the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Aug 2026
ENSO simulation in the coupled Korean Integrated Model
Abstract. This study presents a comprehensive evaluation of the El Niño–Southern Oscillation (ENSO) simulation characteristics in the newly established coupled Korea Integrated Model (coupled KIM), which is designed for extended-range prediction. To robustly diagnose ENSO behavior, a 171-year coupled simulation was conducted and systematically evaluated against eight CMIP6 models that share the Nucleus for European Modelling of the Ocean (NEMO) as their oceanic component. Benchmarking the CLIVAR 2020 ENSO metrics framework, we evaluate diverse aspects of ENSO, including its spatial pattern, intensity, skewness, seasonality, and teleconnections, within the context of the tropical Pacific mean state. The coupled KIM exhibits moderate to above-average performance across most key metrics. Notably, the model successfully mitigates the common systematic bias of an excessive westward extension of the ENSO sea surface temperature (SST) pattern. This improvement is linked to a warmer eastern Pacific mean state compared to other CMIP6 models. However, this warm bias leads to a weak zonal SST gradient and a relatively deeper-than-normal thermocline, which consequently underestimates the overall ENSO intensity. Furthermore, this eastern Pacific warm bias undergoes pronounced seasonal expansion during January–February, intimately synchronized with an amplified double ITCZ bias. This seasonal coupling further flattens the simulated ENSO seasonality, although the ratio of ENSO amplitude between winter and spring remains one of the most realistic among the evaluated models. The model also demonstrates outstanding skill in reproducing ENSO skewness, which is plausibly attributed to recent advancements in the vertical mixing processes of the NEMO component. Additionally, the coupled KIM realistically captures tropical precipitation anomalies and their teleconnection patterns, including the extratropical atmospheric responses in the Northern Hemisphere. These findings validate the current developmental trajectory of the coupled KIM and highlight its robust potential for reliable extended-range forecasting.
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CEC1: 'Comment on egusphere-2026-4120', Juan Antonio Añel, 12 Aug 2026
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AC1: 'Reply on CEC1', Sae-Rim Yeo, 13 Aug 2026
Dear Dr. Añel,
Thank you for your comment and for pointing out the issues regarding compliance with GMD's Code and Data Policy.We sincerely apologise for not having met the policy requirements at the time of submission, and we fully accept the need to correct this before the review process can proceed.We are currently preparing to deposit the data associated with our manuscript in Zenodo, and we would like to ask for your guidance on one practical point before proceeding.The data consist of output from a long-term simulation performed with the Korea Integrated Model (KIM) at 0.5° horizontal resolution.Depositing the complete set of monthly files covering the period 1952–1990 would amount to approximately 115 GB. This exceeds Zenodo's standard limit of 50 GB per record.We would therefore like to ask whether it would be acceptable to deposit a reduced archive containing only the variables that are directly used in the analysis presented in the manuscript, namely tos, tauu, zg, and pr, extracted from the original output. This would allow reviewers and readers to reproduce all figures and results reported in the paper.
If this approach is acceptable to you, we will prepare the archive without delay, obtain a DOI for the deposited data, and post the link and permanent identifier in this discussion as soon as it is available. We are committed to resolving this matter quickly so that the review process can proceed smoothly. We would be grateful for your advice on this point, and we remain happy to follow any alternative arrangement you consider more appropriate.
Yours sincerely,
Sae-Rim Yeo
Citation: https://doi.org/10.5194/egusphere-2026-4120-AC1 -
CEC2: 'Reply on AC1', Juan Antonio Añel, 13 Aug 2026
Dear authors,
Many thanks for your reply. Actually, you should deposit only the variables used in your study. So your proposed solution for sharing the data is correct.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2026-4120-CEC2 -
AC2: 'Reply on CEC2', Sae-Rim Yeo, 14 Aug 2026
Dear Dr. Añel,
Thank you for your careful assessment of our manuscript and for clearly setting out the requirements of GMD's Code and Data Policy.
Following your instruction, we have deposited the processed model output used in this study together with the analysis scripts that generate all figures in the manuscript.
The archive is publicly available at Zenodo under the following DOI:
https://doi.org/10.5281/zenodo.21927687
We have also revised the description of all third-party datasets used in the study. The generic portal links have been replaced with the persistent DOI of each dataset,
and the corresponding dataset citations have been added to the bibliography.
For the CMIP6 output, we now cite the persistent DataCite DOI of each individual model, experiment, and variant in Table 1 rather than referring to the ESGF search portal.The revised text of the 'Code and Data Availability' section reads as follows:
The full source code of the Korean Integrated Model (KIM) is not publicly available due to institutional restrictions related to the development and maintenance of the operational numerical weather prediction system. The processed KIM simulation output and analysis scripts presented in this study are archived at https://doi.org/10.5281/zenodo.21927687 (Yeo et al., 2026). ERA5 monthly averaged data on pressure levels and on single levels were obtained from the Copernicus Climate Data Store (Hersbach et al., 2023a, https://doi.org/10.24381/cds.6860a573; Hersbach et al., 2023b, https://doi.org/10.24381/cds.f17050d7); the ERA5 system is documented in Hersbach et al. (2020). ORAS5 global ocean reanalysis data were obtained from the Copernicus Climate Data Store (Copernicus Climate Change Service, 2021, https://doi.org/10.24381/cds.67e8eeb7); the system is documented in Zuo et al. (2019). NOAA Optimum Interpolation Sea Surface Temperature version 2.1 is available at https://doi.org/10.25921/RE9P-PT57 (Huang et al., 2021). The Global Precipitation Climatology Project monthly precipitation dataset version 2.3 is available at https://doi.org/10.7289/V56971M6 (Adler et al., 2018). NCEP/DOE Reanalysis 2 is available from the NCAR Research Data Archive at https://doi.org/10.5065/KVQZ-YJ93 (NCEP/NWS/NOAA/U.S. Department of Commerce, 2000); the system is documented in Kanamitsu et al. (2002). The CMIP6 model output used in this study is archived in the Earth System Grid Federation (ESGF). The persistent DataCite DOI of each model, experiment, and variant used is listed individually in Table 1, and each DOI resolves directly to the corresponding ESGF dataset landing page.
We would be grateful if you could confirm whether this revised statement meets the requirements of the policy.
In regard to the documentation of the resctiction on the KIM source code,
We fully understand the need to provide documentary evidence of the institutional restriction rather than a general statement.
KIM is the operational global numerical weather prediction system of the Korea Meteorological Administration, and its source code is subject to restrictions arising from the operational status of the system.
We are currently consulting the responsible offices within the Korea Institute of Atmospheric Prediction Systems to identify the applicable regulation and to obtain a formal statement that can be provided to the editorial office.
As this requires internal review and authorisation, it will take some time to complete. We would therefore like to ask whether you could allow us additional time to prepare this documentation.
We appreciate your patience and your guidance on these matters, and we are committed to bringing the manuscript into full compliance with the journal's policy as quickly as possible.Yours sincerely,
Sae-Rim Yeo, on behalf of all co-authors
Citation: https://doi.org/10.5194/egusphere-2026-4120-AC2 -
CEC3: 'Reply on AC2', Juan Antonio Añel, 14 Aug 2026
Dear authors,
Many thanks for moving towards the compliance of your manuscript with the policy of the journal. Unfortunately, your proposed solution for the archival of the third-party data used in your study does not solve the situation. Having a permanent identifier for the datasets is only one of the three conditions mentioned in the first comment on this matter. The sites need to have a published data policy and ensure long-term archival. The sites that you continue to link (Copernicus services, NOAA, NCAR, etc.) do not comply with the mentioned requirements, and therefore you need to store the specific data that you have used in a permanent repository.
Please, let us know as soon as you have evidence that you are not allowed to publish the KIM code so that we can assess an exception to the policy.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2026-4120-CEC3 -
AC3: 'Reply on CEC3', Sae-Rim Yeo, 20 Aug 2026
Dear Dr. Añel,
We thank you for the clarification regarding the three conditions required of a data repository. In response, we have deposited all third-party data used in this study in our Zenodo record, and we write now to report this step while the remaining item concerning the KIM source code is still in progress.
Third-party data. The following datasets, subset to the variables, regions, and periods actually used to produce the figures in the manuscript, have been uploaded to the Zenodo record at https://doi.org/10.5281/zenodo.22003893 (Yeo et al., 2026). In addition, we have deposited the atmospheric, oceanic, and sea-ice initial conditions used to launch the coupled integration, which were derived from ERA5 and ORAS5.
The record now therefore contains the processed KIM output, the initial conditions, the third-party reference datasets, and the NCL and Python scripts that generate each figure. The file description in the record has been updated accordingly, and the Code and Data Availability section of the revised manuscript will cite the Zenodo archive as the authoritative source for these data, with the original provider DOIs retained only as provenance information and attribution, as required by the licence terms of each provider.
CMIP6 model output. As agreed in our previous exchange, the CMIP6 data remain in the Earth System Grid Federation, and Table 1 of the revised manuscript lists the persistent DataCite DOI of every model, experiment, and variant used, each resolving directly to the corresponding ESGF dataset landing page.
KIM source code. We have formally requested from our institute the documentation attesting to the restrictions on the public release of the KIM source code. This request is currently being processed through the internal administrative procedure. We are submitting the present reply now so that the compliance assessment of the data component is not delayed, and we will follow up with a separate communication as soon as the documentation is available. We hope these measures address the concerns raised, and we remain available for any further clarification.Sincerely,
Sae-Rim Yeo on behalf of all co-authorsCitation: https://doi.org/10.5194/egusphere-2026-4120-AC3 -
AC4: 'Reply on CEC3', Sae-Rim Yeo, 18 Sep 2026
Dear Dr. Añel,
Thank you for your guidance on compliance with the GMD code and data policy. As requested, we attach official documentation concerning the availability of the KIM source code. The Korean Integrated Model (KIM) is the operational global numerical weather prediction system of the Korea Meteorological Administration (KMA), and its source code is owned by KMA rather than by the authors. In the attached official letter (KMA Numerical Weather Prediction Center, Ref. No. 3022, 11 September 2026), issued under Article 19 (Utilization and Disclosure of R&D Outcomes) of the National R&D Agreement, KMA states that the code constitutes core infrastructure of the national operational forecasting system and that its external provision or disclosure is restricted. We therefore have no authority to redistribute or publicly archive the source code; enquiries regarding access should be directed to KMA. Both the Korean original and an unofficial English translation are attached, the Korean version being authoritative.
We would be grateful if you could review the attached documentation, and we would be glad to provide any further material you may require.Sincerely,
Sae-Rim Yeo on behalf of all co-authors-
CEC4: 'Reply on AC4', Juan Antonio Añel, 22 Sep 2026
Dear authors,
Thanks for your reply. We could accept the letter and grant you an exception; however, could you clarify the name of the person that has signed it? I guess that the mandate to do not disclose the code comes from the Director of the KMA, as no license is provided in the document. This is not clear to me from the letter attached. Please, understand that we need to establish a chain of authority where you as employees are not allowed to share the code by a superior that forbids you to do it.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2026-4120-CEC4
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CEC4: 'Reply on AC4', Juan Antonio Añel, 22 Sep 2026
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AC3: 'Reply on CEC3', Sae-Rim Yeo, 20 Aug 2026
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CEC3: 'Reply on AC2', Juan Antonio Añel, 14 Aug 2026
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AC2: 'Reply on CEC2', Sae-Rim Yeo, 14 Aug 2026
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CEC2: 'Reply on AC1', Juan Antonio Añel, 13 Aug 2026
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AC1: 'Reply on CEC1', Sae-Rim Yeo, 13 Aug 2026
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RC1: 'Comment on egusphere-2026-4120', Anonymous Referee #1, 05 Sep 2026
Review of “ENSO simulation in the coupled Korean Integrated Model” by Yeo et al.
Overall recommendation: Minor revision
General comment:
This paper examines performance of a newly performed CMIP-style long-term free-run simulation of a newly developed atmosphere-ocean coupled climate model, named KIM, using a community established evaluation toolkit. In particular, the authors focused on the evaluation of ENSO. As the ENSO is one of most influential and significant modes of variability in the climate system, it is logically natural to examine the reproducibility of ENSO for the newly developed model and its simulation. The multiple aspects of ENSO were evaluated collectively from the KIM’s CMIP-Historical-like simulation, and the results were compared to the observation and fellow CMIP6 models that are sharing the same type of ocean modeling component, i.e., NEMO. It was demonstrated for the majority of the ENSO aspects, including climatology, seasonality, and teleconnection, KIM’s performance is in the range of the selected CMIP6 multi-model performance spread, indicating KIM shows reasonable ENSO reproducibility with identifying areas to improve. I acknowledge the importance of documenting the performance of developing model in a collective way, which could serve as an important resource for future development planning and directing. I believe the manuscript is well prepared, and it is within the scope of the journal, GMD. I only have a few minor suggestions, and recommend accepting the paper after those comments get addressed.
Specific comments:
Line 110 “While this introduces an initial discontinuity between the 1850 and forcing and 1979 states, preliminary sensitivity tests confirmed that this reanalysis-based initialization strategy yielded robust performance, with negligible differences compared to simulations that include a standard spin-up period”: I’d be interested to learn more about this result. Is there a citable literature for this sensitivity tests, or do the authors happen to have those results that could be shared maybe in a supplementary document of this paper?
Line 120 “Further details are given in the next sub-Sect..”: This sentence is looking like it is incomplete because of the two periods (although one for acronym and another for ending the sentence). Maybe it could be revised to something like “Further details are given in the next sub-section” for further clarity.
Figure 1a: Any chance to show observed TOA (or from reanalysis) as well in the upper panel?
Code and data availability: While I do understand the institutional restrictions regarding the model source codes, and the authors offer the KIM simulation output and analysis scripts upon request, as this is not comply with the GMD’s Open Source rule, is it fair enough to expect that the simulation output (that might have been post-processed to include a subset of data used for the analysis) and the analysis scripts will become publicly available by the time of publication?
Citation: https://doi.org/10.5194/egusphere-2026-4120-RC1 -
RC2: 'Comment on egusphere-2026-4120', Anonymous Referee #2, 27 Sep 2026
General Comment
This manuscript evaluates the ENSO simulation capability of the coupled Korea Integrated Model (KIM), in which the NEMO ocean model is coupled to the atmospheric component, with the broader aim of extending the model toward extended-range prediction. The authors compare the basic characteristics of ENSO simulated by KIM with those simulated by CMIP6 models that also employ the NEMO ocean model, and attempt to relate the ENSO biases to biases in the tropical Pacific mean state.
I consider this type of evaluation to be an important and necessary step in extending a numerical weather prediction (NWP) model toward climate and extended-range prediction applications. The manuscript also contains useful diagnostics of the ENSO characteristics in KIM. However, I have several major concerns regarding the experimental design, the fairness of the comparison with CMIP6 models, and the quantitative basis for some of the physical interpretations. In its current form, I believe these issues need to be addressed before the manuscript can be considered for publication. Addressing the following issues would help the manuscript move beyond a model-performance report toward a more scientifically rigorous analysis of the physical mechanisms controlling ENSO characteristics in the coupled KIM.
Specific Comments
1. Fairness of the comparison with CMIP6 models and overstatement of model performance
As I understand the experimental design, the ENSO characteristics of the CMIP6 models are evaluated over 1976–2014, whereas the coupled KIM simulation is evaluated over 1952–1990. The observational analysis based on OISST covers 1982–2020. I understand that the observational period does not necessarily have to be identical to the CMIP6 historical period, since the CMIP6 historical simulations are not initialized to reproduce the observed temporal evolution of the climate system.
However, I have a concern with the way the KIM analysis period is selected. The authors examine several 39-year periods from the KIM simulation and select 1952–1990 because this period has a mean SST climatology that is most similar to observations. This selection makes the subsequent comparison with the CMIP6 models potentially unfair, because the KIM period is effectively selected based on its agreement with observations, whereas the CMIP6 models are evaluated over a fixed period (1976–2014). The selection criterion itself is therefore not applied consistently across the models. This issue is particularly important because the manuscript subsequently uses this comparison to characterize KIM as having “above-average performance,” “outstanding skill,” or more realistic ENSO characteristics than other models. These statements appear stronger than what can be supported by the current experimental design.
I therefore suggest that the authors: 1) evaluate KIM over the same 1976–2014 period used for the CMIP6 models, and provide the corresponding comparison. 2) If the authors wish to retain the 1952–1990 period as an additional sensitivity analysis, clearly explain that this period was selected based on its mean-state agreement with observations and avoid using it as the primary basis for ranking KIM against the CMIP6 models. 3) Reconsider and tone down statements such as “above-average performance,” “outstanding skill,” and “more realistically” unless these claims are supported by a comparison based on a common evaluation period and consistent methodology.
Another important issue is that the coupled KIM has substantially higher spatial resolution than the CMIP6 models included in the comparison. Therefore, some of the differences in ENSO characteristics may reflect the higher model resolution rather than the specific physical improvements or configurations of KIM. This difference in resolution should be explicitly acknowledged when interpreting the comparison.
2. Need for more quantitative analysis of ENSO feedbacks and quantitative scientific interpretation
The manuscript attributes several ENSO characteristics of coupled KIM to biases in the tropical Pacific mean state, particularly through zonal advective feedback and thermocline feedback. These are physically reasonable mechanisms, but the current discussion remains largely qualitative.
There is a substantial body of previous literature that quantitatively diagnoses ENSO feedbacks, including studies using the same or closely related CLIVAR ENSO metrics. For example, the zonal advective feedback and thermocline feedback can be quantified through terms such as (-u'dT/dx) and (-wdT’/dz), respectively. Despite the availability of these quantitative approaches, the manuscript does not appear to provide quantitative estimates of the relevant feedback terms, nor does it sufficiently cite the literature establishing these diagnostics.
I recommend that the authors substantially strengthen this part of the analysis by: 1) providing quantitative estimates of the relevant ENSO feedback terms and citing previous studies that have established these diagnostics; and 2) comparing the magnitude of the feedbacks between KIM, observations/reanalysis, and the CMIP6 models, where appropriate. If access to the necessary ocean variables from the observations and CMIP6 models is limited, the authors could alternatively compare the KIM results with those reported in previous studies that have quantitatively diagnosed these feedbacks in CMIP models.
More generally, quantitative information should be provided throughout the manuscript whenever possible. The current manuscript frequently describes differences in terms such as “larger,” “smaller,” “stronger,” or “weaker,” without providing the magnitude of these differences. More quantitative presentation would make the conclusions substantially more rigorous.
3. ENSO seasonality and the mechanism responsible for the flattened seasonal cycle
The discussion of the “flattened ENSO seasonality” in Figures 5–7 primarily focuses on differences in the tropical Pacific mean state between September–October and January–February. While these comparisons are useful, I am not fully convinced that they identify the process responsible for the flattened ENSO seasonal cycle. In particular, the mature phase of ENSO occurs around November–December, and the results appear to suggest that ENSO growth during this period is insufficient. Therefore, rather than focusing primarily on the mean-state differences between September–October and January–February, it would be useful to examine how ENSO actually grows throughout the seasonal cycle.
I suggest that the authors investigate the seasonal evolution of ENSO growth rate and examine the contributions of the different feedback processes discussed above, particularly the zonal advective feedback and thermocline feedback. For example, diagnosing the seasonal evolution of these feedbacks would help determine whether the weakened ENSO peak is associated with reduced growth during the developing phase, changes in thermocline feedback, changes in zonal advective feedback, or other processes. Such an analysis would provide a much stronger physical explanation for the reported “flattened ENSO seasonality” than a comparison of mean-state biases between two selected seasons.
4. Clarification of the scientific objective in the Abstract
The objective of the study is not sufficiently clear from the Abstract. In particular, it is difficult to determine whether the primary purpose of the study is:
to evaluate the ENSO characteristics of a long-term historical coupled KIM simulation, or
to demonstrate the suitability of KIM for extended-range ENSO prediction.
These are related but distinct objectives and require different experimental designs and evaluation frameworks. The Abstract should be revised so that the primary scientific objective is immediately clear and is consistent with the actual experiments and results presented in the manuscript.
I also have concerns about describing the experiment as a “171-year simulation.” According to the methodology, the first 100 years are excluded from the analysis, while the forcing after 2015 is held fixed at the 2014 level. Therefore, the full 171-year integration period does not correspond to the period actually analyzed or to a continuous historical-forcing experiment. I suggest that the authors describe the actual analysis period more explicitly in the Abstract rather than emphasizing the total integration length. If the full integration length is important for model development or spin-up, this can be explained in the main text.
Technical Corrections
1. Definition of Niño regions
The manuscript does not consistently use the Niño-3 and Niño-3.4 regions, and the geographical boundaries of these regions are repeatedly described throughout the manuscript. This makes the results somewhat difficult to follow. I suggest defining all Niño regions, including their longitude/latitude boundaries, clearly in the Methods section. The Results section can then simply refer to “Niño-3,” “Niño-3.4,” etc. This would improve readability and avoid repeatedly presenting geographical definitions.
2. Lines 275–280: Interpretation of the NEMO vertical diffusion scheme
The discussion attributing the simulated ENSO skewness to the improvement in the NEMO vertical diffusion scheme appears rather speculative if the corresponding sensitivity-test results are not presented. I am not necessarily suggesting that an additional experiment is required. However, if the authors do not intend to provide the sensitivity experiments supporting this interpretation, the statement should be toned down and presented as a possible explanation or hypothesis rather than as an established mechanism.
3. Lines 112–115: Forcing after 2014
The forcing is held fixed at the 2014 level for the 2015–2020 period. This makes the 2015–2020 integration different from a standard CMIP historical simulation and also complicates the comparison with the CMIP6 models. Since this period is not used in the primary analysis, I question whether this information needs to be emphasized in the manuscript.
4. The red line in Figure 1b does not appear to represent the 1982–2020 period stated in the caption. Please check the figure and revise the caption accordingly.
5. The units of the model resolutions in Table 1 should be explicitly indicated. It would also improve readability to list the atmospheric and oceanic resolutions separately rather than presenting them in a single field.
6. Units are missing from many of the figures. Please add the appropriate units to the figure captions throughout the manuscript.
Citation: https://doi.org/10.5194/egusphere-2026-4120-RC2
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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
First, it is not clear what prevents you of publishing the code of the KIM. You state in your manuscript "due to institutional restrictions." We can accept this and grant you an exception to the obligation of providing an open repository for the KIM, but you must handle us evidence of the mentioned institutional restrictions. This can be for example a law, rule, official mandate, or license.
Second, you state in your manuscript that the "output and analysis scripts presented in this study will be made publicly available upon the reviewer’s request." We can not accept this. You must publish in a repository openly all the data used and produced in your work, and all the code necessary. The policy of the journal obligates you to do it before submitting a manuscript for consideration for publication.
Also to access several datasets used in your work you cite web sites from NCAR, NOAA, the Copernicus Data Store; however, those sites do not fulfil GMD’s requirements for a persistent data archive because:
- 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.
What we can accept is the ESGF; however, you must provide a clear link to the specific data used, not a generic one to the main data portal.
Regarding the mentioned sites, 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. Please, therefore, 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 note that if you do not fix this problem, we cannot continue with the peer-review process or accept your manuscript for publication in GMD.
Juan A. Añel
Geosci. Model Dev. Executive Editor