the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Apr 2024
Climate variability can outweigh the influence of climate mean changes for extreme precipitation under global warming
Abstract. As global warming progresses, weather conditions like daily temperature and precipitation are changing due to changes in their means and distributions of day-to-day variability. In this study, we show that changes in variability have a stronger influence on the number of extreme precipitation days than the change in the mean state in many locations. We analyze daily precipitation and maximum temperatures at four levels of global warming and under different emission scenarios for the Northern Hemisphere (NH) summer (June – August). Our analysis is based on initial condition large ensemble simulations from three fully coupled Earth System Models (MPI-ESM1-2-LR, CanESM5, and ACCESS-ESM1-5) contributing to the Climate Model Inter-comparison Project phase 6 (CMIP6). We also use information from the Precipitation Driver Response Model Intercomparison Project (PDRMIP) to discern the influence of different climate drivers (notably aerosols and greenhouse gases). We decompose the total changes in daily NH summer precipitation and daily maximum temperature into mean and variability components (standard deviation and skewness). Our results show that in many locations, variability exerts a stronger influence than mean changes on daily precipitation. Changes in the widths and shapes of precipitation distributions are especially dominating over mean changes in Asia, the Arctic and Sub-Saharan Africa. In contrast, temperature changes are primarily driven by changes in the mean state. For the near future (2020–2040), we find that reductions in aerosol emissions would increase the likelihood of extreme summertime precipitation only over Asia. This study emphasizes the importance of incorporating daily variability changes into climate change impact assessments and advocates that future emulator and impact model development should focus on improving the representation of daily variability.
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Status: closed
- RC1: 'Comment on egusphere-2024-1068', Anonymous Referee #1, 25 May 2024
- RC2: 'Comment on egusphere-2024-1068', Anonymous Referee #2, 26 Jun 2024
-
RC3: 'Comment on egusphere-2024-1068', Anonymous Referee #3, 05 Jul 2024
General Comments:
The study investigates the influence of climate variability and mean changes on extreme precipitation under global warming. It aims to determine which factor—variability or mean state changes—has a more significant impact on the frequency of extreme precipitation events. Using simulations from multiple Earth System Models, the authors analyse precipitation and temperature data under various warming scenarios and emissions. The study finds that changes in climate variability often have a stronger effect than mean changes on extreme precipitation events. The manuscript is well-structured, and the methods are appropriate for the research question.
The figures are generally well-designed, but some are too detailed and may overwhelm the reader. Simplifying these figures or breaking them into smaller parts could improve clarity. The study discusses regional impacts, but the analysis of why certain regions show stronger effects of variability will make it more comprehensive like exploration of regional climatic factors and their interactions with variability. The authors should ensure that the formatting is consistent. There are several areas where the manuscript can be improved to enhance clarity and impact.
Specific Comments:
Section 2.1: Although the methodology follows Samset et al. (2019b), the methods section can benefit from a clearer explanation of the process.
Figure 1: Clarify the colour coding used in the figures, especially in Panel b of Figure 1, to avoid confusion with the colour scheme used in Panel a.
Line 88 and Figure 1: The text and the figure should be consistent regarding the threshold for defining extreme events. Given that the 0.999th quantile is mentioned in the text, the figure should be adjusted to reflect this if that is the correct threshold used in the study.
Line 124: The text mentions using the multi-model mean across eight CMIP5-generation models for PDRMIP, but the table actually lists nine models.
Line 136: The text states: “Other common features among the models include a drying over the southern part of Europe.” However, Figure 2 specifically shows “Changes in the average number of days per year of extreme (0.90 quantile) precipitation.” The figure indicates a decrease in the number of days with extreme precipitation, not necessarily “drying,” which could imply a general decrease in precipitation, not just extremes.
Line 138 and Line 144: The text mentions changes in the standard deviation (SD) but does not reference the specific figures (Figure A4, A5, A6) that show these changes. The text should include references to these figures to guide the reader to the relevant visual data.
Figure 2: The caption of Figure 2 states: “Panel titles indicate if a model is emission- (emi) or concentration-driven (conc).” However, this information is not included in the figure itself. The figure should have this information clearly indicated in the panel titles. Although Figure A1, Figure A2 and Figure A3 with nine models are provided, it would be good to state why were those three models selected? HadGEM2 (emi) in Figure A3 certainly shows more changes than the selected HadGEM2 (conc).
Figure 3, Figure 4 and Figure 5: The text mentions stippling as a method to indicate regions where changes in the probability distribution functions (PDFs) are significant at p > 0.05 . However, in Figures 3, 4, and 5, the stippling is either not visible or absent. The absence of stippling suggests that the figures do not highlight areas where the changes are statistically significant according to this criterion. This could be an oversight or intentional if no regions met the significance threshold, but without stippling, the figures do not convey this additional layer of statistical information.
Figure 3 and Figure 4: Ensure the non-linear scale is intentional and justified, since the hue for -1 is the same as the hue for 5.
Line 160: The text should be revised to specify “northern hemisphere summer” or “boreal summer” when discussing seasonal changes in regions like the Amazon basin, South Africa, and Australia. This will ensure clarity and accuracy, as these regions do not experience “summer” in the same way as the Northern Hemisphere.
Line 170: The use of the term “aridity” in the context of Figure 5 may not be appropriate. The figure illustrates changes in the number of extreme JJA precipitation events due to changes in the mean state under different global warming levels.
Technical comments:
Line 20: Cop, 2023 → Copernicus, 2023 (Please correct the formatting in References too).
Line 28: Chen et al. (2021) → (Chen et al., 2021)
Line 29: Samset (2022) → (Samset, 2022)
Line 31: emissions(Persad, 2023 → emissions (Persad, 2023
Line 33: temperatures(Merikanto et al., 2021) → temperatures (Merikanto et al., 2021)
Line 82: ”PDF of total change´´ → “PDF of total change”
Line 97: timeperiod → time period
Line 114: SSP2.4-5 → SSP2-4.5
Line 115: ACCESS-ESM5- 1 → ACCESS-ESM1.5
Line 121: asses → assess
Line 124: year2000 → year 2000
Line 144: test test → test
Line 153: (IPCC, 2021) → IPCC (2021)
Line 187: Above, we have shown, using idealized simulations performed as part of PDRMIP, the influence of different anthropogenic drivers on Earth’s climate 3.1. → Above, we have shown, using idealized simulations performed as part of PDRMIP, the influence of different anthropogenic drivers on Earth’s climate (Section 3.1).
Figure 9 caption: extream → extreme
Line 215: model(Ziehn et al., 2020 → model (Ziehn et al., 2020
Citation: https://doi.org/10.5194/egusphere-2024-1068-RC3 - AC1: 'Comment on egusphere-2024-1068', Kalle Nordling, 24 Sep 2024
Status: closed
- RC1: 'Comment on egusphere-2024-1068', Anonymous Referee #1, 25 May 2024
- RC2: 'Comment on egusphere-2024-1068', Anonymous Referee #2, 26 Jun 2024
-
RC3: 'Comment on egusphere-2024-1068', Anonymous Referee #3, 05 Jul 2024
General Comments:
The study investigates the influence of climate variability and mean changes on extreme precipitation under global warming. It aims to determine which factor—variability or mean state changes—has a more significant impact on the frequency of extreme precipitation events. Using simulations from multiple Earth System Models, the authors analyse precipitation and temperature data under various warming scenarios and emissions. The study finds that changes in climate variability often have a stronger effect than mean changes on extreme precipitation events. The manuscript is well-structured, and the methods are appropriate for the research question.
The figures are generally well-designed, but some are too detailed and may overwhelm the reader. Simplifying these figures or breaking them into smaller parts could improve clarity. The study discusses regional impacts, but the analysis of why certain regions show stronger effects of variability will make it more comprehensive like exploration of regional climatic factors and their interactions with variability. The authors should ensure that the formatting is consistent. There are several areas where the manuscript can be improved to enhance clarity and impact.
Specific Comments:
Section 2.1: Although the methodology follows Samset et al. (2019b), the methods section can benefit from a clearer explanation of the process.
Figure 1: Clarify the colour coding used in the figures, especially in Panel b of Figure 1, to avoid confusion with the colour scheme used in Panel a.
Line 88 and Figure 1: The text and the figure should be consistent regarding the threshold for defining extreme events. Given that the 0.999th quantile is mentioned in the text, the figure should be adjusted to reflect this if that is the correct threshold used in the study.
Line 124: The text mentions using the multi-model mean across eight CMIP5-generation models for PDRMIP, but the table actually lists nine models.
Line 136: The text states: “Other common features among the models include a drying over the southern part of Europe.” However, Figure 2 specifically shows “Changes in the average number of days per year of extreme (0.90 quantile) precipitation.” The figure indicates a decrease in the number of days with extreme precipitation, not necessarily “drying,” which could imply a general decrease in precipitation, not just extremes.
Line 138 and Line 144: The text mentions changes in the standard deviation (SD) but does not reference the specific figures (Figure A4, A5, A6) that show these changes. The text should include references to these figures to guide the reader to the relevant visual data.
Figure 2: The caption of Figure 2 states: “Panel titles indicate if a model is emission- (emi) or concentration-driven (conc).” However, this information is not included in the figure itself. The figure should have this information clearly indicated in the panel titles. Although Figure A1, Figure A2 and Figure A3 with nine models are provided, it would be good to state why were those three models selected? HadGEM2 (emi) in Figure A3 certainly shows more changes than the selected HadGEM2 (conc).
Figure 3, Figure 4 and Figure 5: The text mentions stippling as a method to indicate regions where changes in the probability distribution functions (PDFs) are significant at p > 0.05 . However, in Figures 3, 4, and 5, the stippling is either not visible or absent. The absence of stippling suggests that the figures do not highlight areas where the changes are statistically significant according to this criterion. This could be an oversight or intentional if no regions met the significance threshold, but without stippling, the figures do not convey this additional layer of statistical information.
Figure 3 and Figure 4: Ensure the non-linear scale is intentional and justified, since the hue for -1 is the same as the hue for 5.
Line 160: The text should be revised to specify “northern hemisphere summer” or “boreal summer” when discussing seasonal changes in regions like the Amazon basin, South Africa, and Australia. This will ensure clarity and accuracy, as these regions do not experience “summer” in the same way as the Northern Hemisphere.
Line 170: The use of the term “aridity” in the context of Figure 5 may not be appropriate. The figure illustrates changes in the number of extreme JJA precipitation events due to changes in the mean state under different global warming levels.
Technical comments:
Line 20: Cop, 2023 → Copernicus, 2023 (Please correct the formatting in References too).
Line 28: Chen et al. (2021) → (Chen et al., 2021)
Line 29: Samset (2022) → (Samset, 2022)
Line 31: emissions(Persad, 2023 → emissions (Persad, 2023
Line 33: temperatures(Merikanto et al., 2021) → temperatures (Merikanto et al., 2021)
Line 82: ”PDF of total change´´ → “PDF of total change”
Line 97: timeperiod → time period
Line 114: SSP2.4-5 → SSP2-4.5
Line 115: ACCESS-ESM5- 1 → ACCESS-ESM1.5
Line 121: asses → assess
Line 124: year2000 → year 2000
Line 144: test test → test
Line 153: (IPCC, 2021) → IPCC (2021)
Line 187: Above, we have shown, using idealized simulations performed as part of PDRMIP, the influence of different anthropogenic drivers on Earth’s climate 3.1. → Above, we have shown, using idealized simulations performed as part of PDRMIP, the influence of different anthropogenic drivers on Earth’s climate (Section 3.1).
Figure 9 caption: extream → extreme
Line 215: model(Ziehn et al., 2020 → model (Ziehn et al., 2020
Citation: https://doi.org/10.5194/egusphere-2024-1068-RC3 - AC1: 'Comment on egusphere-2024-1068', Kalle Nordling, 24 Sep 2024
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