the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Role of mean and variability change for changes in European annual and seasonal extreme precipitation events
Abstract. The frequency of precipitation extremes is set to change in response to a warming climate. Thereby, the change in precipitation extreme event occurrence is influenced by both a shift in the mean and a change in variability. How large the individual contributions from either of them (mean or variability) to the change in precipitation extremes are, is largely unknown. This is however relevant for a better understanding of how and why climate extremes change. For this study, two sets of forcing experiments from the regional CRCM5 initial-condition large ensemble are used. A set of 50 members with historical and RCP8.5 forcing as well as a 35-member (700 year) ensemble of pre-industrial natural forcing. The concept of the probability risk ratio is used to partition the change in extreme event occurrence into contributions from a change in mean climate or a change in variability. The results show that the contributions from a change in variability are in parts equally important to changes in the mean, and can even exceed them. The level of contributions shows high spatial variation which underlines the importance of regional processes for changes in extremes. While over Scandinavia or Mid-Europe the mean influences the increase in extremes more, reversely the increase is driven by changes in variability over France, the Iberian Peninsula, and the Mediterranean. For annual extremes the differences between the ratios of contribution of mean and variability are smaller, while on seasonal scales the difference in contributions becomes larger. In winter (DJF) the mean contributes more to an increase in extreme events, while in summer (JJA) the change in variability drives the change in extremes. The level of temporal aggregation (3 h, 24 h, 72 h) has only a small influence on annual and winterly extremes, while in summer the contribution from variability can increase with longer durations. The level of extremeness for the event definition generally increases the role of variability. These results highlight the need for a better understanding of changes in climate variability to better understand the mechanisms behind changes in climate extremes.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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Supplement
(1275 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-32', Anonymous Referee #1, 18 Mar 2023
In this study, the author investigated the contributions of the changes in mean and variability of climate to the change in precipitation extreme events over Europe, basing on CRCM5 simulations. The author suggested that the contributions from a change in variability are in parts equally important to changes in the mean, and can even exceed them. For the level of contributions, there are regional differences. In addition, the contributions also show differences in summer and winter. The topic is interesting and the results are valuable to better understand the changes in the precipitation extremes over Europe. I have following comments and suggestions:
- I remember that the pre-industrial control simulations did not include the natural forcing. If so, the CRCM5 simulations drived by the CanESM2 pre-industrial control simulations cannot be used as the NAT forcing experiment.
- Are the warming levels of 1, 2, 3, and 4 Celsius degrees calculated from global mean or regional mean? The related information should be given in the manuscript.
- In this study, the author used the 50-memer initial-condition large ensemble. So the result uncertainty from the initial conditions should be given in the manuscript.
- The author presented well the results. I suggest that the author could make some discussion on the possible reasons of the results. For example, the strongest increases in the total risk ratio can be seen in the Scandinavian region. Why is the strongest increase in the region? Related discussion can enrich the manuscript.
- The result shows that in summer the PRvar is above the PRmean, and in winter vice versa. Possible reasons should also be discussed.
Citation: https://doi.org/10.5194/egusphere-2023-32-RC1 - AC1: 'Reply on RC1', Raul R. Wood, 11 May 2023
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RC2: 'Comment on egusphere-2023-32', Anonymous Referee #2, 15 Apr 2023
Wood uses a method to attribute changes in the probability of extreme events to either changing mean climate or climate variability. This is applied at a high-resolution regional scale, to explain changes to short-duration (3hr-72hr) precipitation extremes. The results are very interesting, and give an insight into the mechanisms of climate change in Europe.
I expect the results to be of interest to the readership of ESD. The manuscript is generally well written, though needs some clarifications and credits in places. I thus recommend acceptance after revisions.
General point
The analysis leans heavily on the calculation of probability ratio and specifically the separation in two contributing parts. This method was developed in Van der Wiel & Bintanja 2021. This study should therefore be cited in a few key locations in the manuscript, to inform the reader of the origin on the method, and to show on what background you built out with very useful insights on the drivers of changing short-duration precipitation extremes, and to give credit where it is due. I list the locations in the manuscript here, where a reference to the paper should be added:
- Line 75 - Add in this short summary of the paper that you will follow the Van der Weil & Bintanja (2020) methodology, rather than noting you will use ‘the probability risk ratio’.
- Line 116 - Start the Methods section with the correct information.
- Line 487 - Again, in your conclusion section give credit and help the reader find the relevant reference.
- Figure 1 - After looking up the original paper, I noted that this figure is very close (copied from?) their figure 1. I believe you have to add "Taken after their figure 1" or something, and please check if there are copyright issues (maybe not because you replotted?, I’m no expert).
Major points
Line 33 - I don’t understand the addition of ‘mean state’ here. The magnitude of an extreme precip event is the total volume of water in a time period/for an event. Please clarify what you mean (or remove the bit between brackets).
Figure 5 - Maybe add a note in the text on whether you have an idea on whether the trend you see, between different warming levels, is a significant one. In some regions it is steady, but e.g. in IP the lines seem to spread and come together again. I don’t think there is necessarily a dynamic/circulation reason to expect this? This is useful here, but also in other places. Are the changes you note, between warming levels, extremeness, aggrevation, physically in origin?
Minor points
Line 26,27 - maybe remove one of the ‘devastating’ ?
Line 39- 41 - Add more clearly at the beginning of the sentence that you are talking about global mean here. The next sentence came as a surprise to me.
Line 48 - The statement about changes in distribution does not at all follow from the sentence about occurrence. Maybe put the first sentence of this paragraph with the previous, and start here about the distribution/mean and variability etc.
Line 86 - ‘All 50-members’, add the s
Line 190 - Somewhere in this paragraph you might (if you’d like) add that there is no obvious spatial pattern in Fig 2 to be distinguished.
Line 231 - What is Prudence?
Figure 4/5 - I’m not sure what AMAX is in the legend?
Figure 4/5 - Given all your PR values are positive (i.e. above 1, or above 0), you might cut the subplots at y=1. This would give more details on the values and differences between warming levels.
Line 346 - for the change in sign, refer to figure 7?
Figure 7/9 - probably too many lines to be useful/interpretable? Maybe when comparing seasons, don’t show the warming levels? Then you can use the x-axis for seasons maybe.
Figure 10 - most of your y-axis is useless, consider cutting it off at -.4 C ?
Line 423 - You note that more extreme events, have a larger variability contribution? Do you think this is due to a physical process (if so, can you hypothesise which?) or is decreased sampling here an issue?
Citation: https://doi.org/10.5194/egusphere-2023-32-RC2 - AC2: 'Reply on RC2', Raul R. Wood, 11 May 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-32', Anonymous Referee #1, 18 Mar 2023
In this study, the author investigated the contributions of the changes in mean and variability of climate to the change in precipitation extreme events over Europe, basing on CRCM5 simulations. The author suggested that the contributions from a change in variability are in parts equally important to changes in the mean, and can even exceed them. For the level of contributions, there are regional differences. In addition, the contributions also show differences in summer and winter. The topic is interesting and the results are valuable to better understand the changes in the precipitation extremes over Europe. I have following comments and suggestions:
- I remember that the pre-industrial control simulations did not include the natural forcing. If so, the CRCM5 simulations drived by the CanESM2 pre-industrial control simulations cannot be used as the NAT forcing experiment.
- Are the warming levels of 1, 2, 3, and 4 Celsius degrees calculated from global mean or regional mean? The related information should be given in the manuscript.
- In this study, the author used the 50-memer initial-condition large ensemble. So the result uncertainty from the initial conditions should be given in the manuscript.
- The author presented well the results. I suggest that the author could make some discussion on the possible reasons of the results. For example, the strongest increases in the total risk ratio can be seen in the Scandinavian region. Why is the strongest increase in the region? Related discussion can enrich the manuscript.
- The result shows that in summer the PRvar is above the PRmean, and in winter vice versa. Possible reasons should also be discussed.
Citation: https://doi.org/10.5194/egusphere-2023-32-RC1 - AC1: 'Reply on RC1', Raul R. Wood, 11 May 2023
-
RC2: 'Comment on egusphere-2023-32', Anonymous Referee #2, 15 Apr 2023
Wood uses a method to attribute changes in the probability of extreme events to either changing mean climate or climate variability. This is applied at a high-resolution regional scale, to explain changes to short-duration (3hr-72hr) precipitation extremes. The results are very interesting, and give an insight into the mechanisms of climate change in Europe.
I expect the results to be of interest to the readership of ESD. The manuscript is generally well written, though needs some clarifications and credits in places. I thus recommend acceptance after revisions.
General point
The analysis leans heavily on the calculation of probability ratio and specifically the separation in two contributing parts. This method was developed in Van der Wiel & Bintanja 2021. This study should therefore be cited in a few key locations in the manuscript, to inform the reader of the origin on the method, and to show on what background you built out with very useful insights on the drivers of changing short-duration precipitation extremes, and to give credit where it is due. I list the locations in the manuscript here, where a reference to the paper should be added:
- Line 75 - Add in this short summary of the paper that you will follow the Van der Weil & Bintanja (2020) methodology, rather than noting you will use ‘the probability risk ratio’.
- Line 116 - Start the Methods section with the correct information.
- Line 487 - Again, in your conclusion section give credit and help the reader find the relevant reference.
- Figure 1 - After looking up the original paper, I noted that this figure is very close (copied from?) their figure 1. I believe you have to add "Taken after their figure 1" or something, and please check if there are copyright issues (maybe not because you replotted?, I’m no expert).
Major points
Line 33 - I don’t understand the addition of ‘mean state’ here. The magnitude of an extreme precip event is the total volume of water in a time period/for an event. Please clarify what you mean (or remove the bit between brackets).
Figure 5 - Maybe add a note in the text on whether you have an idea on whether the trend you see, between different warming levels, is a significant one. In some regions it is steady, but e.g. in IP the lines seem to spread and come together again. I don’t think there is necessarily a dynamic/circulation reason to expect this? This is useful here, but also in other places. Are the changes you note, between warming levels, extremeness, aggrevation, physically in origin?
Minor points
Line 26,27 - maybe remove one of the ‘devastating’ ?
Line 39- 41 - Add more clearly at the beginning of the sentence that you are talking about global mean here. The next sentence came as a surprise to me.
Line 48 - The statement about changes in distribution does not at all follow from the sentence about occurrence. Maybe put the first sentence of this paragraph with the previous, and start here about the distribution/mean and variability etc.
Line 86 - ‘All 50-members’, add the s
Line 190 - Somewhere in this paragraph you might (if you’d like) add that there is no obvious spatial pattern in Fig 2 to be distinguished.
Line 231 - What is Prudence?
Figure 4/5 - I’m not sure what AMAX is in the legend?
Figure 4/5 - Given all your PR values are positive (i.e. above 1, or above 0), you might cut the subplots at y=1. This would give more details on the values and differences between warming levels.
Line 346 - for the change in sign, refer to figure 7?
Figure 7/9 - probably too many lines to be useful/interpretable? Maybe when comparing seasons, don’t show the warming levels? Then you can use the x-axis for seasons maybe.
Figure 10 - most of your y-axis is useless, consider cutting it off at -.4 C ?
Line 423 - You note that more extreme events, have a larger variability contribution? Do you think this is due to a physical process (if so, can you hypothesise which?) or is decreased sampling here an issue?
Citation: https://doi.org/10.5194/egusphere-2023-32-RC2 - AC2: 'Reply on RC2', Raul R. Wood, 11 May 2023
Peer review completion
Journal article(s) based on this preprint
Data sets
CRCM5-LE ClimEx-Project https://climex-data.srv.lrz.de/Public/
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2098 KB) - Metadata XML
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Supplement
(1275 KB) - BibTeX
- EndNote
- Final revised paper