Rather strangely, the recent Science Advances paper Nonlinear climate sensitivity and its implications for future greenhouse warming, that’s been getting some attention recently, made it into our Journal Club today (and it had nothing to do with me). It’s, consequently, given me some impetus to write about it. Fortunately, James Annan has already written about it, so I don’t need to say much.
Essentially it uses proxies and models to reconstruct temperatures and forcings over the past 784000 years. Their key result is probably that the climate sensitivity is state dependent; higher in warm climates than in cold. They conclude that in warm climates, the equilibrium climate sensitivity (ECS) is 4.88 ± 0.57 K, which only just overlaps with the IPCC’s likely range (1.5 – 4.5K). What’s maybe more interesting is that they also try to estimate the transient climate response (TCR) which, using paleo data, requires a model of ocean heat uptake. They conclude that it is 2.74K with a likely range from 2.23 to 3.43K. This, again, only just overlaps the IPCC’s likely range (1 – 2.5K).
So, their estimates for climate sensitivity are somewhat high and, I would argue, unrealistically so. A TCR of 2.74K would suggest that we should, today, have warmed by around 1.7K. We’ve only warmed by around 1K. It could be so non-linear that we will suddenly see accelerated warming as we approach a doubling of CO2, but we’re already about two-thirds of the way there, so this seems a bit unlikely. It could be that internal variability is masking a large amount of forced warming, but 0.7K of cooling is much higher than is regarded as reasonable. It is currently regarded as extremely unlikely that more than 50% of the observed warming since 1950 could be non-anthropogenic, so it seems similarly unlikely that non-anthropogenic influences could have induced substantial cooling over the same time period.
I should make clear that there are indications that natural influences have induced cooling, but it’s most likely at the 10% level than at the level of almost halving the forced warming. For example, the pattern of sea surface warming may have enhanced the cloud feedback so that we’ve ultimately warmed less than we might have done. Again, however, the impact is probably at the 10% level over the period of a few decades. It, therefore, seems very hard to reconcile a TCR of 2.74K with current observations.
I think that’s all I have to say. Although the ECS and TCR estimates do just overlap the IPCC likely ranges, it does seems as though these estimates are somewhat higher than is reasonable. Of course, we can’t necessarily rule out such high values, but I wouldn’t regard this paper as a reason to give them more weight than they currently have.
...and Then There's Physics 
That it does not fit to the historical warming is something that should be noted as a problem in the paper, but should not be a reason to dismiss it. If only because also the temperature curve could be wrong and show too little warming.
Even if the values are too high, the non-linearity could still hold and would be very interesting and could explain part of the broad range of ECS estimates.
I would like to understand the physics. In this case the reasons why the ECS is higher in warm climates. When it comes to the albedo feedback from snow and sea ice, I would have expected the reverse.
The arguments of James seem sufficiently strong to withhold judgement and see what future papers will say on this topic.
Victor,
Yes, I agree that the state dependence is very interesting. I would quite like to know a bit more about how robust their trend is; for example, I think their estimated temperature changes are higher than some others, and their estimated forcing changes are a bit lower. So, maybe their state dependence results might be indicating something real, even if their actual estimates are a bit too high.
So the paper did not have a section “and then there’s physics”?
When you say,
A TCR of 2.74K would suggest that we should, today, have warmed by around 1.7K.
you neglect to compensate for SO2 aerosol forcing, many of whose parameters have only recently been identified (regional impacts on negative PDO) and some others that are known, poorly understood and subsequently not quantified and yet have very significant potential impacts with regard to atmospheric meridional heat transport vectors (direct cooling of upper troposphere with implications to Lapse Rate, Hadley Cell expansion and polar jet weakening, leading to increased intrusion of latent heat into the arctic cell during Winter.
Victor,
Not that I could see. I’ll post the key figure which shows how the response varies with climate state.
Jai,
Not really; I’m just assuming a net change in external forcing of 2.3W/m^2, which includes the aerosol forcing. Of course, this could be much more negative and could then produce a much smaller net change in forcing, but this is still unlikely, given the probablity distributions of the different forcings.
Even without significant increases in negative forcing associated with clouds, cloud distribution and upper Trop cooling impacts on Lapse Rate (all very likely) the regional impacts on pacific sea surface winds and the increased tendency for negative PDO values produces reduced warming. It is very clear that the past 20 years have been a result of stronger negative PDO values leading to significantly reduced warming values. This is changing now as China’s coal consumption has declined by 10% in the first 6 months of 2016, that they are aggressively working to reduce air pollution impacts and that this trend will continue into the foreseeable future.
Jai,
I agree that we could see a shift towards faster warming, but we could double atmospheric CO2 by the middle of this century. A TCR of 2.74K would imply something like 0.45K/decade warming – just seems a bit too high.
P.S. you cannot hindcast TCR this way as TCR requires discreet annual increase values in radiative forcing and a gradual change in net energy loss/gains going forward. The systemic response does not work when reproduced with historical data.
cheers!
I don’t quite follow. Are you just suggesting that these basic energy balance models have assumptions that mean that they might not be appropriate estimates for TCR?
The TCR response mechanism requires specific boundary conditions that are not met by historic data. They are as good as anything going forward based on what we have, (as long as you utilize the ECS = 5.0 value) I guarantee you here and now that by the time we reach 560 PPMV of CO2 we will be seeing arctic ice free states during the summer solstice and an additional albedo-driven radiative forcing so intense that it will produce 2.3 Watts/meter squared on a global average (though it will be experienced entirely by the arctic seas).
Jai,
Yes, I agree what the energy balance methods are a bit simplistic and have assumptions (linearity) that may not (probably aren’t) true. I wouldn’t be surprised if we did see other factors kicking in if we do get to 560 ppm.
Skimming the paper, it appears that it makes the mistake of neglecting the impact of the distribution of radiative forcing. For the past 800,000 years, the change in radiative forcing was a lot more concentrated at the poles (due to ice-albedo feedback and Milankovitch effect) than for recent changes due to human activity. As a result, the methodology used will give an overestimation of climate sensitivity.
They also completely ignore vegetation changes as a source of forcing (rather they treat it a feedback), but given that vegetation changes can take thousands of years it doesn’t make sense to treat it differently than the ice-albedo feedback when calculating ECS. Also, they don’t take Milankovitch forcing into account (which overall is small, but regionally is quite large, especially Obliquity changes).
Also, as I think I mentioned earlier, the temperature changes are larger than what is suggested by Annan and Hargreaves.
All these things result in a significant overestimation of climate sensitivity.
October PDO is .56… still stubbornly positive.
40 years: slope = 0.0173697 per year
30 years: slope = 0.0179249 per year
15 years: slope = 0.0172551 per year (slight decrease is all that is left of the pause)
10 years: slope = 0.0325856 per year
8 years: slope = 0.0429588 per year
6 years: slope = 0.0768455 per year
4 years: slope = 0.113422 per year
It’s going to take back-to-back La Niña events, and exceptionally strong ones, to reverse the course. I don’t think it is crazy to think 2017 could end a top 5 warmest year, maybe even top 3.
“I think that’s all I have to say. Although the ECS and TCR estimates do just overlap the IPCC likely ranges, it does seems as though these estimates are somewhat higher than is reasonable. Of course, we can’t necessarily rule out such high values, but I wouldn’t regard this paper as a reason to give them more weight than they currently have. “
I don’t know, these climate activists that latch onto the slightest evidence of high climate sensitivity as irrefutable proof of their dogma of cataclysmic anthropogenic climate change armageddon! [shakes head sadly]…. ;o)
It’s a nonlinear gift from Tsonis and Girma and Curry et al, equals…. take it.
They were right about everything except the last thing, the regime shift: we weren’t about to get colder; we were about to get hotter:
and just in time for Trump the Idot.
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-1=e^iπ,
it appears that it makes the mistake of neglecting the impact of the distribution of radiative forcing… As a result, the methodology used will give an overestimation of climate sensitivity.
Different forcing efficacy is a likely issue though I see no reason to assume this aspect means an overestimation rather than underestimation of climate sensitivity.
They also completely ignore vegetation changes as a source of forcing
It’s a grey area in terms of ECS, but I think their 2100 projection should have been informed by a sensitivity estimate incorporating vegetation as a forcing. They do give a forcing estimate of -1.1W/m-2 so you can work out roughly the difference it would make – ~ 15% lower sensitivity I think.
Also, they don’t take Milankovitch forcing into account (which overall is small, but regionally is quite large, especially Obliquity changes).
They are taken into account – marked ‘Orbital’.
Also, as I think I mentioned earlier, the temperature changes are larger than what is suggested by Annan and Hargreaves.
Yes, though that doesn’t mean their estimate has to be wrong and Annan and Hargreaves right.
Table S3 provides a little sensitivity test looking at alternative reconstruction scalings, including one to match AH2012 and another smaller LGM-PI estimate. It suggests that the stated Swarm uncertainty range based on their own reconstructions is too small and towards the high end. Also taking into account vegetation forcing I would suggest a warm-phase ECS range of about 2-6K and TCRP of 1.5-3.5K. Still shifted a bit higher than is typical, but not revolutionary.
JCH,
I don’t think it is crazy to think 2017 could end a top 5 warmest year, maybe even top 3.
I would expect a typical post-large El Nino drop of about 0.1-0.25ºC in the annual average. That would likely put it warmer than 2014, so 3rd warmest.
I’ll be very surprised if it doesn’t make top 5. Assuming a 2016 average of 0.98C that would require the largest inter-annual drop on record by a clear distance.
(Note: all based on GISS)
PaulS – over at Uli, who has been predicting GMST with his model, now has 2017 at .88 ℃ (GISS; would 2nd warmest year.)
This what I was thinking last February:
JCHFebruary 15, 2016 at 10:59 AM
To me the biggest potential difference is where the PDO is now versus then. In 1998 the positive phase of the PDO had been in decline for a long time, whereas the current PDO could be in the initial stages of a positive phase. It’s jumped up in January. If the PDO index goes up and stays up throughout 2016, then 2016 could actually produce a very high anomaly. If the PDO cascades downward, which it did in 1998, then 2016 is going to have a harder time knocking off 2015.
Right now there is a bloom of cold water in the November North Pacific, but how that will affect the November PDO is up in the air. It could drop into negative numbers, but maybe not as coastal upwelling has subsided a bit… seems to be a part of the index calculation as that is where the PDO lives:
Also, the ENSO forecast shows ONI drifting into positive neutral in spring 2017. That could send the GMST higher, making an El Niño lite in 2017… not implausible.
And then there is this… staying stubbornly above the trend:
Click to access sl_ns_global.pdf
@ Paulskio –
“Different forcing efficacy is a likely issue though I see no reason to assume this aspect means an overestimation rather than underestimation of climate sensitivity. ”
This follows from the Stefan-Boltzman law and the fact that the Earth is not a sphere of uniform temperature. In equilibrium, outgoing radiation must equal incoming radiation. Due to the Stefan-Boltzman law, the marginal increase in outgoing radiation per degree of temperature is smaller at lower temperatures, thus an increase in forcing in a low temperature region of the planet will result in a larger increase in temperature than an equivalent increase in forcing in a high temperature region.
“Yes, though that doesn’t mean their estimate has to be wrong and Annan and Hargreaves right. ”
Annan and Hargreaves use a far more spatially complete data set and they are far more rigorous in their methodology to estimate LGM-Holocene temperature changes.
-1,
Yes, but it goes as
, so if you consider two states in which the difference in temperature is 5K (say 283K and 288K) then the ratio is 0.95 (i.e., assuming dT = 1).
The increase in NH high latitude insolation is seasonal eyepie. Not annual. *And* insolation is antiphased between N and S hemispheres. You overplayed this massively last time & now tedious.
Cue endless rope-a-doping at the end of which ECS best estimate is still ~3C and latest paper estimate prolly a bit on the high side.
Maybe we could just skip it this time and go to the pub?
“The increase in NH high latitude insolation is seasonal eyepie. Not annual. *And* insolation is antiphased between N and S hemispheres. You overplayed this massively last time & now tedious.”
… No, it is called obliquity. You are thinking of precession.
And even with respect to precession, if one takes albedo changes in high latitudes due to events like snow cover then there actually is an annual change in forcing.
“Cue endless rope-a-doping at the end of which ECS best estimate is still ~3C and latest paper estimate prolly a bit on the high side. ”
Nah. It seems like the best evidence is converging to a new consensus with best estimate around 2.3C. Gavin Schmidt has also hinted at this “That suggests ECS of 3.7*(4±0.4)/(7.6±0.9)/0.85 ~= 2.3±0.4 (±1 sigma) or a 95% CI of [1.7,3.2]ºC.”.
http://www.realclimate.org/index.php/archives/2016/09/the-snyder-sensitivity-situation/?wpmp_tp=1
Something unusual happening with temperatures at the DMI Daily Arctic mean temperatures north of 80N. Way above normal for this time of year and prolonged.
Either DMI has some more serious explaining to do or something weird is happening to the climate.I certainly hope the former.
Has some slight relevance to above comments re heat loss in the Arctic perhaps.
JCH says the latter..
We should see very soon, very hard to imagine PIOMAS anomaly increasing in such conditions.
.
Angech,
it is real: GISS
and the ice is following suit:
http://nsidc.org/arcticseaicenews/
Indeed, it’s generally termed “climate change”, or alternatively “Global Warming”. Often prefixed by “Anthropogenic” as it’s driven by human activity.
The UN set up a body to report on it, known as the IPCC. It concludes:
Click to access AR5_SYR_FINAL_SPM.pdf
It’s almost as if angech just hasn’t been concentrating.
-1
Obliquity-forced insolation changes are symmetric but antiphased in the northern and southern hemispheres. Feel free to check for yourself. And peak high latitude insolation is only JJA, as stated, not annual. Nobody’s buying, -1.
A serious misrepresentation. No such convergence towards a ‘consensus’ exists outside your imagination. Here’s the bit of Gavin’s response to Nic that you were careful to cut out of your quote:
Please don’t do that again, -1. It looks bad.
Wow BBD, nice bait and switch tactic.
You went from “The increase in NH high latitude insolation is seasonal eyepie” to Obliquity-forced insolation changes are symmetric but antiphased in the northern and southern hemispheres.
High latitude is not the same thing as the entire hemisphere overall.
Look it isn’t rocket science that increasing obliquity increases annual insolation for high latitude regions. If obliquity is zero, you get zero insolation at the north pole. If it is non-zero you get non-zero insolation.
But I guess you want to argue against basic physics.
“A serious misrepresentation. No such convergence towards a ‘consensus’ exists outside your imagination.”
I will also point out that 2.3 C corresponds to the climate sensitivity of models Schmidt works on such as GISS-E2-R, as well as corresponds well with the results from Marvel et al. But if I am misrepresenting Schmidt I apologize. Either way, things do seem to be converging towards a new lower value of climate sensitivity. We have that the best paleoclimate results, best interpretation of instrumental data and best climate models are converging to ECS ~2.3 C.
Non-linear climate sensitivity was covered in a recent review article. One of the authors discusses the Friedrich et. al. paper in a blog article (links below). My reading is that there is increasing evidence that climate sensitivity is state dependent but there is too much uncertainty to make firm predictions about the future based on paleo alone. Quoting the blog –
“However, my feeling is that, given the current uncertainties in determining climate sensitivity in the past, rather than indicating the Earth system is more sensitive than the future, studies like that of Friedrich et al. (2016) and our own (http://www.nature.com/nature/journal/v518/n7537/full/nature14145.html) are very important validators of our understanding of the behavior of the climate system encapsulated by the CMIP5 models. These are very different ways to understand the climate system yet they give the same results – this is very powerful and is a great illustration of the utility of paleoclimate research.”
http://link.springer.com/article/10.1007/s40641-016-0049-3
http://www.thefosterlab.org/blog/2016/11/12/future-relevant-climate-sensitivity-part-deux
I don’t think that it means that it is suddenly a better number than others. I don’t really think we’re in a position to suggest that we’re converging towards a range small enough that we can regard a single number of a reasonable representation of the likely ECS.
thanks for that picture VTG
minus guy
“best” and “my preferred” are not synonyms. Cherrypicking is unimaginative. Try harder.
“as well as corresponds well with the results from Marvel et al. ”
Errr….no.
The whole idea from Marvel et al is that the forcings aren’t identical in their effect on ECS. And so, the results are (going from E=1 to E (iRF -instantaneous) to E (ERF -effective))
Using forcings from… Shindell (2014)
ECS (ºC) 2.1 (1.7-2.7) 3.2 (2.3-5.1) 3.3 (2.4-5.2)
Lewis & Curry (2014)
ECS 1.5 (1.2-2.2) 1.7 (1.2-3.2) 2.1 (1.5-3.6)
Otto et al (2013)
ECS 2.0 (1.4-3.2) 2.5 (1.3-5.6) 3.0 (1.8-6.2)
:sigh:
In the summer. Not all year round.
You keep talking about a net global change in forcing. Which bit of ‘hemispheric antiphase’ don’t you understand?
Still a false claim, so why repeat it? You and Nic with your ‘best’ results. You are like peas in a pod.
correction:
Peak values are In the summer. Not all year round.
Your argument implies that insolation at high (NH) latitude is significantly elevated all year. You ignore the seasonality. And you ignore the SH antiphase in insolation. When you average out the global year, your argument fails.
“I don’t think that it means that it is suddenly a better number than others. I don’t really think we’re in a position to suggest that we’re converging towards a range small enough that we can regard a single number of a reasonable representation of the likely ECS.”
Obviously there is a fair certainty range around the best estimate. I did not mean to imply otherwise.
“You keep talking about a net global change in forcing.”
No, I was referring to the distribution of radiative forcing. A more poleward distribution of forcing generally results in a larger change in global temperature. That’s why you responded by referring to ‘high latitude’. Perhaps you don’t want to admit that you were wrong so wish to pretend distribution of radiative forcing was not discussed?
“Your argument implies that insolation at high (NH) latitude is significantly elevated all year. You ignore the seasonality. And you ignore the SH antiphase in insolation. When you average out the global year, your argument fails.”
Sigh, I can’t believe there is such denial of basic physics. BBD, if you increase obliquity, does mean annual insolation at the north pole increase or decrease. Simple question.
Not as much as you imply / require to make your argument work. What does the hemispheric antiphase mean in terms of the global distribution of RF? You are acting as if there is only the N pole and it is always summer there. That is what I am trying to get you to acknowledge.
Not a lot here, but an article with quotes from two of the authors of the paper.
“Not as much as you imply / require to make your argument work.”
Yes, cause changing local insolation by like 15 W/m^2 couldn’t possibly have a significant impact on global temperatures….
It’s not like The Earth’s surface has a heat capacity or anything.
To quote Max Planck
“A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.”
Perhaps this is true with respect to the people that insist on eternally clinging to the best estimate of 3C despite increasing evidence to the contrary.
I don’t really think that it ending up being 2.3 rather than 3 is the kind of new scientific truth that Planck was referring to.
I said ~2.3. Maybe it’s 2.2, or 2.6 or 1.9. I don’t know. Probably a bit above 2 C, but a fair bit lower than the 3 C ‘consensus’ that died after AR5.
Yeah, obviously Planck wasn’t referring specifically to climate sensitivity. He was referring to the general tendency of entrenched scientists / people to not adopt new ideas, sometimes in spite of overwhelming evidence.
Now you’re just making stuff up. Do better, or go back to CE.
The possibility of the best estimate being around 2.3C, rather than 3C, given a range of 1.5 – 4.5C is probably not the kind of thing Planck was referring to.
“Now you’re just making stuff up.”
Best estimate of ECS in AR4 was 3 C.
In AR5, there was no best estimate.
What exactly am I making up?
“Something unusual happening with temperatures at the DMI Daily Arctic mean temperatures north of 80N. Way above normal for this time of year and prolonged.
or something weird is happening to the climate.”
verytallguy says: November 17, 2016 at 10:00 am
Angech, it is real:
Indeed, it’s generally termed “climate change”, or alternatively “Global Warming”. Often prefixed by “Anthropogenic” as it’s driven by human activity.
De Witt gave me an alternate explanation
“It’s the current La Nina Modoki that’s putting warm air over the Arctic and apparently the Antarctic as well. Antarctic ice extent started dropping into record low territory in September, which was also about the time that the La Nina Modoki started.http://journals.ametsoc.org/do…..12-00055.1″
So if this is right are you saying AGW causes La Nina’s?
“So if this is right are you saying AGW causes La Nina’s?”
No.
@-angtech
“It’s the current La Nina Modoki that’s putting warm air over the Arctic and apparently the Antarctic as well.”
Citation needed for past occasions when this process has caused such high temperatures.
Oh come on, the lack of a best estimate doesn’t suddenly mean that your claim that a consensus of 3C has died is correct. I’m not even really sure what you mean by a “consensus of 3C”. It’s certainly true that there was no best estimate in AR5, but that was – apparently – because the different methods didn’t seem to be able to be combined in a way that could sensibly produce a best estimate. It may mean that it is now more likely below 3C than it was before. On the other hand, there are reasons to be cautious about those methods that produce lower estimates and there have been recent papers suggesting that it is more likely above 3C, than below. Your certainty in your views is a reason why I find it difficult to take much of what you say seriously.
“I said ~2.3. Maybe it’s 2.2, or 2.6 or 1.9. I don’t know. Probably a bit above 2 C, but a fair bit lower than the 3 C ‘consensus’ that died after AR5.”
I showed you the data from Marvel et al, which *you* even dared to cited in support, but which actually gives an ECS closer to 3 (even above with Shindell’s forcing estimates). And so we are back at ECS = 3…
“because the different methods didn’t seem to be able to be combined in a way that could sensibly produce a best estimate.”
Yes. Thus the old consensus of a best estimate of 3C died.
“Your certainty in your views is a reason why I find it difficult to take much of what you say seriously.”
The discrepancy for why the different methods get different results can, for the most part, be explained. And when you take into account various corrections and quantify them, I think this discrepancy disappears.
“I showed you the data from Marvel et al, which *you* even dared to cited in support, but which actually gives an ECS closer to 3 (even above with Shindell’s forcing estimates). And so we are back at ECS = 3…”
Not sure why you would favour Shindell’s forcing estimates.
Aerosol forcing have likely been overestimated, which Bjorn Stevens has argued very effectively. If you take the Marvel et al. results and combine them with Bjorn Stevens results, and use updated forcing data, you end up with a moderate ECS slightly above 2 C.
This doesn’t mean that you then get to choose a new one! The point was that they couldn’t really produce a sensible best estimate, not that they had evidence that the previous one was now wrong.
Yes, I think it takes us back towards a best estimate of 3C. However, since I don’t really think that we should narrow the range without good reason, I’m sticking with a range of around 1.5 – 4.5C, although I do think that there are valid arguments for putting it more in the 2 – 3.5C range.
One of the things that is puzzling about the transcendental/imaginary/irrational poster is the reason for such a persistent campaign to reduce ECS from 3 to 2.5
I wonder what practical difference this makes to the impact of AGW. It seems unlikely that it converts a severe and damaging potential change into a benign and minor event.
Lower climate sensitivity does not mean that less energy has entered the system, just that it is dissipated in ways other than a temperature rise. Assuming that such dissipation will be less harmful than a temperature rise may be an error.
izen,
Indeed, plus – as far as I’m aware – there are very few (if any) estimates that rule out ECS > 3C with high confidence.
minus guy
the best* energy balance model estimate of climate sensitivity (ECS) is actually 4.6 C
http://variable-variability.blogspot.co.uk/2016/07/climate-sensitivity-energy-balance-models.html
*I use the same definiton of best here that you do. Obviously that’s different to the dictionaty definition
“Not sure why you would favour Shindell’s forcing estimates.”
So, how about the Otto et al estimates? With those you get ECS = 3
“If you take the Marvel et al. results and combine them with Bjorn Stevens results, and use updated forcing data, you end up with a moderate ECS slightly above 2 C.”
Followed by a “data and calculations not shown”…Typical.
Also quite fun to see the demand we should not favour Shindell’s forcing estimates, but Stevens paper, well, that just is the ultimate and sole thing you need for aerosol forcing.
Here’s Gavin Schmidt on the matter (this is why I pointed out that -1 seriously misrepresented him above):
Earlier this year an informal poll of climate experts supported 3C. I wouldn’t be surprised to see the lower end of the IPCC range raised at the next update, given the limitations with the energy balance method that have been flagged recently, continuing paleo and modeling studies that support 3C or higher, and the recent temperature spike which is inconsistent with low TCR/ECS.
http://www.bitsofscience.org/real-global-temperature-trend-climate-sensitivity-leading-climate-experts-7106/
angech,
Where is a La-Nina-Modoki? And what? La-Nina-Modoki is the reserve of El-Nino-Modoki which would cause strong warming on the atlantic side of arctic (the EOF-Pattern say so). So if there would be a La-Nina-Modoki, it would cool atlantic arctic, not warm it. Beside this we have a very weak La-Nina-Modoki: http://www.jamstec.go.jp/frcgc/research/d1/iod/sintex_f1_forecast_s.html.en?param=7&
So back in Nov. 2010, we had a stronger La-Nina-Modoki, in Oktober nor in November 2010, it was not warm as it is now. And you know what, the atlantic side was cool back in November 2010, like the response would be expect from La-Nina Modoki, while 2016 is warmist on atlantic side: http://www.karstenhaustein.com/reanalysis/gfs0p5/ANOM2m_arctic/ANOM2m_pastMTH_arctic.html but with a hell of huge values, 6.3K above the 1981-2010 average.
So what is really happen? Simply arctic amplification, not only by less ice, also by a much warmer water arround the ice edge. So and this aplifier the effects of the weather, which is not extraordinary (happens also before 2016) but is amplified by the arctic itself
There is also this notion running around blags that all of “heat” that has accumulated over the last few years has now migrated to the Arctic, where it will be vented to outer space… wacko.
There is a paper that states the stratification of the Arctic atmosphere actually acts a lid that retains heat.
Suddenly there is a chimney to space and Mary Poppins is going open the flue.
To bolster their claim they are frantically pointing to the current formation of ice on Greenland, and that land surface have cooled rapidly in the last several weeks. So once this extra Arctic energy is vented, the rest of the earth will already be cold and global cooling will have taken place and the hoax magically revealed.
The fundamental problem with the sensitivity argument is that the term is misused. Originally it applied to the response of different climate models to the same forcing, in other words in a system that was controlled.
In the real world, however, the forcing is not controlled, and the feedbacks at different times change depending on the state of the cryosphere, clouds, carbon reservoirs and ocean circulation. I believe the range we observe for sensitivity depends on this state dependence. From looking at the past we can determine that there will be a large response to current forcing, but I doubt that additional estimates of sensitivity will converge on one number.
“One of the things that is puzzling about the transcendental/imaginary/irrational poster is the reason for such a persistent campaign to reduce ECS from 3 to 2.5
I wonder what practical difference this makes to the impact of AGW.”
It affects the optimal rate at which to tax CO2 emissions, so it is quite relevant.
“Followed by a “data and calculations not shown”…Typical.”
Go see the Kyle Armor thread’s comment sections for ATTP’s blog. There are numbers there.
@ BBD – With respect to Gavin Schmidt’s blog post, while he is right that forcing efficiency results in energy balance methods underestimating climate sensitivity for the instrumental period he is wrong to think that this some how doesn’t affect paleoclimate estimates (Although perhaps Mr. Schmidt has changed his position). Basically all paleoclimate estimates deal with changes in forcing where the distribution is far more polewardly distributed. This means that, due to the basic physics of the Stefan-Boltzmann law, that these estimates will over estimate climate sensitivity. I’ve been saying this for a long time, before Marvel et al.
-1,
I think you need some kind of citation for this. I understand what you’re suggesting, but I have no idea if what you’re saying is correct, or – even more – if something this obvious is being ignored by those who work in the field.
What ATTP said, really. Either back it up or submit it for publication.
Moreover, the data that we have on extreme climates [for example, the
Eocene warmth and Proterozoic “snowball Earth”] suggest that the climate system
may have been acutely sensitive to radiative forcing during some intervals of Earth’s history. Our results imply that dramatic changes in physical processes are not necessary for dramatic changes in climate sensitivity, provided that those changes in processes can all align in the same direction toward increased sensitivity. These are events of low but not zero probability. – Roe 08
“Go see the Kyle Armor thread’s comment sections for ATTP’s blog. There are numbers there.”
Indeed. Lots of numbers even. Your numbers were all over the place. Most of those you mentioned were well above 2.5.
@-1
“Basically all paleoclimate estimates deal with changes in forcing where the distribution is far more polewardly distributed.This means that, due to the basic physics of the Stefan-Boltzmann law, that these estimates will over estimate climate sensitivity.”
The basic physics of the Stefan-Boltzmann law is that radiated energy is proportional to T^4.
This means that raising the temperature at the equator which is hotter than the poles will cause more energy to be released than a similar change in temperature at the colder poles.
A 2 degree rise at a latitude that is ten degrees warmer than the poles will emit around 10% more energy than a 2 degree rise in the cooler region.
Warming the poles is less effective in raising the amount of energy emitted than warming the equator.
Is this the reason you claim a polewardly distributed forcing gives a larger ECS estimate, because to balance the same amount of energy flow at the pole requires a larger temperature change than it would if that energy flow was at the equator?
-1 sez:
Dr Schmidt seems consistent on this point. From Chubbs’ interesting link above:
Ha! You say; 2.5C! But it makes no real difference to impacts or to optimal tax policy. It doesn’t change anything.
I agree with izen. It’s very difficult to see what you imagine you are achieving here, unless it is simply to insert contrarian memes into the conversation as a basis for making the contentious claim that a small difference in ECS is policy-relevant.
unfortunately, the time-rate-change of forcing in our current modern expansion into unprecedented warming (not seen in at least the last 4 million years) will produce additional climate response mechanisms that will certainly increase ECS. For example, the slow rate of sea surface temperature adjustment to radiative forcing means that land and air temperatures will have to compensate to reach equilibrium, warming more than during the paleoclimate (warm) analogs. This will lead to increased atmospheric circulation changes. Which in turn lead to greater differences in cloud cover regimes (as we have already witnessed in the last 30 years) This effect in and of itself is a significant departure from the IPCC ECS estimate and leads us well into the ‘fat tail’ of > 4.5 K/2XCO2 values. If one includes the near term earth system response of arctic albedo, decreased production of dimethyl sulfite (a consequence of ocean acidification) and the increase in plankton in the arctic (further reducing albedo) we are very likely approaching 6.0C for 2XCO2. Note that this does not include the additional carbon cycle feedbacks associated with rapid regional disassociation of permafrost and the dessication of the tropical peat/rainforests of south america, africa and indonesia.
At this point only a WW II scale total societal mobilization of rapid decarbonization in all sectors (food production, transportation, industrial and electric power generation) will prevent warming > 3.0C by 2050.
@ izen – yes, that is exactly correct.
@ BBD –
“Ha! You say; 2.5C! But it makes no real difference to impacts or to optimal tax policy. It doesn’t change anything. ”
No, it lowers the net optimal tax slightly.
Except the range of estimates (as far as I can tell) is so wide that it’s hard to see how this would really make much difference; or, more correctly, if the range goes from $10 per MtCO2 to $200 per MtCO2 (I don’t know if this is the actual range, but I think the estimates do vary from 10s to low hundreds) are we really going to spend time arguing about a 20% reduction?
As I said way back, just another -1 rope-a-dope designed to insert the ‘consensus is wrong’ and ‘sensitivity is lower that we were told’ memes into the conversation.
Gah.
Ackerman and Stanton in 2013 did an IAM true-up and found values of $900 to $1,300 and that value results from the use of a 3% multi-generational discount mechanism that reduces the value of a human life by 80% over the next 50 years. It should be noted that this analysis was done based on AR4 results, more recent data (ECS, SLR projections) show much greater damage-loss functions associated with RCP 8.5 BAU emissions.
“are we really going to spend time arguing about a 20% reduction?”
Actually it is more than a 20% reduction. Because once you take out the effects proportional to climate sensitivity you are basically left with the CO2 fertilization effect and ocean acidification, which overall is a net benefit of increasing atmospheric CO2. But yes, every small amount matters. Also, I suggest that it makes sense to use an expected social welfare maximization approach to determine the best level of taxation given all known sources of uncertainty.
@ Jai, do you have a link? Was this a more traditional cost-benefit approach or did it have a social welfare function? Also, with respect to RCP 8.5, RCP 8.5 is not a representative business as usual scenario.
-1,
You’re missing my point. If the SCC goes from $10 to $200, then that would suggest that we don’t have confidence about what it should be – it is essentially somewhere between ~$10 and ~>$100. A change of 20%, or so, still leaves it as being between ~$10 and ~>$100. If we’re extremely confident that the change is correct, then it should fed through, but I suspect that others are not quite as confident as you seem to be.
Only if you’re confident that these small amounts are correct. I know you are, but you seem to think that you don’t need to doubt your own estimates, while doubting everyone else’s. If it really was as easy and simple as you continually indicate, I’m pretty sure that others would have made the same arguments. That there seems little agreement that it is might suggest that your confidence in what you’re suggesting isn’t necessarily warranted.
” If the SCC goes from $10 to $200, then that would suggest that we don’t have confidence about what it should be”
This is like arguing that if there is a 5% chance of someone’s house burning down, we don’t have confidence if it will burn down so we cannot decide upon the correct insurance premium. So therefore, we should never have fire insurance.
I think it is possible to take a risk averse approach where one determines the tax that maximizes expected social welfare given the entire probability distribution. Any change to the probability distribution will therefore generally result in a change for the optimal level of taxation.
-1,
No, it’s not like arguing that. I’m simply suggesting that if the range is extremely large (~10 to > 100) then arguing about ~10% changes is probably not very informative as the range would still be ~10 to >100.
-1,
The other point is that you can of course do your calculation to produce a new estimate for the SCC, but all the others will still exist.
“-1,
The other point is that you can of course do your calculation to produce a new estimate for the SCC, but all the others will still exist.”
You are still ignoring the idea of taking an expected social welfare approach to get a single tax. Not taking the expectation obviously leaves you with multiple optimal levels of taxation given imperfect information.
I’m not really ignoring it. I’m suggesting that you don’t really get to impose your views. I think I may have suggested this before, but given your confidence in your calculations, I really think you should aim to publish something.
In the context of discussing the effect of a downward shift in the probability distribution of climate sensitivity on the expected social welfare maximizing level of taxation of CO2 emissions, given a damage function that suggests that the marginal effect of increasing global temperature is negative, the result that the downward shift lowers the optimal level of taxation follows deductively. Going on about ‘confidence in my calculations’, seems like a way to avoid acknowledging this by using a red herring.
Publish it!
Publish what exactly? That a downward shift in climate sensitivity lowers the optimal level of taxation? That is known. That the Stefan-Boltzmann law suggests that a more poleward distribution of radiative forcing causes a larger temperature change? That is also known. Should I publish that the sky is blue as well?
That is essentially the point. The downward shift in climate sensitivity is not accepted by all, or even by a majority. If you think there is a strong argument for doing so (and you think you can make it, which you seem to) then publish it. Getting frustrated on blogs is not particularly constructive; for me or you.
-1=e^iπ,
Read Yoshimori et al. 2009. Figure 3 shows feedback strengths for LGM-all and LGM-ghg (CO2, CH4, N2O) simulations, finding that the high-latitude biased LGM-all simulation actually has weaker total feedback than LGM-ghg.
No it isn’t. Get in into a journal then you can make stronger claims. Not until.
@ ATTP –
So let’s say I make the following 2 claims.
Recent evidence suggests that climate sensitivity is lower than previously thought.
A lower climate sensitivity generally results in a lower optimal level of taxation of CO2 emissions.
Even if you disagree with the first statement, do you at least agree with the second?
@ BBD-
“No it isn’t.”
Well I guess there are still Stefan-Boltzmann law deniers, just like there are climate change deniers.
-1,
Yes, the second seems pretty obvious but has little value unless you can really demonstrate the first. I also add that as an astronomer, if someone tells me that multiple different calculations have estimated something to be between 10 and 200, and then they come back and tell me that they think it’s actually between 7.5 and 150, I’m still going to think it’s roughly between 10 and 200 (or, probably, that it’s between 10 and a few hundred).
@ paulskio –
Interesting. From the paper
“The difference in the climate sensitivity and total feedback strength among experiments is attributed primarily to the shortwave cloud feedback, in which there is a tendency for the shortwave cloud feedback to become weaker or even negative with stronger coolin”
The finding of lower sensitivity for more poleward distributions seems to be due to the more poleward distributions having lower total net forcing, not because the earth is inherently less sensitive to more poleward distributions of forcings.
Increased boreal summer forcing is offset by decreased austral winter forcing. You have to show that your claimed effect is climatologically significant to the extent that it results in an over-estimation of sensitivity and you have not done that.
Stop posturing and get it published or stop asserting that you have an argument. At present, you don’t and I’m surprised that such a smart chap as you perceive yourself to to be can’t see that.
Nope. We’re back to Marvel et al.
“You have to show that your claimed effect is climatologically significant to the extent that it results in an over-estimation of sensitivity and you have not done that.”
I guess maybe add obliquity-effects denier.
“We’re back to Marvel et al.”
Speaking of Marvel et al.
Equilibrium Effective RF Efficiency
0.22 for solar forcing
0.85 for GHG forcing
Which of the 2 has a more poleward distribution of forcing? Solar or GHG? Solar.
Which has 4x the forcing efficiency? GHG forcing.
[Mod: If you can write that in a less condescending way, you can try again. If you can’t, probably best if you didn’t bother.]
-1=e^iπ,
There’s also Yoshimori et al. 2011, which includes an LGMice simulation – only ice sheet change included, which is about the same size global average forcing as LGMghg. The key figures are 4 and 5: global average temperature change is more than twice as large in LGMghg as LGMice.
While the Planck feedback is slightly weaker in the LGMice experiment, total net feedback difference is dominated by SW cloud feedback.
-1=e^iπ,
Regarding your comment at November 26, 2016 at 10:54 pm
“Because once you take out the effects proportional to climate sensitivity you are basically left with the CO2 fertilization effect and ocean acidification, which overall is a net benefit of increasing atmospheric CO2.”
How is ocean acidification an overall net benefit of increasing atmospheric CO2?
@ Paul Skio – Interesting. Thanks for the link. Is this a feature only of high climate sensitivity models?
@ BBD – Total annual irradiance at the poles is proportional to the sine of obliquity, so I’m not sure why you insist obliquity doesn’t affect local annual insolation.
giovannidaprocida,
I was going to ask the same question, but I was concerned that I might hurt my head when it hit the desk.
@ATTP
I have a helmet handy.
“How is ocean acidification an overall net benefit of increasing atmospheric CO2?”
Sorry, maybe I wasn’t clear. I meant ocean acidification + CO2 fertilization effect is overall positive. CO2 fertilization is like a 5, 10 dollar net benefit per metric ton, where as ocean acidification typically is on the order of magnitude of a few cents per metric ton. So I meant that CO2 fertilization effects dominate ocean acidification benefits, not that ocean acidification is a net positive.
-1, references for those numbers, please!
-1
But I *didn’t* say this at all. Here’s a repeat:
Increased boreal summer forcing is offset by decreased austral winter forcing. You have to show that your claimed [net] effect is climatologically significant to the extent that it results in an over-estimation of sensitivity and you have not done that.
Remember at the outset when I reminded you that the effect of obliquity is seasonally and symmetrically antiphased between the hemispheres? (And you denied it, incorrectly, of course). I don’t think the net global effect of peak summer solar forcing at high N latitude is as large as you do because this is a game of two hemispheres.
Why not just stop the blog bloviating and get that paper written?
As I understand -1’s point it is that you can approximate the Planck response as
For
this gets smaller with decreasing 
. Therefore, for a given change in local forcing, the temperature response has to be larger for regions with lower temperatures. However, I would expect that in any GCM, this effect is included. In any energy balance estimate, it is essentially included because the numbers are global averages. The questions is whether or not, this is an effect that is somehow ignored in some circumstances, and the significance of ignoring it. I do not know the answer to that.
But I’m willing to bet the palaeoclimate community does and that’s why I think it’s time for -1 to try and get his claims published.
But we both know he won’t, don’t we? Because this isn’t about the intricacies of orbitally-forced deglaciation, it’s about tax.
Sometimes the disingenuity pisses me off a bit.
On the significance of temperature change being larger in some places than others.
We discussed this here last year.
It’s easily demonstrated to be a very small effect on a global scale, at least insofar as due to the planck response.
vtg,
Thanks. I just worked out that a 30K difference in average temperature is about a 25% effect.
-1=e^iπ,
Is this a feature only of high climate sensitivity models?
I suspect there would be a degree of correlation between 2xCO2 sensitivity and relative LGMghg/LGMice sensitivity. There aren’t many LGMice simulations around though.
The point is that your assumed bias, relating to high-latitude skew of forcing and Planck response, appears to be overly-simplistic, and other feedback factors can easily dominate.
@ Marco – “-1, references for those numbers, please!”
I can’t exactly be expected to do an entire literature review here, can I?
How about some back of the envelope calculations and references?
For CO2 fertilization, let’s just take the results of Hatfield 2011, which are summarized here: http://www.globalwarming-sowhat.com/food-impacts-/. If we go from 400 to 440 ppm, yield of C3 plants increases by ~4% and the yield of C4 plants increases by 1%.
If we look at the world’s top 10 staples (https://en.wikipedia.org/wiki/Staple_food) only 2 of them are C4 plants (corn and sorghum), the rest are C3 plants. In terms of total yields by metric tones, C4 plants make up 27.2% of yields, and C3 plants make up 72.8%. So the CO2 fertilization effect of going from 400 ppm to 440 ppm increases global yields by approximately 1.816%.
Now apparently agriculture makes up 6% of global GDP (http://www.indexmundi.com/world/gdp_composition_by_sector.html). So this means that the CO2 fertilization effect of going from 400 ppm to 440 ppm would be to increase global GDP by 0.11%. The global GDP in 2014 is approximately $114.2 trillion (https://www.cia.gov/library/publications/the-world-factbook/geos/xx.html). Thus the benefit of going from 400 ppm to 440 ppm is roughly $126 billion per year.
Let’s be generous to those that claim that the CO2 fertilization effect is small and assume that total agricultural GDP does not increase over time (even though it will due to population growth and due to countries getting richer). Using a discount rate of 3% (this corresponds to the real after tax riskless market interest rate), the net present value of the CO2 fertilization effect of increasing atmospheric CO2 from 400 ppm to 440 ppm is $4.2 trillion dollars.
Taking into account that 1 ppm of CO2 corresponds to 2.13 gigatones of CO2, gives a benefit of $13 dollars per metric ton.
As for ocean acidification. One paper that attempts to quantify economic costs is:
Click to access kwp-1710.pdf
Where it says “the total global costs of mollusk losses with income rise are estimated to be 96 billion USD and 124 billion USD ” Let’s take $124 billion, the largest of the values.
There are also some significant benefits from ocean acidification. In particular, fish, seaweed and algae tend to benefit. But let’s ignore that benefit in order to try to get a higher number of net damages (and for simplicity).
Under these higher emission scenarios, average emissions are roughly 20 gigatons of carbon per year. Which gives roughly 1760 gigatons from 2012 to 2100.
If we assume a roughly linear increase in damages from 2012 to 2100, starting at zero, and a discount rate of 0.03 then the net present value of damages is $1.14 trillion. Dividing this by the amount of carbon burned gives ~ 65 cents per ton cost from ocean acidification.
This is all rough back of the envelope stuff, but I’m just trying to demonstrate the order of magnitude difference. And the literature tends to agree that the magnitude of the CO2 fertilization effect is quite a bit higher than the magnitude of ocean acidification.
@ BBD –
“Increased boreal summer forcing is offset by decreased austral winter forcing.”
But not completely, because there is this thing called the length of the day. It tends to vary throughout the year.
@ ATTP
“As I understand -1’s point it is that you can approximate the Planck response as
dF = T^3 dT.”
Exactly. And since average temperature tends to vary from ~230 K in Antarctica to ~300K at the equator, T^3 varies by over a factor of 2. I don’t think that temperature difference is something that should be ignored when, for example, calculating climate sensitivity from Paleoclimate data.
@ Paulskio –
“I suspect there would be a degree of correlation between 2xCO2 sensitivity and relative LGMghg/LGMice sensitivity. There aren’t many LGMice simulations around though.”
Well the model used for Marvel et al. seems to support the hypothesis that more poleward distributions of radiative forcing have higher sensitivity. But cloud feedbacks remain a large source of uncertainty for climate models, so it may be possible that cloud feedback counters the effect such that the distribution of radiative forcing doesn’t matter that much. However, given how high the climate sensitivity of the models used in your cited study are, and how inconsistent the results are from, say, climate sensitivity estimated from instrumental observations, I’m inclined to believe that perhaps the cited models are oversensitive due to getting cloud feedback wrong.
“The point is that your assumed bias, relating to high-latitude skew of forcing and Planck response, appears to be overly-simplistic, and other feedback factors can easily dominate.”
Fair enough. It is overly-simplistic. But models used to calculate climate sensitivity in many paleoclimate studies tend to be even more simplistic. I think that the distribution of radiative forcing should be taken into account at some level.
-1,
Do you know that this is being ignored? You really need to demonstrate that it is and that doing so has a significant impact. There is a rough rule of thumb that is worth considering; if you think that a lot of experts are ignoring something that you regard as obvious and that should be included, you should first consider that either there is a good reason for ignoring it, or that you’re wrong about it being ignored.
In my view, you really should try publishing something. You speak as if you are some kind of expert, but – unless I’m mistaken – your credentials don’t really support such an attitude. You may well be a polymath who can improve estimates of climate sensitivity and the SCC, but there are a number of reasons why there is value in publishing. It forces you to formalise what you’re presenting. You will get a chance to get comments from actual experts. You may well end up substantially changing our understanding and making a positive contribution. On the other hand, you may learn that what you thought was simply, was actually more complicated than it seemed, and that you’ve made some kind of silly mistake. There’s only so much that can be done on blogs.
-1
I didn’t say the offset was total. What I have argued consistently is that the net effect is smaller than you claim because your analysis is simplistic and partial.
I’d be willing to make a not-inconsiderable bet that any attempt to get it past peer-review will vindicate my position and invalidate yours.
Want to play?
“I can’t exactly be expected to do an entire literature review here, can I?”
Yes you can be expected to do so. Don’t just throw numbers around if you don’t have references for that.
Take you simple calculations, where you look at the top-10 staples, and get to your $13 dollar/metric ton, and then for ocean acidification….only look at mollusks ($0.65/metric ton, notably a factor 10 higher than your original claim).
You also claim OA will be good for fish, but that definitely does not fit with the information I can find, e.g.
http://ocean.si.edu/ocean-acidification
Yep, seaweed will be doing fine, possibly even better, unfortunately that then comes at a cost for other flora and fauna in the oceans.
Veron et al. (2009) The coral reef crisis: The critical importance of <350 ppm CO2:
“You also claim OA will be good for fish, but that definitely does not fit with the information I can find”
http://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2010.01518.x/full
If you don’t want to read the whole thing, just see figure 2.
@ BBD – Fish in coral reefs only contains a small fraction of the total biomass of fish on the planet.
I also don’t see any attempt to quantify the negative impacts on fish in terms of $/metric ton of CO2.
Slight mistake in a previous comment. The 65 cents per ton was accidentally given in $/ton of carbon instead of $/ton of CO2. It’s 18 cents per ton of CO2.
~25% of *all* fish species live on reefs. You think you can just remove them without any knock-on effects? Ever heard of ‘food webs’?
I find it astonishing that anyone can even try to argue that a rapid warming and pH shift of the oceans can be net beneficial to marine ecosystems. It’s bordering on lunacy. Go and talk to some marine biologists instead of peddling your nonsense on blogs. Really. Please.
As for your link, here’s the core finding:
And :
Food webs. No fish is an island.
“~25% of *all* fish species live on reefs.”
Species, not biomass.
“I find it astonishing that anyone can even try to argue that a rapid warming and pH shift of the oceans can be net beneficial to marine ecosystems.”
I have never said that. I said that some species benefit, some do not benefit. The net effect appears to be negative. Fish, seaweed, and certain types of algae tend to benefit.
-1,
This is getting a bit much. I’m quite serious when I say “publish it”. It may well be interesting and you could make a positive contribution. On the other hand, maybe you’ll learn that you don’t quite understand this as well as you do. However, I’d probably appreciate if you didn’t continue to promote it here.
“If you don’t want to read the whole thing, just see figure 2.”
Well, no, Figure 2 aggregates the results for calcifiers vs non-calcifiers, not fish specifically. They do mention a “positive” effect on growth for fish. That’s all the data they have. Not survival, for example, and as indicated in more recent work, certain fish expose themselves more to predators under high-CO2 conditions.
I also wonder why you did not point me to the more recent meta-analysis from the same group. Is that perhaps because it states there is *no positive effect* on fish growth (Figure 2)?
http://onlinelibrary.wiley.com/doi/10.1111/gcb.12179/full
Here they also point out the potential problem of changes in behavior due to acidification:
“…it should be noted that a decrease in pH is also likely to have effects that are not captured in the physiological and ecological response variable synthesized here. For example, acidification appears to have neurological effects on fish with repercussions for their behavior…”
“I also wonder why you did not point me to the more recent meta-analysis from the same group.”
Oh, thanks. Didn’t know that there was an updated version. Yeah, I guess there is no statistically significant positive effect.
I repeat: food webs. On which biomass depends. Yet again you ignore or misrepresent what I say. If we start poking holes in marine food chains down near the bottom where the calcifiers live, there will be radiating knock-on effects right up to the top predators. Biomass has to eat to be biomass and this applies to pelagic fish.
-1=e^iπ
Well the model used for Marvel et al. seems to support the hypothesis that more poleward distributions of radiative forcing have higher sensitivity.
I don’t think that’s true. The analysis using Instantaneous Radiative Forcing method (iRF) does indicate enhanced aerosol efficacy, but this is probably mostly because the iRF mode does not capture the full magnitude of forcing due to aerosol-cloud interaction. Capturing aerosol forcing as ERF suggests no difference from CO2 efficacy. The finding of lower efficacy for net historical forcing versus CO2 appears to be mostly related to reduced GHG efficacy (for some reason), very low solar efficacy and low Ozone efficacy (which itself has a poleward distribution skew).
However, given how high the climate sensitivity of the models used in your cited study are, and how inconsistent the results are from, say, climate sensitivity estimated from instrumental observations, I’m inclined to believe that perhaps the cited models are oversensitive due to getting cloud feedback wrong.
The CMIP3 historical runs for that model are available at Climate Explorer. Seem to be very much compatible with historical observations.
The energy balance model instrumental sensitivity estimates you reference do not take into account the spatial forcing issue you raise, as well as a number of other sources of uncertainty relating to non-linearity in forcing-response relationships, and known biases in the observations (biases relative to global average SAT). Once that is done the model sensitivity is comfortably consistent.
@ BBD – “I repeat: food webs. On which biomass depends. Yet again you ignore or misrepresent what I say. If we start poking holes in marine food chains down near the bottom where the calcifiers live”
Sea grass and non-calcifier algae are also near the bottom of the food chain.
“Capturing aerosol forcing as ERF suggests no difference from CO2 efficacy.”
The distribution of aerosol forcing is concentrated primarily in the mid latitudes. So it’s a priori indeterminant if it would have a higher or lower efficiency than GHG efficiency due to this effect. So I’m not sure that the result is unexpected. Where you would expect a significant difference is with the distribution of solar forcing (which is more equatorial concentrated than GHG forcing) and with the distrubtion of long term albedo changes over geological time (which is more poleward concentrated and relevant for paleoclimate estimates).
“The finding of lower efficacy for net historical forcing versus CO2 appears to be mostly related to reduced GHG efficacy (for some reason)”
My (crude) understanding is that Marvel et al. get this to count for the effects of ocean heat uptake efficiency, not because GHG forcing is more efficient than itself.
“The CMIP3 historical runs for that model are available at Climate Explorer. Seem to be very much compatible with historical observations.”
The model in the study has a climate sensitivity of 4 C. Which is high even by climate model standards.
Which is why I said “If we start poking holes in marine food chains down near the bottom where the calcifiers live”
Poking holes is not “wiping out the entire base of the food chain”. Poking holes is enough to start food webs unravelling even if sea grass and algae are okay (in the short-term).
Just read the words. They are clear enough.
Where you would expect a significant difference is with the distribution of solar forcing (which is more equatorial concentrated than GHG forcing)
Maybe a bit, I’m not sure there’s a huge difference. Again, I suspect other feedbacks would dominate the simple hypothesis you propose.
The model in the study has a climate sensitivity of 4 C. Which is high even by climate model standards.
It’s towards the upper end of the range, but I’m not sure what you’re point is. If it fits with observations it fits with observations.