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

== 3.3 Polar Ice Sheets and Glaciers: Changes, Consequences and Impacts ==

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=== 3.3.1 Ice Sheet Changes ===

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Changes in ice sheet mass have been derived repeatedly over the satellite era using complementary methods based on time series of satellite altimetry to measure volume change, ice-flux measurements combined with modelled surface mass balance (SMB) to calculate mass inputs and outputs, and satellite gravimetry to measure regional mass change. Ice sheet changes over earlier periods have also been reconstructed from firn/ice core and geological evidence (SM3.3.1).

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<span id="antarctic-ice-sheet-mass-change"></span>
==== 3.3.1.1 Antarctic Ice Sheet Mass Change ====

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It is ''virtually certain'' that the Antarctic Peninsula (AP) and West Antarctic Ice Sheet (WAIS) combined have cumulatively lost mass since widespread measurements began in 1992, and that the rate of loss has increased since around the year 2006 and continued post-AR5 (Martín ‐ Español et al., 2016 <sup>[[#fn:r915|915]]</sup> ; Zwally et al., 2017 <sup>[[#fn:r916|916]]</sup> ; Bamber et al., 2018 <sup>[[#fn:r917|917]]</sup> ; Gardner et al., 2018 <sup>[[#fn:r918|918]]</sup> ; The IMBIE Team, 2018; Rignot et al., 2019 <sup>[[#fn:r919|919]]</sup> ), extending and reinforcing previous findings (IPCC, 2013 <sup>[[#fn:r920|920]]</sup> ) (Figure 3.7, Table 3.3, SM3.3.1.1). From ''medium evidence'' , there is ''high agreement'' in the sign and ''medium agreement'' in the magnitude of both WAIS and AP mass change between the complementary satellite methods (Mémin et al., 2015 <sup>[[#fn:r921|921]]</sup> ; The IMBIE Team, 2018).

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<span id="table-3.3"></span>
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'''Table 3.3'''
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Mass balance (Gt yr -1 ) of the West Antarctic Ice Sheet (WAIS), Antarctic Peninsula (AP), East Antarctic Ice Sheet (EAIS), the combined Antarctic Ice Sheets (AIS) and the Greenland Ice Sheet (GIS) and the total sea level contribution (mm yr -1 ).
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[[File:92398abc51f11dac3260b63c795aa85c table3.3.png]]

WAIS mass loss and recent increases in loss were concentrated in the Amundsen Sea Embayment (ASE) ( ''high confidence'' ) with increases particularly in the late 2000s (Mouginot et al., 2014 <sup>[[#fn:r930|930]]</sup> ), accounting for most of the –112 ± 10 Gt yr –1 WAIS loss from 2003 to 2013 (Martín ‐ Español et al., 2016 <sup>[[#fn:r931|931]]</sup> ). The ice sheet margins of nearby Getz Ice Shelf also lost mass rapidly (–67 ± 27 Gt yr –1 , 2008–2015) (Gardner et al., 2018 <sup>[[#fn:r932|932]]</sup> ). This region also experienced losses during previous warm periods (Cross-Chapter Box 8 in Chapter 3).

On the AP, the Bellingshausen Sea ice sheet margin shifted from close to mass balance in the 2000s to rapid loss from 2009 (–56 ± 8 Gt yr -1 from 2010 to 2014) ( ''high confidence'' ) (Helm et al., 2014 <sup>[[#fn:r933|933]]</sup> ; McMillan et al., 2014b <sup>[[#fn:r934|934]]</sup> ; Wouters et al., 2015 <sup>[[#fn:r935|935]]</sup> ; Hogg et al., 2017 <sup>[[#fn:r936|936]]</sup> ). This shift accompanied ongoing mass loss ( ''high confidence'' ) from the smaller northeastern AP glaciers that fed the former Prince Gustav, Larsen A and B ice shelves, though now at a lower rate than immediately following shelf collapse in 1995 and 2002 (Seehaus et al., 2015 <sup>[[#fn:r937|937]]</sup> ; Wuite et al., 2015 <sup>[[#fn:r938|938]]</sup> ; Rott et al., 2018 <sup>[[#fn:r939|939]]</sup> ). Of 860 marine-terminating AP glaciers, 90% retreated from their 1940s positions (Cook et al., 2014 <sup>[[#fn:r940|940]]</sup> ), established in the early to mid-Holocene (Ó Cofaigh et al., 2014) ( ''medium confidence'' ). Early 21st century combined AP glacier (Fieber et al., 2018 <sup>[[#fn:r941|941]]</sup> ) and ice sheet loss was around –30 Gt yr –1 (Table 3.3).

The East Antarctic Ice Sheet (EAIS, covering 85% of the Antarctic Ice Sheet (AIS)) has remained close to balance, with large interannual variability and no clear mass trend over the satellite record ( ''medium confidence'' ) (Table 3.3, Figure 3.7, SM3.3.1.2), and relatively large observation uncertainties (SM3.3.1) (Velicogna et al., 2014 <sup>[[#fn:r942|942]]</sup> ; Martin-Español et al., 2017 <sup>[[#fn:r943|943]]</sup> ; Bamber et al., 2018 <sup>[[#fn:r944|944]]</sup> ). SMB trends are particularly ambiguous, leading to disagreement between one altimetry and one flux-based estimate of 136 ± 43 Gt yr–1 (spanning 1992–2008) (Zwally et al., 2017 <sup>[[#fn:r945|945]]</sup> ), and –41 ± 8 Gt yr–1 (1979–2017) (Rignot et al., 2019 <sup>[[#fn:r946|946]]</sup> ), respectively. Both differ from the multi-method averages reported here (Table 3.3).

EAIS mass gains on the Siple Coast and Dronning Maud Land (e.g., 63 ± 6 Gt yr –1 from 2003 to 2013 (Velicogna et al., 2014 <sup>[[#fn:r947|947]]</sup> )) contrast with Wilkes Land losses e.g., from –17 ± 4 Gt yr –1 from the Totten Glacier area, 2003–2013 (Velicogna et al., 2014) that drain a large area of deeply-grounded EAIS with potential for multi-metre sea level contributions (Zwally et al., 2017 <sup>[[#fn:r948|948]]</sup> ; Rignot et al., 2019 <sup>[[#fn:r949|949]]</sup> ). Limited palaeo ice sheet evidence suggests that this area has previously lost substantial mass in previous interglacials ( ''medium confidence'' ) (Aitken et al., 2016 <sup>[[#fn:r950|950]]</sup> ; Wilson et al., 2018).

Overall, 2012–2016 AIS mass losses were ''extremely likely'' greater than those from 2002 to 2011 and ''likely'' greater than from 1992 to 2001, and it is ''extremely likely'' that the negative 2012–2016 AIS mass balance was dominated by losses from WAIS (Table 3.3).

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'''Figure 3.7'''

<span id="a-cumulative-ice-sheet-mass-change-19922016-after-bamber-et-al.-2018-the-imbie-team-2018.-b-greenland-ice-sheet-gis-mass-change-components-from-surface-mass-balance-smb-orange-and-dynamic-thinning-blue-from-2000-to-2016-after-van-den-broeke-et-al.-2016-king-et-al.-2018.-uncertainties-are-1-standard-deviation."></span>
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'''(a) Cumulative Ice Sheet mass change, 1992–2016, (after Bamber et al., 2018; The IMBIE Team, 2018). (b) Greenland Ice Sheet (GIS) mass change components from surface mass balance (SMB) (orange) and dynamic thinning (blue) from 2000 to 2016, (after van den Broeke et al., 2016; King et al., 2018). Uncertainties are 1 standard deviation.'''
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[[File:ff677c1128be1370620c9dc35d602654 IPCC-SROCC-CH_3_7.jpg]]

(a) Cumulative Ice Sheet mass change, 1992–2016, (after Bamber et al., 2018; The IMBIE Team, 2018). (b) Greenland Ice Sheet (GIS) mass change components from surface mass balance (SMB) (orange) and dynamic thinning (blue) from 2000 to 2016, (after van den Broeke et al., 2016; King et al., 2018). Uncertainties are 1 standard deviation.

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<div id="section-3-3-1-2components-of-antarctic-ice-sheet-mass-change"></div>

<span id="components-of-antarctic-ice-sheet-mass-change"></span>
==== 3.3.1.2 Components of Antarctic Ice Sheet Mass Change ====

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AIS mass changes are dominated by changes in snowfall and glacier flow. The WAIS and AP loss trends in recent decades are dominated by glacier flow acceleration (also known as dynamic thinning) ( ''very high confidence'' ) (Figure SM3.8). Dynamic thinning losses were –112 ± 12 Gt yr –1 for 2003–2013, largely from the ASE (Figure SM3.8) (Martín ‐ Español et al., 2016 <sup>[[#fn:r951|951]]</sup> ), which contributed –102 ± 10 Gt yr –1 from 2003 to 2011 (Sutterley et al., 2014 <sup>[[#fn:r952|952]]</sup> ). Total ASE ice discharge increased by 77% since the 1970s (Mouginot et al., 2014 <sup>[[#fn:r953|953]]</sup> ), primarily from acceleration of Pine Island Glacier that began around 1945, Smith, Pope and Kohler glaciers around 1980, and Thwaites Glacier around 2000 (Mouginot et al., 2014 <sup>[[#fn:r954|954]]</sup> ; Konrad et al., 2017 <sup>[[#fn:r955|955]]</sup> ; Smith et al., 2017c <sup>[[#fn:r956|956]]</sup> ). Dynamic thinning in the ASE and western AP accounted for 88% of the –36 ± 15 Gt yr –1 increase in AIS mass loss from 2008 to 2015 (Gardner et al., 2018 <sup>[[#fn:r957|957]]</sup> ). Glacier acceleration of up to 25% also affected the Getz Ice Shelf margin from 2007 to 2014 (Chuter et al., 2017 <sup>[[#fn:r958|958]]</sup> ).

Reduction or loss of ice shelf buttressing has dominated AIS dynamic thinning ( ''high confidence'' ). Ice shelves buttress 90% of AIS outflow (Depoorter et al., 2013 <sup>[[#fn:r959|959]]</sup> ; Rignot et al., 2014 <sup>[[#fn:r960|960]]</sup> ; Fürst et al., 2016 <sup>[[#fn:r961|961]]</sup> ; Reese et al., 2018 <sup>[[#fn:r962|962]]</sup> ), and ice shelf thinning increased in WAIS by 70% in the decade to 2012, averaged 8% thickness loss from 1994 to 2012 in the ASE (Paolo et al., 2015 <sup>[[#fn:r963|963]]</sup> ), and explains the post-2009 onset of rapid dynamic thinning on the southern-AP Bellingshausen Sea coast (Wouters et al., 2015 <sup>[[#fn:r964|964]]</sup> ; Hogg et al., 2017 <sup>[[#fn:r965|965]]</sup> ; Martin-Español et al., 2017 <sup>[[#fn:r966|966]]</sup> ) (Figure SM3.8). Grounding line retreat, an indicator of thinning, has been observed with ''high confidence'' (Rignot et al., 2014 <sup>[[#fn:r967|967]]</sup> ; Christie et al., 2016 <sup>[[#fn:r968|968]]</sup> ; Hogg et al., 2017 <sup>[[#fn:r969|969]]</sup> ; Konrad et al., 2018 <sup>[[#fn:r970|970]]</sup> ; Roberts et al., 2018 <sup>[[#fn:r971|971]]</sup> ). From 2010 to 2016, 22%, 3% and 10% of grounding lines in WAIS, EAIS and the AP respectively retreated at rates faster than 25 m yr −1 (the average pace since the Last Glacial Maximum; Konrad et al., 2018), with highest rates along the Amundsen and Bellingshausen Sea coasts, and around Totten Glacier, Wilkes Land, EAIS (Konrad et al., 2018), where dynamic thinning has occurred at least since 1979 (Roberts et al., 2018; Rignot et al., 2019 <sup>[[#fn:r972|972]]</sup> ). Ice shelf collapse has driven dynamic thinning in the northern AP over recent decades ( ''high confidence'' ) (Seehaus et al., 2015 <sup>[[#fn:r973|973]]</sup> ; Wuite et al., 2015 <sup>[[#fn:r974|974]]</sup> ; Friedl et al., 2018 <sup>[[#fn:r975|975]]</sup> ; Rott et al., 2018 <sup>[[#fn:r976|976]]</sup> ).

ASE ice shelf basal melting, grounding line retreat and dynamic thinning have varied with ocean forcing ( ''medium confidence'' ) (Dutrieux et al., 2014 <sup>[[#fn:r977|977]]</sup> ; Paolo et al., 2015 <sup>[[#fn:r978|978]]</sup> ; Christianson et al., 2016 <sup>[[#fn:r979|979]]</sup> ; Jenkins et al., 2018 <sup>[[#fn:r980|980]]</sup> ) but this variability is superimposed on sustained mass losses compatible with the onset of Marine Ice Sheet Instability (MISI) for several major glaciers ( ''medium confidence'' ) (Favier et al., 2014 <sup>[[#fn:r981|981]]</sup> ; Joughin et al., 2014 <sup>[[#fn:r982|982]]</sup> ; Mouginot et al., 2014 <sup>[[#fn:r983|983]]</sup> ; Rignot et al., 2014 <sup>[[#fn:r984|984]]</sup> ; Christianson et al., 2016 <sup>[[#fn:r985|985]]</sup> ). Whether unstable WAIS retreat has begun or is imminent remains a critical uncertainty (Cross-Chapter Box 8 in Chapter 3).

Mass gains due to increased snowfall have somewhat offset dynamic-thinning losses ( ''high confidence'' ). On the AP, snowfall began to increase in the 1930s, accelerated in the 1990s (Thomas et al., 2015 <sup>[[#fn:r986|986]]</sup> ; Goodwin et al., 2016 <sup>[[#fn:r987|987]]</sup> ), and now offsets sea-level rise by 6.2 ± 1.7 mm per century (Medley and Thomas, 2018 <sup>[[#fn:r988|988]]</sup> ). EAIS and WAIS snowfall increases offset 20th century sea-level rise by 7.7 ± 4.0 mm and 2.8 ± 1.7 mm respectively (Medley and Thomas, 2018 <sup>[[#fn:r989|989]]</sup> ) ( ''medium confidence'' ). AIS snowfall increased by 4 ± 1 then 14 ± 1 Gt per decade over the 19th and 20th centuries, of which EAIS contributed 10% (Thomas et al., 2017b <sup>[[#fn:r990|990]]</sup> ). Longer records suggest either an AIS snowfall decrease over the last 1000 years (Thomas et al., 2017a <sup>[[#fn:r991|991]]</sup> ) or a statistically negligible change over the last 800 years ( ''low confidence'' ) (Frezzotti et al., 2013 <sup>[[#fn:r992|992]]</sup> ).

Mass balance contributions from ice sheet basal melting were not described in AR5 (IPCC, 2013 <sup>[[#fn:r993|993]]</sup> ) and the sensitivity of the AIS subglacial hydrological system to climate change is poorly understood. Around half of the AIS bed melts (Siegert et al., 2017 <sup>[[#fn:r994|994]]</sup> ), producing ~65 Gt yr –1 of water (Pattyn, 2010 <sup>[[#fn:r995|995]]</sup> ) ( ''low confidence'' ), some of which refreezes (Bell, 2008 <sup>[[#fn:r996|996]]</sup> ) and some accumulates in subglacial lakes with a total volume of 10s of 1000s of km 3 (Popov and Masolov, 2007 <sup>[[#fn:r997|997]]</sup> ; Lipenkov et al., 2016 <sup>[[#fn:r998|998]]</sup> ; Siegert, 2017 <sup>[[#fn:r999|999]]</sup> ). This system contributes fresh water and nutrients to the ocean (Section 3.3.3.3) (Fricker et al., 2007 <sup>[[#fn:r1000|1000]]</sup> ; Siegert et al., 2007 <sup>[[#fn:r1001|1001]]</sup> ; Carter and Fricker, 2012 <sup>[[#fn:r1002|1002]]</sup> ; Horgan et al., 2013 <sup>[[#fn:r1003|1003]]</sup> ; Le Brocq, 2013 <sup>[[#fn:r1004|1004]]</sup> ; Flament et al., 2014 <sup>[[#fn:r1005|1005]]</sup> ; Siegert et al., 2016 <sup>[[#fn:r1006|1006]]</sup> ), and lubricates glacier sliding (e.g., Dow et al., 2018b). Changes in the ice sheet thickness can redistribute subglacial water, affecting drainage pathways and ice flow (Fricker et al., 2016 <sup>[[#fn:r1007|1007]]</sup> ), but hydrological observations are very scarce.

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==== 3.3.1.3 Greenland Ice Sheet Mass Change ====

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The Greenland Ice Sheet (GIS) experienced a marked shift to strongly negative mass balance between the early 1990s and mid–2000s ( ''very high confidence'' ) (Shepherd et al., 2012 <sup>[[#fn:r1008|1008]]</sup> ; Schrama et al., 2014 <sup>[[#fn:r1009|1009]]</sup> ; Velicogna et al., 2014 <sup>[[#fn:r1010|1010]]</sup> ; van den Broeke et al., 2016 <sup>[[#fn:r1011|1011]]</sup> ; Bamber et al., 2018 <sup>[[#fn:r1012|1012]]</sup> ; King et al., 2018 <sup>[[#fn:r1013|1013]]</sup> ; Sandberg Sørensen et al., 2018 <sup>[[#fn:r1014|1014]]</sup> ; WCRP, 2018 <sup>[[#fn:r1015|1015]]</sup> ). It is ''extremely likely'' that the 2002–2011 and 2012–2016 ice losses were greater than in the 1992–2001 period (Bamber et al., 2018 <sup>[[#fn:r1016|1016]]</sup> ) (Table 3.3, Figure 3.7, SM3.3.1.3). GIS mass balance is characterised by large interannual variability (e.g., van den Broeke et al., 2017) but from 2005 to 2016, GIS was the largest terrestrial contributor to global sea level rise (WCRP, 2018 <sup>[[#fn:r1017|1017]]</sup> ).

A geodetic reconstruction of past ice sheet elevations indicates a GIS mass change of –75.1 ± 29.4 Gt yr –1 from 1900 to 1983, –73.8 ± 40.5 Gt yr –1 from 1983 to 2003, and –186.4 ± 18.9 Gt yr –1 from 2003 to 2010, with the losses consistently concentrated along the northwest and southeast coasts, and more locally in the southwest and on the large west coast Jakobshavn Glacier, though intensifying and spreading to the remainder of the coastal ice sheet in the latest period (Kjeldsen et al., 2015 <sup>[[#fn:r1018|1018]]</sup> ). Palaeo evidence also suggests that the GIS has contributed substantially to sea level rise during past warm intervals (Cross-Chapter Box 8 in Chapter 3).

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==== 3.3.1.4 Components of Greenland Ice Sheet Mass Change ====

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Ongoing GIS mass loss over recent years has resulted from a combined increase in dynamic thinning and a decrease in SMB. Of these, reduced SMB due to an increase in surface melting and runoff recently came to dominate ( ''high confidence'' ) (Andersen et al., 2015 <sup>[[#fn:r1019|1019]]</sup> ; Fettweis et al., 2017 <sup>[[#fn:r1020|1020]]</sup> ; van den Broeke et al., 2017 <sup>[[#fn:r1021|1021]]</sup> ; King et al., 2018 <sup>[[#fn:r1022|1022]]</sup> ), accounting for 42% of losses for 2000–2005, 64% for 2005–2009 and 68% for 2009–2012 (Enderlin et al., 2014 <sup>[[#fn:r1023|1023]]</sup> ) (Figure 3.7).

The GIS was close to balance in the early years of the 1990s (Hanna et al., 2013 <sup>[[#fn:r1024|1024]]</sup> ; Khan et al., 2015 <sup>[[#fn:r1025|1025]]</sup> ), the interior above 2000 m altitude gained mass from 1961 to 1990 (Colgan et al., 2015 <sup>[[#fn:r1026|1026]]</sup> ) and both coastal and ice sheet sites experienced an increasing precipitation trend from 1890 to 2012 and 1890 to 2000 respectively (Mernild et al., 2015 <sup>[[#fn:r1027|1027]]</sup> ), but since the early 1990s multiple observations and modelling studies show strong warming and an increase in runoff ( ''very high confidence'' ). High-altitude GIS sites NEEM and Summit warmed by, respectively, 2.7°C ± 0.33°C over the past 30 years (Orsi et al., 2017 <sup>[[#fn:r1028|1028]]</sup> ) and by 2.7°C ± 0.3°C from 1982 to 2011 (McGrath et al., 2013 <sup>[[#fn:r1029|1029]]</sup> ), while satellite thermometry showed statistically significant widespread surface warming over northern GIS from 2000 to 2012 (Hall et al., 2013 <sup>[[#fn:r1030|1030]]</sup> ). The post-1990s period experienced the warmest GIS near-surface summer air temperatures of 1840–2010 (+1.1˚C) (statistically highly significant) (Box, 2013), and ice core analysis found the 2000–2010 decade to be the warmest for around 2000 years (Vinther et al., 2009 <sup>[[#fn:r1031|1031]]</sup> ; Masson-Delmotte et al., 2012 <sup>[[#fn:r1032|1032]]</sup> ), and possibly around 7000 years (Lecavalier et al., 2017 <sup>[[#fn:r1033|1033]]</sup> ) . This significant summer warming since the early 1990s increased GIS melt event duration (Mernild et al., 2017 <sup>[[#fn:r1034|1034]]</sup> ) and intensity to levels exceptional over at least 350 years (Trusel et al., 2018 <sup>[[#fn:r1035|1035]]</sup> ), and melt frequency to levels unprecedented for at least 470 years (Graeter et al., 2018 <sup>[[#fn:r1036|1036]]</sup> ). GIS melt intensity for 1994–2013 was two to fivefold the pre-industrial intensity ( ''medium confidence'' ) (Trusel et al., 2018 <sup>[[#fn:r1037|1037]]</sup> ). In response, GIS meltwater production and runoff increased (Hanna et al., 2012 <sup>[[#fn:r1038|1038]]</sup> ; Box, 2013; Fettweis et al., 2013 <sup>[[#fn:r1039|1039]]</sup> ; Tedstone et al., 2015 <sup>[[#fn:r1040|1040]]</sup> ; van den Broeke et al., 2016 <sup>[[#fn:r1041|1041]]</sup> ; Fettweis et al., 2017 <sup>[[#fn:r1042|1042]]</sup> ), resulting in 1994–2013 runoff being 33% higher the 20th century mean and 50% higher than the 18th century (Trusel et al., 2018 <sup>[[#fn:r1043|1043]]</sup> ), and 80% higher in a western-GIS marginal river catchment in 2003–2014 relative to 1976–2002 (Ahlstrom et al., 2017 <sup>[[#fn:r1044|1044]]</sup> ).

Only around half of the 1960–2014 surface melt ran off, most of the rest being retained in firn and snow (Steger et al., 2017 <sup>[[#fn:r1045|1045]]</sup> ), particularly in recently observed firn aquifers in south and west Greenland (Humphrey et al., 2012 <sup>[[#fn:r1046|1046]]</sup> ; Forster et al., 2013 <sup>[[#fn:r1047|1047]]</sup> ; Munneke et al., 2014 <sup>[[#fn:r1048|1048]]</sup> ; Poinar et al., 2017 <sup>[[#fn:r1049|1049]]</sup> ) that cover up to 5% of GIS (Miège et al., 2016 <sup>[[#fn:r1050|1050]]</sup> ; Steger et al., 2017 <sup>[[#fn:r1051|1051]]</sup> ) and stored around one fifth of the meltwater increase since the late 1990s (Noël et al., 2017) ( ''medium confidence'' ). While potential aquifer storage is equivalent to about a quarter of annual GIS melt production (Koenig et al., 2014 <sup>[[#fn:r1053|1053]]</sup> ; van den Broeke et al., 2016 <sup>[[#fn:r1054|1054]]</sup> ) and aquifers have spread to higher altitudes (Steger et al., 2017 <sup>[[#fn:r1055|1055]]</sup> ), their potential to buffer runoff has been reduced by firn densification (Polashenski et al., 2014 <sup>[[#fn:r1056|1056]]</sup> ), diversion of water to the bed via crevasses (Poinar et al., 2017 <sup>[[#fn:r1058|1058]]</sup> ), and the formation of ice layers that prevent drainage and promote surface ponding on the firn (Charalampidis et al., 2016) ( ''high confidence'' ). Such ponding lowers the firn albedo, promoting further melting ( ''high confidence'' ) (e.g., Charalampidis et al., 2015), but the extent of bare ice is a fivefold stronger control on melt (Ryan et al., 2019 <sup>[[#fn:r1059|1059]]</sup> ). Bare ice produced ~78% of runoff from 1960 to 2014, and its extent is expected to increase non-linearly as snow cover retreats to higher, flatter areas of ice sheet (Steger et al., 2017 <sup>[[#fn:r1060|1060]]</sup> ). This extent is not well reproduced in climate models, however, with biases of –6% to 13% (Ryan et al., 2019 <sup>[[#fn:r1061|1061]]</sup> ).

The remaining ~40% of non-SMB GIS mass loss from 1991 to 2015 has resulted from increased ice discharge due to dynamic thinning ( ''high confidence'' ) (Enderlin et al., 2014 <sup>[[#fn:r1062|1062]]</sup> ; van den Broeke et al., 2016 <sup>[[#fn:r1063|1063]]</sup> ; King et al., 2018 <sup>[[#fn:r1064|1064]]</sup> ) (Figure 3.7). From 2000 to 2016, dynamic thinning of 89% of GIS outlet glaciers accounted for –682 ± 31 Gt mass change, of which 92% came from the northwest and southeast GIS (King et al., 2018 <sup>[[#fn:r1065|1065]]</sup> ). Half came from only four glaciers (Jakobshavn Isbræ, Kangerdlugssuaq, Koge Bugt, and Ikertivaq South) (Enderlin et al., 2014 <sup>[[#fn:r1066|1066]]</sup> ). Glacier thinning has decreased glacier discharge, however, reducing the dynamic contribution to GIS mass loss (e.g., from 58% from 2000 to 2005 to 32% between 2009 and 2012; Enderlin et al., 2014). Furthermore, there is now ''high confidence'' that for most of the GIS, increased surface melt has not led to sustained increases in glacier flux on annual timescales because subglacial drainage networks have evolved to drain away the additional water inputs (e.g., Sole et al., 2013; Tedstone et al., 2015 <sup>[[#fn:r1068|1068]]</sup> ; Stevens et al., 2016 <sup>[[#fn:r1069|1069]]</sup> ; Nienow et al., 2017 <sup>[[#fn:r1070|1070]]</sup> ; King et al., 2018).

<div id="section-3-3-1-5-drivers-of-ice-sheet-mass-change"></div>

<span id="drivers-of-ice-sheet-mass-change"></span>
==== 3.3.1.5 Drivers of ice sheet mass change ====

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<span id="ocean-drivers"></span>
===== 3.3.1.5.1 Ocean drivers =====

The reduction of ice shelf buttressing that has dominated AIS mass loss (Section 3.3.1.2) has been driven primarily by increases in sub-ice shelf melting (Khazendar et al., 2013 <sup>[[#fn:r1071|1071]]</sup> ; Pollard et al., 2015 <sup>[[#fn:r1072|1072]]</sup> ; Cook et al., 2016 <sup>[[#fn:r1073|1073]]</sup> ; Rintoul et al., 2016 <sup>[[#fn:r1074|1074]]</sup> ; Walker and Gardner, 2017 <sup>[[#fn:r1075|1075]]</sup> ; Adusumilli et al., 2018 <sup>[[#fn:r1076|1076]]</sup> ; Dow et al., 2018a <sup>[[#fn:r1077|1077]]</sup> ; Minchew et al., 2018 <sup>[[#fn:r1078|1078]]</sup> ) ( ''high confidence'' ). Shoaling of relatively warm Circumpolar Deep Water has controlled recent variability in melting in the Amundsen and Bellingshausen seas, Wilkes Land (Roberts et al., 2018 <sup>[[#fn:r1079|1079]]</sup> ) and the AP ( ''medium confidence'' ) (Jacobs et al., 2011 <sup>[[#fn:r1080|1080]]</sup> ; Pritchard et al., 2012 <sup>[[#fn:r1081|1081]]</sup> ; Depoorter et al., 2013 <sup>[[#fn:r1082|1082]]</sup> ; Rignot et al., 2013 <sup>[[#fn:r1083|1083]]</sup> ; Dutrieux et al., 2014 <sup>[[#fn:r1084|1084]]</sup> ; Paolo et al., 2015 <sup>[[#fn:r1085|1085]]</sup> ; Wouters et al., 2015 <sup>[[#fn:r1086|1086]]</sup> ; Christianson et al., 2016 <sup>[[#fn:r1087|1087]]</sup> ; Cook et al., 2016 <sup>[[#fn:r1088|1088]]</sup> ; Jenkins et al., 2018 <sup>[[#fn:r1089|1089]]</sup> ; Roberts et al., 2018 <sup>[[#fn:r1090|1090]]</sup> ). Changes in winds have driven this shoaling by affecting continental shelf edge undercurrents (Walker et al., 2013 <sup>[[#fn:r1091|1091]]</sup> ; Dutrieux et al., 2014 <sup>[[#fn:r1092|1092]]</sup> ; Kimura et al., 2017 <sup>[[#fn:r1093|1093]]</sup> ) and overturning in coastal polynyas (St ‐ Laurent et al., 2015 <sup>[[#fn:r1094|1094]]</sup> ; Webber et al., 2017 <sup>[[#fn:r1095|1095]]</sup> ) ( ''medium confidence'' ). Winds over the Amundsen Sea are highly variable, however, with complex interactions between SAM, El Niño/Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation, and the Amundsen Sea Low (Uotila et al., 2013 <sup>[[#fn:r1095|1095]]</sup> ; Li et al., 2014 <sup>[[#fn:r1096|1096]]</sup> ; Turner et al., 2016 <sup>[[#fn:r1097|1097]]</sup> ) (SM3.1.3).

Through their effects on Antarctic coastal ocean circulation, ENSO or other tropical-ocean variability may have triggered changes to Pine Island Glacier in the 1940s (Smith et al., 2017c <sup>[[#fn:r1098|1098]]</sup> ) and again in the 1970s and 1990s (Jenkins et al., 2018 <sup>[[#fn:r1099|1099]]</sup> ), and recent ENSO variability is correlated with recent changes in ice shelf thickness (Paolo et al., 2018 <sup>[[#fn:r1100|1100]]</sup> ) ( ''medium confidence'' ). Such coupling between wind variability, ocean upwelling, ice shelf melt, buttressing and glacier flow rate has also been observed in EAIS, at Totten Glacier, Wilkes Land (Greene et al., 2017 <sup>[[#fn:r1101|1101]]</sup> ).

Around Greenland, an anomalous inflow of subtropical water driven by wind changes, multi-decadal natural ocean variability (Andresen et al., 2012 <sup>[[#fn:r1102|1102]]</sup> ), and a long-term increase in the North Atlantic’s upper ocean heat content since the 1950s (Cheng et al., 2017 <sup>[[#fn:r1103|1103]]</sup> ), all contributed to a warming of the subpolar North Atlantic (Häkkinen et al., 2013 <sup>[[#fn:r1104|1104]]</sup> ) ( ''medium confidence'' ). Water temperatures near the grounding zone of GIS outlet glaciers are critically important to their calving rate (O’Leary and Christoffersen, 2013) ( ''medium confidence'' ), and warm waters have been observed interacting with major GIS outlet glaciers ( ''high confidence'' ) (e.g., Holland et al., 2008; Straneo et al., 2017 <sup>[[#fn:r1105|1105]]</sup> ).

The processes behind warm-water incursions in coastal Greenland that force glacier retreat remain unclear, however (Straneo et al., 2013 <sup>[[#fn:r1106|1106]]</sup> ; Xu et al., 2013b <sup>[[#fn:r1107|1107]]</sup> ; Bendtsen et al., 2015 <sup>[[#fn:r1108|1108]]</sup> ; Murray et al., 2015 <sup>[[#fn:r1109|1109]]</sup> ; Cowton et al., 2016 <sup>[[#fn:r1110|1110]]</sup> ; Miles et al., 2016 <sup>[[#fn:r1111|1111]]</sup> ), and there is ''low confidence'' in understanding coastal GIS glacier response to ocean forcing because submarine melt rates, calving rates (Rignot et al., 2010 <sup>[[#fn:r1112|1112]]</sup> ; Todd and Christoffersen, 2014 <sup>[[#fn:r1113|1113]]</sup> ; Benn et al., 2017 <sup>[[#fn:r1114|1114]]</sup> ), bed and fjord geometry and the roles of ice melange and subglacial discharge (Enderlin et al., 2013 <sup>[[#fn:r1115|1115]]</sup> ; Gladish et al., 2015 <sup>[[#fn:r1116|1116]]</sup> ; Slater et al., 2015 <sup>[[#fn:r1117|1117]]</sup> ; Morlighem et al., 2016 <sup>[[#fn:r1118|1118]]</sup> ; Rathmann et al., 2017 <sup>[[#fn:r1119|1119]]</sup> ) are poorly understood, and extrapolation from a small sample of glaciers is impractical (Moon et al., 2012 <sup>[[#fn:r1120|1120]]</sup> ; Carr et al., 2013 <sup>[[#fn:r1121|1121]]</sup> ; Straneo et al., 2016 <sup>[[#fn:r1122|1122]]</sup> ; Cowton et al., 2018 <sup>[[#fn:r1123|1123]]</sup> ).

<div id="section-3-3-1-5-drivers-of-ice-sheet-mass-change-block-2"></div>

<span id="atmospheric-drivers"></span>
===== 3.3.1.5.2 Atmospheric drivers =====

Snow accumulation and surface melt in Antarctica are influenced by the Southern Hemisphere extratropical circulation (SM3.1.3), which has intensified and shifted poleward in austral summer from 1950 to 2012 (Arblaster et al., 2014 <sup>[[#fn:r1124|1124]]</sup> ; Swart et al., 2015a <sup>[[#fn:r1125|1125]]</sup> ) ( ''medium confidence'' ). The austral summer SAM has been in its most positive extended state for the past 600 years (Abram et al., 2014 <sup>[[#fn:r1126|1126]]</sup> ; Dätwyler et al., 2017 <sup>[[#fn:r1127|1127]]</sup> ), and from 1979 to 2013 has contributed to intensified atmospheric circulation and increasing and decreasing snowfall in the western and eastern AP respectively (Marshall et al., 2017 <sup>[[#fn:r1128|1128]]</sup> ) ( ''medium confidence'' ). WAIS accumulation trends (Section 3.3.1.2) resulted from a deepening of the Amundsen Sea Low over recent decades (Raphael et al., 2016 <sup>[[#fn:r1129|1129]]</sup> ) ( ''high confidence'' ).

During the 1990s, WAIS experienced record surface warmth relative to the past 200 years, though similar conditions occurred for 1% of the preceding 2000 years (Steig et al., 2013 <sup>[[#fn:r1130|1130]]</sup> ), and WAIS surface melting remains limited. In contrast, AP surface melting has intensified since the mid-20th century and the last three decades were unprecedented over 1000 years (Abram et al., 2013a <sup>[[#fn:r1131|1131]]</sup> ). The northeast AP began warming 600 years ago and past-century rates were unusual over 2000 years (Mulvaney et al., 2012 <sup>[[#fn:r1132|1132]]</sup> ; Stenni et al., 2017 <sup>[[#fn:r1133|1133]]</sup> ). Increased föhn winds due to the more positive SAM (Cape et al., 2015 <sup>[[#fn:r1134|1134]]</sup> ) caused increased surface melting on the Larsen ice shelves (Grosvenor et al., 2014 <sup>[[#fn:r1135|1135]]</sup> ; Luckman et al., 2014 <sup>[[#fn:r1136|1136]]</sup> ; Elvidge et al., 2015 <sup>[[#fn:r1137|1137]]</sup> ) and after 11,000 years intact, the 2002 melt-driven collapse of the Larsen B ice shelf followed strong warming between the mid–1950s and the late 1990s (Domack et al., 2005 <sup>[[#fn:r1138|1138]]</sup> ) ( ''medium confidence'' ).

In Greenland, associations between atmospheric pressure indices such as the North Atlantic Oscillation (NAO) and temperature, insolation and snowfall indicate with ''high confidence'' that, as in Antarctica, variability of large-scale atmospheric circulation is an important driver of SMB changes (Fettweis et al., 2013 <sup>[[#fn:r1139|1139]]</sup> ; Tedesco et al., 2013 <sup>[[#fn:r1140|1140]]</sup> ; Ding et al., 2014 <sup>[[#fn:r1141|1141]]</sup> ; Tedesco et al., 2016b <sup>[[#fn:r1142|1142]]</sup> ; Ding et al., 2017 <sup>[[#fn:r1143|1143]]</sup> ; Hofer et al., 2017 <sup>[[#fn:r1144|1144]]</sup> ). A post-1990s decrease in summer NAO reflects increased anticyclonic weather (e.g., Tedesco et al., 2013; Hanna et al., 2015 <sup>[[#fn:r1145|1145]]</sup> ) that advected warm air over the GIS, explaining ~70% of summer surface warming from 2003 to 2013 (Fettweis et al., 2013 <sup>[[#fn:r1146|1146]]</sup> ; Tedesco et al., 2013 <sup>[[#fn:r1147|1147]]</sup> ; Mioduszewski et al., 2016 <sup>[[#fn:r1148|1148]]</sup> ), and reduced the cloud cover, increasing shortwave insolation (Tedesco et al., 2013 <sup>[[#fn:r1149|1149]]</sup> ) that, combined with albedo feedbacks (Box et al., 2012 <sup>[[#fn:r1150|1150]]</sup> ; Charalampidis et al., 2015 <sup>[[#fn:r1151|1151]]</sup> ; Tedesco et al., 2016a <sup>[[#fn:r1152|1152]]</sup> ; Stibal et al., 2017 <sup>[[#fn:r1153|1153]]</sup> ; Ryan et al., 2018 <sup>[[#fn:r1154|1154]]</sup> ) ( ''high confidence'' ), explains most of the post-1990s melt increase (Hofer et al., 2017 <sup>[[#fn:r1155|1155]]</sup> ). These drivers culminated in July 2012 in exceptional warmth and surface melt up to the ice sheet summit (Nghiem et al., 2012 <sup>[[#fn:r1156|1156]]</sup> ; Tedesco et al., 2013 <sup>[[#fn:r1157|1157]]</sup> ; Hanna et al., 2014 <sup>[[#fn:r1158|1158]]</sup> ; Hanna et al., 2016 <sup>[[#fn:r1159|1159]]</sup> ; McLeod and Mote, 2016 <sup>[[#fn:r1160|1160]]</sup> ).

<div id="section-3-3-1-6natural-and-anthropogenic-forcing"></div>

<span id="natural-and-anthropogenic-forcing"></span>
==== 3.3.1.6 Natural and Anthropogenic Forcing ====

<div id="section-3-3-1-6natural-and-anthropogenic-forcing-block-1"></div>

There is ''medium agreement'' but ''limited evidence'' of anthropogenic forcing of AIS mass balance through both SMB and glacier dynamics ( ''low confidence'' ). Partitioning between natural and human drivers of atmospheric and ocean circulation changes remains very uncertain. Partitioning is challenging because, along with the effects of greenhouse gas increases and stratospheric ozone depletion (Waugh et al., 2015 <sup>[[#fn:r1161|1161]]</sup> ; England et al., 2016 <sup>[[#fn:r1162|1162]]</sup> ; Li et al., 2016a <sup>[[#fn:r1163|1163]]</sup> ), atmospheric and ocean variability in the areas of greatest AIS mass change are affected by a complex chain of processes (e.g., Fyke et al., 2018; Zhang et al., 2018a <sup>[[#fn:r1164|1164]]</sup> ) that exhibit considerable natural variability and have multiple interacting links to sea surface conditions in the Pacific (Schneider et al., 2015 <sup>[[#fn:r1165|1165]]</sup> ; England et al., 2016 <sup>[[#fn:r1166|1166]]</sup> ; Raphael et al., 2016 <sup>[[#fn:r1167|1167]]</sup> ; Clem et al., 2017 <sup>[[#fn:r1168|1168]]</sup> ; Steig et al., 2017 <sup>[[#fn:r1169|1169]]</sup> ; Paolo et al., 2018 <sup>[[#fn:r1170|1170]]</sup> ) and Atlantic (Li et al., 2014 <sup>[[#fn:r1171|1171]]</sup> ), with additional local feedbacks (e.g., Stammerjohn et al., 2012; Goosse and Zunz, 2014 <sup>[[#fn:r1172|1172]]</sup> ). Recent AP warming and consequent ice shelf collapses have evidence of a link to anthropogenic ozone and greenhouse gas forcing via the SAM (e.g., Marshall, 2004; Shindell, 2004 <sup>[[#fn:r1173|1173]]</sup> ; Arblaster and Meehl, 2006 <sup>[[#fn:r1174|1174]]</sup> ; Marshall et al., 2006 <sup>[[#fn:r1175|1175]]</sup> ; Abram et al., 2014 <sup>[[#fn:r1176|1176]]</sup> ) and to anthropogenic Atlantic sea surface warming via the Atlantic Multidecadal Oscillation (e.g., Li et al., 2014). This warming was highly unusual over the last 1000 years but not unprecedented, and along with subsequent cooling is within the bounds of the large natural decadal-scale climate variability in this region (Mulvaney et al., 2012 <sup>[[#fn:r1177|1177]]</sup> ; Turner et al., 2016 <sup>[[#fn:r1178|1178]]</sup> ). More broadly over the AP and coastal WAIS where dynamic mass losses are concentrated, natural variability in atmospheric and ocean forcing appear to dominate observed mass balance ( ''medium confidence'' ) (Smith and Polvani, 2017 <sup>[[#fn:r1179|1179]]</sup> ; Jenkins et al., 2018 <sup>[[#fn:r1180|1180]]</sup> ).

Evidence exists for an anthropogenic role in the atmospheric circulation (NAO) changes that have driven GIS mass loss (Section 3.3.1.5.2) ( ''medium confidence'' ), although this awaits formal attribution testing (e.g., Easterling et al., 2016). Arctic amplification of anthropogenic warming (e.g., Serreze et al., 2009) affects atmospheric circulation (Francis and Vavrus, 2015 <sup>[[#fn:r1181|1181]]</sup> ; Mann et al., 2017 <sup>[[#fn:r1182|1182]]</sup> ) and has reduced sea ice extent (Section 3.2.1.1.1), feeding back to exacerbate both warming and NAO changes (Screen and Simmonds, 2010 <sup>[[#fn:r1183|1183]]</sup> ) that impact GIS mass balance. Negative-NAO wind patterns increased GIS melt observed in a 40-year runoff signal (Ahlstrom et al., 2017 <sup>[[#fn:r1184|1184]]</sup> ), and an increase in melting beginning in the mid-1800s closely followed the onset of industrial era Arctic warming and emerged beyond the range of natural variability in the last few decades (Graeter et al., 2018 <sup>[[#fn:r1185|1185]]</sup> ; Trusel et al., 2018 <sup>[[#fn:r1186|1186]]</sup> ) (Section 3.3.1.4).

<div id="section-3-3-1-7-ice-sheet-projections"></div>

<span id="ice-sheet-projections"></span>
==== 3.3.1.7 Ice sheet projections ====

<div id="section-3-3-1-7-ice-sheet-projections-block-1"></div>

Section 4.2 assesses the sea level impacts from observed and projected changes in ice sheets.

<span id="polar-glacier-changes"></span>
=== 3.3.2 Polar Glacier Changes ===

<div id="section-3-3-2-1-observations-components-of-change-and-drivers"></div>

<span id="observations-components-of-change-and-drivers"></span>
==== 3.3.2.1 Observations, Components of Change, and Drivers ====

<div id="section-3-3-2-1-observations-components-of-change-and-drivers-block-1"></div>

Chapter 3 assesses changes in polar glaciers in the Canadian and Russian Arctic, Svalbard, Greenland and Antarctica, independent of the Greenland and Antarctic ice sheets (Figure 3.8). Glaciers in all other regions including Alaska, Scandinavia and Iceland are assessed in Chapter 2.

Changes in the mass of Arctic glaciers for the ‘present day’ (2006–2015) are assessed using a combination of satellite observations and direct measurements (Figure 3.8; Appendix 2.A, Table 1). During this period,  glacier mass loss was largest in the periphery of Greenland (–47 ± 16 Gt yr –1 ), followed by Arctic Canada North (-39 ± 8 Gt yr –1 ), Arctic Canada South (–33 ± 9 Gt yr –1 ), the Russian Arctic (–15 ± 12 Gt yr –1 ) and Svalbard and Jan Mayen (–9 ± 5 Gt yr –1 ). When combined with the Arctic regions covered in Chapter 2 (Alaska, the Yukon territory of Canada, Iceland and Scandinavia), Arctic glaciers as a whole lost mass at a rate of –213 ± 29 Gt yr –1 , a sea level contribution of 0.59 ± 0.08 mm yr –1 ( ''high confidence'' ). Overall during this period, Arctic glaciers caused a similar amount of sea level rise to the GIS (Section 3.3.1.3), but their rate of mass loss per unit area was larger (Bolch et al., 2013 <sup>[[#fn:r1187|1187]]</sup> ).

There is ''limited evidence'' ( ''high agreement)'' that the current rate of glacier mass loss is larger than at any time during the past 4000 years (Fisher et al., 2012 <sup>[[#fn:r1188|1188]]</sup> ; Zdanowicz et al., 2012 <sup>[[#fn:r1189|1189]]</sup> ). Further back in time during the early to mid- Holocene, pre-historic glacial deposits, ice core records, and numerical modelling evidence shows that many Arctic glaciers were at various stages similar to or smaller than present (Gilbert et al., 2017 <sup>[[#fn:r1190|1190]]</sup> ; Zekollari et al., 2017 <sup>[[#fn:r1191|1191]]</sup> ), experienced greater melt rates (Lecavalier et al., 2017 <sup>[[#fn:r1192|1192]]</sup> ), or may have disappeared altogether (Solomina et al., 2015 <sup>[[#fn:r1193|1193]]</sup> ) ( ''medium confidence'' ). This evidence, however, does not provide a complete assessment of the rates and magnitudes of past glacier mass loss.

Atmospheric circulation changes (Box et al., 2018 <sup>[[#fn:r1194|1194]]</sup> ) have led to pan-Arctic variability in glacier mass balance ( ''high confidence'' ), including different rates of retreat between eastern and western glaciers in Greenland’s periphery (Bjørk et al., 2018 <sup>[[#fn:r1195|1195]]</sup> ), and a high rate of surface melt in the Canadian Arctic (Gardner et al., 2013 <sup>[[#fn:r1196|1196]]</sup> ; Van Wychen et al., 2016; Millan et al., 2017 <sup>[[#fn:r1197|1197]]</sup> ) through persistently high summer air temperatures (Bezeau et al., 2014 <sup>[[#fn:r1198|1198]]</sup> ; McLeod and Mote, 2016 <sup>[[#fn:r1199|1199]]</sup> ). Atmospheric circulation anomalies from 2007 to 2012 associated with glacier mass loss are also linked to enhanced GIS melt (Section 3.3.1.4) and Arctic sea ice loss (Section 3.2.1.1), and exceed by a factor of two the interannual variability in daily mean pressure (sea level and 500 hPa) of the Arctic region over the 1871–2014 period (Belleflamme et al., 2015 <sup>[[#fn:r1203|1203]]</sup> ) (Section 3.3.1.6).

Increased surface melt on Arctic glaciers has led to a positive feedback from lowered surface albedo, causing further melt (Box et al., 2012 <sup>[[#fn:r1204|1204]]</sup> ), and in Svalbard, mean glacier albedo has reduced between 1979 and 2015 (Möller and Möller, 2017 <sup>[[#fn:r1205|1205]]</sup> ). Across the Arctic, increased surface melt and subsequent ice-layer formation via refreezing within snow and firn also reduces the ability of glaciers to store meltwater, increasing runoff (Zdanowicz et al., 2012 <sup>[[#fn:r1206|1206]]</sup> ; Gascon et al., 2013a <sup>[[#fn:r1207|1207]]</sup> ; Gascon et al., 2013b <sup>[[#fn:r1208|1208]]</sup> ; Noël et al., 2017 <sup>[[#fn:r1209|1209]]</sup> ; Noël et al., 2018 <sup>[[#fn:r1210|1210]]</sup> ).

Between the 1990s and 2017, tidewater glaciers have exhibited regional patterns in glacier dynamics; glaciers in Arctic Canada have largely decelerated, while glaciers in Svalbard and the Russian Arctic have accelerated (Van Wychen et al., 2016; Strozzi et al., 2017). Annual retreat rates of tidewater glaciers in Svalbard and the Russian Arctic for 2000–2010, have increased by a factor 2 and 2.5 respectively, between 1992 and 2000 (Carr et al., 2017). Acceleration due to surging (an internal dynamic instability) of a few key glaciers has dominated dynamic ice discharge on time-scales of years to decades (Van Wychen et al., 2014; Dunse et al., 2015).

The recent acceleration and surge behaviour of polythermal glaciers in Svalbard and the Russian Arctic is caused by destabilisation of the marine termini due to increased surface melt, and changes in basal temperature, lubrication and weakening of subglacial sediments (Dunse et al., 2015; Sevestre et al., 2018; Willis et al., 2018) or terminus thinning and response to warmer ocean temperatures (McMillan et al., 2014a) ( ''low confidence'' ). Iceberg calving rates in Svalbard are linked to ocean temperatures which control rates of submarine melt (Luckman et al., 2015; Vallot et al., 2018) ( ''medium confidence'' ). Rapid disintegration of ice shelves in the Canadian and Russian Arctic continues and has led to acceleration and thinning in tributary-glacier basins ( ''high confidence'' ) (Willis et al., 2015; Copland and Mueller, 2017).

Little information is available on Holocene and historic changes in glaciers in Antarctica (separate from the ice sheet), and on sub-Antarctic islands (Hodgson et al., 2014). Mass changes of glaciers in these regions between 2006 and 2015 (–90 ± 860 Gt yr –1 ) have ''low confidence'' as they are based on a single data compilation with large uncertainties in the Antarctic region (Zemp et al., 2019) (Figure 3.8). ''Limited evidence'' with ''high agreement'' from individual glaciers suggests that regional variability in glacier mass changes may be linked to changes in the large-scale Southern Hemisphere atmospheric circulation (Section 3.3.1.5.2). On islands adjacent to the AP, glaciers experienced retreat and mass loss during the mid to late 20th century, but since around 2009 there has been a reduction in mass loss rate or a return to slightly positive balance (Navarro et al., 2017; Oliva et al., 2017). Reduced mass loss has been linked to increased winter snow accumulation and decreased summer melt at these locations, associated with recent deepening of the circumpolar pressure trough (Oliva et al., 2017). Conversely, on the sub-Antarctic Kerguelen Islands, increased glacier mass loss (Verfaillie et al., 2015) may be due to reduced snow accumulation rather than increased air temperature as a result of southward migration of storm tracks (Favier et al., 2016).

<div id="section-3-3-2-1-observations-components-of-change-and-drivers-block-2"></div>

<span id="figure-3.8"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 3.8'''

<span id="glacier-mass-budgets-for-the-six-polar-regions-assessed-in-chapter-3.-glacier-mass-budgets-for-all-other-regions-including-iceland-scandinavia-and-alaska-are-shown-in-chapter-2-figure-2.4.-regional-time-series-of-annual-mass-change-are-based-on-glaciological-and-geodetic-balances-zemp-et-al.-2019.-superimposed-are-multi-year-averages-by-wouters"></span>
<!-- IMG CAPTION -->
'''Glacier mass budgets for the six polar regions assessed in Chapter 3. Glacier mass budgets for all other regions (including Iceland, Scandinavia and Alaska) are shown in Chapter 2, Figure 2.4. Regional time series of annual mass change are based on glaciological and geodetic balances (Zemp et al., 2019). Superimposed are multi-year averages by Wouters […]'''
<!-- IMG FILE -->
[[File:417d2dbe37809ab2795a78c966102cf8 IPCC-SROCC-CH_3_8.jpg]]

Glacier mass budgets for the six polar regions assessed in Chapter 3. Glacier mass budgets for all other regions (including Iceland, Scandinavia and Alaska) are shown in Chapter 2, Figure 2.4. Regional time series of annual mass change are based on glaciological and geodetic balances (Zemp et al., 2019 <sup>[[#fn:r1200|1200]]</sup> ). Superimposed are multi-year averages by Wouters et al. (2019) and Gardner et al. (2013) from the Gravity Recovery and Climate Experiment (GRACE). Estimates by Gardner et al. (2013) were used in the IPCC 5th Assessment Report (AR5). Additional regional estimates in some regions are listed in Appendix 2.1, Table 1. Annual and time-averaged mass-budget estimates include the errors reported in each study. Glacier outlines and areas are based on RGI Consortium (2017).

<!-- END IMG -->
<div id="section-3-3-2-2projections"></div>

<span id="projections"></span>
==== 3.3.2.2 Projections ====

<div id="section-3-3-2-2projections-block-1"></div>

Projections of all glaciers, including those in polar regions, are covered in Cross-Chapter Box 6 in Chapter 2.

<span id="consequences-and-impacts"></span>
=== 3.3.3 Consequences and Impacts ===

<div id="section-3-3-3-1sea-level"></div>

<span id="sea-level"></span>
==== 3.3.3.1 Sea Level ====

<div id="section-3-3-3-1sea-level-block-1"></div>

Chapter 4 assesses the sea level impacts from observed and projected changes in ice sheets (Section 3.3.1) and polar glaciers (Section 3.3.2), including uncertainties related to marine ice sheets (Cross-Chapter Box 8 in Chapter 3).

<div id="section-3-3-3-2physical-oceanography"></div>

<span id="physical-oceanography-1"></span>
==== 3.3.3.2 Physical Oceanography ====

<div id="section-3-3-3-2physical-oceanography-block-1"></div>

The major large-scale impacts of freshwater release from Greenland on ocean circulation relate to the potential modulation/inhibition of the formation of water masses that represent the headwaters of the Atlantic Meridional Overturning Circulation. The timescales and likelihood of such effects are assessed separately in Chapter 6 (Section 6.7). Freshwater release also affects local circulation within fjords through two principle mechanisms; subglacial release from tidewater glaciers enhances buoyancy driven circulation, whereas runoff from land-terminating glaciers contributes to surface layer freshening and estuarine circulation (Straneo and Cenedese, 2015 <sup>[[#fn:r1229|1229]]</sup> ). There is ''limited evidence'' that freshening occurred between 2003 and 2015 in North East Greenland fjords and coastal waters (Sejr et al., 2017 <sup>[[#fn:r1230|1230]]</sup> ).

For Antarctica, freshwater input to the ocean from the ice sheet is divided approximately equally between melting of calved icebergs and of ice shelves ''in situ'' (Depoorter et al., 2013 <sup>[[#fn:r1231|1231]]</sup> ; Rignot et al., 2014 <sup>[[#fn:r1232|1232]]</sup> ). There is ''high confidence'' that the input of ice shelf meltwater has increased in the Amundsen and Bellingshausen Seas since the 1990s, but ''low confidence'' in trends in other sectors (Paolo et al., 2015 <sup>[[#fn:r1233|1233]]</sup> ).

Freshwater injected from the AIS affect water mass circulation and transformation, though sea ice dominates upper ocean properties away from the Antarctic ice shelves (Abernathey et al., 2016 <sup>[[#fn:r1234|1234]]</sup> ; Haumann et al., 2016 <sup>[[#fn:r1235|1235]]</sup> ). Over the ice shelf regions, where dense waters sink and flood the global ocean abyss, the role of glacial freshwater input is clearer. From 1980 to 2012, the salinity of Antarctic Bottom Water reduced by an amount equivalent to 73 ± 26 Gt y –1 of freshwater added, around half the estimated increase in freshwater input by Antarctic glacial discharge up to that time (Purkey and Johnson, 2013 <sup>[[#fn:r1236|1236]]</sup> ). In some places, notably the Indian-Australian sector, Antarctic Bottom Water freshening may be accelerating (Menezes et al., 2017 <sup>[[#fn:r1237|1237]]</sup> ). There is ''medium confidence'' in an overall freshening trend and ''low confidence'' that this is accelerating, given the sparsity of information and significant interannual variability in Antarctic Bottom Water properties at other export locations (Meijers et al., 2016 <sup>[[#fn:r1238|1238]]</sup> ).

For the Southern Ocean, there is ''limited evidence'' for stratification changes in the post-AR5 period, and ''low confidence'' in how stratification changes are affecting sea ice and basal ice shelf melt. An increase in stratification caused by release of freshwater from the AIS was invoked as a mechanism to suppress vertical heat flux and permit an increase in sea ice extent (Bintanja et al., 2013 <sup>[[#fn:r1239|1239]]</sup> ; Bronselaer et al., 2018 <sup>[[#fn:r1240|1240]]</sup> ; Purich et al., 2018 <sup>[[#fn:r1241|1241]]</sup> ), though some studies conclude that glacial freshwater input is insufficient to cause a significant sea ice expansion (Swart and Fyfe, 2013 <sup>[[#fn:r1242|1242]]</sup> ; Pauling et al., 2017 <sup>[[#fn:r1243|1243]]</sup> ) (Section 3.2.1.1). In contrast, where warm water intrusions drive melting within ice shelf cavities, a significant entrained heat flux to the surface can exist and increase stratification and potentially reduce sea ice extent (Jourdain et al., 2017 <sup>[[#fn:r1244|1244]]</sup> ; Merino et al., 2018 <sup>[[#fn:r1245|1245]]</sup> ). It has been argued that freshening from glacial melt can enhance basal melting of ice shelves by reducing dense water production and modulating oceanic heat flow into ice shelf cavities (Silvano et al., 2018 <sup>[[#fn:r1246|1246]]</sup> ).

<div id="section-3-3-3-3biogeochemistry"></div>

<span id="biogeochemistry"></span>
==== 3.3.3.3 Biogeochemistry ====

<div id="section-3-3-3-3biogeochemistry-block-1"></div>

Both polar ice sheets have the potential to release dissolved and sediment-bound nutrients and organic carbon directly to the surface ocean via subglacial and surface meltwater, icebergs, melting of the base of ice shelves (Shadwick et al., 2013 <sup>[[#fn:r1247|1247]]</sup> ; Wadham et al., 2013 <sup>[[#fn:r1248|1248]]</sup> ; Hood et al., 2015 <sup>[[#fn:r1249|1249]]</sup> ; Herraiz-Borreguero et al., 2016 <sup>[[#fn:r1250|1250]]</sup> ; Raiswell et al., 2016 <sup>[[#fn:r1251|1251]]</sup> ; Yager et al., 2016; Hodson et al., 2017), in addition to indirectly stimulating nutrient input via upwelling associated with subglacial meltwater plumes (Meire et al., 2016b; Cape et al., 2018 <sup>[[#fn:r1272|1272]]</sup> ; Hopwood et al., 2018 <sup>[[#fn:r1253|1253]]</sup> ; Kanna et al., 2018 <sup>[[#fn:r1254|1254]]</sup> ) (Figure 3.9). These nutrient additions stimulate primary production in the surrounding ocean waters in some regions ( ''medium confidence'' ) (Gerringa et al., 2012 <sup>[[#fn:r1255|1255]]</sup> ; Death et al., 2014 <sup>[[#fn:r1256|1256]]</sup> ; Duprat et al., 2016 <sup>[[#fn:r1257|1257]]</sup> ; Arrigo et al., 2017b <sup>[[#fn:r1258|1258]]</sup> ). There is also some evidence to support melting ice sheets as source of contaminants (AMAP, 2015 <sup>[[#fn:r1259|1259]]</sup> ).

In Greenland, direct measurements suggest that meltwater is a significant source of bioavailable silica and iron (Bhatia et al., 2013 <sup>[[#fn:r1260|1260]]</sup> ; Hawkings et al., 2014 <sup>[[#fn:r1261|1261]]</sup> ; Meire et al., 2016a <sup>[[#fn:r1262|1262]]</sup> ; Hawkings et al., 2017 <sup>[[#fn:r1263|1263]]</sup> ) but may be less important for the supply of bioavailable forms of dissolved nitrogen or phosphorous (Hawkings et al., 2016 <sup>[[#fn:r1264|1264]]</sup> ; Wadham et al., 2016 <sup>[[#fn:r1265|1265]]</sup> ), which often limit the integrated primary production during summer in fjords (Meire et al., 2016a <sup>[[#fn:r1266|1266]]</sup> ; Hopwood et al., 2018 <sup>[[#fn:r1267|1267]]</sup> ). The offshore export of iron, however, has been linked to primary productivity in surface ocean waters in the Labrador Sea (Arrigo et al., 2017b <sup>[[#fn:r1268|1268]]</sup> ) ( ''limited evidence, high agreement'' ).

Subglacial meltwater plumes from tidewater glaciers have emerged recently as an important indirect source of nutrients to fjords, by entraining nutrient-replete seawater (Meire et al., 2016b <sup>[[#fn:r1269|1269]]</sup> ; Meire et al., 2017 <sup>[[#fn:r1270|1270]]</sup> ; Cape et al., 2018 <sup>[[#fn:r1271|1271]]</sup> ; Hopwood et al., 2018 <sup>[[#fn:r1272|1272]]</sup> ; Kanna et al., 2018 <sup>[[#fn:r1273|1273]]</sup> ) ( ''medium evidence, high agreement'' ). There is ''medium evidence'' with ''high agreement'' that these upwelled nutrient fluxes enhance primary production in fjords over a distance of up to 100 km along the trajectory of the outflowing plume (Juul-Pedersen et al., 2015 <sup>[[#fn:r1274|1274]]</sup> ; Cape et al., 2018 <sup>[[#fn:r1275|1275]]</sup> ; Kanna et al., 2018 <sup>[[#fn:r1276|1276]]</sup> ). ''' '''

In Antarctica ''',''' there is ''medium evidence'' with ''high agreement'' that enhanced input of iron from ice shelves, glacial meltwater and icebergs stimulates primary production in polynyas, coastal regions and the wider Southern Ocean (Gerringa et al., 2012 <sup>[[#fn:r1277|1277]]</sup> ; Shadwick et al., 2013 <sup>[[#fn:r1278|1278]]</sup> ; Herraiz-Borreguero et al., 2016 <sup>[[#fn:r1279|1279]]</sup> ). Satellite observations and modelling also indicate variable potential for icebergs to fertilise the Southern Ocean beyond the coastal zone (Death et al., 2014 <sup>[[#fn:r1280|1280]]</sup> ; Duprat et al., 2016 <sup>[[#fn:r1281|1281]]</sup> ; Wu and Hou, 2017 <sup>[[#fn:r1282|1282]]</sup> ).

Dissolved nutrient fluxes from ice sheets may be increasing during high melt years (Hawkings et al., 2015 <sup>[[#fn:r1283|1283]]</sup> ). The dominant sediment-bound fraction, however, may not increase with rising melt (Hawkings et al., 2015 <sup>[[#fn:r1284|1284]]</sup> ). Thus, there is ''low confidence'' overall in the magnitude of the response of direct nutrient fluxes from ice sheets to enhanced melting.

Future predictions of nutrient cycling proximal to ice sheets is made more challenging by the landward progression of marine-terminating glaciers and the collapse of ice shelves (Cook et al., 2016 <sup>[[#fn:r1285|1285]]</sup> ). This has the potential to drive major shifts in nutrient supply to coastal waters (Figure 3.9). The erosion of newly exposed glacial sediments in front of retreating land-terminating glaciers (Monien et al., 2017 <sup>[[#fn:r1286|1286]]</sup> ) and changes in the diffuse nutrient fluxes from newly exposed glacial sediments on the seafloor (Wehrmann et al., 2014 <sup>[[#fn:r1287|1287]]</sup> ) may amplify nutrient supply, whilst other nutrient sources may be cut off (e.g., icebergs, upwelling of marine water; Meire et al., 2017 <sup>[[#fn:r1288|1288]]</sup> ) ( ''low confidence'' ) ''.''

There is ''medium evidence'' with ''high agreement'' that long-term tidewater glacier retreat into shallower water or onto land, a plausible scenario for about 55% of the 243 distinct outlet glaciers in Greenland (Morlighem et al., 2017 <sup>[[#fn:r1289|1289]]</sup> ), will reduce or diminish upwelling a source of nutrients, thereby reducing summer productivity in Greenland fjord ecosystems (Meire et al., 2017 <sup>[[#fn:r1290|1290]]</sup> ; Hopwood et al., 2018 <sup>[[#fn:r1291|1291]]</sup> ).

<div id="section-3-3-3-3biogeochemistry-block-2"></div>

<span id="figure-3.9"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 3.9'''

<span id="potential-shifts-in-nutrient-fluxes-with-landward-retreat-of-marine-terminating-glaciers-a-at-different-stages-b-and-c."></span>
<!-- IMG CAPTION -->
'''Potential shifts in nutrient fluxes with landward retreat of marine-terminating glaciers (a) at different stages (b and c).'''
<!-- IMG FILE -->
[[File:458cf80bd938340c10b5033b1a5c10c3 IPCC-SROCC-CH_3_9.jpg]]

Potential shifts in nutrient fluxes with landward retreat of marine-terminating glaciers (a) at different stages (b and c).

<!-- END IMG -->
<div id="section-3-3-3-4ecosystems"></div>

<span id="ecosystems"></span>
==== 3.3.3.4 Ecosystems ====

<div id="section-3-3-3-4ecosystems-block-1"></div>

For Greenland and Svalbard, there is ''limited evidence'' with ''high agreement'' that the retreat of marine-terminating glaciers will alter food supply to higher trophic levels of marine food webs (Meire et al., 2017 <sup>[[#fn:r1292|1292]]</sup> ; Milner et al., 2017 <sup>[[#fn:r1293|1293]]</sup> ). The consequences of changes in glacial systems on marine ecosystems are often mediated via the fjordic environments that fringe the edge of the ice sheets, for example changing physical-chemical conditions have affected the benthic ecosystems of Arctic fjords (Bourgeois et al., 2016 <sup>[[#fn:r1294|1294]]</sup> ). The amplification of nutrient fluxes caused by enhanced upwelling at calving fronts (Meire et al., 2017 <sup>[[#fn:r1295|1295]]</sup> ), combined with high carbon/nutrient burial and recycling rates (Wehrmann et al., 2013 <sup>[[#fn:r1296|1296]]</sup> ; Smith et al., 2015 <sup>[[#fn:r1297|1297]]</sup> ), plays an important role in sustaining high productivity of the Arctic fjord ecosystems of Greenland and Svalbard (Lydersen et al., 2014 <sup>[[#fn:r1298|1298]]</sup> ). Glacier retreat, causing glaciers to shift from being marine-terminating to land-terminating, can reduce the productivity in coastal areas off Greenland with potentially large ecological implications, also negatively affecting production of commercially harvested fish (Meire et al., 2017 <sup>[[#fn:r1299|1299]]</sup> ). There is also evidence that marine-terminating glaciers are important feeding areas for marine mammals and seabirds at Greenland (Laidre et al., 2016 <sup>[[#fn:r1300|1300]]</sup> ) and Svalbard (Lydersen et al., 2014 <sup>[[#fn:r1301|1301]]</sup> ).

For Antarctica ''',''' there is ''high agreement'' based on ''medium evidence'' that ice shelf retreat or collapse is leading to new marine habitats and to biological colonisation (Gutt et al., 2011 <sup>[[#fn:r1302|1302]]</sup> ; Fillinger et al., 2013 <sup>[[#fn:r1303|1303]]</sup> ; Trathan et al., 2013 <sup>[[#fn:r1304|1304]]</sup> ; Hauquier et al., 2016 <sup>[[#fn:r1305|1305]]</sup> ; Ingels et al., 2018 <sup>[[#fn:r1306|1306]]</sup> ). The loss of ice shelves and retreat of coastal glaciers around the AP in the last 50 years has exposed at least 2.4 × 10 4 km 2 of new open water. These newly-revealed habitats have allowed new phytoplankton blooms to be produced resulting in new marine zooplankton and seabed communities (Gutt et al., 2011 <sup>[[#fn:r1307|1307]]</sup> ; Fillinger et al., 2013 <sup>[[#fn:r1308|1308]]</sup> ; Trathan et al., 2013 <sup>[[#fn:r1309|1309]]</sup> ; Hauquier et al., 2016 <sup>[[#fn:r1310|1310]]</sup> ) (Section 3.2.3.2.1), and have resulted in enhanced carbon uptake by coastal marine ecosystems ( ''medium confidence'' ), although quantitative estimates of biological carbon uptake are highly variable (Trathan et al., 2013 <sup>[[#fn:r1311|1311]]</sup> ; Barnes et al., 2018 <sup>[[#fn:r1312|1312]]</sup> ). Newly available habitat on coastlines may also provide breeding or haul out sites for land-based predators such as penguins and seals (Trathan et al., 2013 <sup>[[#fn:r1313|1313]]</sup> ) ( ''low confidence'' ). Fjords that have been studied in the subpolar western AP are hotspots of abundance and biodiversity of benthic macro-organisms (Grange and Smith, 2013 <sup>[[#fn:r1314|1314]]</sup> ) and there is evidence that glacier retreat in these environments can impact the structure and function of benthic communities (Moon et al., 2015 <sup>[[#fn:r1315|1315]]</sup> ; Sahade et al., 2015 <sup>[[#fn:r1316|1316]]</sup> ) ( ''low confidence'' ).

<div id="section-3-3-3-4ecosystems-block-2" class="box"></div>

<span id="ccb.8-future-sea-level-changes-and-marine-ice-sheet-instability"></span>