Editing IPCC:AR6/WGI/Chapter-11 (section)

=== 11.1.7 Global-scale Synthesis ===

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Tables 11.1 and 11.2 provide a synthesis for observed and attributed changes in extremes, and projected changes in extremes, respectively, at different levels of global warming. This synthesis assessment focuses on the assessed range of observed and projected changes. In this chapter, the assessed ''likely'' range in a projection typically corresponds to the 90% range of the multi-model ensemble spread to take into account other sources of uncertainty, unless stated otherwise. Some low-likelihood, high-impact scenarios that can be of high relevance are addressed in Box 11.2.

Building on the assessments from Tables 11.1 and 11.2, Figure 11.5 provides a synthesis on the level of confidence in the attribution and projection of changes in extremes. In the case where the signal in the observations is still relatively weak but the physical processes underlying the changes in extremes in response to human forcing are well understood, confidence in the projections would be higher than in the attribution because of strengthening in the signal with warming. But, when the observed signal is already strong and when observational evidence is consistent with model simulated responses, confidence in the projection may be lower than that in attribution if certain physical processes could be expected to behave differently in a much warmer world and under much higher greenhouse gas forcing, and in particular if such a behaviour is poorly understood.

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[[File:a5ba7c3af5ed593cda01d747d3b2d896 IPCC_AR6_WGI_Figure_11_5.png]]

'''Figure 11.5 |''' '''confidence and likelihood of past changes and projected future changes at 2°C of global warming on the global scale.''' The information in this figure is based on Tables 11.1 and 11.2.

Further synthesis for regional assessments are provided in Figure 11.4 (event attribution), Figure 11.6 (projected change in hot temperature extremes) and Figure 11.7 (projected changes in precipitation extremes). A synthesis on regional assessments for observed, attributed and projected changes in extremes is provided in [[#11.9|Section 11.9]] for all AR6 reference regions (see [[IPCC:Wg1:Chapter:Chapter-1#1.4.5|Section 1.4.5]] and Figures 1.18 and Atlas.2 for definitions of AR6 regions).

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[[File:86a62770ec72d8bc8bed568c837492f8 IPCC_AR6_WGI_Figure_11_6.png]]

'''Figure 11.6 |''' '''Projected changes in the frequency of extreme temperature events under 1°C, 1.5°C, 2°C, 3°C, and 4°C global warming levels relative to the 18''' ''50–1900 baseline.'' Extreme temperatures are defined as the maximum daily temperatures that were exceeded on average once during a 10-year period (10-year event, blue) and once during a 50-year period (50-year event, orange) during the 1850–1900 base period. Results are shown for the global land area and the AR6 regions. For each box plot, the horizontal line and the box represent the median and central 66% uncertainty range, respectively, of the frequency changes across the multi-model ensemble, and the ‘whiskers’ extend to the 90% uncertainty range. The dotted line indicates no change in frequency. The results are based on the multi-model ensemble from simulations of global climate models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6) under different Shared Socio-economic Pathway forcing scenarios. Adapted from [[#Li--2021|Li et al. (2021)]] . Further details on data sources and processing are available in the chapter data table (Table 11.SM.9).

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[[File:1726f3bc034390a6043692705fb27ecd IPCC_AR6_WGI_Figure_11_7.png]]

'''Figure 11.7 |''' '''Projected changes in the frequency of extreme precipitation events under 1°C, 1.5°C, 2°C, 3°C, and 4°C global warming levels relative to the 1850''' ''–19'' ''0'' ''0 baseline.'' Extreme precipitation is defined as the annual maximum daily precipitation (Rx1day) that was exceeded on average once during a 10-year period (10-year event, blue) and once during a 50-year period (50-year event, orange) during the 1850–1900 base period. Results are shown for the global land area and the AR6 regions. For each box plot, the horizontal line and the box represent the median and central 66% uncertainty range, respectively, of the frequency changes across the multi-model ensemble, and the ‘whiskers’ extend to the 90% uncertainty range. The dotted line indicates no change in frequency. The results are based on the multi-model ensemble from simulations of global climate models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6) under different Shared Socio-economic Pathway forcing scenarios. Adapted from [[#Li--2021|Li et al. (2021)]] . Further details on data sources and processing are available in the chapter data table (Table 11.SM.9).

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'''Table 11.1 |''' '''Synthesis table on observed changes in extremes and contribution by human influence.''' Note that observed changes in marine extremes are assessed in Cross-Chapter Box 9.1.

{| class="wikitable"
|-
! Phenomenon and Direction of Trend

! Observed/Detected Trends Since 1950 (for +0.5°C global warming or higher)

! Human Contribution to the Observed Trends Since 1950 (for +0.5°C global warming or higher)

|-
| Warmer and/or more frequent hot days and nights over most land areas

Warmer and/or fewer cold days and nights over most land areas

Warm spells/heatwaves: increases in frequency or intensity over most land areas

Cold spells/cold waves: decreases in frequency or intensity over most land areas

| ''Virtually certain'' on global scale {11.3}

'''Continental-scale evidence:'''

Asia, Australasia, Europe, North America: ''Very likely''

Central and South America: ''High confidence''

Africa: ''Medium confidence''

{11.3, 11.9}

| ''Extremely likely'' main contributor on global scale {11.3}

'''Continental-scale evidence:'''

North America, Europe, Australasia, Asia: ''Very likely''

Central and South America: ''High confidence''

Africa: ''Medium confidence''

{11.3, 11.9}

|-
| Heavy precipitation events: increase in the frequency, intensity, and/or amount of heavy precipitation

| ''Likely'' on global scale, over majority of land regions with good observational coverage {11.3}

'''Continental-scale evidence:'''

Asia, Europe, North America: ''Likely''

Africa, Australasia, Central and South America: ''Low confidence''

{11.3, 11.9}

| ''Likely'' main contributor to the observed intensification of heavy precipitation in land regions on global scale.

{11.3}

'''Continental-scale evidence:'''

Asia, Europe, North America: ''Likely''

Africa, Australasia, Central and South America: ''Low confidence''

{11.3, 11.9}

|-
| Increases in agricultural and ecological drought events

| ''Medium confidence'' some regions {11.6, 11.9}

Increasing trends in agricultural and ecological droughts have been observed in AR6 regions on all continents ( ''medium confidence'' ) {11.6, 11.9}

| ''Medium confidence'' some regions

{11.6, 11.9}

|-
| Increase in precipitation associated with tropical cyclones (TCs)

| ''Medium confidence''

{11.7}

| ''High confidence''

{11.7}

|-
| Increase in likelihood that a TC will be at major TC intensity (Cat. 3–5)

| ''Likely''

{11.7}

| ''Medium confidence''

{11.7}

|-
| Changes in frequency of rapidly intensifying tropical cyclones

| ''Likely''

{11.7}

| ''Medium confidence''

{11.7}

|-
| Poleward migration of tropical cyclones in the western Pacific

| ''Medium confidence''

{11.7}

| ''Medium confidence''

{11.7}

|-
| Decrease in TC forward motion over the USA

| It is ''likely'' that TC translation speed has slowed over the USA since 1900.

{11.7}

| It is ''more likely than not'' that the slowdown of TC translation speed over the USA has contributions from anthropogenic forcing.

{11.7}

|-
| Severe convective storms (tornadoes, hail, rainfall, wind, lightning)

| ''Low confidence'' in past trends in hail and winds and tornado activity due to short length of high-quality data records. {11.7}

| ''Low confidence''

{11.7}

|-
| Increase in compound events

| ''Likely'' increase in the probability of compound events.

''High confidence'' that concurrent heatwaves and droughts are becoming more frequent under enhanced greenhouse gas forcing at global scale.

''Medium confidence'' that fire weather, i.e. compound hot, dry and windy events, have become more frequent in some regions.

''Medium confidence'' that compound flooding risk has increased in some locations.

{11.8}

| ''Likely'' that human-induced climate change has increased the probability of compound events.

''High confidence'' that human influence has increased the frequency of concurrent heatwaves and droughts.

''Medium confidence'' that human influence has increased fire weather occurrence in some regions.

''Low confidence'' that human influence has contributed to changes in compound events leading to flooding.

{11.8}

|}

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'''Table 11.2 |''' '''Synthesis table on projected changes in extremes.''' Note that projected changes in marine extremes are assessed in [[IPCC:Wg1:Chapter:Chapter-9|Chapter 9]] and Cross-Chapter Box 9.1 (marine heatwaves). Assessments are provided compared to pre-industrial conditions.

{| class="wikitable"
|-
! Phenomenon and Direction of Trend

! Projected Changes at +1.5ºC Global Warming

! Projected Changes at +2°C Global Warming

! Projected Changes at +4°C Global Warming

|-
| Warmer and/or more frequent hot days and nights over most land areas

Warmer and/or fewer cold days and nights over most land areas

Warm spells/heatwaves; increases in frequency or intensity over most land areas

Cold spells/cold waves: decreases in frequency or intensity over most land areas

| ''Virtually certain'' on global scale

''Extremely likely'' on all continents

Highest increase of temperature of hottest days is projected in some mid-latitude and semi-arid regions, and the South American Monsoon region, at about 1.5 times to twice the rate of global warming ( ''high confidence'' ) {11.3, Figure 11.3}

Highest increase of temperature of coldest days is projected in Arctic regions, at about three times the rate of global warming ( ''high confidence'' ) {11.3}

'''Continental-scale projections:'''

''Extremely likely'' : Africa, Asia, Australasia, Central and South America, Europe, North America

{11.3, 11.9}

| ''Virtually certain'' on global scale

''Virtually certain'' on all continents

Highest increase of temperature of hottest days is projected in some mid-latitude and semi-arid regions, and the South American Monsoon region, at about 1.5 times to twice the rate of global warming ( ''high confidence'' ) {11.3, Figure 11.3}

Highest increase of temperature of coldest days is projected in Arctic regions, at about three times the rate of global warming ( ''high confidence'' ) {11.3}

'''Continental-scale projections:'''

''Virtually certain:'' Africa, Asia, Australasia, Central and South America, Europe, North America

{11.3, 11.9}

| ''Virtually certain'' on global scale

''Virtually certain'' on all continents

Highest increase of temperature of hottest days is projected in some mid-latitude and semi-arid regions, and the South American Monsoon region, at about 1.5 times to twice the rate of global warming ( ''high confidence'' ) {11.3, Figure 11.3}

Highest increase of temperature of coldest days is projected in Arctic regions, at about three times the rate of global warming ( ''high confidence'' ) {11.3}

'''Continental-scale projections:'''

''Virtually certain:'' Africa, Asia, Australasia, Central and South America, Europe, North America

{11.3, 11.9}

|-
| Heavy precipitation events: increase in the frequency, intensity, and/or amount of heavy precipitation

| ''High confidence'' that increases take place in most land regions {11.4}

''Very likely :'' Asia, North America

''Likely:'' Africa, Europe

''High confidence:'' Central and South America

''Medium confidence:'' Australasia

{11.4, 11.9}

| ''Likely'' that increases take place in most land regions {11.4}

''Extremely likely :'' Asia, North America

''Very likely :'' Africa, Europe

''Likely:'' Australasia, Central and South America

{11.4, 11.9}

| ''Very likely'' that increases take place in most land regions {11.4}

''Virtually certain:'' Africa, Asia, North America

''Extremely likely :'' Central and South America, Europe

''Very likely'' Australasia

{11.4, 11.9}

|-
| Agricultural and ecological droughts: increases in intensity and/or duration of drought events

| More regions affected by increases in agricultural and ecological droughts compared to observed changes ( ''high confidence'' ). {11.6, 11.9}

Decreased precipitation is going to increase the severity of drought in some regions; atmospheric evaporative demand will continue to increase compared to pre-industrial conditions and lead to further increases in agricultural and ecological droughts due to increased evapotranspiration in some regions. ( ''high confidence'' )

{11.6, 11.9}

| More regions affected by increases in agricultural and ecological droughts than at 1.5°C of global warming ( ''high confidence'' ). {11.6, 11.9}

Decreased precipitation is going to increase the severity of drought in some regions; atmospheric evaporative demand will continue to increase compared to pre-industrial conditions and lead to further increases in agricultural and ecological droughts due to increased evapotranspiration in some regions. ( ''high confidence'' )

{11.6, 11.9}

| More regions affected by increases in agricultural and ecological droughts than at 2°C of global warming ( ''very likely'' ) . {11.6, 11.9}

Decreased precipitation is going to increase the severity of drought in several regions; atmospheric evaporative demand will continue to increase compared to pre-industrial conditions and lead to further increases in agricultural and ecological droughts due to increased evapotranspiration in several regions. ( ''high confidence'' )

{11.6, 11.9}

|-
| Increase in precipitation associated with tropical cyclones (TCs)

| ''High confidence'' in a projected increase of TC rain rates at the global scale with a median projected increase due to human emissions of about 11%. {11.7}

''Medium confidence'' that rain rates will increase in every basin. {11.7}

| ''High confidence'' in a projected increase of TC rain rates at the global scale with a median projected increase due to human emissions of about 14%. {11.7}

''Medium confidence'' that rain rates will increase in every basin. {11.7}

| ''High confidence'' in a projected increase of TC rain rates at the global scale with a median projected increase due to human emissions of about 28%. {11.7}

''Medium confidence'' that rain rates will increase in every basin. {11.7}

|-
| Increase in mean TC lifetime-maximum wind speed (intensity)

| ''Medium confidence''

{11.7}

| ''High confidence''

{11.7}

| ''High confidence''

{11.7}

|-
| Increase in likelihood that a TC will reach major TC intensity (Category 4–5)

| ''High confidence'' for an increase in the proportion of TCs that reach the strongest (Category 4–5) levels. The median projected increase in this proportion is about 10%.

{11.7}

| ''High confidence'' for an increase in the proportion of TCs that reach the strongest (Category 4–5) levels. The median projected increase in this proportion is about 13%.

{11.7}

| ''High confidence'' for an increase in the proportion of TCs that reach the strongest (Category 4–5) levels. The median projected increase in this proportion is about 20%.

{11.7}

|-
| Severe convective storms

| colspan="3"| ''High confidence'' that the average and maximum rain rates associated with severe convective storms increase in some regions, including the USA. ''High confidence'' that convective available potential energy (CAPE) increases in response to global warming in the tropics and subtropics, suggesting more favourable environments for severe convective storms. ''Medium confidence'' that the frequency of spring severe convective storms is projected to increase in the USA, leading to a lengthening of the severe convective storm season. {11.7}

|-
| Increase in compound events (frequency, intensity)

| colspan="3"| ''Likely'' that probability of compound events will continue to increase with global warming.

''High confidence'' that concurrent heatwaves and droughts will continue to increase under higher levels of global warming, with higher frequency/intensity with every additional 0.5°C of global warming.

''High confidence'' that fire weather, (i.e. compound hot, dry and windy events), will become more frequent in some regions at higher levels of global warming.

''High confidence'' that compound flooding at the coastal zone will increase under higher levels of global warming. {11.8}

|}

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Box 11.2 | Changes in Low-likelihood, High-impact Extremes

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The SREX (Chapter 3) assigned ''low confidence'' to changes in low-likelihood, high-impact (LLHI) events (termed ‘low-probability high-impact scenarios‘). Such events are often not anticipated and thus sometimes referred to as ‘surprises’. There are several types of LLHI events. Abrupt changes in mean climate are addressed in Chapter 4. Unanticipated LLHI events can either result from tipping points in the climate system ( [[IPCC:Wg1:Chapter:Chapter-1#1.4.4.3|Section 1.4.4.3]] ), such as the shutdown of the Atlantic thermohaline circulation (SROCC Chapter 6; [[#Collins--2019|Collins et al., 2019]] ) or the drydown of the Amazonian rainforest (SR1.5 Chapter 3, [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ; [[#Drijfhout--2015|Drijfhout et al., 2015]] ), or from uncertainties in climate processes, including climate feedbacks, that may enhance or damp extremes either related to global or regional climate responses ( [[#Seneviratne--2018a|Seneviratne et al., 2018a]] ; [[#Sutton--2018|Sutton, 2018]] ). The ''low confidence'' does not by itself exclude the possibility of such events occuring, rather it indicates a poor state of knowledge. Such outcomes, while improbable, could be associated with very high impacts, and are thus highly relevant from a risk perspective (see [[IPCC:Wg1:Chapter:Chapter-1#1.4.3|Section 1.4.3]] and Box 11.4; [[#Sutton--2018|Sutton, 2018]] , 2019). Alternatively, high impacts can occur when different extremes occur at the same time, or in short succession at the same location, or in several regions with shared vulnerability (e.g., food-basket regions [[#Gaupp--2019|Gaupp et al., 2019]] ). These ‘compound events’ are assessed in [[#11.8|Section 11.8]] , and Box 11.4 provides a case study example.

Difficulties persist in determining the likelihood of occurrence and time frame of potential tipping points and LLHI events. However, new literature has emerged on unanticipated and LLHI events. There are some events that are sufficiently rare that they have not been observed in meteorological records, but whose occurrence is nonetheless plausible within the current state of the climate system – see examples below and in [[#McCollum--2020|McCollum et al. (2020)]] . The rare nature of such events and the limited availability of relevant data makes it difficult to estimate their occurrence probability and thus gives little evidence on whether to include such hypothetical events in planning decisions and risk assessments. The estimation of such potential surprises is often limited to events that have historical analogues (including before the instrumental records began, [[#Wetter--2014|Wetter et al., 2014]] ), albeit the magnitude of the event may differ. Additionally, there is also a limitation of available resources to exhaust all plausible trajectories of the climate system. As a result, there will still be events that cannot be anticipated. These events can be surprises to many in that the events have not been experienced, although their occurrence could be inferred by statistical means or physical modelling approaches ( [[#Chen--2017|Chen et al., 2017]] ; [[#van%20Oldenborgh--2017|van Oldenborgh et al., 2017]] ; [[#Harrington--2018a|Harrington and Otto, 2018a]] ). Another approach focusing on the estimation of low-probability events and of events whose likelihood of occurrence is unknown consists in using physical climate models to create a physically self-consistent storyline of plausible extreme events and assessing their impacts and driving factors in past ( [[#11.2.3|Section 11.2.3]] ) or future conditions ( [[#11.2.4|Section 11.2.4]] ) (Hazeleger et al. , 2015; [[#Shepherd--2016|Shepherd, 2016]] ; [[#Zappa--2017|Zappa and Shepherd, 2017]] ; Cheng et al. , 2018; Shepherd et al. , 2018; [[#Sutton--2018|Sutton, 2018]] ; Schaller et al. , 2020; Wehrli et al., 2020) .

In many parts of the world, observational data are limited to 50–60 years. This means that the chance to observe an extreme event at a particular location that occurs once in several hundred or more years is small. Thus, when a very extreme event occurs, it becomes a surprise to many ( [[#Bao--2017|Bao et al., 2017]] ; [[#McCollum--2020|McCollum et al., 2020]] ), and very rare events are often associated with high impacts (van Oldenborgh et al. , 2017; Philip et al. , 2018b; Tozer et al. , 2020). Attributing and projecting very rare events in a particular location by assessing their likelihood of occurrence within the same larger region and climate thus provides another way to make quantitative assessments regarding events that are extremely rare locally. Some examples of such events include:

* Hurricane Harvey, that made landfall in Houston, TX in August 2017 ( [[#11.7.1.4|Section 11.7.1.4]] .)
* The 2010–2011 extreme floods in Queensland, Australia ( [[#Christidis--2013a|Christidis et al., 2013a]] )
* The 2018 concurrent heatwaves across the Northern Hemisphere (Box 11.4)
* Tropical Cyclone Idai in Mozambique (Cross-Chapter Box: Disaster in WGII AR6 Chapter 4)
* The California fires in 2018 and 2019
* The 2019–2020 Australia fires (Cross-Chapter Box: Disaster in WGII AR6 Chapter 4)

One factor making such events hard to anticipate is the fact that we now live in a non-stationary climate, and that the framework of reference for adaptation is continuously moving. As an example, the concurrent heatwaves that occurred across the Northern Hemisphere in the summer of 2018 were considered very unusual and were unprecedented given the total area that was concurrently affected (Drouard et al. , 2019; Kornhuber et al. , 2019; Toreti et al. , 2019; Vogel et al. , 2019) ; however, the probability of this event under 1°C global warming was found to be about 16% ( [[#Vogel--2019|Vogel et al., 2019]] ), which is not particularly low. Similarly, the 2013 summer temperature over eastern China was the hottest on record at the time, but it had an estimated recurrence interval of about four years in the climate of 2013 ( [[#Sun--2014|Sun et al., 2014]] ). Furthermore, when other aspects of the risk, vulnerability, and exposure are historically high or have recently increased (see WGII, Chapter 16, Section 16.4), relatively moderate extremes can have very high impacts ( [[#Otto--2015b|Otto et al., 2015b]] ; [[#Philip--2018b|Philip et al., 2018b]] ). As warming continues, the climate moves further away from its historical state we are familiar with, resulting in an increased likelihood of unprecedented events and surprises. This is particularly the case under high global warming levels – for example, the climate of the late 21st century under high-emissions scenarios, above 4°C of global warming (Cross-Chapter Box 11.1).

Another factor highlighted in [[#11.8|Section 11.8]] and Box 11.4 making events high-impact and difficult to anticipate is that several locations under moderate warming levels could be affected simultaneously, or very repeatedly by different types of extremes (Mora et al., 2018; [[#Gaupp--2019|Gaupp et al., 2019]] ; [[#Vogel--2019|Vogel et al., 2019]] ). Box 11.4 shows that concurrent events at different locations, which can lead to major impacts across the world, can also result from the combination of anomalous circulation or natural variability (e.g., El Niño–Southern Oscillation) patterns with amplification of resulting responses to human-induced global warming. Also multivariate extremes at single locations pose specific challenges to anticipation ( [[#11.8|Section 11.8]] ), with low likelihoods in the current climate but the probability of occurrence of such compound events strongly increasing with increasing global warming levels ( [[#Vogel--2020a|Vogel et al., 2020a]] ). Therefore, in order to estimate whether, and at what level of global warming, very high impacts arising from extremes would occur, the spatial extent of extremes and the potential of compounding extremes need to be assessed. Sections 11.3, 11.4, 11.7 and 11.8 highlight increasing evidence that temperature extremes, higher intensity precipitation accompanying tropical cyclones, and compound events such as dry/hot conditions conducive to wildfire or storm surges resulting from sea level rise and heavy precipitation events, pose widespread threats to societies already at relatively low warming levels. Studies have already shown that the probability for some recent extreme events is so small in the undisturbed world that these events were ''extremely unlikely'' to occur without human influence ( [[#11.2.4|Section 11.2.4]] ). Box 11.2, Table 1, provides examples of projected changes in LLHI extremes (single extremes, compound events) of potential relevance for impact and adaptation assessments showing that today’s very rare events can become commonplace in a warmer future.

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'''Box 11.2, Table 1 |'''

'''Examples of changes in low-likelihood, high-impact extreme conditions (single extremes, compound events) at different global''' '''warming levels.'''
{| class="wikitable"
|-
!
! +1°C (Present-day)

! +1.5°C

! +2°C

! +3°C and Higher

|-
| Risk ratio for annual hottest daytime temperature (TXx) with 1% of probability under present-day warming (+1°C) ( [[#Kharin--2018|Kharin et al., 2018]] ): Global land

| 1

| 3.3 (i.e., 230% higher probability)

| 8.2 (i.e., 720% higher probability)

| Not assessed

|-
| Risk ratio for heavy precipitation events (Rx1day) with 1% of probability under present-day warming (+1°C) ( [[#Kharin--2018|Kharin et al., 2018]] ): Global land

| 1

| 1.2 (i.e., 20% higher probability)

| 1.5 (i.e., 50% higher probability)

| Not assessed

|-
| Number of 1–5 day duration extreme floods with 1% of probability under present-day warming (+1°C) (H. [[#Ali--2019|]] [[#Ali--2019|Ali et al., 2019]] ) Indian subcontinent

| Up to 3 in individual locations

| Up to 5 in individual locations

| 2–6 in most locations

| Up to 12 in individual locations (4°C)

|-
| Probability of ‘extreme extremes’ hot days with 1/1000 probability at the end of the 20th century ( [[#Vogel--2020a|Vogel et al., 2020a]] ): Global land

| About 20 days over 20 years in most locations

| About 50 days in 20 years in most locations

| About 150 days in 20 years in most locations

| About 500 days in 20 years in most locations (3°C)

|-
| Probability of co-occurrence in the same week of hot days with 1/1000 probability and dry days with 1/1000 probability at the end of the 20th century ( [[#Vogel--2020a|Vogel et al., 2020a]] ): Amazon

| 0% probability

| About one week in 20 years

| About 4 to 5 weeks in 20 years

| More than 9 weeks in 20 years (3°C)

|-
| Projected soil moisture drought duration per year ( [[#Samaniego--2018|Samaniego et al., 2018]] ): Mediterranean region

| 41 days (+46% compared to the late 20th century)

| 58 days (+107% compared to the late 20th century)

| 71 days (+154% compared to the late 20th century)

| 125 days (+346% compared to the late 20th century) (3°C)

|-
| Increase in days exposed to dangerous extreme heat – measured in Health Heat Index (HHI) (Q. [[#Sun--2019|]] [[#Sun--2019|]] [[#Sun--2019|]] [[#Sun--2019|Sun et al., 2019]] ) global land

| Not assessed, baseline is 1981–2000

| 1.6 times higher risk of experiencing heat &gt;40.6

| 2.3 times higher risk of experiencing heat &gt;40.6

| Around 80% of land area exposed to dangerous heat, tropical regions 1/3 of the year (4°C)

|-
| Increase in regional mean fire season length (Q. [[#Sun--2019|]] [[#Sun--2019|]] [[#Sun--2019|]] [[#Sun--2019|Sun et al., 2019]] ; [[#Xu--2020|Xu et al., 2020]] ) global land

| Not assessed, baseline is 1981–2000

| 6.2 days

| 9.5 days

| About 50 days (4°C)

|}

In summary, the future occurrence of LLHI events linked to climate extremes is generally associated with ''low confidence'' , but cannot be excluded, especially at global warming levels above 4°C. Compound events, including concurrent extremes, are a factor increasing the probability of LLHI events ( ''high confidence'' ). With increasing global warming, some compound events with low likelihood in past and current climate will become more frequent, and there is a higher chance of historically unprecedented events and surprises ( ''high confidence'' ). However, even extreme events that do not have a particularly low probability in the present climate (at more than 1°C of global warming) can be perceived as surprises because of the pace of global warming ( ''high confidence'' ).

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