Editing IPCC:AR6/WGI/Chapter-8 (section)

==== 8.3.2.4 Monsoons ====

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The AR5 reported ''low confidence'' in the attribution of changes in monsoons to human influence, although a detailed attribution assessment of the observed changes in the regional monsoons was not presented.

Large human populations in the monsoon regions of the world heavily depend on freshwater supply for agriculture, water resources, industry, transport and various socio-economic activities. The effects of GHG forcing combined with water vapour feedback (R.J. [[#Allen--2015|]] [[#Allen--2015|Allen et al., 2015]] ; [[#Dong--2015|Dong and Sutton, 2015]] ; [[#Evan--2015|Evan et al., 2015]] ; [[#Dunning--2018|Dunning et al., 2018]] ) and cloud feedbacks ( [[#Stephens--2015|Stephens et al., 2015]] ; [[#Potter--2017|Potter et al., 2017]] ) are fundamental to monsoon precipitation changes in a warming world. Since AR5 there has been improved understanding of precipitation changes associated with regional monsoons. Sections 2.3.1.4.2 and 3.3.3.2 provide an assessment of observed changes and attribution for the global monsoon. Here we provide an assessment of the observed changes in regional monsoons (see [[IPCC:Wg1:Chapter:Annex-v|Annex V]] and Figure 8.11) and underlying causes. In AR6, the definition of regional monsoons slightly differs from AR5 and the rationale for it is provided in [[IPCC:Wg1:Chapter:Annex-v|Annex V]] (see Glossary). Specific examples of regional monsoons are discussed further in [[IPCC:Wg1:Chapter:Chapter-10#10.4.2|Section 10.4.2]] , from the perspective of climate change attribution and in [[IPCC:Wg1:Chapter:Chapter-10#10.6.3|Section 10.6.3]] , from the viewpoint of constructing regional climate messages.

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[[File:ae05328fe795c6cc346a35ff910aecd9 IPCC_AR6_WGI_Figure_8_11.png]]

Figure 8.11 | '''Regional monsoon precipitation changes from observations and model attribution.''' Precipitation changes during 1951–2014 are shown as least-square linear trends in box-whisker plots (first and fourth rows) over the six regional monsoons, for example, North American monsoon (NAmerM, July–August–September, JAS), West African monsoon (WAfriM, June–July–August–September, JJAS), South and South East Asian monsoon (SAsiaM, June–July–August–September, JJAS), East Asian monsoon (EAsiaM, June–July–August), South American monsoon (SAmerM, December–January–February, DJF), Australian and Maritime Continent monsoon (AusMCM, December–January–February, DJF), and over the two land domains, for example, equatorial America (EqAmer, June–July–August, JJA) and South Africa (SAfri, December–January–February, DJF), as identified in the map shown in the middle and as described in Annex V. Precipitation changes are computed from observations and from Detection and Attribution Model Intercomparison Project (DAMIP) CMIP6 experiments over the historical period with all-forcing (ALL), GHG-only forcing (labelled GHG), Aerosol-only (AER) and Natural (NAT) forcings prescribed. Observations are based on the CRU (light green) and GPCC (light blue) datasets and the APHRODITE (light orange) dataset for SAsiaM and EAsiaM. CMIP6 simulations are taken from nine CMIP6 models contributing to DAMIP, with at least three members. Ensembles are weight-averaged for the respective model ensemble size. Observed trends are shown as coloured circles and the simulated trends from the CMIP6 multi-model experiments are shown as box-whisker plots. Precipitation anomaly time-series are shown in the second and third row. The thick black line is the multi-model ensemble-mean precipitation anomaly time-series from the ALL experiment and the grey shading shows the spread across the multi-model ensembles. An 11-year running mean has been applied on the precipitation anomaly time-series prior to calculating the multi-model ensemble mean. Further details on data sources and processing are available in the chapter data table (Table 8.SM.1).

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===== 8.3.2.4.1 South and South East Asian Monsoon =====

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The AR5 reported a decreasing trend of global land monsoon precipitation over the last half-century, with primary contributions from the weakened summer monsoon systems in the Northern Hemisphere (NH). Since AR5, several studies have documented long-term variations and changes in the South and South East Asian summer monsoon (SAsiaM) rainfall. The SAsiaM strengthened during past periods of enhanced summer insolation in the NH, such as the early-to-mid Holocene warm period around 9000 to 6000 years before the present (BP) ( [[#Masson-Delmotte--2013|Masson-Delmotte et al., 2013]] ; [[#Mohtadi--2016|Mohtadi et al., 2016]] ; [[#Braconnot--2019|Braconnot et al., 2019]] ) and weakened during cold periods ( ''high confidence'' ), such as the Last Glacial Maximum (LGM) and Younger Dryas (Shakun et al. , 2007; Cheng et al. , 2012; Dutt et al. , 2015; Chandana et al. , 2018; Hong et al. , 2018; E. Zhang et al. , 2018). These long-time scale changes in monsoon intensity are tightly linked to orbital forcing and changes in high-latitude climate (Braconnot et al. , 2008; Battisti et al. , 2014; Araya-Melo et al. , 2015; Rachmayani et al. , 2016; Bosmans et al. , 2018; E. Zhang et al. , 2018). A weakening trend of the SAsiaM during the last 200 years has been documented based on tree ring oxygen isotope chronology from the northern Indian subcontinent ( [[#Xu--2018|Xu et al., 2018]] ) and South East Asia ( [[#Xu--2013|Xu et al., 2013]] ), oxygen isotopes in speleothems from northern India ( [[#Sinha--2015|Sinha et al., 2015]] ), and tree ring width chronologies from the Indian core monsoon region ( [[#Shi--2017|Shi et al., 2017]] ). Nevertheless, the detection of century-long decreases in regional monsoon rainfall is obscured by the presence of multi-decadal time scale precipitation variations ( [[#Turner--2012|Turner and Annamalai, 2012]] ; [[#Knutson--2018|Knutson and Zeng, 2018]] ) which are evident in long-term rain guage records extending back to the early 1800s ( [[#Sontakke--2008|Sontakke et al., 2008]] ) and emerge in long-term climate simulations ( [[#Braconnot--2019|Braconnot et al., 2019]] ).

A significant decline in summer monsoon precipitation is observed over India since the mid-20th century, which is accompanied by a weakening of the large-scale monsoon circulation (Mishra et al. , 2012; Abish et al. , 2013; Krishnan et al. , 2013, 2016; Saha et al. , 2014; Roxy et al. , 2015; Guhathakurta et al. , 2017; Samanta et al. , 2020). This precipitation decline is corroborated by a decreasing trend in the frequency of monsoon depressions that form over Bay of Bengal ( [[#Prajeesh--2013|Prajeesh et al., 2013]] ; [[#Vishnu--2016|Vishnu et al., 2016]] ), an increasing trend in the frequency and duration of monsoon breaks or ‘dry spells’ ( [[#Singh--2014|Singh et al., 2014]] ), significant decreases in soil moisture and increases in drought severity across different parts of India post-1950 (Niranjan Kumar et al. , 2013; Ramarao et al. , 2015, 2019; Krishnan et al. , 2016; Ganeshi et al. , 2020; Mujumdar et al. , 2020). While recent studies have reported an apparent recovery of the Indian summer monsoon over a relatively short period since 2003 ( [[#Jin--2017|Jin and Wang, 2017]] ; [[#Hari--2020|Hari et al., 2020]] ), long-term trends for the period 1951 – 2015 indicate an overall decrease in the regional monsoon precipitation ( [[#Kulkarni--2020|Kulkarni et al., 2020]] ; [[#Ayantika--2021|Ayantika et al., 2021]] ). A case study on the Indian summer monsoon is provided in [[IPCC:Wg1:Chapter:Chapter-10#10.6.3|Section 10.6.3]] .

Evidence from several climate modelling studies indicates that the observed decrease in the regional monsoon precipitation during the second half of the 20th century is dominated by the radiative effects of NH anthropogenic aerosols, with smaller contributions due to volcanic aerosols from the Mount Pinatubo (1991) and El Chichón (1982) eruptions (Bollasina et al. , 2011; Polson et al. , 2014; Sanap et al. , 2015; Krishnan et al. , 2016; Liu et al. , 2016; [[#Lau--2017|Lau and Kim, 2017]] ; Lin et al. , 2018; Takahashi et al. , 2018; Undorf et al. , 2018a, b; Patil et al. , 2019; M. Singh et al. , 2020; see Box 8.1, Figure 1 and Figure 8.11). Land-use changes over South and South East Asia and the rapid warming trend of the equatorial Indian Ocean during the recent few decades also appear to have contributed to the observed decrease in monsoon precipitation ( [[#Roxy--2015|Roxy et al., 2015]] ; [[#Krishnan--2016|Krishnan et al., 2016]] ; [[#Singh--2016|Singh, 2016]] ). Overall, the magnitude of the precipitation response to anthropogenic forcing exhibits large spread across CMIP5 models pointing to the strong internal variability of the regional monsoon ( [[#Saha--2014|Saha et al., 2014]] ; [[#Salzmann--2014|Salzmann et al., 2014]] ; [[#Sinha--2015|Sinha et al., 2015]] ), including variations linked to phase changes of the Pacific Decadal Variability (Section AVI.2.6; X. [[#Huang--2020|Huang et al., 2020]] a), uncertainties in representing aerosol – cloud interactions ( [[#Takahashi--2018|Takahashi et al., 2018]] ), and the effects of local compared with remote aerosol forcing (Bollasina et al. , 2014; Polson et al. , 2014; Undorf et al. , 2018b). CMIP3 and CMIP5 models do not accurately reproduce the observed seasonal cycle of precipitation over the major river basins of South and South East Asia, limiting the attribution of observed regional hydroclimatic changes ( [[#Hasson--2014|Hasson et al., 2014]] , 2016; [[#Biasutti--2019|Biasutti, 2019]] ). While warm rain processes and organized convection are known to dominate the heavy orographic monsoon rainfall over the Western Ghats mountains ( [[#Shige--2017|Shige et al., 2017]] ; [[#Choudhury--2018|Choudhury et al., 2018]] ), in various parts of India ( [[#Konwar--2012|Konwar et al., 2012]] ) and East Asia ( [[IPCC:Wg1:Chapter:Chapter-11#11.7.3.1|Section 11.7.3.1]] ), there are uncertainties in representing the regional physical processes of the monsoon environment, including cloud – aerosol interactions ( [[#Sarangi--2017|Sarangi et al., 2017]] ), land – atmosphere (e.g., Bartonet al., 2020) and ocean – atmosphere coupling ( [[#Annamalai--2017|Annamalai et al., 2017]] ), in state-of-the-art climate models (see also [[#8.5.1|Section 8.5.1]] ).

In summary, there is ''high confidence'' in observational evidence for a weakening of the SAsiaM in the second half of the 20th century. Results from climate models indicate that anthropogenic aerosol forcing has dominated the recent decrease in summer monsoon precipitation, as opposed to the expected intensification due to GHG forcing ( ''high confidence'' ). On paleoclimate time scales, the SAsiaM strengthened in response to enhanced summer warming in the NH during the early-to-mid Holocene, while it weakened during cold intervals ( ''high confidence'' ). These changes are tightly linked to orbital forcing and changes in high-latitude climate ( ''medium co'' ''nfidence'' ).

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===== 8.3.2.4.2 East Asian Monsoon =====

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The AR5 reported ''low confidence'' in the observed weakening of the East Asian monsoon (EAsiaM) since the mid-20th century. Since AR5, there has been improved understanding of changes in the EAsiaM, based on paleoclimatic evidence, instrumental observations and climate modeling simulations. Rainfall reconstructions from the Loess Plateau in China indicate that the northern extent of the monsoon rain belts migrated at least 300 km to the north-west from the LGM to the mid-Holocene ( [[#Yang--2015|Yang et al., 2015]] ). Similarly, Pliocene reconstructions indicate stronger intensity of the EAsiaM with a more northward penetration of the monsoon rain belt (S. [[#Yang--2018|]] [[#Yang--2018|Yang et al., 2018]] a). EAsiaM variability has been related to Atlantic Meridional Overturning Circulation (AMOC) dynamics, especially during the last glacial period, but whether the relationship is negative or positive remains uncertain ( [[#Sun--2012|Sun et al., 2012]] ; [[#Cheung--2018|Cheung et al., 2018]] ; [[#Kang--2018|Kang et al., 2018]] ).

Long-term precipitation observations from China indicate a trend of drying in the north and wetting in the central-eastern China along the Yangtze river valley since the 1950s ( [[#Qian--2014|Qian and Zhou, 2014]] ; [[#Zhou--2017b|Zhou et al., 2017b]] ; [[#Day--2018|Day et al., 2018]] ), with a weakened EAsiaM low-level circulation that penetrates less far into northern China, increased surface pressure over north-east China and southward shift of the jet stream ( [[#Song--2014|Song et al., 2014]] ). The southward shift and enhancement of the jet stream explains the increase of rainfall especially from the Meiyu front ( [[#Day--2018|Day et al., 2018]] ) at the expense of drying over north-east China.

Anthropogenic factors such as GHGs and aerosols had an influence on the EAsiaM changes (Figure 8.11; T. Wang et al. , 2013; Song et al. , 2014; Xie et al. , 2016; [[#Chen--2017|Chen and Sun, 2017]] ; Ma et al. , 2017; L. Zhang et al. , 2017; Day et al. , 2018; Tian et al. , 2018). Increased precipitation in the southern region has been linked to increased moisture flux convergence driven by GHG forcing while changes in anthropogenic aerosols have weakened the EAsiaM and reduced precipitation in the northern regions ( [[#Tian--2018|Tian et al., 2018]] ). Aerosol-induced cooling, associated atmospheric circulation changes and sea surface temperature (SST) feedbacks weaken the EAsiaM and favour the observed dry-north and wet-south pattern of rainfall anomalies (T. Wang et al. , 2013; Song et al. , 2014; L. Zhang et al. , 2017; G. Chen et al. , 2018; X. Chen et al. , 2018; Undorf et al., 2018b).

Internal variability and volcanic eruptions also contributed to the weakened EAsiaM (Hsu et al. , 2014; [[#Qian--2014|Qian and Zhou, 2014]] ; Zhou et al. , 2017a; [[#Knutson--2018|Knutson and Zeng, 2018]] ). Since the late 1970s, the EAsiaM weakening has been also linked to SST changes in the Pacific Ocean with warm conditions in the central-eastern tropical part and cold ones in the north, similar to a positive phase of the Pacific Decadal Variability (PDV; Section AVI.2.6; Z. Li et al. , 2016b; Zhou et al. , 2017a ). In the late 1990s the transition from a positive to a negative PDV has been associated with the recent recovery observed in the EAsiaM strength ( [[#Zhou--2017a|Zhou et al., 2017a]] ). Atlantic Multi-decadal Variability (AMV) also has an influence on the EAsiaM via the global teleconnection pattern propagating from the North Atlantic through the westerly jet ( [[#Zuo--2013|Zuo et al., 2013]] ; [[#Wu--2016a|Wu et al., 2016a]] , b). This North Atlantic influence has contributed to the increase of precipitation over the Huaihe-Huanghe valley since the late 1990s (Y. [[#Li--2017|]] [[#Li--2017|]] [[#Li--2017|]] [[#Li--2017|Li et al., 2017]] ). When PDV and AMV are in opposite phase, the former has a larger influence in driving the southern flooding and northern drought pattern over the region (Q. [[#Yang--2017|]] [[#Yang--2017|Yang et al., 2017]] ).

In summary, there is strong evidence of a stronger EAsiaM and northward migration of the rainbelt during warmer climates based on paleoclimate reconstructions. There is ''high confidence'' that anthropogenic forcing has been influencing historical EAsiaM changes with drying in the north and wetting in the south observed since the 1950s, but there is ''low confidence'' in the magnitude of the anthropogenic influence. The transition towards a positive PDV phase has been one of the main drivers of the EAsiaM weakening since the 1970s ( ''high co'' ''nfidence'' ).

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===== 8.3.2.4.3 West African Monsoon =====

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Since AR5, there has been improved understanding of the West African monsoon (WAfriM) response to natural and anthropogenic forcing. On paleoclimate time scales, enhanced summer insolation in the Northern Hemisphere (NH) intensified the WAfriM precipitation during the early-to-mid Holocene ( ''high confidence'' ), as seen in rainfall proxy records and climate model simulations (Masson-Delmotte et al. , 2013; Mohtadi et al. , 2016; Braconnot et al. , 2019). Despite improvements in model simulations of the present-day monsoons, CMIP5 and CMIP6 models underestimate mid-Holocene changes in the amount and spatial extent of the WAfriM precipitation ( [[IPCC:Wg1:Chapter:Chapter-3#3.3.3.2|Section 3.3.3.2]] ; [[#Brierley--2020|Brierley et al., 2020]] ).

During the recent past, long-term rain gauge observations display substantial variability in the WAfriM precipitation over the 20th century ( [[IPCC:Wg1:Chapter:Chapter-10#10.4.2.1|Section 10.4.2.1]] ). The WAfriM experienced the wettest decade of the 20th century during the 1950s and early 1960s ( ''high confidence'' ), over much of the western and central Sahel region, followed abruptly by the driest years during 1970 – 1989 ( [[#Ali--2009|Ali and Lebel, 2009]] ; [[#Nicholson--2013|Nicholson, 2013]] ; [[#Descroix--2015|Descroix et al., 2015]] ). The percentage deficit in the annual rainfall during 1970–1989, relative to the long-term mean, ranged from 60% in the north of Sahel to 25 – 30% in the south ( [[#Le%20Barbé--2002|Le Barbé et al., 2002]] ; [[#Lebel--2003|Lebel et al., 2003]] ). The long decline in annual rainfall is related to a decrease of rain occurrence over the Sahel ( [[#Le%20Barbé--1997|Le Barbé and Lebel, 1997]] ; [[#Frappart--2009|Frappart et al., 2009]] ; [[#Bodian--2016|Bodian et al., 2016]] ) and the Soudano-Guinean sub-region of West Africa ( [[#Le%20Barbé--2002|Le Barbé et al., 2002]] ), even though the interannual variability pattern is more complex ( [[#Balme--2006|Balme et al., 2006]] ). Decrease of rainfall occurrences resulted from decreases in large convective events in the core of the rainy season ( [[#Bell--2006|Bell et al., 2006]] ), that modulate interannual variability of the WAfriM ( [[#Panthou--2018|Panthou et al., 2018]] ).

Wetter conditions of the WAfriM prevailed later from the mid-to-late 1990s, although the positive trend in precipitation started since the late 1980s (see also [[IPCC:Wg1:Chapter:Chapter-10#10.4.2.1|Section 10.4.2.1]] ) over the Sahel ( ''high confidence'' ) and in the Guinean coastal region ( ''medium confidence'' ), indicating the geographical variation in the wetting recovery (Descroix et al. , 2015; Sanogo et al. , 2015; Bodian et al. , 2016; Nicholson et al. , 2018). While the interannual and decadal variability of annual rainfall is not homogeneous over the entire Sahel, the rainfall recovery was stronger in the east than in the west of the region ( [[IPCC:Wg1:Chapter:Chapter-10#10.4.2.1|Section 10.4.2.1]] ; [[#Nicholson--2018|Nicholson et al., 2018]] ). A shift in the seasonality of the Sahelian rainfall, including delayed cessation has also been reported ( [[IPCC:Wg1:Chapter:Chapter-10#10.4.2.1|Section 10.4.2.1]] ; [[#Nicholson--2013|Nicholson, 2013]] ; [[#Dunning--2018|Dunning et al., 2018]] ).

In the Sahel region, the emergence of this new rainfall regime is reflected in increased number of heavy and extreme events, compared to the 1970s – 1980s, still not exceeding the values registered in the 1950s to 1960s ( [[#Descroix--2013|Descroix et al., 2013]] , 2015; [[#Panthou--2014|Panthou et al., 2014]] , 2018; [[#Sanogo--2015|Sanogo et al., 2015]] ), and in higher interannual variability (W. [[#Zhang--2017|Zhang et al., 2017]] b; [[#Akinsanola--2020|Akinsanola and Zhou, 2020]] ) associated with SST variations in the tropical Atlantic, Pacific and Mediterranean Sea ( [[#Rodríguez-Fonseca--2015|Rodríguez-Fonseca et al., 2015]] ; [[#Diakhaté--2019|Diakhaté et al., 2019]] ). Increased frequency of extreme rainfall events impacts high flow occurrences of the large Sahelian rivers as well as small to meso-scale catchments ( [[#Wilcox--2018|Wilcox et al., 2018]] ). Overall, extreme intense precipitation events are more frequent in the Sahel since the beginning of the 21st century (Giannini et al. , 2013; Panthou et al. , 2014, 2018; Sanogo et al. , 2015; Taylor et al. , 2017). Intensification of mesoscale convective systems associated with extreme rainfall in the WAfriM is favoured by enhancement of meridional temperature gradient by the warming of the Sahara desert ( [[#Taylor--2017|Taylor et al., 2017]] ) at a pace that is two to four times greater than that of the tropical-mean temperature (K.H. [[#Cook--2015|]] [[#Cook--2015|]] [[#Cook--2015|Cook et al., 2015]] ; [[#Vizy--2017|Vizy et al., 2017]] ). Periods of monsoon-breaks and the persistence of low rainfall events are still prominent, particularly after the onset, thus exposing West Africa simultaneously to the potential impacts of dry spells (W. [[#Zhang--2017|Zhang et al., 2017]] b) and also extreme localized rains and floods ( [[#Engel--2017|Engel et al., 2017]] ; [[#Lafore--2017|Lafore et al., 2017]] ). Occurrence of extreme events is compounded by land use and land cover changes leading to increased runoff ( [[#Bamba--2015|Bamba et al., 2015]] ; [[#Descroix--2018|Descroix et al., 2018]] ).

The Sahel drought from the 1970s until the early 1990s was related to anthropogenic emissions of sulphate aerosols in the Atlantic, which led to an inter-hemispheric pattern of SST anomalies and associated regional precipitation changes (Section 6.3.3.2 and Box 8.1). Also the combined effects of anthropogenic aerosols and GHG forcing appear to have contributed to the late twentieth century drying of the Sahel through their effect on SST, by cooling the North Atlantic and warming the tropical oceans ( [[#Giannini--2019|Giannini and Kaplan, 2019]] ; [[#Hirasawa--2020|Hirasawa et al., 2020]] ). Subsequent aerosol removal led to SST warming of the North Atlantic, shifting the ITCZ further northward and strengthening the WAfriM ( [[#Giannini--2019|Giannini and Kaplan, 2019]] ). The recent recovery has been ascribed to prevailing positive SST anomalies in the tropical North Atlantic potentially associated with a positive phase of the Atlantic Multi-decadal Oscillation ( [[#Diatta--2014|Diatta and Fink, 2014]] ; [[#Rodríguez-Fonseca--2015|Rodríguez-Fonseca et al., 2015]] ). The Sahel rainfall recovery has also been attributed to higher levels of GHG in the atmosphere and increases in atmospheric temperature ( [[#Dong--2015|Dong and Sutton, 2015]] ).

In summary, most regions of West Africa experienced a wet period in the mid-20th century followed by a very dry period in the 1970s and 1980s that is attributed to aerosol cooling of the NH ( ''high confidence'' ). Recent estimates provide evidence of a WAfriM recovery from the mid-to-late 1990s, with more intense extreme events partly due to the combined effects of increasing GHG and decreasing anthropogenic aerosols over Europe and North America ( ''high confidence'' ). On paleoclimate time scales, there is ''high confidence'' that the WAfriM strengthened during the early-to-mid Holocene in response to orbitally-forced enhancement of summer warming in the NH.

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===== 8.3.2.4.4 North American Monsoon =====

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Since AR5, there have been updates on the observed long-term variations and changes in the North American monsoon (NAmerM). During the Last Glacial Maximum (LGM; 21,000 – 19,000 years ago), the NAmerM was substantially weaker due to cold, dry mid-latitude air associated with the Laurentide Ice Sheet ( T. Bhattacharya et al. , 2017, 2018 ). The NAmerM strengthened until the mid-Holocene period, in response to ice-emsheet retreat and rising summer insolation, but probably did not exceed the strength of the modern system ( ''low confidence'' ), as indicated by model simulations ( [[#Metcalfe--2015|Metcalfe et al., 2015]] ) and paleoclimatic reconstructions ( [[#Bhattacharya--2018|Bhattacharya et al., 2018]] ). Paleoclimatic evidence from proxy datasets and mid-Pliocene (PlioMIP1) simulations suggest a wetter south-western USA during that warmer period (A.M. [[#Haywood--2013|]] [[#Haywood--2013|Haywood et al., 2013]] ; [[#Pound--2014|Pound et al., 2014]] ; [[#Ibarra--2018|Ibarra et al., 2018]] ) but it is not clear whether this is due to increases of precipitation associated with the monsoon or occurring during the winter season.

During 1948 – 2010, trends of boreal summer precipitation amount were significantly positive over New Mexico and the core NAmerM region, but significantly negative over south-western Mexico ( [[#Hoell--2016|Hoell et al., 2016]] ). In addition, diverse datasets like CRU, CHIRPS and GPCP show significant decreases of precipitation in parts of the south-western USA and north-western Mexico, including the NAmerM region ( [[#Cavazos--2020|Cavazos et al., 2020]] ; [[#Ashfaq--2021|Ashfaq et al., 2021]] ). Other studies suggest a strengthening of the NAmerM upper level anticyclone since the mid-1970s, with a more frequent northward location ( [[#Diem--2013|Diem et al., 2013]] ). Between 1910 – 2010, the number of precipitation events increased across the northern Chihuahuan desert, within the NAmerM domain, despite a decrease in their magnitude, and the length of extreme dry and wet periods also increased ( [[#Petrie--2014|Petrie et al., 2014]] ).

An increase in intense rainfall and severe weather events has been observed in several locations, especially in south-western Arizona since 1991, resulting from increases in atmospheric moisture content and instability; a change that has been confirmed by convective-permitting model simulations ( [[#Luong--2017|Luong et al., 2017]] ; [[#Pascale--2019|Pascale et al., 2019]] ). A dense network of 59 rain gauges located in south-eastern Arizona suggests an intensification of monsoon sub-daily rainfall since the mid-1970s ( [[#Demaria--2019|Demaria et al., 2019]] ), as expected by a stronger global warming signature for sub-daily rather than daily or monthly precipitation accumulation ( [[IPCC:Wg1:Chapter:Chapter-11#11.4|Section 11.4]] ). [[IPCC:Wg1:Chapter:Chapter-10#10.4.2.3|Section 10.4.2.3]] provides further details on changes in precipitation in south-western North America. Evidence from multiple reanalyses suggests that increases in NAmerM rainfall have contributed to the increasing trend of global monsoon precipitation ( [[IPCC:Wg1:Chapter:Chapter-2#2.3.1.4.2|Section 2.3.1.4.2]] ; [[#Lin--2014|Lin et al., 2014]] ). In addition, more frequent occurrence of earlier retreats of the NAmerM since 1979 is documented ( [[#Arias--2012|Arias et al., 2012]] , 2015), in association with the positive phase of the Atlantic Multi-decadal Variability (AMV) and a westward expansion of the North Atlantic Subtropical High (W. [[#Li--2011|Li et al., 2011]] , 2012).

Analyses from a 50-km resolution GCM indicate that the NAmerM response to CO <sub>2</sub> is very sensitive to SST biases, showing reductions in summer NAmerM precipitation with increased CO <sub>2</sub> when the SST biases are small ( [[#Pascale--2017|Pascale et al., 2017]] ) in contrast to CMIP5 models ( [[#Cook--2013|Cook and Seager, 2013]] ; [[#Maloney--2014|Maloney et al., 2014]] ; [[#Torres-Alavez--2014|Torres-Alavez et al., 2014]] ; [[#Hoell--2016|Hoell et al., 2016]] ). The NAmerM has been shown to be also sensitive to sulphur dioxide (SO <sub>2</sub> ) emissions ( [[#García-Martínez--2020|García-Martínez et al., 2020]] ).

In summary, both paleoclimate evidence and observations indicate an intensification of the NAmerM in a warmer climate ( ''medium confidence'' ). The intensification recorded since about the 1970s has been partly driven by GHG emissions ( ''medium con'' ''fidence'' ).

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<span id="south-american-monsoon"></span>
===== 8.3.2.4.5 South American Monsoon =====

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Since AR5, there has been improved understanding of changes in the South American monsoon (SAmerM) as evidenced from paleoclimate records, instrumental observations and climate model simulations. However, general circulation models (GCMs) still exhibit difficulties in reproducing SAmerM precipitation amount ( [[#Rojas--2016|Rojas et al., 2016]] ; [[#D’Agostino--2020b|D’Agostino et al., 2020b]] ). Paleoclimate evidence suggests a relatively stronger SAmerM during the 1400–1600 period (Bird et al. , 2011b; Vuille et al. , 2012; Ledru et al. , 2013; Apaéstegui et al. , 2014; Novello et al. , 2016; Wortham et al. , 2017). Last millennium GCM simulations are able to reproduce stronger SAmerM during the 1400–1600 period in comparison with warmer epochs such as the 900–1100 period (Rojas et al., 2016) or the current warming period (Díaz and Vera, 2018). PMIP3/CMIP5 simulations indicate a consistent weaker SAmerM during the mid-Holocene (6000 years ago; see Cross-Chapter Box 2.1) in comparison to current conditions (Bird et al., 2011a; [[#Mollier-Vogel--2013|Mollier-Vogel et al., 2013]] ; [[#Prado--2013a|Prado et al., 2013a]] ; [[#D’Agostino--2020b|D’Agostino et al., 2020b]] ), thus favouring savannah/grassland-like vegetation (Smith and Mayle, 2018), in agreement with climate reconstructions from different proxies (Prado et al., 2013b). Signals of weak and strong SAmerM during mid-Holocene and LGM, respectively, are evident also in high-resolution long-term (i.e., more than about 22,000 years) rainfall reconstructions based on oxygen isotopes in speleothems from Brazil (Novello et al. , 2017; Stríkis et al. , 2018; Campos et al., 2019).

Isotope records from caves in the central Peruvian Andes show that the late Holocene (&lt;3000 years ago) was characterized by multi-decadal and centennial-scale periods of significant decline in intensity of the SAmerM ( [[#Bird--2011a|Bird et al., 2011a]] ; [[#Vuille--2012|Vuille et al., 2012]] ). This could be partly due to a reduction in the zonal SST gradient of the Pacific Ocean, favouring El Niño-like conditions (Kanner et al., 2013). Other studies suggest increased SAmerM precipitation amount during the Late Holocene, in association with the expansion of the tropical forest (Smith and Mayle, 2018). Well-dated equilibrium lines of glaciers during the deglaciation suggest that the AMOC enhances Atlantic moisture sources and precipitation amount increase over the tropical and southern Andes ( [[#Beniston--2018|Beniston et al., 2018]] ).

Observations during 1979 – 2014 suggest that poleward shifts in the South Atlantic Convergence Zone (SACZ) noted in recent decades ( [[#Talento--2018|Talento and Barreiro, 2018]] ; [[#Zilli--2019|Zilli et al., 2019]] ), are associated with precipitation amount decrease along the equatorward margin and increase along the poleward margin of the convergenze zone ( [[#Zilli--2019|Zilli et al., 2019]] ). Several observational studies identified delayed onsets of the SAmerM after 1978 related to longer dry seasons in the southern Amazon (Fu et al. , 2013; Yin et al. , 2014; Arias et al. , 2015; Debortoli et al. , 2015; Arvor et al. , 2017; Giráldez et al. , 2020; Haghtalab et al. , 2020; Correa et al. , 2021). In contrast, other studies indicate a trend toward earlier onsets of the SAmerM ( [[#Jones--2013|Jones and Carvalho, 2013]] ). These discrepancies are explained by the methodology used and the domain considered for the SAmerM, confirming the occurrence of delayed onsets of the SAmerM since 1978 ( [[#Correa--2021|Correa et al., 2021]] ). CMIP5 simulations show trends toward delayed onsets of the SAmerM in association with anthropogenic forcing, although the simulated trends underestimate the observed trends ( [[#Fu--2013|Fu et al., 2013]] ). Total rainfall reductions are observed in the southern Amazon during September – October – November after 1978 ( [[#Fu--2013|Fu et al., 2013]] ; [[#Bonini--2014|Bonini et al., 2014]] ; [[#Debortoli--2015|Debortoli et al., 2015]] , 2016; [[#Espinoza--2019|Espinoza et al., 2019]] ), consistent with reductions in river discharge in the region (Molina-Carpio et al. , 2017; Espinoza et al. , 2019; Heerspink et al., 2020).

Significant increases in precipitation have been observed over south-eastern Brazil during 1902 – 2005 while non-significant decreases have been found over central Brazil (Vera andDíaz, 2015). In Bolivia, increases were observed during 1965 – 1984, while reductions have occurred since then ( [[#Seiler--2013|Seiler et al., 2013]] ). However, the Peruvian Amazon does not reveal significant changes in mean rainfall during 1965–2007 ( [[#Lavado--2013|Lavado et al., 2013]] ; [[#Ronchail--2018|Ronchail et al., 2018]] ). Historical simulations from CMIP5 ensembles adequately capture the observed summer precipitation amount over central and south-eastern Brazil, thereby providing ''high confidence'' in interpreting the observed variability of SAmerM for the period 1960 – 1999 ( [[#Gulizia--2015|Gulizia and Camilloni, 2015]] ; [[#Pascale--2019|Pascale et al., 2019]] ). Also, CMIP5 simulations indicate that the anthropogenic forcing associated with increased GHG emissions is necessary to explain the positive trends in upper-troposphere zonal winds observed over the South American Altiplano ( [[#Vera--2019|Vera et al., 2019]] ). However, the detection of anthropogenically-induced signals for precipitation is still ambiguous in monsoon regions, like the SAmerM ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ).

In summary, there is ''high confidence'' that the SAmerM onset has been delayed since the late 1970s. This is reproduced by CMIP5 simulations that consider anthropogenic forcing. There is also ''high confidence'' that precipitation during the dry-to-wet transition season has been reduced over the southern Amazon. Paleoclimate reconstructions and simulations suggest a weaker SAmerM during warmer epochs such as the Mid-Holocene or the 900–1100 period, and stronger monsoon during colder epochs such as the LGM or the 1400–1600 period ( ''high con'' ''fidence'' ).

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===== 8.3.2.4.6 Australian and Maritime Continent Monsoon =====

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Since AR5, several studies have examined observed variability and changes in the Australian and Maritime Continent monsoon (AusMCM) using paleoclimate records, instrumental observations and modeling studies ( [[#Denniston--2016|Denniston et al., 2016]] ; [[#Zhang--2016|Zhang and Moise, 2016]] ). Paleoclimate reconstructions and modelling indicate that the Indo–Australian monsoon may vary in or out of phase with the EAsiaM, depending on whether there is a meridional displacement or expansion of the tropical rainfall belt ( [[#Ayliffe--2013|Ayliffe et al., 2013]] ; [[#Denniston--2016|Denniston et al., 2016]] ). For instance, mid-Holocene simulations suggest that the AusMCM weakens and contracts due to a decreased net energy input and a weaker dynamic component ( [[#D’Agostino--2020b|D’Agostino et al., 2020b]] ).

Rainfall increases have been observed over northern Australia since the 1950s, with most of the increases occurring in the north-west ( [[#Dey--2019a|Dey et al., 2019a]] , b; [[#Dai--2021|Dai, 2021]] ) and decreases observed in the north-east (J. [[#Li--2012|]] [[#Li--2012|Li et al., 2012]] ) since the 1970s. There is also a trend towards more intense convective rainfall from thunderstorms over northern Australia ( [[#Dowdy--2020|Dowdy, 2020]] ). There is no consensus on the cause of the observed Australian monsoon rainfall trends, with some studies suggesting changes are due to altered circulation driving increased moisture transport or increased frequency of the wettest synoptic regimes ( [[#Catto--2012|Catto et al., 2012]] ; [[#Clark--2018|Clark et al., 2018]] ). Other studies find that model simulations that include anthopogenic aerosols ( [[#Rotstayn--2012|Rotstayn et al., 2012]] ; [[#Dey--2019a|Dey et al., 2019a]] ) are better able to capture observed Australian monsoon rainfall trends than simulations with natural or GHG forcing only ( [[#Knutson--2018|Knutson and Zeng, 2018]] ).

The Maritime Continent (MC) experiences the influence of both the Asian and the Australian monsoons, with rainfall peaking during boreal winter/austral summer ( [[#Robertson--2011|Robertson et al., 2011]] ). Reductions in land rainfall and marine cloudiness over the MC and weakening of surface moisture flux convergence have been observed in the period 1950 – 1999 (Tokinaga et al., 2012; [[#Yoden--2017|Yoden et al., 2017]] ). These trends are indicative of a slowdown of the Walker Circulation, with positive sea level pressure trends over the MC and negative trends over the central equatorial Pacific (Tokinaga et al., 2012). More recently (1981 – 2014), a trend of increasing annual rainfall over large areas of the MC has been identified (Hassim and Timbal, 2019). Given the large variability in MC rainfall on interannual time scales, the choice of time period may influence the calculated rainfall trend (Hassim and Timbal, 2019).

During 1951 – 2007 daily rainfall extremes did not increase over the MC, in contrast to the rest of South East Asia ( [[IPCC:Wg1:Chapter:Chapter-11#11.4.2|Section 11.4.2]] ; [[#Villafuerte--2015|Villafuerte and Matsumoto, 2015]] ). Rainfall extremes in Indonesia increased in austral summer, as evidenced from station weather observations for the period 1983 – 2012 (Supari et al., 2018).

In summary, notable rainfall increases have been observed in parts of northern Australia since the 1970s, although there is ''low confidence'' in the human contribution to these changes. Rainfall changes have been observed over the MC region but there is ''low confidence'' in the identification of trends because of large variability at interannual time scales.

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