Editing IPCC:AR6/WGI/TS (section)

===== TS.4.3.2.10 Other Typological Domains =====

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'''Some types of regions found in different continents face common climate challenges regardless of their location. These include biodiversity hot spots that will ''very likely'' see even more extreme heat and droughts, mountain areas where a projected raising in the freezing level height will alter snow and ice conditions ( ''high confidence'' ), and tropical forests that are increasingly prone to fire weather ( ''medium confidence'' ). Links to chapters 8.4, Box 8.2, 9.5, 12.3, 12.4'''
Biodiversity hotspots located around the world will each face unique challenges in CID changes. Heat, drought and length of dry season, wildfire weather, sea surface temperature and deoxygenation are relevant drivers to terrestrial and freshwater ecosystems and have marked increasing trends. Links to chapters 12.3, 12.4.10.1

Desert and semi-arid areas are strongly affected by CIDs such as extreme heat, drought and dust storms, with large-scale aridity trends contributing to expanding drylands in some regions ( ''high confidence'' ). Links to chapters 12.3, 12.4.10.3

Average warming in mountain areas varies with elevation, but the pattern is not globally uniform ( ''medium confidence'' ). Extreme precipitation is projected to increase in major mountainous regions ( ''medium'' to ''high confidence'' depending on location), with potential cascading consequences of floods, landslides and lake outbursts in all scenarios ( ''medium confidence'' ). Links to chapters 8.4.1.5, Box 8.2, 9.5.1.3, 9.5.3.3, 9.5.2.3, Cross-Chapter Box 10.4, 11.5.5, 12.3, 12.4.1–12.4.6, 12.4.10.4

Most tropical forests are challenged by a mix of emerging warming trends that are particularly large in comparison to historical variability ( ''medium confidence'' ). Water cycle changes bring prolonged drought, longer dry seasons and increased fire weather to many tropical forests ( ''medium confidence'' ). Links to chapters 10.5, 12.3, 12.4

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'''Box TS.14 | Urban Areas'''

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'''With global warming, urban areas and cities will be affected by more frequent occurrences of extreme climate events, such as heatwaves, with more hot days and warm nights as well as sea level rise and increases in tropical cyclone storm surge and rainfall intensity that will increase the probability of coastal city flooding ( ''high confidence'' ). Links to chapters Box 10.3, 11.3, 11.5, 12.3, 12.4'''
Urban areas have special interactions with the climate system, for instance in terms of heat islands and altering the water cycle, and thereby will be more affected by extreme climate events such as extreme heat ( ''high confidence'' ). With global warming, increasing relative sea level compounded by increasing tropical cyclone storm surge and rainfall intensity will increase the probability of coastal city flooding ( ''high confidence'' ). Arctic coastal settlements are particularly exposed to climate change due to sea ice retreat ( ''high confidence'' ). Improvements in urban climate modelling and climate monitoring networks have contributed to understanding the mutual interaction between regional and urban climate ( ''high confidence'' ). Links to chapters Box 10.3, 11.3, 11.5, 12.3, 12.4

Despite having a negligible effect on global surface temperature ( ''high confidence'' ), urbanization has exacerbated the effects of global warming through its contribution to the observed warming trend in and near cities, particularly in annual mean minimum temperature ( ''very high confidence'' ) and increases in mean and extreme precipitation over and downwind of the city, especially in the afternoon and early evening ( ''medium confidence'' ). Links to chapters 2.3, Box 10.3, 11.3, 11.4, 12.3, 12.4

Combining climate change projections with urban growth scenarios, future urbanization will amplify ( ''very high confidence'' ) the projected local air temperature increase, particularly by strong influence on minimum temperatures, which is approximately comparable in magnitude to global warming ( ''high confidence'' ). Compared to present day, large implications are expected from the combination of future urban development and more frequent occurrence of extreme climate events, such as heatwaves, with more hot days and warm nights adding to heat stress in cities ( ''very high confidence'' ). Links to chapters Box 10.2, 11.3, 12.4

Both sea levels and air temperatures are projected to rise in most coastal settlements ( ''high confidence'' ). There is ''high confidence'' in an increase in pluvial flood potential in urban areas where extreme precipitation is projected to increase, especially at high global warming levels. Links to chapters 11.4, 11.5, 12.4

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[[#footnote-020-backlink|1]] In this Technical Summary, the following summary terms are used to describe the available evidence: limited, medium, or robust; and for the degree of agreement: low, medium, or high. A level of confidence is expressed using five qualifiers: very low, low, medium, high, and very high, and typeset in italics, e.g., ''medium confidence'' . For a given evidence and agreement statement, different confidence levels can be assigned, but increasing levels of evidence and degrees of agreement are correlated with increasing confidence (see Chapter 1, Box 1.1 for more details).

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[[#footnote-019-backlink|2]] In this Technical Summary, the following terms are used to indicate the assessed likelihood of an outcome or a result: virtually certain 99–100% probability, very likely 90–100%, likely 66–100%, about as likely as not 33–66%, unlikely 0–33%, very unlikely 0–10%, exceptionally unlikely 0–1%. Additional terms (extremely likely : 95–100%, more likely than not &gt;50–100%, and extremely unlikely 0–5%) may also be used when appropriate. Assessed likelihood is typeset in italics, e.g., ''very likely'' (see Chapter 1, Box 1.1 for more details). Throughout the WGI report and unless stated otherwise, uncertainty is quantified using 90% uncertainty intervals. The 90% uncertainty interval, reported in square brackets [x to y], is estimated to have a 90% likelihood of covering the value that is being estimated. The range encompasses the median value, and there is an estimated 10% combined likelihood of the value being below the lower end of the range (x) and above its upper end (y). Often, the distribution will be considered symmetric about the corresponding best estimate, but this is not always the case. In this Report, an assessed 90% uncertainty interval is referred to as a ‘ ''very likely'' range’. Similarly, an assessed 66% uncertainty interval is referred to as a ‘ ''likely'' range’.

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[[#footnote-018-backlink|3]] The regional traceback matrices that provide the location of the assessment findings synthesized in Section TS.4 are in the Supplementary Material (SM) of Chapter 10.

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[[#footnote-017-backlink|4]] Data archive is available at https://catalogue.ceda.ac.uk/uuid/3234e9111d4f4354af00c3aaecd879b7 .

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[[#footnote-016-backlink|5]] https://interactive-atlas.ipcc.ch/

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[[#footnote-015-backlink|6]] The AR6 figures use one of the following approaches. For observations, the absence of ‘x’ symbols shows areas with statistical significance, while the presence of ‘x’ indicates non-significance. For model projections, the method offers two approaches with varying complexity. In the simple approach, ''high agreement'' (≥80%) is indicated with no overlay, and diagonal lines (///) show ''low agreement'' (&lt;80%); In the advanced approach, areas with no overlay display robust signal (≥66% of models show change greater than the variability threshold and ≥80% of all models agree on the sign of change), reverse diagonal lines () show no robust signal, and crossed lines show conflicting signals (i.e., significant change but ''low agreement'' ). Cross-Chapter Box Atlas.1 provides more information on the AR6 method for visualizing robustness and uncertainty on maps.

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[[#footnote-014-backlink|7]] Although not a core concept of the WGI Report, deep uncertainty is used in the Technical Summary in the following sense: ‘A situation of deep uncertainty exists when experts or stakeholders do not know or cannot agree on: (1) appropriate conceptual models that describe relationships among key driving forces in a system; (2) the probability distributions used to represent uncertainty about key variables and parameters; and/or (3) how to weigh and value desirable alternative outcomes’ (Lempert et al., 2003). Lempert, R. J., Popper, S. W., and Bankes, S. C. (2003). ''Shaping the next one hundred years: New methods for quantitative long-term strategy analysis (MR-1626-RPC)'' . Santa Monica, CA: The RAND Pardee Center.

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[[#footnote-013-backlink|8]] The assessment covers scientific literature accepted for publication by 31 January 2021.

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[[#footnote-012-backlink|9]] Human influence on the climate system refers to human-driven activities that lead to changes in the climate system due to perturbations of Earth’s energy budget (also called anthropogenic forcing). Human influence results from emissions of greenhouse gases, aerosols and tropospheric ozone precursors, ozone-depleting substances, and land-use change.

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[[#footnote-011-backlink|10]] Throughout this Technical Summary, ‘main driver’ means responsible for more than 50% of the change.

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[[#footnote-010-backlink|11]] Throughout the WGI report and unless stated otherwise, uncertainty is quantified using 90% uncertainty intervals. The 90% uncertainty interval, reported in square brackets [x to y], is estimated to have a 90% likelihood of covering the value that is being estimated. The range encompasses the median value and there is an estimated 10% combined likelihood of the value being below the lower end of the range (x) and above its upper end (y). Often the distribution will be considered symmetric about the corresponding best estimate, but this is not always the case. In this Report, an assessed 90% uncertainty interval is referred to as a ‘ ''very likely'' range’. Similarly, an assessed 66% uncertainty interval is referred to as a ‘ ''likely'' range’.

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[[#footnote-009-backlink|12]] Increased stratification reduces the vertical exchange of heat, salinity, oxygen, carbon and nutrients. Stratification is an important indicator for ocean circulation.

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[[#footnote-008-backlink|13]] Several baselines or reference periods are used consistently throughout this Report. Baseline refers to a period against which anomalies (i.e., differences from the average value for the baseline period) are calculated. Examples include the 1750 baseline (used for anthropogenic radiative forcings), the 1850–1900 baseline (an approximation for pre-industrial global surface temperature from which global warming levels are calculated) and the 1995–2014 baseline (used for many climate model projections). A reference period indicates a time period over which various statistics are calculated (e.g., the near-term reference period, 2021–2040). Paleo reference periods are listed in Box TS.2. Links to chapters 1.4.1, Cross-Chapter Boxes 1.2 and 2.1

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[[#footnote-007-backlink|14]] Please refer to Section TS.1.3.1 for an overview of the climate change scenarios used in this Report.

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[[#footnote-006-backlink|15]] In this Report, equilibrium climate sensitivity is defined as the equilibrium (steady state) change in the surface temperature following a doubling of the atmospheric carbon dioxide (CO 2 ) concentration from pre-industrial conditions.

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[[#footnote-005-backlink|16]] In this Report, transient climate response is defined as the surface temperature response for the hypothetical scenario in which atmospheric carbon dioxide (CO 2 ) increases at 1% yr <sup>–1</sup> from pre-industrial to the time of a doubling of atmospheric CO 2 concentration.

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[[#footnote-004-backlink|17]] Throughout this Report, scenarios are referred to as SSPx-y, where “SSPx” refers to the Shared Socio-economic Pathway or “SSP” describing the socio-economic trends underlying the scenario, and “y” refers to the approximate target level of radiative forcing (in W m <sup>–-2</sup> ) resulting from the scenario in the year 2100.

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[[#footnote-003-backlink|18]] The transient surface temperature change per unit of cumulative CO 2 emissions, usually 1000 GtC.

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[[#footnote-002-backlink|19]] Throughout this Technical Summary, ‘main driver’ means responsible for more than 50% of the change.

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[[#footnote-001-backlink|20]] For reference, the Planck temperature response for a doubling of atmospheric CO 2 is approximately 1.2°C at equilibrium.

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[[#footnote-000-backlink|21]] Although cirrus cloud thinning aims to cool the planet by increasing longwave emissions to space, it is included in the portfolio of SRM options for consistency with AR5 and SR1.5. Links to chapters 4.6.3.3