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Comments 125101 to 125150:

125101. Marcel Bökstedt at 11:22 AM on 23 January 2010
        The chaos of confusing the concepts
        This is a great site, because it takes the discussion to a high level, but still not so technical that you can't follow it. This particular posting is also quite interesting. I'm wondering about the correct definition and nature of the term "climate". I imagine that "todays weather" is characterized by a large number of parameters, varying in a way which might very well be (weakly) chaotic in the technical sense that the weather of next month is deterministically determined by weather of today, but this dependence is very sensitive to small variations of the initial conditions. Climate on the other hand could be defined not as the weather at a particular point in time, but as a subset of the parameter space. The weather can vary wildly, but only inside the bounds prescribed by the "climate". Or maybe differently, in analogy to the example of the Lorentz attractor, climate is a subset of the parameter space where "weather" spends "most of its time". This would be a slightly different but possibly more flexible definition of "climate". It reminds me of the situation in celestial mechanics. There the laws of motions of the planets in the solar system are quite simple, certainly immensly simpler than the laws governing weather. But you can run into chaos. I believe that at least in some situations you can compute the orbits of the the planets at a time in the far future (climate), but because of chaos you cannot calculate where in the orbit the planet will be at this specific time (weather). In this situation, the orbits of the planets change, so that there is a certain "dynamics of orbits". But it is far easier to predict the development of the orbit of a certain planet at a certain time than to predict exactly where the planet will be at this time. One thing which is unclear to me is if the "climate" of meteorological models can vary on its own. Is there is some sort of "dynamics of climate" - long term non-forced natural variation - or is the climate supposed to be completely determined by the various type of "forcing"?
125102. stevecarsonr at 11:15 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        Marcus, it's not my blog, added to which I'm new here - so apologies if my comment is out of order - but I don't understand the attraction of the labeling of others. (And I've seen it a lot at other blogs). You might characterize their opinion, that's certainly helpful. But "skeptic"/"denialist" seems like a classification of character - or maybe assassination of character. Now you might say the 2 people you are talking about are a distinguished physics professor and a meterologist, so take the following as a general comment that doesn't apply to them as to the specifics, but maybe the general concept does.. Some people don't understand the radiative transfer equation (in fact, I've just realised that maybe I don't understand it properly, maybe someone can help with my totally off-topic question) because they don't have a physics background. So they don't understand how CO2 can impact temperature. Does this make them "a denialist"? Or someone who doesn't understand radiative physics? People are free to call them whatever they like, but one comment I would make it that the more personal attacks thrown the less likely people with questions are to sit down and try and understand a complex subject. And it is complex. And the scientific method is not natural and instinctive.
125103. Marcus at 10:45 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        HumanityRules-also my apologies. I wasn't actually suggesting that the denialists *invented* the urban heat island (even if that's how it comes across), but they have exploited it *mercilessly* to try & undermine the credibility of the surface temperature record-even long after study after study had shown that (a) the bias wasn't as strong as suggested (b) the bias often gave cooler results than for nearby rural areas (c) researchers always adjusted for the bias & (d) that the surface record was closely correlated to the record from satellites. I doubt that this latest paper will silence their misuse of UHI for ideological purposes-even when its based on the work of one of their own!
125104. Marcus at 10:35 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        stevecarsonr, my apologies-I misspoke before. I implied that the Urban Heat Island was a myth-that wasn't my intent. What I meant was that Urban Heat Islands being the primary cause of global warming (rather than CO2 emissions) was an Urban Legend. This paper seems to give added weight to the Urban Legend status of the view that poorly sited measuring stations, alone, are capable of producing a +0.16 degree change per decade in average global temperatures!
125105. Marcus at 10:32 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        CoalGeologist, people who raise doubts about the science, without seeking to prove that those doubts are valid, are not true skeptics-they're denialists-an important distinction. Lindzen, for example, is a skeptic-he doubted that global warming would be as extreme as predicted (due to the Iris Effect) & sought to prove it-so he's a skeptic. On the matter of bias in US temperature records, Watts has behaved as a true skeptic-up to a point-but if he now refuses to publish the results of this study, then he proves himself to be just another denialist. His role as a denialist is already proven, however, in the way he behaves on other matters related to Anthropogenic Global Warming.
125106. chris at 09:19 AM on 23 January 2010
        The chaos of confusing the concepts
        I hope you don’t mind me responding to your message stevecarsonr (I happen to be on line, it’s a Friday night, and I’ve drunk a good part of a bottle of wine!). I think it comes down to the meaning of “chaos” as I suggested in post #12 just above. I'm not sure that the phenomenon you describe (periodic ice-melt-induced cessation of the Atlantic conveyor, which I also used in my post above), is an example of chaotic behaviour. I would say that it is an example of stochastic behaviour. Weather has inherent chaotic elements since (i) its evolution is critically dependent on the starting conditions (that’s why weather models, but not climate models, are continuously “reset” to current atmospheric conditions), (ii) it progresses on, and is influenced by events on, a very small spatial scale, and (iii) there are an almost infinite set of influences that determine the temporal evolution of local atmospheric conditions. That’s not the case with the example of ice-melt-induced cessation of the Atlantic conveyor. There’s no question that this phenomenon (see e.g. http://en.wikipedia.org/wiki/File:Ice-core-isotope.png ) has a stochastic element. But it is a phenomenon that is bounded within a particular climate regime (glacial period of an ice age with a particular continental arrangement that gives a strong thermohaline heat transport to high Northern latitudes), and is predictable in principle. Presumably if one knew something about the relationship between Arctic ice buildup and its evolution towards instability, then one could make a reasonable prediction (if one was around during the last glacial period say!) of when the next ice-collapse-induced cessation event would occur. I think we also have to be careful not to assign the label “chaotic” to behaviour that we happen to lack the knowledge-base to understand predictively. Focussing on the thermohaline circulation (THC) and the effects of melt water, it does seem a possibility (see e.g. ftp://rock.geosociety.org/pub/GSAToday/gt9901.pdf, for an interesting read) that the THC could slow down or stop if sufficient freshwater from Arctic ice melt were to flood the Arctic ocean. But I don’t think this would be an example of chaotic behaviour even if we might not know, at the moment, what specific conditions (how hot does it have to be; how much ice melt and how fast, would be required…). At some point we might well understand this process well enough that it might cease even to be considered “stochastic”.
125107. CoalGeologist at 08:59 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        Markus (Post #1) is already aware that he would be ill-advised to hold his breath waiting for an acknowledgment from Anthony Watts that the U.S. surface temperature data set apparently does not show a systematic bias toward warming. In fact, in the overall scheme of things, I’d wager it’s more likely that Watts would attempt to stop publication of the paper than to make such an admission. This issue has much broader implications, however, that extend well beyond the reliability of this particular data set, and bears on the entire debate over anthropogenic climate change (ACC). Skeptics such as Watts, Joseph D’Aleo and others are well within their rights to question the validity of the data, particularly considering the poor condition and non-ideal location of many of the measurement stations. More than that, it’s their duty (duty…duty…duty!) to raise skeptical criticisms, just as it is the duty of climate scientists to address reasonable concerns. The advancement of science depends on it. The success of this approach demands, however, that skeptical hypotheses be: a) testable, and b) potentially refutable. If not, then they fall into the domain of ideology, not science, and can never be considered anything more than unsubstantiated conjecture. Skeptics feel they’ve done their job merely by raising questions and doubts, while forgetting the essential next step of hypothesis testing. Sadly, past experience shows that in the current "debate", most arguments against anthropogenic climate change are effectively irrefutable, no matter how much evidence is brought to bear. Worse, the premise that ACC is wrong provides the touchstone by which all evidence is measured. Evidence that appears to support ACC is inferred to be wrong; evidence that appears to refute ACC is inferred to be valid. At the same time, the new re-assessment of the data by Menne et al. gives all of us a greater level of confidence in its reliability. (Readers may also be interested to read this analysis of the NOAA & NASA data: http://www.yaleclimatemediaforum.org/2010/01/kusi-noaa-nasa/ In fairness, we have to acknowledge the important role that skeptics have played in this process. It’s a shame if Watts and others are unable to derive any satisfaction from their efforts, even if the rest of us can. Most likely they’ll just keep plugging away, trying to prove what they already ardently believe. The surface temperature data set does, indeed, pose a “challenge” to put it mildly. While the temptation is there to just chuck the entire lot, we can’t afford to do that, as the results are too important. The only other option is to try to make the best use of the available information, by removing as much of the error as possible without introducing bias. This may entail eliminating some stations, and making some adjustments to some data, where warranted. This is what the researchers at the National Climate Data Center have been trying to do in good faith. They deserve our appreciation, and that of Mr. Watts as well!
125108. stevecarsonr at 08:45 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        Philippe, thanks for the clarification - I should have made it clear my comment was directed at some of the comments, not at the post itself. Everyone knows that the UHI exists, the IPCC has it at 0.006'C per decade. Perhaps that's correct, but the Fujibe paper and the Ren paper do question that number. Anyway, I'm off topic, as this post is about the effect of microsite issues on measurement.
125109. stevecarsonr at 08:35 AM on 23 January 2010
        The chaos of confusing the concepts
        It's great to see the chaos subject raised especially from someone with a PhD in complexity studies. Hopefully you will indulge some questions from someone who knows less. First of all, I don't see what you have actually demonstrated. Why is it a demonstration that climate is not chaotic by showing a graph of the temperature parameter in climate over 120 years. And how do you know that that particular graph is not actually chaotic? For example, I could plot a graph of the motions (the 2 angles) of the double pendulum for a period and say "see it's not chaotic". What's the difference between these 2 cases? Second, while of course the climate is bounded in many ways that doesn't mean it's not chaotic. The fact that there will always be 4 seasons or the poles always colder than the equator really isn't relevant. Or the fact that mid-latitudes might be between 0'C and 30'C on any given day. I know you didn't put forward these points, but I see them a lot with a kind of "QED climate is not chaotic" and I'm scratching my head.. In your opinion is this correct? I.e., the fact that the above few points are true doesn't disprove the possibility of chaotic behavior? Third, an example. The well-known "Atlantic conveyor belt" of ocean heat is driven by the thermohaline currents. Sufficient melting ice from Greenland/Arctic would disrupt the thermohaline and the conveyor belt stops, northern Europe gets very cold and the Arctic re-freezes. But at what point does this occcur? Prof FW Taylor in his book "Elementary Climate Physics" (2005 OUP) shows the 2-box model of the oceans, apparently originally proposed by Henry Stommel. It's fairly simple but shows an unstable behaviour against peturbations in either direction. He comments that right now (2005) none of the GCMs show the reversal of the circulation, instead they vary between no real change and a 50% drop over the next 100 years. However, my point finally arrived at, if this model (extended to a more realistic one) is correct, then surely the thermohaline will provide chaotic behavior at some point. (Perhaps strictly speaking it might not be chaotic, perhaps just unknown and complex at this stage). Comments? Fourth, without actually knowing the formulae for many important aspects of climate, how can "the climate community" (or subsection thereof?) be so confident that climate is not chaotic? E.g. the aerosol effect, a negative feedback, but with error bars stretching between zero and the effect of CO2 at 380ppm (according to IPCC AR4). I could happily theorize about changes in ocean temperature increasing the production of sulphides forming more clouds and providing more negative feedback.. or higher winds from higher temperature differentials picking up more dust from every drought ridden deserts and therefore seeding more clouds.. or not. I have the full extent of the error bars and given that we don't really know the formulae they might exhibit strong negative feedback - or they might exhibit actually positive feedback under some circumstances. How to confirm "no chaos" when the equations are somewhere between "cloudy" and "unknown"? Sorry for writing such a lengthy set of questions, but a subject that really needs discussion and thanks for posting on the subject.
125110. chris at 08:30 AM on 23 January 2010
        The chaos of confusing the concepts
        re your comment #13 batsvensson; i.e. "When you say you can predict that the weather in the next 6 month will be 20 to 30 C degree, then you are NOT basing this on the system itself but on a pulse respond to a ramp signal you know exist. However, still there is very tiny and small possibility your prediction may turn out wrong, but it is so unlikely to happened that you are not regarding it, which you probably do perfectly right in. But never less, it less to weather being non-chaotic and more to weather being affected by a ramp signal that you are able to do such prediction. " Surely Ned is basing his prediction on "the system itself". It's got nothing to do with "weather being non-chaotic" (we know weather has significant chaotic elements), it's to do with the likely range of weather events being bounded by a rather well-defined climate regime, and a highly predictable seasonal variation essentially based on Newtonian physics. As you say, there is a tiny and small ("tiny" and "small"?!) possibility that Ned's prediction may turn out to be wrong. There are two main reasons why this might be the case: (i) The variability in the weather encompasses the possibility of rare extreme excursions out of the expected range within a particular climate regime; (ii) a contingent event (volcanic eruption; extraterrestrial impact) might intervene.
125111. Philippe Chantreau at 08:22 AM on 23 January 2010
        The chaos of confusing the concepts
        Very interesting stuff, thanks Jacob.
125112. Philippe Chantreau at 08:15 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        Stevecarsonr you're confusing UHI and microsite issues. Nobody believes that the UHI is a myth and there is an abundant litterature on the subject. GISTEMP corrects for UHI. Many papers about it were mentioned on this very blog. Watts' basic argument, insofar as it remains consistent (which is not always the case)was that siting issues affected readings so that thermometers read to high. Neither Watts nor anyone among his cheerleading crowd ever attempted to do a real data analysis to verify the hypothesis. One of his readers, however, tackled the problem as sson as enough stations were sampled (John V). He evidently found out that the hypothesis was not verified by data analysis and endured so much malice at Watts's site that he didn't post there any more. Further analysis was done by NOAA once enough stations were sampled so that no regional bias could possibly affect the results, and the results were exactly the same. The very premise for the existence of Watts' blog has been invalidated numerous times.
125113. blouis79 at 08:13 AM on 23 January 2010
        Models are unreliable
        We have no idea how reliable climate models are: IPCC AR4 8.6.4 How to Assess Our Relative Confidence in Feedbacks Simulated by Different Models? [quote]A number of diagnostic tests have been proposed since the TAR (see Section 8.6.3), but few of them have been applied to a majority of the models currently in use. Moreover, it is not yet clear which tests are critical for constraining future projections. Consequently, a set of model metrics that might be used to narrow the range of plausible climate change feedbacks and climate sensitivity has yet to be developed.[/quote] Any person on earth knows that clouds can warm and cool. IPCC knows that too. Cloud feedbacks are not well modelled. IPCC AR4 8.6.3.2 Clouds [quote]In many climate models, details in the representation of clouds can substantially affect the model estimates of cloud feedback and climate sensitivity (e.g., Senior and Mitchell, 1993; Le Treut et al., 1994; Yao and Del Genio, 2002; Zhang, 2004; Stainforth et al., 2005; Yokohata et al., 2005). Moreover, the spread of climate sensitivity estimates among current models arises primarily from inter-model differences in cloud feedbacks (Colman, 2003a; Soden and Held, 2006; Webb et al., 2006; Section 8.6.2, Figure 8.14). Therefore, cloud feedbacks remain the largest source of uncertainty in climate sensitivity estimates.[/quote]
125114. batsvensson at 07:51 AM on 23 January 2010
        The chaos of confusing the concepts
        Ned, One can roughly say there are two classes of chaotic system, deterministic and non-deterministic. The behavior of the latter is the same as a random system. However a deterministic chaotic system isn’t the same as a random system. All deterministic system can in principle be predicted. Therefore saying weather or climate is chaotic is not the very same thing as actually claming it can not be predicted to some degree of certainty, they claim is only that it may be hard to predict, how hard is another matter thou. Climate is affected by regular cyclic phenomena and random event, these can be seen as ramps and step pulses to the system. Any system, linear, chaotic or random will respond to such pulses and such response can in principle be measured or filtered out from a time series of measurements. In a linear system this filtering is trivial, but for a chaotic system the process is non-trivial, a detected pulse may very well be a false positive in such system, this is very hard to say with out knowing anything about the history of the system itself. A linear system response to a pulse is easy to predict, but for a chaotic system one can not in general do this, except within small time scales. Chosen time scale short enough even the behavior of a random system can be predicted, but the error will soon grow to large to get any meaning full prediction out from it. The difference in predicting a linear system vs. a nonlinear lies in the rate of error growth. Linear system has a much smaller growth rate, and therefore we can make the prediction over longer times series with high confidence, while this is not the case with non-linear system. That errors in prediction grows by time is an inherent property of any simulations. The task in making a good prediction is to try make a system in which the growth of error is as small as possible. When you say you can predict that the weather in the next 6 month will be 20 to 30 C degree, then you are NOT basing this on the system itself but on a pulse respond to a ramp signal you know exist. However, still there is very tiny and small possibility your prediction may turn out wrong, but it is so unlikely to happened that you are not regarding it, which you probably do perfectly right in. But never less, it less to weather being non-chaotic and more to weather being affected by a ramp signal that you are able to do such prediction.
125115. stevecarsonr at 07:41 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        I don't think the UHI can be regarded as a myth. I can't comment on the US and haven't yet read the Memme/Menne paper. Perhaps the UHI is neglible in the US as Peterson found. But a 2009 IJC paper: Detection of urban warming in recent temperature trends in Japan, by Fumiaki Fujibe, showed a 0.1'C/decade UHI effect for the larger cities. This was based on 1979-2006 from 561 stations recording hourly data and compared with local population density data. You can see more about this paper at http://scienceofdoom.com/2010/01/17/urban-heat-island-in-japan/ There is also the Ren paper from 2008 in Journal of Climate which also found a significant UHI in China.
125116. Doug Bostrom at 06:56 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        It's one thing to endlessly kvetch and complain, another to actually exert some effort. Watts and crew did some work, hats off to them, misguided though they were. I hope these results will encourage doubters to purchase historical weather records for those locations where they are complaining about interpolation. As NewYorkJ remarks, many doubters will play the "hoax" wildcard yet again in order to explain this latest disaster for their strange cause. However, each time the doubt community must draw that card from their hand the remaining slice of the behavioral bell curve containing them loses area.
125117. chris at 06:54 AM on 23 January 2010
        Skeptical Science now an iPhone app
        re #18 Not quite sure what your difficulty is HumanityRules: 1880-current global temperature rise is around 0.85-09 oC (NASA Giss or Hadcrut3v). atmospheric CO2 rise from 290 ppm (mid-late 19th century) to 386 ppm (current), should give 1.24 oC at equilibrium within the mid-range of climate sensitivity (3 oC of warming per doubling of [CO2]). So we've had 0.85-0.9 oC of expected temperature response of ~ 1.25 oC. It's obvious (I would have thought) that the temperature response to enhanced radiative forcing is the equilibrium response. There shouldn't be a lag in the onset of the response of course, but the earth will take quite a while for the slow elements of the response, especially the accumulation of heat into the oceans, to come to equlibrium with the enhanced forcing. So the only "sleight of hand" would be to pretend that the earth should somehow miraculously come instantaneously to the new forced surface temperature. Even the most blatant efforts[*] to pursue that canard didn't go as far as to insinuate an instant temperature response to enhanced forcing. Perhaps you're having a general difficulty with the fact that the earth's temperature response to forcing, while not that complex, isn't amenable to simplistic interpretations. As several of us have pointed out on another thread, you do need to consider all of the forcings and their contributions (including anthropogenic aerosols, which have significantly countered anthropogenic greenhouse gas-induced warming). The question of the temporal response to enhanced forcing is difficult (there are obviously multiple time constants in the earth's response - atmosphere responds quite quickly, the surface and especially the oceans much more slowly), and that's the reason that determination of climate sensitivity is difficult based on analysis of (say) the 20th century response to enhanced greenhouse forcing... [*] e.g. (see Schwartz 2007) http://www.skepticalscience.com/climate-sensitivity.htm and his retraction and revision of the notion of a fast earth temperature response to external forcing
125118. NewYorkJ at 06:36 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        Typo in 3 places: "Memme 2010" should be "Menne 2010". So the Watts project shows there is, if anything, an overall cool bias in the raw data, which is a moot point considering the adjustments remove most of this bias. "Adjustments applied to USHCN Version 2 data largely account for the impact of instrument and siting changes, although a small overall residual negative (“cool”) bias appears to remain in the adjusted maximum temperature series." One criticism of the Menne result is that they are relying on the data the Watts army of volunteers puts together with regards to the rating classification. How reliable is that data? Do they have the expertise and objectivity needed to effectively assign a rating to each station? The Watts project has served it's purpose, which is to spread doubt about the data among the laypersons. Peer-reviewed academic studies will just be dismissed as being part of the hoax. How can they be believed, when "photos" prove otherwise?
        Response: Thanks for the alert, I've fixed the typo. Re the issue of relying on the surfacestations.org classifications, the NOAA also have their own independent ratings. The dotted lines in the figures above represent the good/bad trends according to their own classifications while the solid lines are according to the surfacestations.org classifications.
125119. Albatross at 06:04 AM on 23 January 2010
        The IPCC's 2035 prediction about Himalayan glaciers
        Jesús Rosino @4: Thanks for the link to Karger et al.. It is by far the best objective and quantitative discussion of the status and outlook of the Himalayan glacier that I have come across. I highly recommend it. After reading their "report", it is clear that there is still much reason for concern.
125120. chris at 04:25 AM on 23 January 2010
        The chaos of confusing the concepts
        Nice article.. It's worth restating that treatment of chaos requires a careful consideration of exactly what one means by the term in any particular instance. The notion that climate might be chaotic in the same sense that weather is, not really suportable. The example of ice age cycles just referred to is a good one. During the last several hundreds of thousands of years the earth underwent glacial-interglacial-glacial transitions which had profound effects on climate regimes - there was nothing chaotic about the broad properties of these transitions and the climate state transitions that these induced. The transitions were paced by earth orbital cycles, and in each glacial/interglacial the earth transitions were driven towards new equilibrium states having characteristic, (and rather reproducible through several cycles over hundreds of thousands of years) global temperatures, atmospheric CO2 concentrations, ice sheet coverage, sea levels etc. And in the general state, climates and their responses to variations in forcings are non-chaotic. Of course there may be stochastic elements to forces that vary these states. For example the "transient" temperature rises and falls in the N. hemiphere in glacial periods during Dansgaard-Oeschger and Heinrich events seem to be due to periodic ice discharge fom the Arctic ice sheets, and temporary slowing or stopping of the thermohaline circulation. These may be contingent/stochastic events (i.e. essentially non-predictable), but local climates likely responded in a well-defined manner according to the resulting changes in local ocean/air heat transport; atmospheric moisture contents etc. The idea that climate is something like the long term accumulation of weather is a silly concept that is presumably raised so as to give the impression that climate is hopelessly non-predictable given that one can't predict weather. As Ned has said, this isn't true. The relationship between weather and climate is, of course, more sensibly defined the other way round; i.e. weather is the day to day variation in seasonal atmospheric parameters (temperature, wind, precipitation) within a given climate regime...
125121. danielbacon at 04:24 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        http://ams.confex.com/ams/15AppClimate/techprogram/paper_91613.htm "The National Weather Service MMTS (Maximum-Minimum Temperature System) -- 20 years after Nolan J. Doesken, Colorado State Univ., Ft. Collins, CO During the mid 1980s, the National Weather Service began deploying electronic temperature measurement devices as a part of their Cooperative Network. The introduction of this new measurement system known as the MMTS (Maximum-Minimum Temperature System) represented the single largest change in how temperatures were measured and reported since the Cooperative Network was established in the 1800s. Early comparisons of MMTS readings with temperature measurements from the traditional liquid-in-glass thermometers mounted in Cotton Region shelters showed small but significant differences. During the first decade, several studies were conducted and published results showed that maximum temperatures from the MMTS were typically cooler and minimum temperatures warmer compared to traditional readings. This was a very important finding affecting climate data continuity and the monitoring of local, regional and national temperature trends. It has now been 20 years since the initial deployment of the MMTS. The Colorado Climate Center at Colorado State University has continued side by side daily measurements with both the MMTS and the traditional liquid-in-glass thermometers. This paper presents a 20-year comparison of temperatures measured 4 meters apart. Results show that little has changed in the relationship between MMTS and liquid-in-glass. Despite a yellowing of the MMTS radiation shield over time, the MMTS continues to read cooler during the daylight hours at all times of year. Minimum temperatures show little difference but with a small seasonal cycle in temperature differences. The largest differences continue, as they were first observed in 1985, to occur with low sun angles, clear skies, light winds and fresh snowcover. In addition to quantitative comparisons, some general comments on the impact of MMTS and other electronic temperature measurements on long-term temperature measurements and observed trends will also be offered." So it is consistent with the findings in 2005
125122. Jacob Bock Axelsen at 03:44 AM on 23 January 2010
        The chaos of confusing the concepts
        @Berényi Péter I just browsed through your reference, and I have some rather informal comments. The paper bases its statements solely on power spectral analysis of timeseries data. This gives you resonance frequencies (non-chaos) and characteristic timescales (indicative of chaos). No strange attractors, no direct correlations or actual physical processes. For instance, the paper claims that turbulence is present on millenium scale in less than an order of magnitude in a bounded frequency region. Even for power spectra I would say this is weak evidence. Turbulence in heat transfer over millenia cannot exist within the solar system, which the paper also states. The requirements for turbulent Navier-Stokes dynamics in advection is simply destroyed by viscocity and dissipation. That is also why climate models work well based on average radiation assumptions on the structure of the atmospheric energy budget. The paper claims that the source could be the turbulent galactic electron density field modulating cosmic ray fluxes. However, research indicates that this mechanism is too weak to cause major climate change: http://www.agu.org/pubs/crossref/2009/2009GL037946.shtml http://www.skepticalscience.com/cosmic-rays-and-global-warming.htm The final claim is that CO2 power spectra give indications of chaos during the last 500 million years. Keeping the regularity of ice age cycles in mind, I would personally need more proof to accept more than quasi-linear responses. I hope this was useful.
125123. Ian Love at 03:28 AM on 23 January 2010
        The IPCC's 2035 prediction about Himalayan glaciers
        As earlier posters have implied, other science based sites (e.g. Deltoid, RealClimate) have also put up articles that add to the background and current status of Himalayan glaciers. Of interest is the 2009 article by Xu et al Black soot and the survival of Tibetan glaciers (open access)."We find evidence that black soot aerosols deposited on Tibetan glaciers have been a significant contributing factor to observed rapid glacier retreat."
125124. HumanityRules at 02:42 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        My guess is that it wasn't deniers that instigated the rating process of weather stations but good old climatologist way back. What was the initial justification for this? And Marcus again it wasn't deniers who invented the Urban Heat Island idea. I just put this into Google Scholar search with many limitations and got over 400,000 hits (900,000 without the limitations). As far as I'm aware denier websites don't show in scholar searches.
125125. JasonW at 02:38 AM on 23 January 2010
        The chaos of confusing the concepts
        Excellent post, concise and very readable. Thanks!
125126. Dennis at 02:30 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        Watts writes that "the GISS data isn’t much to be trusted," but he doesn't say why.
125127. Philip64 at 01:53 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        A clear and unambiguous analysis. However, I think it is optimistic to think the outcome of this survey will be presented by Watts or other skeptic bloggers in the way it has been here. If they mention it at all, it will be in a way that shows (if not proves!) somehow or other that the results they were hoping for have indeed been found. Several studies published in SCIENCE a few years ago pretty much demolished the notion of the urban heat island, but since when have such things ever troubled the denialist/skeptic/contrarian campaign? Admittedly, since the field research was organised by their own sympathisers in this occasion, it will be harder to conclude that corrupted scientists and the socialist/liberal/big government conspiracy has rigged the data. But never underestimate the inventiveness of the paranoid mind.
125128. Nick Palmer at 00:31 AM on 23 January 2010
        On the reliability of the U.S. Surface Temperature Record
        Oh dear, poor deniers. Another of their imaginary supportive planks falls away beneath them...
125129. Andreas at 00:20 AM on 23 January 2010
        IPCC is alarmist
        While I understand the two first pictures, I dont get the last one (figure 4) to make sense. The observed trend starts to diverge from the IPCC models mean at latest in the end of the 1970's - so what were those models based on, pre-1980 data?
125130. HumanityRules at 00:15 AM on 23 January 2010
        Skeptical Science now an iPhone app
        But the fall and rise after volcanos is concomitant with the fall and rise in radiative forcing even though the delta T spike is smaller. A lag would suggest at the very least a slower recovery in delta T. Another example is the period 1910-1940. A relatively modest increase in radiative forcing (compared with present times) yet no apparent lag. In fact the rise of ~0.5oC in delta T occurs alongside the smooth rise (no volcano's) in radiative forcing. 1910-1940 RF increase ~0.5, delta T 0.5oC 1980-2003 RF increase ~2, delta T 0.6-0.7oC The numbers don't seem to add up.
125131. Marcus at 23:34 PM on 22 January 2010
        On the reliability of the U.S. Surface Temperature Record
        Oh dear, Watts will not be a happy camper. I wonder how long until we see this as a headline on WUWT? I'm not holding my breath. Point is, after reading about a dozen different articles on the issue, I've known all along that the so-called Urban Heat Island effect was nothing more than an Urban Legend!
125132. Riccardo at 23:07 PM on 22 January 2010
        The IPCC's 2035 prediction about Himalayan glaciers
        Charlie A, it's a typo, the starting year is 1947 not 1847.
125133. Ned at 23:01 PM on 22 January 2010
        The chaos of confusing the concepts
        Berényi Péter writes: "This is not so. Weather/climate is chaotic on all time scales." Hmmmm. Are you suggesting we can't make long-term predictions of trends in temperature, precipitation, etc.? Because where I am now (New England, USA) it's currently -16 C. I am highly confident that six months from now, the outside temperature will be in the +20 to +30 C range here. I can make that prediction confidently because although the day-to-day weather is chaotic and unpredictable, there is a physical process ("the seasons") superimposed on that short-term variability. Likewise, with climate change, we know that increasing CO2, CH4, N2O, CFCs, etc. in the atmosphere will superimpose a warming trend on the global climate. We can't predict the details of the weather on a specific date in 2050 (any more than we can predict them for a given day in New England this summer), but we can predict that on average the climate will be warmer.
125134. Andreas at 21:01 PM on 22 January 2010
        The chaos of confusing the concepts
        I'm not sure if it applies, but I thought of one analogy reflecting the phenomenon that climate on its scale is more predictable than weather. Consider the position at time 0 of a specific N2 molecule in a closed room filled with air, vs the temperature at time 0 in the same room. After one hour, it would be much easier to predict the temperature in the room than it would be to predict the position of the molecule. I assume that from a physics point of view one could argue that the two phenomena described is essentially the same, but on different scales, which you may also say about weather and climate. However my academic background is far from both physics and meterology so I'm not sure that my analogy is a particularily good one.
125135. Berényi Péter at 20:48 PM on 22 January 2010
        The chaos of confusing the concepts
        This is not so. Weather/climate is chaotic on all time scales. Chaotic climate response to long-term solar forcing variability A. Bershadskii 2009 EPL 88 60004 (5pp) doi: 10.1209/0295-5075/88/60004 http://www.iop.org/EJ/abstract/0295-5075/88/6/60004 A slightly earlier (6 Jul 2009 19:10:25 GMT) version of the same paper can be found at arXiv.org http://arxiv.org/abs/0903.2795
125136. Charlie A at 19:22 PM on 22 January 2010
        The IPCC's 2035 prediction about Himalayan glaciers
        Perhaps someone can explain something else in Section 10.6.2: The Himalayan glaciers of the IPCC Fourth Assessment Report: How is the second line of table 10.9 calculated? http://www.ipcc.ch/publications_and_data/ar4/wg2/en/ch10s10-6-2.html Pindari Glacier; 2840 meters of retreat from 1845 to 1966; average retreat 135.2 meters/year. I calculate an average 23.5 meters per year, which more closely matches some other reports of 27 meters/year from 1847 to 1906, slowing to 20 meters per year from 1906 to 1958; with a further slowing to about 10 meters per year since 1966. My e-mails to IPCC go unanswered. Perhaps other readers of this blog can explain the 135.2 meter/year average retreat number for Pindari Glacier.
125137. yocta at 18:58 PM on 22 January 2010
        The chaos of confusing the concepts
        Amazing post!! I remember reading about this in the book "Chaos" by James Gleick years ago and playing around myself with the bundled software doing fractals and strange attractors. You can download the shareware version of it here and source code too. http://www.cs.sjsu.edu/~rucker/chaos.htm From memory...I also remember reading that Lorentz discovered it by accident (like all great science) when he was in a rush or there was a power cut and he had to start his weather model with less decimal points in it and was very surprised by the print out the next day.
125138. HumanityRules at 13:57 PM on 22 January 2010
        Skeptical Science now an iPhone app
        A slight of hand appears to occur in the Hansen paper. Total net forcing 1880-2003 = 1.85Wm-1 delta T 1880-2003 = 0.6oC but 1Wm-1 should give delta T of 0.6oC so where is the delta T from the remain 0.85wm-1 of net radiative forcing? Oh yeah it's "in the pipeline". Three words can dismiss the fact that close to half the delta T is so far unaccounted for. I guess there is a suggestion of a lag here but no attempt to justify it. In fact when you look at the cooling caused by volcano's and the subsequent recovery after aerosols are removed there appears to be no lag in delta T to radiative forcing.
        Response: Actually, volcanic eruptions are a good example of climate lag and how "warming in the pipeline" works. Note the comparison between radiative forcing and global temperature over the 20th Century:
        
        
        
        The big downward spikes in net forcing are due to volcanic eruptions. Why doesn't temperature fall the same amount? Because of the great thermal inertia of the oceans. What happens is a volcano erupts, throwing up sulfate aerosols into the atmosphere. This immediately creates an energy imbalance - suddenly less sunlight is getting in. So the planet starts to cool.
        
        Note - the atmosphere responds relatively quickly. But it takes time for the oceans to cool - this is what you would call "cooling in the pipeline". However, and fortunately for us, the aerosols wash out of the atmosphere within a few years and the energy imbalance bounces back to what it was before. But if for some reason, the aerosols stayed in the atmosphere, what we would observe is the planet cooling over a few decades until the climate reached equilbrium.
        
125139. Tom Dayton at 12:12 PM on 22 January 2010
        The chaos of confusing the concepts
        Excellent post! Thanks!
125140. Jacob Bock Axelsen at 11:22 AM on 22 January 2010
        The chaos of confusing the concepts
        @Riccardo Thanks for your positive comment. The picture is just artwork - or an example, as you put it. The weather attractor would be huge on this scale, so I scaled it down to match the fluctuations instead. I hope you still like it.
125141. Bernard J. at 11:20 AM on 22 January 2010
        Could CFCs be causing global warming?
        I currently am not able to access my institution's library, so I can't go through the paywall to read Lu's paper. I'm curious though to know exactly what technique he employed that permitted him to establish that "correlation between global temperature and CFCs is evidence that CFCs have been the dominant driver of climate over the past century". When I look at the first graph, I see a 20th century warming trend that commences before the increase in EESC, and I see a period of (aerosol attributed) cooling kicking in at the time that EESC does begin to rise. This would seem to indicate that for a decade or so either side of the point where EESC begins to increase, there is no relationship with temperature at all. Any 'correlation' seems to occur after 1960, or even later, and given the vast number of human-produced substances that would demonstrate a similar trend, I would suggest that the correlation is a completely spurious one. At first blush, and given the poor relationship implied by the graph, it's certainly no evidence of a (partial, at best) correlation indicating causation. If this truly is Lu's claim, it should have been weeded out during review.
125142. chris1204 at 11:12 AM on 22 January 2010
        The IPCC's 2035 prediction about Himalayan glaciers
        I am a touch puzzled by the confident assertion that warming may equal increased precipiation which may equal in some cases increased glacier growth. I seem to recall that precipitation may cause at least local warming as water vapor when it turns to liquid water or ice releases latent thermal energy. I'm happy to be subject to correction on this score. Anyway, I will check out the suggested online sources with interest.
125143. Bern at 11:12 AM on 22 January 2010
        The chaos of confusing the concepts
        That's a good question, Riccardo. At first, I thought it was just an illustrative example, but a growth in the Lorenz attractor might represent larger chaotic variation in weather (i.e. more weather extremes). Obviously, whether this occurs or not is an important question when discussing the effects of long-term shifts in climate averages.
125144. Riccardo at 10:16 AM on 22 January 2010
        The chaos of confusing the concepts
        Excellent. Clear, concise and easy enough for averyone to understand. One question, the growth of the Lorenz attractor in the last picture is an observed feature or is just an example?
125145. Doug Bostrom at 10:01 AM on 22 January 2010
        The chaos of confusing the concepts
        Dr. Spencer Weart's "The Discovery of Global Warming" has a truly excellent chapter devoted to the foundations and evolution of climate modeling, particularly general circulation models: http://www.aip.org/history/climate/GCM.htm Note to doubters, skeptics, etc: Even if you're not prepared to join the mainstream, Weart's book covers this topic warts and all. If you're looking for weaknesses, you need to read it. Don't take on faith what you can pull from a primary source.
125146. Doug Bostrom at 09:49 AM on 22 January 2010
        The IPCC's 2035 prediction about Himalayan glaciers
        WeatherRusty at 01:53 AM on 22 January, 2010 Alexandre, You may be interested in this online "textbook" which provides a very good synoptic overview of climate science. It covers most areas of interest in a factual, unbiased way. Also be sure to view Weart's book, also online: http://www.aip.org/history
125147. Jesús Rosino at 08:43 AM on 22 January 2010
        The IPCC's 2035 prediction about Himalayan glaciers
        Yesterday, the IPCC released an apology and reaffirmed that the conclusions reported in the Synthesis Report are robust:

        Climate change is expected to exacerbate current stresses on water resources from population growth and economic and land-use change, including urbanisation. On a regional scale, mountain snow pack, glaciers and small ice caps play a crucial role in freshwater availability. Widespread mass losses from glaciers and reductions in snow cover over recent decades are projected to accelerate throughout the 21st century, reducing water availability, hydropower potential, and changing seasonality of flows in regions supplied by meltwater from major mountain ranges (e.g. Hindu-Kush, Himalaya, Andes), where more than one-sixth of the world population currently lives. This conclusion is robust, appropriate, and entirely consistent with the underlying science and the broader IPCC assessment.

        *I find the apology a bit indulgent anyway, and I hope that they add a corrigendum to the text soon.
125148. Berényi Péter at 06:02 AM on 22 January 2010
        The IPCC's 2035 prediction about Himalayan glaciers
        IPCC still has it on its website with no footnote, comment or whatever. IPCC Fourth Assessment Report: Climate Change 2007 Climate Change 2007: Working Group II: Impacts, Adaption and Vulnerability 10.6.2 The Himalayan glaciers http://www.ipcc.ch/publications_and_data/ar4/wg2/en/ch10s10-6-2.html
125149. chris at 05:09 AM on 22 January 2010
        Skeptical Science now an iPhone app
        Are they so different, HR? The Hansen et al analysis (see pdf in my post #15; it's the same data that John uses in his response in post #8) gives a solar contribution that is around 8% of the greenhouse forcing. Damon's 1999 analysis yields 15% (contribution of solar cycle length to total warming) through the 20th century (up to 1997). These values are not that different, and a number of analyses using up to date estimation of the change of solar irradiance, puts the solar contribution around 10%...these all seem to be reasonably self-consistent. One has to be careful with Damon's analysis. He wasn't particularly determining the solar contribution to warming. He was really addressing an analysis of Friis-Christensen and Lassen which purported to show that apparent correlations between solar cycle length and climate indicated that the solar contribution was 100%. Damon was pointing out that the F-C/L analysis wasn't done correctly and if it were, the solar cycle contribution would be 15% through 1997. However there isn't much evidence I think that the solar cycle length is a very good proxy for solar output, and there isn't a good theoretical basis for this relationship; far better to use a well-characterized analysis of solar irradiance, either by direct measurement, or by analysis of the solar cycle/sunspot measure for periods before direct monitoring of irradiance.
125150. Jesús Rosino at 04:33 AM on 22 January 2010
        The IPCC's 2035 prediction about Himalayan glaciers
        #11 danielbacon, I'm not 100% sure, but it seems to have been Prof Graham Cogley (Trent University, Ontario), who has also sent a letter (with Kargel, Kaser and Van derVeen) to Science. The first public comment seems to be the one by Madhav L. Khandekar (introduced as "research scientist from Environment Canada and is an expert reviewer for the IPCC 2007 Climate Change Documents") in a guest post on Roger Pielke Sr.'s blog on December 1st. But he credits the relevant statement to Graham Cogley.

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