Thanks for following up on it. I had tried looking at climatological comparison maps for 1961-1980 versus 1941-1960 (same dates as used in Zhang et al.) and noticed that other large dust areas (Australia, India, Somalia) were producing a strong decrease in dust load at the same time as the Tropical North Atlantic increase. It made me wonder to what extent natural variability was playing a role, and was meaning to check out the other ensemble members… I don’t have to bother now.

Interesting the Krakatoa reponse seems to be robust, or at least there appears to be a robust increase in dust load lasting between ~1880 and 1900.

just a quick update re HadGEM2-ES. I compared the dust load of the individual members and the ensemble of all 4 runs. In this plot, r1i1p1 vs ensemble is shown for the TNA region and the Barbados region. As expected, they agree very well. What doesn’t agree, however, are the individual ensemble runs (only initial conditions are changed). I plotted all members vs ensemble for the time period past 1960 for Barbados (individual members are smoothed), and it turns out that there is in fact no robust model dust response to external forcing. The ensemble result corresponds with Fig.S6b in Booth SI.

I haven’t checked TOA outgoing SW radiation, but I would expect it to change accordingly. Quite an interesting result.

I hadn’t checked the individual members and the local response. I should have paid much more attention to the dust loading image you’ve shown in the previous post. It makes my previous comment look a bit nonsensical in some way. In fact, the way I thought the bare soil problem acts to inhibit dust emissions works just the other way around. Now I got what you meant when you were referring to “hyperactive with regard to dust”. Plus, I see why you are confused by their discussion of dust. Thanks for following up this matter. Highly appreciated!

Judging by the dust loading in HadGEM2-ES over the TNA, the variability seems fairly high indeed. Doesn’t exactly match the simulated Barbados concentrations (Fig.S6b in SI), though this is what you’d definitely expect to see (as far as my intuition as a dust modeller doesn’t lead me astray). Very strange! Guess I’ve gotta ask Nicolas what is going on here. Perhaps problems with the deposition rate. Good catch Paul. I should have noticed that before. The rational to compare with the Barbados dust is, that it is (1) the longest dust record we’ve got, and (2) that it is indeed considered a very good proxy for the Sahel/Saharan emissions and thus the global dust budget of which the bulk stems from Northern Africa and Middle East. Guess that’s due to continuous dry deposition all the way over the Atlantic.

Hence, a dust-link to the TOA upwelling radiation appears much more likely than previously thought on my part. I totally agree with you. Only the timing is an issue (with regard to Barbados observations). The response to volcanoes in the model seems way over the top. The Pinatubo doesn’t show up in the Barbados record at all, indicative of no effect whatsoever upon dust emissions. Not too surprising, given that it occurred amidst the strongest positive NAO period observed. I wonder what the NAO strength is in the model (haven’t checked). It doesn’t need to be tied to the SSTs.

As far as HadGEM2-AO is concerned, there are three important issues which might explain the discrepancies. (1) The missing tropospheric chemistry affects the conversion rate from SO2 emissions to sulfate aerosols (hence the indirect effect is inevitably affected). (2) The missing ocean biogeochemistry prevents DMS aerosols to be produced interactively. AO uses a DMS climatology instead. (3) The problem with the bare soil fraction leads to excess dust emissions in the ES version (as just discussed), while the AO version tends to underestimate the dust. In any case, the resulting AOD discrepancy is quite large (see Martin et al. 2011). All three points together may explain the apparent mismatch between HadGEM2-ES and AO.

Regarding TNA sulfates, which local SO2 source region are you referring to? Central Africa? Intuitively, I would assume that the dust related DMS fraction is a significant contributor to the total sulfate fraction (apart from the advected fraction from remote sources as Isaac has suggested). The low deposition rate for the local sources (reduced wet deposition I guess) is a fair point however.

I have to say I was somewhat confused by the discussion of dust in both the paper and SI when I tried to relate it to the various model output datasets I had downloaded and was viewing. I even considered they might be looking at a different set of model runs, so I checked the ensemble SST time series and it was an exact match for the one shown in the paper.

I don’t have a good intuition for what would be considered large dust variability, but don’t see how surface dust concentration (I think that’s what it must be) in Barbados could be a reasonable proxy for the total atmospheric dust variability over the Tropical N. Atlantic. The rationale for presenting modelled dust variability in this way isn’t clear when it’s straightforward to plot the modelled dust load over a larger region as I’ve done in the graph linked in the post above. That plot clearly shows the dust load varying, with maxima corresponding to periods of volcanic activity and minima corresponding to volcanic inactivity. I guess it’s possible that this isn’t directly related to a dust emission feedback, but perhaps a feedback which is affecting the deposition rate of dust. Either way there does seem to be significant low frequency atmospheric dust load variability in these model runs.

Regarding the effects of this dust variability, it’s possible the strong correlation between Tropical N. Atlantic (TNA) dust load and TNA upwelling shortwave indicates a tightly-coupled dust feedback/dust-deposition feedback response, with the dust itself being mostly benign, rather than dust dominating upwelling SW flux. However, if that’s the case it leaves me puzzled about why the HadGEM2-AO TOA upwelling SW time series for TNA has such a different shape from HadGEM2-ES, considering the AO version uses the same anthropogenic and volcanic forcing inputs and has the same atmosphere-ocean dynamics. Is there some other biogeochemical feedback which could be driving this?

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Regarding the TNA sulfate load, I had considered the possibility of influence from non-local sources but the shape of the curve doesn’t fit that scenario very well – there is a gradual, linear incline up to 1960, then a rapid increase. If there were significant influences from remote regions I would expect more earlier variability. Modelling the local SO2 sources with a relatively low deposition rate would appear to give a decent fit. It probably is the case that the size of the local sulfate load doesn’t translate linearly to local total forcing, though it’s worth noting that is essentially an assumption built into Booth et al.’s attribution.

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Perhaps oddly, I think CMIP3 models used annually-resolved historical SO2 emissions. The HadGEM1 CMIP3 run shows noticable spikes in NASSTs in the 1930s and 1950s, which correspond well with those large SO2 emission downturns in Smith et al., and similarly-timed spikes in the real NASST datasets.

Not sure what the rationale was for using decadally-resolved emissions data in CMIP5?

HadGEM2-ES got some trouble to get the dust feedback right as it fails to balance the bare soil extent in semi-arid regions properly. Bare soil extent seems to be biased high from the start which makes it less susceptible to further drying. While the model actually captures the drying, the dust feedback is missing (see supplementary material from Booth et al.2012). Hence, regardless of the model scenario, the dust emissions remained fairly constant. I think Isaac got it right that the bulk of the tropical N.Atlantic aerosols in the model isn’t of local origin but advected. In fact, it is highly unlikely that it is dust induced DMS emission as there is barely an increase in simulated dust emissions after all.

Re the Atlantic OHC and the Zhang er al. paper (with you, Isaac, as co-author; apologies for being a bit late to the party):
Given that the HadGEM2 aerosol forcing is running a bit high (I spoke with Nicolas Bellouin about this issue last year), I wonder whether a minimally decreased SO2 forcing could potentially solve the problem in the simulated spatio-temporal OHC pattern? Otherwise, it would be interesting to know how the aerosol effect would play out if the model had a more variable NAO. I spontaneously think of some nudging experiments to push the model more towards the observed state (with regard to the circulation or NAO phase). Mimicking the great salinity anomaly would be another (additional) option. Would you think that any of these measures could have the potential to bring model results and observations in better agreement? If I had to make a bet, I’d say that the better agreement in OHC between the constant forcing run and observations in the current version of HadGEM2 is likely to be right for the wrong reason. No doubt however, that the 80 percent figure for external forcing impact is a bit over the top.

P.S. @Paul: Thanks for hinting to the temporal mismatch between (smoothed) CONUS emissions and the Smith et al. 2011 data. Haven’t exactly noticed that before. I wonder whether the models would reproduce the US dust bowl a bit better given the reduction in SO2 emissions following the great depression. Having said that, the peak in US-SO2 emissions and the rather simultaneous peak in global temperatures (exactly) during WWII never ceases to puzzle me.

As for the volcano-Saharan dust connection — thanks for the links. I’ll have to look into this.

I wasn’t very clear concerning the sulfate loads: There is a notable increase in sulfate over the Extratropical North Atlantic from about 1960 to 1975, which makes sense because of the large increase in North American SO2 emissions at the time. The surprise for me came from observing a similarly-timed sulfate load increase of comparable size over the Tropical North Atlantic despite local SO2 emissions being an order of magnitude smaller than those from North America. It seems that differing modelled deposition rates between the Tropical and ExtraTropical Atlantic can explain this apparent oddity. In both cases, by my crude calculations comparing sulfate load with deposition rate, I’m still talking about a matter of days to weeks for equilibration – about 6 days in ExTrop and 30 in Trop.

(Incidentally, I’m dubious how well the CMIP5 implementation of SO2 emissions could accurately reproduce NASSTs even if they were in reality the entire cause of variability. The problem is that SO2 emissions have been integrated using decadal averages, which smooths over some important variability – for example, this graph plots CMIP5 historical SO2 emissions for CONUS as implemented in HadGEM2-ES against annually-resolved US emissions from Smith et al. 2011. Luckily the period from 1960 matches pretty well.)

The volcano-cooling-dust-cooling feedback loop may be implausible, and I think a couple of papers have noted that HadGEM2-ES tends to be a bit hyperactive with regards dust (e.g. Bellouin et al. 2011). However, it is there in the model: see this comparison of dust load and TOA upwelling shortwave in the Tropical N. Atlantic. The dust load increases in response to volcanic cooling, and seems to be a major factor in the regional shortwave flux. I think another way to appreciate this influence is to look at the difference between regional upwelling shortwave in HadGEM2-ES and HadGEM2-AO, which is functionally the same model, with the same anthropogenic inputs except without biogeochemical feedbacks. I’ve included plots for the less dust-affected Extratropical N. Atlantic region in each to provide some context.

There is also a fairly large increase in modelled sulfate load over the Tropical North Atlantic from about 1960, which is presumably the main cause of modelled present day strong aerosol forcing off the West African coast, as depicted in Booth et al. figure 4b. I thought this might also be partly natural (influence of dust on DMS emissions, perhaps) because local SO2 emissions are comparatively small. However it seems to be the case that modelled aerosol deposition processes in the Tropical North Atlantic are much slower than, say, the Extratropical North Atlantic, by about a factor of 5, which means small SO2 emissions increases can make large cumulative changes to the sulfate load in this region.