Summary: The paper implements a Newton method with step-size control for solving a full Stokes model describing the dynamics of glacial ice. In idealised diagnostic numerical experiments two types of step size control are compared with each other and to Picard iterations with and without step-size control.

General comments:

The chosen topic is important and the paper is well structured and seemingly without any obvious technical mistakes. My main concern is about the novelty of this paper, for the following reasons:

1. The Newton method is faster than Picard is expected and Newtons method is already used in ice sheet models extensively, even with step size control (e.g. in Elmer/Ice). It is true that Newton iterations do not converge for all cases especially without running a few initial Picard iterations, but for the numerical experiments chosen in this paper my guess is that Newton works in most existing codes already. Perhaps exact step size is new but I think in that case a brief summary of the most common step size control methods in the most used ice sheet models should be provided. Furthermore, a significant superiority of exact step-sizes compared to Armijo is not clear from this paper.
2. In comparison to the previous manuscript which is referred to in this paper: Schmidt, 2013 https://arxiv.org/pdf/2307.02930.pdf In Schmidt, 2013 more mathematical details and proves are given, but the method and experiments seems identical. Is Schmidt, 2013 indented to be published?

Nevertheless, I think the paper can be published after major revisions. My suggestions for addressing my above concerns are:

1. If  Schmidt, 2013 https://arxiv.org/pdf/2307.02930.pdf is not already submitted somewhere, I think the mathematical proofs here are novel enough for publication. I am not sure if the Cryosphere is the best journal for this, but possibly the mathematical proofs could be explained and summarized in the main text, and the proofs themselves be kept in the appendix.
2. Otherwise, a solution which probably fits the Cryosphere better, is to extend the numerical experiments and literature study so that the importance to glaciology is clearer. If the authors can show that it is possible to use Newtons method in realistic simulations in an effective way without initial Picard iterations, I think it is a major contribution to the community.  Specifically the following points should be included:
1. In the introduction, go through the most important ice sheet models (especially those using the full Stokes model) and review what method they are using to resolve the non-linearity of the problem
2. Extend the numerical experiments. If the aim of this paper is to show that some method is better than another and could be useful for an ice sheet modeller, it must be for a relevant example. Most importantly, a time-dependancy (free surface movement) should be introduced. This is important since the first time-step (the only one studied here) usually behaves quite differently in terms of number of iterations, as compared to later time-steps when free surface has relaxed. In a real application, there is also a contact problem between the ice and bedrock, which introduces an extra non-linearity. The more realistic example (3D, variable bedrock) the better. Also, I think CPU-times should be measured rather than only number of iterations.

If the original paper Schmidt, 2013 https://arxiv.org/pdf/2307.02930.pdf  is kept as a separate paper, I think still some of the mathematical details must be added to this paper.  I am lacking some mathematical justification of some of the key points of the paper, for instance the justification of the extra diffusion term in the equations, and explanation behind Algorithm 3.

Specific comments:

The abstract and introduction could flow better. The sentences could be longer or better connected.

L 4 and 5: I think these sentences can be removed from the abstract “For the step size control, we need a minimization problem. Minimizing a specific convex function is equivalent to solving the full-Stokes  equations.”

L 18: nonlinear -> non-linearly?

L 18: make it clearer that the stationary variation of these equations is the standard one

L 56: These spaces are for linear Stokes, see e.g. the work by Belenki et al: https://www.jstor.org/stable/41582741 for the appropriate spaces

L 60: Why do you add a diffusion term? This is non-standard and not included in other ice sheet models, which might make the reader wonder if these results are applicable to their model. I suggest trying to get rid of this term.

L 71: I would not say that Picard is standard. Include some references for ice sheet models that use Picard rather than Newton. Most probably use a combination of the two.

L 92-93: It’s true that in Hirn \mu_0 is 0 (and even delta=0 !) . This should be discussed - why is it not possible to set them to zero in this work?

Algorithm 3: what is the stopping criteria, i.e. how many for-loop iterations do you do?

L 104: For the reader of the cryosphere, I think you should introduce the two step-size control methods with a bit more words, discuss pros and cons etc, rather than just stating the algorithm.

Equation 10-11: Does the fact that the terms are smaller really mean that one can surely say that the solution is not impacted significantly, especially in a time-dependent simulation it is not clear to me.

Figure 2: I think it is misrepresentative to compare to models that are not full stokes, please only include full stokes models for the dashed lines.

About the experiments: I strongly recommend that you add a more complex example, something with more complex geometry and time-dependency. A time-dependent simulation of the arolla glacier maybe.

About the experiments: Add plots with relative error vs CPU-time, to show if the step-size control increases the work per iteration significantly or not

The outlook: This is a little bit informally written.

Dear authors,

Please find the my "Referee Comments" as Editor Comments in the interactive discussion, due to the challenges we encountered in finding a suitable second reviewer.

Best, Ludovic Räss - Topical Editor