Vicente‐Serrano et al. (2025) Developing science-informed maps and climate service for extreme rainfall in Spain

Identification

• Journal: Natural Hazards
• Year: 2025
• Date: 2025-10-17
• Authors: Sergio M. Vicente‐Serrano, Santiago Beguerı́a, Fergus Reig, Alejandro A. Royo, Manuel Arretxea, M. Gil, Borja Latorre, Ahmed El Kenawy, Magí Franquesa, Amar Halifa‐Marín, María Adell-Michavila, Alex Crespillo, David Pérez‐Pajuelo, Fernando Domínguez‐Castro, David Barriopedro, José Manuel Gutiérrez, C. Azorin-Molina, L. Gimeno
• DOI: 10.1007/s11069-025-07731-0

Research Groups

• Instituto Pirenaico de Ecología (IPE-CSIC), Zaragoza, Spain
• Laboratorio de Climatologia y Servicios Climaticos (LCSC), CSIC–Universidad de Zaragoza, Zaragoza, Spain
• Estación Experimental de Aula Dei (EEAD-CSIC), Zaragoza, Spain
• Instituto de Geociencias (IGEO-CSIC-UCM), Madrid, Spain
• Instituto de Fisica de Cantabria (IFCA-CSIC - Universidad de Cantabria), Santander, Spain
• Centro de Investigaciones Sobre Desertificación (CIDE, Climate, Atmosphere and Ocean Laboratory (Climatoc-Lab), CSIC-UV- Generalitat Valenciana), Moncada, Valencia, Spain
• Environmental Physics Laboratory (EPhysLab), CIM‑UVigo, Universidade de Vigo, Ourense, Spain
• Unidad Asociada CSIC-Universidad de Vigo: Grupo de Física de La Atmosfera y del Océano, Pontevedra, Spain
• Galicia Supercomputing Center (CESGA), Santiago de Compostela, Spain

Short Summary

This study develops the first high-resolution hazard probability maps of extreme precipitation for Spain, integrating them into a national climate service. Using a stationary Generalized Pareto Distribution and universal kriging on long-term daily precipitation data, the maps provide reliable estimates of extreme precipitation quantiles, revealing distinct spatial patterns and supporting decision-making through an interactive online platform.

Objective

• To develop the first high-resolution hazard probability maps of extreme precipitation quantiles for Spain (including Peninsular Spain, the Balearic Islands, and the Canary Islands) and integrate them into an interactive online climate service for hydrometeorological extremes.

Study Configuration

• Spatial Scale: National scale (Spain), including Peninsular Spain, Balearic Islands, and Canary Islands. Gridded maps at 2.5 km resolution, with aggregated data at the provincial level.
• Temporal Scale: Long-term daily precipitation records from 1961 to 2024.

Methodology and Data

• Models used:
  • Generalized Pareto Distribution (GPD) for extreme value analysis (Peaks-over-threshold approach).
  • Method of probability-weighted moments for GPD parameter estimation.
  • Universal Kriging for spatial interpolation of GPD parameters, using geographic latitude, longitude, and elevation as covariates.
  • Jackknife resampling for validation of interpolated parameters.
• Data sources:
  • Daily precipitation records from 2,840 quality-controlled stations provided by the Spanish Meteorological Agency (AEMET).
  • Topographic data (elevation) from GIS layers.

Main Results

• The 90th percentile of daily precipitation (excluding zero values) was identified as a robust threshold for selecting exceedance series.
• The Generalized Pareto Distribution (GPD) accurately models extreme precipitation quantiles for both maximum daily precipitation and total event precipitation across Spain.
• Spatial mapping of GPD parameters (shape α, origin x0, scale κ, frequency λ) revealed strong geographic coherence and variability, with high α values for daily maximum event precipitation along the Mediterranean coast and mountain areas, and for total event precipitation in the northwestern Atlantic coast.
• Universal Kriging demonstrated high consistency between observed and predicted GPD parameters (Agreement Index D > 0.90 for α, x0, and λ), with small spatial biases.
• Hazard probability maps show significant spatial differences: maximum intensity precipitation is highest along coastal areas (Mediterranean, Pyrenean, Cantabrian) and central mountain systems, while total event precipitation is highest in northwestern, southwestern, and eastern Mediterranean coasts.
• Provincial-level assessment indicates the highest intensities (exceeding 500 mm in 24 hours for 25- and 50-year return periods) in provinces along the eastern Mediterranean coast.
• All generated high-resolution and provincial-level information is integrated into an interactive online climate service (https://retornolluvias.csic.es), allowing users to explore localized hazard probabilities and generate magnitude-frequency curves.

Contributions

• Provides the first high-resolution (2.5 km) hazard probability maps of extreme precipitation for the entirety of Spain, significantly advancing national-scale assessments.
• Develops and integrates an interactive online climate service, enhancing accessibility and usability of extreme precipitation hazard information for various sectors.
• Employs a robust methodology combining a dense network of 2,840 long-term daily precipitation stations with Generalized Pareto Distribution and universal kriging of distribution parameters, incorporating topographic data to improve accuracy in complex terrain.
• Validates the use of a stationary modeling framework, supported by recent findings on the temporal stability of extreme precipitation in Spain, offering more reliable estimates than non-stationary alternatives for current and near-future applications.
• Offers both fine-scale gridded maps and aggregated provincial-level hazard probabilities, bridging the gap between detailed scientific assessment and practical administrative planning.
• Serves as a methodological reference for improving extreme precipitation hazard assessments in other European and global regions due to its comprehensive coverage, high resolution, and extensive data utilization.

Funding

• Spanish Ministry of Science and FEDER (research projects TED2021-129152B-C41 and PID2022-137244OB-I00)
• CSIC’s Interdisciplinary Thematic Platform Clima (PTI-Clima)
• Ministry for the Ecological Transition and the Demographic Challenge (MITECO) and the European Commission NextGenerationEU (Regulation EU 2020/2094) (contract CSC2023-02-00)
• ESA (GLANCE, Contract No. 4000145543/24/I-LR)
• CRUE-CSIC agreement with Springer Nature (Open Access funding)

Citation

@article{VicenteSerrano2025Developing,
  author = {Vicente‐Serrano, Sergio M. and Beguerı́a, Santiago and Reig, Fergus and Royo, Alejandro A. and Arretxea, Manuel and Gil, M. and Latorre, Borja and Kenawy, Ahmed El and Franquesa, Magí and Halifa‐Marín, Amar and Adell-Michavila, María and Crespillo, Alex and Pérez‐Pajuelo, David and Domínguez‐Castro, Fernando and Barriopedro, David and Gutiérrez, José Manuel and Azorin-Molina, C. and Gimeno, L. and Nieto, R.},
  title = {Developing science-informed maps and climate service for extreme rainfall in Spain},
  journal = {Natural Hazards},
  year = {2025},
  doi = {10.1007/s11069-025-07731-0},
  url = {https://doi.org/10.1007/s11069-025-07731-0}
}