2024/05/02 South Brazil Floods


South Brazil Floods locally exacerbated by both human-driven climate change and natural variability

Press Summary (First Published, 10/05/2024)

Event Description

On April 30 to May 2, 2024, the Rio Grande do Sul state in southern Brazil was affected by heavy rainfall, including the state capital Porto Alegre. A low pressure area developed and deepened over central South America on April 15, slowly moving to the East the following day.  As a result, the state received heavy rainfall across several days, with large regions exceeding 200 mm accumulated precipitation over the three days, as reported by Brazil's National Institute of Meteorology in their interactive analysis tool.  There have been reports of extensive flooding, mudslides, burst dams, 90 dead or missing persons and over 500,000 persons lacking water and electricity. The precipitation caused record flooding throughout the region. At the state capital, Porto Alegre, the Guaíba river reached 5,3m on May 5th, surpassing the historical flood of 1941, which reached 4,76m. The local flood level is 3m. Other cities, such as Lajeado, have also seen record high flood levels, surpassing previous levels reached at the 1941 and 2023 extreme events. The consequences may have been exacerbated by other extreme precipitation events in the last 12 months, which had already caused record floods and population displacement. In June 2023, the state capital recorded its wettest June since 1916, reaching 141,7mm

The Surface Pressure Anomalies show a large negative (cyclonic) anomaly. This depression produced heavy rainfall in Rio Grande do Sul. Temperature anomalies show positive values over almost all of the analysed domain, with anomalies in Rio Grande do Sul of up to 5 °C. Precipitation data show high amounts exceeding 50mm/day over southern Brazil. Wind speed data show large areas of the domain affected by moderate winds, with areas close to the low pressure core experiencing values of around 30 km/h.

Climate and Data Background for the Analysis

The impact of climate change on changes in precipitation and flooding in the state of Rio Grande do Sul in Southern Brazil is characterized by a mix of increasing extreme precipitation events and changes in regional precipitation patterns, with implications for agriculture and water resources. Changes in precipitation patterns have been observed in different parts of Brazil over the past century. For example, significant increases in precipitation have been noted in southeastern Brazil, while non-significant decreases have been found in central Brazil (IPCC AR6 WGI FR - Page 1116). In southeast Brazil, there has been a region of highly significant decrease in rainfall in both wet and dry seasons during the period 1979-2011 (IPCC AR6 WGI FR - Page 2012). A warmer climate is projected to intensify very wet and very dry weather events, leading to implications for flooding or drought in the region (IPCC AR6 WGI SPM - Page 19). In particular in the South-Eastern South America, an increase in both mean and extreme precipitation has been observed since 1960 with high confidence and the intensity and frequency of extreme precipitation and pluvial flooding is projected to increase with medium confidence from a 2oC of global warming and above (IPCC AR6 WGI TS4.3.2.4 - Page 140).   Changes in precipitation and extreme temperatures are impacting agricultural production in the region, with increasing mean precipitation positively impacting agriculture in some areas but extremely long dry spells affecting economies in southeastern Brazil (IPCC AR6 WGII FR - Page 1703). 

Our analysis approach rests on looking for weather situations similar to those of the event of interest having been observed in the past. For this event we have medium-high confidence in the robustness of our approach given the available climate data, as the event is similar to other past events in the data record

ClimaMeter Analysis

We analyze here (see Methodology for more details) how events similar to the pressure system leading to the south Brazil Floods changed in the present (2001–2023) compared to what they would have looked like if they had occurred in the past (1979–2001) in the region [53°W 48°W 28°S 32°S]. The Surface Pressure Changes show that similar depressions have about the same intensity around the low pressure centre and they are less deep in the southern region of the domain analysed. The Temperature Changes show no significant changes. The Precipitation Changes show significant increasing precipitation in Rio Grande do Sul state with the Porto Alegre area experiencing (3-6 mm/day) up to 15% more precipitation in the present than in the past. Windspeed Changes indicate no significant changes. We also note that Similar Past Events occur with roughly the same seasonality in the past and present periods. Changes in Urban Areas reveal that Porto Alegre,  Caxias do Sul and São Leopoldo are up to 6 mm/day wetter (up to  15% more precipitation) in the present compared to the past. 

Finally, we find that sources of natural climate variability, notably the Atlantic Multidecadal Oscillation may have influenced the changes in this event. While ElNiño-Southern Oscillation can have an impact on precipitation in south Brasil, we see no significant change in the impacts of ElNiño  events similar to the pressure system leading to the south Brazil Floods in the present compared to the past. This suggests that the changes we see in the event compared to the past may be due to human driven climate change, with a  minor contribution from natural variability.

Conclusion

Based on the above, we conclude that depressions similar to those producing Brazil Floods show locally increasing precipitation (1-6 mm/day, namely up to 15% more precipitation) over the Rio Grande do Sul state in Brazil in the present compared to the past, but no significant large-scale precipitation changes in this state. While ElNiño-Southern Oscillation may have favoured the heavy precipitation, it does not explain changes associated with this event when comparing the past and present periods. We interpret Brazil floods as an event whose local characteristics can mostly be ascribed to human driven climate change.

Contact Authors

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

-Gabriele Messori, Uppsala University, Sweden; 📨gabriele.messori@geo.uu.se 🗣️ Italian, English, French, Swedish

-Suzana J. Camargo, LDEO, Columbia University, USA;   suzana@ldeo.columbia.edu, English, Portuguese 

-Luiza Vargas-Heinz,  The Abdus Salam International Centre for Theoretical Physics, Italy; 📨 lvargas@ictp.it 🗣️Portuguese, English, French, Italian 

-Erika Coppola, The Abdus Salam International Centre for Theoretical Physics, Italy;  📨 coppolae@ictp.it 🗣️Italian, 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.