the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Apr 2024
Compound winter low wind and cold events impacting the French electricity system: observed evolution and role of large-scale circulation
Abstract. To reach climate mitigation goals, the share of wind power in the electricity production is going to increase substantially in France. In winter, low wind days are challenging for the electricity system if compounded with cold days that are associated with peak electricity demand. The scope of this study is to characterize the evolution of compound low wind and cold events in winter over the 1950–2022 period in France. Compound events are identified at the daily scale using a bottom-up approach based on two indices that are relevant to the French energy sector, derived from temperature and wind observations. The frequency of compound events shows high interannual variability, with some winters having no event and others having up to 13, and a decrease over the 1950–2022 period. Based on a k-means unsupervised classification technique, four weather types are identified, highlighting the diversity of synoptic situations leading to the occurrence of compound events. The weather type associated with the highest frequency of compound events presents pronounced positive sea-level pressure anomalies over Iceland and negative anomalies west of Portugal, limiting the entrance of the westerlies and inducing a north-easterly flow bringing cold air over France and Europe generally. We further show that the atmospheric circulation and its internal variability are likely to play a role in the observed reduction in cold days, suggesting that this negative trend may not be entirely be driven by anthropogenic forcings. Despite this suggested role for cold days, the observed decrease in compound events does not seem to be strongly influenced by the regional atmospheric circulation.
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RC1: 'Comment on egusphere-2024-903', Anonymous Referee #1, 11 May 2024
This paper presents an evaluation of compound events of low wind and cold events, which can pose a serious risk to the interconnected grid. The authors show a general decrease in the number of compound events, primarily driven by the significant negative trend in cold days that have decreased over the past decades. Furthermore, the influence of weather regimes is assessed by using a K-means classification technique and a dynamic adjustment is used to evaluate the contribution of atmospheric circulation to the variability in cold, low wind days and compound events. They found that the atmospheric circulation plays a role in the decreasing of cold days, while its impact is not clear in the reduction of compound events.
The paper is well written, clear and in my opinion addresses a relevant topic within the context of the current energy transition. Overall, the results are solid and consistent supported by previous works. I therefore support the publication of this manuscript. I have some minor comments and suggestion that can help to improve the readability of the manuscript.
Line 39. Onshore wind power capacity will increase to 30-39GW also by 2035? Please specify it.
Line 110. Is MERRA interpolated to ERA5 resolution of 0.25º?
Lines 162-164: Figures 1 and 2. Why not to have in the same plot wind and temperature in another plot? e.g., figure 1 a) with 2)b.
Line 180. Can the authors explain more why low wind are based on the 23th percentile? Is there any reasoning behind? I think this point is important.
Line 263. Figure 5. Why there is not green line (E-OBS) in 5a?
Line 305. This can be explained as the compound seem to be mostly driven by cold temperatures, so their patterns are very similar.
Line 403. “Overall” is repeated twice in the same sentence.
Lines 406-407. This is not very clear, can you please clarify what do you mean with “a simple change in the frequency”?
Lines 429-436. The authors state that the large-scale atmospheric circulation did not have influence in the observed decreased in the occurrence compound events, while it did in the occurrence of cold days. But, if the compound events are mostly driven by the cold days, how can the authors explain this?
Line 434. Where is -0.87 in table? This must be a mistake, please correct it.
Line 473-474. Can you be more specific?
Lines 487- 490. I would also add to this multifaceted problem the changes in the demand patterns and therefore, the changes in the compound events. Here, compound events are limited to cold days and low production. But if the demand increases in summer due to higher temperatures, this variability in compound events would change as well.Citation: https://doi.org/10.5194/egusphere-2024-903-RC1 - AC1: 'Reply on RC1', François Collet, 17 Sep 2024
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RC2: 'Comment on egusphere-2024-903', Anonymous Referee #2, 17 Jul 2024
This manuscript presents a study of low wind production and cold days and their compound occurrence, as challenging periods to France's energy system. Their occurrence is linked to certain weather types and the trends in their frequencies are explored through diverse methods.
The manuscript is clear and well presented but there are methodological decisions that are not properly justified and the results are not discussed in the context of existing literature in the field. My recommendation is that this manuscript could be published only after major revision. I include below the major and minor comments related to the manuscript:
Major comments:
- The description of the study is confusing in suggesting that the compound events are defined on the meteorological variables and not on electricity production, but the authors are using wind capacity factors, so they are not necessarily identifying low wind events, but rather low wind generation days. How are the authors ensuring that the so called ‘low wind’ conditions are not due to high wind speeds above cut-off?
- There is an asymmetry in the definition of the extreme events for the single variables (in terms of the percentile thresholds) that is not discussed. Relaxing the definition of the temperature threshold could have led to a larger sample of compound events and less sensitivity of the results for compounds to cold days that is seen throughout the analysis.
- The study is missing a comparison with other work considering weather types, copula approaches or circulation types with similar purposes. Though these body of research is presented in the introduction, there is no comparison or discussion. What is this work adding to the current understanding of regional circulation relevance of compound extremes?
Minor comments:
- Line 116, page 4: should be ‘and so on’.
- Lines 151-157, page 5: what is the impact of using the closest grid point to each site rather than for example a bilinear interpolation? Was this tested? It could reduce the dependence on the resolution of the gridded dataset, which is key when comparing ERA5 and MERRA-2, and the height-scaling could be applied before the interpolation. Also, it is not described how hourly wind speeds are obtained for each wind farm site. Is the same approach used?
- Lines 194-195, page 8: Looking at the distribution of cold days across weather types at a later stage does not imply accounting for the distribution of compound events. This needs to be better explained.
- Lines 217- 220, page 8: How was the choice of 50 constructed analogues justified. For each day the authors are choosing 1500 analogues from a pool of ~11000, so you are forcing more than 10%of the days to be ‘analogues’ that seems like a stretch, then buy repeating the procedure 50 times, the chances of all analogues being extremely similar is really big. Some sensitivity testing must have been performed for the choice of these numbers?
- Lines 237-238, page 9: “when both the dynamic component of low wind days and cold days occur”. This phrase does not make a lot of sense. What does it mean that the dynamic component occurs? It is a construction produced by averaging a lot of different things, so it is not really something that ‘occurs’.
- Figure 4: how is the seasonality of events presented over the full calendar year when they were defined for the extended winter only? Is the same threshold definition applied? How is that justified in terms of the percentiles? I think presenting the full year here is confusing and unnecessary.
- Table I: It reads ‘empty cells correspond to missing data’, but there are no empty cells but rather ‘/’. Also, this actually means different things, for example an incomplete period in MERRA-2, but an unavailable variable in the case of E-OBS.
- Lines 286-287, page 11: The larger sampling is a consequence of methodological choices, since a less extreme definition was considered for ‘low wind’ days
- Figures 6 and 7: they refer the wind composites to a % of climatological mean that is not clearly defined. Is this a seasonal mean? For the full extended winter? Is it the average of each day w.r.t. its daily climatological benchmark?
- Line 319, page 12: in the following what?
- Line 423, page 18: is large-scale circulation a fair description? The domain used for the analogues would seem to constraint it to regional circulation ?
- Lines 487-489, page 20: this discussion should include potential future changes in demand. For example, increases in warm seasons demand could lead to these events being more relevant in transition periods, as it was shown than “low wind” days are even more frequent then.
Citation: https://doi.org/10.5194/egusphere-2024-903-RC2 - AC2: 'Reply on RC2', François Collet, 17 Sep 2024
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