the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Contrasted climatologies in Pamir and Central Himalaya highlighted from MAR high-resolution atmospheric reanalysis over 1950–2025
Abstract. High Mountain Asia (HMA) hosts the largest mass of terrestrial ice outside the polar regions, where combined glacier and snow melting with high precipitation rates supplies water to hundreds of millions of people. HMA hydroclimate is controlled by complex topography that shapes the contrasting atmospheric circulation patterns of the monsoon influence in the South and the westerly fluxes on the West, making particularly challenging the understanding of climate variability in this area. Despite its importance, large observational gaps persist, particularly at high elevation, while the coarse resolution of global climate products and the limited spatial or temporal coverage of existing high-resolution simulations hinder robust analyses of long-term climate variability and trends. Here, we present high-resolution (7 km) simulations performed with the regional climate model MARv3.14 over two climatically contrasted regions of HMA: the westerly-dominated Pamir and the monsoon-dominated Central Himalaya. Covering the 1950–2025 period, these experiments constitute, to our knowledge, one of the longest continuous high-resolution regional climate simulations available over these regions. Model skill is evaluated using multiple gridded observational and reanalysis datasets, satellite-derived snow products, and extensive in situ observations, with a particular focus on temperature, precipitation, snow cover, and strong precipitation events. MAR successfully reproduces the main hydroclimatic characteristics of both regions despite their contrasting climatic influences. It captures the seasonal evolution of temperature, ranging from nearly 30 °C in the lowlands to below −20 °C at the highest elevations, the winter–spring precipitation maximum in the Pamir (up to ~110 mm ⋅ month⁻¹), the summer monsoon peak in the Central Himalaya (up to ~550 mm ⋅ month⁻¹), and the seasonal migration of the snowline from ~3800 to ~4800 m in the Pamir and from ~4700 to ~5400 m in the Central Himalaya. The evaluation reveals an elevation-dependent precipitation bias, characterized by underestimated precipitation at low elevations (<40–60 mm ⋅ month⁻¹), and excessive snowfall accumulation at high elevations, which is associated with cold temperature bias (<2–4 °C) and an excessive snow persistence. High-resolution dynamical downscaling substantially improves the representation of orographic precipitation and its spatial distribution over the Khumbu area compared to the driving ERA5 reanalysis. These simulations provide a new long-term climatic reference for the Pamir and Central Himalaya and a validated modelling framework for investigating climate variability, cryosphere evolution, and natural hazards, as well as high-resolution atmospheric forcing for impact models such as glacier mass balance, snowpack, and hydrological models. The validated model configuration also provides a robust and transferable framework for extending the simulations to the entire High Mountain Asia domain.
- Preprint
(8155 KB) - Metadata XML
-
Supplement
(6219 KB) - BibTeX
- EndNote
Status: open (until 14 Dec 2026)
-
CEC1: 'Comment on egusphere-2026-4572 - No compliance with the policy of the journal and stop of peer-review', Juan Antonio Añel, 02 Nov 2026
reply
-
AC1: 'Reply on CEC1', María Santolaria-Otín, 06 Nov 2026
reply
Dear Juan A. Añel,
Thank you for your time. We fully understand the importance of the GMD Code and Data Policy and strongly support the principles of open and reproducible science. We have therefore made several modifications to our submission to address your comments and improve the accessibility and reproducibility of our work.
Regarding the MAR model code and simulations, we have updated the Code and Data Availability and section to include a link to a public repository containing the MAR model source code, together with documentation and a tutorial explaining how to run the model. We would like to point out that MAR is a computationally demanding regional climate model requiring appropriate computing infrastructure and a relatively complex configuration. Therefore, although the source code is publicly available, reproducing the simulations requires more than simply downloading and running the model on a standard computer.
To facilitate reproducibility, we have also created two new Zenodo repositories, one for each simulation domain (Pamir: https://zenodo.org/records/23921900 and Central Himalaya : https://zenodo.org/records/24011336 ). These repositories include README files describing the specific model configuration and the main steps required to reproduce the simulations over High Mountain Asia. We have additionally included the corrected ice mask referred to in the manuscript, which is an essential input for reproducing our experiments. The README files also provide links to the MAR source code and the relevant documentation.
Regarding the observational datasets listed in Table 1, we have further revised the Code and Data Availability section, providing persistent identifiers (DOIs) whenever available, in addition to the references already included in the table. Most of these datasets are produced and maintained by independent data centres or research groups and are already publicly accessible through their respective repositories. As we are not the producers of these datasets, we believe that directing readers to their original repositories is the most appropriate approach, both to preserve data provenance and to ensure that users access the authoritative versions of the datasets. Some datasets, however, do not have individual DOIs beyond their associated publications or dataset references.
To further facilitate the reproducibility of our processing workflow, we have also included the scripts used to postprocess some of these datasets, particularly the HMA-SR product (~3.3TB) (e.g., script ‘method_snow_HMA_SR_aggregation_byyear.py’ in https://zenodo.org/records/24012148). These scripts document the processing steps required to aggregate the original, high-resolution data to the common kilometre-scale grid used in our study, following the methodology described in the manuscript.
We would like to emphasise that we are fully committed to open and reproducible science. We are very happy to make our simulations, model configuration, input files generated for the experiments, and all the codes developed for this study openly available. We have made a particular effort to ensure that the dataset produced in this work can be accessed and reused by the scientific community, as it provides valuable atmospheric forcing for snow, glacier and hydrological modelling applications.
Thank you again for your time and consideration.
Best regards,
The authors
Citation: https://doi.org/10.5194/egusphere-2026-4572-AC1 -
CEC2: 'Reply on AC1', Juan Antonio Añel, 06 Nov 2026
reply
Dear authors,
Many thanks for your reply. Unfortunately, it does not address most of the issues I raised in my previous comment, so your manuscript remains non-compliant with the journal's policy. Namely:- In your reply, you say that you have shared the code of the model in a Zenodo repository; however, you do not provide the permanent handle, link, or citation for it. You must publish it here and include it in any reviewed version of your manuscript.- In your reply, you do not include the repositories for the datasets used in your manuscript. Again, you say you have done it, but the information is missing in your reply. Moreover, you say you point readers to the original data sources. Please note that we can accept links and citations to the original sites only if they comply with the requirements outlined in my previous comment. If they do not comply, you must store them in a new repository that complies. I want to note that we cannot accept the judgment in your reply that you do not think you should republish data produced by others. Only the fact that laws or licenses expressly prohibit you from publishing a copy of the data would exempt you from your responsibility to make them available to ensure the long-term reproducibility of the work presented in your manuscript.Therefore, please reply to this comment with links and citations (including permanent handlers) for the code and data used in your work, so we can continue considering it for peer review in the journal.Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2026-4572-CEC2
-
CEC2: 'Reply on AC1', Juan Antonio Añel, 06 Nov 2026
reply
-
AC1: 'Reply on CEC1', María Santolaria-Otín, 06 Nov 2026
reply
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 279 | 101 | 30 | 410 | 56 | 30 | 30 |
- HTML: 279
- PDF: 101
- XML: 30
- Total: 410
- Supplement: 56
- BibTeX: 30
- EndNote: 30
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
In your "Code and Data Availability" statement you do not include a repository for the code of the model used in your work. Our policy clearly states that all the code and data necessary to replicate a manuscript must be published openly and freely to anyone before submission. Also, you do not provide repositories for the data used in your work (listed in the Table 1) and produced in it. Instead you list several sites that do not comply with the policy of the journal to access them.
- They do not appear to have a published policy for data preservation over many years or decades (some flexibility exists over the precise length of preservation, but the policy must exist).
- They do not appear to have a published mechanism for preventing authors from unilaterally removing material. Archives must have a policy which makes removal of materials only possible in exceptional circumstances and subject to an independent curatorial decision,
- They do not appear to issue a persistent identifier such as a DOI or Handle for each precise dataset.
If we have missed a published policy which does in fact address this matter satisfactorily, please post a response linking to it. If you have any questions about this issue, please post them in a reply.
The GMD review and publication process depends on reviewers and community commentators being able to access, during the discussion phase, the code and data on which a manuscript depends, and on ensuring the provenance of replicability of the published papers for years after their publication. Therefore, the current situation with your manuscript in Discussions is irregular, and not allowed by the policy of the journal, and your manuscript should have never been accepted for this stage because of it. This occurred in this case clearly due to an editorial oversight on our part, and we apologize for it.
Please, therefore, in order to try to solve the situation and be able to consider your manuscript for further peer-review and Discussions, publish your code and data in one of the appropriate repositories and reply to this comment with the relevant information (link and a permanent identifier for it (e.g. DOI)) as soon as possible. We cannot have manuscripts under discussion that do not comply with our policy.
Later, if the Topical Editor decides to continue with the review or publication process of your manuscript and you are requested to upload a new version of it, then The 'Code and Data Availability’ section of your manuscript must also be modified to cite the new repository locations, and corresponding references added to the bibliography.
I must insist that if you do not fix this problem replying as soon as possible to this comment, we cannot continue with the peer-review process or accept your manuscript for publication in GMD.
Juan A. Añel
Geosci. Model Dev. Executive Editor