June-July-August 2019

Last update: 11/09/2019

Did you spend your summer relaxing on the beach instead of following new papers coming out? Good for you. And no worries, I kept an eye open and I have got your back. In this post I write about a global sea level reconstruction by Dangendorf et al., a relation between greenhouse gas emissions and Antarctic mass loss by Holland et al., a framework to make high-end sea level projections by Stammer et al. and others papers about ice sheets and sea level projections.

A global sea level reconstruction for the period 1900-2015 was published by Dangendorf et al. They propose a novel approach to tackle the long standing issue of reconstructing the global sea level from tide gauge measurements that are mainly located along the European and North American coasts, especially at the beginning of the 20th century. The hybrid method presented in this work merges two previous approaches. On the one hand a probabilistic technique based on fitting the known spatial patterns of individual sea-level contributors to the tide gauge records. For example, these spatial patterns take into account the fact that when Greenland looses mass, sea level in Scotland is not impacted while in Southern California it is similar to the global average. On the other hand during the satellite altimetry period (1993-now) one can observe what are the main spatial mode of variability in the ocean (EOFs). These EOF modes can then be used to reconstruct sea level over the whole ocean from a few coastal locations. The EOF method performs best at short time scale while the fingerprint method is best at longer time scales so these two methods can be combine in an optimised way to reconstruct sea level.

What do the results show? As we already knew global sea level rose continuously over the period of the study (1900-2015). However, the speed of rise varied between 0.5 and 2 mm/y during the 20th century with no clear trend but recently rose to more than 3 mm/y (Fig. 2). This is because of a sustained sea level rise acceleration since the late 1960th. Over the last 50 years the acceleration stayed rather constant because while the acceleration due to steric effects decreased, there was a compensating increase in acceleration from land ice melt (Fig. S9c). The authors also find that wind stress over the southern ocean between 40-60ºS modulates ocean heat uptake and therefore explain the large variability of the global steric sea level rise pace.

Further south, winds in the Southern Ocean are also believed to have a large climate effect, not on steric sea level but on Antarctic mass loss. Both the Greenland and the Antarctic ice sheet have been loosing mass over the last 20 years. The reason for the Greenland mass loss is widely agreed to be mainly due to external forcing, meaning Anthropogenic greenhouse gas emissions (Bamber et al.). In contrast, experts were rather indecisive on the culprit of recent Antarctic mass loss with around 50% chance that mass loss is due to external forcing and 50% that is is due to natural climate variability. While we know that the Antarctic ice sheet is loosing mass because the ocean is melting it from bellow, so far the reason for increased ocean heat flux towards the ice shelves was unknown. There was strong suspicions that warm ocean water has been pushed towards the shelf because of wind changes but the first convincing argument for this effect was published by Holland et al. over the summer.

This new paper by Holland et al. focuses on changes in wind stress on the shelf break offshore the Pine Island and Thwaites glaciers, two big glaciers of West Antarctica. To overcome the problem that the winds are highly variable in that region and that there are no long term measurements, they use a climate model ensemble. The authors noticed that the wind in that area is highly correlated to sea surface temperature (SST) in the tropical Pacific, for which good observations are available. Therefore, they nudge the tropical Pacific SST towards observations in the model to produce an improved reconstruction of winds around Antarctica. They find that while on decadal time scale the wind change is mostly due to natural variability, there is also a measurable long term trend that has shifted the main winds in that area from westward (pushing the cold surface water towards the coast) to eastward (pushing the cold surface water off-shore and allowing warm sub-surface water to move under the shelf). Since this wind trend is expected to continue over the coming century because of greenhouse gases emissions if Holland et al.’s argument is right then we can also expect that more and more warm water will be pushed towards the Antarctic continent. Add to this mechanism that the water mass itself, called circumpolar deep water (CDW), will also warm up and we are good for new Antarctic ice sheet "surprises".

So what does it mean for sea level projections? Well, since the model used in that study is a standard climate model with atmosphere/ocean/sea-ice components but no ice sheet it is hard to quantify the effect on future sea level. In fact no numerical model has been able to reproduce the increased heat transport towards the shelf and the resulting Antarctic mass loss. There is a long way to go for climate models to be up to the task of making reliable future Antarctic mass loss projections. So far the sea level community doesn’t think this is an issue for projections of the “likely range”, the range in which the future has 66% chance to fall in assuming it follows an RCP scenario (I personally think it is a big issue). However, for high-end sea level projections, that fall above the likely range, the community agrees that traditional IPCC method to make projections is not enough. A new paper by Stammer et al. tackles this problem by designing a method to build consensus around high-end sea level projections. This is a very welcome effort because it is a very hard problem, in which social science also has an important role to play. The idea is that different stakeholders have different needs of high-end sea level scenarios so scientists could provide a discrete scenario. It could look like this (see figure below): In 2100, for an RCP8.5 concentration pathway, using the IPCC method the upper end of the likely range is 98cm. This comes with many assumptions. For example that climate models participating in CMIP5 have a good representation of clouds and that they are able to model the right climate sensitivity, that neither marine ice sheet instability nor marine ice cliff instability will start in Antarctica, that the Atlantic Meridional Overturning Circulation will not collapse, that the Amazonian forest will not burn, that permafrost will melt slowly... Some decision makers do not want to make their plans depending on these assumptions so scientists would pick the most likely assumptions to break and quantify how much additional sea level would result. That would results in a few levels of uncertainty. But the probability for these assumptions to be broken cannot be quantified. It is a situation of deep uncertainty. Users just need to choose what is their level of risk aversion and look at what is the high-end scenario corresponding to that level. The paper only covers the methodology to build the high-end scenarios, it does not attempt to make scenarios but some efforts are ongoing at the UK met office.

Ok I think this post is already too long so I will finish with a quick round of other papers that caught my attentions. Favier et al. compare different ways to represent the ocean/ice interactions under the Antarctic ice shelves with an ocean/ice coupled model. Bassis and Ultee develop a new parameterisation of fractured ice flow. I think this is a big step in the development of ice sheet models. For background, large scale ice sheet models are based on equations of fluid mechanics but ice can break and form icebergs, this is not in the equations and needs to be parameterised. Another bonus of their method is that they are able to provide a first principle estimate of the rate of retreat associated with marine ice cliff instability. Aschwanden et al. make a new projection of Greenland mass loss with a sobering conclusion: "We project that Greenland will very likely become ice free within a millennium without substantial reductions in greenhouse gas emissions". Jevrejeva et al. give a review of recent probabilistic sea level projections and Le Cozannet et al. look into low-end probabilistic sea level projections.

References:

• Aschwanden, A., Fahnestock, M. A., Truffer, M., Brinkerhoff, D. J., Hock, R., Khroulev, C., … Khan, S. A. (2019). Contribution of the Greenland Ice Sheet to sea level over the next millennium. Science Advances, 5(6), eaav9396. https://doi.org/10.1126/sciadv.aav9396
• Bamber, J. L., Oppenheimer, M., Kopp, R. E., Aspinall, W. P., & Cooke, R. M. (2019). Ice sheet contributions to future sea-level rise from structured expert judgment. Proceedings of the National Academy of Sciences, 116(23), 11195–11200. https://doi.org/10.1073/pnas.1817205116
• Bassis, J. N., & Ultee, L. (2019). A Thin Film Viscoplastic Theory for Calving Glaciers: Toward a Bound on the Calving Rate of Glaciers. Journal of Geophysical Research: Earth Surface, 2019JF005160. https://doi.org/10.1029/2019JF005160
• Dangendorf, S., Hay, C., Calafat, F. M., Marcos, M., Piecuch, C. G., Berk, K., & Jensen, J. (2019). Persistent acceleration in global sea-level rise since the 1960s. Nature Climate Change, 9(9), 705–710. https://doi.org/10.1038/s41558-019-0531-8
• Favier, L., Jourdain, N. C., Jenkins, A., Merino, N., Durand, G., Gagliardini, O., … Mathiot, P. (2019). Assessment of sub-shelf melting parameterisations using the ocean–ice-sheet coupled model NEMO(v3.6)–Elmer/Ice(v8.3). Geoscientific Model Development, 12(6), 2255–2283. https://doi.org/10.5194/gmd-12-2255-2019
• Holland, P. R., Bracegirdle, T. J., Dutrieux, P., Jenkins, A., & Steig, E. J. (2019). West Antarctic ice loss influenced by internal climate variability and anthropogenic forcing. Nature Geoscience. https://doi.org/10.1038/s41561-019-0420-9
• Jevrejeva, S., Frederikse, T., Kopp, R. E., Le Cozannet, G., Jackson, L. P., & van de Wal, R. S. W. (2019). Probabilistic Sea Level Projections at the Coast by 2100. Surveys in Geophysics, (0123456789). https://doi.org/10.1007/s10712-019-09550-y
• Le Cozannet, G., Thiéblemont, R., Rohmer, J., Idier, D., Manceau, J.-C., & Quique, R. (2019). Low-End Probabilistic Sea-Level Projections. Water, 11(7), 1507. https://doi.org/10.3390/w11071507
• Stammer, D., Wal, R. S. W., Nicholls, R. J., Church, J. A., Le Cozannet, G., Lowe, J. A., … Hinkel, J. (2019). Framework for High‐End Estimates of Sea Level Rise for Stakeholder Applications. Earth’s Future, 2019EF001163. https://doi.org/10.1029/2019EF001163