| 23 Apr 2026
The one-Layer Antarctic model for Dynamical Downscaling of Ice–ocean Exchanges (LADDIE) version 2.0
Abstract. Projections of Antarctic mass loss and its contribution to sea-level rise are highly sensitive to the applied ocean-driven melting. As fully coupled continental-scale ocean–ice sheet models are scarce, ice sheet models are typically run in standalone configurations, forced with parameterised sub-shelf melting. To provide a physically more detailed alternative to melt parameterisations, we here present version 2.0 of the one-Layer Antarctic model for Dynamical Downscaling of Ice–ocean Exchanges (LADDIE). LADDIE is a two-dimensional model of the upper mixed layer below ice shelves and can reproduce observed spatial patterns in sub-shelf melting. Version 2.0 has improved computational performance due to parallellisation, discretisation on an unstructured mesh, and a more stable time stepping scheme. The model is fully integrated with the UFEMISM ice sheet model, allowing for coupled simulations on the same mesh. We evaluate the model by comparing it to LADDIE 1.0, showing that the simulated melt patterns are consistent across both model versions, whilst the computation time can be reduced by one order of magnitude due to parallellisation. The model is evaluated against an ensemble of 3D ocean models in both idealised and realistic pan-Antarctic domains at 2 km resolution. In both cases, LADDIE melt rates, melt patterns, and melt sensitivities are close to the multi-model mean. An evaluation against four pan-Antarctic satellite estimates, shows an overall good agreement in integrated melt rates per ice shelf, without the need for regional tuning. At a resolution of 120 m, LADDIE is able to reproduce the fine-scaled network of basal channels, observed on Pine Island ice shelf. Finally, we compare an idealised coupled UFEMISM–LADDIE simulation to a simulation with a quadratic melt parameterisation. The coupled simulation produces a threefold increase in grounding line retreat and volume above floatation loss. Based on these results, we conclude that LADDIE 2.0 can be a useful tool to simulate ice–ocean interactions in a computationally efficient way.
This manuscript presents an updated version of the existing one-layer melt rate model LADDIE. The new model version is not just incremental; it includes translation to a new code language, a new mesh structure, parallelisation and full integration with an ice sheet model, making this a significant upgrade to the older version. Differences in the new model version are described thoroughly in a well-referenced and easy-to-follow section of the paper. The model is then assessed against LADDIE v1, multi-model means from ice-ocean coupled ensembles and satellite-derived melt rates in a detailed analysis, showing its strengths and honestly discussing potential drawbacks. Results are then presented of a coupled simulation using the MISOMIP+ protocol, compared to using a parameterised melt. The discussion section raises a few important points which I was pleased to see highlighted.
I enjoyed reading and learning about this work, and am very interested to see future applications of this new model version. I find the manuscript to be exceptionally well-written and contain a good level of detail in its presentation. I found very few instances where I felt the need to suggest improvement. This manuscript is certainly suitable for publication in GMD, and I recommend publication after a few minor revisions, detailed below.
Fig. 3: I don’t find the blue/grey colourscale in panel (c) to be clear unless I zoom in on the image. Perhaps using the same colourmap as panel (f), or something similar, would be a better choice for easy visibility of the differences. It may also be beneficial to show the velocity vectors as well as the speed distribution.
Line 242-3: It looks as if doubling from 16 to 32 does not make much difference, and to get the ~33% time reduction you would need to quadruple to 64. Is this common in other tests than the one shown in Fig.4?
Line 245-6: Related to the above, 32 or 64 cores may produce the most rapid simulations, but looking at the results in Fig.4, I would question whether increasing the number of CPUs beyond 16 is justified by the fairly minimal gains in time. What would your thoughts be on the optimal number of cores for efficient use of computing resources?
Line 333: While LADDIE has higher mean melt rates, it has a much lower median melt rate, which I think should be addressed in this section. In Fig.6 it is clear that LADDIE produces close to zero melt over large areas of the ice shelves, where the multi-model mean from RISE has a baseline ~1m/yr melt across many of these areas. This is particularly noticeable when comparing the melt rates of Amery ice shelf, but is a common occurrence. In many places the satellite estimates in Fig.7 also show this (although notably not on Amery, where estimates actually show more refreezing) Why does LADDIE not replicate this low, but non-zero, melting?