always on Prof. Pielke to test his hypothesis before publicising it, as he himself said. I am deinitely in favour of building bridges with the skeptics, but if the the foundations of the bridge have to be built on the tacit acceptance of scientific arguments that are clearly fundamentally flawed, then the bridge is unlikely to stand for long, even if it can be completed. I doubt any of us here at SkS expect skeptics to accept any argument just because we think it is obvious, and it is not unreasonable to expect the same from the skeptics (a term I view as high praise rather than perjorative).
  36. Eric (skeptic) at 00:21 AM on 16 October 2011
    Continued Lower Atmosphere Warming
    It seems to me that a good way to determine the significance of a trend in a particular portion of a time series is to perform an analysis on the entire length of the series based on an assumed model. The model will prescribe the length of the series needed. The model is based on theories of various phenomena in the physical system being studied, in this case the atmospheric temperatures and their strong dependence on ocean-atmosphere heat exchange in quasi-cycles, in particular ENSO. When the entire time series is analyzed based on the model, the analysis produces an explanation of the variance in the series which can then be used to determine the statistical significance of a trend in a portion of the series. Here's an example: http://www.atmos.berkeley.edu/~jchiang/Class/Fall08/Geog249/Week13/gv91.pdf
  37. Ocean Heat Poised To Come Back And Haunt Us?
    # Heat buried in the deep ocean remains there for hundreds to thousands of years. It is not involved in the heat exchange occurring in shallower layers. # The ocean, as a whole, is still steadily building up heat, so the next warm phase of this natural cycle may drive global temperatures to new record highs (the ocean heat coming back to haunt us). I am having difficulty reconciling the two statements litsted above. Also when you say # The deep ocean warms during these hiatus decades because heat builds up in mid-latitude regions and is quickly funneled downwards. Do you mean the mechanism can be imagined as a giant funnel whereby the warm water is gathered over a large area at the mouth of the funnel and is somehow compressed downward towards the spigot by which it is transported to depth? I see it as some sort of giant hypodermic syringe by which the warm water is injected to depth. Am I right in these assumptions or is there some other mechanism at play.
  38. Dikran Marsupial at 23:41 PM on 15 October 2011
    Continued Lower Atmosphere Warming
    So how could Prof. Pielke estimate the statistical power of the test? There are many ways you could go about this, but this would be my recipe: According to Tamino, temperature time series are well approximated by a linear trend with ARMA(1,1) noise process. The first step would be to detrend the data and estimate the parameters of the ARMA(1,1) noise process (see this article by Tamino and this one). I can then simulate as many synthetic temperature times series as I like, with the expected effect size under the alternative hypothesis (warming has continued at a constant rate throughout the UAH dataset), by adding ARMA(1,1) noise to a linear trend of (IIRC) 0.138 degrees per decade. Next I generate a large number of these, where we know by construction that the null hypothesis is false, and see how often we get a statistically significant trend from 2002-2011. The proportion of trials where we can reject the (false) null hypothesis (zero trend) is an estimate of the statistical power of the test. I very much doubt it will be 0.8 or above, which is the traditional threshold for useful statistical power. Note we should test the significance of the trend assuming ARMA noise, not white noise. We know the data are correlated, so the confidence interval for the OLS trend will be optimistically narrow, which biases the test. This would be my approach, and if Prof. Pielke could demonstrate useful power by an estimate of that nature, then I would be convinced that the "flat trend since 2002" was of genuine scientific interest, rather than just the a random artifact from looking at a noisy signal over too short a period. Unlike me, Tamino is a genuine expert in time series analysis, so he may have a better test, or be able to pick holes in my recipe, I would of course take any critcisim seriously. The ball is in Prof. Pielke's court; if he wants to convince us that the post-2002 trend is interesting, I have set out what he needs to do. If he wants to concede the point and move on, then that also is fine.
  39. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Joe Romm reports on extreme flooding in Thailand this month and last. It is by far the most expensive flood in Thai history and has resulted in 10% of their rice farms destruction. They are (were?) the largest rice exporter in the world. They often get heavy rain during La Nina, but the current Nina is fairly weak. Joe links to Jeff Masters blog about this flood. Do you eat much rice? The price will rise this year. Maybe this is just another coincidence and the weather has not responded to AGW, or maybe we are looking at the future.
  40. Every Picture Tells A Story
    Since we're talking about pictures telling a story, watch this on the BBC homepage (and apologies if someone already posted it): http://www.bbc.co.uk/news/world-south-asia-15216875 Melting in the Himalayas captured in photographs.
  41. Continued Lower Atmosphere Warming
    53, Ger,
    I have the impression that all models used are equilibrium models...
    And why exactly would you think that? I suggest you read Climate Models: An Assessment of Strengths and Weaknesses (click the Download PDF link to get the full report).
  42. Dikran Marsupial at 20:57 PM on 15 October 2011
    Continued Lower Atmosphere Warming
    Following on from Glen's excellent comment, I'm going to have a go at explaining to a non-technical audience what I was asking for when I asked Prof. Pielke for the statistical power of the test of the hypothesis. Hopefully this will help explain why Prof. Pielke's assertiones relating to short term trends are potentially deeply misleading. This is likely to be quite a long post, so I may have to make it in installments. Statistical Hypotheis Testing Statistical hypothesis testing is a confusing issue to many, so I will start by running through a simple example. The first step is to form an hypothesis. Lets say I have a coin, and you want to determine if the coin is fair (equally likely to fall as heads as it is as tails), or biased (more likely to fall on one side than the other). Let P be the probability of the coin falling as a head. We first construct the alternative hypothesis (H1), which is usually the thing we want to prove (though not in Prof. Pielke's case as we shall see later), which we can write as H1: P is not equal to 1/2 We also need a null hypothesis, H0, which is normally a statement of what we want to disprove. This is usually the opposite of the alternative hypothesis, H0: P is equal to 1/2 The way statistical hypothesis testing works is to observe some data, and then to see how unlikely it is to observe a set of data as "extreme" or "more extreme" than that we actually observed, if the null hypothesis is true. We call this value the p-value. If the p-value is less than some threshold, α, then we conclude that the null hypothesis is unlikely to be true, so we say "we reject the null hypothesis at the 1-α level of significance". Scientists traditionally set α=0.05, which gives the usual "95% level of significance" that people often talk about. If the p-value is higher than α then we conclude that we can't rule out the possibility that the null hypothesis is true, so we say "we fail to reject the null hypothesis at the 1-α level of significance". At this point, I want to make some observations:
    • If we are able to reject H0, that doesn't prove that H1 is true. We haven't evaluated the probability of the observations if we assume that the H1 is true, and that probability might also be very small!
    • If we can't reject H0, that doesn't mean that H1 is false, it just means that we can't rule H0 out, and if we can't rule H0 out, we can hardly claim that H1 is true.
    • The test is not symmetrical, the outcome of the test only depends on H0, H1 doesn't come into the calculation at all. So if we repeat the test and exchange H0 and H1, we won't necessarily obtain the opposite result.
    O.K., so lets have a practical example, say we flip the coin eight times and it comes down heads each time (this ought to make us rather suspicious!). If we assume that the coin is fair, then the probability of observing a head on each flip is 1/2 and as each flip is independent the p-value is given by p = ½ ×½ ×½ ×½ ×½ ×½ ×½ ×½ = 1/256 This is less than α = 0.05, so we say that "the null hypothesis (the coin is fair) is rejected at the 95% level of statistical significance", which is in accord with out expectations. Lets now consider what happens when we only observe one flip of the coin. Our intuition should tell us that in this case there clearly isn't enough data to data to determine whether the coin is fair or not, so lets see what the test tells us. This time, computing the p-value, we get p = ½ This is much greater than α=0.05, so we say that "we fail to reject the null hypothesis at the 95% level of statistical significance". This example demonstrates that a failure to reject H0 does not necessarily imply that H1 is false, it may just be the case that there simply isn't enough evidence to reject H0, and both H0 and H1 remain plausible given what we have observed. So, how can we distinguish between the situation where H0 is true and the situation where H0 is false, but we just don't have enough data to demonstrate that H0 is likely to be false? One thing we can do is to look at... The Statistical Power of the Test The statistical power of a test is the probability that the test will reject H0 if H0 actually is false. Let us assume that the coin actually has a head on both sides so that P=1, in which case we know for a fact that H0 is false. In this extreme case, we will get a head every time we flip the coin, so if we flip it once the p-value will always be p = ½ and we will always fail to reject the null hypothesis, even though it is false, so the statistical power of the test is zero. If we flip it twice, the p-value is p = ½×½=¼ and again we will always fail to reject H0, even though it is false, so the statistical power of the test is still zero. The fact that the statistical power of the test is zero tells us that even though we weren't able to reject H0, it was probably just the case we didn't have enough data, rather than because H1 was false and H0 was true. If we carry on flipping the coin, when we get to six flips that all come down head, the p-value is p=½×½×½×½×½×½× = 1/64 we have now reached a point where the test always rejects H0 when it is false, so the statistical power of the test is now 1. Now this is an extreme case, where P=1 or P=½. If we could have a less biased coin, say P=0.75, it would take more data to be able to reject the H0 when it was false, because in that case you would see tails in the sequence of flips whether the coin was biased (H1) or not (H0). However, that would make the maths more complicated, but is not necessary to get the basic idea of statistical power. In practice, the statistical power of the test depends on (i) the amount of data available, the more data, generally the higher the power; (ii) the expected size of the observed effect if H1 is true, the larger the expected effect size, the higher the power; (iii) the amount of noise masking the expected effect, the more noise, the lower the power of the test. This makes computing the statistical power of the test rather difficult to evaluate, so most scientists ignore it. This is often O.K., provided you are not trying to base an argument on the fact that we fail to reject the null hypothesis, which is exactly what Prof. Pielke is doing, which is why he is required to show that the statistical power of his test is high enough that the failure to reject H0 is meaningful. I asked Prof. Pielke no less than three times to state the statistical power of the test, and he was either unable or unwilling to answer the question, or even engage in a discussion of the subject. I find this highly disturbing behaviour for an experienced scientist. Just looking at the data and seeing the obvious is not a reliable way to conduct science, if the obvious is not confirmed by statistics, perhaps it isn't as obvious as you think. N.B. Bernard J. is also asking Prof. Pielke for the statistical power of the test, which is often written as (1-β), where β is the false-negative rate of the test (α is the false-positive rate). As Prof. Pielke is making an argument based on a failure to reject a null hypothesis, he needs to address this point if he wants the argument to be taken seriously. His failure to address this point is extemely damaging to his position.
  43. Ocean Heat Poised To Come Back And Haunt Us?
    @Rob Painting Hansen presented an image (figure 9b) with the ocean heat uptake (0-700m) in his paper: ACPD 2011 Earth’s Energy Balance and Implications The green line in his figure 9b is from the Levitus-data. The 0-2000 m ocean heat content data are now also available. I used these data to construct the same graph graph for both datasets (700m and 2000 m). When you subtract the ocean heat uptake values of the two datasets, you should get an idea in which period the deeper ocean gains more heat than the upper ocean. A nice wave pattern appears with roughly a decadal pattern: Is this image a visualization of the decadal pattern you're talking about here or am I messing things up?
  44. Continued Lower Atmosphere Warming
    ssn tsi, correlate somewhat http://woodfortrees.org/plot/pmod/normalise/mean:30/plot/sidc-ssn/from:1970/normalise/mean:30
  45. Continued Lower Atmosphere Warming
    With this thread seemingly coming to a close, with the next installment shortly, I would like to thank all the participants for the way in which this has been conducted. It is uncommon that 'on-line' debates actually have anything but a marginal relationship to the true principle of debating. The civility of the tone here is in welcome contrasts to the majority of the AGW Blogosphere. That said, I would like to make a general philosophical observation that is related to this topic in a broad sense. Climate models make predictions of future temperature changes based on assumed GH gas concentration changes. These predictions contain error bands for the predictions which reflect the various uncertainties in the estimate. In particular the limitations that models have had (at least up to now) in predicting variability, sub-decadal changes etc. Climate variability of +/- 0.2 C/decade is typical and since this is also within the range of estimates for underlying trend, certainly decade or less time scales are inappropriate for comparing observations with projections, particularly with reference to atmospheric temps alone, TLT or SAT. So observed temps to date are entirely consistent with expectations of an underlying trend with an overlaid variability. If such a hiatus period persisted for several decades that would be cause for re-evaluation. The statement I made above however is what I would expect any reasonable person in professional person in Climate Science to reasonably agree with, as well as technically educated and well-numerate lay observers/enthusiasts of Climate Science. Such would be the circle of Authors here at SkS and many of the regular posters. However, that does not include 99.99% of the human race. Most people don't have technical educations that let them easily evaluate the sort of information presented her at SkS, Dr Pielke's Blog, RC or even the IPCC. Being able to evaluate the difference or significance between a 10 year trend and a 17 or 30 year trend, let alone a model based trend with 'error bars'; To those familiar with science, an error bar is a margin of accuracy. To most people, an error is something that is incorrect. So when discussing the sorts of issues put here, everyone needs to be aware that the discussion is being carried out in front of an audience of others with wildly varying degrees of technical and numeric literacy. And that is before we delve into the world of those individuals who want, need, to believe that AGW is all wrong. To the commenters here discussion of the 'it hasn't warmed much since xxxx has significance yyyy' variety is a reasonable technical discussion. To many of the lay-public this sounds like someone saying 'It hasn't warmed since xxxx therefore WARMING HAS STOPPED! So much for these AGW theories!' The point I am trying to make is that in puting up comments in a technical discussion, participants need to be aware that their conversation is being read by others who may not 'process' their comments in the way intended by the author. So there is a continuous, demanding requirement to express ideas in ways that cannot be mis-construed by a less technical audience. Our comments can easily mislead just because we do not allow for the knowledge-base of our audience. So when authors here at SkS defend the use of longer time-scales as a basis for looking at trends, they are not simply attempting to ignore the shorter timescale details that may have a relevence in considering the dynamics of short term climate variability questions - a technical discussion. They are also trying to defend against a less technical audience drawing inaccurate conclusions from the comments because they do not understand the numerical details, or because they have an entrenched position where they want to find grounds to reject AGW in-toto and simply want ammunition. Look at the example of Al Gore and his movie. This was aimed at a mass audience who know diddly-squat about climate science. So he shows the Ice Core data with CO2 & Temps tracking each other pretty much in synch but he doesn't highlight the 800 year time-lag. He was aiming this at a mass audience trying to give a generalised, simplified over-view perspective. Then the fact that he didn't highlight the Temp/CO2 time lag (or the Methane signature, Ice Sheet change time lags, variations in dust levels, changes in vegetation patterns, ocean circulation patterns etc) has been taken by some as being evidence of a deception. When in fact it was simply a simplification for general consumption. It is a reality in the hyper-charged world of AGW Politics/Science that there are some groups and individuals who WANT to show AGW as false - hence the D-word applied to them. And they will commonly take comments & statements, whether from the IPCC or a simple blog-post and try to build ammunition from it to distort and mislead others and defend their 'needed' position. This is in contrast to those who may be truely skeptical - with the critical open-mindedness this implies. However the D'ers are all to eager to cloak themselves in the rainment of 'skeptics'. So as a general comment/plea to all participants here. Ask yourself: 'Who is my intended target audience when I make this comment?'. And more importantly, 'Who will be the ACTUAL audience for my comment, intended or otherwise?'. When making a point on a technical issue of statistics or thermodynamics, will my comment be something that can easily be miscontrued by the uninformed, or worse, misrpresented by the malicious well informed. In this technical debate is important. But care and precision with semantics and language is vitally important when the debate is public. And this is the Internet. EVERYTHING is public.
  46. Continued Lower Atmosphere Warming
    Like others, I feel disappointed by this discussion with Dr. Pielke. We all have been taught that if the data are not sufficient to come to any conclusion we should look for more, not just stay there. The reason why one should stubbornly stick to a non statistical significant trend disgregarding the great part of the data (which we have) is beyond me.
  47. Continued Lower Atmosphere Warming
    With a climate system obeying a more or less chaotic model,is the type of statistics applied the correct one? I have the impression that all models used are equilibrium models, on which a kind of perbutration theory is applied, which is assumed to be Gaussian in nature. All the methods in deriving general parameters are based on those assumptions known to hold for stable, equilibrium models. Just saying that one can battle for years to come over a method which is not applicable in this case. What does stand is that CO2 has rissen sharply and sure it will end up into a different environment, probably not one we or any other higher life form can adapt to so quickly (I give the simple single cell forms a good chance to survive)
  48. Pete Dunkelberg at 16:06 PM on 15 October 2011
    The Dai After Tomorrow
    Daniel, Thanks for looking into this! I'm not sure it's cleared up though. I referred to figure 11 (c) which is for 2000-2009, a period we have just lived through. The base period is 1950-1979, also familiar. I would expect the base period for the online PDSI maps at NOAA to be similar. In addition, reading Dai's paper from the top as I did, and seeing his other figures including figure 7, I still have trouble matching fig. 11 (c) to everything else. Perhaps I should ask Dai unless you have another thought. By the way how do you get these diagrams? do you have the paper as html?
    Response:

    [DB] Pete, the versions in the article above are taken directly from HQ versions hosted by UCAR (Dr. Dai works at UCAR).  My assumption is that they were re-worked to be more reflective of the depth of the data available than the pixilated versions in the final paper.  HTH.

  49. Philippe Chantreau at 15:20 PM on 15 October 2011
    Continued Lower Atmosphere Warming
    Dr Pielke, we are not going in circles, you are. I am joining Paul Tremblay on his questions. If the result of a discussion is going to be "it's not that important and we should move on" why do you raise the question in the first place? I believe that some of these were given some attention on your blog, so at the time you must have thought they did have some importance, what has changed? Paul made a summary of various different points that have been given that treatment, I am as eager to know about why they are now unimportant as he is. Perusing through your posts on the threads on which you have participated, I found both that "policy makers have been misled to think that warming should be monotonous year after year" and extreme attention on your part on time periods during which no trend can be established with significance by any statistical means. This latter emphasis on short time "trends" is exactly why policy makers would come to expect that change be monotonous if they read your blog or other "skeptic" outlets. I admit it is rather surprising and confusing. If you're concerned about policy makers' perception of the trend, should you not only focus on trends that are statistically significant?
  50. The Dai After Tomorrow
    Pete, that's a good question. Perusing the paper I find this:
    "We emphasize that quantitative interpretation of the PDSI values shown in Figure 11 requires caution because many of the PDSI values, which are calibrated to the 1950–1979 model climate, are well out of the range for the current climate, based on which the PDSI was designed."
    For reference, here's Figure 11: A description of their methodology:
    "Here monthly PDSI pm and sc PDSI pm were computed using multi-model ensemble-mean monthly data of precipitation, surface air temperature, specific humidity, net radiation, wind speed, and air pressure from 22 coupled climate models participated in the IPCC AR4,128 and used to assess changes in aridity over global land. Thus, these PDSI values may be interpreted as for the multi-model mean climate conditions. As the PDSI is a slow varying variable, the lack of high-frequency variability in the ensemble mean climate is unlikely to induce mean biases. Figure 11 shows the select decadal-mean sc PDSI pm maps from the 1950s to 2090s from the IPCC 20th century (20C3M) and SRES A1B scenario simulations. Results for PDSI pm are similar with slightly larger magnitudes."
    The other graphics you link to, March 2000-March 2009 and August+September of 2011, are of much more limited snapshots in time & reflect actual measurements of PDSI. Hope that's more clear than mud!

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