Heuzé et al. (2023) The deep Arctic Ocean and Fram Strait in CMIP6 models

C. Heuzé, H. Zanowski, S. Karam, and M. Muilwijk (2023), The deep Arctic Ocean and Fram Strait in CMIP6 models. Journal of Climate, vol 36, pp 2551–2584, doi:10.1175/JCLI-D-22-0194.1.

This paper describes biases in the CMIP6 models’ representation of the Arctic Ocean, from the Atlantic layer down. Although this study reports on only 14 models, we originally computed the biases on the same 36 models as Heuzé (2021).

  • hydrographic biases: The Atlantic Water is too deep (400 m on average) and too cold (0.5 deg C on average), while the deep and bottom waters are too warm (1 deg C on average). Or rather, for most models, there’s no real distinction between the various water masses. The properties are also not changing throughout the Arctic, even though they should:
Mean temperature profile for each model and basin, compared to observations in black. After Heuzé et al. (2023)
  • ventilation: Two models clearly have dense water overflows in St Anna Trough, and another one might but it could not be detected with the monthly output. We found a strong disconnect between shelf properties / dense water overflows and polynya activity that needs further investigating. Only one other model has some relatively-deep convection instead of overflows.
  • circulation within the Arctic: Not very well represented, but until we have better velocity data in the Arctic and more straightforward ways to un-rotate the model grids, we cannot be more specific. The age of water diagnostic was not useful as it was available for only half the models, and these models used different protocols anyway.
  • Fram Strait: Volumes fluxes in and out are too weak, but Fram Strait itself is biased warm, so the heat fluxes appeared correct enough, albeit not necessarily at the correct depth or east-west location.

And now what?

For starters, we need more observations. Obviously the models are incorrect in the hardly-observed deep Arctic!

We also need more model diversity. Isopycnal and terrain following grids seemed better (as expected) at representing overflows. Higher resolutions, directly or via grid refinment, are required to better represent the bathymetry, which drives most of the circulation. And “polar-friendly” parameterisations need to be routinely deployed.

See also our companion paper Muilwijk et al. (2023) that details why these biases matter, focussing on future stratification and sea ice.

Download the full-text here.

Research theme: Arctic Polynyas

Project “Monitoring Arctic Polynyas from Space (MAPS)”, funded by the Swedish National Space Agency, grant 2022-00149.
Ca 5.3 million SEK. I am the PI.
January 2023 – December 2026

The aim of the project is to determine the variability and improve the retrievability of polynyas in the Arctic. The three sub objectives are:

  • To determine why the polynyas open where and when they do in the Arctic, both in winter and in summer, both for coastal and open-ocean / hybrid ones;
  • To determine why they change shape while they are open, in particular the respective roles of dynamics and thermodynamics, and how predictible this is;
  • To model the air-sea fluxes and more generally the impact of the polynyas on the weather, in order to (eventually) improve the polynya retrievability.


  • A PhD student, whose recruitment is ongoing;
  • Myself as main supervisor, and for the first two objectives;
  • Luisa Ickes from Chalmers as co-supervisor, and for the third objective;
  • Collaboration with Kay Ohshima, Hokkaido University, Japan.


Nothing yet, come back later 🙂

Muilwijk et al. (2023) Divergence in Climate Model Projections of Future Arctic Atlantification

M. Muilwijk, A. Nummelin, C. Heuzé, I.V. Polyakov, H. Zanowski, and L.H. Smedsrud (2023), Divergence in Climate Model Projections of Future Arctic Atlantification. Journal of Climate, vol 36, pp 1727–1748. doi:10.1175/JCLI-D-22-0349.1

In the companion paper Heuzé et al. (2023), we showed that the CMIP6 models are extremely biased in the Arctic Ocean. This study investigates whether it matters, focussing on stratification.

TL;DR: yes, biases matter. They’re so strong that models do not agree regarding the future of Arctic stratification, and that matters for the future of sea ice.

Stratification is changing in the Arctic. We show that since the 1970s, it has increased in the Amerasian Arctic but weakened in the Eurasian Arctic.

Using a new method, more adapted to biased climate models during climate change runs than the standard ones based on fixed thresholds, we compute the stratification of the upper ocean, all around the Arctic, until 2100 in the historical and SSP5-8.5 runs.

And we see things like this:

Stratification changes in two basins of the Arctic, until 2100, for each CMIP6 model in this study. Adapted from Muilwijk et al. (2023)

That is, a strong agreement among models that stratification will continue to increase in the Amerasian Arctic, but no agreement whatsoever in the Eurasian Arctic. This is because of different rates of changes in properties in the upper ocean vs the Atlantic layer, which, besides, are both differently-biased in the different models.

Finally, unsurprisingly, the models that project an Atlantification of the Eurasian Arctic (decrease in stratification) also project a strong sea ice decline.

Download the full-text here.

Zhou et al. (2023) Sea Ice Production in the 2016 and 2017 Maud Rise Polynyas

L. Zhou, C. Heuzé, and M. Mohrmann (2023), Sea Ice Production in the 2016 and 2017 Maud Rise Polynyas. Journal of Geophysical Research Oceans, vol 128, pp e2022JC019148, doi:10.1029/2022JC019148

Zhou et al. (2022) determined why the Maud Rise Polynyas opened. In this subsequent study, we looked at whether it mattered, i.e. the heat and moisture fluxes and resulting sea ice production within the polynya after it had opened.

The main points are:

  • That the sea ice production within the open-ocean polynyas of 2016 and 2017 was of the same order of magnitude than that of the largest coastal polynyas, often dubbed “ice factories”.
  • That this was the first study, to the best of our knowledge, where we estimated the heat flux from the ocean to the ice and atmosphere in the Maud Rise polynya region using year-round autonomous profiling floats.
  • That all methods to estimate sea ice production are highly sensitive to the choice of parameters / reanalysis data that have to be used instead of inexistent in-situ observations. Or, as usual, that more observations are urgently needed.
Daily sea ice production on the maximum extent of the 2017 Maud Rise polynya. Adapted from Zhou et al. (2023).

Download the full-text here.

Konrad-Schmolke et al. (2022) Discrimination of thermodynamic and kinetic contributions to the heavy rare earth element patterns in metamorphic garnet

It’s about rocks. I won’t lie, I too am surprised I am a co-author on this paper.

The lead author is a colleague from my department. Some point late 2021 / early 2022, he sent a desperate plea for help to “those who can code”: He needed to implement the heat diffusion equation in Matlab. It’s something I had done many times before and by some miracle I had a few spare hours then, so I did it for him. In the following days, I helped him here and there to refine it. Many months later, I helped put the script into words for the paper. But that’s about it.

Cool paper though, if you’re into garnets and how they form.

Click here to download the full-text.

Heuzé et al. (2022) It’s high time we monitor the deep ocean

C. Heuzé, S. Purkey, and G.C. Johnson (2022) It’s high time we monitor the deep ocean. Environmental Research Letters, vol 17, pp 121002. doi:10.1088/1748-9326/aca622

Earth is 71% ocean, 79% of which is deeper than 2000 m. Why 2000 m? That’s the current depth limit of our most advanced autonomous oceanographic instruments.

Put more bluntly: the largest component of the climate system is hardly observed. We counted; 200 000 profiles going deeper then 2000 m vs 6.5 million in the upper 500 m (that’s 3% if you prefer it this way). I knew it was bad, but even I am shocked.

See for yourself on the map below: Anywhere where you can see some blue in the background, we have 0 hydrographic profile there.

So unsurprisingly, models are bad at representing the deep ocean, but even if we had plenty of observations, they would still struggle as most of their geometry and settings are designed for the rest of the world.

Why should you care? Because there is A LOT of water down there, and it is warming. And when water warms, it expands, and that is very bad news for people like me who live by the coast.

We finish on some comparatively good news: The technology to observe the deep ocean is ready, and modellers can investigate alternative designs. All everyone need to start monitoring the deep ocean is money (easy, right?).

Click here to download the full-text

Figure 1 from Heuzé et al. (2022): shades of blue show the sea floor depth; yellow dots, where deep profiles have been collected AND are publicly available (looking at you Arctic Ocean). The more blue you can see, the least studied the region.

Gong et al. (2022) Of Atlantic Meridional Overturning Circulation in the CMIP6 Project

X. Gong, H. Liu, F. Wang, and C. Heuzé (2022). Of Atlantic Meridional Overturning Circulation in the CMIP6 Project. Deep Sea Research Part II: Topical Studies in Oceanography, p.105193, doi: 10.1016/j.dsr2.2022.105193

The Atlantic Meridional Overturning Circulation or AMOC is one of the most famous climate tipping points, even mentioned in disaster movies. But its future is still uncertain, as climate models do not represent it as accurately as we wished.

In this publication, we computed the mean state and variabilities of the AMOC in the latest generation of global climate models used by the IPCC, a.k.a. CMIP6 models, and determine whether the representation of the AMOC has improved since CMIP5. The answer is: it depends…

The CMIP6 models disagree regarding the sign of the current trend in the AMOC, with several even saying that there is no trend. Adapted from Fig.6 of Gong et a. (2022).

The models agree more with each other in terms of AMOC value now in CMIP6 than they did in CMIP5, but disagree when it comes to the variability. More worryingly, while most CMIP5 models had the AMOC weakening currently, CMIP6 models now diverge: half say it weakens, and half say it does not or even increases. And this divergence persists when looking at the climate change scenarios. I personally think that it is not surprising given their inaccurate representation of deep water formation in the North Atlantic (see e.g. my publication [22]), but I am biased.

Download the full-text here.

de Boer et al. (2022) The impact of Southern Ocean topographic barriers on the ocean circulation and the overlying atmosphere

A.M. de Boer, D.K. Hutchinson, F. Roquet, L.C. Sime, N.J. Burls, and C. Heuzé (2022) The impact of Southern Ocean topographic barriers on the ocean circulation and the overlying atmosphere, Journal of Climate, vol 35, pp 5805–5821, doi:10.1175/JCLI-D-21-0896.1

Does the seafloor matter for the climate? More specifically, if the under-water mountains were gone, would any climate process be affected? We conducted four model experiments where we flattened a part of the seafloor around the Southern Ocean to answer that question.

The entire climate system was impacted, from the formation of deep water to precipitation. Which in hindsight is not surprising: like mountains on land, these under-water mountains block the flow and force it to go around, taking a longer, different route. If you remove the mountains, the flow can now take the shortest route from A to B. In the Southern Ocean, that meant that the entire water column was modified, fronts were relocated, modifying the temperature/pressure gradients at the ocean surface and lower atmosphere, hence even changing precipitation patterns.

That is: another proof that the deep ocean matters 🙂

The modified Southern Ocean bathymetry: in the red boxes, the usual underwater mountains have been replaced with a flat, deep seafloor. Adapted from Fig. 1b of de Boer et al. (2022)

Download the full-text here.

Mohrmann et al. (2022) Observed Mixing at the Flanks of Maud Rise in the Weddell Sea

M. Mohrmann, S. Swart, and C. Heuzé (2022) Observed Mixing at the Flanks of Maud Rise in the Weddell Sea, Geophysical Research Letters, vol 49, e2022GL098036, doi:10.1029/2022GL098036

At the beginning of his PhD under our supervision, Martin Mohrmann deployed two high frequency autonomous profilers with under ice capability by Maud Rise. That means that even in the middle of winter, we have daily profiles of the water column. The “fun” thing is that they drifted in opposite directions, so their synchronous sampling of two different locations revealed crucial spatial effects in that region.

Key findings (copied from the paper):

  • High frequency (1–3 days) float profiles were collected over both Maud Rise and its vicinity over several seasonal cycles
  • Temperature and salinity below the mixed layer are strongly bathymetry-dependent at Maud Rise
  • Enhanced spiciness variability indicates intrusions and mixing between Maud Rise Deep Water and the surrounding Warm Deep Water

Stay tuned for paper number 3, to be submitted soon, where these profilers are compared to older floats to this time determine the temporal effects.

Download the full text here.

Snoeijs-Lejonmalm et al. (2022) Unexpected fish and squid in the central Arctic deep scattering layer

P. Snoeijs-Leijonmalm, H. Flores, S. Sakinan, N. Hildebrandt, A. Svenson, G. Castellani, K. Vane, F.C. Mark, C. Heuzé, S. Tippenhauer, B. Niehoff, J. Hjelm, J. Hentati Sundberg, F.L. Schaafsma, R. Engelmann and The EFICA-MOSAiC Team (2022) Unexpected fish and squid in the central Arctic deep scattering layer, Science Advances, vol 8, doi:10.1126/sciadv.abj7536

During the MOSAiC expedition, as the ship was embedded in the sea ice pack, one of the ways through which biodiversity and abundance were measured was via the (hydroacoustic) backscatter of the “deep scattering layer”. We find here that the backscatter is strongly correlated to the water mass properties: life, and there’s quite a lot of it, sits primarily in the comparatively warm Atlantic layer.

The team also collected fish samples and recorded hours of video footages. These reveal that, unexpectedly, that layer also contained healthy polar cods and squids.

Extract from Snoeijs-Lejonmalm et al. (2022) Fig. 6: Squid happily swimming around caught on camera

The abundance is way too low for fisheries, but these results prove that the ice-covered Arctic Ocean is far from being the desert it’s often described as (CH’s personal opinion: and consequently, it should be protected accordingly).

Download the full-text here.