A life cycle definition of year-round weather regimes in the North Atlantic European region

Grams, Christian M.

doi:10.5194/egusphere-2025-6385

Preprints

https://doi.org/10.5194/egusphere-2025-6385

Preprints

05 Jan 2026

| 05 Jan 2026

A life cycle definition of year-round weather regimes in the North Atlantic European region

Christian M. Grams

Abstract. Weather regimes are quasi-stationary, persistent, and recurrent states of the large-scale extratropical circulation. Weather regimes explain most of the multi-day atmospheric variability on sub-seasonal time scales of 5 to 30 days. While regime definitions have been explored for the European region extensively, in recent years the existence of regimes in other world regions such as North and South America and East Asia has been confirmed. Importantly, traditional regime definitions focus on a specific season and different techniques are needed for year-round applications.

Using ERA-Interim reanalysis, Grams (2017) introduced a year-round weather regime definition for the North-Atlantic European region which accounts for inter-seasonal differences by construction. Following established regime approaches they identified seven regime patterns based on 500 hPa geopotential height anomalies. The definition has been used in numerous studies for e.g. explaining surface weather modulation on multi-day time scales and the occurrence of extremes with applications, particularly in the energy sector. Furthermore the definition identifies objective regime life cycles facilitating process studies. These studies revealed dynamical behaviour of regime life cycles, and specific physical processes that determine regime life cycles, in particular those characterised by blocking. Finally, the predictability and forecast skill for the year-round regimes have been explored, linked to the representation of physical and dynamical processes, and pre-operational forecasting tools have been implemented.

This study now provides an update on ERA5 reanalysis data 1979-2019 and a thorough documentation of the seamingless year-round definition of seven North-Atlantic European weather regimes, accompanied with the open release of data and auxiliary scripts at Zenodo (Grams, 2025) for an easy start working with the regimes. First, the paper explains in detail the technical implementation of the weather regimes and why there is an optimal number of seven year-round regimes in the North Atlantic European region. Next, it shows similarities and differences to the canonical definition of seasonal weather regimes in Europe. A discussion of key characteristics follows, focussing on the inter-annual and intra-annual variability in regime occurrence, the duration of life cycles, regime transitions, and the modulation of surface weather and extremes. Finally, potential trends in regime occurrence are explored by extending the regime identification to the period 1950–2024. Overall inter-annual variability of regime occurrence dominates and there are hardly significant trends. The only exemption is Scandinavian Blocking which shows a significant positive trend in summer and autumn in line with expected trends. The trend can be related to the thermal expansion of the troposphere under global warming but is highly sensitive to the methodology used.

Received: 19 Dec 2025 – Discussion started: 05 Jan 2026

Competing interests: At least one of the (co-)authors is a member of the editorial board of Weather and Climate Dynamics.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

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Christian M. Grams

Status: closed

RC1:
'Comment on egusphere-2025-6385', Anonymous Referee #1, 11 Feb 2026
This is an engaging and informative account of the development of the seven year-round weather regimes. I am convinced of the utility of the approach, and feel the author justifies the conclusions made. I did find the manuscript quite long, and wonder whether this would deter others from reading it fully. I do find some places where a re-write could reduce the length and, partly for this reason, I recommend “major revision”. Below, I give some general comments, more specific points, and finally highlight some typos and difficult to understand text
General comments
I several places the words “cause” and “affect” are used when the relationship might simply represent consistency: For example, correlations between surface conditions and the regime classification might not represent direct causation, but be due to a latent/hidden variable (namely the mean of the synoptic-scale weather), which affects both the regime classification and the surface conditions.

I think Section 4.2 (Overview of the seven year-round regimes and comparison to canonical seasonal regime definitions) could be re-focused and shortened (see below for specifics)

I found Section 6 (Variability and trends in regime occurrence 1950–2024) quite confusing (see below for specifics)

Specific point
Line 122: “This could only be achieved using a life cycle definition”. Why only?

Line 171: “fuzzy clustering”. A brief description and citation (currently given later) would be useful.

Line 193: What about tc = February 29?

Line 203: Change “smoothed” to “running”?

Line 213: Change “up to” to “including”?

Line 223-234: “The scalar is defined as the spatial average of the climatological “temporal 30-day running standard deviation…” I find this explanation difficult to follow. Is the following in agreement with process?:

(a) For each grid point and calendar time, we calculate the standard deviation of Z500^LF(gp,tc) over the years 1979-2019.
(b) We then calculate the 30-day running mean of these grid point standard deviations.
(c) We then calculate the area integral of these running means
(d) These area integrals are used to normalise Z500^LT(t)
Lines 256-257: “The EOF-clustering attributes each 6-hourly time step t unambiguously to one of the clusters by minimizing the intra- and inter-cluster distances in EOF phase space”. The word “unambiguously” suggests to me that the author is setting up the fuzzy-c-means clustering to replicate k-means clustering (with no fuzziness). I also suspect that the minimisation is just based on intra-cluster distances(?). I wondered in the author could also comment on sensitivity to cluster seeding. Looking later, maybe the similarity of clusters with increasing k (Fig. 3) also demonstrates that the regimes are insensitive to seeding(?)

Line 280: Is it fair to say that the regimes Z500*wr are not standardised, and that normalisation is done separately for the each weather regime index time series so that all regimes effectively get equal weight even if the rms of projections onto some weather regimes are stronger than for others? Maybe it would be worth noting this.

Line 292: “statistical jargon”. I find this phraseology a bit too familiar for an academic paper.

Line 315 and 316: “to some degree”. Maybe add “(to be discussed later)”.

Line 333: I am a bit perplexed by the gradient approach to defining the start and end of a saturation period. If one imagines a Gaussian curve, there will be low gradients far from the maximum and also close to the maximum (with stronger gradients in-between). How does the approach choose between the two regions with low gradient?

Line 352: 100 days sounds a lot. Is there some reason for this?

Line 397: “into I_EuBL”. Should this be “onto weather regime EuBC”?

Line 398-399: “At that time a transition into a GL life cycle begins and the ScBL life cycle ultimately decays on 3 March (dark green). This is also when – out of the perspective of the ScBL life cycle (dcto) – the transition tr to GL is objectively identified”. It looks slightly odd that the transition time is not closer to 1 March. Is it not possible (in reality) to have a transition prior to time dc?

Figure 2. I see a transition “ScBL to GL” marked at 3 March, and the next transition seems to be “AT to GL”. Is there supposed to be a transition “GL to AT” in between? If not, some extra explanation would be useful.

Figure 3. Were different seeds used for each value of k? (Maybe there has to be by virtue of k changing?). If so, then this might also be a good opportunity to highlight that the clusters appear to be insensitive to the initial seed. I do wonder if this figure could be reduced to just rows 3 and 6 (perhaps with the no regime added and percentages altered accordingly).

Line 470: “and a weak positive anomaly south of Iceland”. Change to “negative”?

Section 4.2 (“Overview of the seven year-round regimes and comparison to canonical seasonal regime definitions” is currently over 4 pages long in the double-spaced submission). I think this could be re-focused and shortened. For me, the two key points to make here are (a) that the seasonal regimes differ over the annual cycle and (b) that all 4x4=16 seasonal regime patterns are well catered for in the seven year-round regimes. To this end, I would simply include in the main body of the text Fig. A3 (rows 2,3,4,5) to highlight the differences over the annual cycle, and Fig. A4 (a,b,c,d) to demonstrate that (with the possible exception of “ZO”in DJF) all seasonal regimes have a single preferred projection onto the year-round regimes. (This is in opposition to the four year-round regimes which generally project on 2 or 3 of the seven year-round regimes in Fig 6a). This means Fig. 4, 5, 6 could be eliminated (and Fig. A3 and A4 removed from the appendix). In any case, Fig. 4 (Fig. 5) seems to be the same as row 3 (row 6) of Fig. 3, except for a scaling difference(?). The other message from Fig. 3, that regimes become sharper as k increases, might be adequately portrayed by simply showing rows 3 and 6.

Lines 583-587: Confusing to use the word “Europe” in the context of Scandinavian blocking, since “Europe” is used in the title for the other blocking regime. Maybe the seasonal cycle in dominance of EuBL vs ScBL relates to the seasonal cycle in mean latitude of the jet stream?

Line 601: “the very hot year 2003”. Change to “the very hot year 2003 in Europe”?

Line 602-604: “Already by visual inspection Figure 7b gives the impression of an increase of the frequency of blocked regimes (in particular ScBL, dark green, but also EuBL, light green, and GL, blue) recent decades”. Not very clear to me. Stacked plots can be a bit misleading. May be a graph with 8 curves would be clearer?

Line 612: “By definition regime life cycles have a minimum duration of 5 days”. Change to “By the current definition, regime life cycles have a minimum duration of 5 days”?

Line 627-628: “However, for the canonical European regimes it is difficult to identify such clearly preferred regime transitions”. What has been tried and not worked? The weather regimes are based on 10-day low-pass filtered data. However, for classification, a minimum duration of only 5 days is required. Discussion of these choices (and sensitivities) would be useful. Is this choice of 5 days minimum duration inspired by/consistent with the timescales for propagation of Rossby waves (with commensurate scales to the regime patterns)? Maybe there is a timescale which optimises coherent transitions between regimes?

Lines 635-651: I am not sure readers will learn much from this discussion. Maybe it would be better to concentrate on just the most striking transitions (or lack of transitions) that the author can or cannot explain?

Line 645: The transition GL to AT is striking. I’m not sure if the explanation is correct. Surely GL represents a weakening of the jet stream while AT represents a southward shift?

Line 654: “in terms of duration the mean” change to “in terms of duration of the mean”?

Line 718: “also affect”. See general comment 1.

Line 723: “GL brings above average precipitation”. See general comment 1.

Line 738: “how regimes affect surface weather”. See general comment 1.

Figure 9 column 1, row 7 (GL DJF): Is it extreme warm anomaly to the west of the Greenland High in winter due to warm meridional advection?

Lines 774-776: “Recalling that the mean Z500 anomalies associated with the regimes are of an order of O(100 gpm), the trends in Z500 are an order of magnitude smaller (O(10 gpm)) so that one may argue that the anomalies imposed by regimes still dominate over a potential signal by global trends in Z500”. Is the author referring to Fig.1b? Does it make sense to compare magnitudes of intra-seasonal variability with inter-annual trends?

Lines 783-784: “We follow Lee et al. (2023) and compute the residual trend by subtracting the linear trend 1979-2019 of 5.398 gpm (10yr)−1 from the full-trend (Figure 14c)”. I am not sure I understand. Does the author mean “We follow Lee et al. (2023) and compute the residual trend by subtracting the area-integrated linear trend 1979-2019 of 5.398 gpm (10yr)−1 from each the local linear trend (Figure 14c)”? It is also confusing to start with “We follow…” since it seems that this is only for Fig. 14c. After that, the area-integrated trend seems to be removed(?)

Line 801-802: “The trend signal is likely of the same order of magnitude as internal variability of regime occurrence”. I am not sure I understand this, or why it should be likely.

Line 816: “depending on the period considered for linear trend analysis”. This caveat seems to confuse things. Moreover, are the cluster definitions AND the projections onto the clusters based on de-trended data. This is not clear.

Lines 819-820: “Detrending or not does not affect the overall regime identification, yet, but gives helpful insight in the interpretation of trends”. This is confusing. Maybe delete “or not does not affect the overall regime identification, yet, but”?

Lines 823-824: “Notwithstanding, overall higher geopotential height amplifies the impact of blocking in terms of surface weather, in particular with respect to summer heat waves”. This seems very speculative to me.

Lines 862-863: “This is likely due to the thermal expansion of the troposphere under global warming, which is regionally amplified in that region”. I thought the author was not accounting for regional anomalies in trends in the case were the ScBL signal disappeared (?)

Typos
Lines 15 and 172: seamingless replaced with seamless?

Lines 31-35: These two sentences are difficult to read

Lines 80-81: “Another perspective looks at regimes in the eddy-driven jet and could be reconciled with the regime perspective”. The two uses of regime here is confusing.

Line 89: “an” to “and”

Line 617: Change “exemption” to “exception”?
Citation: https://doi.org/10.5194/egusphere-2025-6385-RC1
RC2:
'Comment on egusphere-2025-6385', Anonymous Referee #2, 20 Feb 2026
This paper was a very interesting read - as someone who has followed the Gramms groups outputs since publication of the original ERA-interim based set of patterns in 2017. This is as the author intended, an excellent detailed summary of the methodology for any new users of the year-round weather regime methodology with access to the dataset in zenodo (this downloads fine and has a high quality documentation attached).
My first question here – to the editors and author – is if weather and climate dynamics is the right home for this work as this is a dataset description paper, with minimal scientific advancement from the perspective of fundamental meteorology/climate science. From what I can see the advancement is limited to section 6, since upgrading from ERA-int to ERA5 makes next to no difference in the assignment/implementation of the methods. I emphasise I am not denying the usefulness of this work, just if a transfer could ease the review process. Some comments on the attached manuscript are below, but it may require some relatively major revision to the text/further analysis to sit in WCD.

General comments
Abstract: consider if keeping in WCD increasing the description of the novelty of this work as the first 15 lines currently review/introduce the methods history.

L87, weather types are sometimes referred to as ‘weather patterns’ e.g. Neal et al., (2016) which you cite.

L169-185: This could be better placed in literature review than methods.

I would suggest moving Appendix A1 into the main text of the paper as this is the scientific advancement presented in this paper compared to previous studies. Similarly Figure A1.

L210: Is the result significantly different without the low pass filtering?

Figure 1: Can you add a axis label to the colourbar? Figure 1 also appears in the text before it is referenced (check throughout).

L246: There is a mix of We/I in the paper, and a mix of active and passive voice that could be made consistent.

L247: The other methods often use a cosine based latitudinal weighting on the grid to make sure that their are no biases to larger grid box areas. Have you also done this?

L254: How does this work? e.g. The difference of the fuzzy-c-means from k-means that is used in the Cassou (2008) method?

L271: Remind readers this was first described in Bueler et al., 2021 and you're expanding here. Rather than this paper ‘newly introducing’.

L308: I was not sure what you meant by ‘catch up’.

L318: I found the quantitative descriptions more useful than the qualitive statements, so these could come after the quantitative descriptions for readers who require them?

L328: Why is 5 days used as a threshold?

L363-365: I appreciate the statement about criteria selection but are you able to provide any more details as to why these decisions are optimal/ideal?

L389: reference Figure 2 in first sentence.

Fig 2: it’s a bit hard to read the 'on' and 'oc' and 'tr' on the graph, can you offset them slightly from the line centre or give the text a white background? It would also be useful to have the IWr maximum regime (i.e. which is furthest above 1) as a bar like the unambiguous categorical definition so it is easier to compare the differences when using the lifecycle definition.

Section 4 lines 4.14 -430 can be removed. This information is present in the introduction.

Figure 3: This is interesting, but could be made supplementary and focus on Figure 5

L453: I don't not really agree about the patterns look blurry they look very similar to me, can you direct my eye to the key difference points I should see?

Section 4.2, Given the limited differences between these patterns and those described with ERA-int in Gramms et al., 2017 this could be condensed?

In Fig 6 can you use colours for the 4 that are not used in the 7 to make the plot easier to interpret? I got a bit confused when I first used these on the double use of the primary colours.

L578: EuBl and AR also look relatively similar for their year round occurrences in Fig 7?

L585: There is repetition here from previous sections.

Fig 8 caption, add (LC) so we know what the acronym stands for in the Figure.

L619: Are the differences statistically significant?

L625-635: Move to appropriate point in literature review.

Section 5.4: Consider if this section is needed in so much depth or if the material could be moved to the supplement. It's noted that the results are present in other papers that are cited. For example, ‘The following provides an overview of these studies’ should not be the topic of a results section in a new science paper.

Conclusions: Can you clarify the novelty vs. synthesis aspects of this work compared to the previous studies more clearly in the conclusions.

Figure A1: This would be interesting for the main text and methods given the update of the method for the new dataset.

Figure A2: A difference plot here would be interesting as they look the same to me by eye instead of the comparison.
Citation: https://doi.org/10.5194/egusphere-2025-6385-RC2
EC1: 'Comment on egusphere-2025-6385', Juliane Schwendike, 25 Feb 2026

The paper fits within the scope of WCD as dynamical weather regimes are investigated and characterized. These regimes are widely used and relevant for the atmospheric dynamics community. However, the framing of the paper could be improved to de-emphasize the technical aspects and focus more on the scientific findings, for instance regarding temporal variability and trends in weather regime occurrence. The novel aspects of the work could be highlighted more as well.

Citation: https://doi.org/10.5194/egusphere-2025-6385-EC1
AC1: 'Comment on egusphere-2025-6385', Christian Grams, 08 May 2026

I thank the reviewers and the editor for their thoughtful review and careful recommendations on the manuscript and their general appreciation of the work. The editor and reviewers raise two somewhat similar major concerns. The first concern is about the fit in WCD, and the second concern about the length of the article. I will address these as outlined in the attached detailed author responses.

Citation: https://doi.org/10.5194/egusphere-2025-6385-AC1

Status: closed

RC1:
'Comment on egusphere-2025-6385', Anonymous Referee #1, 11 Feb 2026
This is an engaging and informative account of the development of the seven year-round weather regimes. I am convinced of the utility of the approach, and feel the author justifies the conclusions made. I did find the manuscript quite long, and wonder whether this would deter others from reading it fully. I do find some places where a re-write could reduce the length and, partly for this reason, I recommend “major revision”. Below, I give some general comments, more specific points, and finally highlight some typos and difficult to understand text
General comments
I several places the words “cause” and “affect” are used when the relationship might simply represent consistency: For example, correlations between surface conditions and the regime classification might not represent direct causation, but be due to a latent/hidden variable (namely the mean of the synoptic-scale weather), which affects both the regime classification and the surface conditions.

I think Section 4.2 (Overview of the seven year-round regimes and comparison to canonical seasonal regime definitions) could be re-focused and shortened (see below for specifics)

I found Section 6 (Variability and trends in regime occurrence 1950–2024) quite confusing (see below for specifics)

Specific point
Line 122: “This could only be achieved using a life cycle definition”. Why only?

Line 171: “fuzzy clustering”. A brief description and citation (currently given later) would be useful.

Line 193: What about tc = February 29?

Line 203: Change “smoothed” to “running”?

Line 213: Change “up to” to “including”?

Line 223-234: “The scalar is defined as the spatial average of the climatological “temporal 30-day running standard deviation…” I find this explanation difficult to follow. Is the following in agreement with process?:

(a) For each grid point and calendar time, we calculate the standard deviation of Z500^LF(gp,tc) over the years 1979-2019.
(b) We then calculate the 30-day running mean of these grid point standard deviations.
(c) We then calculate the area integral of these running means
(d) These area integrals are used to normalise Z500^LT(t)
Lines 256-257: “The EOF-clustering attributes each 6-hourly time step t unambiguously to one of the clusters by minimizing the intra- and inter-cluster distances in EOF phase space”. The word “unambiguously” suggests to me that the author is setting up the fuzzy-c-means clustering to replicate k-means clustering (with no fuzziness). I also suspect that the minimisation is just based on intra-cluster distances(?). I wondered in the author could also comment on sensitivity to cluster seeding. Looking later, maybe the similarity of clusters with increasing k (Fig. 3) also demonstrates that the regimes are insensitive to seeding(?)

Line 280: Is it fair to say that the regimes Z500*wr are not standardised, and that normalisation is done separately for the each weather regime index time series so that all regimes effectively get equal weight even if the rms of projections onto some weather regimes are stronger than for others? Maybe it would be worth noting this.

Line 292: “statistical jargon”. I find this phraseology a bit too familiar for an academic paper.

Line 315 and 316: “to some degree”. Maybe add “(to be discussed later)”.

Line 333: I am a bit perplexed by the gradient approach to defining the start and end of a saturation period. If one imagines a Gaussian curve, there will be low gradients far from the maximum and also close to the maximum (with stronger gradients in-between). How does the approach choose between the two regions with low gradient?

Line 352: 100 days sounds a lot. Is there some reason for this?

Line 397: “into I_EuBL”. Should this be “onto weather regime EuBC”?

Line 398-399: “At that time a transition into a GL life cycle begins and the ScBL life cycle ultimately decays on 3 March (dark green). This is also when – out of the perspective of the ScBL life cycle (dcto) – the transition tr to GL is objectively identified”. It looks slightly odd that the transition time is not closer to 1 March. Is it not possible (in reality) to have a transition prior to time dc?

Figure 2. I see a transition “ScBL to GL” marked at 3 March, and the next transition seems to be “AT to GL”. Is there supposed to be a transition “GL to AT” in between? If not, some extra explanation would be useful.

Figure 3. Were different seeds used for each value of k? (Maybe there has to be by virtue of k changing?). If so, then this might also be a good opportunity to highlight that the clusters appear to be insensitive to the initial seed. I do wonder if this figure could be reduced to just rows 3 and 6 (perhaps with the no regime added and percentages altered accordingly).

Line 470: “and a weak positive anomaly south of Iceland”. Change to “negative”?

Section 4.2 (“Overview of the seven year-round regimes and comparison to canonical seasonal regime definitions” is currently over 4 pages long in the double-spaced submission). I think this could be re-focused and shortened. For me, the two key points to make here are (a) that the seasonal regimes differ over the annual cycle and (b) that all 4x4=16 seasonal regime patterns are well catered for in the seven year-round regimes. To this end, I would simply include in the main body of the text Fig. A3 (rows 2,3,4,5) to highlight the differences over the annual cycle, and Fig. A4 (a,b,c,d) to demonstrate that (with the possible exception of “ZO”in DJF) all seasonal regimes have a single preferred projection onto the year-round regimes. (This is in opposition to the four year-round regimes which generally project on 2 or 3 of the seven year-round regimes in Fig 6a). This means Fig. 4, 5, 6 could be eliminated (and Fig. A3 and A4 removed from the appendix). In any case, Fig. 4 (Fig. 5) seems to be the same as row 3 (row 6) of Fig. 3, except for a scaling difference(?). The other message from Fig. 3, that regimes become sharper as k increases, might be adequately portrayed by simply showing rows 3 and 6.

Lines 583-587: Confusing to use the word “Europe” in the context of Scandinavian blocking, since “Europe” is used in the title for the other blocking regime. Maybe the seasonal cycle in dominance of EuBL vs ScBL relates to the seasonal cycle in mean latitude of the jet stream?

Line 601: “the very hot year 2003”. Change to “the very hot year 2003 in Europe”?

Line 602-604: “Already by visual inspection Figure 7b gives the impression of an increase of the frequency of blocked regimes (in particular ScBL, dark green, but also EuBL, light green, and GL, blue) recent decades”. Not very clear to me. Stacked plots can be a bit misleading. May be a graph with 8 curves would be clearer?

Line 612: “By definition regime life cycles have a minimum duration of 5 days”. Change to “By the current definition, regime life cycles have a minimum duration of 5 days”?

Line 627-628: “However, for the canonical European regimes it is difficult to identify such clearly preferred regime transitions”. What has been tried and not worked? The weather regimes are based on 10-day low-pass filtered data. However, for classification, a minimum duration of only 5 days is required. Discussion of these choices (and sensitivities) would be useful. Is this choice of 5 days minimum duration inspired by/consistent with the timescales for propagation of Rossby waves (with commensurate scales to the regime patterns)? Maybe there is a timescale which optimises coherent transitions between regimes?

Lines 635-651: I am not sure readers will learn much from this discussion. Maybe it would be better to concentrate on just the most striking transitions (or lack of transitions) that the author can or cannot explain?

Line 645: The transition GL to AT is striking. I’m not sure if the explanation is correct. Surely GL represents a weakening of the jet stream while AT represents a southward shift?

Line 654: “in terms of duration the mean” change to “in terms of duration of the mean”?

Line 718: “also affect”. See general comment 1.

Line 723: “GL brings above average precipitation”. See general comment 1.

Line 738: “how regimes affect surface weather”. See general comment 1.

Figure 9 column 1, row 7 (GL DJF): Is it extreme warm anomaly to the west of the Greenland High in winter due to warm meridional advection?

Lines 774-776: “Recalling that the mean Z500 anomalies associated with the regimes are of an order of O(100 gpm), the trends in Z500 are an order of magnitude smaller (O(10 gpm)) so that one may argue that the anomalies imposed by regimes still dominate over a potential signal by global trends in Z500”. Is the author referring to Fig.1b? Does it make sense to compare magnitudes of intra-seasonal variability with inter-annual trends?

Lines 783-784: “We follow Lee et al. (2023) and compute the residual trend by subtracting the linear trend 1979-2019 of 5.398 gpm (10yr)−1 from the full-trend (Figure 14c)”. I am not sure I understand. Does the author mean “We follow Lee et al. (2023) and compute the residual trend by subtracting the area-integrated linear trend 1979-2019 of 5.398 gpm (10yr)−1 from each the local linear trend (Figure 14c)”? It is also confusing to start with “We follow…” since it seems that this is only for Fig. 14c. After that, the area-integrated trend seems to be removed(?)

Line 801-802: “The trend signal is likely of the same order of magnitude as internal variability of regime occurrence”. I am not sure I understand this, or why it should be likely.

Line 816: “depending on the period considered for linear trend analysis”. This caveat seems to confuse things. Moreover, are the cluster definitions AND the projections onto the clusters based on de-trended data. This is not clear.

Lines 819-820: “Detrending or not does not affect the overall regime identification, yet, but gives helpful insight in the interpretation of trends”. This is confusing. Maybe delete “or not does not affect the overall regime identification, yet, but”?

Lines 823-824: “Notwithstanding, overall higher geopotential height amplifies the impact of blocking in terms of surface weather, in particular with respect to summer heat waves”. This seems very speculative to me.

Lines 862-863: “This is likely due to the thermal expansion of the troposphere under global warming, which is regionally amplified in that region”. I thought the author was not accounting for regional anomalies in trends in the case were the ScBL signal disappeared (?)

Typos
Lines 15 and 172: seamingless replaced with seamless?

Lines 31-35: These two sentences are difficult to read

Lines 80-81: “Another perspective looks at regimes in the eddy-driven jet and could be reconciled with the regime perspective”. The two uses of regime here is confusing.

Line 89: “an” to “and”

Line 617: Change “exemption” to “exception”?
Citation: https://doi.org/10.5194/egusphere-2025-6385-RC1
RC2:
'Comment on egusphere-2025-6385', Anonymous Referee #2, 20 Feb 2026
This paper was a very interesting read - as someone who has followed the Gramms groups outputs since publication of the original ERA-interim based set of patterns in 2017. This is as the author intended, an excellent detailed summary of the methodology for any new users of the year-round weather regime methodology with access to the dataset in zenodo (this downloads fine and has a high quality documentation attached).
My first question here – to the editors and author – is if weather and climate dynamics is the right home for this work as this is a dataset description paper, with minimal scientific advancement from the perspective of fundamental meteorology/climate science. From what I can see the advancement is limited to section 6, since upgrading from ERA-int to ERA5 makes next to no difference in the assignment/implementation of the methods. I emphasise I am not denying the usefulness of this work, just if a transfer could ease the review process. Some comments on the attached manuscript are below, but it may require some relatively major revision to the text/further analysis to sit in WCD.

General comments
Abstract: consider if keeping in WCD increasing the description of the novelty of this work as the first 15 lines currently review/introduce the methods history.

L87, weather types are sometimes referred to as ‘weather patterns’ e.g. Neal et al., (2016) which you cite.

L169-185: This could be better placed in literature review than methods.

I would suggest moving Appendix A1 into the main text of the paper as this is the scientific advancement presented in this paper compared to previous studies. Similarly Figure A1.

L210: Is the result significantly different without the low pass filtering?

Figure 1: Can you add a axis label to the colourbar? Figure 1 also appears in the text before it is referenced (check throughout).

L246: There is a mix of We/I in the paper, and a mix of active and passive voice that could be made consistent.

L247: The other methods often use a cosine based latitudinal weighting on the grid to make sure that their are no biases to larger grid box areas. Have you also done this?

L254: How does this work? e.g. The difference of the fuzzy-c-means from k-means that is used in the Cassou (2008) method?

L271: Remind readers this was first described in Bueler et al., 2021 and you're expanding here. Rather than this paper ‘newly introducing’.

L308: I was not sure what you meant by ‘catch up’.

L318: I found the quantitative descriptions more useful than the qualitive statements, so these could come after the quantitative descriptions for readers who require them?

L328: Why is 5 days used as a threshold?

L363-365: I appreciate the statement about criteria selection but are you able to provide any more details as to why these decisions are optimal/ideal?

L389: reference Figure 2 in first sentence.

Fig 2: it’s a bit hard to read the 'on' and 'oc' and 'tr' on the graph, can you offset them slightly from the line centre or give the text a white background? It would also be useful to have the IWr maximum regime (i.e. which is furthest above 1) as a bar like the unambiguous categorical definition so it is easier to compare the differences when using the lifecycle definition.

Section 4 lines 4.14 -430 can be removed. This information is present in the introduction.

Figure 3: This is interesting, but could be made supplementary and focus on Figure 5

L453: I don't not really agree about the patterns look blurry they look very similar to me, can you direct my eye to the key difference points I should see?

Section 4.2, Given the limited differences between these patterns and those described with ERA-int in Gramms et al., 2017 this could be condensed?

In Fig 6 can you use colours for the 4 that are not used in the 7 to make the plot easier to interpret? I got a bit confused when I first used these on the double use of the primary colours.

L578: EuBl and AR also look relatively similar for their year round occurrences in Fig 7?

L585: There is repetition here from previous sections.

Fig 8 caption, add (LC) so we know what the acronym stands for in the Figure.

L619: Are the differences statistically significant?

L625-635: Move to appropriate point in literature review.

Section 5.4: Consider if this section is needed in so much depth or if the material could be moved to the supplement. It's noted that the results are present in other papers that are cited. For example, ‘The following provides an overview of these studies’ should not be the topic of a results section in a new science paper.

Conclusions: Can you clarify the novelty vs. synthesis aspects of this work compared to the previous studies more clearly in the conclusions.

Figure A1: This would be interesting for the main text and methods given the update of the method for the new dataset.

Figure A2: A difference plot here would be interesting as they look the same to me by eye instead of the comparison.
Citation: https://doi.org/10.5194/egusphere-2025-6385-RC2
EC1: 'Comment on egusphere-2025-6385', Juliane Schwendike, 25 Feb 2026

The paper fits within the scope of WCD as dynamical weather regimes are investigated and characterized. These regimes are widely used and relevant for the atmospheric dynamics community. However, the framing of the paper could be improved to de-emphasize the technical aspects and focus more on the scientific findings, for instance regarding temporal variability and trends in weather regime occurrence. The novel aspects of the work could be highlighted more as well.

Citation: https://doi.org/10.5194/egusphere-2025-6385-EC1
AC1: 'Comment on egusphere-2025-6385', Christian Grams, 08 May 2026

I thank the reviewers and the editor for their thoughtful review and careful recommendations on the manuscript and their general appreciation of the work. The editor and reviewers raise two somewhat similar major concerns. The first concern is about the fit in WCD, and the second concern about the length of the article. I will address these as outlined in the attached detailed author responses.

Citation: https://doi.org/10.5194/egusphere-2025-6385-AC1

Christian M. Grams

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Christian M. Grams

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Short summary

The study discusses key characteristics, impact on surface weather, and trends of year-round North Atlantic European weather regimes for 1950–2024. Novel insight is gained in inter-annual variability and recent trends in regime occurrence. Regimes are important because they affect weather in Europe for several days to a few weeks and enable weather forecasts several weeks ahead. Regimes also affect extremes, such as heat waves. Data is published at Zenodo (doi:10.5281/zenodo.17080146).


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A life cycle definition of year-round weather regimes in the North Atlantic European region

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