Climatology of heatwaves in South America identified through ERA5 reanalysis data
The rise in the Earth's global average surface temperature and the increase of extreme weather events have been the focus of scientific discussion in the last decades. Extreme heat combined with other environmental extremes, like high concentrations of air pollution, may induce health problems—...
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description | The rise in the Earth's global average surface temperature and the increase of extreme weather events have been the focus of scientific discussion in the last decades. Extreme heat combined with other environmental extremes, like high concentrations of air pollution, may induce health problems—especially in socioeconomically vulnerable populations. Spring in South America requires particular attention due to its association with hot, dry weather and air pollution in most parts of the continent. This paper intends to better comprehend the behaviour of heatwaves during the austral winter–spring transition. We propose identifying the spatial coverage, frequency and intensity of heatwaves in homogeneous areas of maximum air temperature near the surface (Tmax). We employed cluster analyses during the period between July and October for 41 years (1979–2019) through the ERA5 reanalysis. Homogeneous Tmax areas in South America were defined by cluster analyses that indicated three homogeneous Tmax regions, as follows: a larger area of the continent including the tropical region (Area 1), eastern and southeastern South America (Area 2) and southernmost and steep areas in the Andes (Area 3). The heatwave events identified via ERA5 reanalysis were classified according to their intensity (intense, moderate and weak events). Spatial frequency and trend analyses were also performed regarding the intensity and persistence of heatwave episodes. These methods allowed the identification of the behavioural aspect of heatwaves spanning the last four decades. The Mann–Kendall statistical test (MK) was applied in order to analyse the heatwave trend with a statistical significance level of 5%. A total of 191 heatwave episodes were identified. Of this total, 47.12, 35.60 and 17.28% of episodes occurred in Areas 2, 3 and 1, respectively. The hotter area extending from northeast to southwest in central South America stood out by its largest frequencies of intense heatwave episodes. Across the continent there was a significant increase in the intensity and persistence of heatwaves over the period of 1979 through to 2019.
(a) Analysis of the Silhouette index and (b) spatialized clusters applied to Tmax ERA5 reanalysis for three cluster groups (Z = 3) over the JASO period (1979–2019). Cluster 1 is indicated by Area 1, cluster 2 is indicated by Area 2 and cluster 3 is indicated by Area 3. |
doi_str_mv | 10.1002/joc.7831 |
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(a) Analysis of the Silhouette index and (b) spatialized clusters applied to Tmax ERA5 reanalysis for three cluster groups (Z = 3) over the JASO period (1979–2019). Cluster 1 is indicated by Area 1, cluster 2 is indicated by Area 2 and cluster 3 is indicated by Area 3.</description><identifier>ISSN: 0899-8418</identifier><identifier>EISSN: 1097-0088</identifier><identifier>DOI: 10.1002/joc.7831</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>2‐m temperature ; Air pollution ; Air temperature ; climate change ; Climatology ; Clusters ; Extreme heat ; Extreme high temperatures ; Extreme weather ; extreme weather events ; Frequency analysis ; Frequency dependence ; Health problems ; Heat waves ; Heatwaves ; hot weather ; Identification ; South America ; Spatial analysis ; Spring ; Spring (season) ; Statistical tests ; Statistics ; Surface temperature ; temperature extremes ; Tropical environment ; Tropical environments ; Weather</subject><ispartof>International journal of climatology, 2022-12, Vol.42 (16), p.9430-9448</ispartof><rights>2022 Royal Meteorological Society</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2231-7e25903d107e4c71bd86c85303326dadccf8815ff3ff2a31fcc34541b1319a653</citedby><cites>FETCH-LOGICAL-c2231-7e25903d107e4c71bd86c85303326dadccf8815ff3ff2a31fcc34541b1319a653</cites><orcidid>0000-0001-8420-8033 ; 0000-0002-9716-4006 ; 0000-0001-5858-7287 ; 0000-0001-6727-4290 ; 0000-0002-3901-2362</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjoc.7831$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjoc.7831$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27903,27904,45553,45554</link.rule.ids></links><search><creatorcontrib>Araújo, Glícia Ruth Garcia</creatorcontrib><creatorcontrib>Frassoni, Ariane</creatorcontrib><creatorcontrib>Sapucci, Luiz Fernando</creatorcontrib><creatorcontrib>Bitencourt, Daniel</creatorcontrib><creatorcontrib>Brito Neto, Francisco Agustinho</creatorcontrib><title>Climatology of heatwaves in South America identified through ERA5 reanalysis data</title><title>International journal of climatology</title><description>The rise in the Earth's global average surface temperature and the increase of extreme weather events have been the focus of scientific discussion in the last decades. Extreme heat combined with other environmental extremes, like high concentrations of air pollution, may induce health problems—especially in socioeconomically vulnerable populations. Spring in South America requires particular attention due to its association with hot, dry weather and air pollution in most parts of the continent. This paper intends to better comprehend the behaviour of heatwaves during the austral winter–spring transition. We propose identifying the spatial coverage, frequency and intensity of heatwaves in homogeneous areas of maximum air temperature near the surface (Tmax). We employed cluster analyses during the period between July and October for 41 years (1979–2019) through the ERA5 reanalysis. Homogeneous Tmax areas in South America were defined by cluster analyses that indicated three homogeneous Tmax regions, as follows: a larger area of the continent including the tropical region (Area 1), eastern and southeastern South America (Area 2) and southernmost and steep areas in the Andes (Area 3). The heatwave events identified via ERA5 reanalysis were classified according to their intensity (intense, moderate and weak events). Spatial frequency and trend analyses were also performed regarding the intensity and persistence of heatwave episodes. These methods allowed the identification of the behavioural aspect of heatwaves spanning the last four decades. The Mann–Kendall statistical test (MK) was applied in order to analyse the heatwave trend with a statistical significance level of 5%. A total of 191 heatwave episodes were identified. Of this total, 47.12, 35.60 and 17.28% of episodes occurred in Areas 2, 3 and 1, respectively. The hotter area extending from northeast to southwest in central South America stood out by its largest frequencies of intense heatwave episodes. Across the continent there was a significant increase in the intensity and persistence of heatwaves over the period of 1979 through to 2019.
(a) Analysis of the Silhouette index and (b) spatialized clusters applied to Tmax ERA5 reanalysis for three cluster groups (Z = 3) over the JASO period (1979–2019). Cluster 1 is indicated by Area 1, cluster 2 is indicated by Area 2 and cluster 3 is indicated by Area 3.</description><subject>2‐m temperature</subject><subject>Air pollution</subject><subject>Air temperature</subject><subject>climate change</subject><subject>Climatology</subject><subject>Clusters</subject><subject>Extreme heat</subject><subject>Extreme high temperatures</subject><subject>Extreme weather</subject><subject>extreme weather events</subject><subject>Frequency analysis</subject><subject>Frequency dependence</subject><subject>Health problems</subject><subject>Heat waves</subject><subject>Heatwaves</subject><subject>hot weather</subject><subject>Identification</subject><subject>South America</subject><subject>Spatial analysis</subject><subject>Spring</subject><subject>Spring (season)</subject><subject>Statistical tests</subject><subject>Statistics</subject><subject>Surface temperature</subject><subject>temperature extremes</subject><subject>Tropical environment</subject><subject>Tropical environments</subject><subject>Weather</subject><issn>0899-8418</issn><issn>1097-0088</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1kMtOwzAQRS0EEqUg8QmW2LBJ8cRxYi-rqBRQpYrXOnL9aFyldbETqvw9KWXLajZnru49CN0CmQAh6cPGq0nBKZyhERBRJIRwfo5GhAuR8Az4JbqKcUMIEQLyEXotG7eVrW_8usfe4trI9iC_TcRuh99919Z4ujXBKYmdNrvWWWc0buvgu3WNZ29ThoORO9n00UWsZSuv0YWVTTQ3f3eMPh9nH-VTsljOn8vpIlFpSiEpTMoEoRpIYTJVwErzXHFGCaVprqVWynIOzFpqbSopWKVoxjJYAQUhc0bH6O6Uuw_-qzOxrTa-C0OTWKUF44LSYvAwRvcnSgUfYzC22odhcOgrINVR2PClqqOwAU1O6ME1pv-Xq16W5S__A8kAa1w</recordid><startdate>20221230</startdate><enddate>20221230</enddate><creator>Araújo, Glícia Ruth Garcia</creator><creator>Frassoni, Ariane</creator><creator>Sapucci, Luiz Fernando</creator><creator>Bitencourt, Daniel</creator><creator>Brito Neto, Francisco Agustinho</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0001-8420-8033</orcidid><orcidid>https://orcid.org/0000-0002-9716-4006</orcidid><orcidid>https://orcid.org/0000-0001-5858-7287</orcidid><orcidid>https://orcid.org/0000-0001-6727-4290</orcidid><orcidid>https://orcid.org/0000-0002-3901-2362</orcidid></search><sort><creationdate>20221230</creationdate><title>Climatology of heatwaves in South America identified through ERA5 reanalysis data</title><author>Araújo, Glícia Ruth Garcia ; Frassoni, Ariane ; Sapucci, Luiz Fernando ; Bitencourt, Daniel ; Brito Neto, Francisco Agustinho</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2231-7e25903d107e4c71bd86c85303326dadccf8815ff3ff2a31fcc34541b1319a653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>2‐m temperature</topic><topic>Air pollution</topic><topic>Air temperature</topic><topic>climate change</topic><topic>Climatology</topic><topic>Clusters</topic><topic>Extreme heat</topic><topic>Extreme high temperatures</topic><topic>Extreme weather</topic><topic>extreme weather events</topic><topic>Frequency analysis</topic><topic>Frequency dependence</topic><topic>Health problems</topic><topic>Heat waves</topic><topic>Heatwaves</topic><topic>hot weather</topic><topic>Identification</topic><topic>South America</topic><topic>Spatial analysis</topic><topic>Spring</topic><topic>Spring (season)</topic><topic>Statistical tests</topic><topic>Statistics</topic><topic>Surface temperature</topic><topic>temperature extremes</topic><topic>Tropical environment</topic><topic>Tropical environments</topic><topic>Weather</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Araújo, Glícia Ruth Garcia</creatorcontrib><creatorcontrib>Frassoni, Ariane</creatorcontrib><creatorcontrib>Sapucci, Luiz Fernando</creatorcontrib><creatorcontrib>Bitencourt, Daniel</creatorcontrib><creatorcontrib>Brito Neto, Francisco Agustinho</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>International journal of climatology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Araújo, Glícia Ruth Garcia</au><au>Frassoni, Ariane</au><au>Sapucci, Luiz Fernando</au><au>Bitencourt, Daniel</au><au>Brito Neto, Francisco Agustinho</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Climatology of heatwaves in South America identified through ERA5 reanalysis data</atitle><jtitle>International journal of climatology</jtitle><date>2022-12-30</date><risdate>2022</risdate><volume>42</volume><issue>16</issue><spage>9430</spage><epage>9448</epage><pages>9430-9448</pages><issn>0899-8418</issn><eissn>1097-0088</eissn><abstract>The rise in the Earth's global average surface temperature and the increase of extreme weather events have been the focus of scientific discussion in the last decades. Extreme heat combined with other environmental extremes, like high concentrations of air pollution, may induce health problems—especially in socioeconomically vulnerable populations. Spring in South America requires particular attention due to its association with hot, dry weather and air pollution in most parts of the continent. This paper intends to better comprehend the behaviour of heatwaves during the austral winter–spring transition. We propose identifying the spatial coverage, frequency and intensity of heatwaves in homogeneous areas of maximum air temperature near the surface (Tmax). We employed cluster analyses during the period between July and October for 41 years (1979–2019) through the ERA5 reanalysis. Homogeneous Tmax areas in South America were defined by cluster analyses that indicated three homogeneous Tmax regions, as follows: a larger area of the continent including the tropical region (Area 1), eastern and southeastern South America (Area 2) and southernmost and steep areas in the Andes (Area 3). The heatwave events identified via ERA5 reanalysis were classified according to their intensity (intense, moderate and weak events). Spatial frequency and trend analyses were also performed regarding the intensity and persistence of heatwave episodes. These methods allowed the identification of the behavioural aspect of heatwaves spanning the last four decades. The Mann–Kendall statistical test (MK) was applied in order to analyse the heatwave trend with a statistical significance level of 5%. A total of 191 heatwave episodes were identified. Of this total, 47.12, 35.60 and 17.28% of episodes occurred in Areas 2, 3 and 1, respectively. The hotter area extending from northeast to southwest in central South America stood out by its largest frequencies of intense heatwave episodes. Across the continent there was a significant increase in the intensity and persistence of heatwaves over the period of 1979 through to 2019.
(a) Analysis of the Silhouette index and (b) spatialized clusters applied to Tmax ERA5 reanalysis for three cluster groups (Z = 3) over the JASO period (1979–2019). Cluster 1 is indicated by Area 1, cluster 2 is indicated by Area 2 and cluster 3 is indicated by Area 3.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/joc.7831</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0001-8420-8033</orcidid><orcidid>https://orcid.org/0000-0002-9716-4006</orcidid><orcidid>https://orcid.org/0000-0001-5858-7287</orcidid><orcidid>https://orcid.org/0000-0001-6727-4290</orcidid><orcidid>https://orcid.org/0000-0002-3901-2362</orcidid></addata></record> |
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subjects | 2‐m temperature Air pollution Air temperature climate change Climatology Clusters Extreme heat Extreme high temperatures Extreme weather extreme weather events Frequency analysis Frequency dependence Health problems Heat waves Heatwaves hot weather Identification South America Spatial analysis Spring Spring (season) Statistical tests Statistics Surface temperature temperature extremes Tropical environment Tropical environments Weather |
title | Climatology of heatwaves in South America identified through ERA5 reanalysis data |
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