Imagine a group of 100 fisherman faced with declining stocks and worried about the sustainability of their resource and their livelihoods. One of them works out that the total sustainable catch is about 20% of what everyone is catching now (with some uncertainty of course) but that if current trends of increasing catches (about 2% a year) continue the resource would be depleted in short order. Faced with that prospect, the fishermen gather to decide what to do. The problem is made more complicated because some groups of fishermen are much more efficient than the others. The top 5 catchers, catch 20% of the fish, and the top 20 catch almost 75% of the fish. Meanwhile the least efficient 50 catch only 10% of the fish and barely subsist. Clearly, fairness demands that the top catchers lead the way in moving towards a more sustainable future.

The top 5 do start discussing how to manage the transition. They realise that the continued growth in catches - driven by improved technology and increasing effort - is not sustainable, and make a plan to reduce their catch by 80% over a number of years. But there is opposition - manufacturers of fishing boats, tackle and fish processing plants are worried that this would imply less sales for them in the short term. Strangely, they don't seem worried that a complete collapse of the fishery would mean no sales at all - preferring to think that the science can't possibly be correct and that everything will be fine. These manufacturers set up a number of organisations to advocate against any decreases in catch sizes - with catchy names like the Fisherfolk for Sound Science, and Friends of Fish. They then hire people who own an Excel spreadsheet program do "science" for them - and why not? They live after all in a free society.

After spending much energy and money on trying to undermine the science - with claims that the pond is much deeper than it looks, that the fish are just hiding, that the records of fish catches were contaminated by being done near a supermarket - the continued declining stocks and smaller and smaller fish make it harder and harder to sound convincing. So, in a switch of tactics so fast it would impress Najinsky, the manufacturers lobby suddenly decides to accept all that science and declares that the 'fish are hiding' crowd are just fringe elements. No, they said, we want to help with this transition, but …. we need to be sure that the plans will make sense. So they ask their spreadsheet-wielding "advocacy scientists" to calculate exactly what would happen if the top 5 (and only the top 5) did cut their catches by 80%, but meanwhile everyone else kept increasing their catch at the current (unsustainable rate). Well, the answers were shocking - the total catch would be initially still be 84% of what it is now and would soon catch up with current levels. In fact, the exact same techniques that were used to project the fishery collapse imply that this would only delay the collapse by a few years! and what would be the point of that?

The fact that the other top fishermen are discussing very similar cuts and that the fisherfolk council was trying to coordinate these actions to minimise the problems that might emerge, are of course ignored and the cry goes out that nothing can be done. In reality of course, the correct lesson to draw is that everything must be done.

In case you think that no-one would be so stupid as to think this kind of analysis has any validity, I would ask that you look up the history of the Newfoundland cod fishery. It is indeed a tragedy.

And the connection to climate? Here.

I'll finish with a quotation attributed to Edmund Burke, one the founders of the original conservative movement:

"Nobody made a greater mistake than he who did nothing because he could do only a little."

See here for a much better picture of what coordinated action could achieve.

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Two recent papers (Lockwood & Frolich, 2008 - 'LF08′; Scafetta & Willson, 2009 - 'SW09′) compare the analysis of total solar irradiance (TSI) and the way the TSI measurements are combined to form a long series consisting of data from several satellite missions. The two papers come to completely opposite conclusions regarding the long term trend. So which one (if either) is right, then? And does it really matter?

This issue is a very familiar one when it comes to long-time series from satellite data. Each individual satellite only lasts a few years, and so a 30 year time series needs to be stitched together from a series of satellites. Each of those instruments might have a different calibration, and may have non-climatic drifts associated with instrument degradation, or orbital effects. Thus it can often be the case that there is a degree of ambiguity in putting together the series. This issue is at least part of the difference between the RSS and UAH tropospheric temperature trends, and in the CERES/ERBE analyses discussed recently.

The differences between PMOD and ACRIM have already been discussed by the SkepticalScientist and Tamino, so here is just an update in the light of the two recent papers. The important issue here is the so-called 'ACRIM-gap', the time between the ACRIM-I instrument ceased and when the ACRIM-II observations started (mid-1989 to late 1991), and how the data from these two instruments are combined using other overlapping observations. Note that the 'ACRIM' name for the Willson et al time-series simply implies that it was put together by some people on the ACRIM science team, not that they use different satellite data.

The focus on these papers is what the 'ACRIM gap' implies for TSI levels during the solar minimum at solar cycles 21 and 22. Whereas PMOD suggests that the TSI levels during these minima are similar, ACRIM suggests that the TSI level is higher during the minimum of cycle 22. SW08 even claim that there has been a positive 'minima trend'.

LF08 conclude that the PMOD is more realistic, since the change in the TSI levels during the solar minima, suggested by ACRIM, is inconsistent with the known relationship between TSI and galactic cosmic rays (GCR). It is well-known that the GCR flux is generally low when the level of solar activity is high, because the solar magnetic fields are more extensive and these shield the solar system against GCR (charged particles). However the two effects don't always go in lockstep, so this is suggestive rather than conclusive.

It is also clear from the instrumental data that the TSI tends to increase with the solar activity level - at least over the solar cycle. LF08 argue that if the ACRIM 'minimum trend' is correct, this will mean that past reconstruction of TSI based on e.g. sunspots are incorrect, and a lot of studies on the past climate variations would be wrong. This does not mean that the ACRIM data are useless, but that there are uncertainties regarding the relationship TSI-levels, solar activity for different time scales.

I found insufficient detailed description in SW09 of the methodology used in their analysis to be able to judge the real merit of their work. The paper provides a link to auxiliary material that does not work. However, the figures in the paper don't really convince when I don't know how they were made.

Furthermore, I found the SW09 a bit confusing, as it gives the impression that the PMOD composite relies on ERBS/ERBE data during the ACRIM-gap (“The PMOD team uses the sparse ERBS/ERBE data base to 'bridge' the ACRIM gap, conforming the higher cadence Nimbus 7/ERB to it by making adjustments due to …”). However the information in LF08 says PMOD used HF from Nimbus 7 (ERB).

The PMOD analysis involves an adjustment to correct for a glitch in the ERB data (orientation changes and/or switching off), but SW09 claims - without providing convincing arguments - that this correction cannot be justified.

The ACRIM composite does not account for a jump in the 'ACRIM-gap' due to instrumental changes. SW09 show a comparison between different analyses and Krivova et al. (2007) modeled TSI, but later acknowledge that the latter modeled TSI disagrees with measurements on decadal time scales. Furthermore, when the TSI is not adjusted over the 'ACRIM-gap', there is the apparent inconsistency between TSI and GCR.

Update: My conclusion is that the LF08 paper is far more convincing than the SW09 in temrs of whether the TSI data should be adjusted over the 'ACRIM-gap'. But the this is probably not the final word on the matter.

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Our favorite contrarian, the potty peer Christopher Monckton has been indulging in a little aristocratic artifice again. Not one to be constrained by mere facts or observable reality, he has launched a sally against Andy Revkin for reporting the shocking news that past industry disinformation campaigns were not sincere explorations of the true uncertainties in climate science.

The letter he has written to the NY Times public editor, with its liberal sprinkling of his usual pomposity, has at its heart the following graph:

Among other issues, it is quite amusing that Monckton apparently thinks that;

• trends from January 2002 are relevant to a complaint about a story discussing a 1995 report,
• someone might be fooled by the cherry-picked January 2002 start date,
• no-one would notice that he has just made up the IPCC projection curves

The last is even more amusing because he was caught out making stuff up on a slightly different figure just a few weeks ago.

To see the extent of this chicanery, one needs only plot the actual IPCC projections against the observations. This can be done a number of ways, firstly, plotting the observational data and the models used by IPCC with a common baseline of 1980-1999 temperatures (as done in the 2007 report) (Note that the model output is for the annual mean, monthly variance would be larger):

These show clearly that 2002-2009 is way too short a period for the trends to be meaningful and that Monckton's estimate of what the IPCC projects for the current period is woefully wrong. Not just wrong, fake.

Even if one assumes that the baseline should be the year 2002 making no allowance for internal variability (which makes no sense whatsoever), you would get the following graph:

- still nothing like Monckton showed. Instead, he appears to have derived his 'projections' by drawing a line from 2002 to a selection of real projections in 2100 and ignoring the fact that the actual projections accelerate as time goes on, and thus strongly over-estimating the projected changes that are expected now (see here).

Lest this be thought a mere aberration or a slip of his quill, it turns out he has previously faked the data on projections of CO₂ as well. This graph is from a recent presentation of his, compared to the actual projections:

How can this be described except as fake?

Apart from this nonsense, is there anything to Monckton's complaint about Revkin's story? Sadly no. Once one cuts out the paranoid hints about dark conspiracies between "prejudiced campaigners", Al Gore and the New York Times editors, the only point he appear to make is that this passage from the scientific advice somehow redeems the industry lobbyists who ignored it:

The scientific basis for the Greenhouse Effect and the potential for a human impact on climate is based on well-established scientific fact, and should not be denied. While, in theory, human activities have the potential to result in net cooling, a concern about 25 years ago, the current balance between greenhouse gas emissions and the emissions of particulates and particulate-formers is such that essentially all of today’s concern is about net warming. However, as will be discussed below, it is still not possible to accurately predict the magnitude (if any), timing or impact of climate change as a result of the increase in greenhouse gas concentrations. Also, because of the complex, possibly chaotic, nature of the climate system, it may never be possible to accurately predict future climate or to estimate the impact of increased greenhouse gas concentrations.

This is a curious claim, since the passage is pretty much mainstream. For instance, in the IPCC Second Assessment Report (1995) (p528):

Complex systems often allow deterministic predictability of some characteristics … yet do not permit skilful forecasts of other phenomena …

or even more clearly in IPCC TAR (2001):

In climate research and modeling, we should recognize that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible. The most we can expect to achieve is the prediction of the probability distribution of the system's future possible states….

Much more central to the point Revkin was making was the deletion of the sections dealing with how weak the standard contrarian arguments were - arguments that GCC publications continued to use for years afterward (and indeed arguments that Monckton is still using) (see this amendment to the original story).

Monckton's ironic piece de resistance though is the fact that he entitled his letter "Deliberate Misrepresentation" - and this is possibly the only true statement in it.

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As imitation is the sincerest form of flattery, we've naturally been delighted that a number of sites have sprung up over the past few years with missions complementary to our own focussing on the science of climate change. Last year, we were introduced to "climate ethics", whose mission it is to focus on the ethical dimensions of climate change. Now there is "RealClimateEconomics", whose aim it is to focus on the economic considerations surrounding climate change. Neither this site nor climateethics.org has any formal relationship with RealClimate, despite the similarity in name. We do nonetheless welcome them to the fray. We are pleased to add them to our blogroll, which we hope has become a useful resource for those wishing to explore the broader discourse on climate change that lies beyond the science.

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There is a climate splash in Nature this week, including a cover showing a tera-tonne weight, presumably meant to be made of carbon (could it be graphite?), dangling by a thread over the planet, and containing two new articles (Allen et al and Meinshausen et al), a "News & Views" piece written by two of us, and a couple commentaries urging us to “prepare to adapt to at least 4° C” and to think about what the worst case scenario (at 1000 ppm CO2) might look like.

At the heart of it are the two papers which calculate the odds of exceeding a predefined threshold of 2°C as a function of CO₂ emissions. Both find that the most directly relevant quantity is the total amount of CO₂ ultimately released, rather than a target atmospheric CO₂ concentration or emission rate. This is an extremely useful result, giving us a clear statement of how our policy goals should be framed. We have a total emission quota; if we keep going now, we will have to cut back more quickly later.

There is uncertainty in the climate sensitivity of the Earth and in the response of the carbon cycle, and the papers are extremely useful in the way that they propagate these uncertainties to the probabilities of different amounts of warming. Just looking at the median model results, many people conclude that a moderately optimistic but not terribly aggressive scenario such as IPCC B1 would avoid 2°C warming relative to pre-industrial. But when you take into account the uncertainty, you find that there is a disturbingly high likelihood (roughly even odds) that it won't.

Both papers come to the same broad conclusion, summarized in our figure, that unless humankind puts on the brakes very quickly and aggressively (i.e. global reductions of 80% by 2050), we face a high probability of driving climate beyond a 2°C threshold taken by both studies as a “danger limit”. Comparing the two papers is obscured by the different units; mass of carbon versus mass of CO₂ (moles, anyone? Is there a chemist in the house?). But chugging through the math, we find the papers to be broadly consistent. Both papers conclude that humankind is already about half-way toward releasing enough carbon to probably reach 2°C, and that most of the fossil fuel carbon (the coal, in particular) will have to remain in the ground.

We feel compelled to note that even a "moderate" warming of 2°C stands a strong chance of provoking drought and storm responses that could challenge civilized society, leading potentially to the conflict and suffering that go with failed states and mass migrations. Global warming of 2°C would leave the Earth warmer than it has been in millions of years, a disruption of climate conditions that have been stable for longer than the history of human agriculture. Given the drought that already afflicts Australia, the crumbling of the sea ice in the Arctic, and the increasing storm damage after only 0.8°C of warming so far, calling 2°C a danger limit seems to us pretty cavalier.

Also, there are dangers to CO₂ emission other than the peak, such as the long tail of the CO₂ perturbation which will dominate the ultimate sea level response, and the acidification of the ocean. A building may be safe from earthquakes but if it is susceptible to fires it is still considered unsafe.

The sorts of emission cuts that are required are technologically feasible, if we were to build wind farms instead of coal plants, an integrated regional or global electrical power grid, and undertake a crash program in energy efficiency. But getting everybody to agree to this is the discouraging part. The commentary by Parry et al advises us to prepare to adapt to climate changes of at least 4°C, even though they recognize that it may not be possible to buy our way out of most of the damage (to natural systems, for example, including the irreversible loss of many plant and animal species). Anyway, how does one "adapt" to a train wreck? There is also the fairness issue, in that the beneficiaries of fossil energy (rich countries today) are not the ones who pay the costs (less-rich countries decades from now). We wonder why we were not advised to prepare to adapt to crash curtailing CO₂ emissions, which sounds to us considerably less frightening.

p.s. For our German-speaking readers: Stefan's commentary on the KlimaLounge blog.

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They knew all along?
A recent story in NYT: 'Industry Ignored Its Scientists on Climate' has caught our attention.

Update: Marc Roberts' take:

Latest skeptical song from Singer

This week, the annual European Geophysical Union (EGU)'s general assembly was held in Vienna. Friday afternoon, I went to one of the conference's last talks to learn about the latest news from the climate skeptics (have to keep an open mind…). It was probably the talk with the smallest audience in the whole conference (see the photo, but note there were a couple of individuals who were not captured by camera), despite an unusually long slot (30 min) allocation.

And not much news, I'm afraid, apart from that SEPP plans to release it's NIPCC'09 in May. I understand it will be a thick report (800 pages?). The main messages were (a) that GHGs were unimportant - allegedlly supported by Douglass et al. (2007), and (b) solar activity was the main reason for the recent global warming and the mechanism involved galactic cosmic rays (GCR).

I asked Singer how he could explain the most recent warming when there is no trend in the GCR-flux or other indices of solar activity since 1952. He countered by saying he was glad I asked him this question, and announced that he had done his thesis exactly on the topic solar wind and GCRs.

So I had to answer that I had written a book about solar activity and climate, and I repeated my question. He could not answer in the end - other than saying that we have to look at the data. I told him that we already have looked at the data (e.g. Richardsson et al 2002; Benestad, 2005; Lockwood & Frohlich, 2007), so I recommended him to read up on RC.

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Guest post from Drew Shindell, NASA GISS

Our recent paper “Climate response to regional radiative forcing during the twentieth century”, has generated some interesting discussion (some of it very 'interesting' indeed). So this post is an attempt to give a better context to the methods and implications of the study.

First, some history. Global model responses to aerosols have been looked at since the early 1990s (Taylor and Penner, 1994; Mitchell et al, 1995, Santer et al, 1995). These studies and subsequent ones have shown that when a forcing is spatially concentrated, the regional climate response does not closely follow the spatial pattern of the forcing. These two figures show an example of that from two recent models (GISS ModelE and GFDL). Despite extremely large localized forcings over the industrialized areas, the climate response is spread out much more broadly in the zonal direction. Similarly, although forcing is extremely large over India and Southeast Asia, those areas show only very weak warming. In particular, the Arctic climate response can be quite different from what the local forcing would imply.

Figure 1. Ensemble mean annual average 1880–2003 radiative forcing (Fs, the top-of-the-atmosphere forcing with fixed SSTs and sea-ice, left column) and the surface air temperature (SAT) response (ºC, local linear trends, right column) from 5-member ensemble simulations driven by tropospheric aerosols including their direct radiative effect only (top row) and both their direct and indirect (via cloud cover) effects (bottom row). [Shindell et al., 2007].

Figure 2. Annual mean-adjusted radiative forcing (W/m2) between years 2100 and 2000 from tropospheric aerosols and ozone changes simulated under an A1B scenario (top) and annual surface air temperature change (°K) from the 2000s (years 2001–2010) to the 2090s (years 2091–2100) due to those same short-lived species in the GFDL model [Levy et al., 2008].

In our paper, we wanted to characterize the geographic forcing/response relationship more clearly. Prior studies had looked at particular scenarios or time periods when forcings were typically changing over much of the world (albeit most strongly in certain regions). So we put idealized forcings from GHGs, aerosols, and ozone in the tropics, mid-latitudes and polar regions to see what would happen. The results showed that the temperature response in the tropics, like the global mean, is only mildly sensitive to the location of forcing. That is, you get an enhanced tropical response to forcing in the Northern Hemisphere extratropics (where you can activate strong positive feedbacks like snow/ice albedo), but the enhancement is only 40-50% over that found with forcings applied elsewhere. In contrast, the extratropical zones are much, much more sensitive to local radiative forcing than to tropical forcing or to forcing in the opposite hemisphere. So to quote from the paper

"global and tropical mean temperature trends during the twentieth century would have been quite similar if short-lived-species radiative forcing had been distributed homogeneously rather than being concentrated in the northern extratropics. Regional concentration of forcing contributed to the departures of Northern Hemisphere mid-latitude and Arctic temperature trends from the global or Southern Hemisphere extratopical means, however."

We then used the regional forcing/response relationships to derive the aerosol forcing needed to explain the observed global and regional temperature trends. Our results have a substantial uncertainty range which arises primarily from the influence of unforced, internal variability. The global mean preindustrial to present-day aerosol forcing we calculate is -1.31 +- 0.52 W/m2, consistent with the IPCC AR4 range of -0.6 to -2.4 W/m2.

We also estimated aerosol forcing for the tropics and Northern Hemisphere mid-latitudes for several time periods, and compared with historical emissions estimates to tie the forcings to sulfate or black carbon (BC) aerosols when possible. The results show, for example, that nearly all CMIP3 models require strong aerosol cooling at Northern Hemisphere mid-latitudes during the 1931-1975 period to capture both the global mean trends and the NH mid-latitude versus Southern Hemisphere extratropics temperature trends (many CMIP3 models had both sulfate and BC, but not necessarily the correct amounts as modeling their forcing directly is quite uncertain, hence we compared the CMIP3 models' responses to non-aerosol forcings with observations to see how well they could do without aerosols). During the last 3 decades (1976-2007), the best fit to the temperature responses in the models require negative forcing from tropical aerosols but positive forcing from Northern Hemisphere mid-latitude aerosols. It's the latter, the positive Northern Hemisphere mid-latitude aerosol forcing that leads to the strong warming impact on the Arctic as well, as the Arctic responds to mid-latitude and local forcing, but the local forcing is primarily driven by mid-latitude emissions that are transported to the Arctic, so the overall climate response ends up being closely tied to Northern Hemisphere mid-latitude emissions. Given the strong sensitivity of the Northern Hemisphere extratropical zones to aerosol forcing, it's then understandable that those areas could have cooled during the mid 20th century when the aerosol forcing we calculate was substantially larger than greenhouse gas forcing (in absolute magnitude).

A big uncertainty is still the influence of unforced internal variability, which we estimated from coupled ocean-atmosphere climate runs. Though that contribution is large, it was still not large enough to account for many of the mid-latitude and Arctic temperature trends without including aerosol forcing. For many cases, the influence of aerosols and internal variability were comparable in size. Though the influence of internal variability leads to a substantial uncertainty range in our results, they are nonetheless useful as other techniques of estimating aerosol forcing of climate have comparably large or larger uncertainties. These include ‘forward’ modeling from emissions to concentration to optical properties (e.g. see [Schulz et al., 2006]), and various estimates based at least in part on satellite observations (see this previous post).

Some of the most interesting conclusions of the study include those relating to the Arctic. For example, we estimate that black carbon contributed 0.9 +/- 0.5ºC to 1890-2007 Arctic warming (which has been 1.9ºC total), making BC potentially a very large fraction of the overall warming there. We also estimated that aerosols in total contributed 1.1 +/- 0.8ºC to the 1976-2007 Arctic warming. This latter aerosol contribution to Arctic warming results from both increasing BC and decreasing sulfate, and as both were happening at once their contributions cannot be easily separated (unlike several earlier time periods we analyzed, when one increased while the other remained fairly constant). Though the uncertainty ranges are quite large, it can be useful to remember that the 95% confidence level conventionally used by scientists is not the only criteria that may be of interest. As the total observed Arctic warming during 1976-2007 was 1.5 +/- 0.3ºC, our results can be portrayed in many ways: there is about a 95% chance that aerosols contributed at least 15% to net Arctic warming over the past 3 decades, there is a 50% chance that they contributed about 70% or more, etc.

It’s also worth considering how to interpret the effects of decreasing sulfate during the past 3 decades. To try to make sure that the complex role of aerosols wouldn't be misunderstood, when referring to the recent warming due to aerosols at Northern Hemisphere mid-latitudes and in the Arctic, we stated in the conclusions of the paper:

"much of this warming may stem from the unintended consequences of clean-air policies that have greatly decreased sulfate precursor emissions from North America and Europe (reducing the sulfate masking of greenhouse warming) and from large increases in Asian black carbon emissions."

So it is incorrect, or at least quite incomplete, to say that that controls on air pollution such as those created under the Clean Air Act in the US have caused the recent warming. In the absence of increasing greenhouse gases, our large historical emissions of sulfate precursors would have led to substantial cooling from sulfate, and the subsequent reduction in emissions would have brought temperatures back towards their previous level. So reduced sulfate does not cause warming in an absolute sense, only relative warming compared to a time when emissions were larger. Over the mid-20th century, sulfate precursor emissions appear to have been so large that they more then compensated for greenhouse gases, leading to a slight cooling in the Northern Hemisphere. During the last 3 decades, the reduction in sulfate has reversed that cooling, and allowed the effects of greenhouse gases to clearly show. In addition, black carbon aerosols lead to warming, and these have increased during the last 3 decades.

For an analogy, picture a reservoir. Say that around the 1930s, rainfall into the watershed supplying the reservoir began to increase. However, around the same time, a leak developed in the dam. The lake level stayed fairly constant as the rainfall increased at about the same rate the leak grew over the next few decades. Finally, the leak was patched (in the early 70s). Over the next few decades, the lake level increased rapidly. Now, what’s the cause of that increase? Is it fair to say that lake level went up because the leak was fixed? Remember that if the rainfall hadn’t been steadily increasing, then the leak would have led to a drop in lake levels whereas fixing it would have brought the levels back to normal. However, it’s also incomplete to ignore the leak, because then it seems puzzling that the lake levels were flat despite the increased rain during the first few decades and that, were you to compare the increased rain with the lake level rise, you’d find the rise was more rapid during the past three decades than you could explain by the rain changes during that period. You need both factors to understand what happened, as you need both greenhouse gases and aerosols to explain the surface temperature observations (and the situation is more complex than this simple analogy due to the presence of both cooling and warming types of aerosols).

Hence the implication should not be that cleaning up the air causes warming, but that air pollution plays a substantial role in climate, and we can better understand regional climate changes during the past by taking this into account. Economists have argued that inclusion of a broader array of climate forcing agents leads to more cost-effective strategies to mitigate climate change (e.g. [O'Neill, 2003]), so that taking into account the large impact of air pollution and its ancillary effects on human and ecosystem health may also lead to better solutions for climate change.

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Guest post by Bart Verheggen, Department of Air Quality and Climate Change , Energy research Institute of the Netherlands (ECN)

In Part I, I discussed how aerosols nucleate and grow. In this post I'll discuss how changes in nucleation and ionization might impact the net effects.

Cosmic rays

Galactic cosmic rays (GCR) are energetic particles originating from space entering Earth’s atmosphere. They are an important source of ionization in the atmosphere, besides terrestrial radioactivity from e.g. radon (naturally emitted by the Earth’s surface). Over the oceans and above 5 km altitude, GCR are the dominant source. Their intensity varies over the 11 year solar cycle, with a maximum near solar minimum. Carslaw et al. give a nice overview of potential relations between cosmic rays, clouds and climate. Over the first half of the 20th century solar irradiance has slightly increased, and cosmic rays have subsequently decreased. RC has had many previous posts on the purported links between GCR and climate, e.g. here, here and here.

The role of ions

The role played by ions relative to neutral (uncharged) molecules in the nucleation process is still very much under discussion. For instance, based on the same dataset, Yu and Turco found a much higher contribution of ion induced nucleation (to the total amount of particles produced) than Laakso et al did. Evidence for a certain nucleation mechanism is often of an indirect nature, and depends on uncertain parameters. Most literature points to a potential importance of ion induced nucleation in the upper troposphere, but the general feeling is that neutral pathways for nucleation (i.e. not involving ions) are likely to be dominant overall. Most field studies, however, have been performed over land, whereas over the open ocean nucleation rates are generally lower due to lower vapor concentrations. In theory at least, this gives more opportunity for ion induced nucleation to make a difference over the ocean (even though the ion production rate is smaller).

The ion production rate (increasing with altitude from ~10 to ~50 ion pairs per cubic centimeter per second over land) sets a limit to what the particle formation rate due to ion induced nucleation can be. Based on his model for ion induced nucleation, Yu found that at low altitude, the number of particles produced is most sensitive to changes in cosmic ray intensity. At first sight, this may be a surprising result in light of the increasing cosmic ray intensity with increasing altitude. The reason is that high aloft, the limiting factor for particle formation is the availability of sulfuric acid rather than ions. Above a certain GCR intensity, increasing ionization further could even lead to a decrease in ion induced nucleation, because the lifetime of ion clusters is reduced (due to increased recombination of positive and negative ions). In contrast, at low altitude particle formation may be limited by the ionization rate (under certain circumstances), and an increase in ionization leads to an increase in nucleation.

How important is nucleation for climate?

Different modeling exercises have been performed to investigate this question. The strong dependency on input data and assumptions used, e.g. relating to primary particle emissions and nucleation parameterizations, and the different sensitivities tested, hampers an overall assessment. However, it is clear that globally, nucleation is significant for the number of cloud condensation nuclei (CCN) e.g. in the absence of boundary layer nucleation, the number of CCN would be 5% lower (Wang and Penner) or 3-20% lower (Spracklen et al.), and in a recent follow up study, they concluded that the number of cloud droplets would be 13-16% lower (in 2000 and 1850, respectively). Pierce and Adams took a different approach and looked at the variation of predicted number of CCN as a result of using different nucleation schemes. The tropospheric number of CCN varied by 17% (and the boundary layer CCN by 12%) amongst model runs using different nucleation rate parameterizations. Note that the globally averaged nucleation rates differed by a factor of a million (!).

It should be noted that the sensitivity of the number of CCN to nucleation depends greatly on the amount of primary emissions and secondary organic aerosol (SOA) formed. These are very uncertain themselves, which further limit our ability to understand the connection between nucleation and CCN. If there are more primary emissions, there will be more competition amongst aerosols to act as CCN. If more organic compounds partition to the aerosol phase (to form SOA), the growth to CCN sizes will be quicker.

Locally, particle formation has been observed to contribute significantly to the number of CCN; the second figure in Part I gives an example of freshly nucleated aerosols which grew large enough to influence cloud formation. Kerminen et al observed a similar event, followed by activation of part of the nucleated aerosols into cloud droplets, thus providing a direct link between aerosol formation and cloud droplet activation.

How important are cosmic rays for climate?

At the recent AGU meeting (Dec 2008), Jeff Pierce presented results on the potential effects of GCR on the number of CCN (their paper is currently in press at GRL (sub. required)). Two different parameterizations for ion induced nucleation were used (Modgil et al and an ‘ion-limit’ assumption that all ions go on to form a new particle). They ran their model with both high and low cosmic ray flux, simulating conditions during solar maximum and minimum, respectively. This happens to be comparable to the change in cosmic ray flux over the 20th century (mostly confined to the first half), and amounts to a 20% change in tropospheric ion production. With both mechanisms of ion-induced nucleation, this leads to a 20% change in globally averaged particle nucleation, but only to a 0.05% change in globally averaged CCN. The authors concluded that this was “far too small to make noticeable changes in cloud properties based on either the decadal (solar cycle) or climatic time-scale changes in cosmic rays.” To account for some reported changes in cloud cover, a change in CCN on the order of 10% would be needed. More studies of this kind will undoubtedly come up with different numbers, but it’s perhaps less likely that the qualitative conclusion, as quoted above, will change dramatically. Time will tell, of course.

The bottom line

Freshly nucleated particles have to grow by about a factor of 100,000 in mass before they can effectively scatter solar radiation or be activated into a cloud droplet (and thus affect climate). They have about 1-2 weeks to do this (the average residence time in the atmosphere), but a large fraction will be scavenged by bigger particles beforehand. What fraction of nucleated particles survives to then interact with the radiative budget depends on many factors, notably the amount of condensable vapor (leading to growth of the new particles) and the amount of pre-existing particles (acting as a sink for the vapor as well as for the small particles). Model-based estimates of the effect of boundary layer nucleation on the concentration of cloud condensation nuclei (CCN) range between 3 and 20%. However, our knowledge of nucleation rates is still severely limited, which hampers an accurate assessment of its potential climate effects. Likewise, the potential effects of galactic cosmic rays (GCR) can only be very crudely estimated. A recent study found that a change in GCR intensity, as is typically observed over an 11 year solar cycle, could, at maximum, cause a change of 0.1% in the number of CCN. This is likely to be far too small to make noticeable changes in cloud properties.

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Guest post by Bart Verheggen, Department of Air Quality and Climate Change , Energy research Institute of the Netherlands (ECN)

The impacts of aerosols on climate are significant, but also very uncertain. There are several reasons for this, one of which is the uncertainty in how and how fast they are formed in the atmosphere by nucleation. Here, in part I, I’ll review some of the basic processes that are important in determining the climate effects of aerosols, focusing in particular on their formation. This is also relevant in order to better understand –and hopefully quantify- the hypothetical climate effects of galactic cosmic rays which I'll discuss in a follow-up post.

Background

Aerosols are liquid or solid particles suspended in the atmosphere (but not including water droplets or ice crystals). They can either be directly emitted into the atmosphere (primary aerosols like dust), or they can be formed in the atmosphere by condensation (secondary aerosol like sulfates). Almost all of their properties, and thus effects, are size dependent: The particle size governs the rate at which they fall out (and thus atmospheric lifetime), their interaction with radiation, their impact on clouds, or even their health effects. And they come in very different sizes, ranging from a few nanometers to tens of micrometers. Some sites with good introductory explanations to aerosols and their climate effects are here, here and here (German). RC also had some posts on the same generic topic here and here.

Climate effects of aerosols

Aerosol particles can influence climate in several ways: They scatter and absorb (in the case of black carbon) solar radiation (direct effects). They also act as cloud condensation nuclei (CCN) around which clouds can form, and thereby influence cloud reflectivity and cloud lifetime (indirect effects). Black carbon can have another indirect effect by changing the albedo of snow and ice, but that’s not the topic of this post. The aerosol indirect effects are the greatest source of uncertainty in assessing the human impact on climate change (reviewed here. The main idea is that more CCN causes liquid clouds to consist of more, but smaller, droplets. The resulting cloud is more reflective (first indirect effect). Due to the smaller size of cloud droplets, the formation of precipitation may be suppressed, resulting in a longer cloud lifetime and larger cloud cover (second indirect effect).

The mass of a freshly nucleated aerosol particle is more than 100,000 times smaller than that of an ‘aged’ aerosol of a size optimal to affect climate. As a rule of thumb, particles have to grow past 100 nm (1 nm = 10^-9 meters) in order to become climatically active; below this size they are not easily activated into a cloud droplet and they don’t scatter solar radiation very efficiently. It is thus not immediately obvious that the climate effects of aerosols will depend very strongly on nucleation; the dependence is likely considerably damped, because a lot can happen to the aerosol particle as it comes of age.

Aerosol formation

The most prevalent trace gases do not generally nucleate new aerosols (or even condense onto existing ones), because they are too volatile (i.e. they have a high saturation vapor pressure and thus evaporate readily). They first have to be oxidized (usually under the influence of sunlight) to produce a compound with a lower vapor pressure. The prime example of this is the oxidation of sulfur dioxide (SO₂) into sulfuric acid (H₂SO₄), which has a very low vapor pressure. The H₂SO₄ can then condense together with water vapor (and perhaps organic compounds and/or ammonia) to form a stable cluster of molecules: A new particle is typically 1-2 nanometers in diameter. Ions can also play a role, by lowering the energy barrier that needs to be overcome: The attractive forces between the molecules are stronger when one of them is charged. See here and here for a review of atmospheric nucleation processes.

Instead of nucleating into a new particle, H₂SO₄ could also condense on an existing aerosol particle, making it grow in size. Because of this competition for the vapor, nucleation is more likely to happen when there is only a little aerosol present.

Aerosol growth

Condensation of more vapor onto the nucleated aerosol makes it grow in size. However, other processes hamper its possibility to grow large enough to substantially influence the climate: Two aerosols can collide together, in a process called coagulation. Coagulation is particularly efficient between very small nano-particles and larger particles (of a few hundred nanometers). It causes the bigger one to grow in size, whereas the smaller (recently nucleated) one disappears. When there are a lot of very small aerosols around (i.e. after a nucleation event), they can also coagulate together. This causes them to grow in size, but decreases their number concentration. The loss processes for the number of aerosols (deposition and coagulation with bigger particles) are stronger when they’re very small.

Figure 1: Different factors influence the extent to which nucleation contributes to the number of cloud condensation nuclei (CCN). (Figure partly based on AGU presentation by Jeff Pierce)

Measurements

New particle formation has been observed all over the globe, from the Poles to the Tropics, from urban to remote areas, and from surface sites to the upper troposphere (see here for a review of such observations). Of these locations, only nucleation in the free troposphere and in the vicinity of clouds seems to agree with theoretical predictions. In most other cases the number of aerosol particles produced is under-predicted. This has led to the development of semi-empirical approaches to describe nucleation. Laboratory studies have typically found much stronger dependencies on H₂SO₄ than atmospheric measurements. A confounding factor is that newly formed particles of 1 to 2 nanometers can not be directly measured by commercially available instrumentation (though there are new developments in this area). Nucleation takes place in a kind of no-man's land between the gas and the liquid phase, about which we know surprisingly little.

Figure 2: Measurements of an atmospheric nucleation and growth event in the Lower Fraser Valley, Canada. The color gives the (normalized) number concentration, where the red color indicates the enhanced concentration of nucleated particles, growing into the CCN size range. (from Mozurkewich et al.)

So what is needed for nucleation to occur? Favorable conditions include a strong source of condensable vapor; high UV radiation intensity; low aerosol surface area; high relative humidity; low temperature; presence of ions; and atmospheric mixing processes. Under different environmental conditions, different nucleation mechanisms may be at work. For example, in industrial plumes and over urban areas enough sulfuric acid may be present to form new particles and have them grow to a stable size. Ammonia may neutralize the acidic cluster, and thereby help stabilizing it. Over forested areas, the relative role of organic compounds is expected to be much larger (though a strong correlation of nucleation events with sulfuric acid remains). In coastal areas, iodine compounds are likely involved in the nucleation process. In the upper troposphere, the ion density is usually larger, whereas the sulfuric acid concentration is lower. The relative role of ion induced nucleation may therefore be larger up there. The dominant role of sulfuric acid has remained a steady conclusion over the years, whereas the potential roles of organic compounds and ions are still hotly debated.

In part II, I'll discuss the potential importance of nucleation and of galactic cosmic rays for climate change.

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Did you know that in 1965 the U.S. Department of Agriculture planted a particular variety of lilac in more than seventy locations around the U.S. Northeast, to detect the onset of spring — in turn to be used to determine the appropriate timing of corn planting and the like? The records the USDA have kept show that those same lilacs are blooming as much as two weeks earlier than they did in 1965. April has, in a very real sense, become May. This is one of the interesting facts that you’ll read about in Amy Seidl’s book, Early Spring, a hot-off-the-press essay about the impacts of climate change on the world immediately around us – the forest, the birds, the butterflies in our backyards.

The brilliant title of Seidl’s book was one of the reasons that it caught my attention. The other was that I have realized I need to better educate myself about the impact of climate change on everyday life. I’ve been dismissive of the idea that the average person can really detect the impacts of recent warming on, for example, the timing of the apple-blossom season, but I’ve been taken to task by several of RealClimate’s readers for this. If you are paying attention, they have argued, the changes are actually rather obvious.

Of course, Amy Seidl is not the average person. Rather, she’s a trained ecologist with a Ph.D. (as well as an avid gardener) and she’s clearly paying extremely close attention. Her book is the first one I have read that effectively brings home the tangible impacts that global warming will have – is having – on our everyday lives. “We are increasingly familiar,” she writes, of images of melting glaciers, “but how do we give them relevance in our lives? From my window I see no glaciers.” She answers her own question with a series of vignettes, some from her own experiences, many more from her extensive research (well referenced throughout the book).

Cardinals, robins and cowbirds are all arriving earlier in Vermont than they did a century ago. Kingfishes, fox sparrows and towhees are not. Why the difference? The answer, as Seidl explains, is that the former group has the ability to respond ecologically to the changes, because these birds cue their arrival to temperature. The latter, it appears, respond more directly to temporal cues, that won’t change even as climate does. It’s obvious from this example that the make up of bird life in Vermont – the species distribution – will change over time. This may not necessarily be a bad thing of course. On the other hand, it turns out that the robins are the most important host for West Nile virus; the early bird gets the worm, so to speak, and passes it along to humans.

Maple seedlings need about 100 days of below-freezing weather. As this becomes rarer, fewer maples will populate the forests. This, Seidl explains, is why species-range models predict the decline and eventual loss of sugar maple (at least in New England) in the future. But, she notes, the models don’t take into account the full complexity of the system, such as the impact of competition among different species. So we don’t really know what will happen, or how fast. What we do know is that maple-sugar farmers have noticed – and documented – an earlier maple sugaring season over the last few decades.

There are many other examples in Early Spring both of clear climate-related changes (such as the early arrival of robins), and of less clear-cut changes (the maple sugaring season). Seidl doesn’t make the common mistake of assuming that the more ambiguous examples are necessarily due to climate change. For example, she quotes a maple-sugarer who points out that technological changes have allowed them to tap maples earlier, and hence that the timing of sugaring is a weak measure of climate change. The point though, is that even rather minor changes are, after all, being noticed. And if much larger changes do occur, as predicted, they will most certainly have impacts we can’t ignore, even if we don’t live in the Arctic or in Bangladesh. In other words, Seidl tells us, listen to the farmers and gardeners, and the observations of regular people: they are meaningful.

The soberness of Seidl’s approach to the subject of climate change impacts contrasts starkly with that of many books before it. It couldn’t be further, for example, from Mark Lynas’s book, Six Degrees, which is a truly alarming read. In my comments on Six Degrees, I said that it wasn’t an alarmist book. I stand by that characterization, because – and this is what I liked about it – it doesn’t go beyond what is in the scientific literature. However, while Lynas’s book is a straightforward reading of the scientific literature, it is a somewhat uncritical one, and hence tends to emphasize what might happen in the future over what will happen; this is a point that many readers of my review seem to have missed. Seidl’s book, on the other hand, is focused on the more certain – and often less dramatic — things, and on the impacts we are likely to see in our own lifetimes.

The calm demeanor of Seidl’s book, and the very personal nature of it, could lead one to think that it is primarily just a philosophical reflection on the climate change story. Indeed, Bill McKibben, in his introduction to Early Spring, says that in the face of changes we may not be able to prevent, “one of our tasks is simply to bear witness”. Certainly, the book is partly that. But Seidl’s voice, like Rachel Carson’s before her, has the authentic and authoritative voice of a scientist, made all the more compelling for being very much rooted in the author’s own story and experiences. And she doesn’t pull punches when she has something definitive to say: “One thing is clear:” she writes, “we will not be able to manage the climate”.

Early Spring has the potential to be immensely influential, a real turning point in the popular appreciation of climate change impacts among laypersons and scientists alike. Read it.

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Note that we review books on a fairly ad hoc basis. For earlier reviews of other books, see here.

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