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Comments 113001 to 113050:

113001. thingadonta at 00:07 AM on 14 August 2010
        NASA-GISS: July 2010-- What global warming looks like
        I'm sorry but I simply dont beleive some of your Figure 1 in this case. I have been living in Indonesia for the last 12 months and there is no way temperatures have been above average in hte last 6 months, as indicated in figure 1. We are in the tropics and right now we are wearing warm jackets. The locals say it hasnt been this cold in 35 years. It is also a really wet year, due to La Nina. Another point you already know, floods and rain and drought come and go, dont get in the trap of blaming everything on some mysterious 'other' factor. You refer to a comment above-global warming makes more rain and worse droughts, but you cant have it both ways-in some or many cases these will cancel each other out. Current conditions in Russia are a good eample, the heat in Russia is balanced by the heavy rain and lower temperatures in SE Asia all through this year-they are almost certainly related, and some major benefits flow from it (water), it's not all doom and gloom.
113002. Rick1521 at 23:43 PM on 13 August 2010
        NASA-GISS: July 2010-- What global warming looks like
        The UHI effect can easily explain the change in record highs and lows. Last night the three Oklahoma City sites on the Oklahoma Mesonet recorded low temperatures of 82, 83, and 84 (Oklahoma City is in the center of the state). Only one other site in the state of Oklahoma recorded a value in this range (there are 122 sites statewide), the rest were lower. Yesterday, lows at these three sites were 81, 81, and 82. No other sites recorded low temperatures this high.
113003. Berényi Péter at 23:11 PM on 13 August 2010
        On Statistical Significance and Confidence
        #42 kdkd at 09:54 AM on 13 August, 2010 For reasonable sample sizes parametric statistics are usually good enough. Yes, but you have to get rid of the assumption of normality. Temperature anomaly distribution does get more regular with increasing sample size, but it never converges to a Gaussian. The example below is the GHCN stations from the contiguous United States (lower 48) from 1949 to 1979, those with at least 15 years of data for each month of the year (1718 locations). To compensate for the unequal spatial distribution of stations, I have taken average monthly anomaly for each 1×1° box and month (270816 data points in 728 non-empty grid boxes). Mean is essentially zero (0.00066°C), standard deviation is 1.88°C. I have put the probability density function of a normal distribution there with the same mean and standard deviation for comparison (red line). We can see temperature anomalies have a distribution with a narrow peak and fat tail (compared to a Gaussian). This property has to be taken into account. It means it's way harder to reject the null hypothesis ("no trend") for a restricted sample from the realizations of a variable with such a distribution than for a normally distributed one. Bayesian approach does not change this fact. We can speculate why weather behaves this way. There is apparently something that prevents the central limit theorem to kick in. In this respect it resembles to the financial markets, linguistic statistics or occurrences of errors in complex systems (like computer networks, power plants or jet planes) potentially leading to disaster. That is, weather is not the cumulative result of many independent influences, there must be self organizing processes at work in the background, perhaps. The upshot of this is that extreme weather events are much more frequent than one would think based on a naive random model, even under perfect equilibrium conditions. This variability makes true regime shifts hard to identify.
113004. Eric (skeptic) at 23:04 PM on 13 August 2010
        NASA-GISS: July 2010-- What global warming looks like
        Are there separate stats for record high minimums? According to the "10 fingerprints" page, nights are warming faster than days and we should see even more record high minimums than record high maximums. Second question, are there ways to adjust for UHI in the records (similar to what is done with the averages)?
113005. Englishborn at 23:00 PM on 13 August 2010
        NASA-GISS: July 2010-- What global warming looks like
        Thanks Toby and CBDunkerson, I was in zombie mode when reading the "article" and was not really putting it all together in my head.
113006. michael sweet at 22:13 PM on 13 August 2010
        NASA-GISS: July 2010-- What global warming looks like
        Another great post Doug, very helpful. On the subject of attribution. How long will it take for scientists to analyize the weather patterns seen this year (and the recent past) and give some numbers on attribution? For example, if there is a 1:1000 chance of the Russian weather and a 1:500 chance of the Pakistan weather and so on for all these events, can a link to global warming eventualy be established? A comparision could be made to the graphic you have on temperature records. We do not know which records were set because of warming, but certainly the dicotomy of hot to cold records is caused by warming.
113007. gp2 at 21:54 PM on 13 August 2010
        NASA-GISS: July 2010-- What global warming looks like
        There is another interesting point in the press release (and the submitted paper) i.e. the use of (only) station located in area below satellite's lights detection limits doesn't affect temperature increase: "The biggest change in the paper is inclusion of an additional analysis is which global temperature change is based only on stations located in "pitch dark" regions, i.e., regions with satellite-observed brightness below the satellite's detection limit (1 μW/m2/sr/μm). Our standard analysis uses stations with satellite-observed brightness below 32 μW/m2/sr/μm. This more strict brightness limitation has no significant effect on analyzed global temperature change, providing additional confirmation that any urban effect on the GISS analysis of global temperature change is small."
113008. CBDunkerson at 21:48 PM on 13 August 2010
        NASA-GISS: July 2010-- What global warming looks like
        Englishborn, the reality of the situation is explained in the comments below the article. Basically, it was a cloudy day and the satellite wasn't able to take any accurate readings. That happens all the time and just means they don't have satellite data for that day. Thus no, it doesn't mean that NOAA is evil and faking their data to 'make up' global warming. At that, NOAA's global temperature anomaly set is based on SURFACE readings... their satellites weren't originally intended for temperature measurement at all, but some of them are now used to estimate such by UAH and RSS.
113009. Eric (skeptic) at 21:23 PM on 13 August 2010
        On Statistical Significance and Confidence
        I'm not sure I agree with the argument that having additional degrees of freedom beyond the one degree in the linear model "has to be justified". How is the single degree of freedom justified? That it allows us to answer an arbitrarily chosen question (linear trend hypothesis for CO2-based warming) does not seem like a strong justification considering that natural temperature cycles can last for years, decades, centuries, or longer.
113010. bluegrue at 19:12 PM on 13 August 2010
        Abraham reply to Monckton
        I have looked into Monckton's "SPPI temperature index" and written a blog post on the findings: Evolution of the “SPPI global temperature index” It started out as a simple mean of HadCRUt3, NCDC, RSS, and UAH. However, NCDC and HadCRUt3 were soon dropped and right now the "index" seems to be down to just RSS. In addition, the "index" is shifted for each plot such that its minimum value within the given graph is 0°C. So the value of the "index" may change depending on the time period covered.
113011. Pete Ridley at 19:09 PM on 13 August 2010
        Has Global Warming Stopped?
        Here’s the latest comment from John O’Sullivan on the response to his articles: “Since writing those articles concerned researchers have come forward to offer more shocking information regarding systemic failures in the satellite temp. measuring network. The following are what I have so far been advised are the key areas of concern. Please feel free to add this information to your communications with other interested parties-it seems as if the entire edifice of credibility in the satellite temp recording is about to collapse: * The NPOESS (National Polar-orbiting Operational Environmental Satellite) will not have any sensors that measure the sun’s energy output on the 2nd and 4th satellites. * The GOES-R (Geostationary Operational Environmental Satellite-R Series) has had 14 sensors cancelled. No data for cloud base height, ozone layer, ocean color, ocean turbidity and cloud imagery, snow cover, etc. Effectively neutered. * Landsat 7 (currently in orbit) is broken leaving data gaps. Scientists do not get all the information they should. * No sensor for movement of greenhouse gases and pollutants. * No sensor to monitor temperature changes on Earth over time. * The sensor to measure how Earth’s temperature reacts to changes in Solar energy was cancelled by the Obama Administration at the end of June 2011”. John also advises that Dr. Roy Spencer says “"We always had trouble with NOAA-16 AMSU, and dropped it long ago. It had calibration drifts that made it unsuitable for climate monitoring. Obviously, whatever happened to NOAA-16 AVHRR (or the software) introduced HUGE errors.” [note: climate modelling and climate monitoring are two very different disciplines].” John will keep me updates so I’ll pass further information to. Best regards, Pete Ridley
113012. Pete Ridley at 19:08 PM on 13 August 2010
        Has Global Warming Stopped?
        Admin, sorry that I hadn’t realised from the blog’s comment policy that even mention of the blog I linked to was “itself a violation”. I hope that you consider Climate Realists (Note 1) to be “a better source to cite for the satellite instrumentation issue” and I submit another modified version (the fourth) of the comment that you found unacceptable. Alden, on 3rd August NewYorkJ at 09:12 said “The statistical significance argument is also of limited value when you're dealing with a variety of indicators. .. Then there is satellite data, which is mostly independent. I believe these reach similar levels of confidence as HadCrut over this time period .. ”. I tried to post the following comment today on your “On Statistical Significance and Confidence” article but it was removed for some reason. Perhaps it was considered to be off-topic, which can’t be the case on this thread. You say in the “On Statistical Significance … ” article “So let’s think about the temperature data from 1995 to 2009 and what the statistical test associated with the linear regression really does .. ” but there is a much more fundamental test to be undertaken on those data. By far the greatest contribution to “Statistical Significance and Confidence” is the integrity of the raw data itself. There is much scepticism about this, only days ago highlighted by the revelations about another set of data purporting to be representative of global temperatures during a similar period. I refer here to the satellite data used by NOAA in support of its claims about global temperature change during the past decade. On 12th August the “Climate Realists” blog posted an article “Official: Satellite Failure Means Decade of Global Warming Data Doubtful by John O'Sullivan”. It provided links to two articles by John O’Sullivan. The first “US Government in Massive New Global Warming Scandal – NOAA Disgraced” reported on 9th August of significant errors in data collected by the NOAA-16 satellite. The second links to John’s follow-up article “Official: Satellite Failure Means Decade of Global Warming Data Doubtful” of 1th August in which he starts with “US Government admits satellite temperature readings “degraded.” All data taken offline in shock move. Global warming temperatures may be 10 to 15 degrees too high” and concludes “With NOAA’s failure to make further concise public statements on this sensational story it is left to public speculation and ‘citizen scientists’ to ascertain whether ten years or more of temperature data sets from satellites such as NOAA-16 are unreliable and worthless”. Everything in between is worth reading, as are the numerous postings about it flying around the blogosphere – enjoy. NOTES: 1) see http://climaterealists.com/index.php?id=6127&utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+ClimaterealistsNewsBlog+%28ClimateRealists+News+Blog%29 Best regards, Pete Ridley
113013. tobyjoyce at 18:16 PM on 13 August 2010
        NASA-GISS: July 2010-- What global warming looks like
        I had a look at the site referred to by Englishborn #1. It is the usual denialist tactic of seizing on an honest mistake as evidence of "fraud". WUWT had a similar post about temperature adjustments at Katmandu Airport (used by GISS). The tactic comes from a misunderstanding of science, the belief that it is a "chain of evidence" and if one link is broken, the whole case falls. But scientific evidence, and climate science is a good example, is multiple interwoven strands (more like a rope or cable). You need to break many strands before the theory starts to look ragged. Great post. Money quote from the paper: "What we can say is that global warming has an effect on the probability and intensity of extreme events."
113014. Englishborn at 18:02 PM on 13 August 2010
        NASA-GISS: July 2010-- What global warming looks like
        Sorry to go off topic slightly, but I have noticed some blogs reporting (by that I mean copy and pasting each other) about errors found in the NOAA satalite data, and how they have taken them from public view. Reading the blogs I quickly got lost in the propaganda attacks and lost what really the NOAA is being accused of and what errors are really being admitted. one such blog (god I hope that link worked) There seems to be a lack of this being reported in any other media outlet, can any kind soul enlighten me on the issue? Is it a major error on the NOAA behalf, does it call into question their global temp data? or is it being blown out of proportion for the skepitical blogoshere? Thanks Also great post Doug, keep it up
        Moderator Response: We've added a new thread for discussion of this topic: Of satellites and temperatures
113015. Pete Ridley at 17:41 PM on 13 August 2010
        Models are unreliable
        KR, on 30th July at 02:41 (#228) you said that “Regarding temperature data .. there are three independent data sets .. ”. NASA appears to think otherwise according to its 3rd August draft of paper "Global surface temperature change". It says “Analyses of global surface temperature change are routinely carried out by several groups, including the NASA Goddard Institute for Space Studies, the NOAA National Climatic Data Center (NCDC), and a joint effort of the UK Met Office Hadley Centre and the University of East Anglia Climatic Research Unit (HadCRUT). These analyses are not independent, as they must use much the same input observations.” (See http://data.giss.nasa.gov/gistemp/paper/gistemp2010_draft0803.pdf). Any comment? Best regards, Pete Ridley
113016. gallopingcamel at 14:51 PM on 13 August 2010
        Why I care about climate change
        Posts #131 through #138, Thanks for remaining so reasonable and so eloquent. I am impressed. It reminds me of Lawrence Durrell and the Alexandrian Quartet. We are looking at the same Justine while drawing entirely different conclusions. I guess we will continue locking horns until Mother Nature reveals herself. I suspect we will not have to wait much longer. muoncounter (#137), Texas and California are indeed dominant when it comes to selecting which science text books will make huge sales. Your apology is appropriate and welcome John Hubisz details the "howlers" in the physics text books but the errors are seldom corrected when new editions are published. When a student finds something in a science text book that makes no sense he asks his teacher for an explanation. As long as the teacher knows the subject he will be able to set things straight. Unfortunately, most of the time in my state the teacher cannot say whether the text book is right or wrong and as a result many students are permanently "turned off". I hope we can agree that widespread scientific illiteracy is dangerous when our survival depends on sophisticated technology.
113017. kdkd at 14:44 PM on 13 August 2010
        On Statistical Significance and Confidence
        Jeff Freymueller #47 Classical (null hypothesis based) significance tests for the regression slopes are very low power, so it will take a long time for any increase in trend to be statistically significant. It's really a limitation of the correlation based methodology.
113018. Jeff Freymueller at 14:12 PM on 13 August 2010
        On Statistical Significance and Confidence
        #45 barry, I think you are close. What you can say from this is that the *best estimate* of the rate of warming has increased with each decade over the last 30 years. What you don't get from this analysis is whether the increase in the rate is significant, or whether it could plausibly be explained by random chance. To determine that you need to work out the uncertainties in your trend estimates, and then apply an appropriate test for significance of the change.
113019. Jeff Freymueller at 14:07 PM on 13 August 2010
        On Statistical Significance and Confidence
        #44 HumanityRules, the choice of null hypothesis depends on what you are trying to test -- you seem to be saying that the choice is completely subjective, which then "influences the outcome of what are posited as objective facts". That's jumping to conclusions, to put it mildly. The null hypothesis you test against always depends on what you are trying to test. The result of a statistical test is to accept or reject that hypothesis. In the case of the paper you reference, "best performance" is not explicitly defined, but it appears that what they are saying is that if you look at the historical record, taking the average temperature over a <30 year period does a better job of predicting the next 20 years than extrapolating the trend. (Is this also what you interpret it to be?). What they do next is to compare the Hansen model predictions to determine if the model predicted the future better than the null hypothesis. For this question, it is especially important to choose the best possible predictor as the null hypothesis, because you want to see if the model can out-do that to a significant degree. If you chose a poor predictor as the null hypothesis, you could get a false positive, in which you conclude the model has significant predictive power ("skill") when it really does not. What I think you are doing here is you are interpreting the authors' careful discussion of what is the most skillful null hypothesis as evidence that everything is subjective, which is pretty much the opposite of what you should have concluded here. Far from choosing a subjective null hypothesis to falsely "prove" something, the authors are actually showing that they have been careful to avoid a false positive result.
113020. barry1487 at 13:56 PM on 13 August 2010
        On Statistical Significance and Confidence
        Thanks for the replies above. I'll endeavour to follow up the suggestions. One last question, then I'll refrain from interrupting with my naive experiments. Curious about the effects of decadal temps on the centennial trend, I plotted linear regressions from 1900 - 1979, and then to 1989, 1999 and 2009 at the woodfortrees site. With each additional ten years, the trend rate increases, and each time it increases by more than the last. Figures below are per century. 1900 to 1979 - 0.53 1900 to 1989 - 0.57 1900 to 1999 - 0.64 1900 to 2009 - 0.73 Would I be over-interpreting the results to suggest that the rate of warming has increased with each decade over the last 30 years? (I'm trying to think of simple and effective ways to respond to the memes about global temperatures for last 10 - 12 years)
113021. muoncounter at 13:54 PM on 13 August 2010
        We're heading into an ice age
        Here's an interesting figure, derived from a compilation of ice core CO2 data. From the file history: "connect it to the glacial cycles by marking 230 ppm as a transition level and colored "glacial periods" blue and interglacial periods yellow. There's a clear 80,000-110,000 period of repeating glacier even if they vary in quality." I'm not aware of any credible evidence for 15k year glacial cycles or any factual support for suggestions that we're heading into an ice age. What I have seen are mis-statements of fact: "Some say we are "nearing the end of our minor interglacial period", and may in fact be on the brink of another Ice Age." Incredibly this statement is linked to a source, which says very little of the kind: "We currently are nearing the end of a small, minor interglacial period ". Of course, this figure doesn't include our own increase in CO2 to 390 ppm, but it does make it obvious that glacial stages don't happen in high CO2 environments -- in our current plate tectonic/ocean circulation setting. You're not in the Ordovician any longer.
113022. HumanityRules at 11:56 AM on 13 August 2010
        On Statistical Significance and Confidence
        Alden, I wonder if you could discuss the choice of null hypothesis? I ask because yesterday I read this paper. For them they are comparing the observed trend in the last two decades with the Hansen 1988 modelled trend. They investigate two possible null hypothesis, either the temperature is a continuation of the trend from the previous two decades or is a continuation of the average for the previous two decades (read the paper it's explained better there!). They suggest the average of the previous two decades is a better null hypothesis, I understand how they come to that conclusion. It struck me that while one null hypothesis might be better than another, both might still be bad. Put simplistically the hypotheses could be good and bad, or they could be bad and very bad. In a reference to the real world the question might be does one years temperature have any strong relationship to the previous or next years temperature? On a crude level it might be true because we roughly have the same sun and earth but in terms of understanding the fine variability of the system is there any relation? If something like CO2 dominates the movement in temperature, which is meant to be a linear trend then maybe the null hypotheses choosen are good. But if the climate is dominated by cycles or is simply chaotic then these null hypothesis that depend on the temperature of the previous 20 years may not be very good choices. There appears to be a subjective aspect to the choice of a null hypothesis which then influences the outcome of what are posited as objective facts.
113023. muoncounter at 10:57 AM on 13 August 2010
        More evidence than you can shake a hockey stick at
        #23: "quantify how much heat energy resides in each of the individual components that comprise the atmosphere, that would bring the role that the heat energy resident in water vapour has in measured temperatures into perspective." Why is this distinction necessary? Whether the heat is in the water vapor or the air, the measured temperature is higher. For some fun and instructive graphics in this regard, try the NOAA climate indicators. For some not-so-much-fun, yet still instructive results, try searching google news for "record heat and record high humidity".
113024. kayve at 10:15 AM on 13 August 2010
        We're heading into an ice age
        I need to do more reading on Broecker on this, and I tend to be at odds with some of the literature. However, some of it has given me some hunches. The PETM was a period 55 million years ago with no glaciation. The popular media presented this as a possible future state due to greenhouse forcing. I believe this must be a complete error. Moran et al. presents Arctic Ocean sediment core data that argues for a transition period between glaciations during the same time (between 45 and 35 million years ago (Ma)) when the southern ocean Antarctic Circumpolar Current (ACC) was being formed. Their graphic describes before and after the ACC formation as "Greenhouse" and "Icehouse" climate states respectively. One estimate of that formation using neodymium isotope ratios by Scher et al. estimates the opening of the Drake Passage based on ocean mixing to be around 41Ma. Data such as Zachos et al. shows how northern glaciations occured at a time after a robust southern ice cap has been built up and maintained. I hold a MS in Physiology, and have only done some independent study in geology and audited a course in Earth's Climate History and completed one in Physical Oceanography. Long before this, being acquainted with climate swings, I drew an analogy between a mechanism in my field, the excitable membrane action potential conduction mechanism seen most robustly in nerve and muscle tissues to the climate system. In the action potential mechanism, there is a rectification reaction that occurs because sodium and potassium ions are set in opposing gradients accross the plasma membrane, and have selective channel proteins that conduct the two ions with differing time courses so that the fast response sodium causes a change in voltage in one direction called depolarization while the slower response potassium channels cause a voltage change in the opposite direction by virtue of the fact of their opposite gradient. I draw my analogy to the climate system in this manner: Temperature is an analogue for voltage, a greenhouse stimulus that occurs in the atomosphere is an analogue for the sodium response, and an oceanic/cryospheric rectification mechanism is analogous to the potassium response. I of course cannot deny orbital forcing mechanisms that occur on 40Ka, 100Ka, and I believe 20Ka range changes, as has been mentioned here, but I believe another very important part of the equation is the ability of the earth to respond to heating changes, which shows the contrast in response pre-ACC formation, the greenhouse earth, and post-ACC icehouse earth. The time course of cryospheric/oceanic response is on the order of multi-century to millenial, putting it an order of magnitude smaller than the orbital forcings. There is evidence in the fossil record of events that may corroborate this idea. Terms to look for are "Iceberg Armada," "Heinrich Events," "Younger (and Older) Dryas," as well as the "8200 year before present event." I have a while to go to fully quantify this idea, but since the ocean stores about 1000 times as much heat as the atmosphere, it is not absurd to envision the domination of the atmosphere by oceanic responses. It is conceivable that a threshold for the response will be crossed where greatly increased motility of global major glacial masses could lead to a reversal of a warming trend that would include a reversal of the ability of the ocean to absorb CO2. By far the lion's share of ocean is very cold, fed by yearly calving of glaciers at both poles leading to what is known as North Atlantic Deep Water (NADW) and Antarctic Bottom Water (AABW). These masses can represent a very adequate repository for resequestered CO2. I'm still in the "hunch" stage here, but I have posted some of my ideas at http://kayve.net/kayve
113025. kdkd at 09:56 AM on 13 August 2010
        On Statistical Significance and Confidence
        Sorryast bit should be "response to information loss"
113026. kdkd at 09:54 AM on 13 August 2010
        On Statistical Significance and Confidence
        BP #40 "Temperature anomaly distribution is usually very far from a Gaussian. Therefore one has to be extremely cautious when applying standard statistical methods" This is only partly true. For reasonable sample sizes parametric statistics are usually good enough. You can assess this with a rule of thumb. If the p value for a parametric test is less than that for the equivalent nonparametric test you can almost always conclude that the pRametrkc test is a reasonable approximation. This is because you are indirectly assesing the response to I formation loss caused by using a nonparametric method
113027. Doug Bostrom at 09:18 AM on 13 August 2010
        On Statistical Significance and Confidence
        BP I don't think it would fit in the topic of this thread but it would be fun to see what happens if you paint a color spectrum across the distribution and then superimpose those colors as blobs on the station locations. Maybe at the Are surface temperature records reliable? thread (I have no idea what this says about reliability, just seems like the right place to develop more visualization).
113028. Doug Bostrom at 08:48 AM on 13 August 2010
        More evidence than you can shake a hockey stick at
        JohnD I'm so accustomed to folks arguing against data here that I'm actually struggling to understand what you're saying, trying to interpret your remarks as not somehow being an argument -against- there being more latent heat residing in the atmosphere as a result of it including increased water vapor content. Put more simply, you're not trying to say that -more- water vapor in the air is -not- evidence of increased latent heat in the air, are you?
113029. Berényi Péter at 08:44 AM on 13 August 2010
        On Statistical Significance and Confidence
        Temperature anomaly distribution is usually very far from a Gaussian. Therefore one has to be extremely cautious when applying standard statistical methods. I show you an example: This is the distribution of monthly temperature anomalies in a 3×3° box containing South-East Nebraska and part of Kansas. There are 28 GHCN stations there which have a full record during the five years long period 1964-68. 42572455002 39.20 -96.58 MANHATTAN 42572458000 39.55 -97.65 CONCORDIA BLO 42572458001 39.13 -97.70 MINNEAPOLIS 42572551001 40.10 -96.15 PAWNEE CITY 42572551002 40.37 -96.22 TECUMSEH 42572551003 40.62 -96.95 CRETE 42572551004 40.67 -96.18 SYRACUSE 42572551005 40.90 -97.10 SEWARD 42572551006 40.90 -96.80 LINCOLN 42572551007 41.27 -97.12 DAVID CITY 42572552000 40.95 -98.32 GRAND ISLAND 42572552001 40.10 -98.97 FRANKLIN 42572552002 40.10 -98.52 RED CLOUD 42572552005 40.65 -98.38 HASTINGS 4N 42572552006 40.87 -97.60 YORK 42572552007 41.27 -98.47 SAINT PAUL 42572552008 41.28 -98.97 LOUP CITY 42572553002 41.77 -96.22 TEKAMAH 42572554003 40.87 -96.15 WEEPING WATER 42572556000 41.98 -97.43 NORFOLK KARL 42572556001 41.45 -97.77 GENOA 2W 42572556002 41.67 -97.98 ALBION 42572556003 41.83 -97.45 MADISON 42574440000 40.10 -97.33 FAIRBURY, NE. 42574440001 40.17 -97.58 HEBRON 42574440002 40.30 -96.75 BEATRICE 1N 42574440003 40.53 -97.60 GENEVA 42574440004 40.63 -97.58 FAIRMONT It looks like this on the map (click on it for larger version):
113030. johnd at 08:17 AM on 13 August 2010
        More evidence than you can shake a hockey stick at
        CoalGeologist at 06:50 AM, the heat energy absorbed by phase transition extracts heat energy from the surface waters and transfers it into water vapour which then transports it aloft through the atmosphere. Thus that heat energy is then contained in the water vapour component of the atmosphere (until it is given up as the vapour reforms back to water) and as such becomes part of the total heat energy measured as air temperature. Your comment about water vapour % being small, whilst it may be in regards to the atmosphere as a whole, it is THE major component of all those that the heat energy of the atmosphere resides in. Perhaps if you could go back to the basics and quantify how much heat energy resides in each of the individual components that comprise the atmosphere, that would bring the role that the heat energy resident in water vapour has in measured temperatures into perspective. Perhaps a dreaded analogy can help. As steam from a pot of water, being heated by whatever means, circulates within a room, the air temperature of the room rises quite quickly due to the circulation of the heat energy that is contained in the steam. Take away the pot of water, and any moisture content of the air within the room, what components of the air remaining would absorb the heat that continues to be released from the source and would that make any difference to the temperatures measured in the room?
113031. Doug Bostrom at 07:27 AM on 13 August 2010
        On Statistical Significance and Confidence
        Could I dare suggest that it looks cyclical - if not a bit sinusoidal?? It has pleasingly smooth curves superimposed on it because of the mathematical treatment and visualization, combined with varying slope. Suggesting it's sinusoidal is indeed daring, some might say even reckless.
113032. Doug Bostrom at 07:21 AM on 13 August 2010
        1934 - hottest year on record
        What your references have in common Broadlands is that they're all at least 34 years old. You've not addressed the questions I asked about what you think is wrong with each of the specific corrections Peter Hogarth pointed you to. Earlier you said, I believe you may have missed a point too... the NCDC-NOAA has systematically lowered the early Weather Bureau records." That sounds really terrible on its face but it's not new information, the NCDC is quite open about what adjustments they do and why. Then you said, "The winter months have been lowered more the summer months...every time. It would be absurd to think that some sort of conspiracy has taken place but some plausible explanation should be available for this consistent trend. Indeed, and Peter Hogarth pointed you to answers, but you're still working from the perspective of mystification with regard to why those corrections are done. If you have a problem with corrections and adjustments, be specific. Show how the meteorologists are wrong. Doubt is not an argument.
113033. Eric L at 06:53 AM on 13 August 2010
        Why I care about climate change
        GC (130), Science progresses by a series of testable hypotheses. More precisely it progresses by testing those hypotheses against eachother, keeping the best ones around, and weaving them into larger theories with broad explanatory power. Theories are never perfect, but science doesn't advance because we reject every hypothesis if it's prediction is ever off by a little bit, it progresses when new theories are found or little previously unconsidered things are added to old theories to make their predictions better. That ultimately is what I wish I could see more of from the climate denial community. I wish I saw more working to advance our understanding of climate rather than to exaggerate our ignorance. That's a big part of why I have trouble taking denial scientists seriously. That and whenever I look into the latest "proof" that global warming is all wrong, it never amounts to anything. That and I have enough of a physics background to understand how the greenhouse effect works, and besides being measurable in a lab it really is an unavoidable consequence of perfectly well understood physics. So for global warming to be wrong, something about our climate must conspire to prevent it from having much effect, but that something must not prevent other things affecting our climate from having an effect too, as clearly our climate can change. Here is a talk on causes of climate change throughout the Earth's history that you may find interesting: http://thingsbreak.wordpress.com/2009/12/19/richard-alley-the-biggest-control-knob-carbon-dioxide-in-earths-climate-history/ Our understanding of climate is quite far reaching. One finding of climate science is that if you change greenhouse gas levels and thus at the ground get additional trapped infrared radiation measured in W/m^2 averaged over the surface of the Earth, the effect on the Earth's average temperature is about the same as if the intensity of the sun changes, or the amount of blocked sunlight due to dust changes, or the amount of sunlight reflected directly back into space by glaciers changes by the same W/m^2 averaged over the Earth's surface. And if you put these all together and look over the century+ of thermometer data or the billions of years of Earth's history, just about every change is about as big as it should have been. Which is more likely, that we're basically right and in a few cases we don't have the complete picture of what drove change or how the Earth changed, or that we're completely wrong about how the climate works and no one (certainly not any climate deniers) has figured any of it out? On a side topic, Galileo was a good friend of the Medici family that ran Florence and they sponsored his work. Scientists have been working for government grants for as long as science has been done. He erred in thinking they could protect him from the Pope, though. Lysenkoism is a good example of what happens when science is corrupted by a government in the service of a specific ideology held by that government, but you imagine a worldwide conspiracy of governments of differing ideologies and economic interests all trying to corrupt science the same way. There is no historical precedent for this. What do you imagine to be the common interest? Were Arrhenius and Tyndall and Fourier in on this when they discovered the phenomenon back in the 1800s?
113034. CoalGeologist at 06:50 AM on 13 August 2010
        More evidence than you can shake a hockey stick at
        Actually, johnd @#20, the phase transition from liquid H2O to vapour, or solid to vapour, absorbs energy (as I believe you understand). Thus, when water evaporates, it cools it lowers the temperature. This quantity of heat (latent heat of vapourization) would need to be ADDED to the atmosphere, not subtracted, from the standpoint of energy balance. Without doing any calculations, considering that water vapor represents at most a few mole-% of the atmosphere, and we're only dealing with about the incremental amount of water vapour that would be added as a result of a very slight increase in temperature, the amount would be very small. The key point here is that water vapor pressure increases as a function of temperature (Clausius-Clapeyron relationship). So far as I'm aware, this is the effect we're seeing in the increasing moisture content of the atmosphere with warming. It's just another independent "thermometer" for skeptics who don't trust HadCRUT, GISS, etc.
113035. Broadlands at 06:27 AM on 13 August 2010
        1934 - hottest year on record
        "What's your point, Broadlands?" Well, one point is, as I mentioned earlier, these changes alter the record years (1921 no longer the warmest). Then, the systematic lowering of the early years tends to increase the slope of the overall trend. 
 "For that matter, why are you pointing us to a scan of a National Geographic article from 1976 as some kind of authoritative source for temperature data?" An NG article is, of course, not "peer-reviewed". But, if you will read the legend on that chart (just above 1920 to 1940) you should see that the chart is based on peer-reviewed publications... If you will look at the authoritative? National Academy of Sciences Fig A.6 (1975) you should see they are similar. If you will look at Budyko's Fig. 1 (1969) you should see that they are similar. This should provide substantiation for the overall trend up to 1976 shown in the NG article..
113036. kdkd at 06:22 AM on 13 August 2010
        On Statistical Significance and Confidence
        Ken's response at #32 is instructive - it shows that he does't understand the statistical concepts properly, as nicely explained by CBW at #36 :). Recall my comment at #29: "I've asked Ken elsewhere quite a few times what's so special about the last decade or so to make him reach his conclusion, but he can't or won't answer the question." It's very clear that he still won't or can't answer that question.
113037. tobyjoyce at 04:49 AM on 13 August 2010
        On Statistical Significance and Confidence
        I workd in Statistical Process Control for many years and it gave me a feel for evaluating time series, with rules of thumb if necessary or with more substantial analysis if the means was available. One rule of the Western Electric Rules for control charts is "if there are 8 points in succession on one side of the mean line through the process indicators", it indicates a shift in the process mean upwards. The logic behind the rule is this: a single point has a probability of being on one side of the mean of 0.5. The probability of two points in succession is 0.5 x 0.5 = 0.25. Three points is 0.5 x 0.5 x 0.5 = 0.125. At what point is the sequence less than 1%? The first number is 7 points, and the rule goes for 8. But if the blue line in Figure 1 is the mean, then there is a "run" of 7 points above the mean. Assuming a widget process in which "high" is "bad", that should have a good engineer or production manager looking more closely at the process to find out was it raw material, equipment or operators that were the source of the disimprovement. Not much help to climate scientists, maybe, but perhaps of use in explaining to the public what the indicators are saying.
113038. Doug Bostrom at 02:50 AM on 13 August 2010
        More evidence than you can shake a hockey stick at
        I'm not quite getting the point of your question/remark, JohnD. Maybe not enough coffee here yet.
113039. CBW at 02:23 AM on 13 August 2010
        On Statistical Significance and Confidence
        Ken @ 34: Statisticians are perfectly happy to fit non-linear functions to data, and to suggest otherwise is to admit a lack of knowledge about statistical practice. Fitting a more complicated function to data involves two important issues, however: First, a polynomial or other non-linear function adds additional degrees of freedom to the fit, and while those functions may improve the overall fit, tests are required to determine if the additional degrees of freedom are justified. There are various ways to do this, but the Akaike and Bayesian information criteria are illustrative. One could, for example, perfectly fit any timeseries using the Lagrange Interpolation Formula, but the additional degrees of freedom would never be justified under any useful criterion (not to mention the function is essentially useless for extrapolation). Second, the function one selects to fit the data makes an implicit statement about physical processes. Fitting a function is assuming a model. In an extremely complicated system like the global climate, no simple model will be likely to adequately summarize the multiple interacting processes. Using a straight line makes the fewest assumptions, and allows one to answer the questions: Is there a trend? and, What is the approximate magnitude of the trend? Finally, all of the forcings you mention, and many other factors, are included in the global climate models. The effects of varying the magnitude and functional relationships of the various forcings have been (and continue to be) systematically explored, and are informed by real-world data and experimental results in an ongoing process of improvement. The models are not, and never will be perfect, but I can assure you that no one is ignoring solar input or the T^4 factor in thermal radiation. But modeling the climate is a completely different animal than looking for a trend in the annualized surface temperature record.
113040. tobyjoyce at 02:20 AM on 13 August 2010
        On Statistical Significance and Confidence
        Barry @16, Check up a book on linear regression. There is a good book called "Data Analysis and Decision Making with Microsoft Excel" by Albright, Wilson & Zappe. The result of an F-test is in the Excel output (cell F12). This is a hyposthesis test with the null hypothesis that the linear co-efficient = 0. As you can see, a probablity = 0.48 suggests this is not an unusual outcome under such an assumption of a "null model" - basically no linear fit. So the null hypothesis is not rejected in this case. To evaluate small datasets, permutation tests are much more effective, such as John Brookes did in #4.
113041. Pete Ridley at 02:18 AM on 13 August 2010
        Has Global Warming Stopped?
        PS: I posted a similar comment on the “Grappling With Change: London and the River Thames” thread but it was removed by the administrator for some reason unknown to me. I don’t see where I have been in breach of the blog’s “Comment Policy”. It would be helpful if the administrator would mention what the problem is with any comment that he decides to remove. Best regards, Pete Ridley
        Moderator Response: The name and entire premise of the website you refer to is itself a violation of the comments policy here. Find a better source to cite for the satellite instrumentation issue, preferably one concerned primarily with science as opposed to conspiracy theories.
113042. muoncounter at 02:02 AM on 13 August 2010
        On Statistical Significance and Confidence
        Sorry, that should have been Look back at this graph from Confidence in climate forecasts.
113043. muoncounter at 01:57 AM on 13 August 2010
        On Statistical Significance and Confidence
        #32: "the sum of all these warming and cooling forcings is highly likely to be non-linear - so the polynomial curve fit seems to make good sense of a complex relationship between energy imbalance and measured global temperatures." A single polynomial is just as arbitrary as a single straight line. The question remains -- what is the meaning of any curve fit, other than as a physical descriptor of what has already taken place? Look back at this graph from On Statistical Significance. It is certainly reasonable to say 'the straight line is a 30 year trend of 0.15 dec/decade'. But this straight line is about as good a predictor as a stopped clock, which is correct twice a day. Superimposed on that trend are more rapid cooling and warming events, which are clearly biased towards warming.
113044. johnd at 01:29 AM on 13 August 2010
        More evidence than you can shake a hockey stick at
        doug_bostrom at 08:32 AM, regarding "Not only is global humidity rising with the warming trend as expected, even its year-to-year fluctuations match well with those of global temperature." The question I think it raises is "Is specific humidity tracking temperature, or is it instead temperature that is tracking specific humidity?" If the heat resident within the water vapour as a result of it's change of state on the earth's surface was to be removed from the equation, how much heat would be be left in the other components that comprise the atmosphere and how well would temperature track it?
113045. muoncounter at 00:55 AM on 13 August 2010
        Why I care about climate change
        GC, #128: "The quality of science text books is critical when so few teachers have an adequate background in the subject." Oh, textbooks are important even when teachers have the requisite background; if only as an anchor against the fluctuating 'truthiness' one finds on wikipedia etal. That said, I live in one of the states that sets the textbook standards for the rest of the US; you have my profound apologies. "I hope you will want to support John Hubisz in his efforts to improve science text books:" I certainly enjoyed his comments on lab notebooks. #130: "Scientific consensus is worthless, especially when it is authoritarian and lacking in accountability or transparency." I'm not at all sure what you mean. Would you prefer that we act on ideas that are not supported by a consensus? If so, the folks at conservapedia have a bridge they'd like to sell. But authoritarian? Have you ever tried forcing an unsupported point through a room full of scientists? Good luck with that. An unmistakable sign of authoritarianism is the presence of an unthinking mob, ever-ready to take up 'four legs good, two legs bad,' rather than listen to something they don't want to hear. That kind of behavior is hardly ever seen here; but you do find it quite frequently among the Watts Up Doc crowd. So which side is authoritarian?
113046. Ken Lambert at 00:07 AM on 13 August 2010
        On Statistical Significance and Confidence
        ABG #18 Your plots of random data points are very useful illustrations of what is and is not significant in curve fitting. The issue might be that we don't have 1000 sets of independent land and ocean temperature data to do the experiment. In fact the surface temperature data is obtained from basically only one raw data source (GCHN) with several software processors giving results and the RSS and UAH satellite data. Chris G #26 Useful points Chris. Indeed the temperature slopes in the past 60-100 years have been higher (through the 1920-1940 period perhaps?)and lower (1950-1980?). The issue remains that CO2GHG warming forcing is rising logarithmically with CO2 concentration; aerosols and cloud cooling has no representative Equation which I have seen (aerosol forcing strangely flatlines on the IPCC graphs); WV warming feedback is highly contentious with no agreed relationship I know of; radiative cooling is exponential with T^4; and the sun has many overlapping cycles, the shortest being the 11 year sinusoidal cycle which equates to about 25% of the claimed warming imbalance. My point is that the sum of all these warming and cooling forcings is highly likely to be non-linear - so the polynomial curve fit seems to make good sense of a complex relationship between energy imbalance and measured global temperatures. Now this might not suit the tidy linear world of the statistician - but it sure fits the highly non-linear real world. The polynomial fit from "Has Global Warming Stopped" looks like a flattening to me. Could I dare suggest that it looks cyclical - if not a bit sinusoidal?? As for the argument that models predict a noisy period where temperatures don't increase - well that defies the first law which dictates that the energy gained by the earth system from a warming imbalance must show up as a temperature increase somewhere in the system - and we have fought out long and hard elsewhere on this blog ("Robust warming of the Upper Oceans etc") - to show that it is not being measured in the oceans; and the overall energy budget is not anywhere near balanced for the claimed AGW imbalances. Obviously the place to look is at each warming and cooling forcing and see how 'robust' they really are.
113047. The Skeptical Chymist at 23:23 PM on 12 August 2010
        On Statistical Significance and Confidence
        Barry @16 Although I'm no expert with stats I'll try to help a little. Q1 & 2 - Yes, sounds like you have got the gist of it. As for ANOVA, multiple regression etc I would suggest trying to get your head around these tests, what they do and what you tell you before being let loose with them. Not necessarily mathematically but certainly conceptually. Can anyone recommend some introductory material accessible via the web?
113048. Dikran Marsupial at 21:43 PM on 12 August 2010
        Why I care about climate change
        Joining this thread a bit late, but here goes: I am also a practicing Christian ([Groucho] and believe me I need the practice! [/Groucho]), however religious people don't have a monopoly on wanting to "love thy neighbour" (and before anyone says "fnarr fnarr", this isn't "Carry on Climate Change", that's not what I meant! ;o). It is basically the golden rule, which is common to many ethical systems, both religious and secular. There is indeed no need to invoke motivators other than professional concern for humanities future, however that does not imply other well-meaning forms of motivation are a bad thing if they do actually motivate the correct action. My own motivation although I am a Christian is based on a golden rule style argument, and is not conciously of religious origin. Even if the effects of anthropogenic GHG emissions result in only a modest increase in temperatures, that may be enough to have serious consequences in places like Bangladesh, which are economically and agnriculturally already quite marginal. Unlike most of us in in places that are climatically stable (such as the UK) they are easily affected by climate change, and unlike most of us in the first world they do not necessarily have the resources to adapt. We in the first world have a responsibility for out past, present and future actions if they have a negative effect on others. We shouldn't need religious teachings to know that, it is merely justice. However that doesn't mean the religious teachings are not spot on in this case.
113049. michael sweet at 21:36 PM on 12 August 2010
        Three new studies illustrate significant risks and complications with geoengineering climate
        This is the link to the scientific american blog: http://www.scientificamerican.com/blog/post.cfm?id=what-happens-when-coal-is-gone-2010-06-29 Here they say coal will last 200 years.
113050. michael sweet at 21:31 PM on 12 August 2010
        Three new studies illustrate significant risks and complications with geoengineering climate
        Doug, Indeed, the authors conclusion is that the IPCC is being alarmist in their projections of CO2 release. "The real problem 40 years from 2009 will be an insufficient supply of fossil energy, not its overabundance, as the IPCC economists would have it." They do not discuss the need to access alternate energy supplies, which is required if fossil fuels run out. The primary author also told Bloomburg that the gulf oil gusher was probably only 20,000 barrels per day so no worries. That is now known to be 60,000 bpd. My impression is this is a new angle for skeptics: the coal is running out anyway so we might as well continue BAU. I have seen estimates all over the map on when peak coal will happen. scientific american blog on coal for example. The skeptics realize they are losing the "climate is not changing" argument with the temperatures this year and are looking for a new argument to support BAU.

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