Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
4
datasets available to search
ShareScore release 0.9.0
Dataset results
4 results for “Daily SPEI”
Daily SPEI dataset in China from 1980 to 2100
<p>The future state of drought in China under climate change remains uncertain. This study investigates drought events, focusing on the region of China, using simulations from five global climate models (GCMs) under three Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, and SSP5-8.5) participating in the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b). The daily Standardized Precipitation Evapotranspiration Index (SPEI) is employed to analyze drought severity, duration, and frequency over three future periods. Evaluation of the GCMs' simulations against observational data indicates their effectiveness in capturing historical climatic change across China. The rapid increase in CO<sub>2</sub> concentration under high emission scenarios in the mid- and late- future century (2040–2070 and 2071–2100) substantially influences vegetation behavior via regulation on leaf stomata and canopy structure. This regulation decelerates the increase in potential evapotranspiration, thereby mitigating the sharp rise in future drought occurrences in China. These findings offer valuable insights for policymakers and stakeholders to develop strategies and measures for mitigating and adapting to future drought conditions in China.</p>
Daily SPEI dataset in China from 1980 to 2100
Open the record for dataset details and reuse information.
SPEI-GD: The first global multi-scale daily SPEI dataset for 1983-2020
<p>The global daily SPEI dataset (SEPI-GD) at 0.25° spatial resolution form 1982 to 2021. This depository includes the five files of the daily SPEI data with five time scales (5, 30, 90, 180, and 360 days). The calculation based on ERA5's precipitation and Singer's potential evapotranspiration. All data are geographic latitude-longitude projection and NetCDF format. See paper for detailed explanation: Liu X, Yu S, Yang Z, et al. The first global multi-timescale daily SPEI dataset from 1982 to 2021[J]. Scientific Data, 2024, 11(1): 223.</p>
Daily SPEI-90 Days Values – Elevation Below 1500 m a.s.l., 1950–2023
<table> <tbody> <tr> <td> <p><strong>Science Case Name</strong> </p> </td> <td> <p>Multi-Hazards in the Downstream Area of the Adige River Basin. </p> </td> </tr> <tr> <td> <p><strong>Dataset Name/Title</strong> </p> </td> <td> <p>Daily SPEI-90 Days Values – Elevation Below 1500 m a.s.l., 1950–2023</p> </td> </tr> <tr> <td> <p><strong>Dataset Description</strong> </p> </td> <td> <p>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. </p> </td> </tr> <tr> <td> <p><strong>Key Methodologies</strong> </p> </td> <td> <p>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.</p> </td> </tr> <tr> <td> <p><strong>Temporal Domain</strong> </p> </td> <td> <p>1950–2023</p> </td> </tr> <tr> <td> <p><strong>Spatial Domain</strong> </p> </td> <td> <p>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).</p> </td> </tr> <tr> <td> <p><strong>Key Variables/Indicators</strong> </p> </td> <td> <p>Standardized Precipitation Evapotranspiration Index 90-days (SPEI-90 days)</p> </td> </tr> <tr> <td> <p><strong>Data Format</strong> </p> </td> <td> <p>netCDF </p> </td> </tr> <tr> <td> <p><strong>Source Data</strong> </p> </td> <td> <p>E-OBS dataset (v29.0e)</p> </td> </tr> <tr> <td> <p><strong>Accessibility</strong> </p> </td> <td> <p>https://doi.org/10.5281/zenodo.13778103</p> </td> </tr> <tr> <td> <p><strong>Stakeholder Relevance</strong> </p> </td> <td> <p>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).</p> </td> </tr> <tr> <td> <p><strong>Limitations/Assumptions</strong> </p> </td> <td> <p>Excludes areas above 1500 m a.s.l. </p> </td> </tr> <tr> <td> <p><strong>Additional Outputs/Information</strong> </p> </td> <td> <p>DBSCAN 3D Clusters of SPEI-90 Days Values – Italian NUTS3 (ITH31, 32, 34, 35, 36, 37), 1950–2023 (https://zenodo.org/records/13785996) </p> <p>The dataset access is currently restricted due to pending related publication.</p> </td> </tr> <tr> <td> <p><strong>Contact Information</strong></p> </td> <td> <p>Crespi, Alice (Center for Climate Change and Transformation, Eurac Research, Bolzano, Italy) - Data manager<br>Lemus 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 curator<br>Maines, Elena (Center for Climate Change and Transformation, Eurac Research, Bolzano, Italy) - Data curator<br>Masina, Marinella (CMCC Foundation - Euro-Mediterranean Center on Climate Change)- Data curator<br>Maraschini, Margherita (CMCC Foundation - Euro-Mediterranean Center on Climate Change) - Data curator<br>Ferrario, Davide Mauro (CMCC Foundation - Euro-Mediterranean Center on Climate Change) - Data curator<br>Furlanetto, Jacopo (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - Data manager<br>Pittore, Massimiliano (Center for Climate Change and Transformation, Eurac Research, Bolzano, Italy) - Data manager<br>Terzi, Stefano (Center for Climate Change and Transformation, Eurac Research, Bolzano, Italy) - Data manager<br>Torresan, Silvia (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - Data manager</p> </td> </tr> </tbody> </table>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.