the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Jan 2024
Could old tide gauges help estimate past atmospheric variability?
Abstract. The storm surge is the non-tidal component of coastal sea-level. It responds to the atmosphere both through the direct effect of atmospheric pressure on the sea-surface, and through Ekman transport induced by wind-stress. Tide gauges have been used to measure the sea-level in coastal cities for centuries, with many records dating back to the 19th-century or even further, at times when direct pressure observations were scarce. Therefore, these old tide gauge records may be used as indirect observations of sub-seasonal atmospheric variability, complementary to other sensors such as barometers. To investigate this claim, the present work relies on tide gauge records of Brest and Saint-Nazaire, two portal cities in western France, and on the members of NOAA's 20th-century reanalysis (20CRv3) which only assimilates surface pressure observations and uses numerical weather prediction model. Using simple statistical relationships between storm surges and pressure maps, we show that the tide gauge records reveal part of the 19th-century atmospheric variability that was uncaught by the pressure-observations-based reanalysis. In particular, weighing the 80 reanalysis members based on tide gauge observations indicates that a large number of members are very unlikely, which induces corrections of several tens of Hectopascals in the Bay of Biscay. These findings support the use of early tide gauge records in sensor-scarce areas, both to validate old atmospheric reanalyses and to better probe old atmospheric sub-seasonal variability.
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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
(9929 KB)
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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
(9929 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2997', Anonymous Referee #1, 29 Jan 2024
Summary: The study explores the possibility of using tide gauge records to reduce uncertainty in reconstructing past (19th century) sea-level pressure fields. The authors focus on the 20CR reanalysis, a long reanalysis product covering parts of the 19th century, and two tide gauge records in Northwestern France. The main conclusion is that the tide records can provide valuable information to constrain the 20CR reanalysis ensemble by attaching lower probabilities to the members of the ensemble that are less compatible with the implied sea level at those two tide records.
Recommendation: I think the idea of the study is interesting, and the study is, to a large extent, technically sound. I have some suggestions that the authors may want to consider in a revised version. My recommendation of 'major revisions' is more dictated by my interest in the revised version. The needed revisions are, in my opinion, between 'minor' and 'major'
1) This is somewhat a cosmetic comment, but the the manuscript refers to ‘storm surges’ whereas actually, the study considers the sea-level record after filtering out the tides and the long-term sea-level rise. In my understanding, the residuals are not the ‘storm surge’ component. The storm surge is, by definition, caused by the passage of a storm. The mechanisms connecting the storm atmospheric forcing and the sea surface elevation are more complex in cases of storms than those for the ‘normal’ sea level. For instance, depending on the coastline topography, the wind may cause a direct elevation of se-alevel in the direction of the wind. This is clear for estuaries, and it is the main cause of storm surges in many North Sea locations. The study statistically analyses the full range of sea-level variations, not only the extremes, and it is unclear why the text highlights ‘storms’. This is only the cause for the last section, and this is related to some additional problems (see next point)
2) The studies used a linear statistical regression method to link atmospheric predictors and sea-level elevation (after tidal and long-term trend filtering). The skill of the linear model is shown in Figure 4. It is visually clear that the linear model underestimates sea-level extremes, both high and low. This is very usual for linear models. But, while using tide gauges to constrain the reconstructed SLP would be permissible for ‘normal’ situations, it is clearly problematic for extremes. Thus, the last section needs a bit more attention, in my opinion. It could very well happen that the SLP from the ensemble members of the 20CR reanalysis passed through the linear model underestimates the storm surge (in this case, it is indeed a storm surge), and therefore, more ensemble members appear not compatible with the sea-level observations than they are. I suggest testing this approach with a recent storm when the 20CR has assimilated sufficient SLP observations to be considered accurate. In that recent storm, if I am correct in my concern, the study’s approach would also find that the 20CR ensemble is biased towards implied lower storm surges. This would test the study's main claim, namely that ‘storm surges’ can constrain the 20CR reanalysis.
Even if the test results fall against the study's claim, the study itself can still be useful, albeit in a modified form. Long records would still be useful to constrain the 20CR, but this constraint in case of storms would be too restrictive, attaching too low a probability to too many ensemble members of the 20CR reanalysis. Alternatively, a non-linear model should be set up to more accurately estimate extreme-level from atmospheric forcing.
Minor points:
3) ‘Anomalies are considered with a reference climatology computed as an average over all members and over ±30 calendar days, ± 3 day hours ‘
This sentence is unclear.
4) Table 1, Table 3 units are missing
Citation: https://doi.org/10.5194/egusphere-2023-2997-RC1 - AC1: 'Reply on RC1', Paul Platzer, 13 May 2024
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RC2: 'Comment on egusphere-2023-2997', Anonymous Referee #2, 07 Feb 2024
Please, see the file attached with the detailed revision
- AC2: 'Reply on RC2', Paul Platzer, 13 May 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2997', Anonymous Referee #1, 29 Jan 2024
Summary: The study explores the possibility of using tide gauge records to reduce uncertainty in reconstructing past (19th century) sea-level pressure fields. The authors focus on the 20CR reanalysis, a long reanalysis product covering parts of the 19th century, and two tide gauge records in Northwestern France. The main conclusion is that the tide records can provide valuable information to constrain the 20CR reanalysis ensemble by attaching lower probabilities to the members of the ensemble that are less compatible with the implied sea level at those two tide records.
Recommendation: I think the idea of the study is interesting, and the study is, to a large extent, technically sound. I have some suggestions that the authors may want to consider in a revised version. My recommendation of 'major revisions' is more dictated by my interest in the revised version. The needed revisions are, in my opinion, between 'minor' and 'major'
1) This is somewhat a cosmetic comment, but the the manuscript refers to ‘storm surges’ whereas actually, the study considers the sea-level record after filtering out the tides and the long-term sea-level rise. In my understanding, the residuals are not the ‘storm surge’ component. The storm surge is, by definition, caused by the passage of a storm. The mechanisms connecting the storm atmospheric forcing and the sea surface elevation are more complex in cases of storms than those for the ‘normal’ sea level. For instance, depending on the coastline topography, the wind may cause a direct elevation of se-alevel in the direction of the wind. This is clear for estuaries, and it is the main cause of storm surges in many North Sea locations. The study statistically analyses the full range of sea-level variations, not only the extremes, and it is unclear why the text highlights ‘storms’. This is only the cause for the last section, and this is related to some additional problems (see next point)
2) The studies used a linear statistical regression method to link atmospheric predictors and sea-level elevation (after tidal and long-term trend filtering). The skill of the linear model is shown in Figure 4. It is visually clear that the linear model underestimates sea-level extremes, both high and low. This is very usual for linear models. But, while using tide gauges to constrain the reconstructed SLP would be permissible for ‘normal’ situations, it is clearly problematic for extremes. Thus, the last section needs a bit more attention, in my opinion. It could very well happen that the SLP from the ensemble members of the 20CR reanalysis passed through the linear model underestimates the storm surge (in this case, it is indeed a storm surge), and therefore, more ensemble members appear not compatible with the sea-level observations than they are. I suggest testing this approach with a recent storm when the 20CR has assimilated sufficient SLP observations to be considered accurate. In that recent storm, if I am correct in my concern, the study’s approach would also find that the 20CR ensemble is biased towards implied lower storm surges. This would test the study's main claim, namely that ‘storm surges’ can constrain the 20CR reanalysis.
Even if the test results fall against the study's claim, the study itself can still be useful, albeit in a modified form. Long records would still be useful to constrain the 20CR, but this constraint in case of storms would be too restrictive, attaching too low a probability to too many ensemble members of the 20CR reanalysis. Alternatively, a non-linear model should be set up to more accurately estimate extreme-level from atmospheric forcing.
Minor points:
3) ‘Anomalies are considered with a reference climatology computed as an average over all members and over ±30 calendar days, ± 3 day hours ‘
This sentence is unclear.
4) Table 1, Table 3 units are missing
Citation: https://doi.org/10.5194/egusphere-2023-2997-RC1 - AC1: 'Reply on RC1', Paul Platzer, 13 May 2024
-
RC2: 'Comment on egusphere-2023-2997', Anonymous Referee #2, 07 Feb 2024
Please, see the file attached with the detailed revision
- AC2: 'Reply on RC2', Paul Platzer, 13 May 2024
Peer review completion
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Pierre Tandeo
Pierre Ailliot
Bertrand Chapron
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(9929 KB) - Metadata XML