DBSCAN 3D Clusters of Heatwaves – Linguere, Senegal, 1950-2023

Science Case Name Multi-Hazards in Senegal. Dataset Name/Title DBSCAN 3D Clusters of Heatwaves – Linguere, Senegal, 1950-2023 Dataset Description The dataset contains gridded data on heatwaves over Linguere area of Senegal. Key Methodologies Heatwaves were defined as at least 3-day-long events on which daily maximum air temperature exceeded the 95$^{th}$ percentile of the 15-day moving average daily maximum air temperature. Daily maximum air temperature at 2 meters was downloaded from ERA5-Land dataset. Spatio-temporal DBSCAN was conducted with Python packages st_dbscan https://github.com/eren-ck/st_dbscan (Cakmak et al., 2021). Spatial proximity (epsilon 1) was set to 0.5 (0.5 degree), temporal proximity (epsilon 2) was set to 1.5 (1.5 days); min number of samples was set to 30. The values in the NetCDF files represent cluster numbers (from 0 to 11), with values -1 (negative 1) representing outliers. A summary table in CSV represents rows for each cluster with start and end dates, average severity and intensity, and maximum number of affected cells, starting from 1981. Temporal Domain 1950–2023, daily Spatial Domain Linguere, Senegal, West Africa Spatial resolution ca 0.1°x0.1° (EPGS:4326) Key Variables/Indicators Spatio-temporal clusters of heatwave events Data Format netCDF CSV Source Data ERA5-Land daily max air temperature Accessibility Zenodo, https://doi.org/10.5281/zenodo.15212719 Stakeholder Relevance Identifying and assessing past heatwave events for multi-hazard events monitoring, prediction and preparedness. Limitations/Assumptions The clustering was done over the specified region only. Each calendar year was clustered independently. Additional Outputs/information The dataset access is currently restricted due to pending related publication. Contact Information Egor Prikaziuk (UT-ITC, Faculty of Geo-Information Science and Earth Observation, ITC, University of Twente, the Netherlands)