the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 Aug 2024
Earth’s future climate and its variability simulated at 9 km global resolution
Abstract. Earth’s climate response to increasing greenhouse gas emissions occurs on a variety of spatial scales. To assess climate risks on regional scales and implement adaptation measures, policymakers and stakeholders often require climate change information on scales that are smaller (less than 10 km) than the typical resolution of global climate models [O (100 km)]. To close this important knowledge gap and consider the impact of small-scale processes on the global scale, we adopted a novel iterative global earth system modeling protocol. This protocol provides key information on Earth’s future climate and its variability on storm-resolving scales (less than 10 km). To this end we used the coupled Earth system model OpenIFS-FESOM2 (AWI-CM3) with a 9 km atmospheric resolution (TCo1279) and a 4–25 km ocean resolution. We conducted a 20-year 1950 control simulation and four 10-year-long coupled transient simulations for the 2000s, 2030s, 2060s, and 2090s. These simulations were initialized from the trajectory of a coarser 31 km (TCo319) SSP5-8.5 transient greenhouse warming simulation of the coupled model with the same high-resolution ocean. Similar to the coarser resolution TCo319 transient simulation, the high resolution TCo1279 simulation with SSP5-8.5 scenario exhibits a strong warming response relative to present-day conditions, reaching up to 6.5 °C by the end of the century at CO2 levels of about 1,100 ppm. The TCo1279 high resolution simulations show a substantial increase in regional information and granularity relative to the TCo319 experiment (or any other lower resolution model), especially over topographically complex terrain. Examples of enhanced regional information include projected changes in temperature, rainfall, winds, extreme events, tropical cyclones, and in the hydroclimate teleconnection patterns of the El Niño-Southern Oscillation and the North Atlantic Oscillation. The novel iterative modelling protocol, that facilitates storm-resolving global climate simulations for future climate time-slices, offers major benefits over regional climate models. However, but it also has some drawbacks, such as initialization shocks and resolution-dependent biases, which will be further discussed.
- Preprint
(23212 KB) - Metadata XML
-
Supplement
(8417 KB) - BibTeX
- EndNote
Status: open (until 24 Sep 2024)
-
RC1: 'Comment on egusphere-2024-2491', Anonymous Referee #1, 27 Aug 2024
reply
General comments:
The authors present results from a novel set of climate change simulations with a very high resolution coupled ocean-atmosphere model. They compare these results to simulations using a version of that coupled model with a somewhat coarser atmospheric resolution.
I am confident that readers will be interested in the results of this work - the construction of a very high resolution coupled climate model, its computational characteristics, and its simulations. I also am confident that scientists will be interested is using the model output that has been made available. The team of researchers is to be congratulated for this significant computational achievement.
Having said that, I do have significant concerns. A primary goal in such a study is to evaluate what impact the very high resolution grid has on a model's ability to simulate the current climate and to simulate the response of the climate system to radiative forcing changes. Due in part to the short length of the simulations, single realization, and initialization shocks from the land and atmosphere, it is difficult to pinpoint changes in the model behaviour that come about from the use of very high resolution (with the notable exception of tropical cyclones). Therefore, the scientific results of the study (especially their robustness) are rather limited.
The repeated initialization shocks, especially from the land conditions, contribute to drift and uncertainty in the simulations. It is possible that a simpler experimental design could have been more useful. For example, some sort of idealized CO2 increase experiment (gradual, or switch on) might have offered the possibility of more statistical significance in the results. A notable issue in the manuscript is the lack of assessment of statistical significance - understandable due to the short length of the records, but this makes it very difficult to assess robustness. What is noise and what is a signal of climate change that is different in the HR model than in the MR model?
The focus on regional changes is somewhat problematic, given the short length of the simulations and the considerable climate noise on such small scales. Oftentimes the results are presented without statistical significance or dynamical assessments in a very descriptive, qualitative style. It is difficult to know what to make of such findings. As one example: page 13, lines 04-06 ... the regionally enhanced drying is called out without an assessment of significance or quantification of the role of the high resolution model in simulating this impact. What should the reader conclude from that, given the short simulations? There are many similar examples of qualitative discussion of regional changes without a quantification of the extent to which these changes are related to the high resolution of the model.
Specific comments:
1. p. 2, line 37 What is meant by "... increase in regional information"?
2. I do not find Fig 1 especially illuminating
3. Fig 2: There are multiple acronyms that are not explained in the caption. I do not understand what this Figure is trying to convey.
4. p. 4, line 99 The text is discussing the sequence of runs (2000s, etc) but the referenced figure shows the spatial grid. I am not clear why Fig 3 is referenced for that discussion.
5. p. 5 Lines 18-24 There are lots of acronyms used here that do not convey much information to those unfamiliar with those terms.
6. p. 5, line 4 Is there any parameterization of ocean mesoscale eddies used? If not, is the model able to adequately represent ocean mesoscale eddies at mid to higher latitudes?
7. p. 6, lines 45-46 Does the model simulate sudden stratospheric warming events realistically? If such a statement is included in the text it would be warranted to have a figure, perhaps in the supplementary section, documenting that.
8. Fig 4a: The MR model warms quite rapidly over the observational record. This seems inconsistent with the observational record. How does that impact the overall results presented in the manuscript?
9. p. 7, line 56 Why not just state what the radiative imbalance is?
10. p. 8, bottom I am very surprised at the decision to use 1990 land initial conditions for all of the runs, even those starting at 2090. There is tremendous inertia in the soil which can take up to a decade or longer to adjust. It seems to me that the entire duration of these transient simulations would be during a period of strong land adjustment. Wasn't there some way to use the land conditions from the MR run and perhaps regrid to the HR run? That would also have issues, but might have less drift.
11. p. 10, Line 11 The bias reduction here may not be due to changes in physics, but to the cold drift of the HR coupled model relative to the MR model; starting from the very warm state of the MR model, the HR model drifts cooler and therefore appears to have a lower error, but it is certainly not clear that this is attributable to any improved physical representations. Further, what is the reason for this cold drift?
The short durations of all of these simulations really preclude a robust assessment of changes to resolution and physics.12. p. 10, line 29 I am not sure what is meant by "relatively weak" here. Is there some metric of the double ITCZ that is used?
13. p. 17, lines 40-52 Is there anything about the behaviour of the hi res model that differs from most CMIP6 class models? If so it would be useful to focus on those differences and assess whether the differences are robust, and explain those differences that may be the resolution of improved dynamics and resolution.
14. Fig. 15 How confident are the authors that the differences between Fig, 15b and 15c are robust given the very short length of the simulations?
15. p. 35, lines 88-90 This is a rather qualitative assessment that I am not sure is supported by the results of the manuscript. For example, the pattern and amplitude of tropical ENSO SST variability in HR is noticeably worse than in MR.
Citation: https://doi.org/10.5194/egusphere-2024-2491-RC1
Data sets
Code and data for reproducing figures with AW-CM3 HR simulations in J.-Y. Moon et al. "Earth's Future Climate and its Variability simulated at 9 km global resolution", Climate data server of the IBS Center for Climate Physics Ja-Yeon Moon, Jan Streffing, Sun-Seon Lee, Tido Semmler, Miguel Andrés-Martínez, Jiao Chen, Eun-Byeoul Cho, Jung-Eun Chu, Christian Franzke, Jan P. Gärtner, Rohit Ghosh, Jan Hegewald, Songyee Hong, Nikolay Koldunov, June-Yi Lee, Zihao Lin, Chao Liu, Svetlana Loza, Wonsun Park, Woncheol Roh, Dmitry V. Sein, Sahil Sharma, Dmitry Sidorenko, Jun-Hyeok Son, Malte F. Stuecker, Qiang Wang, Gyuseok Yi, Martina Zapponini, Thomas Jung, and Axel Timmermann http://doi.org/10.22741/ICCP.20240001
Video supplement
Supplementary videos with AW-CM3 HR simulations in J.-Y. Moon et al. "Earth's Future Climate and its Variability simulated at 9 km global resolution" Climate data server of the IBS Center for Climate Physics, Ja-Yeon Moon, Jan Streffing, Sun-Seon Lee, Tido Semmler, Miguel Andrés-Martínez, Jiao Chen, Eun-Byeoul Cho, Jung-Eun Chu, Christian Franzke, Jan P. Gärtner, Rohit Ghosh, Jan Hegewald, Songyee Hong, Nikolay Koldunov, June-Yi Lee, Zihao Lin, Chao Liu, Svetlana Loza, Wonsun Park, Woncheol Roh, Dmitry V. Sein, Sahil Sharma, Dmitry Sidorenko, Jun-Hyeok Son, Malte F. Stuecker, Qiang Wang, Gyuseok Yi, Martina Zapponini, Thomas Jung, and Axel Timmermann http://doi.org/10.22741/ICCP.20240002
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,154 | 248 | 18 | 1,420 | 32 | 3 | 5 |
- HTML: 1,154
- PDF: 248
- XML: 18
- Total: 1,420
- Supplement: 32
- BibTeX: 3
- EndNote: 5
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1