Should we take the risk of Antarctic collapse seriously?

The IPCC AR5 sea level chapter considered instability of marine-based sectors of the ice sheets to be unlikely (Church et al., 2013). However, post-AR5 modelling indicates that Pine Island Glacier in Antarctica is already engaged in an unstable retreat (Favier et al., 2014), a situation that is projected to extend to neighboring Thwaites glacier (Favier et al., 2014), and even to East Antarctica (Sun et al., 2014). A recent observational study found an observed sustained increase in ice discharge from the Amundsen Sea Embayment, West Antarctica, from 1973 to 2013 (Mouginot et al. 2014). This prompted this reaction from Eric Steig:

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I am disappointed in how the sea level rise projection uncertainties are presented in the IPCC AR5. The way the numbers are presented makes people believe 98 cm by 2100 is a worst-case scenario which it clearly isn’t. The AR5 does have caveats which explains why it could be more, but unfortunately this is buried in language that clearly goes over the heads of most people.

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We construct the probability density function of global sea level at 2100, estimating that sea level rises larger than 180 cm are less than 5% probable. An upper limit for global sea level rise of 190 cm is assembled by summing the highest estimates of individual sea level rise components simulated by process based models with the RCP8.5 scenario.

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In order to extract the intrinsic information of climatic time series from background red noise, in this paper, we will first give an analytic formula on the distribution of Haar wavelet power spectra of red noise in a rigorous statistical framework.

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It can be quite difficult to interpret what likely exactly means sometimes. For example in the AR5 sea level chapter they report a likely range of 21-33 cm for thermal expansion (RCP8.5 table 13.5). I have taken that to mean that this was the 66% uncertainty interval based on the IPCC uncertainty guideline note (see table 1). However, I just realized that this range was actually calculated as the 5-95% range from CMIP5. From table 1 I would have called that the very likely range. Can anybody explain to me the motivation for calling it the likely range?

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Me at EGU 2014:

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We examined the impact of the 5 & 9 most major volcanic eruptions on global sea level. We construct a record of sea level and its uncertainty since 1854. From this we isolate the volcanic signature which surprisingly behaves very differently than models predict.

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El Nino is not well represented by many climate models.

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I assess the feasibility of multi-variate scaling relationships to estimate glacier volume from glacier inventory data. Scaling laws are calibrated against volume observations optimized for the specific purpose of estimating total global glacier ice volume. I find that adjustments for continentality and elevation range improve skill of area-volume scaling.

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Detection and attribution of past changes in cyclone activity is hampered by biased cyclone records due to changes in observational capabilities. Here we relate a new homogeneous record of Atlantic tropical cyclone activity based on storm surge statistics from tide gauges to changes in global temperature patterns. We examine 10 competing hypotheses using non-stationary generalized extreme value analysis with different predictors

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We review the two main approaches to estimating sea level rise over the coming century: physically plausible models of reduced complexity that exploit statistical relationships between sea level and climate forcing, and more complex physics-based models of the separate elements of the sea level budget. Previously, estimates of future sea level rise from semi-empirical models were considerably larger than those from process-based models.

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Global average calorie intake is: 2940 kCal/capita/day.

We are 7 billion people on Earth.

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