In this section
@article{Lee:2026:1748-9326/aea7b9,
author = {Lee, D and Chen, CS and Ceppi, P and Otto, FEL and Park, I-H and Leach, NJ and Sparrow, SN and Allen, M},
doi = {1748-9326/aea7b9},
journal = {Environmental Research Letters},
title = {Attribution and projection of February extreme rainfall events in Southeast Africa},
url = {http://dx.doi.org/10.1088/1748-9326/aea7b9},
year = {2026}
}
TY - JOUR
AB - <jats:title>Abstract</jats:title> <jats:p>Record-breaking extreme rainfall events, such as those observed in Southeast Africa (SEAF) in February 2023, underscore the urgent need to quantify anthropogenic impacts on extreme weather risks. This study presents an attribution and projection analysis of February extreme rainfall in SEAF by evaluating probabilistic risk changes across multiple Earth System Model (ESM) ensembles and Numerical Weather Prediction (NWP) experiments. While NWP models reliably capture the magnitude and frequency of these extremes, ESMs generally exhibit a wet bias, necessitating the use of relative thresholds. Our attribution analysis reveals that greenhouse gas (GHG) forcing significantly increases the risk of extreme events (e.g., once-in-70-year and once-in-150-year events, comparable to the precipitation intensities of 2000 and 2023). However, this risk increase remains less certain under all-forcing simulations, as ESMs show substantial disagreement regarding aerosol (AER) influences. Future projections under various Shared Socioeconomic Pathways (SSPs) indicate that a higher GHG emission exacerbates these risks, highlighting the critical importance of aggressive mitigation efforts. Furthermore, shifts in Generalized Extreme Value (GEV) parameters demonstrate how forcing-driven climate changes may deform the risk probability distribution, with a higher emission of GHG potentially altering both the climatological mean and interannual variability of SEAF extreme rainfall. Our findings are supported by both ESM and NWP results (particularly short-lead forecasts), with the latter exhibiting lower uncertainty due to constraints on synoptic systems and internal oceanic variability. We conclude that GHG forcing likely elevates the risk of 2023-like extreme events in SEAF and discuss the remaining sources of uncertainty in these projections.</jats:p>
AU - Lee,D
AU - Chen,CS
AU - Ceppi,P
AU - Otto,FEL
AU - Park,I-H
AU - Leach,NJ
AU - Sparrow,SN
AU - Allen,M
DO - 1748-9326/aea7b9
PY - 2026///
TI - Attribution and projection of February extreme rainfall events in Southeast Africa
T2 - Environmental Research Letters
UR - http://dx.doi.org/10.1088/1748-9326/aea7b9
UR - https://doi.org/10.1088/1748-9326/aea7b9
ER -