Articles | Volume 15, issue 2
Research article
 | Highlight paper
18 Mar 2024
Research article | Highlight paper |  | 18 Mar 2024

Possible role of anthropogenic climate change in the record-breaking 2020 Lake Victoria levels and floods

Rosa Pietroiusti, Inne Vanderkelen, Friederike E. L. Otto, Clair Barnes, Lucy Temple, Mary Akurut, Philippe Bally, Nicole P. M. van Lipzig, and Wim Thiery

Data sets

Data used in Pietroiusti et al. 2024 ESD Rosa Pietroiusti et al.

Database for Hydrological Time Series over Inland Waters (DAHITI) Technical University Munich

NOAA Climate Data Record (CDR) of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN-CDR) S. Sorooshian et al.

ISIMIP3b bias-adjusted atmospheric climate input data Stefan Lange and Matthias Büchner

GISS Surface Temperature Analysis (GISTEMP) GISTEMP Team

Dipole Mode Index (DMI) Global Climate Observing System Working Group on Surface Pressure

Global Land Cover 2000 database (Africa) Joint Research Centre

Soil Atlas of Africa and its associated Soil Map (data). JRC European Soil Data Center (ESDAC)

Shoreline, Lake Victoria, vector polygon, 2015 S. Hamilton

Model code and software

Climate Explorer KNMI/WMO

VUB-HYDR/2024_Pietroiusti_etal_ESD: Release of Lake Victoria Python water balance model and analysis scripts (v1.0) Rosa Pietroiusti

Chief editor
This paper examines a highly impactful climate extreme in Africa - a region which is very vulnerable to climate change but has received comparatively little attention in the extreme event attribution literature. Its analysis brings event attribution science closer to societal impacts.
Short summary
Heavy rainfall in eastern Africa between late 2019 and mid 2020 caused devastating floods and landslides and drove the levels of Lake Victoria to a record-breaking maximum in May 2020. In this study, we characterize the spatial extent and impacts of the floods in the Lake Victoria basin and investigate how human-induced climate change influenced the probability and intensity of the record-breaking lake levels and flooding by applying a multi-model extreme event attribution methodology.
Final-revised paper