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All IPCC definitions taken from Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I, Glossary, pp. 941-954. Cambridge University Press.

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Comments 24751 to 24800:

  1. Global Warming Basics: What Has Changed?

    billev,

    You are quite right that the long-term record has intermittent temp rises over multidecadal time scales, with a mid-century period relatively flat.

    First thing to note is that the overall trend is upwards.

    Second thing to note is that all sorts of factors affect surface temperatures and their evolution, and over different time scales.

    Third thing to note is that CO2 warming effect was less in the early part of the 20th century than the latter. Often this is used to argue that CO2 increase can't be the cause, or the primary cause. 

    Early 20th century warming has been attributed to combination of strong solar and weak CO2 (volcanism plays a part, too). Let's plot solar and temps together. I had to match phase in solar cycle - peak to peak in this case, which forces me to start in 1907 and finish in 1946. Plotting a trend with solar beginning and ending in different phases would give spurious results.

    Solar / Surface temps 1907 - 1946

    There is some contribution from solar (but solar effect is meant to be quite minimal). There is also a warming from volcanism. 3 factors (at least) contributed to warming in this period (sorry, volcano data is not available at the website I'm using)

    How about solar vs recent warming?

    Again, I had to make sure phases were matched in the solar cycle, so the post-1974 warming trend has to begin in 1982 and finish in December 2014. I also want to use at least 30-year periods to avoid short-term natural phases (like el Ninos) skewing the results. Note that I have excluded the warm years and months of 2015/16. Though I was forced to in order to match solar cycle phasing, I'm actually glad because I prefer conservative results.

    Solar / Surface temps 1982 - 2014

    This time, solar is a negative contributon. (Volcanism has been fairly steady for this period)

    Now let's compare rates of warming for the first period you indicate, and then the recent period from 1975.

    1911 - 1945 rate of warming is 0.138C/decade (+/- 0.045 uncertainty)

    1975 - 2015 rate of warming is 0.175C/decade (+/-0.033 uncertainty)

    Both trends are statistically signficant (trends since 2002 are not). The more recent mean trend is higher than the earlier one, BUT... the uncertainties overlap, so we can't honestly say that these trends are statistically distinguishable. We can't say that the recent warming rate is faster, slower or the same as 1911-1945. However, this is only one of many statistical tests we could run.

    By the same token, we can't claim that the similarity relative periods 'disprove' CO2 contribution. We need attribution studies for that - the graphs above are just a beginning.

    One thing that we can definitely not claim is that the future evolution of temp trends will match the previous. We are kind of designed to see patterns whether or not they are actual. If one wants to claim that there is some kind of cycle in climate evolution, one has to deterine a physical mechanism. Attempts have been made to do just that with mixed results.

    Whatever natural multidecadal cycles may be present in the long-term evolution of climate, they are not sufficient to explain the long-term (centennial) trend. There are longer temperature cycles (ie the ice ages) but these are at a much slower pace than current.

    This is not so much as to finalise an answer, but to get you thinking. If this stuff is well-known to you, hopefully you'll forgive an unnecessary post.

    Moderator Response:

    [RH] Reduced image size to 500px wide to prevent breaking page format.

  2. After 116 days, MIT fossil fuel divestment sit-in ends in student-administration deal for climate action

    Well its longest week for the activities of Fosil free MIT the Vice President and towards all along the research team involvement. Well we have a great opportunity for the entire blogger website because we have a easy website builder for you that is a systematically done by expert developers.

  3. Heat from the Earth’s interior does not control climate

    bozza @52 &53, of course the figures are approximate, in the sense that they have error margins. The figure for geothermal flux is plus or minus 4.3%, for example.  Given that, it is quite possible although very improbable that it would change by plus or minus 4% from year to year - an amount so small as to be inconsequential to climate change.  Errors on radiative forcing of greenhouse gases are typically in the plus or minus 10% range.

    With regard to human produced energy, total human energy production by fossil fuel burning and nuclear power stations was 143 x 10^12 Watts as of 2005.  Obviously it has increased since then.  Your 10 TW value is therefore approximately 7% of the actual value.  However, I am not sure I have properly understood what you were saying.

     

  4. Global Warming Basics: What Has Changed?

    billev @6, you can only "only have an observation" if you make no projection.  You, however, make projections out to 2099 unconditionally, and to 2350 conditionally.  Ergo, you have a theory about the observations, which in fact happens to be false.  It does not fit the observations even over the period 1880-2015 unless your terminology is so loose as to make your claims void of meaning, as shown above.

  5. Heat from the Earth’s interior does not control climate

    I was of course referring to this figure, "..Earth’s 47 TW interior heat..", quoted in comment 50!

  6. Heat from the Earth’s interior does not control climate

    ..I was of the long held opinion that humanity used about 10 TW of man-made energy: could it be possible that these figures actually be anywhere near approximate from a rational pov?

  7. 2016 SkS Weekly Digest #12

    Today's toon is hardly pro climate science education (or I don't see it that way): it rather reaffirms the n#1 denier's myth on the top left: Climate's changed before.

  8. Global Warming Basics: What Has Changed?

    I don't have a theory.  I only have an observation.  That observation, based on observing the NOAA furnished temperature history chart, is that the warming experienced since 1880 has not been continuous.  I am not talking trends I am talking temperature history.  I also believe that the significant imbalance between the scale of the presentation of the years on  the horizontal axis versus the temperature anomalies on the vertical axis diminish the ability to read the charts accurately.  One thing I  have noticed in various comments on the charts is a desperate attempt to mask the probable beginning of another pause in continuous warming that began (in my opinion) in 2002 or 2003.  I think that those observing the temperature charts over the next 10 to 15 years will probably see that a pause in warming has occurred.    

  9. Heat from the Earth’s interior does not control climate

    pjcarson2015 @50, you claim the rate of release of geothermal energy varies significantly due to earthquakes and volcanism, but provide no numbers.  Numbers, however, are easy to find.  For example, the largest geologically recent eruption is that of Lake Toba in Indonesia, 74 thousand years ago.  Here is a comparison of ejected lava for Lake Toba compared to other geologically recent volcanoes:

    The Lake Toba erruption was so large that its global impacts may nearly have caused the extinction of the human race.  It errupted with a force of 3.3 x 10^18 Joules, equivalent to 9.15 on the Richter scale.  Despite that, globally and annually averaged, it represents a forcing of just 0.0002 W/m^2.  That is only a 0.2% increase in background geothermal flux, or 0.005% of the forcing from a doubling of CO2.

    Of course, for a change in geothermal flux to significantly effect climate, a 0.2% change for just one year isn't going to do it.  Rather, you would need significantly more than that increase year in and year out over the long term.  So your theory is, not that one Lake Toba erruption equivalent has occurred, but that multiple such eruptions are occuring year in and year out, and we are simply not noticing.  

    Alternatively you might consider the flux to come from increased earthquake activity, and that we are experiencing significantly greater than twenty times the normal rate of magnitude 9+ earthquakes year in, year out without noticing.

    Of course, magnitude 9 earthquakes are fairly noticable, so you may prefer a increase in a lower magnitude quake.  But it takes 52,400 magnitude 6 earthquakes to release the same amount of energy as a Lake Toba erruption (magnitude 9.15 equivalent).  So for a 0.2% increase in the background rate, you have to imagine that the rate of magnitude 6 earthquakes has increased, year in, year out, by 52,400 per annum over their normal background rate.  Unfortunately, the background rate of magnitude 6 earthquakes measured over the twentieth century is 100 to 150 per year.  Ergo your theory requires the rate to have risen to that level from a prior rate of -52,275 magnitude 6 earthquakes a year.

    Quite frankly, all these alternative proposals are ridiculous.

    And what is even more riduculous given that for the change in geothermal flux to be significant relative to the change in heatflow due to the enhanced greenhouse effect, you need a change in the background flux, not of 0.02% but of 10,000%.  Again, we would have noticed.  Indeed, the measurements which determined the current background rate would have picked it up.  The greatest increase in background rate of geothermal flux you can concievably argue for is the current rate of flux of 0.09 W/m^2.  And that is insignificant compared to the change due to the change in greenhouse gases, and relies on the unphysical assumption that there was no geothermal flux prior to about 1850.

    In short, that you provide no numbers in support of your contention is no accident.  That is because if you look at the numbers, you see immediately that your theory cannot be true.

  10. Heat from the Earth’s interior does not control climate

    Planet Earth does its own (analog) calculations which it always gets right. It doesn’t have error bars. (Man is playing catch up in the calculation stakes.) Earth’s input and output energy always balance to zero when the Earth’s temperature is at equilibrium. As I wrote previously, this is the circumstance when Earth’s 47 TW interior heat comes into significance.

    As you say, the rate of Earth’s heat production is a very slowly changing property – too slow to be of any significance in these discussions – but its rate of release does vary significantly, principally with earthquakes and volcanism, both of which known to change.

    Moderator Response:

    [PS] Please note the Comments Policy statement on "No sloganeering". If you wish to make assertions about "Planet Earth does its own calculations",  or that geothermal rate can change in a way that could be significant to climate, then you must back your assertions with data and/or papers. You beliefs fly in the face of known data and laws of physics. Please provide the basis for such beliefs.

  11. Tracking the 2°C Limit - February 2016

    Rob Honeycutt @16, thanks for the headsup.

    Mann's tweet says:

    "Feb GISTEMP +1.35C 1951-80 baseline is ~2C relative to true pre-industrial baseline"

    Citing the GISTEMP global anomally as he does, that should indicate that he is talking about global temperatures, but it turns out he is not.

    Specifically, when you follow up to the referenced article in the Huffington Post, he makes use of information cited in two other articles, one peer reviewed, and one from Scientific American, both of which deal exclusively with Northern Hemisphere temperatures.  Indeed, he is quite clear about that in the Huffington Post article.

    In the end, the data he shows is used in this graph from the Scientific American article:

    This is derived from a combination of temperature data, including BEST NH land back to 1750, forcing data and an energy balance model.  Exactly how these are combined to produce the preindustrial temperature is unclear to me.  He does provide Matlab code, but as I do not have Matlab, I am unable to read the code.  He writes (Huffington Post):

    "There are a number of things to note from Fig. 3. First of all, using the more appropriate 1750-1850 pre-industrial baseline, we see that the Northern Hemisphere average temperature (gray squiggly curve) has already warmed nearly 1.2C. Temperatures have exceeded 1C above pre-industrial levels for most of the past decade. So 2015 obviously won’t be the first time this has happened, despite press reports to the contrary."

    The 1.2 C figure for the NH is significantly less than the 2001-2011 mean for BEST NH land relative to a 1750-1779 baseline, which is 1.67 C.  That is no surprise as a land only anomaly will be higher than an ocean/land anomaly.  The difference shows, however, that Mann has not simply taken the BEST land only value, although he may have taken the straight 1750 value, which was high relative to the 1750-1779 mean.  I suspect, however, he has used a much better method than that and would not dispute his figure.

    What I do dispute is taking the NH as an analogue for the globe.  There are good reasons for doing so in the cited articles, specifically the much better historical and paleo records for the NH.  But the 2 C target is for global temperatures.  Because the NH is approximatley 2/3rds land, it is expected to have a higher anomally than the whole globe at 2 C, and thus 2 C NH is not equivalent to 2 C globally.  Suggesting that the February 2016 temperature gives us an idea of what 2 C is like is misleading.  We still have significant warming to go before we crack 2 C globally, and thus actually reach the 2 C limit.  

  12. Heat from the Earth’s interior does not control climate

    pjcarson2015 @48, had you read the original paper from which that diagram it taken, you would notice that the error margins in the absolute values of the "two large quantities" was so large as to not narrow down the difference at all (and would have indicated a much larger difference taken at face value).  Consequently the authors used reanalysis products to narrow down difference in the values.  More recently, the principle of conservation of energy has been used in conjunction with the much better known increase in surface heat content (mostly in the form of Ocean Heat Content) to constrain the difference between the values.

    More importantly, the 47 TerraWatts is a product of radioactive decay and tidal stresses.  The tidal energy is also the product of tidal stresses.  Absent a major change in the relative orbits of the Earth, Moon and Sun (which has not occurred at any time over the last 4.5 billion years), and/or radical change over time of the fundamental physical constants, these cannot increase over the long term.  Indeed, both will gradually decrease over the long term as the amount of radioactive material decreases, and as the Moon gradually moves further from the Earth (reducing tidal stress).  In the geologically short term, tidal stresses will change at a rate proportional to continental drift as different configurations of continents induce more or less tidal friction.  At the moment the northward migragion of Africa, India, Australia and South America are (very gradually) reducing tidal stress, not increasing it, and the slowness of the process will not result in changes detectable on a centenial scale.  In like manner, there has been no new formation of large ignious provinces, or rapid acceleration of continental drift that would be necessary to increase heat flow from the interior (but not heat generation in the interior that necessarilly decreases).

    In short, theories that the rapid recent rise in temperatures is primarilly due to factors other than the increase in greenhouse gases suffer the same impediment as another famous 'theory':

  13. GWPF throws out centuries of physics, climate scientists laugh, conservative media fawns

    I have responded to richpender on the moderator suggested thread.  I'll note here that the very existence of that thread, not to mention papers like this one, and the host of papers on the water vapour feedback effect falsify richpender's claim that "All the attention is given to CO2".  It may well be true that he "...see[s] no discussion of [the effect of water vapour] on global warming", but that is not because it is not copiously discussed by the scientific community.

  14. Water vapor is the most powerful greenhouse gas

    richpender elsewhere suggests that there is 80 times by volume more H2O and CO2 in the atmosphere.  

    According to Trenberth and Smith (2005) the total dry mass of the atmosphere is 5.1352 +/-0.0003 x 10^18 kg, while the mean mass of H2O in the atmosphere is 1.27 x 10^16 kg.  According to the CDIAC FAQ on Climate Change, each ppmv of CO2 in the atmosphere has a mass of 2.13 Gigatonnes.  The most recent IPCC report (AR5) has corrected that to a value of 2.12 Gigatonnes, or 2.12 x 10^12 Kgs.  That means with 400 ppmv of CO2, there are approximately 848 x 10^12 Kgs CO2 in the atmosphere.  In other words, by mass, there is approximately 1.5 times as much H2O in the atmosphere as there is water.  CO2 is heavier than H2O, however.

    To run the comparison of the ratio by volume, however, we need to convert from Mass to molar units.  Apparently water vapour has a molar mass of 18.02 Kg per kilomole, while CO2 has a molar mass of 44.01 Kg per kilomole.  It follows that there are 705.8 x 10^15 moles of H2O in the atmosphere; but only 19.3 x 10^15 moles of CO2 at 400 ppmv.  The ratio of H2O to CO2 by volume is therefore 36.6, just under half of richpender's estimate.

    I am not sure why richpender got the estimate wrong.  Taking a median value on surface humidity, the ratio is approximately 53 moles of H2O per mole of CO2 - a value which does not include clouds (unlike Trenberth's figure).  Perhaps richpender has used an area weighted mean of humidity, which would give a larger ration at the surface.  Crucially to the strength of the greenhouse effect, what such comparisons nearly always get wrong is using only surface values.  Because the volume of H2O in the atmosphere is closely tied to temperature, the H2O concentration falls rapidly with altitude, as seen in this graph by Science of Doom:

    (Note that the graph only shows about 320 ppmv for CO2, not the current 400 ppmv).

    Because of the rapid decline of H2O concentration with altitude, in the upper troposphere where the greenhouse effect has its major impact, CO2 has a far greater impact than would be expected from surface calculations alone.  Indeed, CO2 contributes 20% of the total greenhouse effect, compared to 50% by water vapour and 25% by clouds.  The ratio of the instantanous impact of water vapour (plus clouds) to CO2 for the total greenhouse effect is not 80 to 1, not 36.6 to 1, but 3.75 to 1.

    That is the instantanious impact only.  Because the concentration of H2O in the atmosphere is highly temperature dependent, if the CO2 were eliminated from the atmosphere, the amount of H2O in the atmosphere would fall drastically due to the reduced temperature.  That in turn would lead to a further reduction in atmospheric H2O, and a further fall in temperature.  The end of the process would leave very little H2O in the atmosphere, and a total greenhouse effect a very small fraction of current values.

    Conversely, increasing CO2 increases the amount of H2O in the atmosphere, amplifying the impact of that increase in CO2.  This is called the water vapour feedback.

  15. Sanders, Clinton, Rubio, and Kasich answer climate debate questions

    Suggested supplemental reading:

    John Kasich is no better than Donald Trump on climate change by Rebecca Leber, Grist, Mar 15, 2016

  16. GWPF throws out centuries of physics, climate scientists laugh, conservative media fawns

    Water vapor is a global warming gas, yet I see no discussion of its effect on global warming.  All the attention is given to CO2, yet there is more then 80 times (by volume) H2O versus CO2.  You would think that H2O would play some role in atmospheric temperature rises.

    Moderator Response:

    [TD] See the post "Explaining How the Water Vapor Greenhouse Effect Works." First read the Basic tabbed pane, then the Intermediate one. In future, to find discussion of a topic, enter search terms in the Search field that is at the top left of every page. Or peruse the list of myths/arguments below that Search field.

  17. Heat from the Earth’s interior does not control climate

    Figure 6 diagram is repeated everywhere, in fact I think it’s the only one I’ve seen. It glosses over the fact that the final output results from the difference between 2 large numbers, both of which are known only approximately, being zero when Earth is neither heating nor cooling, and approximately balances otherwise. In these circumstances, compared to a mean of zero, the 47 TW released by Earth, and perhaps even the 3.75 TW of tidal energy, is no longer “puny”.

  18. CO2 measurements are suspect

    h4x354xOr @82, the 'eerily rigid' trajectory is effectively explained by this graph:

    The ratio between cumulative emissions and cumulative atmospheric increase in CO2 is explained by the equilibrium of partial pressure of CO2 in the oceans relative to the atmosphere, ie, Henry's Law (with a couple or nuances relating to the biosphere and the deep ocean).

    The variation in actual atmospheric concentration from that predicted by that curve from year to year is almost entirely explained by variation in GMST and to a lesser extent precipitation, ie, by the temperature dependance in Henry's Law and by increase or decrease of global vegetation driven by changes in precipitation.

    That is the bare bones explanation.  Scientists specializing in the CO2 cycle have modelled the various exchanges in detail and are able to reproduce the increase in CO2 given anthropogenic emissions and GMST changes with surprising accuracy.

  19. CO2 measurements are suspect

    Regarding the issue of accuracy or agreement of various sampling methods or ice cores: Dendrochronology (tree rings) provide another surprisingly rich, near continuous data source that includes decipherable clues about CO2 levels. Data from dendrochronology agrees, very strongly, with data from the ice cores. 

  20. CO2 measurements are suspect

    The Keeling Curve seems almost uniquely consistent to me, compared to almost every other type of measurement in the natural world, which tends to be highly variable, regardless of long-term trends. The Keeling Curve, by comparison, is almost eerily rigid in trajectory, especially compared to variability of total carbon releases over time. It's like it's got some kind of governor that simply keeps the increase and accelleration from going any faster, no matter how much more carbon we pump into the atmosphere. 

    Can anyone help me understand how the Keeling Curve is so "tight", while so many other measurements have so much higher variability? Is it just because the other sinks - ocean, land, and plants - have so much more capacity that they can absorb whatever else the atmosphere can't? Even if that's a reasonable simple explanation, I still feel like I'm missing something from the 'limiter' aspect of the phenomenon.

    I mean don't get me wrong, I'm figuratively poop-my-pants scared about climate change, particularly that "unprecidented rate" part. I've just recently been struck by the relatively tight natural regulation of the Keeling Curve, compared to a much greater variability I observe in almost every other aspect of nature. 

    Appreciate anything that might help a mostly layman level understanding of things dude wrap his head around that. Thanks! 

  21. Global Warming Basics: What Has Changed?

    Just for Billev's (@1 and @3) benefit, here are the NASA GISTEMP annual values detrended to make the trend from 1880-1945 zero, and with the 1974-2002 trend line of the adjusted data shown:

    First, you can see quite plainly that while 7 out of 13 years after 2002 do indeed fall below the 1974-2002 trendline, that is not because of any evident reduction in the trend.  There is no more basis for assuming a reduction in the trend then there would have been in the 13 years after 1984.  Indeed, with an odd number of years in the interval, of necessity the number of years below the trend cannot have equalled those above the trend.  If we included 2002 so that we had an even number, we would have equal number under and over the trend.  Further, with the monthly value for January and February of 2016, it is almost certain that the 2016 temperature will be at least near that of 2015, and hence over the trend, again leading to equal numbers over and below.

    Further, the 1974-2002 trend is exagerated by the near record breaking La Nina of 1974/5, and the near record breaking El Nino of 1997/98.  In contrast the period after 2002 has (until now) not experienced a strong El Nino and has experienced near record breaking La Nina's in 2008 and 2012/13.  The slight deviation from the 1974-2002 trend in nearly fully accounted for by short term ENSO fluctuation.  It is fully accounted for when changes in forcing are included.  In contrast, Billev's nascent theory would predict the data, having been adjusted for the trend over a full cycle, should show a strongly negative trend after 2002.

    Second, it should be noted that the data, having been adjusted for the trend over a full cycle, does not show significant similarity between phases of the purported cycle.  Neither the slope nor temperature pattern from 1880-1910 matches that from 1945-1974.  Nor do slope or pattern match between 1910 to 1945 and 1974-2002.  Nor to the periods of the half cycles match , with respective half cycle lengths of 30, 35, 29, and 28 years.  If you look at longer temperature records you also find the purported cycle disappears prior to 1880, or at best halves its period.

    In all, Billev's ad hoc theory has nothing to support it.  It is based on an interpretation of only 1 and a half cycles, which is a very statistically tenuous projection; is falsified in its first actually predictive interval; does not have a clear cycle and has no physical basis.  Even the half periods are ad hoc, as can be seen by the fact that the 1974-2002 trend fits the data quite will for several years before 1974, which is (as previously mentioned) a near record La Nina year. 

  22. Digby Scorgie at 11:08 AM on 20 March 2016
    Global Warming Basics: What Has Changed?

    Trends don't have to be linear.  When I look at the graphs for shortish periods, the trend seems linear.  When I look at the graphs for really long periods, the trend looks to me to be following a curve with gradually increasing slope.

  23. Global Warming Basics: What Has Changed?

    In the second chart labled NASA a line is drawn from the 1970's to the present.  If the line were drawn from the temperature at 1880 to the present the line would show a warming trend through the period it covered.  It would also show that there was not constant warming throughout that same perod.  If you alter the line shown in the second NASA graph to pass through the temperature for 2002 (what I believe was the end of the warming period that started around 1974) you will observe that most of the temperatures after 2002 fall below the altered line.  

  24. Lots of global warming since 1998

    Bob@45,

    That's great. I hadn't seen them, though I have seen people chases mirages based on variations of the third and fourth graphs - I once was silly enough to start a PhD with some scientists (bad ones, obviously) who had not looked at their raw data in a scatterplot. In the end, they were basing a major project on something like the 4th graph, and the whole thing was spurious.

  25. Lots of global warming since 1998

    Whenever discussion of linear regression and related statistics comes up, I always like to refer to Anscombe's Quartet. Although the four datasets result in very similar statitical results (of the ones listed on the wiki page - follow the link), it is abundantly obvious from the graphs that the four data sets are not at all similar.

    I won't embed the graphs (spoiler), so look at the wiki page.

    https://en.wikipedia.org/wiki/Anscombe%27s_quartet

  26. Tracking the 2°C Limit - February 2016

    Ubrew12 I completely agree. Are you a structural engineer? I started engineering long before computers when everything was done with hand calculations using basic assumptions. I have trained several engineers and with the latter ones coming right out of college I’ve become very concerned that they so completely depend on the computer. I’ve had them bring me results that I could see in 2 seconds was not even close. It’s like the proverbial pulling eye teeth to get them to do a rough hand calculation.

    Unfortunately some of my models are complicated plate and solid models which can be difficult to do classical hand calculations but I try to at least do exactly as you have said, run different meshes to see if they converge on a number.

  27. Lots of global warming since 1998

    Kevin C,

    Nice tester!

    I've read the answers - I would have picked Green as having the most uncertainty, though it actually has the least.

    Couple of queries/clatifications:

    Blue: 0.2 +/- 0.0
    Green: 0.2 +/- 0.07
    Red: 0.2 +/- 0.15
    Cyan: 0.2 +/- 0.12

    ...We can see the trend in the red line very clearly, and yet it isn't significant.

    1. Red is (statistically) significant isn't it? (I'm red green colour blind, so I assume the order of the values matches the order of the charts).

    2. Anomalising the seasonal data would decrease the uncertainty, right?

    BTW, 2nd chart looks like satellite temp anomalies, 3rd looks like Antarctic, 4th looks like global sea ice mean (+trend), though they are artificial.

    ...testing the statistical significance of a trend may be helpful, but it can't settle an argument.

    Technically yes, though I think it can if the cofidence interval is mutually agreed upon as a robust degree of uncertainty. Ie, a centennial temp trend of 2.3C +/-0.04, 95% confidence interval, would settle that there is a warming trend for all but the most reclacitrant (eg Lubos Motl).

  28. Global Warming Basics: What Has Changed?

    Sigh...
    Climate isn't the stock market  and economics (both only constructs in the human mind), climate science is real billev.

  29. Lots of global warming since 1998

    Tom,

    Had Dana said something more nuanced regarding 1998 sat trends I almost certainly would not have commented. As it is the statement is unambiguous, whatever the intention.

    Why, in fact, in a popular discourse, are you discussing a purely academic question.

    SkS straddles the line between the academic and the popular. Maybe I set too much store in what the words in the blog title actually mean (no sarc intended).

    Stephen Schneider's famous quote is apropos:

    "Each of us has to decide what the right balance is between being effective and being honest. I hope that means being both."

    I put in my 2 cents with that idea in mind. The ongoing has been a bit more expensive!

    [I read up on Carter's article about 4 years ago (written in 2006, not 2005, I believe). There's plenty of dross just like it around the skeptiverse]

  30. Tracking the 2°C Limit - February 2016

    Re: Climate models

    => This Is Why The Record Warmth is Not Natural

    by Dan Satterfield

  31. Lots of global warming since 1998

    The fourth curve is actually chaotic - it's a cubic spline fit through a logistic equation.

    There's an error in my analysis though, because I only checked for short range autocorrelation. If I'd corrected for longer autocorrelations (specifically 12 months), then the autocorrelation correction would have corrected for the annual cycle, and given a somewhat lower trend uncertainty for the red curve in line with out expectations.

    I should have used a pseudo-periodic function where the period varies over time. The trend would still be plainly apparent to the human eye, but would still give a large uncertainty even with long range autocorrelation correction.

    I've got another example where the trend uncertainty tells us the wrong thing which doesn't depend on uncertainty - I'll try and work up some pictures later.

  32. Tracking the 2°C Limit - February 2016

    Hank@20 said "from a structural engineering perspective... [the models] better at least be close or bad things happen"  I typically make 3 models of anything I'm tasked with understanding: a full 20k-2000k finite-element or difference model using appropriate software, a 100 node model performed with a spreadsheet, and a 1-5 node model calculated 'back-of-envelope' by hand.  Always tie your calculations back to something you did by hand.  It confirms the most critical assumptions in your calculation and prevents embarrassment.  A 2000k-node model can be right in its particulars, and yet spectacularly wrong in its generals.

    "anything can be fit with a Fourier series"  John von Neumann: "with four parameters I can fit an elephant, and with five I can make him wiggle his trunk."  Earth does not exist outside Physics.  If your friend cannot tie his math modelling back to the Physical fundamentals, thats a 'red flag'.

  33. Global Warming Basics: What Has Changed?

    The trend may be up but global temperature has not risen steadily since 1880.  There were pauses in temperature rise from about 1880 until about 1910 and from about 1945 until about 1974 and now since about 2002.  If this pattern continues then there will only be a steady rise in warming from about 2030 until 2060 and then again from 2090 until 2099 in the current century.  The warming trend will continue, however, until about 2350 if the climatologists are correct in saying the Earth began to experience a 500 year warming period around 1850. 

  34. Lots of global warming since 1998

    Kevin, am I correct in assuming the fourth curve involves the superpostion of 3 or 4 sine curves of different amplitudes plus linear trend?  Also, is the noise model for the second curve white noise or red noise?

    I am surprised at the ordering of error margins (obviously), but not surprised that I guessed wrong given that I was trying to eyeball the 95th percentile range of variation from the trend.  Although 2 and 4 have the greater peak amplitude, over much of their range the amplitude of the residual is much less than in 3.

  35. Lots of global warming since 1998

    Tom: I adjusted for autocorrelation in every case, but I thought that was too much detail!

  36. Lots of global warming since 1998

    Kevin C @36, I would guess that all have the same trend by construction, although the second (green) looks to have had its trend reduced slightly by random variability.  Clearly the first is statistically significant, while the following three are not, which look to have approximately the same standard deviation by construction, with the linear trend being approximately 0.75% of the error margins.  Not sure if they would have the same error margin useing an autocorrelative model though.  If not, order as per rkrolph.

  37. Lots of global warming since 1998

    Well done for giving it a go! As you may have guessed, the examples were set up to expose a misconception, and so the answers are rather counterintuitive. Here are the actual trends and uncertainties:

    Blue:  0.2 +/- 0.0
    Green: 0.2 +/- 0.07
    Red:   0.2 +/- 0.15
    Cyan:  0.2 +/- 0.12

    So something interesting is going on here. All the trends are the same. You correctly identified the straight line as being most significant. But you identified the trend+seasonal cycle (red) as next most significant when it was least significant. And the trend+noise as least significant, when it was second.

    We can see the trend in the red line very clearly, and yet it isn't significant. It's very hard to spot the trend in the green line, and yet it is. What's going on?

    It's easy, on the basis of common discussions on the web, to imagine that linear regression is some magical tool which can spit out objective answers concerning the existance or non-existance of a trend. But it isn't.

    Linear regression is a model which we can use, and which may help our understanding. However if it is used blindly, then it can also lead to completely invalid conclusions. Most importantly are the answers it can give, which can be characterized roughly as:

    1. Yes, there appears to be a trend, assuming that the model is correct. Or...
    2. No trend could be detected, either because there is no trend, or because the data are inadaquate, or because the model is inaqequate.

    In the latter case we don't know whether there is no trend, or whether there is a problem in the model or the data. Even in the former case, we may detect a non-existant trend if our model is wrong. So the results are in no way objective, and are contingent on a number of other factors.

    In other words, testing the statistical significance of a trend may be helpful, but it can't settle an argument.

    So let's go back to the examples and try and understand them some more. Linear regression involves an implicit model: that the data consist of a constant, a linear trend, and noise. The green data fit that model exactly. And the noise is not too large, so the calculation correctly identifies the presence of a trend

    In the other two cases, the model isn't really representative of the data. In the case of the seasonal cycle, the deviations from linearity aren't noise-like. If we used a better model which included a seasonal cycle, the trend would have come out clearly. Linear regression tells us it can't detect the linear trend because the data aren't linear, even when the trend is totally clear to us.

    Of course the application to real data arises because we know the real data also contains contributions which are not remotely linear - in particular very strong El Ninos at either end of the period (and indeed significant La Ninas just in from them). Since this non-linearity is not accounted for in the linear model, it inflates the uncertainty such that the underlying trend is not detected. (That's not a stupid - if we didn't happen to have El Ninos at both ends of the study period, they would also distort the trend as well as inflating the uncertainty.)

  38. Tracking the 2°C Limit - February 2016

    Ubrew12:

    Thanks for the links. There were helpful and interesting.
    No my denier friend has never given any projections by skeptics. I’ve even pointed out that they have been predicting a downturn in temperature for 20 years and it hasn’t happened yet. Those emails are ignored. Although he has sent me some curve fitting that was used to show ‘natural change’ (never any definition of what ‘natural’ is) and then subtracted from the actual to show that climate sensitivity is very low. I’m sure you have seen those. A few natural cycle sine curves with the amplitude and frequency adjusted and anything can be fit with a Fourier series.

    My friend is very intelligent. I’ve even asked him how he picks between which science fields he accepts and which he rejects since he rejects very few but just get a convoluted answer about it has to be based on the evidence of all things! He accepts the temperature is rising and CO2 has some effect but not enough that even if we did something it would matter much or that it’s going to get that bad. I’m pretty sure the problem is his conservative views about the government getting involved in this with taxes. You know the story. I don’t think I will ever convince him in this lifetime but I actually enjoy learning something new and our debates require me to study the subject in order to give factual and rational responses. So that’s the benefit I get from our debates. I’m a long way from knowing a lot about the subject but I can follow the math and science part enough to know I need to be worried about my children and grandchildren.

    I will respectively disagree with you on comparing projections with models. I do know that models are incorrect as I use finite element almost every day in my work. However at least from a structural engineering perspective they better at least be close or bad things happen. On occasion I have the opportunity to verify my designs by observations from the field. It happened just a few weeks ago when a structure had to be loaded for testing and we took deflection readings while it was loaded. The deflections were within 10% of what my model predicted so I was ecstatic. It verified my model was created correctly and was also a step towards validating the entire method of the software finite element program I was using. I think projections reasonable close to matching the models is a powerful argument that the science is correct and we need to do something about global warming.

  39. Rob Honeycutt at 06:30 AM on 19 March 2016
    Tracking the 2°C Limit - February 2016

    Here's an interesting comparison I just found...

  40. Rob Honeycutt at 06:23 AM on 19 March 2016
    Tracking the 2°C Limit - February 2016

    There was a lot of heat coming out of the ocean in the mid latitudes as well...

    Whereas I believe the 1998 El Nino was primarily limited to the equitorial Pacific.

  41. How Exxon Overstates the Uncertainty in Climate Science

    Maybe these chart makers need to standardize their assumptions and only make charts based on current laws, or current pledges. Showing the difference between what has been pledged, and what has been implemented only.

  42. Lots of global warming since 1998

    Ok Kevin, I will give my visual assessment.  I would say that all datasets show a trend. I would guess that if you put these datasets into an excel spreadsheet and applied linear trend lines to each, the trendlines would all match closely to the slope of the top blue line.  In order of most to least statistical significance I would say blue, red, cyan, and green.

  43. Tracking the 2°C Limit - February 2016

    I keep reading reports about how climate scientists are responding to this February peak with words like ‘shocking,’ ‘stunning,’ and just ‘wow.’

    I agree, and I know they expected _some_ increases in an El Nino year. But now I want to know what the science didn’t anticipate that has made this monthly peak so high.

    Is it just the super strong El Nino on top of GW? Or aret there carbon, or albedo or other feedbacks kicking in? Are we losing our 'aerosol umbrella'? Perhaps calculations of climate sensitivity have been too low? Do we have any clue at all why the reading for February is so much higher than anticipated?

  44. Worst Mediterranean drought in 900 years has human fingerprints all over it

    Would it be correct to see this as part of the predicted shift of the Sahara and Arabian Deserts north, just as the tropical zones are shifting poleward?

  45. Lots of global warming since 1998

    I think there is possibly a more fundamental issue here than the semantics, which relates to the meaning of 'statistical significance'. Statistical significance is not an indicator of whether there is a trend or not, it is an indication of whether a trend can be detected by a particular approach under a given set of assumptions.

    So what is being identified as a 'lack of statistically significant trend' in some datasets does not mean that there is no trend. It means that under a particular set of assumptions using a particular method of diagnosing a trend, the diagnosed trend could not be confidently distinguished from zero. However, the assumptions affect the answer. These include features such as the nature of the noise, the noise model, the variable used, the presence of a residual annual cycle and other factors. And the assumptions in the method have no bearing on whether or not there is a trend in the data, only on whether we diagnose one.

    To illustrate the problem, would anyone care to speculate on which of the following datasets contain a trend? Is the trend significant in each case?

  46. Rob Honeycutt at 01:08 AM on 19 March 2016
    Tracking the 2°C Limit - February 2016

    Tom Curtis... Mann also tweeted several comments related to this anomaly being 2°C over preindustrial. 

    https://twitter.com/MichaelEMann/status/708814127267885057

  47. Tracking the 2°C Limit - February 2016

    Basically Feb has peaked at ~2C above pre-industrial, a level considerred so dangerous to geopoltical stability that even the politicians have made honest pledges that they don't want to go above it.

    What carbon budget??????

    Like we can seriously put more GHG into the atmosphere safely, what a load of nonsesne.

    2015 was also the highest yearly CO2 rise at ~3ppm.

    Wars are raging and Wars cost lots CO2 (manufacturing all those nice weapons) and cause mass environmental damage.

    And the highly elite driven system humankind is under isn't intending to change anything any time soon and when pressure falls on the basic necessities and the weather ravages homes and crops, more wars and migrants are inevitable.

    The pope has already called the plight of the Syrian refugees who are average kind people escaping tyranny and terror an invasion of a holy nature into Europe.

    Antartica is melting quickly, Greenland too, the Arctic sea ice is vanishing rapidly and the permafrost is melting, forest fires raging and peaks lands burning all relaeasing more GHG than expected in all the policy makers models.

    ???

    Isn't time to transform everything we do?

    Impossible???

    Or does anyone know a place of sanctuary for those who care to escape to?

     

     

  48. Lots of global warming since 1998

    barry @29:

    "Once again you are presenting a different argument to the one I made."

    No!  I am presenting my own argument in relationship to the claim that you made.  If you were not so busy trying to call strawman or agreement, you might have learnt something - possibly realized that what you already knew but weren't thinking about made your original claims misleading and obfusticatory.

    Very briefly, once more, had Dana said:

    "The line which has the least sum of the squared differences for the satellite data has a positive slope"

    and you objected:

    "It does not. Not to statistical significance."

    Your claim would be simply false, representing a category error.  You would have interpreted a claim about the data as a claim about reality.

    Conversely, had Dana said:

    "That the line which has the least sum of the squared differences for the satellite data has a positive slope shows temperatures in fact rose over the interval"

    and you had objected:

    "Not it does not, for the error margin on the slope of the line includes zero"

    you would have been correct.

    Dana, of course, said nothing so precise as either of those statements.  He wrote:

    "The satellites show warming since 1998[.]"

    The question is then, which of the more formal statements above most closely conveys Dana's meaning.  It think it is the first, and clearly the first.  That is (firstly), because it was made to a popular audience, and popular audiences do not trouble themselves with error margins.  Therefore, it is invalid to interpret the claim in a way that requires understanding of error margins to be understood unless dictated by necessity.  It is also because Dana would, if challenged as to whether or not the satellite record by itself shows the warming to be real (ie, statistically significant), be genuinely puzzled as to why you would ask that question to the exclusion of the majority of the data, and to the exclusion of physics.  Why, in fact, in a popular discourse, are you discussing a purely academic question.

    Perhaps you are confused on this point because the 'no warming since 1998' has gone through several incarnations.  It started in 2005 with Bob Carter pointing out that the annual temperature of no year to 2005 was higher than 2005 (totally ignoring trends).  Overtime, it started bringing in discussion of statistical significance, but over the last year the argument has reverted to Carter's fraudulent basis.  In particular, the deniers have countered the fact that 2014 and 2015 were record setting years in the surface record by pointing out that they were not in the satellite record.  And, that simplistic argument no longer works.  Indeed, given that Spencer and Christy know about the lag in satellite temperature response to ENSO as well as anybody else, they knew it was only a matter of time before that argument would stop working when they made it.  That is, they knew the argument to be deceptive as they spoke. 

  49. Tracking the 2°C Limit - February 2016

    It turns out that Michael Mann's claim was made in an email, the rest of which has not been quoted.  As such, I can make no informed comment on what he meant.  Supposing TonyW @13 is correct, however, then using GISTEMP, the February 2016 anomaly relative to 1951-1980 was 1.9 C, making it 2.18 C greater than the 1880-1909 average.

  50. Lots of global warming since 1998
    Let's not get rid of the term 'statistical signicance' because it will mean the deniers keep trying to undermine the science by simply saying uncertainty exists rather than providing their own predictions!Contrast draws the eye and the wolves in sheets clothing will remain easier to spot be keeping the term 'statistically significant' by my rationale... That's what you call a cunning strategy: "..shhhhhhhhh!"

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