2023/11/13-19 Brazil Heatwave
High temperatures in November 2023 Brazil heatwave mostly strengthened by human-driven climate change
Contact Authors
Gabriele Messori, Uppsala University, 📨gabriele.messori@geo.uu.se 🗣️Swedish, French, Italian, English
Davide Faranda, IPSL-CNRS, France 📨davide.faranda@lsce.ipsl.fr 🗣️French, Italian, English
Citation
Messori, G., & Faranda, D. (2024). High temperatures in November 2023 Brazil heatwave mostly strengthened by human-driven climate change. ClimaMeter, Institut Pierre Simon Laplace, CNRS. https://doi.org/10.5281/zenodo.14164307
Press Summary (First published 2023/11/22)
Heatwaves similar to the Brazil heatwave are between 1 ºC and 4 ºC hotter in the present than they would have been in the past across much of central-southern Brazil and surrounding countries.
The heatwave was a largely unique event; we thus have low confidence in the robustness of our approach.
Natural climate variability likely played a role in driving the pressure pattern and the associated increase in temperatures linked to the Brazilian heatwave, but human-driven climate change may have also contributed.
Event Description
On November 13-19 2023, Brazil faced its eighth heatwave of the year, a month before the start of meteorological summer in the southern hemisphere. Brazil recently experienced its highest-ever recorded temperature, reaching 44.8°C (112.6°F) in the town of Araçuaí, located in the state of Minas Gerais. The National Institute of Meteorology (Inmet) reported that Araçuaí's temperature surpassed the previous national record of 44.7°C set in 2005. Red alerts have been issued across the country due to the extreme heat. The soaring temperatures have led to a surge in energy consumption as residents strove to stay cool.
The heatwave raised serious health concerns, leading to emergency measures in leisure venues to ensure access to water for attendees. Tragically, a Taylor Swift concert in Rio de Janeiro witnessed the death of a fan', and numerous others suffering from dehydration. The oppressive heat, reaching a perceived temperature of 59.7 °C in Rio, exacerbated social inequalities, especially affecting low-income residents living in poor-quality housing and who lacked access to cooling resources.
Surface Pressure Anomalies show negative anomalies in the southern part of the analyzed domain, while Temperature Anomalies show that large areas of Southern Brazil reach temperatures of up to 8°C higher than climatology. Precipitation data shows that this period was also characterized by dry conditions in most of Brazil, and Windspeed Data shows low values across the region considered.
Climate and Data Background for the Analysis
According to the IPCC AR6 report, there is high confidence that warm spells/heatwaves have increased in frequency or intensity over most land areas in South America, and high confidence that this is due to anthropogenic climate change (p. 1532), albeit with a marked regional variability. The IPCC report further states that: “the expected increase in temperature will also expose the populations in large cities to extreme heat” (p. 1711) and that there is medium confidence in a number of adverse effects of higher temperatures on urban populations.
Our analysis approach rests on looking for weather situations similar to those of the event of interest having been observed in the past. For the Brazilian heatwave, 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 Cerberus 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 [-80°E– 30°E, 10°S–30°S]. Surface Pressure Changes over the considered domain mainly show modest increases (about 1 hPa). Temperature Changes show that similar events produce temperatures which are between 1 ºC and 4 ºC hotter than what they would have been in the past. Precipitation Changes show that similar events are also dryer in the present than in the past (by 0-15 mm/day in southwestern Brazil). Windspeed Changes show that present events are associated with weaker winds (by 0-7 km/h). We also note that Similar Past Events have become more frequent in November, while they previously occurred more in October and December. These changes coincided with higher temperatures, lower precipitation and slightly strengthen winds in Rio de Janeiro, Corumba and Sao Paulo than what they would have been in the past.
Finally, we find that sources of natural climate variability, notably the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation, may have influenced the event. This suggests that the changes we see in the event compared to the past may be partly due to human driven climate change, with a contribution from natural variability.
Conclusion
Based on the above, we conclude that events similar to the Brazilian heatwave are showing increasing pressure and between 1 ºC and 4 ºC warmer temperatures in the present than in the past. We interpret this heatwave as a largely unique event for which natural climate variability played a role.
Additional Information : Complete Output of the Analysis
NB1: The following output is specifically intended for scientists and contain details that are fully understandable only by reading the methodology described in Faranda, D., Bourdin, S., Ginesta, M., Krouma, M., Noyelle, R., Pons, F., Yiou, P., and Messori, G.: A climate-change attribution retrospective of some impactful weather extremes of 2021, Weather Clim. Dynam., 3, 1311–1340, https://doi.org/10.5194/wcd-3-1311-2022, 2022.
NB2: Colorscales may vary from the ClimaMeter figure presented above.
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.