This paper describes an integrated, high-resolution dataset of hydro-meteorological variables (rainfall and discharge) concerning a number of high-intensity flash floods that occurred in Europe and in the Mediterranean region from 1991 to 2015. This type of dataset is rare in the scientific literature because flash floods are typically poorly observed hydrological extremes. Valuable features of the dataset (hereinafter referred to as the EuroMedeFF database) include (i) its coverage of varied hydro-climatic regions, ranging from Continental Europe through the Mediterranean to Arid climates, (ii) the high space–time resolution radar rainfall estimates, and (iii) the dense spatial sampling of the flood response, by observed hydrographs and/or flood peak estimates from post-flood surveys. Flash floods included in the database are selected based on the limited upstream catchment areas (up to 3000 km²), the limited storm durations (up to 2 days), and the unit peak flood magnitude. The EuroMedeFF database comprises 49 events that occurred in France, Israel, Italy, Romania, Germany and Slovenia, and constitutes a sample of rainfall and flood discharge extremes in different climates. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the identification and analysis of the hydro-meteorological causative processes, evaluation of flash flood hydrological models and for hydro-meteorological forecast systems. The dataset also provides a template for the analysis of the space–time variability of flash flood triggering rainfall fields and of the effects of their estimation on the flood response modelling. The dataset is made available to the public with the following DOI: https://doi.org/10.6096/MISTRALS-HyMeX.1493.

Periodic climate zoning is an essential classification of land cover to account for anthropogenic activities resulting from population increase and urbanization that affect key climate response parameters. Rainfall, relative humidity (RH), maximum (T_max) and minimum temperature (T_min) data from the Ghana Meteorological Agency were used to zone Ghana by adopting cluster and PCA analysis methods and verifying the groupings with the seasonal trend and Tukey Honestly Significance Difference (HSD) analysis. The cluster analysis grouped the synoptic stations into four major homogenous clusters while the PCA distributed them into three sub‐divisions with reference to 1976–2018. Rainfall, RH, T_max and T_min were characterized by five, three, two and three factors with factor loadings in the range of 0.71–0.78, 0.53–0.70, 0.54–0.74 and 0.50–0.72, respectively. HSD found transition stations like Bole and Kete Krachi in cluster 1 and 2 to have no significant difference with cluster 1, while Wenchi, Sunyani, Sefwi Bekwai and Koforidua in cluster 2 had no significant difference with cluster 3. Accra station which was classified in cluster 3 showed the seasonal pattern of cluster 4 and was confirmed by HSD to belong in cluster 4. Therefore, Ghana‐based on‐point analysis is climatically grouped into Savannah (11°0′0′′N–7°46′11′′N), Forest (from 7°46′11′′N to the coast) and Coastal (about 30 km from the Gulf of Guinea coastline) based on the assessed parameters. These findings are vital for planners and decision‐makers especially for industries that depend on weather and climatic conditions for their activities.