Editing IPCC:AR6/WGII/Chapter-12 (section)

=== 12.3.6 Southeastern South America Sub-region ===

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==== 12.3.6.1 Hazards ====

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An increase in the intensity and frequency of hot extremes and decrease in the intensity and frequency of cold extremes were observed with ''high confidence'' ( [[#Rusticucci--2017|Rusticucci et al., 2017]] ; [[#Wu--2017|Wu and Polvani, 2017]] ) (WGI AR6 Table 11.13) ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ). There is ''low confidence'' that the decrease in hot extremes over SES is related to an increase in extreme precipitation ( [[#Wu--2017|Wu and Polvani, 2017]] ).

Over SES most stations have registered an increase in annual rainfall, largely attributable to changes in the warm season; this is one of few sub-regions where a robust positive trend in precipitation and significant intensification of heavy precipitation have been detected since the early 20th century ( ''high confidence'' ) but with ''medium confidence'' in a reduction of hydrological droughts ( [[#Vera--2015|Vera and Díaz, 2015]] ; [[#Saurral--2017|Saurral et al., 2017]] ; [[#Lovino--2018|Lovino et al., 2018]] ; [[#Avila-Diaz--2020|Avila-Diaz et al., 2020]] ; [[#Carvalho--2020|Carvalho, 2020]] ; [[#Dereczynski--2020|Dereczynski et al., 2020]] ; [[#Dunn--2020|Dunn et al., 2020]] ; [[#Marengo--2020a|Marengo et al., 2020a]] ; [[#Olmo--2020|Olmo et al., 2020]] ) (WGI AR6 Table 11.14) ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ). A higher observed frequency of extratropical cyclones in the region has been detected ( [[#Parise--2009|Parise et al., 2009]] ; [[#Reboita--2018|Reboita et al., 2018]] ) with three cyclogenetic foci: south-southeastern Brazil, extreme south of Brazil and Uruguay, and southeastern Argentina.

In Montevideo, mean sea levels have increased over the past 20 years, reaching 11 cm from 1902 to 2016, and a recent accelerating trend has been observed ( [[#Gutiérrez--2016b|Gutiérrez et al., 2016b]] ). A value of water level rise and its acceleration for Buenos Aires was calculated from a record of annual mean water levels obtained from hourly levels (1905–2003). Annual mean water level showed a trend of +1.7 ± 0.05 mm yr −1 and an acceleration of +0.019 ± 0.005 mm yr −2 ( [[#D’Onofrio--2008|D’Onofrio et al., 2008]] ).

Increasing trends in mean air temperature and extreme heat and decreasing cold spells are projected ( ''high confidence'' ) (WGI AR6 Table 12.6) ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ). The increase in the frequency of warm nights is larger than that projected for warm days, consistent with observed past changes that have been related to changes in cloud cover that affect daytime temperatures differently than nighttime temperatures ( [[#López-Franca--2016|López-Franca et al., 2016]] ; [[#Menéndez--2016|Menéndez et al., 2016]] ; [[#Feron--2019|Feron et al., 2019]] ).

Increases in mean precipitation ( ''high confidence'' ), pluvial floods and river floods are projected ( ''medium confidence'' ) ( [[#Nunes--2018|Nunes et al., 2018]] ) (WGI AR6 Table 12.6) ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ). Droughts in the River Plate basin will be more frequent in the medium term (2011–2040) and the distant future (2071–2100) (with respect to the 1979–2008 period), but also shorter and more severe, for the more extreme emission scenario (RCP8.5) ( ''low confidence'' ) ( [[#Carril--2016|Carril et al., 2016]] ) ''.''

Negative trends in the annual number of cyclone events in the long term of 3.6% to 6.5% (2070–2098) are projected and showed an increase of 3% to 11% (2080–2100 for the A1B scenario) ( [[#Grieger--2014|Grieger et al., 2014]] ; [[#Reboita--2018|Reboita et al., 2018]] ). All coastal and oceanic climate impact drivers (relative sea level, coastal flood and erosion, marine heatwaves and ocean aridity) are expected to increase by mid-century in the RCP8.5 scenario ( ''high confidence'' ) (WGI AR6 Table 12.6) ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ).

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==== 12.3.6.2 Exposure ====

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Higher temperatures and SLR, changes in rainfall patterns, and an increased frequency and intensity of extreme weather events could generate risks to the energy and infrastructure sectors and to the mining and metals industry. In the River Plate basin, urban floods have become more frequent, causing infrastructure damage and sometimes substantial mortality ( ''high confidence'' ) ( [[#Barros--2015|Barros et al., 2015]] ; [[#Zambrano--2017|Zambrano et al., 2017]] ; [[#Nagy--2019|Nagy et al., 2019]] ; [[#Mettler-Grove--2020|Mettler-Grove, 2020]] ; [[#Morales-Yokobori--2021|Morales-Yokobori, 2021]] ; [[#Oyedotun--2021|Oyedotun and Ally, 2021]] ). A large increase in landslides and flash floods is also predicted for the Brazilian portion of SES, where they are responsible for the majority of deaths related to disasters in the country ( ''high confidence'' ) ( [[#Debortoli--2017|Debortoli et al., 2017]] ; [[#Haque--2019|Haque et al., 2019]] ; [[#Saito--2019|Saito et al., 2019]] ; [[#Marengo--2020d|Marengo et al., 2020d]] ; [[#da%20Fonseca%20Aguiar--2021|da Fonseca Aguiar and Cataldi, 2021]] ). Due to uncontrolled urban growth, 21.5 million people living in the large Brazilian cities of São Paulo, Rio de Janeiro and Belo Horizonte (estimate for 2019 fromIBGE [2020]]) are expected to be exposed to water scarcity, despite widespread water availability in the region ( ''medium evidence, medium agreement'' ) ( [[#Marengo--2017|Marengo et al., 2017]] , [[#Marengo--2020b|Marengo et al., 2020b]] ; Lima and Magaña Rueda, 2018).

The expected increase in temperature will also expose the populations in large cities to extreme heat. Urban heat islands are already a reality in large cities in the region, such as Buenos Aires ( ''high confidence'' ) ( [[#Wong--2013|Wong et al., 2013]] ; [[#Sarricolea--2019|Sarricolea and Meseguer-Ruiz, 2019]] ; [[#Wu--2019|Wu et al., 2019]] ; [[#Mettler-Grove--2020|Mettler-Grove, 2020]] ), Rio de Janeiro ( ''high confidence'' ) ( [[#Ceccherini--2016|Ceccherini et al., 2016]] ; [[#Neiva--2017|Neiva et al., 2017]] ; [[#Geirinhas--2018|Geirinhas et al., 2018]] ; Peres et al., 2018; [[#Sarricolea--2019|Sarricolea and Meseguer-Ruiz, 2019]] ; [[#Wu--2019|Wu et al., 2019]] ; [[#de%20Farias--2021|de Farias et al., 2021]] ) and São Paulo ( ''high confidence'' ) ( [[#Mishra--2015|Mishra et al., 2015]] ; [[#Barros--2016|Barros and Lombardo, 2016]] ; [[#Ceccherini--2016|Ceccherini et al., 2016]] ; [[#Vemado--2016|Vemado and Pereira Filho, 2016]] ; [[#de%20Azevedo--2018|de Azevedo et al., 2018]] ; Lima and Magaña Rueda, 2018; [[#Ferreira--2019|Ferreira and Duarte, 2019]] ; [[#Lapola--2019a|Lapola et al., 2019a]] ; [[#Sarricolea--2019|Sarricolea and Meseguer-Ruiz, 2019]] ; [[#Wu--2019|Wu et al., 2019]] ), with reported impact on human health in the latter ( ''medium confidence: medium evidence, medium agreement'' ) (e.g., Araujo et al. 2015; Son et al. 2016; Diniz et al. 2020). These cities alone represent 22 million people exposed to increased heat (estimate for 2019 fromIBGE [2020]] and from INDEC [2010]).

The sub-region presents a high frequency of occurrence of intense severe convection events ( [[#12.3.6.1|Section 12.3.6.1]] ). Because of this situation, strong winds from the south or southeast and high water levels affect the whole Argentine coast, as well as the River Plate shores, Uruguay and southern Brazil ( [[#Isla--2009|Isla and Schnack, 2009]] ). The coast of the River Plate is subject to flooding when there are strong winds from the southeast (sudestadas). As sea level rises as a result of global climate change, storm surge floods will become more frequent in this densely populated area, particularly in low-lying areas ( ''high confidence'' ) (Figure 12.8) ( [[#D’Onofrio--2008|D’Onofrio et al., 2008]] ; [[#Nagy--2014a|Nagy et al., 2014a]] ; [[#Santamaria-Aguilar--2017|Santamaria-Aguilar et al., 2017]] ; [[#Nagy--2019|Nagy et al., 2019]] impacts and adaptation in Central and South America coastal areas; [[#Cerón--2021|Cerón et al., 2021]] ).

The region’s natural systems are also exposed to climate change. The SES region is home to two important biodiversity hotspots, with high levels of species endemism: the Cerrado and the Atlantic Forest, where about 72% of Brazil’s threatened species can be found ( [[#PBMC--2014|PBMC, 2014]] ).

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==== 12.3.6.3 Vulnerability ====

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The River Plate basin and the city of Buenos Aires are highly vulnerable to recurring floods, and the increasing number of newcomers to the area reduce the collective cultural adaptation developed by older neighbours ( ''high confidence'' ) ( [[#Barros--2006|Barros, 2006]] ; [[#Nagy--2019|Nagy et al., 2019]] ; [[#Mettler-Grove--2020|Mettler-Grove, 2020]] ; [[#Morales-Yokobori--2021|Morales-Yokobori, 2021]] ; [[#Oyedotun--2021|Oyedotun and Ally, 2021]] ). Extreme events, including storm surges and coastal inundation/flooding, cause injuries and economic/environmental losses on the urbanised coastline of Southern Brazil (States of São Paulo and Santa Catarina) ( ''high confidence'' ) ( [[#Muehe--2010|Muehe, 2010]] ; [[#Khalid--2020|Khalid et al., 2020]] ; [[#Ohz--2020|Ohz et al., 2020]] ; [[#de%20Souza--2021|de Souza and Ramos da Silva, 2021]] ; [[#Quadrado--2021|Quadrado et al., 2021]] ; [[#Silva%20de%20Souza--2021|Silva de Souza et al., 2021]] ).

Cities like Rio de Janeiro and São Paulo are overpopulated, where most people live in poor conditions of inadequate housing and sanitation, such as slums, with little and no trees and high temperatures. These people have low access to sanitation, public health and residential cooling and are vulnerable to the effects of heat islands on human comfort and health (Figure 12.7). These include cardiopulmonary, vector-borne diseases and even death ( ''medium confidence: medium evidence, medium agreement'' ) ( [[#Araujo--2015|Araujo et al., 2015]] ; [[#Mishra--2015|Mishra et al., 2015]] ; [[#Geirinhas--2018|Geirinhas et al., 2018]] ; Peres et al., 2018). Heat stress is known to worsen cardiovascular, diabetic and respiratory conditions ( [[#Lapola--2019a|Lapola et al., 2019a]] ). In connection with the heat island effect, these people are also vulnerable to injuries and casualties due to increased thunderstorms, causing economic losses and other social problems ( [[#Vemado--2016|Vemado and Pereira Filho, 2016]] ).

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==== 12.3.6.4 Impacts ====

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Despite the observed increase in rainfall in the region, between 2014 and 2016 Brazil endured a water crisis that affected the population and economy of major capital cities in the SES region ( [[#Blunden--2014|Blunden and Arndt, 2014]] ; [[#Nobre--2016a|Nobre et al., 2016a]] ). Extremely long dry spells have become more frequent in southeastern Brazil, affecting 40 million people and the economies in cities such as Rio de Janeiro, São Paulo and Belo Horizonte, which are the industrial centres of the country ( ''medium confidence: medium evidence, medium agreement'' ) ( [[#PBMC--2014|PBMC, 2014]] ; [[#Nobre--2016a|Nobre et al., 2016a]] ; [[#Cunningham--2017|Cunningham et al., 2017]] ; [[#Marengo--2017|Marengo et al., 2017]] , 2020b; Lima and Magaña Rueda, 2018). They have also impacted agriculture, affecting food supply and rural livelihoods, especially in Minas Gerais ( [[#Nehren--2019|Nehren et al., 2019]] ). Agricultural prices increased by 30% in some cases, and harvest yields of sugar cane, coffee and fruits suffered a reduction of 15–40% in the region. The number of fires increased by 150%, and energy prices increased by 20–25%, as most electricity comes from hydroelectric power ( [[#Nobre--2016a|Nobre et al., 2016a]] ). In Argentina, projected changes in the hydrology of Andean rivers associated with glacier retreat are predicted to have negative impacts on the region’s fruit production ( ''low evidence, medium agreemen'' t) ( [[#Barros--2015|Barros et al., 2015]] ).

Heat islands affect ecosystems by increasing the energy consumption for cooling, the concentration of pollutants and the incidence of fires ( ''high confidence'' ) ( [[#Wong--2013|Wong et al., 2013]] ; [[#Akbari--2016|Akbari and Kolokotsa, 2016]] ; [[#Singh--2020b|Singh et al., 2020b]] ; [[#Ulpiani--2021|Ulpiani, 2021]] ). It also affects human health, as well increasing the incidence of respiratory and cardiovascular diseases ( ''medium confidence: medium evidence, medium agreement'' ) ( [[#Araujo--2015|Araujo et al., 2015]] ; [[#Barros--2016|Barros and Lombardo, 2016]] ; [[#de%20Azevedo--2018|de Azevedo et al., 2018]] ; [[#Geirinhas--2018|Geirinhas et al., 2018]] ).

Warming temperatures have been implicated in the emergence of dengue in temperate latitudes, increasing populations of ''Aedes aegypti'' ( ''high confidence'' ) ( [[#Natiello--2008|Natiello et al., 2008]] ; [[#Robert--2019|Robert et al., 2019]] , 2020; [[#Estallo--2020|Estallo et al., 2020]] ; [[#López--2021|López et al., 2021]] ) (Table 12.1), and field studies have demonstrated the role of local climate in vector activity ( [[#Benitez--2021|Benitez et al., 2021]] ). Figure 12.5 shows the modelled transmission suitability for dengue for two climate-change scenarios. Future increases in the number of months suitable for transmission of dengue will be highest in SES (see SM12.8 for additional information). There is additional evidence of the spread of arbovirus into southern temperate latitudes ( [[#Basso--2017|Basso et al., 2017]] ); however, a longer historical time series is needed to understand climate–disease interactions, given the relatively recent emergence of arborvirus in this region.

SLR impacts the port complex in Santa Catarina, which during the last 6 years has interrupted its activities 76 times due to strong winds or big waves, with estimated losses varying between USD 25,000 and 50,000 for each 24 idle hours ( [[#Ohz--2020|Ohz et al., 2020]] ). Historically, extratropical cyclones associated with frontal systems cause storm surges in the city of Santos. Although there are no fatality records, these events cause several socioeconomic losses, especially in vulnerable regions, including the Port of Santos, the largest port in Latin America (São Paulo). In an 88-year time span (1928–2016), the frequency of storm surge events was three times greater in the last 17 years (2000–2016) than in the previous period of 71 years (1928–1999) (Souza et al., 2019).

There are many projected impacts of climate change on natural systems. The impacts of SLR are habitat destruction and the invasion of exotic species, which affect biodiversity and the provision of ecosystem services (Figure 12.8) ( [[#Nagy--2019|Nagy et al., 2019]] ).

SES is a global priority for terrestrial biodiversity conservation and is home to two important biodiversity hotspots—the Atlantic Forest and Cerrado—which are among the world’s most studied biodiversity hotspots in connection with climate-change impact on biodiversity, especially for terrestrial vertebrates (Section [https://www.ipcc.ch/chapter/12#CCP1.2.2 CCP1.2.2] ; [[#Manes--2021|Manes et al., 2021]] ). An increasing number of studies show that the Atlantic Forest and Cerrado are at risk of biodiversity loss, largely due to projected reductions of species’ geographic distributions in many different taxa (e.g., Loyola et al. 2012, 2014; Ferro et al. 2014; Hoffmann et al. 2015; Martins et al. 2015; Aguiar et al. 2016b; Vale et al. 2018; Borges et al. 2019; Braz et al. 2019; Vale et al. 2021). Cerrado savannahs are projected to be the hotspot most negatively impacted by climate change within SA, mostly though range contraction of plant species ( ''very high confidence'' ), while the Atlantic Forest is projected to be highly impacted especially though the contraction of the distribution of endemic species ( ''very likely'' ) (Section [https://www.ipcc.ch/chapter/12#CCP1.2.2 CCP1.2.2] ; Figure 12.10) ( [[#Manes--2021|Manes et al., 2021]] ). Reductions in species’ distribution are also projected in the River Plate basin for sub-tropical amphibians ( [[#Schivo--2019|Schivo et al., 2019]] ) and the river tiger ( ''Salminus brasiliensis'' ), a keystone fish of economic value ( [[#Ruaro--2019|Ruaro et al., 2019]] ). Farming of mussels and oysters in the region is predicted to be negatively impacted by climate change, particularly SLR, and ocean warming and acidification ( [[#Gasalla--2017|Gasalla et al., 2017]] ). Some more localised habitats are also at risk of losing area due to climate change, such as the meadows of northwestern Patagonia ( [[#Crego--2014|Crego et al., 2014]] ) and mangroves of southern Brazil ( [[#Godoy--2015|Godoy and Lacerda, 2015]] ). Predicted changes in global climate along with agricultural expansion will strongly affect South American wetlands, which comprise around 20% of the continent and bring many benefits, such as biodiversity conservation and water availability ( [[#Junk--2013|Junk, 2013]] ).

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