| 05 Jun 2026
Full parallelization of the finite-element Lagrangian sea ice model neXtSIM for kilometer-scale simulations
Abstract. Accurate modeling of sea ice dynamics is a major challenge, but also a key requirement for forecasting its future evolution and assessing its impact on climate change. The sea-ice model neXtSIM is specifically designed for this purpose, relying on a Lagrangian framework to accurately capture highly localized features such as leads and ridges, which likely play an important role in controlling the energy exchanges at the interfaces of the atmosphere-ice-ocean coupled system. Despite a parallelisation effort a few years ago, several components of the code, which are intrinsically required by a Lagrangian framework, such as the remeshing procedure, remained sequential, which created significant bottlenecks that limited the model's overall capabilities. To tackle this problem, we further developed the parallel anisotropic mesh adaptation tool ParMMG2D, which demonstrates excellent scalability up to 512 processors with 20 million elements. This tool has been integrated within neXtSIM to enable parallel remeshing, currently limited to homogeneous isotropic meshes. In addition, parallelization of subsequent interpolation, output writing, and drifting buoy tracking has also been achieved. Together, these improvements now enable kilometer-scale simulations within a reasonable timeframe: a one-year simulation with 2 km elements takes only a few days, while a full season with 1 km elements can be simulated in about a week on 128 processors. Therefore, neXtSIM now stands out as cutting-edge software for simulating highly resolved sea ice dynamics, combining the accuracy of a Lagrangian framework with high computational efficiency.
General comments
The presented manuscript contributes to the well-established neXtSIM model development framework. The primary development introduced is the full parallelization of the Lagrangian sea ice model, which enables kilometer-scale simulations within a reasonable runtime. This full parallelization encompasses a set of improvements to the current version of neXtSIM, most notably the implementation of a parallel anisotropic mesh adaptation tool that addresses a major structural bottleneck in the remeshing procedure of previous parallel version. The authors first validate these tools using controlled test cases before applying them to the full neXtSIM model. They demonstrate that the output of the fully parallelized model is consistent with that of the previous version, while achieving a substantial reduction in simulation time.
Overall, the manuscript is clear and well structured, with a title and abstract that reflect the scope and content of the paper. The introduction clearly outlines the limitations of the current neXtSIM parallel implementation and frames the novel development. However, some parts of the introduction need clarification and details (see Specific Comments). The mathematical formulations are generally clear, though a few additional details noted below could further enhance readability. The methodological advancements are thoroughly described, with the main development (ParMMG2D) reasonably placed in a dedicated section of the paper. A few specific comments on the validation methodology may help strengthen the presentation. Finally, the results are sufficiently clear to prove that the parallelization strategy is effective.
In summary, the developments presented in the manuscript are worthy of consideration for publication in GMD, since the authors address questions within the scope of the journal. The novel contribution of this work lies in the application of tools previously unused within the neXtSIM framework.
Specific comments
Lines 17-18: “...shift in the dynamical regime, characterized by an increase in extreme fracturing events and an acceleration of sea ice drift”. Please, provide at least one reference for both the mentioned characteristics, it is not straightforward that in the upcoming Arctic regime the fracturing events will increase.
Lines 35-42: In this paragraph, the authors do not discuss why they parallelized an open-source library (MMG), which is good, instead of adopting an already parallelized remeshing tool. It can be that the latter doesn’t exist, but please specify.
Equations (6)-(7): Pmax is defined but its meaning is not specified. It would be nice for the reader to have few lines describing why it is important.
Equation (10-11): dcrit is used but not defined.
Line 135-138: Does each process read the full-domain forcing files or just a portion defined in the pre-processing stage? From the last paragraph of Conclusions I guess the first option, however, is not clearly stated.
Line 205: Please, elaborate the meaning of “the meshes must look clean”.
Algorithm 1: It is not referenced within the text.
Line 237-238 and figures 4-5: The validation test results in Fig. 4 display low quality in the final mesh from the function f1, with close to 20% of elements having quality smaller than 0.8. Could you elaborate on these results further? What are the reasons behind and is this result acceptable?
Line 266-267: I find it difficult to understand if there are any reasons why scalability performance is better for the shock wave test case than for the circle test case? Do you have any ideas?
Figure 9: Please, indicate the meaning of the numbers in the caption.
Line 372-373 and section 4.4: Please, clarify what you mean with “each point must be handled individually”. I might have lost something, but I don’t understand why you define a new rectangular partitioning instead of directly printing information from the nodes of the domain decomposition with MPI I/O routines. A mapping from local to global domain and a condition for avoiding simultaneous writing would allow you to efficiently store the information in a binary file (I don’t know if MPI I/O supports NetCDF).
Line 419: Is there any reason why you decided to start the validation process from February?
Figure 15: I think that the line is too thick compared to the dots, this may lead to not easy evaluations, especially in panel (c).
Line 430: For the sake of completeness, please also report the maximum discrepancy between the two models.
Line 433 and Figure 15(c): Do you have any idea of why larger differences between the models arise at local minima and maxima?
Technical corrections
Line 72: ice density does not appear in equation (1) where it is stated, but in (12).
Line 73-74: f (Coriolis factor), 𝜂 (SSH), and g (gravity constant) are not specified.
Line 119: Space missing after “Boost.”
Line 176: not uniform citation style.
References: last three items are not in alphabetical order.