Editing IPCC:AR6/SROCC/Chapter-6 (section)

=== 6.5.2 Impacts on Human and Natural Systems ===

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Increasing frequency of extreme ENSO and IOD events have the potential to have widespread impacts on natural and human systems in many parts of the globe. Though the occurrence of the extreme 2015–2016 El Niño has produced a large body of literature, it is still not clear how climate change may have altered such an impact, nor how such impacts might change in the future with increasing frequency of extreme ENSO events. We highlight here some studies that have attempted to assess the joint impact of mean change and variability. In addition to observed high variability of rainfall, severe weather events and impacts on TCs activity (Yonekura and Hall, 2014 <sup>[[#fn:r541|541]]</sup> ; Zhang and Guan, 2014 <sup>[[#fn:r542|542]]</sup> ; Wang and Liu, 2016 <sup>[[#fn:r543|543]]</sup> ; Zhan, 2017 <sup>[[#fn:r544|544]]</sup> ), extreme El Nino events have substantial impacts on natural systems which include those on marine ecosystems (Sanseverino et al., 2016 <sup>[[#fn:r545|545]]</sup> ; Mogollon and Calil, 2017 <sup>[[#fn:r546|546]]</sup> ; Ohman et al., 2017 <sup>[[#fn:r537|537]]</sup> ), such as severe and repeated bleaching of corals (Hughes et al., 2017a <sup>[[#fn:r548|548]]</sup> ; Hughes et al., 2017b <sup>[[#fn:r549|549]]</sup> ; Eakin et al., 2018 <sup>[[#fn:r550|550]]</sup> ), and glacial growth and retreat (Thompson et al., 2017 <sup>[[#fn:r551|551]]</sup> ). On the other hand, impacts on human, including managed systems are: increased incidences of forest fires (Christidis et al., 2018b <sup>[[#fn:r552|552]]</sup> ; Tett et al., 2018 <sup>[[#fn:r553|553]]</sup> ), degraded air quality (Koplitz et al., 2015 <sup>[[#fn:r554|554]]</sup> ; Chang et al., 2016 <sup>[[#fn:r555|555]]</sup> ; Zhai et al., 2016 <sup>[[#fn:r556|556]]</sup> ) such as the dense haze over most parts of Indonesia and the neighbouring countries in Southeast Asia as a result of prolonged Indonesian wildfires, thus imposing adverse impacts on public health in the affected areas (Koplitz et al., 2015 <sup>[[#fn:r557|557]]</sup> ; WMO, 2016), decreased agricultural yields in many parts of the globe (e.g., in most of the Pacific Islands countries, Thailand, eastern and southern Africa and others which had resulted food insecurity, particularly in eastern and southern Africa (UNSCAP, 2015; WMO, 2016; Christidis et al., 2018b <sup>[[#fn:r558|558]]</sup> ; Funk et al., 2018 <sup>[[#fn:r559|559]]</sup> ), and regional uptick in the number of reported cases of plague and hantavirus in Colorado and New Mexico, cholera in Tanzania, dengue in Brazil and Southeast Asia (Anyamba et al., 2019 <sup>[[#fn:r560|560]]</sup> ) and Zika virus in South America (Caminade et al., 2017 <sup>[[#fn:r561|561]]</sup> ), including increases in heat stroke cases (Christidis et al., 2018b <sup>[[#fn:r562|562]]</sup> ). Substantial economic losses had resulted from droughts and floods across various parts of the globe due to teleconnections. For instance, direct losses of 10 billion USD (Sun and Miao, 2018 <sup>[[#fn:r563|563]]</sup> ; Yuan et al., 2018 <sup>[[#fn:r564|564]]</sup> ) and 6.5 billion USD (Christidis et al., 2018b <sup>[[#fn:r565|565]]</sup> ) were estimated to have been incurred from severe urban inundation in cities along the Yangtze River in China and the extreme drought in Thailand, respectively.

ENSO events affect TCs activity through variations in the low-level wind anomalies, vertical wind shear, mid-level relative humidity, steering flow, the monsoon trough and the western Pacific subtropical high in Asia (Yonekura and Hall, 2014 <sup>[[#fn:r566|566]]</sup> ; Zhang and Guan, 2014 <sup>[[#fn:r567|567]]</sup> ). The subsurface heat discharge due to El Niño can intensify TCs in the eastern Pacific (Jin et al., 2014 <sup>[[#fn:r568|568]]</sup> ; Moon et al., 2015b <sup>[[#fn:r569|569]]</sup> ). TCs are projected to become more frequent (~20–40%) during future-climate El Niño events compared with present climate El Niño events ( ''medium confidence'' ), and less frequent during future-climate La Niña events, around a group of small island nations (for example, Fiji, Vanuatu, Marshall Islands and Hawaii) in the Pacific (Chand et al., 2017 <sup>[[#fn:r570|570]]</sup> ). The Indian Ocean basin-wide warming has led to an increase in TC heat potential in the Indian Ocean over the last 30 years, however the link to the changes in the frequency of TCs is not robust (Rajeevan et al., 2013 <sup>[[#fn:r571|571]]</sup> ).

During the early stages of an extreme El Niño event (2015–2016 El Niño), there is an initial decrease in atmospheric CO 2 concentrations over the tropical Pacific Ocean, due to suppression of equatorial upwelling, reducing the supply of CO 2 to the surface (Chatterjee et al., 2017 <sup>[[#fn:r572|572]]</sup> ), followed by a rise in atmospheric CO 2 concentrations due reduced terrestrial CO 2 uptake and increased fire emissions (Bastos et al., 2018 <sup>[[#fn:r573|573]]</sup> ). It is not clear how a future increase in the frequency extreme events would modulate the carbon cycle on longer decadal time scales.

Studies on projections of changes in ENSO impacts or teleconnections are rather limited. Nevertheless, Power and Delage (2018) provide a multi-model assessment of CMIP5 models and their simulated changes in the precipitation response to El Niño in the future (Figure 6.6). They identify different combinations of changes that might further impact natural and human systems. El Niño causes either positive or negative precipitation anomalies in diverse regions of the globe. Dry El Niño teleconnection anomalies may be further strengthened by, either mean climate drying in the region (Amazon, Central America and Australia in June to August (JJA)), or a strengthening of the El Niño dry teleconnection, or both. Conversely, wet El Niño teleconnections can be further strengthened by either increases in mean precipitation (East Africa and southeastern South America in December to February (DJF)) or a strengthening of the El Niño wet teleconnection (southeastern South America in JJA), or both (Tibetan Plateau, DJF). However, a present day dry El Niño response may be dampened by a wet mean response (South, East and Southeast Asia in JJA) or a wet present day El Niño response may be weakened by a dry mean change (Southern Europe/Mediterranean and West Coast South America in JJA). Finally, changes in the mean and El Niño response may be in the opposite direction (Southeast Asia, JJA and Central North America, DJF). Such changes could have an impact on phenomena such as wildfires (Fasullo et al., 2018 <sup>[[#fn:r575|575]]</sup> ). However, in many other regions that are currently impacted by El Niño, e.g., regions of South America, studies have found no significant changes in the ENSO-precipitation relationship (Tedeschi and Collins, 2017 <sup>[[#fn:r576|576]]</sup> ) and agreement between models for many regions suggests ''low confidence'' in projections of teleconnection changes (Yeh et al., 2018 <sup>[[#fn:r577|577]]</sup> ).

Along with extreme El Niño events, abrupt warming in the Indian Ocean and extreme IOD events have largely altered the Asian and African monsoon, impacting the food and water security over these regions. As a response to rising global SSTs and partially due to extreme El Niño events, the NH summer monsoon showed substantial intensification during 1979–2011, with an increase in rainfall by 9.5% per degree Celsius of global warming (Wang et al., 2013 <sup>[[#fn:r578|578]]</sup> ). However, the Indian summer monsoon circulation and rainfall exhibits a statistically significant weakening since the 1950s. This weakening has been hypothesised to be a response to the Indian Ocean basin-wide warming (Mishra et al., 2012 <sup>[[#fn:r579|579]]</sup> ; Roxy et al., 2015 <sup>[[#fn:r580|580]]</sup> ) and also to increased aerosol emissions (Guo et al., 2016 <sup>[[#fn:r581|581]]</sup> ) and changes in land use (Paul et al., 2016 <sup>[[#fn:r582|582]]</sup> ). Warming in the north Indian Ocean has resulted in increasing fluctuations in the southwest monsoon winds and a three-fold increase in extreme rainfall events across central India (Roxy et al., 2017 <sup>[[#fn:r583|583]]</sup> ). The frequency and duration of heatwaves have increased over the Indian subcontinent, and these events are associated with the Indian Ocean basin-wide warming and frequent El Niños (Rohini et al., 2016 <sup>[[#fn:r584|584]]</sup> ). In April 2016, as a response to the extreme El Niño, Southeast Asia experienced surface air temperatures that surpassed national records, increased energy consumption, disrupted agriculture and resulted in severe human discomfort (Thirumalai et al., 2017 <sup>[[#fn:r585|585]]</sup> ). A strong negative IOD event in 2016 led to large climate impact on East African rainfall, with some regions recording below 50% of normal rainfall, leading to devastating drought, food insecurity and unsafe drinking water for over 15 million people in Somalia, Ethiopia and Kenya.

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'''Figure 6.6'''

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'''Figure 6.6 | Schematic figure indicating future changes in El Niño teleconnections based on the study of Power and Delage (2018). The background pattern of sea surface temperature (SST) anomalies (oC) are averaged from June 2015 to August 2015 (panel a) and December 2015 to February 2016 (panel b), during the most recent extreme El […]'''
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[[File:f08939c94162605d6103183bb40c3ccd IPCC-SROCC-CH_6_6.jpg]]

Figure 6.6 | Schematic figure indicating future changes in El Niño teleconnections based on the study of Power and Delage (2018) <sup>[[#fn:r589|589]]</sup> . The background pattern of sea surface temperature (SST) anomalies (oC) are averaged from June 2015 to August 2015 (panel a) and December 2015 to February 2016 (panel b), during the most recent extreme El Niño event (anomalies computed with respect to 1986–2005). Symbols indicate present day teleconnections for El Niño events. Black arrows indicate if there is a model consensus on change in mean rainfall in the region. Red arrows indicate if there is a model consensus on change in the rainfall anomaly under a future El Niño event. Direction of the arrow indicates whether the response in precipitation is increasing (up) or decreasing (down). Significance is determined when two-thirds or more of the models agree on the sign.

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