DOI: 10.5281/zenodo.13778103
title: Daily SPEI-90 Days Values – Elevation Below 1500 m a.s.l., 1950–2023

description: Science Case Name 



Multi-Hazards in the Downstream Area of the Adige River Basin. 





Dataset Name/Title 



Daily SPEI-90 Days Values – Elevation Below 1500 m a.s.l., 1950–2023





Dataset Description 



SPEI (Standardized Precipitation Evapotranspiration Index) data calculated using the E-OBS daily gridded data with a spatial resolution of 0.1° for the period from 1950 to 2023. The dataset describes the anomalies of the balance between precipitation and potential evapotranspiration with respect to the average conditions (Vicente-Serrano et al., 2010), considering both temperature and precipitation as inputs. 





Key Methodologies 



Daily SPEI is here calculated at a time scale of 90 days (3 months). The SPEI calculation is based on the ‘SPEI’ R package by Beguería and Vicente-Serrano (2023) (https://github.com/sbegueria/SPEI) with the potential evapotranspiration derived from Hargreaves-Samani formulation. Based on E-OBS orography, SPEI values for altitudes above 1500 m a.s.l. are excluded from the current analysis to focus on low and mid-elevation areas only.





Temporal Domain 



1950–2023





Spatial Domain 



The dataset is provided over the [7.10, 44.10, 15.30, 49.10] spatial domain (min longitude, min latitude, max longitude, max latitude in WGS84, EPSG:4326).





Key Variables/Indicators 



Standardized Precipitation Evapotranspiration Index 90-days (SPEI-90 days)





Data Format 



netCDF 





Source Data 



E-OBS dataset (v29.0e)





Accessibility 



https://doi.org/10.5281/zenodo.13778103





Stakeholder Relevance 



SPEI represents a valuable insight for researchers working on drought related issues, technical experts from public agencies and practitioners, as it is a comprehensive index able to identify drought hazard (dry event), while also considering temperature in the computation. Moreover, it can foster the use of Earth Observation when coupled with event identification methods by providing a robust meteorological-based event identification. This can be then further refined by the use of higher spatial resolution EO data capable of capturing subtle spatial patterns (e.g., soil moisture as influenced by droughts).





Limitations/Assumptions 



Excludes areas above 1500 m a.s.l. 





Additional Outputs/Information 



DBSCAN 3D Clusters of SPEI-90 Days Values – Italian NUTS3 (ITH31, 32, 34, 35, 36, 37), 1950–2023 (https://zenodo.org/records/13785996) 

The dataset access is currently restricted due to pending related publication.





Contact Information



Crespi, Alice (Center for Climate Change and Transformation, Eurac Research, Bolzano, Italy) - Data managerLemus i Cánovas, Marc (Center for Climate Change and Transformation, Eurac Research, Bolzano, Italy, CRETUS, Non-linear Physics Group, Universidade de Santiago de Compostela, Galicia, Spain)- Data curatorMaines, Elena (Center for Climate Change and Transformation, Eurac Research, Bolzano, Italy) - Data curatorMasina, Marinella (CMCC Foundation - Euro-Mediterranean Center on Climate Change)- Data curatorMaraschini, Margherita (CMCC Foundation - Euro-Mediterranean Center on Climate Change) - Data curatorFerrario, Davide Mauro (CMCC Foundation - Euro-Mediterranean Center on Climate Change) - Data curatorFurlanetto, Jacopo (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - Data managerPittore, Massimiliano (Center for Climate Change and Transformation, Eurac Research, Bolzano, Italy) - Data managerTerzi, Stefano (Center for Climate Change and Transformation, Eurac Research, Bolzano, Italy) - Data managerTorresan, Silvia (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - Data manager