the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 28 May 2025
Projected climate change in Fennoscandia – and its relation to ensemble spread and global trends
Abstract. The need for information about climate change is constantly increasing. This information is usually based on climate model data — data that often have systematic biases. Furthermore, there are questions about how climate model ensembles are affected by the choice of models and emission scenarios. Here, we aim to give a description of climate change in Sweden and neighbouring countries, as well as a discussion on how local climate change relates to global warming. We present climate change projections based on bias adjusted Euro-CORDEX (Coordinated Regional Downscaling Experiment) regional climate model data centred over Sweden. Global warming results in higher temperature, more warm days and fewer cold days in Sweden. The regional climate models capture the signal of the driving global models. The choice of emission scenario has minimal effect on the calculation of mean climate change at a global warming level of 2 degrees. This implies that it would be safe to mix emission scenarios in calculations of global warming levels, as long as mean values are concerned. Moreover, the differences in local and global warming rates seem to decrease with time, suggesting that climate change in Sweden may currently be at its fastest.
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Status: open (until 09 Jul 2025)
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RC1: 'Comment on egusphere-2025-2002', Anonymous Referee #1, 20 Jun 2025
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Review of ‘Projected climate change in Fennoscandia — and its relation to ensemble spread and global trends’ by Strandberg et al.
The manuscript presents results how temperature and precipitation change under projected climate change over Fennoscandia and Sweden using an ensemble CORDEX regional models with different GCMs, RCMs and three different rcp scenarios. The results provide important information about climate change in this region and should be published if the authors consider some major concerns described below. My main concern is that the Method section is not clearly presented, and several results are introduced without sufficient explanation of how they were calculated. For the findings to be properly understood and evaluated, methods should be linked to the results
The Introduction is generally well written. The choice of RCMs (CORDEX )is described, however there are some known issues with CORDEX data that should be mentioned, e.g. lack of aerosol impacts, precipitation and temperature biases (Vautard et al., 2021).
The Method section should be revised to enhance clarity and allow for a better understanding of the results. What variables are bias corrected, and what are the results of this correction. Over what period is this correction performed? How does it affect future projections? The effect of the bias correction is missing in the representation of the results further in the manuscript. If some models are biased corrected more than others, I guess this would impact the comparisons. If it is described and represented in Berg et al (missing in references) the results should be briefly presented. Is it only over land? (Region A covers the ocean as well)
The selection and analyses of sub-ensembles section is also unclear. Is it only these 17 models that is used further in the manuscript? What are these 17 models used for? This is the first mention of GWL (not written out). How is the GWL found? In the GCMs that drive the RCM? This should be described better. How and when GWL 2 is reached in different models and projections should be included in a Figure. Only results for tas and csu are presented in the manuscript, while several are stated here.
The methods section should also include a brief description of which periods the results are calculated.
Figure 1, is region B used in any analysis, I did not find any further reference to this region.
Figure 2 and 3, Is this the mean over all the CORDEX models available or only the 17? The introduction and title of the manuscript focuses on the spread of ensembles that are not shown in this figure. Could this be included in the figure by shading be added where there is a large spread between the models?
For climate adaptations, the change in seasonality of precipitation is important, as summers become drier and autumn wetter for crop security. Although mentioned, the results could be included in supplementary. ‘The signal is not robust’, this needs to be shown, maybe by showing the spread between the RCMs in the Figures. As a general comment, since supplementary material is already included, the results described in the manuscript should also be provided. Referring to results and then stating 'not shown' is inconsistent and reduces clarity for the reader
The calculations in section 3.3 are not described in the method section. Are these also bias corrected? What models are included? Should also include CMIP6 models as they have been available for several years(CMIP7 results are available soon).
Figure 4 should have a legend, and darker color for the RCP4.5 and RCP8.5 models.
Figure 5- 8. These results would be more significant for future work if the different RCMs and GCMs were identified by model name on the y-axis. As some GCMs are too warm or too dry (or cold and wet) and labeling them would help highlight which models show large discrepancies.
Figure 9 Change colors (same as Figure 4) and the different time periods could have different markers. The calculations in section 3.5 is also not mentioned in Methods, how is the global temperature calculated?
Need to justify the statement ‘and that a GWL could be based on only one RCP’. This is not shown in the manuscript.
The references section should be checked. I could not find the Berg et al. 2022 reference and IPPC chapters should be referenced as they state on the first(second) page.
Minor Comments
P2. L38: Give some examples of the physical processes that is better represented.
P2. L42-43: Give a reference for this statement.
p.2 l.49-51. This sentence could be improved
p3. L.67: CMIP5 has been written out previously.
P5. L78-79: SMHIGridClim should not be in the same parenthesis as the reference (split), it is confusing if it is a reference or an abbreviation.
P6. Table 2 Could be simplified by putting ‘season or year’ in the legend of the table.
P7. L108. Split the parenthesis.
P11 Figure 3. Are these yearly means?
P12 l 183. Use another word than distance.
P15. L 233: Use different word than instead. Both results are presented.
Citation: https://doi.org/10.5194/egusphere-2025-2002-RC1
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