Characteristics of Intense Multi‐Day Wet Spells Over West Africa

This study examines the characteristics of intense multi-day wet spells in West Africa, which have significant socioeconomic impacts but remain understudied, using rain gauge and satellite-based rainfall data from 1982 to 2020. A gridded dataset, developed from the Karlsruhe African Surface Station-Database (KASS-D) using the SPHEREMAP interpolation method with data from 239 rain-gauging stations was compared with GPCC, CHIRPS and IMERG datasets. Wet days (rainfall > 1.0 mm) were aggregated into 3-day and 5-day events, with the 90th percentile threshold identifying intense wet spells. The quantile distribution of wet-day rainfall amounts in KASS-D aligns closely with GPCC, CHIRPS and IMERG datasets, although discrepancies occur at the tails of the distribution. KASS-D and the arithmetic mean of station data show similar quantile distributions when grid pixels contain 1–4 stations, but KASS-D values increase with more than four stations per pixel. The analysis reveals a latitudinal variation in wet spell frequency, with 5-day events often extending from 3-day events, peaking in June and September along the Guinea Coast and in August in other climatic zones. Over the course of the study period, the frequency of intense wet spells increased significantly, particularly in KASS-D, highlighting the added value of dense rain gauge networks in creating reanalysis and improving satellite rainfall products. Spatially large-sized intense events, along with average and maximum sizes, have increased, while small and medium-sized events have declined significantly (both in GPCC and CHIRPS), leading to a greater contribution of 3-day and 5-day wet spells to annual rainfall. The Guinea Coast experienced the highest increase in percentage contribution, while the Sahel saw the lowest. This study underscores the rising intensity, size and contribution of multi-day wet spells to annual rainfall in West Africa, emphasising the need for high-quality rain gauge networks and a deeper understanding of the dynamics driving these events.