Yet another Younger Dryas impact paper

Just when you thought that Holliday et al (2014) had dealt the Younger Dryas impact hypothesis a mortal blow, along comes another paper proclaiming that the hypothesis lives yet.

Kinzie et al (2014) claim that nanodiamonds are indicators of cosmic impacts and look at the evidence of nanodiamonds at the start of the Younger Dryas at two dozen sites across three continents. They find them, and argue that a cosmic impact is the only explanation.

The paper is dependent on the quality of the chronologies used to date the nanodiamond containing layers – if they are not synchronous the hypothesis of a global catastrophe fails. Some of the chronologies are woeful,  for example, the age-depth model from Lake Cuitzeo. This age-depth model is based on only six radiocarbon dates over the last 30,000 years (that would be a low number for a Holocene-length core); the dates are on bulk sediment, so are potentially affected by radiologically-dead volcanic-carbon; many outliers are rejected; and one of these dates is not from the lake core, but from a nearby trench that has been stratigraphically linked to the lake core. This is not the most robust age depth model.

Rather than examining all the age-depth models, I want to look at something that caught my attention in the abstract.

Isotopic evidence indicates that YDB NDs [nanodiamonds] were produced from terrestrial carbon, as with other impact diamonds, and were not derived from the impactor itself.

Isotopic evidence from nanodiamonds! Someone must either have extracted and purified a lot of nanodiamonds or have a very sensitive mass-spectrometer. I want to know more.

More details in the body of the paper

YDB NDs were most likely formed from terrestrial carbon, based on their carbon isotopic composition (Tian et al. 2011; Israde-Alcántara et al. 2012b)

This line of evidence is important as Kinzie et al (2014) use the terrestrial origin  to exclude the possibility that the nanodiamonds are the product of cosmic dust, and so must be the result of a high energy event on Earth.

Time to look at Tian et al. (2011) and Israde-Alcántara et al. (2012), both published in the high-impact PNAS.

Tian et al. (2011) examine a site in Belgium and show that the black layer supposed to mark the start of the Younger Dryas has carbon isotopic values consistent with a terrestrial source. They explicitly state that they did not measure the isotopic composition of the nanodiamonds.

Also carbon isotope measurements and C/N values were determined from the black material of the Lommel YDB layer. The nanodiamond particles in the present material could not be analyzed separately because of their small size.

Israde-Alcántara et al. (2012) do not measure the isotopic composition of nanodiamonds either. Instead they measure the isotopic composition of bulk sediment.

Sediment samples of approximately 1 cm thickness were taken every 5 cm across the critical section between 2.80 and 2.65 m and at 10 cm intervals above and below this section. These samples were quantitatively analyzed for diatoms and pollen assemblages, carbonate (%TIC), organic carbon (%TOC), bulk major-element composition, stable carbon isotopes (both organic and inorganic), organic nitrogen, MSp, NDs, CSp, charcoal, and aciniform soot.

They do, however, mis-cite Tian et al.

Cosmic NDs occur in meteorites and cosmic dust, but Tian et al.  concluded that YDB NDs are not cosmic because they display δ13C abundances (−28.1 to −26.3‰) that are terrestrial.

Kinzie et al (2014) shares several authors with Israde-Alcántara et al. (2012), so they really ought to remember what analyses they ran. This is very shoddy.

Neither paper cited by Kinzie et al (2014) as evidence that the nanodiamonds are terrestrial actually offer any evidence in this direction. Kinzie et al (2014) relies on non-existent isotopic data.

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Holocene forcing, trends and conundrums

Before  Marcott et al (2013) published their synthesis of over 70 Holocene palaeoclimate reconstructions, I didn’t have a strong expectation of how global annual mean temperature should vary over the Holocene, except that changes would be small relative to glacial-interglacial changes. Marcott et al found a warm early Holocene followed by a gradual cooling in the mid and late Holocene. This is a pattern found in many reconstructions from summer-sensitive proxies from northern high latitudes where it mirrors the Holocene trend in summer insolation.

It might seem curious that global annual mean temperatures should follow the seasonal response in one region, but the northern high latitudes have strong positive feedbacks to insolation changes. For example, as summer insolation declines, summers are no longer warm enough to melt all the snow that accumulated in the previous winter, increasing the albedo and leading to further cooling. Such processes are important on glacial-interglacial time scales, so perhaps also in the Holocene.

Liu et al (2014) challenged Marcott et al’s reconstruction, showing that three climate models predicted rising temperatures throughout the Holocene. Liu et al argue that seasonal biases in the reconstructions used by Marcott et al could account for the discrepancy between the proxy data and models.

Liu et al Fig 1. Global surface temperature over the last 22 ka:  reconstructions of Marcott et al (blue) after 11.3 ka and by Shakun et al. (cyan) before 6.5 ka,  model annual mean temperature averaged over the global grid points (black), and model seasonally biased temperature averaged over the proxy sites (red). Models are CCSM3, FAMOUS (□) , and LOVECLIM (○), with the ensemble mean shown by heavy lines and individual members shown by thin lines. Temperature curves are aligned at 1 ka. The ensemble mean model annual temperature averaged over proxy sites is also shown (yellow), whose similarity to the model grid average demonstrates the insensitivity of the temperature trend to the average scheme.

Liu et al Fig 1. Global surface temperature over the last 22 ka: reconstructions of Marcott et al (blue) after 11.3 ka and by Shakun et al. (cyan) before 6.5 ka, model annual mean temperature averaged over the global grid points (black), and model seasonally biased temperature averaged over the proxy sites (red). Models are CCSM3, FAMOUS (□) , and LOVECLIM (○), with the ensemble mean shown by heavy lines and individual members shown by thin lines. Temperature curves are aligned at 1 ka. The ensemble mean model annual temperature averaged over proxy sites is also shown (yellow), whose similarity to the model grid average demonstrates the insensitivity of the temperature trend to the average scheme.

In my previous post, I showed how seasonal biases in proxies can occur. In this post, I am going to think more about the Holocene conundrum.

Some of the major forcings are shown in figure 2 from Marcott et al.

Figure 2 Holocene climate forcings and paleoclimate records. Contour plots of (A) December, (B) June, and (C) annual mean latitudinal insolation anomalies relative to present for the past 11,500 years. (D) Calculated radiative forcing derived from ice-core greenhouse gases (GHG) (CO2 + N2O + CH4). (E) Total solar irradiance anomalies (ΔTSI) relative to 1944–1988 CE derived from cosmogenic isotopes. (F and G) Proxies for the strength of the Atlantic meridional overturning circulation. (H) Volcanic sulfate flux (in kg/km2) from Antarctica and volcanic sulphate concentration (in parts per billion) from Greenland in 100-year bins. Both records are normalized relative to the Krakatoa eruption.

Figure 2 Holocene climate forcings and paleoclimate records. Contour plots of (A) December, (B) June, and (C) annual mean latitudinal insolation anomalies relative to present for the past 11,500 years. (D) Calculated radiative forcing derived from ice-core greenhouse gases (GHG) (CO2 + N2O + CH4). (E) Total solar irradiance anomalies (ΔTSI) relative to 1944–1988 CE derived from cosmogenic isotopes. (F and G) Proxies for the strength of the Atlantic meridional overturning circulation. (H) Volcanic sulfate flux (in kg/km2) from Antarctica and volcanic sulphate concentration (in parts per billion) from Greenland in 100-year bins. Both records are normalized relative to the Krakatoa eruption.

The seasonal and latitudinal distribution of insolation changed over the Holocene due to changes in the Earth’s orbit, but the total amount varied little. Liu et al show that climate models are insensitive to this orbital forcing using both their three models (CCSM3, LOVECLIM and FAMOUS) and 29 models in the PMIP3 mid-Holocene vs pre-industrial runs (mean response 0.1 °C warming since the mid-Holocene).

Greenhouse gases, measured in ice cores, decline in the early Holocene and then increase after 6 kyr BP. Ruddiman (2003) suggested that this increase represented an early Anthropocene contribution to greenhouse gases, as previous interglacials had a monotonic decline in greenhouse gases. More recent work suggests that the trends in greenhouses gases can be explained by natural processes. The increase in radiative forcing from greenhouse gases should yield a warming of ~0.4°C (depending on climate sensitivity).

Solar variability during the Holocene shows high frequency variability but little trend. Volcanic forcing is uncertain but is stable or decreasing through the Holocene (volcanic activity may have been higher at the start of the Holocene in the previously glaciated regions because of unburdening of the magma chambers when the ice melted).

The waning of the large ice sheets in the early Holocene would have reduced albedo (causing warming) and changed circulation patterns. The ice sheets since the last glacial maximum have been reconstructed by Peltier (2004) based on post-glacial isostatic adjustment and other data. There is an animation here.

Figure 3. Holocene ice area. Data from ICE -5g (Peltier 2004).

Figure 3. Holocene ice area. Data from ICE -5g (Peltier 2004). Apologies, the time axis is the reverse of the previous two figures.

I’ve extracted the area of ice from the 1° x 1° resolution ncdf files. For reference, the area of Canada is 107 km2. The ice sheets that covered large parts of North America and Europe melted during the early Holocene, before 7 kyr BP. The well known re-advance of ice in the late Holocene in Norway and the Alps is very small compared to the ice lost in the early Holocene.

Meltwater from the ice sheets will have cooled the early Holocene climate, for example, the 8.2 ka event.

To summarise, changes in ice-sheet albedo, meltwater flux and greenhouse gases will all have acted to make the late Holocene warm relative to the early Holocene. Set against this is the orbital forcing that should give high-latitude warm summers in the early Holocene, but no annual forcing. It would appear difficult to reconcile Marcott et al’s cooling Holocene temperature trends with these forcings. However, I’m not yet convinced. It is possible that feedbacks from the orbital forcing could lead to annual warming from a summer only forcing.

I’m thinking particularly of vegetation climate feedbacks. Two examples:

  • During the early Holocene, forests approached the Arctic Ocean in Siberia under the influence of warmer summers. Forests have now retreated 200-300 km south, and have been replaced by tundra with a higher albedo.
  • During the early Holocene, the Sahara was an area of lakes, grasslands and savannah. In the late Holocene, this lush landscape was replaced by desert which has a higher albedo. The desert is also a source of dust which has a cooling effect on climate.

Two of the models used by Liu et al, CCSM3 and LOVECLIM, have a dynamic vegetation module and should in principle be able to recreate these shifts in vegetation and their climate impacts. FAMOUS, a speeded up version of HADCM3, does not.  It is not clear without digging how many of the 29 PMIP3 models have dynamic vegetation. Those that don’t were instructed to use pre-industrial vegetation, and so will miss vegetation-climate feedbacks, biasing the mid-Holocene – pre-industrial contrast.

I don’t think any of the PMIP3 model have an interactive dust component.

I would be more confident of Liu et al’s Holocene trends if I knew that the behaviour of vegetation in the model was a good match for what is known about Holocene vegetation trends. I’d also like to see if the PMIP3 models with a dynamic vegetation model have a different response to orbital forcing than those that don’t.

I agree with Liu et al that Marcott et al’s reconstruction of global annual mean temperatures may be biased because of the seasonal biases in proxy sensitivity, but I’m not yet ready to accept Liu et al’s progressively warming Holocene as I don’t see many reconstructions with that shape.

We need to better understand the seasonal biases and limitations of proxies to make better syntheses. We also need  independent data. I think the Holocene sea-level curve could help determine whether the proxy data or the climate models are closer to reality.

Sea levels rose by 2-3 m between 7 and 3 ky BP. (IPCC AR5 2013). About 10% of the rise can be attributed to mid-late Holocene  melting on west Antarctica, the rest is presumably from thermal expansion, either due to a warming climate, or a long lag between warming at the start of the Holocene and the deep oceans re-equilibrating. Since 3 ky BP, sea levels have fluctuated only slightly, which does not appear to be consistent with either reconstruction.

I predict there are going to be several papers over the next year or so trying to solve this Holocene conundrum.

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Seasonally biased proxies and the Holocene temperature conundrum

Last year, Marcott et al (2013) published a synthesis of Holocene proxy temperature records showing a warm early Holocene followed by a slight cooling in the mid and late Holocene. Liu et al, in a paper to be published in PNAS, challenge this reconstruction, showing climate model runs that show a progressive warming throughout the Holocene as ice sheets melted and greenhouse gasses increased. Liu et al argue that part of the divergence is due to seasonal biases in the proxies used by Marcott et al and show that the global Holocene trend in Marcott et al can be recreated by averaging the temperature at each proxy location using  seasonal temperature that each proxy is sensitive to rather than the annual mean.

Lui et al Fig 1. Global surface temperature over the last 22 ka:  reconstructions of Marcott et al (blue) after 11.3 ka and by Shakun et al. (cyan) before 6.5 ka,  model annual mean temperature averaged over the global grid points (black), and model seasonally biased temperature averaged over the proxy sites (red). Models are CCSM3, FAMOUS (□) , and LOVECLIM (○), with the ensemble mean shown by heavy lines and individual members shown by thin lines. Temperature curves are aligned at 1 ka. The ensemble mean model annual temperature averaged over proxy sites is also shown (yellow), whose similarity to the model grid average demonstrates the insensitivity of the temperature trend to the average scheme.

Liu et al Fig 1. Global surface temperature over the last 22 ka:
reconstructions of Marcott et al (blue) after 11.3 ka and by Shakun et al. (cyan) before 6.5 ka, model annual mean temperature averaged over the global grid points (black), and model seasonally biased temperature averaged over the proxy sites (red). Models are CCSM3, FAMOUS (□) , and LOVECLIM (○), with the ensemble mean shown by heavy lines and individual members shown by thin lines. Temperature curves are aligned at 1 ka. The ensemble mean model annual temperature averaged over proxy sites is also shown (yellow), whose similarity to the model grid average demonstrates the insensitivity of the temperature trend to the average scheme.

When Marcott et al was published, it got a lot of attention. Tamino showed that the uptick at the end of the record was due to proxy-dropout (not all proxies records continue till the end of the reconstruction). Steven McIntyre made a lot of noise about essentially irrelevant problems with the age-depth models used by Marcott et al (they had had to make new age-depth models for their Monte Carlo methods and had made the assumption that the top of the core was 1950 unless otherwise stated. This is a commonly used assumption, but is not always appropriate).  McIntyre’s concerns about 20th Century patterns in the alkenone records used in Marcott et al are more interesting.

I spent so much time discussing the trivial issues about the age-depth models, I had no energy for considering other potential problems with Marcott et al. The seasonality of the proxies is an obvious candidate, and which Marcott et al give due consideration. In this post, I’m going to first show how these seasonal biases in proxies can occur and then examine how Marcott et al investigated this potential problem.

Many temperature sensitive palaeoceanographic proxies have been used in the Norwegian Sea: diatoms, foraminifera and radiolarian assemblages, alkenones (biomarkers from coccolithophorids), and trace element and isotope geochemistry of planktonic foraminifera. All these proxies are predominantly produced in the spring-summer months as there is very little biological production during the cold dark winter, so we might expect all of the proxies to record a common signal. However, the different reconstructions are very different, as shown by Andersson et al 2010.

Fig. 6. (A) Mean July temperature based on pollen from Tsuolbmajavri, Finland (Seppa and Birks, 2001).  (B) Alkenone derived sea-surface temperatures from the Vøring Plateau (MD95-2011) (Calvo et al., 2002; Jansen et al., 2008). (C) Diatom-based sea-surface August temperature estimates from MD95-2011 (Birks et al., 2002). (D) Foraminiferal-based transfer function sea-surface temperature estimates for summer (JAS) for MD95-2011 (Andersson et al., 2003; Risebrobakken et al., 2003). (E) Radiolarian-based transfer function sea-surface summer temperature estimates for MD95-2011 (Dolven et al., 2002).

Fig. 6. (A) Mean July temperature based on pollen from Tsuolbmajavri, Finland (Seppa and Birks, 2001). Other proxies are from core MD952-11 from the Vøring Plateau (B) Alkenone derived sea-surface temperatures (Calvo et al., 2002; Jansen et al., 2008). (C) Diatom-based sea-surface August temperature estimates (Birks et al., 2002). (D) Foraminiferal-based transfer function sea-surface temperature estimates for summer (JAS) (Andersson et al., 2003; Risebrobakken et al., 2003). (E) Radiolarian-based transfer function sea-surface summer temperature estimates (Dolven et al., 2002). The alkenone and radiolarian reconstructions are included in Marcott et al.

The diatom and alkenone (U37k) reconstructions resemble one another, and share the downward trend since the Holocene thermal maximum with pollen-inferred summer temperature and the decline in summer insolation at these high latitudes as the Earth’s orbit changed. The foraminifera and radiolarian transfer function-based reconstructions have weak but opposing trends to the diatoms and alkenones. Not shown here are the isotope and trace element analyses on the foraminifera that share the same trend as the foraminiferal assemblages.

The critical difference between the proxies reconstructing a declining Holocene temperature and those reconstructing an increasing temperature is the depth habitat of the organisms. Diatoms and the coccolithophorids that produce alkenones are photosynthetic. They are constrained to live in the photic zone, the upper 50m of the water column where there is sufficient light. The foraminifera and radiolaria live over a range of depths. The dominant foraminifera in this area live between about 75 and 250 m.

The depth habitat of the organisms is important because of the seasonal pattern of stratification in the Norwegian Sea. All the organisms are living within the current of warm Atlantic water that flows into the Nordic Seas. In summer, the surface layers of this water mass absorb sunlight and become warmer and less dense, separated from the subsurface water by a thermocline. Consequently the subsurface warms little in summer. In autumn, the surface cools and stormy weather force mixing over the winter months. The temperature of the surface in winter sets the temperature in the subsurface year round. So although all the organisms are growing in summer, the temperature of the water they are living in is set by either the summer or winter.

Over the Holocene, the amount of summer insolation declined, summers became cooler, and this is reflected by the surface proxies. Winter insolation increases slightly over the Holocene. Hence we would not expect surface and subsurface proxies to show the same trends in this region. In other regions the seasonal biases attached to proxies may differ.

Marcott et al were well aware of the potential problems with seasonality and discuss it in the supplementary material. They examine the difference between alike and unalike proxies from the same 5° grid cells and find no difference in the mean difference, so assume that  “that if a seasonal bias exists between proxies, it adds no more uncertainty than that associated with proxy-temperature calibrations.” This is optimistic. First, that any bias is no larger than the variance does not imply that the result will be unbiased. Second, the test is weak as unalike proxies may be sensitive sensitive to the same season, so the number of genuine contrasts may be smaller than it appears.

Marcott et al also run an analysis akin to that in Liu et al, comparing climate model output averaged across the core sites for the annual mean temperature and the seasonal temperatures that the proxies are most sensitive to. The result is surprisingly similar to that obtained by Liu et al – the temperature increases throughout the Holocene – but the difference between the two analyses is smaller, so Marcott et al argue that with the inclusion of proxies with different seasonal biases, the biases have cancelled out.

The final test is to re-make the global Holocene reconstruction with just the proxies defined as annual proxies by the original authors. Here the reconstruction shows the same trend, but with a higher amplitude than the inclusive reconstruction, the opposite of what is expected if seasonal biases are important. This analysis depends on the original authors assignment being correct – some are dubious.

That the seasonality (and perhaps other factors) have proved to be a problem for Marcott et al does not surprise me greatly. Earlier this year I discussed Hessler et al who found that proxies from the mid-Holocene were difficult to reconcile with each other and with models. I warned that if this result was correct, Marcott et al’s reconstruction would be questionable.  

Liu et al is certainly not the last word. Even though they show that by accounting for seasonal biases in the proxies the global mean temperature trends in the model and proxies can be reconciled, the correlation between the trends in the model and individual proxies is near zero. Part of the problem may be the depth assignment of proxies – all reconstructions are assumed by Liu et al to be surface reconstructions. I showed above that depth matters, different Holocene temperature trends can occur at the same locality at different depths.

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Early warning signals before the Bølling transition

Towards the end of the last glaciation, as solar insolation at high latitudes slowly increased as the Earth’s orbit changed, the climate over Greenland suddenly tipped from a glacial climate to an interglacial climate — a warming of over 10°C — in a decade or so. The following warm period, known as the Bølling in northern Europe was short lived, no more than a flicker of warmth, before the climate cooled first into the tepid Allerød and then the frigid Younger Dryas. The next time the climate abruptly warmed, the following warm period, the Holocene, was more enduring.

The rapid warming into the Bølling and Holocene are critical transitions between alternative stable climate states. Critical transitions can be either noise induced or the result of forcing pushing the system until one climate state is no longer stable and the system tips to the other at a bifurcation point. The latter type of critical transition is at least in principle possible to predict due to early warning signals as the system approaches the bifurcation. The three classic early warning signals are increases in autocorrelation, variance and kurtosis as the basin of attraction becomes shallower (See here for an explanation of these indicators).

Several papers have looked for early warning signals before the transitions into the Bølling and Holocene. The usual procedure is to detrend the record and then use a running variance and running autoregressive model over the data. The choice of the bandwidth for the detrending and the window size for the running analysis can be critical.

Dakos et al (2008) find autocorrelation in the GISP2 isotope-temperature record increases weakly and non-significantly before the Bølling transition, and increases strongly and significantly before the Holocene transition in the Cariaco basin grey-scale record. However, variance increases in GISP2 and decreases before the transition in Cariaco (Lenton et al 2012).

Ditlevsen and Johnsen (2010) in the excellently titled paper “Tipping points: Early warning and wishful thinking” argue that both autocorrelation and variance need to increase before a critical transition to be considered an early warning signal. In an analysis of the NGRIP isotope record, they do not find any evidence of early warning signals before the abrupt warming of any of the Dansgaard-Oeschger cycles (including the Bølling transition). This implies that these transitions are noise-induced rather than bifurcations.

Praetorius & Mix (2014) look for evidence of synchronisation between the North Atlantic and Pacific prior to the Bølling transition as an alternative early warning signal, but I think their results are an artefact of their methods.

The evidence for early warning signals before the Bølling transition is underwhelming. Despite this, I am going to argue that the results of a recent paper in Nature indicate that there could have been early warning signals before the Bølling transition but that existing records are not in the right place to detect them.

Thiagarajan et al (2014) use my favourite proxy, clumped isotopes, to reconstruct temperature from cold-water corals across a depth gradient in the North Atlantic. Clumped isotopes rely on the temperature-dependent tendency for heavy isotopes of 13C and 18O to co-occur in carbonate molecules more often than expected by chance. It is a fairly new proxy, and the uncertainties on individual measurements are large, but corals are large enough to support multiple replicates, driving down the uncertainty on the mean.

They date the coral using uranium/thorium dating and use the difference between the expected and observed radiocarbon date – the reservoir age – as a metric of the time elapsed since the water mass was last in contact with the atmosphere.

They find that in the period before the Bølling transition, the thermal structure of the ocean suddenly changes with warm, 14C-depleted  water at depth overlain by cooler water. This inverts the normal temperature stratification and is presumably maintained by a salinity gradient (unfortunately the authors do not try to use 18O and clumped isotopes together to estimate salinity – perhaps the uncertainties are too large). The sudden change in temperature indicates that the warm water has been advected rather than being warmed in situ.

This thermal stratification would be inherently unstable even if supported by a salinity gradient because of a property of water known as thermobaricity. Water is compressed, becoming denser, when subjected to high pressure at depth in the ocean. Warm water is compressed more by high pressures than cold water. So if cold fresh (in an oceanographic sense) water overlies slightly denser warm salty water, any disturbance that brings the warmer water nearer to the surface will reduce the pressure and reduce the density, reversing  the density gradient. The large reservoir of warm saline water will then punch its way to the surface, releasing the heat to the atmosphere, as recorded by the Greenland ice cores. As the warm water cools, it will become dense due to its high salinity and sink, drawing subtropical water north and kickstarting the Atlantic meridional overturning circulation.

Before the warm water punched its way to the surface, there may well have been a host of early warning signals at the boundary between the cold fresh and warm saline waters. As the density difference declined, disturbances that were not quite large enough to cause overturn would cause increasing variance and autocorrelation. It is doubtful that any palaeoceanographic proxy will have the temporal resolution and sensitivity to record these possible early warning signals. Proxies records from Greenland and elsewhere, away from the thermocline, will not show early warning signals.

The inverted thermal gradient did not reoccur at the end of the Younger Dryas: some other process was responsible. So even if the last of the mammoths had identified the early warning signals before the Bølling transition and sought to use this information, they would have been taken unaware by the Holocene transition. So much for the utility of early warning signals.

Oceanographically-aware mammoths should have been aware that the thermal structure of the pre-Bølling Atlantic was unstable and, regardless of early warning signals, taken remedial action. My feeling is that today, we should take a physics based approach to identifying tipping points rather than relying on statistical tools.


Thiagarajan, N. et al 2014. Abrupt pre-Bølling–Allerød warming and circulation changes in the deep ocean. Nature, 511, 75–78 doi:10.1038/nature13472

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Glaciers are dangerous

Nigardsbreen, an outlet glacier of Jostedalsbreen — the largest glacier in continental Europe — is one of the most accessible glaciers in Norway. It is visited by many tourists by boat from the museum Breheimsenteret.

Beautiful and dramatic, but also dangerous. Tragically, blocks of ice falling from the glacier’s snout killed two tourists on Sunday.

Guided tours traverse the glacier, equipped with rope, ice axe and crampons.  I’ve heard these tours wonderful. While, like everything in Norway, they are not cheap, these tours are the only safe way to go on or near the ice.

 

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The tropical thermostat is broken

I mainly work on Holocene and late glacial palaeoclimate, occasionally delving back as far as the last glacial maximum, but the tools I use are of value for reconstructing climate over a longer period, albeit with greater uncertainty. The Pliocene, a generally warm period before the advent of large northern hemisphere ice sheets, is becoming an important target for palaeoclimate research, as its high atmospheric CO2 concentration make it an analogue for future climate.

High latitudes were warmer during the Pliocene — the ice sheets were much smaller, consequently sea-level was ~20m higher than modern, and coniferous forests grew on Greenland.  In contrast, reconstructions of Pliocene tropical climate have suggested little warming.

The apparent stability of tropical climates is part of the evidence that led Prof Richard Lindzen (a man who “never met a negative feedback he didn’t like“)  to propose that negative feedbacks cause low climate sensitivity in the tropics, a sort of thermostat that regulates temperature change. His suggested mechanism — known as the iris — that high-cloud cover contracts when tropical sea surface temperatures (SST) are high causing an increase in outgoing long-wave radiation, has not fared well in the literature. Now the evidence for tropical stability is looking shaky.

The best estimates of Pliocene SST came from the ratio of magnesium to calcium in the shells (tests) of planktonic foraminifera which are constrained by their algal symbionts to live in the photic zone near the sea surface. The Mg/Ca ratio is temperature dependent, but also depends on other factors, in particular the Mg/Ca ratio of sea-water. If the Mg/Ca ratio of sea-water has changed since the Pliocene, Mg/Ca based reconstructions will be biased.

This is what O’Brian et al (2014) argue in a recent paper in Nature Geosciences (see also the associated editorial). O’Brian et al compare reconstructions of tropical SST derived from Mg/Ca ratios of planktonic foraminifera from two biomarkers, alkenones, and TEX86. Both the biomarkers indicate tropical SST ~2 °C warmer than today, suggesting that Mg/Ca reconstructions are biased low. This has several implications such as the global estimate for Pliocene temperature anomaly is too low and that there is no need to invoke a thermostat to regulate topical temperatures.

When I read this paper, my first thought was that coral reefs would struggle to survive under the reconstructed temperatures. A quick check shows that the Caribbean was dominated by free-living corals rather than reef-building corals.


O’Brien, C.L. et al 2014. High sea surface temperatures in tropical warm pools during the Pliocene. Nature Geoscience 7, 606–611 (2014) doi:10.1038/ngeo2194

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Scroll bar defeats Lord Monckton

I’ve been watching some of the videos from the Heartland’s fake climate conference in Las Vegas. It is the real cargo cult: all the trappings of a real conference, none of the substance.

Lord Monckton has a lunchtime keynote: light on the science, heavy on the showmanship, very heavy on the conspiracy theory. Perhaps the biggest conspiracy of all is that the UNFCCC is hiding their plans for World Domination.

If you go to the links where you were supposed to be able to find the documents of those conferences [COP18 & COP19], and you click on the button marked decisions, it is a self-referential link. It just goes back and back to the same page. You will not be able to find the decisions that they took, because they are so embarrassed that they no longer want you to know. The want to be able to get away this process without any demographic scrutiny whatsoever from anyone and we are not going to let them get away with it.[01:12:00]

So lets go to the webpage Monckton cites http://unfccc.int/meetings/doha_nov_2012/meeting/6815/php/view/decisions.php. There is a button on this page marked “decisions”. Click on it. The same page reloads.

Now click the scroll bar and scroll down. What do you see? The documents that Monckton claims are hidden.

The scroll bar, what a devious device, defeats the finest mind amongst the climate sceptic.

Posted in climate, Fake climate sceptics, Silliness | Tagged | 3 Comments