Editing IPCC:AR6/SROCC/Chapter-3 (section)

=== 3.4.2 Projections ===

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==== 3.4.2.1 Seasonal Snow ====

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Historical simulations from CMIP5 models tend to underestimate observed reductions in spring snow cover extent due to uncertainty in the parameterisation of snow processes (Essery, 2013 <sup>[[#fn:r1518|1518]]</sup> ; Thackeray et al., 2014 <sup>[[#fn:r1519|1519]]</sup> ), challenges in simulating snow-albedo feedback (Qu and Hall, 2014 <sup>[[#fn:r1520|1520]]</sup> ; Fletcher et al., 2015 <sup>[[#fn:r1521|1521]]</sup> ; Li et al., 2016b <sup>[[#fn:r1522|1522]]</sup> ), unrealistic temperature sensitivity (Brutel-Vuilmet et al., 2013 <sup>[[#fn:r1523|1523]]</sup> ; Mudryk et al., 2017 <sup>[[#fn:r1524|1524]]</sup> ), and biases in climatological spring snow cover (Thackeray et al., 2016 <sup>[[#fn:r1525|1525]]</sup> ). The role of precipitation biases is not well understood (Thackeray et al., 2016 <sup>[[#fn:r1526|1526]]</sup> ).

Reductions in Arctic snow cover duration are projected by the CMIP5 multi-model ensemble due to later snow onset in the autumn and earlier snow melt in spring (Brown et al., 2017 <sup>[[#fn:r1527|1527]]</sup> ) driven by increased surface temperature over essentially all Arctic land areas (Hartmann et al., 2013). There is ''high confidence'' that projected snow cover declines are proportional to the amount of future warming in each model realisation (Thackeray et al., 2016 <sup>[[#fn:r1528|1528]]</sup> ; Mudryk et al., 2017 <sup>[[#fn:r1529|1529]]</sup> ). Projections to mid-century are primarily dependent on natural variability and model dependent uncertainties rather than the choice of forcing scenario (Hodson et al., 2013 <sup>[[#fn:r1530|1530]]</sup> ). By end of century, however, differences between scenarios emerge. Under RCP2.6 and RCP4.5, Arctic snow cover duration stabilises at 5–10% reduction (compared to a 1986–2005 reference period); under RCP8.5, snow cover duration declines reach –15 to –25% (Brown et al., 2017 <sup>[[#fn:r1531|1531]]</sup> ) (Figure 3.10) ( ''high confidence'' ).

Positive Arctic snow water equivalent changes emerge across the eastern Eurasian Arctic by mid-century for both RCP4.5 and RCP8.5 (Brown et al., 2017 <sup>[[#fn:r1532|1532]]</sup> ) ( ''medium confidence'' ). Projected snow water equivalent increases across the North American Arctic are only modest, emerge later in the century, and only under RCP8.5 (Brown et al., 2017 <sup>[[#fn:r1533|1533]]</sup> ). These projected increases are due to enhanced snowfall (Krasting et al., 2013 <sup>[[#fn:r1534|1534]]</sup> ) from a more moisture-rich Arctic atmosphere coupled with winter season temperatures that remain sufficiently low for precipitation to fall as snow. There is ''low confidence'' in changes to snow properties such as density and stratigraphy (relevant for understanding the impacts of changes to Arctic snow on ecosystems) which are not resolved directly by climate model simulations, but require detailed snow physics models.

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==== 3.4.2.2 Permafrost ====

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Circumpolar- or global-scale models represent permafrost degradation in response to warming scenarios as increases in thaw depth only. The CMIP5 models project with ''high confidence'' that thaw depth will increase and areal extent of near-surface permafrost will decrease substantially (Koven et al., 2013 <sup>[[#fn:r1535|1535]]</sup> ; Slater and Lawrence, 2013 <sup>[[#fn:r1536|1536]]</sup> ) (Figure 3.10). However, there is only ''medium confidence'' in the magnitude of these changes due to at least a five-fold range of estimated present day near-surface permafrost area (&lt;5 – &gt;25 x 10 6 km 2 ) by these models. This was caused by a wide range of model sensitivity in permafrost area to air temperature change, resulting in a large range of projected near-surface permafrost loss by 2100: 2–66% for RCP2.6 (24 ± 16%; ''likely'' range), 15–87% under RCP4.5 and 30–99% (69 ± 20%; ''likely'' range) under RCP8.5. A more recent analysis of near-surface permafrost trends from a subset of models that self-identified as structurally representing the permafrost region had a significantly smaller range of estimated present day near-surface permafrost area (13.1–19.3 x 10 6 km 2 ; mean ± SD, 14.1 ± 3.5 x 10 6 km 2 ) (McGuire et al., 2018 <sup>[[#fn:r1537|1537]]</sup> ). This subset of models also showed large reductions of near-surface permafrost area, averaging a 90% loss (12.7 ± 5.1×10 6 km 2 ) of permafrost area by 2300 for RCP8.5 and 29% loss (4.1 ± 0.6×10 6 km 2 ) for RCP4.5, with much of that long-term loss already occurring by 2100.

Pulse disturbances are not included in the permafrost projections described above, and there is ''high confidence'' that fire and abrupt thaw will accelerate change in permafrost relative to climate effects alone, if the rates of these disturbances increase. The observed trend of increasing fire is projected to continue for the rest of the century across most of the tundra and boreal region for many climate scenarios, with the boreal region projected to have the greatest increase in total area burned (Balshi et al., 2009 <sup>[[#fn:r1538|1538]]</sup> ; Kloster et al., 2012 <sup>[[#fn:r1539|1539]]</sup> ; Wotton et al., 2017 <sup>[[#fn:r1540|1540]]</sup> ). Due to vegetation-climate interactions, there is only ''medium confidence'' in projections of future area burned. As fire activity increases, flammable vegetation, such as the black spruce forest that dominates boreal Alaska, is projected to decline as it is replaced by low-flammability deciduous forest (Johnstone et al., 2011 <sup>[[#fn:r1541|1541]]</sup> ; Pastick et al., 2017 <sup>[[#fn:r1542|1542]]</sup> ). In other regions such as western Canada, by contrast, black spruce could be replaced by the even more flammable jack pine, creating regional-scale feedbacks that increase the spread of fire on the landscape (Héon et al., 2014 <sup>[[#fn:r1543|1543]]</sup> ). A regional process-model study of Alaska projected annual median area burned during the 21st century to be 1.3-1.7 times higher compared with the historical average  (Pastick et al., 2017 <sup>[[#fn:r1544|1544]]</sup> ). Fire also appears to be expanding as a novel disturbance into tundra and forest-tundra boundary regions previously protected by a cool, moist climate (Jones et al., 2009 <sup>[[#fn:r1545|1545]]</sup> ; Hu et al., 2010 <sup>[[#fn:r1546|1546]]</sup> ; Hu et al., 2015 <sup>[[#fn:r1547|1547]]</sup> ) ( ''medium confidence'' ). Annual tundra area burned in Alaska is projected to double under RCP6.0 from a historic rate of 270 km 2 yr -1 to 500–610 km 2 yr -1 over the 21st century (Hu et al., 2015 <sup>[[#fn:r1548|1548]]</sup> ). A statistical approach projected a fourfold increase in the 30-year probability of fire occurrence in the forest-tundra boundary by 2100 (Young et al., 2017 <sup>[[#fn:r1549|1549]]</sup> ). In contrast to fire, there has not yet been a comprehensive circumpolar projection of how abrupt thaw rates may change in the future, but one component of abrupt thaw, change in abrupt thaw lake area, has been projected to increase to increase by 53% under RCP8.5 (Walter Anthony et al., 2018 <sup>[[#fn:r1550|1550]]</sup> ) above the 1.4 x 10 6 km 2 of small lakes and ponds that currently exist in the permafrost region (Muster et al., 2017 <sup>[[#fn:r1551|1551]]</sup> ). As a result, there is ''low confidence'' in the ability to assess the magnitude by which abrupt thaw across the entire landscape will affect regional permafrost, even though this mechanism for rapid change appears critically important for projecting future change (Kokelj et al., 2017 <sup>[[#fn:r1552|1552]]</sup> ).

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==== 3.4.2.3 Freshwater Systems ====

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Climate model simulations project a warmer and wetter Arctic (Krasting et al., 2013 <sup>[[#fn:r1553|1553]]</sup> ), with increased specific humidity due to enhanced evaporation (Laîné et al., 2014 <sup>[[#fn:r1554|1554]]</sup> ), and moisture flux convergence increases into the Arctic (Skific and Francis, 2013 <sup>[[#fn:r1555|1555]]</sup> ). Increased cold-season precipitation is projected across the Arctic by CMIP5 models (Lique et al., 2016 <sup>[[#fn:r1556|1556]]</sup> ) due to increased moisture flux convergence from outside the Arctic (Zhang et al., 2012 <sup>[[#fn:r1557|1557]]</sup> ) and enhanced moisture availability from reduced sea ice cover (Bintanja and Selten, 2014 <sup>[[#fn:r1558|1558]]</sup> ) ( ''high confidence'' ). Increases in precipitation extremes are also projected over northern watersheds (Kharin et al., 2013 <sup>[[#fn:r1559|1559]]</sup> ; Sillmann et al., 2013 <sup>[[#fn:r1560|1560]]</sup> ), while rain on snow events are expected to increase (Hansen et al., 2014 <sup>[[#fn:r1561|1561]]</sup> ). A net increased ratio of precipitation minus evaporation is projected, resulting in increased freshwater flux from the land surface to the Arctic Ocean, projected to be 30% above current values by 2100 under RCP4.5 (Haine et al., 2015 <sup>[[#fn:r1562|1562]]</sup> ) (Figure 3.10). This is consistent with CMIP5 model projections of increased discharge from Arctic watersheds (van Vliet et al., 2013 <sup>[[#fn:r1563|1563]]</sup> ; Gelfan et al., 2016 <sup>[[#fn:r1564|1564]]</sup> ; MacDonald et al., 2018 <sup>[[#fn:r1565|1565]]</sup> ). The water temperature of this increased discharge is projected to be approximately 1°C warmer than current conditions, increasing the heat flux to Arctic Ocean (van Vliet et al., 2013 <sup>[[#fn:r1566|1566]]</sup> ).

Lake ice phenology is sensitive to projected changes in surface temperature (Sharma et al., 2019 <sup>[[#fn:r1567|1567]]</sup> ). Lake ice models project an earlier spring break-up of between 10–25 days by mid-century (compared with 1961–1990), and up to a 15-day delay in the freeze-up for lakes in the North American Arctic, with more extreme reductions for coastal regions (Brown and Duguay, 2011 <sup>[[#fn:r1568|1568]]</sup> ; Dibike et al., 2011 <sup>[[#fn:r1569|1569]]</sup> ; Prowse et al., 2011 <sup>[[#fn:r1570|1570]]</sup> ) ( ''medium confidence'' ). Mean maximum ice thickness is projected to decrease by 10–50 cm over the same period (Brown and Duguay, 2011 <sup>[[#fn:r1571|1571]]</sup> ). High-latitude warming is projected to drive earlier river ice break-up in spring due to both decreasing ice strength, and earlier onset of peak discharge (Cooley and Pavelsky, 2016 <sup>[[#fn:r1572|1572]]</sup> ). Complex interplay between hydrology and hydraulics in controlling spring flooding and ice jam events complicate projections of these events (Prowse et al., 2010 <sup>[[#fn:r1573|1573]]</sup> ; Prowse et al., 2011 <sup>[[#fn:r1574|1574]]</sup> ).

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