Linus Vogt

Thanks for your interest and I'm glad you liked this part. I'm certainly no expert on these instrument uncertainties, but for our purposes they ended up being negligible relative to the scales of interest (i.e., model bias and inter-model spread in sea ice extent).

By linking Antarctic sea ice, cloud cover, deep ocean temperatures, and global warming, our new study led by @linusvogt.bsky.social finds that ocean heat uptake and thermal sea level rise by 2100 could be 3–14% higher, and global surface warming 3–7% greater than previously thought👇

That sounds really interesting, let me know when there is a preprint!

Funnily enough, using HadISST in our study would also have led to an exaggerated "conservative" estimate of high warming, since then the models would underestimate Antarctic SIE even more. But fortunately we are not sailors.

Thanks for the clarification!

Special thanks to @polarocean.bsky.social who had the initial idea for this project, and to all coauthors: @jbsallee.bsky.social, Casimir de Lavergne, @froeltho.bsky.social, and Lester Kwiatkowski.

Two box plots showing the distribution of future global heat uptake with and without an observational constraint. The constrained estimate is larger and less uncertain than the prior.

📈 As CMIP6 models underestimate historical Antarctic sea ice extent on average, this leads to an upward correction of climate projections by 2100 under all considered scenarios:

- OHU +3–14%
- Cloud feedback +19–32%
- Global surface warming +6–7%

A scatter plot showing the relationship between historical Antarctic sea ice extent (x-axis) and future ocean heat uptake (y-axis) across an ensemble of 28 climate models. There is a positive correlation of r=0.87. Also indicated is the observed value of Antarctic sea ice extent, showing that models tend to underestimate it.

Thus, the state of Antarctic sea ice today quantifies the potential for global climate change in the future.

More sea ice now → more warming later

This is evident as a strong correlation across CMIP6 models (and it also holds in CMIP5)

Part of a schematic from a paper showing a transition from an initial climate state to a future climate state under 21st century climate change. In climate models with a cold initial state, the transition is larger than in models with a mild initial state. The "coldness" of the initial state is quantified using Antarctic sea ice extent.

The constraint is based on Antarctic sea ice extent 🧊

Models with more sea ice today also simulate colder Southern Ocean SSTs, a colder deep ocean, and more mid-latitude cloud cover.

In the future, these models lose more sea ice and clouds, amplifying SW cloud feedback, surface warming, and OHU.

Increased future ocean heat uptake constrained by Antarctic sea ice extent Abstract. The ocean takes up over 90 % of the excess heat stored in the Earth system as a result of anthropogenic climate change, which has led to sea level rise and an intensification of marine extre...

🚨🌊 New highlight paper out today in Earth System Dynamics!

We find an observational constraint implying more future global ocean heat uptake, cloud feedback, and warming than the CMIP6 mean.

This contrasts with previous estimates based on past warming trends.

🔗 esd.copernicus.org/articles/16/...

I had an engagement with blogger, failed California gubernatorial candidate, and self-identified reporter Michael Shellenberger this past week, which started out being about this new paper being heralded by climate skeptics as disproving global sea-level acceleration. (LONG 🧵)

🌊
Looking for a #postdoc to join us at @ipsl.bsky.social within the #ANR project #AIAI (AI to improve coupling between the Antarctic 🧊 and the 🌊/🌧️), a collaboration between @igegrenoble.bsky.social , @lsce-ipsl.bsky.social and #LOCEAN!
Deadline: Aug 8th
Apply here: emploi.cnrs.fr/Offres/CDD/U...

Paper just out in AI4Earth led by the incredible @eveapiedagnel.bsky.social. We show how to exploit the ocean’s tight T-S relationship at constant pressure to map trends in salinity from sparse data doi.org/10.1175/AIES.... GMM works well because the relationships are so linear, but why are they?

Will anyone review this paper? Screening, sorting, and the feedback cycles that imperil peer review Scholarly publishing relies on peer review to identify the best science. Yet finding willing and qualified reviewers to evaluate manuscripts has become an increasingly challenging task, possibly even ...

1. Kevin Gross and I just posted a new science-of-science preprint.

This one explores the looming peer review crisis. As many of you know, it's becoming significantly more difficult for journal editors to find scholars willing to serve as peer reviewers for submitted manuscripts.

Studies in History and Philosophy of Science journal homepage: www.elsevier.com/locate/shpsa Understanding data uncertainty Alisa Bokulich", Wendy S. Parker b," " Department of Philosophy, Boston University, United States › Department of Philosophy, Virginia Tech, United States ABSTRACT Scientific data without uncertainty estimates are increasingly seen as incomplete. Recent discussions in the philosophy of data, however, have given little attention to the nature of uncertainty estimation. We begin to redress this gap by, first, discussing the concepts and practices of uncertainty estimation in metrology and showing how they can be adapted for scientific data more broadly; and second, advancing five philosophical theses about uncertainty estimates for data: they are substantive adequacy-for-purpose view of uncertainty estimation, addresses a weakness in a recent philosophical account of data, and provides a new perspective on the "safety" versus "precision" debate in metrology. 1. Introduction Uncertainty is an inescapable part of science. Yet while much has been written in recent years on uncertainty in computational modeling contexts (especially related to climate modeling; see, e.g., Parker, 2010; Frigg, Thompson, & Werndl, 2015; Knutti et al., 2019), comparatively little philosophical attention has been given to uncertainty associated with scientific data collected via observation, measurement, and experiment. Important preliminary work on this topic examines the evaluation of systematic uncertainty in measurement (Staley, 2020), changing conceptions of uncertainty in metrology (de Courtenay & Grégis, 2017; Grégis, 2019b), and the representation of uncertainty when measurements are discordant (Grégis, 2019a). Overall, however, when it comes to uncertainty associated with scientific data obtained via observation, measurement, and experiment—what we will call "data uncertainty"-the territory remains largely unexplored from a philosophical point of view. Conception…

⏰ Free access to read & download thru August 20 the final published version of Wendy Parker & my paper "Understanding Data Uncertainty" at this link ⬇️
authors.elsevier.com/c/1lMUI8yuR6...

#philsci #metasci 🧪 ⚒️

Influence of Wave‐Induced Variability on Ocean Carbon Uptake Wave effects introduce high-frequency variability and amplify the air-sea CO2 flux seasonality, with the largest impacts during storms Wave effects enhance carbon storage and amplify hemispheric ...

Do bubbles matter for ocean carbon uptake? 🌊🫧
Yes, especially for local CO2 fluxes, where wave breaking can enhance variability by up to 40%. That’s an important consideration for #mCDR, where fluxes could otherwise be miscalculated. More in our paper here: [https://doi.org/10.1029/2024GB008382]

Check out the full paper for a detailed analysis of all the inter-model links between stratification patterns, overturning, MLD, and OHUE.

Huge thanks to my (now former 🥲) PhD advisors, @jbsallee.bsky.social and Casimir de Lavergne!

A map showing the difference in historical upper-ocean stratification between the CMIP6 ensemble mean and observations (ECCO state estimate). The models have a more strongly stratified upper ocean in the Tropics, midlatitude Southern Ocean, and subpolar North Atlantic.

We further find that the previously assumed importance of the AMOC for OHU efficiency can be explained by an inter-hemispheric connection in stratification strength between these two regions.

As CMIP6 models are too stratified in precisely these regions on average, they tend to underestimate OHUE.

A map showing the inter-model correlation coefficient between local upper ocean stratification and OHUE. In the mid-latitude Southern Ocean and the subpolar North Atlantic, stronger stratification is associated with lower OHUE across models.

We show that upper-ocean stratification inhibits OHU efficiency in the Southern Ocean and the subpolar North Atlantic.
This is because stratification in these regions is linked to large overturning cells: the Southern Ocean upper cell and the AMOC.

So which oceanic parameters are responsible for setting the value of the OHU efficiency?
Many answers have been previously proposed, including AMOC strength, mixed layer depths, and stratification.

In our paper, we use an ensemble of CMIP6 models to disentangle this issue.

A violin plot showing the distribution of ocean heat uptake efficiency (OHUE) across 28 CMIP6 models. The OHUE values span a range of approx. 0.5 -- 1 W/m²K

In observations, the OHU efficiency in recent decades was around 0.6 W/m² per °C of global warming (Cael 2022, doi.org/10.1029/2022...).

However, current-generation climate models simulate a large range of values for this quantity, almost spanning a factor of 2:

The ocean buffers climate change by removing heat from the atmosphere and storing it at depth.

This effect can be quantified by the "ocean heat uptake efficiency", the amount of heat uptake per degree of global warming.

OHU efficiency = OHU / ΔT

Stratification and overturning circulation are intertwined controls on ocean heat uptake efficiency in climate models Abstract. The global ocean takes up over 90 % of the excess heat added to the climate system due to anthropogenic emissions, thereby buffering climate change at Earth's surface. A key metric for quant...

New paper alert! 🌊

What processes control the efficiency of ocean heat uptake under CO₂ forcing?

We show that Southern Ocean stratification and overturning are key, check out our publication in Ocean Science here:
doi.org/10.5194/os-2...

More details below 🧵👇

Sea ice controls net ocean uptake of carbon dioxide by regulating wintertime stratification - Communications Earth & Environment Interannual variability of ocean uptake of carbon dioxide is governed by winter sea ice cover, according to analysis of carbonate chemistry observations along the West Antarctic Peninsula.

📢 New paper alert! 📢

New insight into how sea ice controls the ocean uptake of carbon dioxide around Antarctica, obtained from the unique year-round Rothera Time Series.

Delighted to be part of this study, led by the very excellent Elise Droste.

🧪❄️🥼🌊

www.nature.com/articles/s43...

Photo of the a large group of GISS employees/colleagues in front of Toms Restaurant with a prominent street sign saying "112th St" taken from the middle of Broadway. Credit: Tricia Baron.

Last day at the GISS building (Wed. May 28th). 🥲

Great panel discussion, although sad that this was probably my first and last time visiting this venue (for the foreseeable future)

Hi David, I'm not sure if I am added as a contributor yet, if not could you add me please?

Interested in the freshwater distribution and variability in the Southern Ocean 🌊 ?

Come by my #EGU25 presentation where I will show new insights from oxygen stable isotopes!

🗓️: Monday April 28
🕰️: 14:32 - 14:42
⛓️‍💥: meetingorganizer.copernicus.org/EGU25/EGU25-...

Internal variability effect doped by climate change drove the 2023 marine heat extreme in the North Atlantic Communications Earth & Environment - The 2023 North Atlantic marine heatwave was driven by an extreme phase of internal atmospheric variability but would have been impossible without the doping...

🌊 The N.Atlantic has been experiencing extreme T°C in 2023. This situation raises a number of questions: Have we missed something? Do climate models allow us to understand such an event, or have we entered a new climate regime?
We attempted to answer these questions in this study:
rdcu.be/eh0e8
1/14

Composite model-based estimate of the ocean carbon sink from 1959 to 2022 Abstract. The ocean takes up around one-quarter of anthropogenically emitted carbon and is projected to remain the main carbon sink once global temperatures stabilize. Despite the importance of this n...

A new estimate of the composite model-based estimate of the annually averaged ocean carbon sink. 🌊

This composite model-based estimate of the ocean carbon sink from 1959 to 2022 is similar in magnitude to the best estimate of the Global Carbon Budget but 70 % less uncertain.

Key takeaways from our study on the record-breaking global sea surface temperature jump in 2023-24:
• A rare 1-in-512-year event
• Only possible due to human-caused global warming
• Climate models capture it—no signs of unexpected climate change

More details below 👇