This paper presents a detailed methodology of processing Sentinel-1 radar data (TOPS mode) using an updated module “autoRIFT '' of ISCE platform in order to generate ITS_LIVE Sentinel-1 ice velocity products. The paper walks through the different elements of the sequential processing chain and highlights key points that improve the resolution and accuracy of the velocity products. The paper is clear and generally well-written. I have a few comments and suggestions which may be incorporated for more clarity. 

MAJOR COMMENTS: 

1. The products will be openly available. The module of ISCE platform will also be publicly available. These free resources will be used by many folks across the globe for their scientific analysis or processing data over areas other than polar regions. This paper limits the presentation and analysis of ITS_LIVE velocity products to Greenland, but the products will be available for mountain glaciers as well. The title should reflect this aspect; maybe by adding “polar regions'' in the title. Alternatively, more insights based on presentation and analysis over mountainous regions (e.g. European Alps, High-Asia) should be added in the paper. It is obvious that ITS_LIVE products and associated uncertainties are different in regions other than polar ice sheets.  
2. We have a number of ice velocity products based on Sentinel-1 radar data and it is increasingly challenging which product is the best way to carry out a scientific analysis without processing the raw GRD/SLC data. Boncori et al., 2018 compared ice velocity products from several international research groups, highlighted different strategies on the processing and uncertainty estimation and found significant differences, also recommending a universal approach. This paper provides a new or updated algorithm (which is great) but needs to be compared with similar contemporaneous products (e.g. PROMICE). Otherwise, the scientific users will have to do this exercise or cherry-pick one of the available products. Both will not serve the ongoing efforts of establishing standard method development, ice velocity product generation and documentation. It would be nice to compare Sentinel-1 ITS_LIVE products with previous ITS_LIVE products obtained from optical remote sensing data (e.g. Landsat).  
3. If this paper serves only a method development, there should be some more test cases (e.g. ice shelves in Antarctica, debris-covered glaciers in Alaska/high-Asia) to present the applicability of the algorithm other than Greenland Ice Sheet. 
4. So finally these products will not be average over a certain time-period like PROMICE 21-day ice velocity mosaics? Please clarify and highlight, if this is the case, in your paper as this is a unique aspect.  

MINOR COMMENTS: 

L40: Several satellite derived regional ice velocity products are released annually 

L45: As described in Lei et al., 2021a (CHECK ELSEWHERE) 

L55: 6 days repeat is not everywhere but limited to polar regions and Europe or some key areas of the world. 

L70: Revise “ We do …… Greenland” 

L90: Have you ever considered 2m Arctic DEM instead of GIMP DEM? That may be a better choice for transformation between radar and geographic coordinates. 

L95: There is no reference velocity for mountain glaciers. What will be the approach for those areas?

L100: What do you mean by “successful match”? Based on cross-correlation or similarity function value?

L130: ..the extent of..

L140-145: Repetitive

L175 or elsewhere: “autoRIFT” should be clearly distinguished – italic? 

L180-200: I strongly recommend a graphical representation of an algorithm – clearly distinguishing chip size, overlapping region, search size etc. on images. 

L220-230: It was not very much clear why it was done that way. A lot of parameters with equations break the flow of writing here. Simpler writing with rationale might help us better understand. 

L290: Is this subjective? Any insights? 

L305: 7>>seven

L450: Maybe I miss something, but the slant range displacement component contributes to ground range (East-West (your x) and North-South (your y)) and vertical movement (z) and the azimuth displacement component contributes to x and y only. Your equations don’t consider vertical velocities. It is known that the vertical velocities exist as well due to slope/elevation changes in the flow direction or ablation. Please clarify. 

This study provides a processing chain for Sentinel-1 TOPS mode data. Authors have used a modified module of autoRIFT to generate ice velocity global products. This paper is successful in demonstrating the processing chain and efforts in overcoming associated errors. This study also demonstrated improvement in terms of accuracies and resolution of velocity products. The paper is methodologically well organized.  However, I have a few comments. Authors may include these comments from the reader’s perspective. My sequential comments are;

Abstract: Authors should re-write the abstract clearly indicating quantitative improvements when they say *higher accuracy*, *finer resolution*, *improvements*. In the present abstract, the reader cannot find what level of improvements, how much accuracy, and what resolution authors refer to. In general, this abstract reads very generically as a project report. To attract a wider audience, this abstract should be heavily revised to clearly state main achievements quantitative, limitations of the current product, and comparative analysis with existing data. 

Introduction: This section only focuses on operational velocity product generation attempts. Authors should enrich this section by providing literature on glacier velocity generation in general, the use of glacier velocity in glaciological studies, various ways of deriving velocity fields and uncertainties, and the strengths of different methods. Currently, this introduction section does not discuss existing regional attempts using a variety of methods. After the literature review, the authors should provide gaps in current knowledge and what additional knowledge this study provides to the scientific community.

2.1 Product and methodology overview

2.1.1 Input dataset: This section provides only example input datasets for the Greenland case study. I will suggest including other reference input datasets used for other regions. This can be added in the supplementary information as a table or description. Reference velocity for the Greenland ice sheet is mentioned in the study but I am wondering which stable reference velocities are being used for other parts of the globe. Similarly, input DEMS for other regions should be included in the supplementary information. The impact of varying resolution of DEMs in different regions should be discussed. Have you tried Arctic DEM?

2.1.2 ITS_LIVE Sentinel-1 Image-Pair Data Product

Authors should elaborate *offset tracking success* for readers. What criteria do they use for deciding offset tracking and do they calculate it quantitatively?

“Hence, the selection of the appropriate sensor combination is dependent on the actual use case including data availability, quality, study area, etc.” Such statements are made a couple of times without actually providing clear guidance on these criteria. The authors should clearly state how did they estimate such criteria for different regions on the globe. Authors should provide practical challenges in deciding these criteria while selecting input datasets.

The output glacier velocity maps are generated in 120 m spatial resolution. Is this specifically because computational resources or authors have used a specific criterion for choosing this as the optimal resolution.

How have authors calculated the magnitude of errors? The authors have discussed thoroughly geolocation and ionospheric errors introduced in the analysis and how they tried to overcome these errors. However, the final product error magnitude calculations seem to be missing. If I am not wrong, can you re-direct to the existing literature for elaborating this process?

“This sparse/dense combinative searching strategy substantially improve computational efficiency”. I would like to see numbers on efficiency and improvement.

General comments: Authors have demonstrated the processing on Greenland but state that the products are global. I am wondering if they can describe practical implementation challenges in processing global datasets and how uncertainties associated with other regions are dealt with. This is important because the research community will use these datasets for their research in the coming years and they would like to see practical challenges in the Arctic, Antarctic, mountain areas in the Himalayas, Alps. Also, the major limitation of this paper is that the authors have only focused on Greenland. I will suggest including a good distribution of test sites covering different parts of the globe.

Validation: As we know that there are multiple velocity products are being generated both using SAR and optical methods. This study does not provide any guidance on comparing the present product with existing velocity products. This will be very useful for researchers as they would like to know reliable velocity products for their studies. Similarly, new algorithms are being developed for improvement in velocity products. This study does not comment on state-of-the-art methods and the comparison with other algorithms. Eventually, the scientific community will be benefited from such inter-comparison experiments.

Ground validation: Authors have not mentioned about validation of velocity products with in situ measurements. Have they attempted such validation?

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