The manuscript presents a clear, well-structured and compelling analysis of the impact of Storm Louis on two Spanish harbours using a comprehensive multi-sensor observational approach. The writing is strong, the methodology is robust, and the results are clearly articulated and well contextualised within the broader synoptic dynamics of the event. In my view, the manuscript is suitable for publication in its current form.

Below, I provide a series of comments and questions that could further strengthen clarity and interpretation for the reader.



The authors refer to synoptic-scale conditions “at the maximum on the 23rd”. It is unclear whether the maps represent:

a daily mean, a specific time step (e.g., 00 / 06 / 12 / 18 UTC), or a daily maximum field. Clarifying this would help readers better connect the synoptic configuration with the timing of the metocean forcing.



Storm Louis primarily affected the northeastern Atlantic, and its impacts in the Mediterranean were, operationally speaking, relatively limited. To my knowledge, Louis did not generate significant swell or storm surge in the western Mediterranean; observed wave heights were below historical maxima, and its most notable impacts in the region were related to wind and precipitation (e.g., northern Italy), rather than oceanographic extremes. Given this context, I was surprised by the relatively strong harbour agitation reported at Tarragona. Were any operational issues or disruptions actually observed in Tarragona during the event? How do the recorded agitation values compare with typical operational thresholds or known port sensitivities? To what extent is the unexpectedly strong response primarily attributable to the harbour’s directional sensitivity, as highlighted in the manuscript?



The paper defines extreme agitation levels using high climatological percentiles (>99%). However, the absolute thresholds differ markedly between Langosteira (~0.5 m) and Tarragona (~1.2 m). Could the authors clarify:

whether these percentile-based thresholds correspond to real operational limits used by port authorities, or are purely statistical indicators;

and what drives the strong difference—e.g., harbour geometry, resonance characteristics, exposure, or differences in instrumentation or reference periods?

This would help readers understand whether the identified extreme conditions have direct operational implications.



The manuscript provides an excellent explanation of the synoptic drivers of Louis. Given that the synoptic peak occurred on 23 February, whereas the harbour agitation maxima occurred later (24th for NWI, 26th for NEI), it would be valuable to expand briefly on the mechanisms underlying these temporal shifts. I.e, propagation time of wave energy from the North Atlantic to the regional offshore areas, directional effects and wave transformation processes, intrinsic response times or resonant behaviour within the harbours. A short discussion would enhance the physical interpretation of the multi-scale connections that the paper aims to highlight.

Overall, this is a strong and insightful manuscript with clear scientific and operational relevance. My comments are intended purely to clarify some aspects and enhance interpretability, not to challenge the quality of the work. I recommend publication after minor revisions.

Overall recommendation: Minor revision

This is a well-executed, scientifically robust paper that successfully links real-time multi-platform monitoring with climate-resilient port operations. With modest editorial refinements and expanded contextual discussion it will represent an exemplary contribution to State of the Planet 2025.

General comments

This manuscript provides a robust and timely analysis of Storm Louis (February 2024) and its impact on two Spanish ports: Langosteira (NW Iberia) and Tarragona (NE Iberia), through a multi-platform observing system that combines in situ moored buoys and tide gauge data with High-Frequency Radar (HFR) land-based remote sensing. The study is scientifically rigorous, well structured, and operationally relevant, offering valuable insights into harbour agitation dynamics under extreme conditions. Its novelty lies in the real-time, multi-platform assessment of a deep extratropical cyclone affecting two contrasting coastal regions, supported by strong offshore-in-port statistical relationships and a meaningful validation of HFR-derived wave parameters.

The methods are clearly described and reproducible, and the results are well supported by high-quality figures and tables. The discussion effectively contrasts the responses of Langosteira and Tarragona and highlights the influence of geometry, exposure, and wave directionality on port vulnerability. The percentile-based contextualisation is appropriate for the available 11-year record, though the authors should clarify that this does not constitute a full climatological baseline. The comparison of HFR performance between regions is insightful and would benefit from additional clarification regarding network specifications, retrieval methods, and local factors affecting skill.

A minor but important recommendation is to revise the title by replacing “multi-sensor” with “multi-platform,” as this terminology is broader, more accurate, and aligned with current operational oceanography and observing-system frameworks.

Contextualisation is strong and well referenced, with opportunities to incorporate additional key literature on observing systems, HFR wave estimation, and climate-related port adaptation. Minor editorial refinements, including condensing the introduction, harmonising terminology, improving reference formatting, and clarifying technical details in Section 4.3, will further enhance clarity and coherence.

Specific comments

Novelty and contribution (Score: 1- Excellent)

The manuscript offers several high-value contributions:

• A real-time, multi-platform assessment of a deep extratropical cyclone and its contrasting impact on two ports under the same synoptic forcing.
• New insights into harbour agitation dynamics, supported by long-term offshore–in-port statistical relationships.
• A meaningful validation of HFR-derived wave parameters during an extreme storm.
• A cross-regional comparison (Atlantic vs. Mediterranean) effectively illustrating how geometry, exposure, and wave directionality modulate port vulnerability.
• A complementary perspective to long-term climate-adaptation literature (e.g., Sierra et al., 2023; Portillo Juan et al., 2022), reinforcing the need for port-level resilience assessments.
• Suggestions for improvement:
  • Add a short paragraph in the discussion explicitly positioning the study in the broader context of climate-resilient port management framework, and multi-hazard early warning systems (e.g., link to SDG 13 and 14, or EU Mission Ocean).
  • Explicitly note AEMET’s classification of Storm Louis as a high-impact storm (winds >140 km h⁻¹, waves >8 m), , underlining its relevance as a test case.

Scientific approach and methods (Score: 1- Excellent)

• Methods are clearly described and reproducible, with tables summarizing datasets (ERA5, HFR, REDMAR, and in-situ buoys) and their temporal coverage (Tables 1–5) with strong statistical analysis.
• The percentile-based approach for contextualizing extremes and capturing the spatio-temporal footprint of Storm Louis is appropriate for characterizing the event within the available 11-year record, although it should be noted that this period does not constitute a full climatological baseline.
• The analysis of long-term relationships between significant wave height, mean wave period, and mean wave direction with port agitation, supported by directionally resolved scatterplots, offers a valuable quantification of harbour sensitivity under energetic offshore conditions.
• HFR–buoy comparison is statistically rigorous (correlation, RMSE, regression slopes) and consistent with existing literature
• Suggestion for improvement:
  • Briefly discuss uncertainties related to (i) the distance between HFR range cells and their comparison buoys (e.g., 22–47 km; Fig. A2), and (ii) local bathymetric influences on wave transformation, which are relevant for future HFR calibration, etc. These elements are relevant for future calibration and are consistent with existing HFR literature. 

Results and discussion (Score: 2- Good)

• Results are detailed and supported by clear figures (e.g., Fig. 1–4, and three additional ones in Annexes).
• The contrasting wave-induced agitation responses between Langosteira and Tarragona are well substantiated by geometry and exposure.
• The manuscript effectively quantifies high correlations between offshore wave height and in-port agitation (R = 0.88 for Langosterira, R=  0.75 for Tarragona).
• The manuscript analyzes Tarragona’s marked sensitivity to wave incidence angle and its role in amplifying internal hydrodynamic response.
• The seasonal analysis (Fig. 3g–h) operational relevance for long-term risk management.
• Suggestions for improvement:
  • Suggestion to expand the discussion on operational thresholds (e.g., downtime limits for mooring and cargo handling) to better link with the port operability metrics proposed by Sierra et al. (2023)
  • Briefly compare Storm Louis with notable historical storms such as Storm Gloria (2020) to contextualise its magnitude.
  • Section 4.3: This section is strong but would benefit from additional clarity:
    • Note that an 11-year dataset is not a climatological baseline (WMO requires ≥30 years). I would suggest referring instead to “historical percentiles based on the available 11-year record.”
    • Use the official names of the HFR networks: HFR-Galicia and HFR-DeltaEbro, and list specific sites and frequencies.
    • Specify HFR direction of arrival (e.g. direction-finding) and CODAR software version, given its influence on wave algorithms.
    • Clarify reasons for lower HFR skill in the NEI region (e.g. reduced coverage, geometry, bathymetry, lower energy levels, and CWP sensitivity to SNR).
    • Confirm that the analysed range cells are in sufficiently deep water to avoid shallow-water artefacts.
    • Cite additional HFR wave-estimation studies (Tian et al., 2017; Lipa et al., 2018).
    • Emphasize that NWI vs. NEI differences are consistent with Saviano et al. (2022), who describe similar skill contrasts under varying energy and bathymetric conditions.

Structure, clarity and presentation (Score: 1- Excellent)

• The manuscript follows a clear and coherent structure, progressing logically
• English language quality is excellent, with minor redundancies.
• Figures, tables, and annexes are well designed and informative as well as professionally prepared and properly referenced.
• Suggestions for improvement:  Condense the introduction (pp. 2–4), reducing the number of historical storm examples and emphasising the novelty of the multi-platform approach.

References and contextualization (Score: 1- Excellent)

The reference list is extensive (over 70 entries), up-to-date, and integrates both global and regional literature.

• Suggested additions and improvements:
  • Tintoré et al. (2019): importance of sustained/integrated observing systems.
  • Lorente et al. (2021):  HFR wave field review.
  • Sierra et al. (2023) and Portillo Juan et al. (2022): climate change impacts and port adaptation.
  • Toledo et al. (2024) : storm surge processes and atmospheric forcing.
  • De Alfonso et al. (2021): for storm statistics in the Spanish Mediterranean.
  • Saviano et al., (2022): HFR performance under varying sea-state and bathymetric conditions.
• Formatting suggestions: to bring the reference list fully in line with the journal’s formal requirements.
  • Ensure all authors follow the “Surname, Initials” format (e.g., change forms like “J. Goggins, M. Hartnett” to “Goggins, J., Hartnett, M.”) and use “and” consistently instead of “&”.
  • Standardise journal names and apply the required order (journal – volume – pages – DOI – year). Some entries may need harmonisation and DOI inclusion (e.g., Morales-Márquez et al., 2020, Harley (2017)).
  • Cite reports/datasets (e.g., Aon-Benfield; Copernicus/CMEMS manuals) with full institutional details, URLs, and DOIs where available.
  • For discussion papers or preprints, use the final published version when possible, or include the correct preprint DOI per journal guidelines.

Figures/tables and supplementary material (Score: 1- Excellent)

• Tables 1–5 and Figures 1–4 are informative and well integrated.
• The annexes (A1–A3) add clarity to the site configurations and validation procedures, enhancing reproducibility.
  
  Suggestions for improvement:
• Table 1:  Include DOIs for datasets where applicable.
• Table 2: Add definitions of all EOV acronyms in the caption to improve readability.
• Tables 3 and 4: Several parameters repeat information already provided in Table 2 for buoys and tide gauges. Either remove redundancies or ensure full consistency between the variables listed across the tables.
• Table 5:  
  • Use official HFR network names (HFR-Galicia / HFR-DeltaEbro).
  • Replace “systems” with “networks.”
  • Verify site frequencies (HFR-Galicia includes 4.463 MHz and 13.5 MHz sites).
  • Include the HFR direction of arrival method (e.g. direction-finding).
• Figure 1d and e: Add a bounding box or visual marker to clearly highlight the Langosteira and Tarragona Harbour areas, respectively.
• Figure 4 - caption: Please indicate in the caption that the y-axis scales differ between the Langosteira and Tarragona panels, so that readers can correctly interpret and compare the magnitudes of offshore wave height and period.

Technical corrections (throughout manuscript)

• Page 1, line 14: include “low pressure dipole” and “intense north-westerly maritime-polar winds”.
• Page 1, line 16: clarify location (“over the northeastern Atlantic Ocean and the Iberian Peninsula”) and specify wave heights (“6–8 m, locally exceeding 8 m in Galician and Cantabrian coasts and wind gusts above 140 kmh-1 in exposed mountainous and coastal areas ”).
• Page 2, line 44: Remove “which is projected” for conciseness.
• Page 3-4, Introduction: Condense background on historical storms; emphasize Louis-specific context and novelty.
• Page 3, line 92: Replace with  “...two High Frequency Radar Networks”
• Page 3, line 98: Use “networks” instead of “systems”.
• Page 5, line 134: Replace “Additionally” with “Complementarily”  
• Page 5, line 134: Consider moving Table 3 to Supplementary Material if length reduction is needed.
• Page 5, line 152: Use the official names of the HFR networks registered in the European HFR Node: HFR-Galicia (FIST, SILL, LPRO, PRIO, VILA) and HFR-DeltaEbro (ALFA, SALO, VINA).
• Page 7, line 203: Consider adding recent HFR wave-estimation references (e.g., Tian et al., 2017; Lipa et al., 2018) to complement Lipa and Nyden (2005)
• Page 7, lines 220-224: Verify and confirm whether the range cells are located in sufficiently deep water to avoid shallow-water nonlinear ‘contamination’.
• Page 8, line 211: Consider adding Wyatt (1990) to strengthen the citation.
• Page 8, line 212: Specify the CODAR software version, as retrieval algorithms differ across releases and reproducibility depends on it.
• Page 8, line 232: Include SLP values for high and low (as shown in Figure 1)
• Page 9, line 280: Include reference to (Fig. 3c and e, respectively)
• Page 10, lines 322-326: Expand briefly on the physical/technical reasons for lower HFR skill in the NEI region (e.g., greater distance from buoy, geometric constraints, bathymetric complexity, lower sea-state energy during parts of the storm, and mixed-sea states that affect period retrieval).
• Terminology corrections (throughout manuscript)
  • Use “metocean” consistently.
  • Replace “multi-sensor” by “multi-platform”.
  • Replace buoys” by “moored buoys” (as in Figure caption A2).
  • Replace “HFR systems” by “HFR networks” (for HFR-Galicia and HFR-DeltaEbro)
  • Ensure Villano HFR site and Alfacada HFR site are consistently named.
• Page 11, line 343: Confirm whether the HFR coverage in each region is sufficiently wide and unobstructed to ensure stable directional solutions.
• Page 13, line 397- 405: Consider adding a brief synthesis noting that the comparison between HFR-derived and buoy-observed wave parameters during Storm Louis aligns with the performance patterns reported by Saviano et al. (2022).