the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Mar 2024
Precursors and pathways: Dynamically informed extreme event forecasting demonstrated on the historic Emilia-Romagna 2023 flood
Abstract. The ever-increasing complexity and data volumes of numerical weather prediction demands innovations in the analysis and synthesis of operational forecast data. Here we show how dynamical thinking can offer directly applicable forecast information, taking as a case study the extreme north Italian flooding of May 2023. We compare this event with historical north Italian rainfall events – in order to determine a) why it was so extreme, b) how well it was predicted, and c) how we may improve our predictions of such extremes. Lagrangian analysis shows, in line with previous work, that extreme rainfall in Italy can be caused by moist air masses originating from the North Atlantic, North Africa, and, to a lesser extent, Eastern Europe, with compounding moisture contributions from all three regions driving the May 2023 event. We identify the large-scale precursors of typical north Italian rainfall extremes based on geopotential height and integrated vapour transport fields. We show in ECMWF operational forecasts that a precursor perspective was able to identify the growing possibility of the Emilia-Romagna extreme event eight days beforehand – four days earlier than the direct precipitation forecast. Such dynamical precursors prove well-suited for identifying and interpreting predictability barriers, and could help build forecaster's understanding of unfolding extreme scenarios in the medium-range. We close by discussing the broader implications and operational potential of dynamically-rooted metrics for understanding and predicting extreme events, both in retrospect and in real-time.
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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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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
(20260 KB) - BibTeX
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-415', Anonymous Referee #1, 24 Mar 2024
Summary
This manuscript explores forecasts of the May 2023 heavy precipitation event in northern Italy, its meteorological precursors/drivers, and the possibilities of anticipating such events at greater lead times using dynamical understanding and model ensembles. The manuscript represents a well-rounded effort with overall clear analysis and figures. In my view, only minor revisions are necessary prior to publication.
Most important points
The generalizability of certain concluding thoughts, for example about the importance of simulations accurately capturing cyclone development near Newfoundland, could be more firmly established. It is not clear to me whether this identified predictability barrier is applicable also to other northern-Italian heavy-precipitation events, or if the point is simply that further work could be done to determine what sorts of predictability barriers are common across multiple cases.
Both in the aggregate and in this event, there seems to be substantially more moisture uptake from land compared to ocean (Figures 1 and 10). It would be helpful to explain why this is – or maybe why the figures are misleading in this respect -- especially as Section 2 refers to the Mediterranean Sea as the primary moisture source. Relying on previous literature for this would be fine. Is the phenomenon related to convection preferentially occurring over land, perhaps?
There is much discussion of anomalous moisture and its origins in the Introduction, but I think would be helpful to have more literature review of the role of instability anomalies and/or forced ascent in driving extreme precipitation in Italy.
Minor/line-by-line points
Title: demonstrated on -> demonstrated for OR demonstrated with
1: demands -> demand
11: forecaster’s -> forecasters’
16: typo
26: i.e. a week in advance?
28: i.e. the ensemble-mean forecast?
39: extreme-events -> extreme events
44-46: a citation or two for this sentence would be good
47-48: the commas after ‘events’ and ‘characteristics’ should be removed
120: ‘magnitude’ would be the more typical term, rather than ‘amplitude’.
153: typo
204: I would think that this potential increased strength of relationship between SST and moisture uptake would have more to do with the types of synoptic weather systems in summer/fall (i.e. more convective, less frontal) than with SST values per se. Or is this perhaps discussed in the Sanchez reference?
212: ‘Dynamical’ should be removed, as the sentence refers to both thermodynamical and dynamical characteristics
216: Are these negative q tendencies over Italy?
Fig 2: I’m confused about the units here – for comparison with the text, mm/day might be a better choice. The ‘May 2023’ label at top left should also be moved, perhaps down a bit, to not interfere with the title.
Fig 3: This one is a bit hard to read – I would recommend increasing the line widths. The axis and tick labels are also on the small side.
253: dependent on -> separated according to
281: Tyrhennian -> Tyrrhenian
282: Appenines -> Apennines
293: While I follow most of this discussion well, the northwesterly flow is hard to see in Fig 5. It might be helpful to add a clarifying remark that it can be seen crossing France, then plunging south into Algeria and back to Italy, at least on the 15th.
Fig 7: The labeling of this figure needs improvement in image quality and in the text
Fig 8: Line 281 states Storm Minerva was located in the Tyrrhenian Sea, while here the Adriatic is mentioned for May 16. The geopotential map would seem to support the Tyrrhenian, however – unless these phrases refer to different days?
313: I don’t see this – Fig 3e looks to show that theta-E is highest for NAlow trajectories (and that East trajectories have only slightly higher values)?
320: ‘Particularly’ can be removed as redundant. ‘Unusual’ might also be a better choice than ‘unique’.
330: It might not be necessary to add, but on this point for me, Fig 7 helped to illustrate that the low-level flow almost perfectly circles around the Italian peninsula without encountering major topographic barriers before reaching Emilia-Romagna.
Fig 11: It could be made clearer in the caption and/or the main text that (if my interpretation is correct) this figure compares inferred precipitation from the trajectory analysis and observed precipitation from satellite data.
335: It’s unclear what ‘most saturated’ means in this context.
348: The word ‘chance’ is confusing here; I think it could simply be removed without much loss of meaning.
373: A citation that discusses this potential utility in some way would be helpful, as the point is not immediately evident to me (i.e. perhaps many forecasts in general have a small number of ensemble members showing extreme cases that never come to pass?).
405: no -> little
407: carry moisture?
412: It would be more precise to say ‘contributing to precipitation’.
420: Are there any studies that suggest this in the Mediterranean broadly, for example?
446-447: I am a little confused by the wording of this sentence.
Citation: https://doi.org/10.5194/egusphere-2024-415-RC1 - AC1: 'Reply on RC1', Joshua Dorrington, 03 May 2024
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RC2: 'Comment on egusphere-2024-415', Anonymous Referee #2, 10 Apr 2024
This paper examines the atmospheric dynamics leading to the 2023 floods in northern Italy, and proposes some recently developed precursors as useful tools to enhance the predictability of extreme precipitation to longer lag times. Last, it provides some insights on how the use of these tools can help identifying potential predictability barriers.
I find this study excellently executed and presented. I enjoyed reading it.
I have some minor aspects that the authors could address to improve readability (mainly formal). Other than that, I commend the authors for this great work.The study and the methodology applies to large-scale and relatively long-duration precipitation events (as opposed to convective extremes that are examined in other studies). I think this should be stated more clearly in the abstract and introduction.
Line 26 – I don’t understand what you mean by “increased rainfall probability” here
Line 91: both is a repetition
Line 118: “defining an event as a day with rainfall exceeding the 90th percentile of this index (≈ 8.5mm/day)” is this a spatial average over the domain? The peak? Please specify
Line 141: why up to 480 hPa?
Line 151: “lower” instead of “smaller”?
Lines 156-158: this explains why 5 days are used for NA but not why 7 days are used for the other categories.
Line 163: I think the t in qt should be subscript
Citation: https://doi.org/10.5194/egusphere-2024-415-RC2 - AC1: 'Reply on RC1', Joshua Dorrington, 03 May 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-415', Anonymous Referee #1, 24 Mar 2024
Summary
This manuscript explores forecasts of the May 2023 heavy precipitation event in northern Italy, its meteorological precursors/drivers, and the possibilities of anticipating such events at greater lead times using dynamical understanding and model ensembles. The manuscript represents a well-rounded effort with overall clear analysis and figures. In my view, only minor revisions are necessary prior to publication.
Most important points
The generalizability of certain concluding thoughts, for example about the importance of simulations accurately capturing cyclone development near Newfoundland, could be more firmly established. It is not clear to me whether this identified predictability barrier is applicable also to other northern-Italian heavy-precipitation events, or if the point is simply that further work could be done to determine what sorts of predictability barriers are common across multiple cases.
Both in the aggregate and in this event, there seems to be substantially more moisture uptake from land compared to ocean (Figures 1 and 10). It would be helpful to explain why this is – or maybe why the figures are misleading in this respect -- especially as Section 2 refers to the Mediterranean Sea as the primary moisture source. Relying on previous literature for this would be fine. Is the phenomenon related to convection preferentially occurring over land, perhaps?
There is much discussion of anomalous moisture and its origins in the Introduction, but I think would be helpful to have more literature review of the role of instability anomalies and/or forced ascent in driving extreme precipitation in Italy.
Minor/line-by-line points
Title: demonstrated on -> demonstrated for OR demonstrated with
1: demands -> demand
11: forecaster’s -> forecasters’
16: typo
26: i.e. a week in advance?
28: i.e. the ensemble-mean forecast?
39: extreme-events -> extreme events
44-46: a citation or two for this sentence would be good
47-48: the commas after ‘events’ and ‘characteristics’ should be removed
120: ‘magnitude’ would be the more typical term, rather than ‘amplitude’.
153: typo
204: I would think that this potential increased strength of relationship between SST and moisture uptake would have more to do with the types of synoptic weather systems in summer/fall (i.e. more convective, less frontal) than with SST values per se. Or is this perhaps discussed in the Sanchez reference?
212: ‘Dynamical’ should be removed, as the sentence refers to both thermodynamical and dynamical characteristics
216: Are these negative q tendencies over Italy?
Fig 2: I’m confused about the units here – for comparison with the text, mm/day might be a better choice. The ‘May 2023’ label at top left should also be moved, perhaps down a bit, to not interfere with the title.
Fig 3: This one is a bit hard to read – I would recommend increasing the line widths. The axis and tick labels are also on the small side.
253: dependent on -> separated according to
281: Tyrhennian -> Tyrrhenian
282: Appenines -> Apennines
293: While I follow most of this discussion well, the northwesterly flow is hard to see in Fig 5. It might be helpful to add a clarifying remark that it can be seen crossing France, then plunging south into Algeria and back to Italy, at least on the 15th.
Fig 7: The labeling of this figure needs improvement in image quality and in the text
Fig 8: Line 281 states Storm Minerva was located in the Tyrrhenian Sea, while here the Adriatic is mentioned for May 16. The geopotential map would seem to support the Tyrrhenian, however – unless these phrases refer to different days?
313: I don’t see this – Fig 3e looks to show that theta-E is highest for NAlow trajectories (and that East trajectories have only slightly higher values)?
320: ‘Particularly’ can be removed as redundant. ‘Unusual’ might also be a better choice than ‘unique’.
330: It might not be necessary to add, but on this point for me, Fig 7 helped to illustrate that the low-level flow almost perfectly circles around the Italian peninsula without encountering major topographic barriers before reaching Emilia-Romagna.
Fig 11: It could be made clearer in the caption and/or the main text that (if my interpretation is correct) this figure compares inferred precipitation from the trajectory analysis and observed precipitation from satellite data.
335: It’s unclear what ‘most saturated’ means in this context.
348: The word ‘chance’ is confusing here; I think it could simply be removed without much loss of meaning.
373: A citation that discusses this potential utility in some way would be helpful, as the point is not immediately evident to me (i.e. perhaps many forecasts in general have a small number of ensemble members showing extreme cases that never come to pass?).
405: no -> little
407: carry moisture?
412: It would be more precise to say ‘contributing to precipitation’.
420: Are there any studies that suggest this in the Mediterranean broadly, for example?
446-447: I am a little confused by the wording of this sentence.
Citation: https://doi.org/10.5194/egusphere-2024-415-RC1 - AC1: 'Reply on RC1', Joshua Dorrington, 03 May 2024
-
RC2: 'Comment on egusphere-2024-415', Anonymous Referee #2, 10 Apr 2024
This paper examines the atmospheric dynamics leading to the 2023 floods in northern Italy, and proposes some recently developed precursors as useful tools to enhance the predictability of extreme precipitation to longer lag times. Last, it provides some insights on how the use of these tools can help identifying potential predictability barriers.
I find this study excellently executed and presented. I enjoyed reading it.
I have some minor aspects that the authors could address to improve readability (mainly formal). Other than that, I commend the authors for this great work.The study and the methodology applies to large-scale and relatively long-duration precipitation events (as opposed to convective extremes that are examined in other studies). I think this should be stated more clearly in the abstract and introduction.
Line 26 – I don’t understand what you mean by “increased rainfall probability” here
Line 91: both is a repetition
Line 118: “defining an event as a day with rainfall exceeding the 90th percentile of this index (≈ 8.5mm/day)” is this a spatial average over the domain? The peak? Please specify
Line 141: why up to 480 hPa?
Line 151: “lower” instead of “smaller”?
Lines 156-158: this explains why 5 days are used for NA but not why 7 days are used for the other categories.
Line 163: I think the t in qt should be subscript
Citation: https://doi.org/10.5194/egusphere-2024-415-RC2 - AC1: 'Reply on RC1', Joshua Dorrington, 03 May 2024
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Joshua Dorrington
Marta Wenta
Federico Grazzini
Linus Magnusson
Frederic Vitart
Christian Grams
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(15759 KB) - Metadata XML
-
Supplement
(20260 KB) - BibTeX
- EndNote
- Final revised paper