Ocean heat uptake prevents polar climate reversibility in HadGEM3-GC3.1-LL climate model - Jeff Ridley; Mark Ringer; Ed Blockley (Climatic Change, 2026)
The reversibility of climate change has seen much discussion – in particular through consideration of scenarios that overshoot a warming target before being cooled through carbon sequestration. The uptake of heat into the deep ocean during warming can result in a lag in the response of global and local climate when warming is reversed. The impact of ocean heat uptake on climate reversibility can be efficiently investigated using an idealised abrupt transition from pre-industrial atmospheric CO 2 concentrations to four times pre-industrial levels followed by an abrupt transition back to pre-industrial levels. New multi-centennial simulations are undertaken, using the HadGEM3-GC3.1-LL climate model, in which abrupt transitions to pre-industrial conditions are simulated after 25, 100, 250 and 1000 years from the start of the existing instantaneous abrupt-4xCO2 CMIP6 experiment. These simulations result in an increasing amount of heat being input to the ocean, which is subsequently released during the cooling phase. We show that the loss of heat from the ocean in the cooling phase is slower than the heat uptake during warming, with the climate, on a multi-centennial timescale, tending towards a warmer state than the pre-industrial control. During the warm state, the Arctic undergoes Atlantification and, after the cooling phase, returns to a quasi-equilibrium state with greater poleward transport of Atlantic water. The Southern Ocean becomes more isolated from the global system during warming and takes up considerable local heat, which is vented through sustained deep convection during cooling. In neither polar region does the sea ice return to its pre-industrial state, and thus we find that the climate system is not readily reversible for high warming levels. This will have implications for climate overshoot in the real world if warming is not controlled.

Editorial: The state of knowledge from operational ice service perspectives: previous and future mandates - Penelope Wagner; Ed Blockley; Ludovic Brucker; Wolfgang Dierking; John Falkingham; Andrew Fleming; Nick Hughes (Frontiers in Marine Science, 2026)

SIPN South: six years of coordinated seasonal Antarctic sea ice predictions - François Massonnet; Sandra Barreira; Antoine Barthélemy; Roberto Bilbao; Edward Blanchard-Wrigglesworth; Ed Blockley; David H. Bromwich; Mitchell Bushuk; Xiaoran Dong; Helge F. Goessling; Will Hobbs; Doroteaciro Iovino; et al. (Frontiers in Marine Science, 2023)
Antarctic sea ice prediction has garnered increasing attention in recent years, particularly in the context of the recent record lows of February 2022 and 2023. As Antarctica becomes a climate change hotspot, as polar tourism booms, and as scientific expeditions continue to explore this remote continent, the capacity to anticipate sea ice conditions weeks to months in advance is in increasing demand. Spurred by recent studies that uncovered physical mechanisms of Antarctic sea ice predictability and by the intriguing large variations of the observed sea ice extent in recent years, the Sea Ice Prediction Network South (SIPN South) project was initiated in 2017, building upon the Arctic Sea Ice Prediction Network. The SIPN South project annually coordinates spring-to-summer predictions of Antarctic sea ice conditions, to allow robust evaluation and intercomparison, and to guide future development in polar prediction systems. In this paper, we present and discuss the initial SIPN South results collected over six summer seasons (December-February 2017-2018 to 2022-2023). We use data from 22 unique contributors spanning five continents that have together delivered more than 3000 individual forecasts of sea ice area and concentration. The SIPN South median forecast of the circumpolar sea ice area captures the sign of the recent negative anomalies, and the verifying observations are systematically included in the 10-90% range of the forecast distribution. These statements also hold at the regional level except in the Ross Sea where the systematic biases and the ensemble spread are the largest. A notable finding is that the group forecast, constructed by aggregating the data provided by each contributor, outperforms most of the individual forecasts, both at the circumpolar and regional levels. This indicates the value of combining predictions to average out model-specific errors. Finally, we find that dynamical model predictions (i.e., based on process-based general circulation models) generally perform worse than statistical model predictions (i.e., data-driven empirical models including machine learning) in representing the regional variability of sea ice concentration in summer. SIPN South is a collaborative community project that is hosted on a shared public repository. The forecast and verification data used in SIPN South are publicly available in near-real time for further use by the polar research community, and eventually, policymakers.

Author Correction: Resolving and Parameterising the Ocean Mesoscale in Earth System Models - Helene T. Hewitt; Malcolm Roberts; Pierre Mathiot; Arne Biastoch; Ed Blockley; Eric P. Chassignet; Baylor Fox-Kemper; Pat Hyder; David P. Marshall; Ekaterina Popova; Anne-Marie Treguier; Laure Zanna; et al. (Current Climate Change Reports, 2020)

Resolving and Parameterising the Ocean Mesoscale in Earth System Models - Helene T. Hewitt; Malcolm Roberts; Pierre Mathiot; Arne Biastoch; Ed Blockley; Eric P. Chassignet; Baylor Fox-Kemper; Pat Hyder; David P. Marshall; Ekaterina Popova; Anne-Marie Treguier; Laure Zanna; et al. (Current Climate Change Reports, 2020)
Purpose of Review Assessment of the impact of ocean resolution in Earth System models on the mean state, variability, and future projections and discussion of prospects for improved parameterisations to represent the ocean mesoscale. Recent Findings The majority of centres participating in CMIP6 employ ocean components with resolutions of about 1 degree in their full Earth System models (eddy-parameterising models). In contrast, there are also models submitted to CMIP6 (both DECK and HighResMIP) that employ ocean components of approximately 1/4 degree and 1/10 degree (eddy-present and eddy-rich models). Evidence to date suggests that whether the ocean mesoscale is explicitly represented or parameterised affects not only the mean state of the ocean but also the climate variability and the future climate response, particularly in terms of the Atlantic meridional overturning circulation (AMOC) and the Southern Ocean. Recent developments in scale-aware parameterisations of the mesoscale are being developed and will be included in future Earth System models. Summary Although the choice of ocean resolution in Earth System models will always be limited by computational considerations, for the foreseeable future, this choice is likely to affect projections of climate variability and change as well as other aspects of the Earth System. Future Earth System models will be able to choose increased ocean resolution and/or improved parameterisation of processes to capture physical processes with greater fidelity.

Should Sea-Ice Modeling Tools Designed for Climate Research Be Used for Short-Term Forecasting? - Elizabeth Hunke; Richard Allard; Philippe Blain; Ed Blockley; Daniel Feltham; Thierry Fichefet; Gilles Garric; Robert Grumbine; Jean-François Lemieux; Till Rasmussen; Mads Ribergaard; Andrew Roberts; et al. (Current Climate Change Reports, 2020)
In theory, the same sea-ice models could be used for both research and operations, but in practice, differences in scientific and software requirements and computational and human resources complicate the matter. Although sea-ice modeling tools developed for climate studies and other research applications produce output of interest to operational forecast users, such as ice motion, convergence, and internal ice pressure, the relevant spatial and temporal scales may not be sufficiently resolved. For instance, sea-ice research codes are typically run with horizontal resolution of more than 3 km, while mariners need information on scales less than 300 m. Certain sea-ice processes and coupled feedbacks that are critical to simulating the Earth system may not be relevant on these scales; and therefore, the most important model upgrades for improving sea-ice predictions might be made in the atmosphere and ocean components of coupled models or in their coupling mechanisms, rather than in the sea-ice model itself. This paper discusses some of the challenges in applying sea-ice modeling tools developed for research purposes for operational forecasting on short time scales, and highlights promising new directions in sea-ice modeling.

Uncertainty estimation for operational ocean forecast products—a multi-model ensemble for the North Sea and the Baltic Sea - Inga Golbeck; Xin Li; Frank Janssen; Thorger Brüning; Jacob W. Nielsen; Vibeke Huess; Johan Söderkvist; Bjarne Büchmann; Simo-Matti Siiriä; Olga Vähä-Piikkiö; Bruce Hackett; Nils M. Kristensen; et al. (Ocean Dynamics, 2015)