the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 13 Jan 2026
From Single Storms to Global Waves: A Global 2.5 km ICON Simulation of Weather and Climate
Abstract. Global kilometer-scale (km-scale) weather and climate models offer new opportunities to unify numerical weather prediction (NWP) and climate modeling by explicitly simulating convection and mesoscale circulations globally within a single modeling framework. We present results from the first multi-year (April 2020–March 2024) global atmosphere-land simulation using the GPU-refactored ICON model at a 2.5 km horizontal grid spacing and 120 vertical levels. The simulation uses NWP physics and observed sea-surface temperatures. We assess its performance against satellite, reanalysis, and in-situ observations using standard statistics and the MOAAP feature-tracking framework to evaluate a wide spectrum of atmospheric phenomena. ICON reproduces global temperature and precipitation patterns, including a realistic single Intertropical Convergence Zone and physically consistent diurnal precipitation cycles. However, ICON exhibits continental warm and dry biases during the warm season, linked to an overestimation of incoming solar radiation and excessive surface sensible heat fluxes. The model realistically captures the intensity and frequency of hourly precipitation and near-surface winds, as well as the structure and occurrence of tropical cyclones. Mesoscale convective systems (MCSs) exhibit realistic spatial initiation patterns, but their frequency is underestimated over oceans and overestimated over tropical land. Long-lived MCSs are too infrequent and small, while excess rainfall from shallow and mid-level clouds suggests overactive warm-cloud microphysics. These biases likely stem in part from an underrepresentation of convectively coupled equatorial waves. Our results demonstrate the feasibility and scientific value of multi-year global convection-permitting simulations for exploring the weather–climate system and local-scale extreme events, while identifying key directions for future model development.
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CEC1: 'Comment on egusphere-2025-6414 - No compliance with the policy of the journal', Juan Antonio Añel, 11 Feb 2026
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AC1: 'Reply on CEC1', Andreas F. Prein, 15 Feb 2026
Dear Dr. Añel,
Thank you for your comment and for highlighting the requirements of the GMD Code and Data Policy.
We have now archived the simulation output, model configuration, and analysis and visualization code in permanent public repositories with DOIs:
Simulation output and analysis data:
https://doi.org/10.6084/m9.figshare.31341982ICON configuration files, namelists, and run scripts:
https://doi.org/10.5281/zenodo.17250248Analysis and visualization code:
https://doi.org/10.5281/zenodo.18648539In addition, we have updated the references for all observational and reanalysis datasets to include persistent archive locations and DOIs where available. For example, ERA5 reanalysis data are now referenced via the Copernicus Climate Data Store DOI:
https://doi.org/10.24381/cds.adbb2d47We will update the Code and Data Availability section of the manuscript accordingly and include all repository links and DOIs in the revised manuscript.
Thank you for your guidance.
Best regards,
Andreas Prein (on behalf of the authors)Citation: https://doi.org/10.5194/egusphere-2025-6414-AC1 -
CEC2: 'Reply on AC1', Juan Antonio Añel, 15 Feb 2026
Dear authors,
Thank you for addressing these issues so quickly. Please, clarify if all the ICON model code is included in the mentioned repositories.
Also, you have submitted your manuscript as a "Model evaluation paper". Please, remember that according to the policy of the journal and submission guidelines you must include in the title of the manuscript the version number of the model that you have used. Therefore, please, suggest a new title for your manuscript that reflects it, and remember changing it for any reviewed version.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2025-6414-CEC2 -
AC2: 'Reply on CEC2', Andreas F. Prein, 15 Feb 2026
Dear Dr. Añel,
Thank you for your quick response, your clarification, and guidance.
The ICON model version used in this study corresponds to ICON-EXCLAIM v0.2.0. The complete model source code, including the EXCLAIM extensions, is publicly archived at Zenodo: https://doi.org/10.5281/zenodo.17255275
This repository provides a permanently archived version of the exact model code used to produce the simulations presented in this manuscript.The configuration files, namelists, and run scripts used to perform the global 2.5 km simulation are archived separately at: https://doi.org/10.5281/zenodo.17250248
We will update the manuscript title to include the model version number. The revised title will be:
“From Single Storms to Global Waves: A Global 2.5 km Simulation of Weather and Climate with ICON-EXCLAIM v0.2.0”We will update the manuscript accordingly in the revised version.
Thank you again for your help.All the best,
Andreas PreinCitation: https://doi.org/10.5194/egusphere-2025-6414-AC2
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AC2: 'Reply on CEC2', Andreas F. Prein, 15 Feb 2026
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CEC2: 'Reply on AC1', Juan Antonio Añel, 15 Feb 2026
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AC1: 'Reply on CEC1', Andreas F. Prein, 15 Feb 2026
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RC1: 'Comment on egusphere-2025-6414', Anonymous Referee #1, 15 Mar 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2025-6414/egusphere-2025-6414-RC1-supplement.pdf
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RC2: 'Comment on egusphere-2025-6414', Anonymous Referee #2, 18 Mar 2026
In this manuscript, the authors have comprehensively shown the results of a multi-year ICON simulation with a NWP configuration and a 2.5-km horizontal mesh. The analyses focused on mean precipitation and radiative fields and global statistics of local-to-synoptic-scale weather phenomena such as MCSs, tropical cyclones, and equatorial waves, compared with several observational data sets. The evaluation of these aspects suggested that complied statistics of local winds and precipitation as well as the mean precipitation distribution are reproduced relatively well, whereas the simulation still has inevitable biases, as found in the morphology of MCSs, tropical waves (incl. the MJO), and radiative budgets.
I acknowledge that this is the first step of addressing weather and climate using this version of ICON, and that it is worth being reported as one of milestones. Meanwhile, some of the presented results are interpreted speculatively without concrete evidence. Also, I wonder what clear merits of this ICON simulation are, compared to preexisting km-scale regional climate simulations, because the results except for global mean fields weigh heavy on regional statistics of meso-to-synoptic-scale variability (rather than large-scale circulation), which could have been addressed by regional modeling. Furthermore, I feel that the Introduction does not precisely describe historical advances in global km-scale modeling, with too much emphasis on the recent trend. Based on these points, I think this paper must undergo major revision before it can be considered for publication.
[Major comments]
1. The authors have tried to interpret a source of the biases in several subsections: for example, reasons for high temperature biases over land, for lower differences at high wind speeds over several regions, and for underestimated equatorial waves. However, I wonder if their interpretation could be done by relatively narrow insights without sufficient evidence. While I do not intend to request very detailed analyses, it would be better to provide more hints about the emergence of biases for the future model improvement. The suggestions and/or issues are listed below.
* Impacts of cloud radiative forcing, in addition to the issues of land-atmosphere coupling, on the surface temperature bias (cf. Sections 3.1 and 3.2)
* Representation of extratropical cyclones around CNA, WCE, and eastern North America (cf. LL. 307-310)
* Equatorial Rossby waves are affected by coupling between moisture and dynamics (e.g., Yasunaga and Mapes, 2012. JAS; Yasunaga et al., 2019, JCLI; Nakamura and Takayabu, 2022, JAS), not just by dynamics.2. While the authors presented the geographical variability of mesoscale phenomena (e.g., MCSs, diurnal cycles) in Figures 5, 6, 7, 11, and 12, I wonder how different it is simulated when comparing the accumulated results from the regional km-scale modeling framework. It is true that the presented results have global aspects, but they should be somewhat described without global models. I would appreciate it if the authors could discuss added values of this study to address the above points.
3. The descriptions about the advances in global km-scale modeling are heavily biased by the recent trend observed in Europe. This kind of activities started two decades ago in the Japanese community with the Nonhydrostatic ICosahedral Atmospheric Model (NICAM), and it has published many research articles describing its importance of both weather and climate modeling. To ensure the correct historical advances in science, please reorganize the Introduction with appropriate citations (please see also the specific comments).
[Specific and/or minor comments]
Title: I feel that the title is exaggerated compared to the contents in the main text. What are "global waves", despite not fully mentioning planetary-scale waves? I would like the authors to reconsider the title to be consistent with the fact that the present study mainly addresses global statistics of meso-to-synoptic-scale features.
LL.13-14: I do not fully agree on this speculation. I wonder if the poor representation of convectively coupled equatorial waves is attributed to misrepresentation of thermodynamic-convection coupling (cf., Takasuka, Becker, and Bao, 2025).
LL.14-15: I wonder if the main text, especially the concluding section, does not provide the sufficient value of multi-year global km-scale simulations, even though it tells us some information about biases.
LL.25-29: "historically restricted its use to..." has been true in the main stream, but NICAM already succeeded in this type of simulation. I would like the authors to reflect the historical review by Satoh et al. (2019) in the revised Introduction.
LL.36-37: Sato et al. (2009, JCLI) also showed the better representation of diurnal cycles in the global km-scale model.
LL.37-39: Miura et al. (2007, Science) showed the first success of the realistic MJO simulation and associated tropical cyclogenesis, featured by the realistically simulated multi-scale convective organization.
LL.49-50: The same comment as that for LL.25-29.
L.60: These were already (i.e., before 2020s) shown by Miura et al. (2007, Science), Nasuno et al. (2008, JAS), Holloway et al. (2012, JAS)...
LL.65-66: Miura et al. (2023, BAMS) have also pointed out this direction.
L.129: slow-evolving waves -> slow-evolving variability (because the MJO is not a dynamical wave...)
LL.228-232: In addition to this problem, it seems that a large bias of radiation budget (at the TOA and SFC) has impacts on T2m bias. Also, how are the distributions of cloud radiative forcing?
LL.259-260: This does not necessarily hold true for all the regions; for example, over the North America and South America in the subtropics.
LL.266-271: Figure 2a shows the weak precipitation band in the Southern Hemisphere very near the equator. I think this can be a glimpse of a double ITCZ... Also, how about mentioning the reproducibility of precipitation bands in the mid-latitude?
L.271: Note that Takasuka et al. (2024, JAMES) showed that resolving the double ITCZ problem was achieved by the reconsideration of microphysics.
LL.291-292: I'm a bit surprised at this, because the phase lag of diurnal cycles of precipitation has been found in IMERG, which uses passive sensors for the estimation of precipitation, compared to radar-based precipitation products.
LL.321-322: What is a possible reason for the low bias over the North Atlantic Basin? I wonder if this could be related to the underestimation of easterly waves (similar to equatorial waves, as shown in Fig. 9)
LL.327-328: Is this attributed to the poor representation of rapid intensification? Also, Baker et al. (2024, GRL) should be cited somewhere in this paragraph, because they already showed benefits of km-scale models in representing tropical cyclones.
L.322: Equatorial waves -> Equatorial waves and the Madden-Julian oscillation (because MJO is not a equatorial wave.)
L.339, L.341: Please cite appropriate references.
Section 3.7: It would be better to provide a brief description about the criteria for the detection of MCSs. Readers may not read other paper carefully that introduces the methodology.
LL.359-360: The same comment as that for LL.13-14.
LL.400-401: Is this also related to underestimated shortwave incoming (especially over ocean)? I wonder if water clouds have higher albedo and thus prevent radiation from reaching the surface.Citation: https://doi.org/10.5194/egusphere-2025-6414-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, in the Code and Data Availability section of your manuscript you do not provide a repository for the version of ICON that you use in your work. Also, you state "The global 2.5 km ICON simulation... will be made publicly available through the DYAMOND-III intercomparison archive upon completion of the coordinated data release. Until then, access can be provided by the corresponding author upon reasonable request.", which is neither acceptable.
Finally, for the other datasets used to produce your work, you provide links to the generic web pages that contain them, and what is needed is that you cite specific repositories that comply with the policies of the journal and contain the data you have used.
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 process depends on reviewers and community commentators being able to access, during the discussion phase, the code and data on which a manuscript depends. 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.
The 'Code and Data Availability’ section 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