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

=== 3.4.1 Observations ===

<div id="section-3-4-1-1seasonal-snow-cover"></div>

<span id="seasonal-snow-cover"></span>
==== 3.4.1.1 Seasonal Snow Cover ====

<div id="section-3-4-1-1seasonal-snow-cover-block-1"></div>

Terrestrial snow cover is a defining characteristic of the Arctic land surface for up to nine months each year, with changes influencing the surface energy budget, ground thermal regime and freshwater budget. Snow cover also interacts with vegetation, influences biogeochemical activity and affects habitats and species, with consequences for ecosystem services. Arctic land areas are almost always completely snow covered in winter, so the transition seasons of autumn and spring are key when characterising variability and change.

<div id="section-3-4-1-1seasonal-snow-cover-block-2"></div>

<span id="extent-and-duration"></span>
===== 3.4.1.1.1 Extent and duration =====

Dramatic reductions in Arctic (land areas north of 60°N) spring snow cover extent have occurred since satellite charting began in 1967 (Estilow et al., 2015). Declines in May and June of –3.5% (± 1.9%) and –13.4% respectively per decade (± 5.4%) between 1967 and 2018 (relative to the 1981–2010 mean) were determined from multiple datasets based on the methodology of (Mudryk et al., 2017 <sup>[[#fn:r1351|1351]]</sup> ) (Figure 3.10) ( ''high confidence'' ). The loss of spring snow extent is reflected in shorter snow cover duration estimated from surface observations (Bulygina et al., 2011 <sup>[[#fn:r1352|1352]]</sup> ; Brown et al., 2017 <sup>[[#fn:r1353|1353]]</sup> ), satellite data (Wang et al., 2013 <sup>[[#fn:r1354|1354]]</sup> ; Estilow et al., 2015 <sup>[[#fn:r1355|1355]]</sup> ; Anttila et al., 2018 <sup>[[#fn:r1356|1356]]</sup> ), and model-based analyses (Liston and Hiemstra, 2011 <sup>[[#fn:r1357|1357]]</sup> ) ( ''high confidence'' ). These trends range between –0.7 and –3.9 days per decade depending on region and time period, but all spring snow cover duration trends from all datasets are negative (Brown et al., 2017 <sup>[[#fn:r1358|1358]]</sup> ). These same multi-source datasets also identify reductions in autumn snow extent and duration (-0.6 to -1.4 days per decade; summarized in Brown et al., 2017) ( ''high confidence'' ). There is ''low confidence'' in positive October and November snow cover extent trends apparent in a single dataset (Hernández-Henríquez et al., 2015 <sup>[[#fn:r1359|1359]]</sup> ) because they are not replicated in other surface, satellite and model datasets (Brown and Derksen, 2013 <sup>[[#fn:r1360|1360]]</sup> ; Mudryk et al., 2017 <sup>[[#fn:r1361|1361]]</sup> ).

<div id="section-3-4-1-1seasonal-snow-cover-block-3"></div>

<span id="depth-and-water-equivalent"></span>
===== 3.4.1.1.2 Depth and water equivalent =====

Weather station observations across the Russian Arctic identify negative trends in the maximum snow depth between 1966 and 2014 (Bulygina et al., 201 <sup>[[#fn:r1362|1362]]</sup> ; Osokin and Sosnovsky, 2014 <sup>[[#fn:r1363|1363]]</sup> ). There is ''medium confidence'' in this trend because the pointwise nature of these measurements does not capture prevailing conditions across the landscape. Seasonal maximum snow depth trends over the North American Arctic are mixed and largely statistically insignificant (Vincent et al., 2015 <sup>[[#fn:r1364|1364]]</sup> ; Brown et al., 2017 <sup>[[#fn:r1365|1365]]</sup> ). The timing of maximum snow depth has shifted earlier by 2.7 days per decade for the North American Arctic (Brown et al., 2017 <sup>[[#fn:r1366|1366]]</sup> ); comparable analysis is not available for Eurasia. Gridded products from remote sensing and land surface models identify negative trends in snow water equivalent between 1981 and 2016 for both the Eurasian and North American sectors of the Arctic (Brown et al., 2017 <sup>[[#fn:r1367|1367]]</sup> ). While the snow water equivalent anomaly time series show reasonable consistency between products when averaged at the continental scale, considerable inter-dataset variability in the spatial patterns of change (Liston and Hiemstra, 2011 <sup>[[#fn:r1368|1368]]</sup> ; Park et al., 2012 <sup>[[#fn:r1369|1369]]</sup> ; Brown et al., 2017 <sup>[[#fn:r1370|1370]]</sup> ) mean there is only ''medium confidence'' in these trends.

<div id="section-3-4-1-1seasonal-snow-cover-block-4"></div>

<span id="drivers"></span>
===== 3.4.1.1.3 Drivers =====

Despite uncertainties due to sparse observations (Cowtan and Way, 2014 <sup>[[#fn:r1371|1371]]</sup> ), surface temperature has increased across Arctic land areas in recent decades (Hawkins and Sutton, 2012 <sup>[[#fn:r1372|1372]]</sup> ; Fyfe et al., 2013 <sup>[[#fn:r1373|1373]]</sup> ), driving reductions in Arctic snow extent and duration ( ''high confidence'' ) ''.'' Changes in Arctic snow extent can be directly related to extratropical temperature increases (Brutel-Vuilmet et al., 2013 <sup>[[#fn:r1374|1374]]</sup> ; Thackeray et al., 2016 <sup>[[#fn:r1375|1375]]</sup> ; Mudryk et al., 2017 <sup>[[#fn:r1376|1376]]</sup> ). Based on multiple historical datasets, there is a consistent temperature sensitivity for Arctic snow extent, with approximately 800,000 km 2 of snow cover lost per degrees Celsius warming in spring (Brown and Derksen, 2013 <sup>[[#fn:r1377|1377]]</sup> ; Brown et al., 2017), and 700,000–800,000 km 2 lost in autumn (Derksen and Brown, 2012 <sup>[[#fn:r1379|1379]]</sup> ; Brown and Derksen, 2013 <sup>[[#fn:r1380|1380]]</sup> ) ( ''high confidence'' ).

There is ''high confidence'' that darkening of snow through the deposition of black carbon and other light absorbing particles enhances snow melt (Bullard et al., 2016 <sup>[[#fn:r1381|1381]]</sup> ; Skiles et al., 2018 <sup>[[#fn:r1382|1382]]</sup> ; Boy et al., 2019 <sup>[[#fn:r1383|1383]]</sup> ). The global direct radiative forcing for black carbon in seasonal snow and over sea ice is estimated to be 0.04 W m –2 , but the effective forcing can be up to threefold greater at regional scales due to the enhanced albedo feedback triggered by the initial darkening (Bond et al., 2013). Lawrence et al. (2011) <sup>[[#fn:r1393|1393]]</sup> estimate the present-day radiative effect of black carbon and dust in land-based snow to be 0.083 W m –2 , only marginally greater than the simulated 1850 effect (0.075 W m –2 ) due to offsetting effects from increased black carbon emissions and reductions in dust darkening ( ''medium confidence'' ). Kylling et al. (2018) <sup>[[#fn:r1394|1394]]</sup> estimate a surface radiative effect of 0.292 W m –2 caused by dust deposition (largely transported from Asia) to Arctic snow, approximately half of the black carbon central scenario estimate of Flanner et al. (2007) <sup>[[#fn:r1395|1395]]</sup> . The forcing from brown carbon deposited in snow (associated with both combustion and secondary organic carbon) is estimated to be 0.09−0.25 W m –2 , with the range due to assumptions of particle absorptivity (Lin et al., 2014 <sup>[[#fn:r1396|1396]]</sup> ) ( ''low confidence'' ).

Precipitation remains a sparse and highly uncertain measurement over Arctic land areas: ''in situ'' datasets remain uncertain (Yang, 2014 <sup>[[#fn:r1397|1397]]</sup> ) and are largely regional (Kononova, 2012 <sup>[[#fn:r1398|1398]]</sup> ; Vincent et al., 2015 <sup>[[#fn:r1399|1399]]</sup> ). Atmospheric reanalyses show increases in Arctic precipitation in recent decades (Lique et al., 2016 <sup>[[#fn:r1400|1400]]</sup> ; Vihma et al., 2016 <sup>[[#fn:r1401|1401]]</sup> ), but there remains ''low confidence'' in reanalysis-based closure of the Arctic freshwater budget due to a wide spread between available reanalysis derived precipitation estimates (Lindsay et al., 2014 <sup>[[#fn:r1484|1484]]</sup> ). Despite improved process understanding, estimates of sublimation loss during blowing snow events remain a key uncertainty in the mass budget of the Arctic snowpack (Sturm and Stuefer, 2013 <sup>[[#fn:r1485|1485]]</sup> ).

<div id="section-3-4-1-2permafrost"></div>

<span id="permafrost"></span>
==== 3.4.1.2 Permafrost ====

<div id="section-3-4-1-2permafrost-block-1"></div>

<span id="temperature-1"></span>
===== 3.4.1.2.1 Temperature =====

Record high temperatures at ~10–20 m depth in the permafrost (near or below the depths affected by intra-annual fluctuation in temperature) have been documented at many long-term monitoring sites in the Northern Hemisphere circumpolar permafrost region (AMAP, 2017d <sup>[[#fn:r1386|1386]]</sup> ) (Figure 3.10) ( ''very high confidence'' ). At some locations, the temperature is 2°C–3°C higher than 30 years ago. During the decade between 2007 and 2016, the rate of increase in permafrost temperatures was 0.39°C ± 0.15°C for colder continuous zone permafrost monitoring sites, 0.20°C ± 0.10°C for warmer discontinuous zone permafrost, giving a global average of 0.29 ± 0.12°C across all polar and mountain permafrost (Biskaborn et al., 2019 <sup>[[#fn:r1387|1387]]</sup> ). Relatively smaller increases in permafrost temperature in warmer sites indicate that permafrost is thawing with heat absorbed by the ice-to-water phase change, and as a result, the active layer may be increasing in thickness. In contrast to temperature, there is only ''medium confidence'' that active layer thickness across the region has increased. This confidence level is because decadal trends vary across regions and sites (Shiklomanov et al., 2012 <sup>[[#fn:r1388|1388]]</sup> ) and because mechanical probing of the active layer can underestimate the degradation of permafrost in some cases because the surface subsides when ground ice melts and drains (Mekonnen et al., 2016 <sup>[[#fn:r1389|1389]]</sup> ; AMAP, 2017d <sup>[[#fn:r1390|1390]]</sup> ; Streletskiy et al., 2017 <sup>[[#fn:r1391|1391]]</sup> ). Permafrost in the Southern Hemisphere polar region occurs in ice-free exposed areas (Bockheim et al., 2013 <sup>[[#fn:r1392|1392]]</sup> ), 0.18% of the total land area of Antarctica (Burton-Johnson et al., 2016). This area is three orders of magnitude smaller than the 13–18 x 10 6 km 2 area underlain by permafrost in the Northern Hemisphere terrestrial permafrost region (Gruber, 2012). Antarctic permafrost temperatures are generally colder (Noetzli et al., 2017 <sup>[[#fn:r1403|1403]]</sup> ) and increased 0.37°C ± 0.10°C between 2007 and 2016 (Biskaborn et al., 2019 <sup>[[#fn:r1404|1404]]</sup> ).

<div id="section-3-4-1-2permafrost-block-2"></div>

<span id="figure-3.10"></span>
<!-- START IMG -->
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'''Figure 3.10'''

<span id="schematic-of-important-land-surface-components-influenced-by-the-arctic-terrestrial-cryosphere-permafrost-1-ground-ice-2-river-discharge-3-abrupt-thaw-4-surface-water-5-fire-6-tundra-7-shrubs-8-boreal-forest-9-lake-ice-10-seasonal-snow-11.-time-series-of-snow-cover-extent-anomalies-in-june-relative-to-19812010-climatology-from"></span>
<!-- IMG CAPTION -->
'''Schematic of important land surface components influenced by the Arctic terrestrial cryosphere: permafrost (1); ground ice (2); river discharge (3); abrupt thaw (4); surface water (5); fire (6); tundra (7); shrubs (8); boreal forest (9); lake ice (10); seasonal snow (11). Time series of snow cover extent anomalies in June (relative to 1981–2010 climatology) from […]'''
<!-- IMG FILE -->
[[File:1f09753851439dd6e693fe4f8198d24b IPCC-SROCC-CH_3_10.jpg]]

Schematic of important land surface components influenced by the Arctic terrestrial cryosphere: permafrost (1); ground ice (2); river discharge (3); abrupt thaw (4); surface water (5); fire (6); tundra (7); shrubs (8); boreal forest (9); lake ice (10); seasonal snow (11). Time series of snow cover extent anomalies in June (relative to 1981–2010 climatology) from 5 products based on the approach of Mudryk et al. (2017) (a); permafrost temperature change normalised to a baseline period (Romanovsky et al., 2017), Region A: Continuous to discontinuous permafrost in Scandanavia, Svalbard, and Russia/Siberia, Region B: Cold continuous permafrost in northern Alaska, Northwest Territories, and NE Siberia, Region C: Cold continuous permafrost in Eastern and High Arctic Canada, Region D: Discontinuous permafrost in Interior Alaska and Northwest Canada (b), and runoff from northern flowing watersheds normalised to a baseline period (1981–2010) (Holmes et al., 2018), multi-station average (± 1 standard deviation) (c). Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model average (± 1 standard deviation) projections for different Representative Concentration Pathway (RCP) scenarios for June snow cover extent change (based on Thackeray et al., 2016) (d), area change of near-surface permafrost (e), and runoff change to the Arctic Ocean (based on McGuire et al., 2018) (f).

<!-- END IMG -->
<div id="section-3-4-1-2permafrost-block-3"></div>

<span id="ground-ice"></span>
===== 3.4.1.2.2 Ground ice =====

Permafrost thaw and loss of ground ice causes the land surface to subside and collapse into the volume previously occupied by ice, resulting in disturbance to overlying ecosystems and human infrastructure (Kanevskiy et al., 2013 <sup>[[#fn:r1405|1405]]</sup> ; Raynolds et al., 2014 <sup>[[#fn:r1406|1406]]</sup> ). Excess ice in permafrost is typical, varying for example from 40% of total volume in some sands up to 80–90% of total volume in fine-grained soil/sediments (Kanevskiy et al., 2013 <sup>[[#fn:r1407|1407]]</sup> ). Ice rich permafrost areas where impacts of thaw could be greatest include the Yedoma deposits in Siberia, Alaska, and the Yukon in Canada, with ice divided between massive wedges interspersed with frozen soil/sediment containing pore ice and smaller ice features (Schirrmeister et al., 2011 <sup>[[#fn:r1408|1408]]</sup> ; Strauss et al., 2017 <sup>[[#fn:r1409|1409]]</sup> ). Other areas including, for example, Northwestern Canada, the Canadian Archipelago, the Yamal and Gydan peninsulas of West Siberia, and smaller portions of Eastern Siberia and Alaska contain buried glacial ice bodies of significant thickness and extent (Lantuit and Pollard, 2008; Leibman et al., 2011; Kokelj et al., 2017; Coulombe et al., 2019). The location and volume of ground ice integrated across the northern permafrost region (5.63–36.55 x 10 3 km 3 , equivalent to 2–10 cm sea level rise) is known with ''medium confidence'' and with no recent updates at the circumpolar scale (Zhang et al., 2008 <sup>[[#fn:r1410|1410]]</sup> ).

<div id="section-3-4-1-2permafrost-block-4"></div>

<span id="carbon"></span>
===== 3.4.1.2.3 Carbon =====

The permafrost region represents a large, climate sensitive reservoir of organic carbon with the potential for some of this pool to be rapidly decayed and transferred to the atmosphere as CO 2 and methane as permafrost thaws in a warming climate, thus accelerating the pace of climate change (Schuur et al., 2015 <sup>[[#fn:r1414|1414]]</sup> ). The current best mean estimate of total (surface plus deep) organic soil carbon (terrestrial) in the northern circumpolar permafrost region (17.8 x 10 6 km 2 area) is 1460 to 1600 petagrams ( ''medium confidence'' ) (Pg; 1 Pg = 1 billion metric tonnes) (Schuur et al., 2018 <sup>[[#fn:r1415|1415]]</sup> ). All permafrost region soils estimated to 3 m in depth (surface) contain 1035 ± 150 Pg C (Tarnocai et al., 2009 <sup>[[#fn:r1416|1416]]</sup> ; Hugelius et al., 2014 <sup>[[#fn:r1417|1417]]</sup> ) ( ''high confidence'' ). Of the carbon in the surface, 800–1000 Pg C is perennially frozen, with the remainder contained in seasonally-thawed soils. The northern circumpolar permafrost region occupies only 15% of the total global soil area, but the 1035 Pg C adds another 50% to the rest of the 3 m soil carbon inventory (2050 Pg C for all global biomes excluding tundra and boreal; Jobbágy and Jackson, 2000 <sup>[[#fn:r1418|1418]]</sup> ; Schuur et al., 2015 <sup>[[#fn:r1419|1419]]</sup> ).

Substantial permafrost carbon exists below 3 m depth ( ''medium confidence'' ). Deep carbon (&gt;3 m) has been best quantified for the Yedoma region of Siberia and Alaska, characterised by wind- and water-moved permafrost sediments tens of meters thick. The Yedoma region covers a 1.4 x 10 6 km 2 area that remained ice-free during the last Ice Age (Strauss et al., 2013 <sup>[[#fn:r1420|1420]]</sup> ) and accounts for 327–466 Pg C in deep sediment accumulations below 3 m (Strauss et al., 2017).

The current inventory has also highlighted additional carbon pools that are likely to be present but are so poorly quantified ( ''low confidence'' ) that they cannot yet be added into the number reported above. There are deep terrestrial soil/sediment deposits outside of the Yedoma region that may contain about 400 Pg C (Schuur et al., 2015 <sup>[[#fn:r1421|1421]]</sup> ). An additional pool is organic carbon remaining in permafrost but that is now submerged on shallow Arctic sea shelves that were formerly exposed as terrestrial ecosystems during the Last Glacial Maximum ~20,000 years ago (Walter et al., 2007 <sup>[[#fn:r1423|1423]]</sup> ). This permafrost is degrading slowly due to seawater intrusion, and it is not clear what amounts of permafrost and organic carbon still remain in the sediment versus what has already been converted to greenhouse gases. A recent synthesis of permafrost extent for the Beaufort Sea shelf showed that most remaining subsea permafrost in that region exists near shore with much reduced area ( ''high confidence'' ) as compared to original subsea permafrost maps that outlined the entire 3 x 10 6 km 2 shelf area (&lt;120 m below sea level depth) that was formerly exposed as land (Ruppel et al., 2016 <sup>[[#fn:r1424|1424]]</sup> ). These observations are supported by similar studies in the Siberian Arctic Seas (Portnov et al., 2013 <sup>[[#fn:r1425|1425]]</sup> ), and by modelling that suggests that subsea permafrost would be thawed many meters below the seabed under current submerged conditions (Anisimov et al., 2012 <sup>[[#fn:r1426|1426]]</sup> ; AMAP, 2017d <sup>[[#fn:r1427|1427]]</sup> ; Angelopoulos et al., 2019 <sup>[[#fn:r1428|1428]]</sup> ).

<div id="section-3-4-1-2permafrost-block-5"></div>

<span id="drivers-1"></span>
===== 3.4.1.2.4 Drivers =====

Changes in temperature and precipitation act as gradual ‘press’ (i.e., continuous) disturbances that directly affect permafrost by modifying the ground thermal regime, as discussed in Section 3.4.1.2.1. Climate change can also modify the occurrence and magnitude of abrupt physical disturbances such as fire, and soil subsidence and erosion resulting from ice rich permafrost thaw (thermokarst). These ‘pulse’ (i.e., discrete) disturbances (Smith et al., 2009 <sup>[[#fn:r1429|1429]]</sup> ) often are part of the ongoing disturbance and successional cycle in Arctic and boreal ecosystems (Grosse et al., 2011 <sup>[[#fn:r1430|1430]]</sup> ), but changing rates of occurrence alter the landscape distribution of successional ecosystem states, with permafrost characteristics defined by the ecosystem and climate state (Kanevskiy et al., 2013 <sup>[[#fn:r1431|1431]]</sup> ).

Pulse disturbances often rapidly remove the insulating soil organic layer, leading to permafrost degradation (Gibson et al., 2018 <sup>[[#fn:r1423|1423]]</sup> ). Of all pulse disturbance types, wildfire affects the most high-latitude land area annually at the continental scale. In some well-studied regions, there is ''high confidence'' that area burned, fire frequency and extreme fire years are higher now than the first half of the last century, or even the last 10,000 years (Kasischke and Turetsky, 2006 <sup>[[#fn:r1433|1433]]</sup> ; Flannigan et al., 2009 <sup>[[#fn:r1434|1434]]</sup> ; Kelly et al., 2013 <sup>[[#fn:r1435|1435]]</sup> ; Hanes et al., 2019 <sup>[[#fn:r1436|1436]]</sup> ) ''.'' Recent climate warming has been linked to increased wildfire activity in the boreal forest regions in Alaska and western Canada where this has been studied (Gillett, 2004 <sup>[[#fn:r1437|1437]]</sup> ; Veraverbeke et al., 2017 <sup>[[#fn:r1438|1438]]</sup> ). Based on satellite imagery, an estimated 80,000 km 2 of boreal area was burned globally per year from 1997 to 2011 (van der Werf et al., 2010 <sup>[[#fn:r1439|1439]]</sup> ; Giglio et al., 2013 <sup>[[#fn:r1440|1440]]</sup> ). Extreme fire years in northwest Canada during 2014 and Alaska during 2015 doubled the long-term (1997–2011) average area burned annually in this region (Canadian Forest Service, 2017), surpassing Eurasia to contribute 60% of the global boreal area burned (van der Werf et al., 2010 <sup>[[#fn:r1441|1441]]</sup> ; Randerson et al., 2012 <sup>[[#fn:r1442|1442]]</sup> ; Giglio et al., 2013 <sup>[[#fn:r1443|1443]]</sup> ). These extreme North American fire years were balanced by lower-than-average area burned in Eurasian forests, resulting in a 5% overall increase in global boreal area burned. The annual area burned in Arctic tundra is generally small compared to the forested boreal biome. In Alaska—the only region where estimates of burned area exist for both boreal forest and tundra vegetation types—tundra burning averaged approximately 270 km 2 yr -1 during the last half century (French et al., 2015 <sup>[[#fn:r1445|1445]]</sup> ), accounting for 7% of the average annual area burned throughout the state (Pastick et al., 2017 <sup>[[#fn:r1446|1446]]</sup> ). There is ''high confidence'' that changes in the fire regime are degrading permafrost faster than had occurred over the historic successional cycle (Turetsky et al., 2011 <sup>[[#fn:r1447|1447]]</sup> ; Rupp et al., 2016 <sup>[[#fn:r1448|1448]]</sup> ; Pastick et al., 2017 <sup>[[#fn:r1449|1449]]</sup> ), and that the effect of this driver of permafrost change is under-represented in the permafrost temperature observation network.

Abrupt permafrost thaw occurs when changing environmental and ecological conditions interact with geomorphological processes. Melting ground ice causes the ground surface to subside. Pooling or flowing water causes localised permafrost thaw and sometimes mass erosion. Together, these localised feedbacks can thaw through meters of permafrost within a short time, much more rapidly than would be caused by increasing air temperature alone. This process is a pulse disturbance to permafrost that can occur in response to climate, such as an extreme precipitation event (Balser et al., 2014 <sup>[[#fn:r1450|1450]]</sup> ; Kokelj et al., 2015 <sup>[[#fn:r1451|1451]]</sup> ), or coupled with other disturbances such as wildfire that affects the ground thermal regime (Jones et al., 2015a <sup>[[#fn:r1452|1452]]</sup> ). There is ''medium confidence'' in the importance of abrupt thaw for driving change in permafrost at the circumpolar scale because it occurs at point locations rather than continuously across the landscape, but the risk for widespread change from this mechanism remains high because of the rapidity of change in these locations (Kokelj et al., 2017 <sup>[[#fn:r1453|1453]]</sup> ; Nitze et al., 2018 <sup>[[#fn:r1454|1454]]</sup> ). New research at the global scale has revealed that 3.6 x 10 6 km 2 , about 20% of the northern permafrost region, appears to be vulnerable to abrupt thaw (Olefeldt et al., 2016 <sup>[[#fn:r1455|1455]]</sup> ).

<div id="section-3-4-1-3freshwater-systems"></div>

<span id="freshwater-systems"></span>
==== 3.4.1.3 Freshwater Systems ====

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

There is increasing awareness of the influence of a changing climate on freshwater systems across the Arctic, and associated impacts on hydrological, biogeophysical and ecological processes (Prowse et al., 2015 <sup>[[#fn:r1456|1456]]</sup> ; Walvoord and Kurylyk, 2016 <sup>[[#fn:r1457|1457]]</sup> ), and northern populations (Takakura, 2018 <sup>[[#fn:r1458|1458]]</sup> ) (Section 3.4.3.3.1). Assessing these impacts requires consideration of complex interconnected processes, many of which are incompletely observed. The increasing imprint of human development, such as flow regulation on major northerly flowing rivers adds complexity to the determination of climate-driven changes.

<div id="section-3-4-1-3freshwater-systems-block-2"></div>

<span id="freshwater-ice"></span>
===== 3.4.1.3.1 Freshwater ice =====

Long-term ''in situ'' river ice records indicate that the duration of ice cover in Russian Arctic rivers decreased by 7–20 days between 1955 and 2012 (Shiklomanov and Lammers, 2014 <sup>[[#fn:r1459|1459]]</sup> ) ( ''high confidence'' ). This is consistent with historical reductions in Arctic river ice cover derived from models (Park et al., 2015) and regional analysis of satellite data (Cooley and Pavelsky, 2016 <sup>[[#fn:r1461|1461]]</sup> ).

Analysis of satellite imagery between 2000 and 2013 identified a significant trend of earlier spring ice break-up across all regions of the Arctic (Šmejkalová et al., 2016 <sup>[[#fn:r1462|1462]]</sup> ); independent satellite data showed approximately 80% of Arctic lakes experienced declines in ice cover duration during 2002–2015, due to both a later freeze-up and earlier break-up (Du et al., 2017 <sup>[[#fn:r1463|1463]]</sup> ) ( ''high confidence'' ). There are indications that lake ice across Alaska has thinned in recent decades (Alexeev et al., 2016 <sup>[[#fn:r1464|1464]]</sup> ), but ice thickness trends are not available at the pan-Arctic scale. Analysis of satellite data over northern Alaska show that approximately one-third of bedfast lakes (the entire water volume freezes by the end of winter) experienced a regime change to floating ice over the 1992–2011 period (Surdu et al., 2014 <sup>[[#fn:r1465|1465]]</sup> ; Arp et al., 2015 <sup>[[#fn:r1466|1466]]</sup> ). This can result in degradation of underlying permafrost (Arp et al., 2016 <sup>[[#fn:r1467|1467]]</sup> ; Bartsch et al., 2017 <sup>[[#fn:r1468|1468]]</sup> ). Lakes of the central and eastern Canadian High Arctic are transitioning from a perennial to seasonal ice regime (Surdu et al., 2016 <sup>[[#fn:r1469|1469]]</sup> ).

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

<span id="runoff-and-surface-water"></span>
===== 3.4.1.3.2 Runoff and surface water =====

A general trend of increasing discharge has been observed for large Siberian (Troy et al., 2012 <sup>[[#fn:r1470|1470]]</sup> ; Walvoord and Kurylyk, 2016 <sup>[[#fn:r1471|1471]]</sup> ) and Canadian (Ge et al., 2013 <sup>[[#fn:r1472|1472]]</sup> ; Déry et al., 2016 <sup>[[#fn:r1473|1473]]</sup> ) rivers that drain to the Arctic Ocean ( ''medium confidence'' ). Between 1976 and 2017, trends are 3.3 ± 1.6% for Eurasian rivers and 2.0 ± 1.8% for North American rivers (Holmes et al., 2018 <sup>[[#fn:r1474|1474]]</sup> ) (Figure 3.10). Extreme regional runoff events have also been identified (Stuefer et al., 2017 <sup>[[#fn:r1475|1475]]</sup> ). An observed increase in baseflow in the North American (Walvoord and Striegl, 2007 <sup>[[#fn:r1476|1476]]</sup> ; St. Jacques and Sauchyn, 2009) and Eurasian Arctic (Smith et al., 2007 <sup>[[#fn:r1477|1477]]</sup> ; Duan et al., 2017 <sup>[[#fn:r1478|1478]]</sup> ) over the last several decades is attributable to permafrost thaw and concomitant enhancement in groundwater discharge. The timing of spring season peak flow is generally earlier (Ge et al., 2013 <sup>[[#fn:r1479|1479]]</sup> ; Holmes et al., 2015 <sup>[[#fn:r1480|1480]]</sup> ). There is consistent evidence of decreasing summer season discharge for the Yenisei, Lena, and Ob watersheds in Siberia (Ye et al., 2003 <sup>[[#fn:r1481|1481]]</sup> ; Yang et al., 2004a <sup>[[#fn:r1482|1482]]</sup> ; Yang et al., 2004b <sup>[[#fn:r1483|1483]]</sup> ) and the majority of northern Canadian rivers (Déry et al., 2016 <sup>[[#fn:r1484|1484]]</sup> ). Long-term records indicate water temperature increases (Webb et al., 2008 <sup>[[#fn:r1485|1485]]</sup> ; Yang and Peterson, 2017 <sup>[[#fn:r1486|1486]]</sup> ); attribution to rising air temperatures is complicated by the influence of reservoir regulation over Siberian regions (Liu et al., 2005 <sup>[[#fn:r1487|1487]]</sup> ; Lammers et al., 2007 <sup>[[#fn:r1488|1488]]</sup> ). Increases in discharge and water temperature in the spring season represent notable freshwater and heat fluxes to the Arctic Ocean (Yang et al., 2014 <sup>[[#fn:r1489|1489]]</sup> ).

A large proportion of low-lying Arctic land areas are covered by lakes because permafrost limits surface water drainage and supports ponding even across areas with high moisture deficits (Grosse et al., 2013 <sup>[[#fn:r1490|1490]]</sup> ). While thaw in continuous permafrost is linked to intensified thermokarst activity and subsequent ponding (resulting in lake/wetland expansion), observations of change in surface water coverage across the Arctic are regionally variable (Nitze et al., 2017 <sup>[[#fn:r1491|1491]]</sup> ; Ulrich et al., 2017 <sup>[[#fn:r1492|1492]]</sup> ; Pastick et al., 2019 <sup>[[#fn:r1493|1493]]</sup> ). In landscapes with degrading ice-wedge polygons, subsidence can reduce inundation, increase runoff, and decrease surface water (Liljedahl et al., 2016 <sup>[[#fn:r1494|1494]]</sup> ; Perreault et al., 2017 <sup>[[#fn:r1495|1495]]</sup> ). In discontinuous permafrost, thaw opens up pathways of subsurface flow, improving the connection among inland water systems which supports the drainage of lakes and overall reduction in surface water cover (Jepsen et al., 2013 <sup>[[#fn:r1496|1496]]</sup> ). Enhanced subsurface connectivity from thaw in discontinuous permafrost serves tempers short-term lake fluctuations (Rey et al., 2019 <sup>[[#fn:r1497|1497]]</sup> ).

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

<span id="drivers-2"></span>
===== 3.4.1.3.3 Drivers =====

There is ''high confidence'' that environmental drivers of Arctic surface water change are diverse and depend on local and regional factors such as permafrost properties and geomorphology (Nitze et al., 2018 <sup>[[#fn:r1498|1498]]</sup> ). Thermokarst lake expansion has been observed in the continuous permafrost of northern Siberia (Smith et al., 2005 <sup>[[#fn:r1499|1499]]</sup> ; Polishchuk et al., 2015 <sup>[[#fn:r1500|1500]]</sup> ) and Alaska (Jones et al., 2011 <sup>[[#fn:r1501|1501]]</sup> ); surface water area reduction has been observed in discontinuous permafrost of central and southern Siberia (Smith et al., 2005 <sup>[[#fn:r1502|1502]]</sup> ; Sharonov et al., 2012 <sup>[[#fn:r1503|1503]]</sup> ), western Canada (Labrecque et al., 2009 <sup>[[#fn:r1504|1504]]</sup> ; Carroll et al., 2011 <sup>[[#fn:r1505|1505]]</sup> ; Lantz and Turner, 2015 <sup>[[#fn:r1506|1506]]</sup> ) and interior Alaska (Chen et al., 2012 <sup>[[#fn:r1507|1507]]</sup> ; Rover et al., 2012 <sup>[[#fn:r1508|1508]]</sup> ). Increased evaporation from warmer/longer summers, decreased recharge due to reductions in snow melt volume, and dynamic processes such as ice-jam flooding (Chen et al., 2012 <sup>[[#fn:r1509|1509]]</sup> ; Bouchard et al., 2013 <sup>[[#fn:r1510|1510]]</sup> ; Jepsen et al., 2015 <sup>[[#fn:r1511|1511]]</sup> ) are important considerations for understanding observed surface water area change across the Arctic.

Satellite and model-derived estimates of evapotranspiration show increases across the Arctic (Rawlins et al., 2010 <sup>[[#fn:r1512|1512]]</sup> ; Liu et al., 2014 <sup>[[#fn:r1513|1513]]</sup> ; Liu et al., 2015b <sup>[[#fn:r1514|1514]]</sup> ; Fujiwara et al., 2016 <sup>[[#fn:r1515|1515]]</sup> ; Suzuki et al., 2018 <sup>[[#fn:r1516|1516]]</sup> ) ( ''medium confidence'' ). Increases in the seasonal active layer thickness impact temporary water storage and thus runoff regimes in drainage basins. Formation of taliks underneath lakes and rivers may result in reconnection of surface with sub-permafrost ground water aquifers with varying hydrological consequences depending on local geological and hydraulic settings (Wellman et al., 2013 <sup>[[#fn:r1517|1517]]</sup> ).

<span id="projections-1"></span>