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DSL at 12:28 PM on 28 July 2014Rupert Murdoch doesn't understand climate change basics, and that's a problem
Donny, you say this: "I am surprised to see a site with this kind of name be full of so many absolutely non scientific commentary and or mindsets."
And then you follow it with this:
"I am starting to doubt our understanding of how much c02 actually does effect temperature. I feel like the recent pause in warming doesn't sit right with my expectations"
This site is here just for you to work through your doubts and "feelings." So do it, and bring the evidence — on the appropriate threads, of course.
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Donny at 11:05 AM on 28 July 2014Rupert Murdoch doesn't understand climate change basics, and that's a problem
Mancan. ...
Don't you think there may be some variables in all those "certainties" that you are listing? Maybe Murdoch thinks that the climate systems are extremely complex and to say that everything is decided in the CC debate may be a little premature.
I have a degree in environmental biology so I am by no means an expert in climate change. ... However I follow the debate closely and have enough science background to understand that the lack of having proper controls while experimenting in nature is a real problem. Thinking that you have a set of truths like your 5 can take away your scientific objectivity. I am surprised to see a site with this kind of name be full of so many absolutely non scientific commentary and or mindsets.
I am starting to doubt our understanding of how much c02 actually does effect temperature. I feel like the recent pause in warming doesn't sit right with my expectations. So I am looking back at what I assumed to be true and re questioning everything. .... and assuming nothing.
Moderator Response:[PS] This would be best discussed under a more focussed topic. eg here. " I feel like the recent pause in warming doesn't sit right with my expectations". Perhaps you havent read enough climate science to have very accurate expectation then? Try the appropriate sections of the IPCC WG1 report and bring questions to the appropriate topic.
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Ken in Oz at 09:49 AM on 28 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
I should say that I don't think the most serious impediments to action on climate are down to failure to communication of the science. My wish list on that front isn't going to turn the tables.
It may well be that more of the public demanding action is what overcomes the resisting inertia, but I think it's failures of politics, which sees people in positions of trust and responsibility putting their perceived role as advocates for agendas and interests that they support and that support them - their 'side' - ahead of their broader and longer term responsibilities that prevents such a public groundswell. As it prevents serious and effective policy action.
Rejection of mainstream science is given a stamp of respectability and authenticity when it comes from those with established power and influence - from those who are perceived to be essential to our own bit of economic security and prosperity. When the public is mislead and misinformed by those we should be able to trust that groundswell of public demand for appropriate action is inhibited. Better, more compelling communication that targets politicians and community leaders will lead to greater community acceptance of both the reality of the climate problem and of roads to solutions.
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Paul R Price at 08:26 AM on 28 July 20142014 SkS Weekly News Roundup #30B
On the Oreskes and Conway Washington Post article.
O&C have done great service in their Merchants of Doubt research and many of the "14 concepts that will be obsolete after catastrophic climate change" hit the target but one sticks out like a sore thumb as being dead wrong. Apparently along with "Fugitive emissions" one of the great evils contributing to catastrophic climate change is "Physical scientists" (I kid you not) who are described as:
The practitioners in a network of scientific disciplines derived from the 18th-century natural philosophy movement. Overwhelmingly male, they emphasized study of the world’s physical constituents and processes — the elements and compounds; atomic, magnetic and gravitational forces; chemical reactions; flows of air and water — to the neglect of biological and social realms, and focused on reductionist methodologies that impeded understanding of the crucial interactions between the physical, biological and social realms.
This is laughably absurd, it's just nonsense. It does not take too much knowledge of climate literature, both science and policy, to realise that the problem lies with special interests and competitive national interests, all at the expense of long-term global well being (yet O&R obscured these under "Market failure"). It is certainly not the physical scientists that bear blame for doing their job. How can O&R get this so wrong?
O&R's dig smacks of the Pielke Jr [dis]Honest Broker schtick of blaming the scientists, its very disappointing coming from them as historians of science.
Among the academics my own reading of conferences, research and policy documents is that it is the social sciences especially those in policy and in economics who have failed far more than the physical and biological scientists. After all the latter groups report the observations and best explanations whereas resolving the problem is all about how humans respond, which is the area where social scientists are supposed to be expert. But no, blame the poor physical scientists, next O&R'll be saying it's a conspiracy.
And what is this 'overwhelmingly male' quip? There seem to be a great many excellent women climate scientists, well represented on Twitter for example. Very odd to be demeaning them in the group. I don't get the gender comment. It might make sense if they were talking about climate disinformers who are predominantly older, white, rich, educated and male, but physical scientists? Puzzling.
Having nailed the Merchants of Doubt and their special interest funders showing how they to ensure that policy and politicians and economists stay on board the fossil fuel supertanker O&R somehow themselves come over all MsofD themselves and blame the scientists. 'Climate denial' doesn't even make the article's list.
Irony level seems high.
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Chris Crawford at 00:49 AM on 28 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Thanks for explaining it to me, Bob.
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Ken in Oz at 17:21 PM on 27 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
I'm not sure what Rob Painting has in mind. Antarctic ice, in isolation, is being actively employed by climate action obstructionists to mislead and deceive so giving some perspective to that should be as prominent and clear as possible, with the hope and intention that mass media should notice and pick up on it. If that can be done in ways that link to the bigger picture without getting too bogged down in excessive details and complexities, then it will be more compelling. But the bigger picture, including snow cover, glaciers, ice shelves and ice sheets as well as sea ice, appears to tell a compelling story, if it can be communicated well. The balance between big picture vs clarity on details seems very important.
I realise there are many excellent resources out there (including this site) and some may be already doing what I had in mind - with it not entirely clear in my own mind I suppose; what I've been thinking being many things rather than one.
It's making things as clear as possible to the widest possible audience that's needed, which probably takes it into the realm of video documentary rather than a revved up woodfortrees idea. I would still like to see improved and more compelling visual graphical representations available in user friendly form. For example I would like to see relative contributions to global average temperatures of various forcings through time - with the individual contributions being shown in an "additive" or perhaps subtractive manner; a bit like a series of Foster and Rahmstorf style temperature evolution graphs but including as many forcings as possible, with an option to see what temperature evolution would be with and without specific ones to help communicate their relative contributions. The links between ocean oscillations like ENSO, sea surface temperatures and surface air temperatures would be another, showing how much they impact year to year temperatures, whilst revealing how they do not, by themselves, create a longer term trends. Sea levels and distribution of water over land masses, revealing and accounting for the seasonal and year to year variations we see.
I would note that I think that Dana's heat content metric is probably a superior indicator of actual systemic change to the climate system than SAT's but it looks like we are stuck with global average surface air temperatures as the familiar, all inclusive metric of choice. As such, communicating the variations of the climate processes and phenomena that contribute to it's ups and downs, pauses and accelerations is important, if only to put to rest the false idea that climate science fails to take into account natural variations (in turn falsely suggestive that warming is down to those variations).
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Bob Loblaw at 13:06 PM on 27 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Chris:
Keep in mind that portions of a model can be verified in the manner you suggest. Take radiation transfer, for example. It is not difficult to take a vertical profile of radiation measurements, combined with a vertical profile of atmospheric conditions (pressure, humidity, aerosols, radiatively-active gas concentrations such as CO2 and O3, etc.) and compare the observed radiation to a model. You can also examine such things as surface energy balance sub-models (surface evaporation, thermal transfer from the surface to the atmosphere, soil temperatures) or other components of a GCM.
It's the "model the whole world" stage that is difficult to compare in a statistical sense. The model won't be an exact fit, and you can't easily tell if that is because of a model error or because you don't know something like atmospheric compostion well enough. In a physics-based model there aren't a lot of "tuning knobs", and adjusting one to fit one condition - e.g., temperature - may make another condition (precipitation) worse.
The other characteristic in complex models is that you can get good fits over quite a wide range of input variables, due to co-dependence of variables - e.g., add some reflective aerosols to the model atmosphere, but reduce your surface albedo. Trying to tweak results that way is, as you say, not of high scientific value.
To use a crude analogy, it's like having a model that says A+B=C, and you have measurements that say C=4 +/- 0.1, and you think that A is in the range 0.9-1.1 and B is in the range 2.9-3.1, and you start playing around with different values of A and B to try to best match C=4. You'll find an infinite number of values of A and B that will do the job equally well - without learning anything more about the accuracy of your model.
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barry1487 at 12:50 PM on 27 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Ken, we should probably add snow cover to the cryospheric list.
http://tamino.wordpress.com/2012/10/05/snow-2/
http://tamino.wordpress.com/2012/10/08/snowice-by-request/
Yes, it would be great for various purposes to have data for a multitude of metrics lined up and plottable/mappable in a super-app. But how long before contrarians start denouncing such a thing as a model? ;-)
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barry1487 at 12:33 PM on 27 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Ken,
Have you seen Nick Stokes Climate Plotter?
My main computer is down so facts and figures aren't to hand, but of glaciers, sea ice and land ice, only Antarctic sea ice and 15% of glaciers are increasing or unchanging. The Antarctic ice sheet, Greenland's, 85% of studied glaciers and Arctic sea ice are in decline. That's a fairly hefty statement against those zeroing in on metrics bucking the trend.
Jim Hunt,
My question hinges on whether the same algorithm is used North and South for AR4/AR5 (per the differences mentioned in the article Ashton linked). I don't know the answer to that, hence my query. This wasn't discussed in the article or the paper.
Here's the full paper.
http://www.the-cryosphere.net/8/1289/2014/tc-8-1289-2014.pdf
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Tom Curtis at 10:36 AM on 27 July 2014Challenges in Constraining Climate Sensitivity: Should IPCC AR5’s Lower Bound Be Revised Upward?
VictorVenema @3, using HadCRUT4 and calculating the temperature difference of the hiatus as the difference after 15 years between the Jan 1983 to Dec 2012 and the Jan 1998 to Dec 2012 trends, I calculate the temperature difference to be 0.18 C. I use HadCRUT4 because it is the most commonly used of the well known climate indices (even though there are good reasons to think GISS, and now BEST, are better). As a result, it is the temperature index most likely to be used in climate sensitivity studies.
Further, warming from 1910 is about 1 C, but warming from the preindustrial era (and certainly from 1850) is about 0.8 C. The difference is because of a low temperature due to a sequence of large volcanoes in the preceding decades (effectively starting with Krakatoa), and a solar minimum in 1910 as strong, or stronger than that we are currently experiencing. Combining the difference in the values, the "hiatus" would make a difference of 22.7% in a climate sensitivity estimate which was a simple function of temperature and forcing. It would reduce a climate sensitivity estimate from 3 C to 2.3 C per doubling of CO2; or from 2 C to 1.5 C. That is, it is sufficient to account for the reduction on climate sensitivity estimates in the IPCC AR5.
Never-the-less, there are other factors involved. One is lower estimates of the temperature difference between the pre-industrial and the LGM, which has resulted in a number of lower paleoclimate estimates of climate sensitivity. Another is variations of technique such as Nic Lewis's use of a "non-informative prior" which turns out to be an assumption of low climate sensitivity built into the Bayesian methodology (and which is justified only by subjective preference IMO).
Further factors (particularly relevant to Otto et al 2013) include the adjustment of estimated forcings to reflect lower values of aerosol radiative forcing from AR5 (which drops the estimate from 2.4 to 2.0 C per doubling), and the assumption that radiative forcing per doubling of CO2 is 3.44 W/m^2 rather than the more commonly accepted 3.7 W/m^2, without which assumption their estimate would be 2.2 C per doubling. The later assumption is based on Forster et al (2013), who estimate an average adjusted forcing for the CMIP5 models of 3.44 W/m^2. "Adjusted forcing" is a different concept to "radiative forcing", and allows for some rapid tropospheric feedbacks. It is not clear to me that using adjusted forcing rather than radiative forcing in their climate sensitivity estimate is not a mistake.
Finally, some of the perception of a lower climate sensitivity comes from treating all estimates as being equal. They are not. Otto et al, for example state that their estimate is for a "lower bound" of climate sensitivity as it does not allow "... delayed ocean warming at high latitudes can mask the impact of local positive feedbacks". That is, Otto et al {with the probable exception of Nic Lewis ;)} expect climate sensitivity to be greater than their estimate (ignoring error margins), a fact that is frequently ignored.
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VictorVenema at 06:15 AM on 27 July 2014Challenges in Constraining Climate Sensitivity: Should IPCC AR5’s Lower Bound Be Revised Upward?
I wonder if the relationship between the estimates of climate sensitivity and the apparent warming slowdown is really there.
The "missing" warming is in the order of 0.1°C for a decade. The man-made warming itself is in the order of 1°C over a century. Thus we are talking about a deviation in the order of one to a few percent.I would personally not expect that small deviation to influence the estimates of the climate sensitivity that much. Aren't the recent estimates of climate sensitivity lower for other reasons? Or is there some nonlinearity in these estimation methods that I am overlooking?
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Chris Crawford at 03:26 AM on 27 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Bob Loblaw @ 64
Thanks for explaining that. Yes, it would surely be quite a job to put together a statistical analysis of the reliability of various models, and there would be a lot of tough judgements to be made that would detract from the rigor of the analysis. It *is* certainly possible; the pattern matching you describe can be carried out with mathematical rigor.
I suspect, however, that the value of such a project to the scientific community would be low; in the long run, a well-informed scientist's judgement will always produce better results than any formalized analysis such as I am suggesting. I suppose that such an analysis would be of utility only for debunking deniers' claims that the models don't work. The few knowledgeable deniers have already, in all likelihood, come up with such analyses and realized just how good the climate models are.
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PhilippeChantreau at 02:24 AM on 27 July 2014There is no consensus
"L,C&C who often claim nobody listens to them"
Someone at APS listened enough to bother with yet another ClimateAudit insinuation of impropriety, which I find a little disappointing. Of course, if "skeptics" were part of that commitee then all bets are off...
L,C & C were listened to when they first spoke. As they kept on repeating themselves, the amount of listening they garnered decreased, which is entirely normal and even desirable. Sometimes I wish that the the mass media out there would have the same sloganeering policy that SkS has.
L, C&C receive exactly the attention they deserve from the scientific community and way more than that in the public media, they have no reason to complain.
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Bob Loblaw at 22:54 PM on 26 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Chris Crawford @ 62:
With a huge variety of variables (temperature, precipitation, wind speed, pressure, radiation, etc.) to compare, combined with the fact that model output often represents averages at fixed grid spacing whereas observations are rather randomly distributed with different temporal and spatial resotuion, there is no simple mathematical relationship to derive such an error statistic. Climate GCMs are not statistical models: they do not reproduce data at points specified by observations.
What can be done is pattern-matching: does a map of modelled global temperature look like the map of observed global temperature?, etc.
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MA Rodger at 18:18 PM on 26 July 2014There is no consensus
PhysicsProf @618 & PhilippeChantreau @619/620.
The APS is reviewing its statement on Climate Change and the document link given @618 is to a document that was an early part of that process. It is a pukka APS document produced by the sub-committee appointed to look into the review. (It is the "Framing Document for Workshop" mentioned on the page linked above.) It was a sort-of agenda document for a workshop held in January this year. What was curious was the list of experts invited to that workshop. These included obvious suspects (Bill Collins, Isacc Held, Ben Santer) and controversially arch-denialists Lindzen, Curry & Christy. I know of no offical reason for their invite but there was comment I read that this would disarm L,C&C who often claim nobody listens to them. The workshop transcript is available on-line and stretches to 573 pages (of big print).
The next step in the process, a decisionof whether to stick with the old statement from 2007 (which itself got some skeptics grinding teeth) or whether to start a process to develop a fresh statement - that decision has yet to be made. However the whole thing got a lot of airing in March when a professional twit of the British press called Delingpole kicked off a story that L,C&C had been appointed to the committee considering the APS statement review. Although utter bunk, the skeptical twitosphere feasted heavily on this "news" for some days.
So we await the outcome of the sub-committee's deliberations.
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PhilippeChantreau at 16:18 PM on 26 July 2014There is no consensus
I sent an e-mail with the url to APS, hopefully they'll respond in a few days and tell us something on the nature of this statement.
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Ken in Oz at 16:15 PM on 26 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Rob @15 - I look forward to it.
As an aside, I have had an ongoing wish for improved graphical demonstration more broadly. Perhaps out of naivete, I keep imagining animated graphs progressing through various time periods, with a whole lot of variables/indicators being shown individually as well as together, and additively as well - some kind of woodfortrees on steroids, like 'here's global heat content and surface air temperatures, here's surface air temperatures with sea surface temperatures, with ENSO and with AO, milankovic cycle, aerosols, albedo changes. etc.' ie visually revealing real world connections and contributions where they exist or lack of them where they don't. Ultimately we get an additive 'here, with everything we know about!'
Needless to say that would be a mammoth undertaking; I'm not holding my breath!
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PhilippeChantreau at 16:09 PM on 26 July 2014There is no consensus
PhysicsProf, the document you link is worded and presented in a rather peculiar fashion. What is its exact origin?
When I go to the APS website and follow the links, I find this page:
http://www.aps.org/policy/statements/07_1.cfm
It is much more consistent with the normal tone of APS statements, which usually do not contain an abundance of graphs and data, or text highlighted in red. I looked at a variety of other statements and none of them has a format similar to the one you linked. I had too much difficulty to keep the document running on my computer to study it in enough detail, it kept on triggering error messages when trying to scroll. However, I did see a reference to the CimateAudit blog, which I find highly suspicious. APS does not normally refer to blogs of any kind.
Do you know where exactly that document came from? As I see it, it appears more fraudulent than anything else. Did you talk to anyone at APS about it?
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chriskoz at 14:49 PM on 26 July 20142014 SkS Weekly News Roundup #30A
The relationship between global warming denial and speaking English, as noticed by Chris Mooney, is incidental. Similar to once popular meme about the number of pirates on Indian Ocean and GW.
The ranking of 20 countries on the denial scale in Chris' article is truely explained by conflict of national interests. It happens that the top industrialised countries that mostly benefited from FF (and continue to benefit under bau scenario) do speak English. Those countries are joined by non-English speaking Poland, where coal mining and processing is the main driver of the economy, with virualy all top paying jobs.
On the other hand, India with its largest in the world English-speaking population (note Indians who took this survey online must speak English fluently with no exceptions) is at the end of the list. That's because there is no conflict of interest in this country, while their language is irrelevant.
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PhysicsProf at 13:26 PM on 26 July 2014There is no consensus
Has skeptical science done an article responding to the American Physical Society Framing document on climate science which raised substantial questions on the state of climate science: http://www.aps.org/policy/statements/upload/climate-review-framing.pdf
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Tom Curtis at 10:37 AM on 26 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Anne Ominous @59, the authors of the paper only constrained their selection of model runs to be in phase with temperature trends in the NINO 3.4 region, as demarcated in the figure below:
That area is just 3.1 million km^2, or 1.2% of the Earth's surface (1.9% of the Pacific's area). Were you to select an equivalent area at random from the Earth's surface, and filter model runs to have the same phase of trends in that area, it is highly unlikely that it would sort the models runs into high and low trend groupings. Consequently your analogy is inapt.
This is only an unsurprising result because a number of other studies (formal and informal) have already shown that ENSO trends are probably the major cause in the relatively flat GMST trends over the last 15-20 years. The authors have in fact done what scientists should do - tested a currently popular hypothesis by an alternative method to those that have already been tried to see if it avoids falsification when you do so. It did, which is fairly ho-hum given the other results.
The only problem is that AGW deniers refuse to acknowledge the ENSO connection. The simultaneously (it seems) maintain that:
1) 1998 was only a very hot year because of ENSO, so the very high temperatures in 1998 are not evidence of global warming;
2) Only short term trends including 1998 at or near the start year can be of any interest for testing the validity of global warming; and
3) The slightly positive trend between 1998 and 2012 has nothing whatever to do with the very strong El Nino in 1998 and the strong La Ninas in 2008, and 2011/12.
Some people notice a certain inconsistency in the denier opinion.
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Chris Crawford at 10:31 AM on 26 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
I have a question regarding the measurement of the success of the models. I don't see anything in this paper suggesting a calculation of deviance (sum of squares of errors) of the models. I realize that they make multiple predictions; hence, there would be a LOT of calculating to get an overall assessment of the reliability of the model. Yet I would think that a solid calculation of the deviance would make it easy to address questions about the reliability of the models.
So the question is: where are the deviance results?
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Rob Honeycutt at 07:14 AM on 26 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Anne... My thought on the relevance of the paper is this: What are the potential outcomes of the experiment?
a) Models phased with La Nina do not show any detectable difference from out of phase models.
b) Models phased with La Nina do show a detectable difference from out of phase models that agree with the observed surface trend.
If the results were (a), that would suggest there is potentially something wrong in the models that are causing them not tracking the observed trend in surface trend of the past 15 years.
If the results were (b), then we have an indicator that prevailing La Nina conditions can at least partially explain the observed temperature trend of the past 15 years.
The results ended up agreeing with (b).
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KR at 07:07 AM on 26 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Anne Ominous - Climate deniers frequently note that observations are at the edge of the model envelope, and then claim the models are useless/wrong and we should ignore them. Foolish rhetoric, really, since even perfect models show stochastic variation on different runs, and neither the model mean nor any single individual run will therefore exactly match the trajectory of observations. Climate models aren't expected to track short term observations of climate variations, but rather explore long term trend averages.
This paper is an elegant demonstration that models do reproduce shorter term global temperature trends and patterns when model variations match observations - strong support for the accuracy and physical realism of those models, and their usefulness when exploring longer term trends where those variations average out.
Demonstrating that models are physically accurate enough to model the range of short term variations, and that observations are indeed within the envelope of modeled behavior, is hardly a waste of time. It shows that the models are useful.
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Anne Ominous at 05:56 AM on 26 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
scaddenp @48:
"The paper does demonstrate that a mean created from runs which are in phase with actual state are a closer match to observed global temperature."
This is so, but it is also a statement of the blatantly obvious. Why would a sane person need proof of this? I'm not asking this as flamebait, I am being completely serious. A very good analogy would be to say "this paper shows that periods during which the door of the darkroom was open are correlated with an increase in ambient illumination."
Seriously? And it's even pretty weak evidence of correlation, as Russ quite correctly pointed out.
The question remains: what does this paper actually demonstrate that wasn't already pretty darned obvious without it? The fact that models have to model reality in order to be valid (including the past) has been long known. So even if this paper is 100% true and valid, it is nothing more than a confirmation of something already known to REASONABLE people. I add that qualifier intentionally.
One might say "Yeah, but there was a time when the existence of phlogiston was considered to be 'obvious'." But these aren't those days. Reference Asimov's "The Relativity of Wrong."
We know what models are for, and at least roughly what evidence they provide and what not. To show that a few models that best (albeit badly) modeled the past also best (albeit very very badly) modeled the present is hardly a revelation. If I were a reviewer I would have rejected it out-of-hand as grandstanding and a waste of everybody's time.
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Magma at 01:16 AM on 26 July 20142014 SkS Weekly News Roundup #30A
Attack of the Chicago climate change maggots
I was a little surprised to see that level of vituperation in a Washington Post headline... but it turns out the article mentioned maggots hatching from fly eggs brought up from sewage backups caused by heavy rainstorms.
Literal maggots, not figurative ones.
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HK at 23:27 PM on 25 July 2014Seal of approval - How marine mammals provide important climate data
WRyan:
I think the different numbers depend on what period Hansen and others have used in their calculations. Hansen was probably most interested in the recent energy imbalance.
Based on figure 1 here and temperature data from GISS I got the following results for the troposphere’s fraction of the total heat accumulation:1961-2008
1.5 %
1975-1998
2 %
1993-2008
1.2 %The higher fraction of tropospheric warming in the second period is caused mostly by a very slow ocean warming between 1975 and 1990 compared to the warming we have seen after that.
It’s worth noting that the linear trend for the troposphere between 1993 and 2008 was 0.22°C/decade, and that is actually higher than the trend between 1975 and 1998 (0.18°/decade).BTW, this graph clearly shows that the ocean warming has been far from uniform. Note that the difference between these depth intervals would be even larger if they didn’t overlap each other.
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Rob Painting at 20:05 PM on 25 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Ken in Oz - That's a very good point. I think you will find the comparison quite mindboggling. I'll work on a post, although given the enormous disparity I'm not sure how to demonstrate it graphically.
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Ken in Oz at 13:04 PM on 25 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Barry @ 4
With a counter intuitive increase in winter maximum for Antarctica in a warming world, it seems that there is something to be gained by giving some comparisons with overall changes to Antarctic ice. In order to undercut the opportunities from that for climate science deniers and obstructionists creating false perceptions it seems to me that some perspective could be gained by looking at land ice and sea ice side by side, both qualitively (seasonal vs permanent) and quantitively. How does this periodic, winter only increase in sea ice look alongside the estimates of 160 billion tonnes a year of land ice being lost without being replaced? Anyone know how much mass that winter sea ice increase comes to?
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WRyan at 10:54 AM on 25 July 2014Seal of approval - How marine mammals provide important climate data
With regard to the different heat capacity of the ocean and atmosphere, the absolute heat content of the two systems is not in question here. Rather we are looking at their respective changes in heat content.
The changes in heat content depend on their respective specific heat capacities and the respective changes in average temperature of each system.
The troposphere has had a fairly uniform temperature increase throughout its entire mass. So we can calcualte its increase in heat content by using its entire mass. I don't know if the same can be said of the ocean.
I imagine that heat distribution in the ocean is much slower than heat distribution in the atmosphere, so the temperature increase of the upper ocean is probably different to the temperature change in the deeper ocean. So I don't know how accurate it would be to use the total mass of the ocean when calculating heat gain in recent periods unless you had the average temperature increase for the entire ocean.
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WRyan at 10:19 AM on 25 July 2014Seal of approval - How marine mammals provide important climate data
Thanks for the graph.
Older calculations had the atmospheric warming at around 2% of the total heat content. These two graphs include periods after 2005 where the atmosphere was not warming. So this difference in atmospheric heat gain might be due to this lack of temperature increase, or maybe Hansen is using a different way calculating heat gain for different parts of the system than was used in the earlier calculations.
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HK at 05:21 AM on 25 July 2014Seal of approval - How marine mammals provide important climate data
WRyan:
This figure on page 13 in Earth’s energy imbalance and implications by James Hansen et al shows the estimated energy imbalance (rate of warming or cooling) for different parts of the climate system given as watt/m² spread over the entire surface of the Earth.
Notice that the atmosphere has accumulated a nearly negligible fraction of the entire climate system’s heat increase and a pretty small part of the non-ocean climate system as well. The amount of heat penetrating into the ground is several times larger than the accumulation in the atmosphere and the second largest component of non-ocean, after the melting of sea ice and ice sheets.
Regarding the heat capacity of the ocean vs. the atmosphere:
Water has about 4 times larger heat capacity than air measured by mass, i.e. it takes 4 times more energy to heat one gram of water by 1°C than one gram of air. The total mass of the oceans is about 250 timer larger than the atmosphere, hence the 1000-fold larger heat capacity overall. -
CBDunkerson at 04:36 AM on 25 July 2014Where is global warming going?
WRyan... how does the photon know the temperature of the object it would eventually impact if it were emitted? I mean... it could have to travel hundreds of light years to get there. Say a photon emitted from a distant star is going to hit the International Space Station, but if the station hadn't been constructed (hundreds of years after the photon was emitted) then it would have just passed through empty space and continued on to hit the Sun (which in this hypothetical is hotter than the emitting star). How does the photon instantaneously 'know' something that won't happen for hundreds of years? For that matter... how is it NOT emitted just because it will eventually strike a warmer object?
You should really publish on this. Among other things it allows faster than light communication. Aim a laser at a target location and then raise or lower the temperature of that target to higher/lower than the laser's temp and the laser will instantaneously stop emitting when the temperature is higher... regardless of the distance involved. Messages could thus be 'transmitted' instantly to the laser end by changing the temperature at the target end.
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Mammal_E at 02:33 AM on 25 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
What the comments on this post highlight is the difficulty in our brains coming to grips with two very distinct aspects of modeling climate (or any dynamic system):
1) The conceptual and quantitative understanding of mechanism
2) Assumptions about future states that contribute to the quantity being modeled.
Both have to hold true in order to make skillful predictions about future conditions, especially in the short term when essentially random factors can hold sway. Mismatch between predictions and observed conditions (assuming the observations are reliable — that's another topic) can derive from failures of 1) or 2), but 1) is the component that science is most interested in, and is most relevant to long-term prediction. Therefore, to assess the strength of our understanding, we need to figure out how much of the mismatch can be attributed to 2).
Here's an example:As I understand it, my bank balance changes according to this equation:
change in balance = pay + other income - expenses
I can predict how my bank balance will change in the future if I assume some things that are pretty well understood (my monthly paycheck, typical seasonal utility bills, etc.). However, some aspects of the future are random (unexpected car repairs, warm/cool spells affecting utility bills, etc.) — these cannot be predicted specifically but their statistical properties can be estimated (e.g., average & variance of car repair bills by year, etc.) to yield a stochastic rather than deterministic forecast. Also, I could get an unexpected pay raise (ha!), need to help my brother out financially, etc. All of these factors can generate mismatch between predicted changes in the balance and what actually happens.
But (and here's the important bit): that mismatch does not mean that my mechanistic understanding of the system is faulty, because it stems entirely from item 2). How can I demonstrate that? Well, if I plug the actual values of income & expenses into the equation above it yields a perfect match (hindcasting). Alternatively, (as was done by Risbey et al), I could select those stochastic forecasts that happened to get income and expense values close to what actually occurred, and find that the forecasts of those runs are close to the actual change in my balance.
Examining these runs is not "cherry picking" in any sense of the word, it is a necessary step to separate out the effects of items 1) and 2) on model-data mismatch. If these tests failed, that would imply that my understanding is faulty: some other source of gain or loss must be operating. Perhaps a bank employee is skimming?
Climate forecasts are necessarily much less precise than my personal economic forecasts, because the system is observed with error and because many more inputs are involved that interact in complicated, nonlinear, spatially explicit ways. But the logic involved is the same.
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Christian Moe at 00:56 AM on 25 July 2014New study investigates the impact of climate change on malaria
This sentence doesn't parse:
They downscale global climate models “to provide high-resolution temperature data for four different sites (in Kenya) and show that although outputs from the global and downscaled models predict diverse but qualitatively similar effects,” and some of the modeling approaches led to quite different findings.
Also, there's a stray quotation mark in the Mann quote, which might indicate some text got included in the blockquote that shouldn't be.
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Tom Curtis at 23:31 PM on 24 July 2014Where is global warming going?
WRyan @94&95, that is the trap of thinking in terms of the temperature of the emitting source rather than the energy of the photon. The Sun also emitts IR radiation, for example. A PV cell behind such a filter would react in the same way to the IR photons from the Sun as it would to IR photons from any other source. Light from an LED or fluorescent light is carried by high energy photons, even though the method of emission is not thermal.
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WRyan at 21:49 PM on 24 July 2014Where is global warming going?
p.s. With regard to my previous comment. The temperature difference requirement applies only to thermal radiation.
A PV panel can absorb light from a light source like an LED or a fluorescent light without having ot be cooler than the light source. This is because the light from those sources is not being produced by a thermal process.
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WRyan at 21:44 PM on 24 July 2014Where is global warming going?
just read this article and comments. With regard to the hypothetical photovoltaic IR panel, it would work if it was cooled below the temperature of the emitting body (the earth's surface, in this case.) PV panels work because they are cooler than the Sun's surface, which is where the light originates.
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WRyan at 20:12 PM on 24 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
The text you quoted about spatial trends is from the abstract and it is stated without any context. Perhaps someone who has read the paper can provide that context by giving a description of how the authors support that statement in the main body of the paper.
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WRyan at 18:35 PM on 24 July 2014Seal of approval - How marine mammals provide important climate data
I'm guessing that the heat absorbed to produce the net loss of ice is also included in the land-ice-air value.
There is also some heat involved in raising the land's temperature. It would be interesting to see that calculated. I can't imagine that heat would penetrate far below the land's surface, but it would have to gain some heat to keep the surface temperature in a rough equilibrium with the increased air temperature over land.
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Rob Painting at 18:25 PM on 24 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Ashton - Yes, perhaps it was in the original text and later omitted. Rightly so, there are other data which suggest a robust increase in the Antarctic sea ice even though the Earth is very obviously warming.
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WRyan at 18:14 PM on 24 July 2014Seal of approval - How marine mammals provide important climate data
That graph is showing the change in heat content. So the relative values probably reflect the fact that that the temperature of the tropopause has increased more than the temperature of the ocean, combined with the much larger volume of the tropopause compared to the volume of ocean water that has undergone a measurable increase in temperature. That's just a guess though.
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miro at 15:15 PM on 24 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
The words used in the context provided definitely seem to signify the spatial trend for the entire Pacific. So therefore the line above is either poorly worded or taken out of context (I don't have access to the paper and so I can't verify, but going off history I'd put my money on the latter).
Indeed I agree that it's not an important point in the context of the paper's goals, but most deniers will be happy to focus on the one incidental discrepency and ignoring the point made by the paper as a whole. This helps them ignore the fact that this paper completely decimates just about the only argument they were hanging onto - that climate models failed to predict the current period of slower warming. This unambiguously shows that the models did in fact predict the current slowdown in warming - within the bounds of what they attempt to predict.
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scaddenp at 14:21 PM on 24 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
I'd go with 1/ more or less. The spatial pattern of interest is the cooling eastern pacific cf warming central-western. This pattern is visible in both the selected models and observation but missing in the anti-phased model. I would definitely say "good" means something different to the authors than it does to Russ. I think it is accurate for the 15 year trend, but somewhat dependent on your expectation to apply it to the spatial trend. However, I think it is a very small point blown right of proportion when it comes to evaluation of the paper as a whole. The main text barely mentions it.
It is easier to make the comparison looking at the figs at HotWhopper than in the Russ gif, if you dont have access to the paper.
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Chris Crawford at 14:13 PM on 24 July 2014Seal of approval - How marine mammals provide important climate data
Thanks for explaining that for me, Mr. Painting. I had not taken into account the differences due to distribution between land and ocean as a function of latitude. I suppose that there are further differences between the heat capacity in ideal conditions and the heat capacity in practice.
Thanks again.
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miro at 13:29 PM on 24 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
We present a more appropriate test of models where only those models with natural variability (represented by El Niño/Southern Oscillation) largely in phase with observations are selected from multi-model ensembles for comparison with observations. These tests show that climate models have provided good estimates of 15-year trends, including for recent periods and for Pacific spatial trend patterns.
I'm a bit confused by this as well. I must admit looking at the maps of the regional trends around the Pacific look inaccurate based on the graphs shown by Russ. This seems to conflict with the bolded text above. I'm not convinced anyone has really provided a reasonable answer to this. Either;
1) The authors actually mean a different thing when they talk about "Pacific spatial trend patterns" than what Russ believes, and that phrase does not refer to the regional distribution of warming in the Pacific region but rather something else. In this case, what exactly are the authors referring to here?
2) The maps are misleading in some way, making similar trends actually look completely different.
3) The models are in fact inaccurate, and the authors are incorrect in the bolded statement.
It's confusing because the paper's goal seems to be to test whether models can provide the correct global temperature scales if the ENSO input is modelled correctly, and it shows that the models are actually accurate globally. But this almost throwaway line seems to suggest that the spatial distribution of the warming was also predicted correctly, when it really looks like it wasn't.
Some commentators have pointed out that the model's aren't expected to get the spatial distribution of warming accurate, and that's fine, I don't think anyone (excluding Watts, Monckton, et al) can reasonably expect accuracy where the models are not designed to provide it, but if that's the case, why is the bolded phrase even included in the paper?
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Tom Curtis at 11:45 AM on 24 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Charlie A @32 shows the following image, and comments:
"Figure 2 of this paper show the "small amount" by which forecasted trends have diverged from reality in the sort period of true forecast vs. hindcast. Look closely at the trends from recent observations vs the models. Note it is nearly outside the 2.5 percentile line."
From 97 fifteen year trends, 5 instances of observations being at the 2.5% limit, and two of them being at the 97.5% limit. (Because trends overlap, clusters of trends at the limit are treated as single instances.) That is enough to suggest the models do not capture the range of natural variability, but not enough to data to suggest a bias towards warm or cool result.
Of the two warm episodes, both are associated with strong positive 15 year trends in the inverted, lagged SOI. Of the 5 cool episodes, four are associated with strong negative trends in the lagged SOI. That is, 6 out of seven strongly tending temperature excursions in observed temperatures relative to modelled temperatures are associated with same sign excursions in lagged inverted SOI, and therefore are probably the results of large La Nina trends. The one low escursion not related to ENSO trends occurs in the twenty year period from 1880 to 1899 in which there were twelve major volcanic erruptions (VEI 4 +), leading of with Krakatoa.
When comparing the lagged, inverted SOI trends to GISS LOTI, the match in the early half of the century is quite good (with the exception of the first 20 years). In the latter half of the twentieth, and the early thirtyieth century two discrepancies stand out. One is the major positive trend excursion around 1980 associated with the 1982/83 El Nino. That event coincided with the 1982 El Chichon erruption, the effects of the two events on global temperatures more or less cancelling out. The other is the large disparity in the early twentieth century, where GMST trends are far more positive than would be expected from the SOI trends. Something, in other words, has been warming the Earth far more strongly than would be expected from looking at natural variation alone.
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Tom Dayton at 11:43 AM on 24 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Yes, thank you Russ for withdrawing your claim of cherrypicking.
You still misunderstand the main purpose of the paper, as revealed by your comment "The higher the correlation, the more the method would treat luck as skill." The authors of the paper did not treat luck as skill. Indeed, they conceived their project on the basis of their and everyone else's explicit and repeated acknowledgment that the GCMs get the timing of ENSO events correct entirely by chance! Their main conclusion was, as scaddenp noted, that the GCMs could be improved substantially (not completely!) in their projections of 15 year periods if the GCMS' timing of ENSO events was improved substantially. The authors did not claim any method for accomplishing that improvement of ENSO timing, and did not even claim that it is possible for anyone, ever, to accomplish that improvement. Their paper leaves unchallenged the suspicion that GCMs forever will lack the skill to accurately project the timing of ENSO events. That means their paper leaves unchallenged the suspicion that GCMs forever will lack the skill to much more accurately project global mean surface temperature for 15 year periods.
What the authors did claim (I think; somebody please correct me if I'm wrong) is that:
- The consequences of ENSO events for global mean surface temperature are responsible for a large portion (not all!) of the GCM's poor projection of global mean surface temperature in 15 year timescales.
- GCMs fairly accurately project the spatial pattern of ENSO events within (only) the Nino 3.4 geographic area (see Steve Metzler's comment of 22:41 PM on 23 July, 2014, on Lewandowsky's post), when by sheer chance the GCMs happen to project the timing correctly. It is fair for you to use your own judgment of what qualifies as "fairly accurate," but my judgment is that the smeared-out temperature of the bad-timing-GCM runs is sufficiently different from the concentrated temperature of the good-timing GCM runs. (See HotWhopper's reproduction of Figure 5's pieces, for easy visual comparison.)
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Tom Curtis at 11:17 AM on 24 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
"[If] the only model problem is phasing of Enso, and the current 15 year GMST trends are below all model runs (or perhaps only below 97.5% of all model runs). then I would expect that either 1) that La Nina in the real world over the last 15 years is at or above the 97 percentile point, or 2) that the distribution of Enso in the entire CMIP5 ensemble of model runs is overwhelmingly biased towards El Nino."
1) The authors of the paper, SFAIK, make no claim that ENSO is the only factor supressing recent observed trends in GMST. Therefore you are not entitled to assume that because the observed 1998-2012 trend in GMST is at the 2.5% limit that the ENSO trend will also be at or near that limit. Indeed, the 4 best modelled trends are unlikely to be within the 2.5% limit of ENSO trends as they are selected only for having the same phase out of far fewer than 100 realizations. Yet they match the observed trend fairly closely (see first figure in OP), therefore falsifying your assumption. (Note, the lower limit is the 2.5% limit, not the 97.5% limit.)
2) Even if a ENSO trend approaching the 2.5% limit was required to explain the depressed observed trend in GMST, it is the trend that needs to be statistically unlikely, not the individual ENSO states in any period. An unusual trend can be formed by a couple of stronger than normal El Nino events at the start of the trend period and a couple of stronger than usual La Nina events at the end of the trend period without any of those events being 97.5% (for El NIno) or 2.5% (for La Nina) events.
3) In the so obvious it is unbelievable that you missed it category, an unusually strong El Nino at the start of the trend period is just as capable of generating a very strong trend as an unusually strong La Nina at the end. Your restricting the test to the later condition only is uncalled for, and very puzzling given that it is known the 97/98 El Nino was unusually strong:
4) Your claim that the observed ENSO trends were not unusual (based solely on claims regarding the strength of recent La Ninas) is not backed up by the data. For temperature based indices (plotted above), the observed percentile rank of the 1998-2012 ENSO trends are:
NINO1+2_|_ NINO3_|_ NINO4_|_ NINO3.4
_10%_____|_ 7.1%___|_ 38.1%__|_ 25.7%That is, two out of four such indices do show very low percentile ranks. That they do not show lower percentile ranks is probably due to two unusualy strong El Ninos appearing in the short record. (Note, the ONI is just the three month running mean of NINO 3.4, and so will differ little from that record.)
5) Single region temperatre indices for ENSO are fatally flawed (IMO) in that they will incorporate the general warming trend due to global warming as a trend to more, and stronger El Ninos. Far better are multiple region indices (such as ENSO 1+2) where the common global warming signal can be cancelled out, or non temperature indices such as the SOI:
The inverted five month lagged SOI trend for 1998-2012 has a percentile rank of 2.52%, compared the GISS LOTI trend of 42.9%. For what it is worth, the inverted, lagged 1998 ranks at the 95.6th percentile in the SOI, and 2011 ranks at the 0th percentile. The inverted, lagged SOI index for 2011 was -17.3, which is less than the strongest shown on the graph above (which was not lagged). The five month lagged 2011 La Nina has a percentile rank of 0.8% among all 12 month averages of the SOI index.
So, when you say the 2011 La Nina was not unusually strong, that only indicates over reliance on one ENSO index, and an unsuitable one in a warming world.
In summary, nearly every claim you make @37 is wrong. To be so comprehensively wrong should be a matter of embarrassment for you. You should certainly pause and reconsider your position.
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scaddenp at 10:52 AM on 24 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Thank you Russ. That is appreciated.
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