Loading...

Follow RealClimate on Feedspot

Continue with Google
Continue with Facebook
or

Valid

A bimonthly open thread on climate solutions and policies. If you want to discuss climate science, please use the Unforced Variations thread instead.

Read Full Article
  • Show original
  • .
  • Share
  • .
  • Favorite
  • .
  • Email
  • .
  • Add Tags 

This month’s open thread about climate science topics. For discussions about solutions and policy, please use the Forced Variations open thread.

Read Full Article
  • Show original
  • .
  • Share
  • .
  • Favorite
  • .
  • Email
  • .
  • Add Tags 

Wow.

Perhaps unsurprisingly given the exceptional (relative) warmth in Alaska last month and in February, the record for the Nenana Ice Classic was shattered this year.

The previous official record was associated with the exceptional conditions in El Niño-effected winter of 1939-1940, when the ice went out on April 20th 1940. Though since 1940 was a leap year, that was actually a little later (relative to the vernal equinox) than the ice out date in 1998 (which wasn’t a leap year). 

Other records are also tumbling in the region, for instance the ice out data at Bethel, Alaska:

The Kuskokwim River at Bethel has gone out. This is, by far, the earliest breakup in the 90+ years of breakup data. This follows the warmest February and warmest March on record. @kuskoiceclassic @Climatologist49 @AlaskaWx pic.twitter.com/auEfe0YQ7J

— IARC Fairbanks (@IARC_Alaska) April 13, 2019

While the trend at Nenana since 1908 has been towards earlier ice-out dates (by about 7 days a century on average), the interannual variability is high. This is consistent with the winter warming in this region over that period of about 2.5ºC.  Recent winters have got close (2012/14/15/16) (3 to 4 days past the record),  but this year’s April 14th date is an impressive jump (and with no leap year to help calendrically).

As usual, I plot both the raw date data and the version adjusted to relative to the vernal equinox (I’m estimating the time of breakup at ~12:11am based on twitter, pending official notification).

  [As usual, I predict that there will be no interest from the our favorite contrarians in this]

Read Full Article
  • Show original
  • .
  • Share
  • .
  • Favorite
  • .
  • Email
  • .
  • Add Tags 

This month’s open thread on climate science issues. Remember that discussions about climate solutions go here.

Read Full Article
  • Show original
  • .
  • Share
  • .
  • Favorite
  • .
  • Email
  • .
  • Add Tags 

Guest post by Matteo Willeit, Potsdam Institute for Climate Impact Research

A new study published in Science Advances shows that the main features of natural climate variability over the last 3 million years can be reproduced with an efficient model of the Earth system.

The Quaternary is the most recent geological Period, covering the past ~2.6 million years. It is defined by the presence of glacial-interglacial cycles associated with the cyclic growth and decay of continental ice sheets in the Northern Hemisphere. Climate variations during the Quaternary are best seen in oxygen isotopes measured in deep-sea sediment cores, which represent variations in global ice volume and ocean temperature. These data show clearly that there has been a general trend towards larger ice sheets and cooler temperatures over the last 3 million years, accompanied by an increase in the amplitude of glacial-interglacial variations and a transition from mostly symmetry cycles with a periodicity of 40,000 years to strongly asymmetric 100,000-year cycles at around 1 million years ago.  However, the ultimate causes of these transitions in glacial cycle dynamics remain debated.

Among others, the role of CO2 changes in shaping Quaternary climate dynamics is not yet fully understood, largely because of the poor observational constraints on atmospheric CO2 concentrations for the time before 800,000 years BP, beyond the period covered by high-quality ice core data.

In a paper published today in Science Advances, we were able to reproduce the natural climate variability of the whole Quaternary with an Earth system model of intermediate complexity. Besides ocean and atmosphere, the model includes interactive ice sheets for the Northern Hemisphere and a fully coupled global carbon cycle and was driven only by changes in orbital configuration and different scenarios for slowly varying boundary conditions, namely CO2 outgassing from volcanoes as a geologic source of CO2, and changes in sediment distribution over the continents.

The model simulations provide a self-consistent reconstruction of CO2, climate and ice sheets constrained by available observations, i.e. oxygen isotopes and reconstructions of sea surface temperature. The fact that the model can reproduce the main features of the observed climate history gives us confidence in our general understanding of how the climate system works and provides some constraints on the contribution of external forcings and internal feedbacks to climate variability.

Our results imply a strong sensitivity of the Earth system to relatively small variations in atmospheric CO2. A gradual decrease of CO2 to values below ~350 ppm led to the start of continental ice sheet growth over Greenland and more generally over the NH at the end of the Pliocene, beginning of Pleistocene. Subsequently, the waxing and waning of the ice sheets acted to gradually remove the thick layer of unconsolidated sediments that had been formed previously over continents by the undisturbed action of weathering over millions of years. The erosion of this sediment layer – it was essentially bulldozed away by moving glaciers – affected the evolution of glacial cycles in several ways. First, ice sheets sitting on soft sediments are generally more mobile than ice sheets grounded on hard bedrock, because ice slides more easily over sediments compared to bedrock. Additionally, glacial sediment transport to the ice sheet margins generates substantial amounts of dust that, once deposited on the ice sheet surface, increases melting of the ice sheets by lowering surface albedo. Our results show that the gradual increase in the area of exposed bedrock over time led to more stable ice sheets which were less responsive to orbital forcing and ultimately paved the way for the transition to 100,000 years cycles at around 1 million years ago.

The simulations further suggest that global temperature never exceeded the preindustrial value by more than 2°C during the Quaternary. Ice sheet evolution is very sensitive to temperature, and the initiation of NH glaciation at around 3 million years ago would not have been possible in the model if global temperature would have been higher than 2°C relative to preindustrial during the early Quaternary. Since the model has been shown to accurately reproduce the sea level variations over the last 400,000 years and also the spatial ice sheet distribution at the last glacial maximum (Ganopolski & Brovkin 2017), we are confident that the sensitivity of ice sheets to climate is well represented in the model.

Likewise, our results indicate that the current CO2 concentration of ~410 ppm is unprecedented over the past 3 million years. The climate sensitivity of the model is around 3°C global warming for a doubling of CO2 concentration, which is at the center of the range of current best estimates of climate sensitivity that range between 1.5 and 4.5°C. It is possible that the real climate sensitivity is lower than 3°C, in which case the modelled CO2 concentration needed to fit the oxygen isotope record during the early Quaternary would be higher than in the present model simulations, but it would still be unlikely to exceed the present day value.

In the context of future climate change, our results imply that a failure to significantly reduce CO2 emissions to comply with the Paris Agreement target of limiting global warming well below 2°C will not only bring Earth’s climate away from Holocene-like conditions, but also push it beyond climatic conditions experienced during the entire current geological period.

Read Full Article
  • Show original
  • .
  • Share
  • .
  • Favorite
  • .
  • Email
  • .
  • Add Tags 

Guest post by Matteo Willeit, Potsdam Institute for Climate Impact Research

A new study published in Science Advances shows that the main features of natural climate variability over the last 3 million years can be reproduced with an efficient model of the Earth system.

The Quaternary is the most recent geological Period, covering the past ~2.6 million years. It is defined by the presence of glacial-interglacial cycles associated with the cyclic growth and decay of continental ice sheets in the Northern Hemisphere. Climate variations during the Quaternary are best seen in oxygen isotopes measured in deep-sea sediment cores, which represent variations in global ice volume and ocean temperature. These data show clearly that there has been a general trend towards larger ice sheets and cooler temperatures over the last 3 million years, accompanied by an increase in the amplitude of glacial-interglacial variations and a transition from mostly symmetry cycles with a periodicity of 40,000 years to strongly asymmetric 100,000-year cycles at around 1 million years ago.  However, the ultimate causes of these transitions in glacial cycle dynamics remain debated.

Among others, the role of CO2 changes in shaping Quaternary climate dynamics is not yet fully understood, largely because of the poor observational constraints on atmospheric CO2 concentrations for the time before 800,000 years BP, beyond the period covered by high-quality ice core data.



Fig 1 Comparison of results of model simulations with observations over the last 3 million years for oxygen isotopes (top), atmospheric CO2 concentration (middle) and global temperature anomalies relative to preindustrial (bottom). All black lines and symbols are observations, while the model results are represented by the colored lines. For CO2 and global temperature the historical observations and the approximate present day values are shown in red.

In a paper published today in Science Advances, we were able to reproduce the natural climate variability of the whole Quaternary with an Earth system model of intermediate complexity. Besides ocean and atmosphere, the model includes interactive ice sheets for the Northern Hemisphere and a fully coupled global carbon cycle and was driven only by changes in orbital configuration and different scenarios for slowly varying boundary conditions, namely CO2 outgassing from volcanoes as a geologic source of CO2, and changes in sediment distribution over the continents.

The model simulations provide a self-consistent reconstruction of CO2, climate and ice sheets constrained by available observations, i.e. oxygen isotopes and reconstructions of sea surface temperature. The fact that the model can reproduce the main features of the observed climate history gives us confidence in our general understanding of how the climate system works and provides some constraints on the contribution of external forcings and internal feedbacks to climate variability.

Our results imply a strong sensitivity of the Earth system to relatively small variations in atmospheric CO2. A gradual decrease of CO2 to values below ~350 ppm led to the start of continental ice sheet growth over Greenland and more generally over the NH at the end of the Pliocene, beginning of Pleistocene. Subsequently, the waxing and waning of the ice sheets acted to gradually remove the thick layer of unconsolidated sediments that had been formed previously over continents by the undisturbed action of weathering over millions of years. The erosion of this sediment layer – it was essentially bulldozed away by moving glaciers – affected the evolution of glacial cycles in several ways. First, ice sheets sitting on soft sediments are generally more mobile than ice sheets grounded on hard bedrock, because ice slides more easily over sediments compared to bedrock. Additionally, glacial sediment transport to the ice sheet margins generates substantial amounts of dust that, once deposited on the ice sheet surface, increases melting of the ice sheets by lowering surface albedo. Our results show that the gradual increase in the area of exposed bedrock over time led to more stable ice sheets which were less responsive to orbital forcing and ultimately paved the way for the transition to 100,000 years cycles at around 1 million years ago.

The simulations further suggest that global temperature never exceeded the preindustrial value by more than 2°C during the Quaternary. Ice sheet evolution is very sensitive to temperature, and the initiation of NH glaciation at around 3 million years ago would not have been possible in the model if global temperature would have been higher than 2°C relative to preindustrial during the early Quaternary. Since the model has been shown to accurately reproduce the sea level variations over the last 400,000 years and also the spatial ice sheet distribution at the last glacial maximum (Ganopolski & Brovkin 2017), we are confident that the sensitivity of ice sheets to climate is well represented in the model.

Likewise, our results indicate that the current CO2 concentration of ~410 ppm is unprecedented over the past 3 million years. The climate sensitivity of the model is around 3°C global warming for a doubling of CO2 concentration, which is at the center of the range of current best estimates of climate sensitivity that range between 1.5 and 4.5°C. It is possible that the real climate sensitivity is lower than 3°C, in which case the modelled CO2 concentration needed to fit the oxygen isotope record during the early Quaternary would be higher than in the present model simulations, but it would still be unlikely to exceed the present day value.

In the context of future climate change, our results imply that a failure to significantly reduce CO2 emissions to comply with the Paris Agreement target of limiting global warming well below 2°C will not only bring Earth’s climate away from Holocene-like conditions, but also push it beyond climatic conditions experienced during the entire current geological period.

Read Full Article
  • Show original
  • .
  • Share
  • .
  • Favorite
  • .
  • Email
  • .
  • Add Tags 

Guest Commentary by Mauri Pelto (Nichols College)

Preliminary data reported from the reference glaciers of the World Glacier Monitoring Service (WGMS) in 2018 from Argentina, Austria, China, France, Italy, Kazakhstan, Kyrgyzstan, Nepal, Norway, Russia, Sweden, Switzerland and United States indicate that 2018 will be the 30th consecutive year of significant negative annual balance (> -200mm); with a mean balance of -1247 mm for the 25 reporting reference glaciers, with only one glacier reporting a positive mass balance (WGMS, 2018).

A view of how alpine glaciers in the Pacific Northwest fit into the broader ecosystem (Megan Pelto, Jill Pelto).

I have spent 35 consecutive summers measuring mass balance on alpine glaciers, and more than 750 nights in a tent to record their response to climate change. A decade ago I described what was happening to alpine glaciers here at RC, but the continued signal of mass loss is inescapable and has been getting worse. The decadal mean annual mass balance of WGMS reference alpine glaciers was -171 mm in the 1980’s, -460 mm in the 1990’s, -500 mm for 2000’s and – 850 mm for 2010-2018.

Figure 1. Global Alpine glacier annual mass balance record of reference glaciers submitted to the World Glacier Monitoring Service, with a minimum of 30 reporting glaciers. Global values are calculated using only one single value (averaged) for each of 19 mountain regions in order to avoid a bias to well observed regions.

Just as people need to consume as many calories as the expend or they will lose mass, glaciers need to accumulate as much snow and ice as is lost to melt and calving icebergs in order to survive. After 30 consecutive years of alpine glacier mass loss it is clear that the “diet/lifestyle” of alpine glaciers is not healthy and as the climate they live in changes, alpine glaciers will continue a downward health spiral.

Alpine glaciers are recognized as one of most sensitive indicators of climate change. WGMS record of mass balance and terminus behavior (WGMS, 2017) providing a global index for alpine glacier behavior. This record illustrates a consistent signal from alpine glaciers around the world of significant mass loss and consequent retreat. Glacier mass balance is the difference between accumulation and ablation, reported here in mm of water equivalence (mm). Mean annual glacier mass balance in 2017 was -921 mm for the 42 long term reference glaciers and -951 mm for all 142 monitored glaciers. Figure 1 and 2 are graphs of global glacier mass change showing the annual balance for a set of global reference glaciers with more than 30 continued observation years for the time-period 1950-2018.

Figure 2. Decadal average mass balance of WGMS reference glaciers.

Glacier retreat reflects sustained negative mass balances over the last 30 years (Zemp et al., 2015). The increasing rate of glacier mass loss during a period of retreat indicates alpine glaciers are not approaching equilibrium and retreat will continue to be the dominant terminus response (Pelto, 2018). Ongoing global glacier retreat is currently affecting human society by increasing the rate of sea-level rise, changing seasonal discharge in glacier fed rivers, and increasing geo-hazard potential (Huss et al, 2017) (pdf). The recent mass losses 1991-2010 are due to anthropogenic forcing (Marzeion et al. 2014).

The cumulative mass balance from 1980-2018 is -21.7 m, the equivalent of cutting a 24 m thick slice off the top of the average glacier (Figure 1). The trend is remarkably consistent across regions (WGMS, 2017). WGMS mass balance from 42 reference glaciers, which have a minimum 30 years of record, is not appreciably different from that of all monitored glaciers at -21.5 m.

The number of reference glaciers is small compared to the total number of alpine glaciers (~200,000) in the world, but has proved to be a good approximation of global alpine glacier change. Marzeion et al (2017) compared WGMS direct observations of mass balance on a few glaciers to both remote sensing mass balance calculations based all alpine glaciers over the shorter period of available satellite data and climate driven mass balance model calculations and found that each method yields reconcilable estimates relative to each other and fall within their respective uncertainty margins. The WGMS record appears to have a slight negative bias compared to modeling and remote sensing approaches, but this bias has been much reduced with the regionalized approach now used by WGMS.

In 2018 exceptional glacier melt was noted across the European Alps, leading to high snowlines and contributing to large negative mass balance of glaciers. In the European Alps, annual mass balance has been reported from 17 glaciers in Austria, France, Italy and Switzerland. All 17 had negative annual balances, with 15 exceeding -1000 mm with a mean of -1640 mm. This continues the pattern of substantial negative balances in the Alps, which will equate to further terminus retreat. Of 81 observed glaciers in 2017 in Switzerland, 80 retreated, and only 1 was stable (Huss et al, 2018, [Fr]). In 2017, 83 glaciers were observed in Austria,; 82 retreated, and again only one was stable. Mean terminus retreat was 25 m, the highest observed since 1960 when mean length change reporting began (Lieb and Kellerer-Pirklbauer, 2018).

In Norway and Sweden, mass balance surveys with completed results are available for eight glaciers; all had negative mass balances with an average loss of -1420 mm w.e. All 25 glaciers with terminus observations during the 2007-2017 period have retreated (Kjøllmoen et al, 2018).

Figure 3. Taku Glacier transient snowline in Landsat 8 images from July 21, 2018 and September 16, 2018. The July 21 snowline is at 975 m and the September 16 snowline is at 1400 m. The average end of summer snowline from is m with the 2018 snowline being the highest observed since observations began in 1946.

In western North America data has been submitted from 11 glaciers in Alaska and Washington in the United States. All eleven glaciers reported negative mass balances with a mean loss of -870 mm. The longest mass balance record in North America is from Taku Glacier in Alaska. In 2018 the glacier had its most negative mass balance since the beginning of the record in 1946 and the highest end of summer snowline elevation at 1400 m. The North Cascade Range, Washington from 2014-2018 had the most negative five-year period for the region of the 1980-2018 WGMS record.

In the High Mountains of Asia (HMA) data was reported from ten glaciers including from China, Kazakhstan, Kyrgyzstan and Nepal. Nine of the ten had negative balances with a mean of -710 mm. This is a continuation of regional mass loss that has driven thinning and a slowdown in glacier movement in 9 of 11 regions in HMA from 2000-2017 (Dehecq et al. 2018).

Time series of glacier mass balance and temperature (as rendered by J. Pelto).

The key take away is the same for alpine glaciers around the globe, warming temperatures lead to mass balance losses, which leads to velocity slow down. Mass balance is the key driver in glacier response, and a sustained negative mass balance leads to thinning and retreat, which leads to a glacier velocity decline, whether the glacier is in the Himalayas, Alps or Andes.

References
  1. M. Zemp, H. Frey, I. Gärtner-Roer, S.U. Nussbaumer, M. Hoelzle, F. Paul, W. Haeberli, F. Denzinger, A.P. Ahlstrøm, B. Anderson, S. Bajracharya, C. Baroni, L.N. Braun, B.E. Cáceres, G. Casassa, G. Cobos, L.R. Dávila, H. Delgado Granados, M.N. Demuth, L. Espizua, A. Fischer, K. Fujita, B. Gadek, A. Ghazanfar, J. Ove Hagen, P. Holmlund, N. Karimi, Z. Li, M. Pelto, P. Pitte, V.V. Popovnin, C.A. Portocarrero, R. Prinz, C.V. Sangewar, I. Severskiy, O. Sigurđsson, A. Soruco, R. Usubaliev, and C. Vincent, "Historically unprecedented global glacier decline in the early 21st century", Journal of Glaciology, vol. 61, pp. 745-762, 2015. http://dx.doi.org/10.3189/2015JoG15J017
  2. M. Pelto, "How Unusual Was 2015 in the 1984–2015 Period of the North Cascade Glacier Annual Mass Balance?", Water, vol. 10, pp. 543, 2018. http://dx.doi.org/10.3390/w10050543
  3. M. Huss, B. Bookhagen, C. Huggel, D. Jacobsen, R. Bradley, J. Clague, M. Vuille, W. Buytaert, D. Cayan, G. Greenwood, B. Mark, A. Milner, R. Weingartner, and M. Winder, "Toward mountains without permanent snow and ice", Earth's Future, vol. 5, pp. 418-435, 2017. http://dx.doi.org/10.1002/2016EF000514
  4. B. Marzeion, J.G. Cogley, K. Richter, and D. Parkes, "Attribution of global glacier mass loss to anthropogenic and natural causes", Science, vol. 345, pp. 919-921, 2014. http://dx.doi.org/10.1126/science.1254702
  5. B. Marzeion, N. Champollion, W. Haeberli, K. Langley, P. Leclercq, and F. Paul, "Observation-Based Estimates of Global Glacier Mass Change and Its Contribution to Sea-Level Change", Surveys in Geophysics, vol. 38, pp. 105-130, 2016. http://dx.doi.org/10.1007/s10712-016-9394-y
  6. A. Dehecq, N. Gourmelen, A.S. Gardner, F. Brun, D. Goldberg, P.W. Nienow, E. Berthier, C. Vincent, P. Wagnon, and E. Trouvé, "Twenty-first century glacier slowdown driven by mass loss in High Mountain Asia", Nature Geoscience, vol. 12, pp. 22-27, 2018. http://dx.doi.org/10.1038/s41561-018-0271-9
Read Full Article
  • Show original
  • .
  • Share
  • .
  • Favorite
  • .
  • Email
  • .
  • Add Tags 
RealClimate by Gavin - 2M ago

This is a thread for collecting the oddball theories, tinfoil hat level conspiracies and other nonsense in the comments that would otherwise derail substantive discussion.

Read Full Article
  • Show original
  • .
  • Share
  • .
  • Favorite
  • .
  • Email
  • .
  • Add Tags 

This month’s open thread on climate science topics.

Read Full Article
  • Show original
  • .
  • Share
  • .
  • Favorite
  • .
  • Email
  • .
  • Add Tags 

The “end of the world” or “good for you” are the two least likely among the spectrum of potential outcomes.

Stephen Schneider

Scientists have been looking at best, middling and worst case scenarios for anthropogenic climate change for decades. For instance, Stephen Schneider himself took a turn back in 2009. And others have postulated both far more rosy and far more catastrophic possibilities as well (with somewhat variable evidentiary bases).

This question came up last year in the wake of a high profile piece “The Uninhabitable Earth” by David Wallace-Wells in New York magazine. That article was widely read, and heavily discussed on social media – notably by David Roberts, Mike Mann and others, was the subjected to a Climate Feedback audit, a Salon Facebook live show with Kate Marvel and the author, and a Kavli conversation at NYU with Mike Mann this week as well. A book length version is imminent.

In a similar vein, Eric Holthaus wrote “Ice Apocalypse” about worst-case scenarios of Antarctic ice sheet change and the implications for sea level rise. Again, this received a lot of attention and some serious responses (notably one from Tamsin Edwards).

It came up again in discussions about the 4th National Assessment Report which (unsurprisingly) used both high and low end scenarios to bracket plausible trajectories for future climate.

However, I’m not specifically interested in discussing these articles or reports (many others have done so already), but rather why it always so difficult and controversial to write about the worst cases.

There are basically three (somewhat overlapping) reasons:

  1. The credibility problem: What are the plausible worst cases? And how can one tell?
  2. The reticence problem: Are scientists self-censoring to avoid talking about extremely unpleasant outcomes?
  3. The consequentialist problem: Do scientists avoid talking about the most alarming cases to motivate engagement?

These factors all intersect in much of the commentary related to this topic (and in many of the articles linked above), but it’s useful perhaps to tackle them independently.

1. Credibility

It should go without saying that imagination untethered from reality is not a good basis for discussing the future outside of science fiction novels. However, since the worst cases have not yet occurred, some amount of extrapolation, and yes, imagination, is needed to explore what “black swans” or “unknown unknowns” might lurk in our future. But it’s also the case that extrapolations from incorrect or inconsistent premises are less than useful. Unfortunately, this is often hard for even specialists to navigate, let alone journalists.

To be clear, “unknown unknowns” are real. A classic example in environmental science is the Antarctic polar ozone hole which was not predicted ahead of time (see my previous post on that history) and occurred as a result of chemistry that was theoretically known about but not considered salient and thus not implemented in predictions.

Possible candidates for “surprises in the greenhouse”, are shifts in ecosystem functioning because of the climate sensitivity of an under-appreciated key species (think pine bark beetles and the like), under-appreciated sensitivities in the West Antarctic Ice Sheet, or the North Atlantic overturning, and/or carbon feedbacks in the Arctic. Perhaps more important are the potential societal feedbacks to climate events – involving system collapses, refugee crises, health service outages etc. Strictly speaking these are “known unknowns” – we know that we don’t know enough about them. Some truly “unknown unknowns” may emerge as we get closer to Pliocene conditions of course…

But some things can be examined and ruled out. Imminent massive methane releases that are large enough to seriously affect global climate are not going to happen (there isn’t that much methane around, the Arctic was warmer than present both in the early Holocene and last interglacial and nothing similar has occurred). Neither will a massive oxygen depletion event in the ocean release clouds of hydrogen sulfide poisoning all life on land. Insta-freeze conditions driven by a collapse in the North Atlantic circulation (cf. “The Day After Tomorrow”) can be equally easily discounted.

Importantly, not every possibility that ever gets into a peer reviewed paper is equally plausible. Assessments do lag the literature by a few years, but generally (but not always) give much more robust summaries.

2. Reticence

The notion that scientists are so conservative that they hesitate to discuss dire outcomes that their science supports is quite prevalent in many treatments of worst case scenarios. It’s a useful idea, since it allows people to discount any scientists that gainsay a particularly exciting doomsday mechanism (see point #1), but is it actually true?

There have been two papers that really tried to make this point, one by Hansen (2007) (discussing the ‘scientific reticence’ among ice sheet modelers to admit to the possibility of rapid dynamic ice loss), and more recently Brysse et al (2013) who suggest that scientists might be ‘erring on the side of least drama’ (ESLD). Ironically, both papers couch their suggestions in the familiar caveats that they are nominally complaining about.

I am however unconvinced by this thesis. The examples put forward (including ice sheet responses and sea level rise, and a failed 1992 prediction of Arctic ozone depletion, etc) demonstrate biases towards quantitative over qualitative reasoning, and serve as a lesson in better caveating contingent predictions, but as evidence for ESLD they are weak tea.

There are plenty of scientists happy to make dramatic predictions (with varying levels of competence). Wadhams and Mislowski made dramatic predictions of imminent Arctic sea ice loss in the 2010s (based on nothing more than exponential extrapolation of a curve) with much misplaced confidence. Their critics (including me) were not ESLD when they pointed out the lack of physical basis in their claims. Similarly, claims by Keenlyside et al in 2008 of imminent global cooling were dramatic, but again, not strongly based in reality.  But these critiques were not made out of a fear of more drama. Indeed, we also made dramatic predictions about Arctic ozone loss in 2005 (but that was skillful). 

The recent interest in ice shelf calving as a mechanism of rapid ice loss (see Tamsin’s blog) was marked by a dramatic claim based on quantitative modelling, later tempered by better statistical analysis (not by a desire to minimise drama). 

Thus while this notion is quite resistant to being debunked (because of course the reticent scientists aren’t going to admit this!), I’m not convinced that there is any such pattern behind the (undoubted) missteps that have occurred in writing the IPCC reports and the like.

3. Consequentialism

The last point is similar in appearance to the previous, but has a very different basis. Recent social science research (for instance, as discussed by Mann and Hasool (also here)) suggests that fear-based messaging is not effective at building engagement for solving (or mitigating) long-term ‘chronic’ problems (indeed, it’s not clear that panic and/or fear are the best motivators for any constructive solutions to problems). Thus an argument has been made that, yes, scientists are downplaying worst case scenarios, but not because they have a personal or professional aversion to drama (point #2), but because they want to motivate the general public to become engaged in climate change solutions and they feel that this is only possible if there is hope of not only averting catastrophe but also of building a better world. 

Curiously, on this reading, the scientists could find themselves in a reverse double ethical bind – constrained to minimize the consequences of climate change in order to build support for the kind of actions that could avert them.

However, for this to be a real motivation, many things need to be true. It would have to widely accepted that downplaying seriously bad expected consequences would indeed be a greater motivation to action, despite the risk of losses of credibility should the ruse be rumbled. It would also need the communicators who are expressing hope (and/or courage) in the face of alarming findings to be cynically promoting feelings that they do not share. And of course, it would have to be the case that actually telling the truth would be demotivating. The evidence for any of this seems slim. 

Summary

To get to the worst cases, two things have to happen – we have to be incredibly stupid and incredibly unlucky. Dismissing plausible worst case scenarios adds to the likelihood of both. Conversely, dwelling on impossible catastrophes is a massive drain of mental energy and focus. But the fundamental question raised by the three points above is who should be listened to and trusted on these questions?

It seems clear to me that attempts to game the communication/action nexus either through deliberate scientific reticence or consequentialism are mostly pointless because none of us know with any certainty what the consequences of our science communication efforts will be. Does the shift in the Overton window from high profile boldness end up being more effective than technical focus on ‘achievable’ incremental progress or does the backlash shut down possibilities? Examples can be found for both cases. Do the millions of extra eyes that see a dramatic climate change story compensate for technical errors or idiosyncratic framings?  Can we get dramatic and widely read stories that don’t have either? These are genuinely difficult questions whose solutions lie far outside the expertise of any individual climate scientist or communicator.

My own view is that scientists generally try to do the right thing, sharing the truth as best they see it, and so, in the main are neither overly reticent nor are they playing a consequentialist game. But it is also clear that with a wickedly complex issue like climate it is easy to go beyond what you know personally to be true and stray into areas where you are less sure-footed. However, if people stick only to their narrow specialties, we are going to miss the issues that arise at their intersections.

Indeed, the true worst case scenario might be one where we don’t venture out from our safe harbors of knowledge to explore the more treacherous shores of uncertainty. As we do, we will need to be careful as well as bold as we map those shoals.

References
  1. J.E. Hansen, "Scientific reticence and sea level rise", Environmental Research Letters, vol. 2, pp. 024002, 2007. http://dx.doi.org/10.1088/1748-9326/2/2/024002
  2. K. Brysse, N. Oreskes, J. O’Reilly, and M. Oppenheimer, "Climate change prediction: Erring on the side of least drama?", Global Environmental Change, vol. 23, pp. 327-337, 2013. http://dx.doi.org/10.1016/j.gloenvcha.2012.10.008
Read Full Article

Read for later

Articles marked as Favorite are saved for later viewing.
close
  • Show original
  • .
  • Share
  • .
  • Favorite
  • .
  • Email
  • .
  • Add Tags 

Separate tags by commas
To access this feature, please upgrade your account.
Start your free month
Free Preview