Data Description

This dataset contains estimates of extreme sea level quantiles at selected locations along the Italian coastline. The quantiles correspond to different return periods and are derived using both observational records and ocean model simulations. The analysis using observations covers the period 1999–2024 for all locations, except for Venice and Trieste, where the data cover 1983–2023 and 1905–2022, respectively. The analysis using ocean model simulations covers the period 1994–2020.

The analysis applies two main statistical frameworks:

• Peak Over Threshold (POT)
• Metastatistical Extreme Value Distribution (MEVD)

Two indpendent event selection methodologies used are overlapping and sorting approaches. The dataset provides a comparison across multiple methodological implementations, supporting research on coastal risk, hazard assessment, and climate adaptation.

Data Contents

The dataset includes:

1. Tabular Data (CSV files)

A total of five CSV files:

• Four files based on observational data, each corresponding to a different statistical approach
• One file based on ocean model simulations, using the MEVD-sorting approach

Structure of CSV files

Each CSV file contains the following columns:

Notes:

• The 1000-year return period is available only for observational datasets
• Model-based outputs include 100-year and 300-year return levels

2. Visualization Files (PNG)

A set of .png images showing:

• Spatial distribution of extreme sea level quantiles along the Italian coastline generated using different statistical approaches

Potential Applications

This dataset can support:

• Coastal flood risk assessment
• Climate change impact studies
• Design of coastal infrastructure
• Hazard mapping and early warning systems

Spatial Coverage

• Region: Italian coastline

File Naming Convention

• Files are named according to:
  • Data source (observations (O) or model (M))
  • Statistical method used

Acknowledgements

This work was supported by the RETURN project under the PNRR – Next Generation EU framework.

Funding

This study was carried out within the project “RETURN – Multi-risk science for resilient communities under a changing climate”, funded by the European Union – Next Generation EU under the National Recovery and Resilience Plan (PNRR), Mission 4 “Education and Research”, Component 2 “From Research to Business”, Investment 1.3 (identification code PE0000005, Spoke 8 – DS – Science underpinning Climate services for risk mitigation and adaptation, CUP code C93C22005160002).