2023/09/24-25 Cape Town floods

Low confidence prevents ascribing heavy precipitation in Cape Town to human-driven climate change 

Press Summary (First published 2023/09/28, Updated 2023/11/23)

Event Description

From September 24th to 25th, the Western Cape Province in South Africa experienced severe weather conditions, resulting in significant disruptions and adverse impacts on the region. The South African Weather Service for the Western Cape issued a high-level warning, an indication that severe impact is expected, in response to a cut-off low system intensifying on Sunday, leading to widespread thunderstorms and strong winds. The system resulted in rainfall of up to 300mmm in 24 hours in some places, and gale-force winds were anticipated along the western coast. Moreover a sharp drop in temperatures was observed, up to 10-15°C below the seasonal average. 

The severe weather had a significant impact on the Western Cape, resulting in one fatality in Mfuleni village, Cape Town City, as of September 26th. Additionally, two people remain missing, and six children have been displaced due to flooding in Cape Town City. Reports of road closures and mudslides have added to the disruption caused by these extreme weather events.  Surface Pressure Anomalies show a depression offshore South Africa with intense anomalies reaching up to -10 hPa. The Temperature Anomalies show negative values across most of the domain analyzed. Precipitation Data show that large rain amount (over 50 mm/day) have fallen in the province of Cape Town and Windspeed data show daily wind-speed above 50 km/h.

Climate and Data Background for the Analysis

The IPCC AR6 WG1 report states that the frequency and intensity of heavy precipitation events are projected to increase almost everywhere in Africa with additional global warming (high confidence).  Observed increase in heavy precipitation and pluvial flooding has been already detected in South Western Africa (medium confidence).  

South Africa's annual rainfall varies significantly year-to-year, averaging 450 mm from 1900 to 2009. Rainfall exceeded average levels in the 1970s, late 1980s, and mid to late 1990s but dipped below average in the 1960s and early 2000s before returning to average around 2010. Extreme rainfall events have increased, particularly in spring and summer, with fewer rainy days observed .Rainfall varies across South Africa, with arid to semi-arid conditions along the west coast due to dry, cold air from the Benguela current. Conversely, moist air from the Indian Ocean and Agulhas Current brings rain to the east when forced to ascend along the eastern escarpment. The southwestern Cape receives winter rainfall, while the Cape south coast experiences rain year-round. Flood risk is moderate along most of the coast but increases in high-rainfall areas. Average September rainfall at the Cape Town International Airport in the period 1979-2000 is 44 mm and in June (the climatologically wettest month) is 101mm, during the storm 86mm fell at the airport and in some places more rain fell in 2 days than in the previous 2 months.

Our analysis approach rests on looking for weather situations similar to those of the event of interest observed in the past. For the Cape Town Floods we have low confidence in the robustness of our approach given the available climate data, as the event is largely unique in the data record.

ClimaMeter Analysis

We analyse here (see Methodology for more details) how events similar to the low pressure systems leading to the recent Cape Town floods have changed in the present (2001–2022) compared to what they would have looked like if they had occurred in the past (1979–2000) in the region [12°E 35°E -40°N -28°N]. The Surface Pressure Changes show that low pressure systems have not changed their intensity compared to the past. Precipitation Changes show that similar events produce lower (between 1 and 8 mm/day) amounts of precipitation in Cape Town area. However, they also tend to produce the same precipitation amount in other areas, or more precipitation in  limited areas of the central part of the country. Considering the affected urban areas, Cape Town, Paarl and George see a decrease in precipitation in the present (1-10 mm/day). Only for the city of George this changes are statistically significant. We also find that Similar Past Events have become more frequent in October and slightly less frequent in September.

Finally, we find that sources of natural climate variability, notably the Pacific Decadal Oscillation/El Nino—Southern Oscillation and the Atlantic Multidecadal Oscillation, may have heavily influenced the event. This means that the changes we see in the event compared to the past may be primarily due to natural climate variability.


Based on the above, we conclude that low pressure systems leading to Cape Town floods similar to that observed in September 2023 are 1-10 mm/day dryer in the Cape Town province than they would have been in the past.  We interpret Cape-Town Floods as a largely unique event for which natural climate variability likely played an important role.

Contact Authors

Davide Faranda, IPSL-CNRS, France  📨davide.faranda@lsce.ipsl.fr  🗣️French, Italian, English

Erika  Coppola, ICTP, Italy  📨coppolae@ictp.it  🗣️Italian, English

Chris Lennard, Climate System Analysis Group, University of Cape Town 📨lennard@csag.uct.ac.za  🗣️English

Additional Information : Complete Output of the Analysis

The figure shows the average of surface pressure anomaly (msl) (a), average 2-meter temperatures anomalies (t2m) (e), cumulated total precipitation (tp) (i),  and average wind-speed (wspd) in the period of the event. Average of the surface pressure analogs found in the counterfactual [1979-2000] (b) and factual periods [2001-2022] (c), along with corresponding 2-meter temperatures (f, g),  cumulated precipitation (j, k), and wind speed (n, o).  Changes between present and past analogues are presented for surface pressure ∆slp (d),  2 meter temperatures ∆t2m (h), total precipitation ∆tp (i), and windspeed ∆wspd (p): color-filled areas indicate significant anomalies with respect to the bootstrap procedure. Violin plots for past (blue) and present (orange) periods for Quality Q analogs (q), Predictability Index D (r), Persistence Index Θ (s), and distribution of analogs in each month (t). Violin plots for past (blue) and present (orange) periods for ENSO (u), AMO (v) and PDO (w).  Number of the Analogues occurring in each subperiod (blue) and linear trend (black).  Values for the peak day of the extreme event are marked by a blue dot. Horizontal bars in panels (q,r,s,u,v,w) correspond to the mean (black) and median (red) of the distributions.