Editing IPCC:AR6/SROCC/Chapter-2 (section)

=== 2.2.2 Snow Cover ===

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Snow on the ground is an essential and widespread component of the mountain cryosphere. It affects mountain ecosystems and plays a major role for mass movement and floods in the mountains. It plays a key role in nourishing glaciers and provides an insulating and reflective cover at their surface. It influences the thermal regime of the underlying ground, including permafrost, with implications for ecosystems. Climate change modifies key variables driving the onset and development of the snow cover (e.g., solid precipitation), and those responsible for its ablation (e.g., air temperature, radiation). The snow cover, especially in low-lying and mid-elevation areas of mountain regions, has long been identified to be particularly sensitive to climate change.

The mountain snow cover is characterised by a very strong interannual and decadal variability, similar to its main driving force solid precipitation (Lafaysse et al., 2014 <sup>[[#fn:r52|52]]</sup> ; Mankin and Diffenbaugh, 2015 <sup>[[#fn:r53|53]]</sup> ). Observations spanning several decades are required to quantify trends. Long-term ''in situ'' records are scarce in some regions of the world, particularly in High Mountain Asia, Northern Asia and South America (Rohrer et al., 2013 <sup>[[#fn:r54|54]]</sup> ). Satellite remote sensing provides new capabilities for monitoring mountain snow cover on regional scales. The satellite record length is often insufficient to assess trends (Bormann et al., 2018 <sup>[[#fn:r55|55]]</sup> ). Evidence of past changes from regional studies is provided in Table SM2.6. At lower elevation, there is ''high confidence'' that the mountain snow cover has generally declined in duration (on average by 5 snow cover days per decade, with a ''likely'' range from 0 to 10 days per decade), mean snow depth and accumulated mass (snow water equivalent) since the middle of the 20th century, with regional variations. At higher elevation, snow cover trends are generally insignificant ( ''medium confidence'' ) or unknown ''.''

Most of the snow cover changes can be attributed, at lower elevation, to more precipitation falling as liquid precipitation (rain) and to increases in melt at all elevations, mostly due to changes in atmospheric forcings, especially increased air temperature (Kapnick and Hall, 2012 <sup>[[#fn:r56|56]]</sup> ; Marty et al., 2017 <sup>[[#fn:r57|57]]</sup> ) which in turn are attributed to anthropogenic forcings at a larger scale (Section 2.2.1). Formal anthropogenic attribution studies provide similar conclusions in Western North America (Pierce et al., 2008 <sup>[[#fn:r58|58]]</sup> ; Najafi et al., 2017 <sup>[[#fn:r59|59]]</sup> ).

Assessing the impact of the deposition of short-lived climate forcers on snow cover changes is an emerging issue (Skiles et al., 2018 <sup>[[#fn:r60|60]]</sup> and references therein). This concerns light absorbing particles, in particular, which include deposited aerosols such as black carbon, organic carbon and mineral dust, or microbial growth (Qian et al., 2015 <sup>[[#fn:r61|61]]</sup> ), although the role of the latter has not been specifically quantified. Due to their seasonally variable deposition flux and impact, and mostly episodic nature in case of dust deposition (Kaspari et al., 2014 <sup>[[#fn:r62|62]]</sup> ; Di Mauro et al., 2015 <sup>[[#fn:r63|63]]</sup> ), light absorbing particles contribute to interannual fluctuations of seasonal snowmelt rate (Painter et al., 2018) ( ''medium evidence, high agreement'' ). There is ''limited evidence (medium agreement'' ) that increases in black carbon deposition from anthropogenic and biomass burning sources have contributed to snow cover decline in High Mountain Asia (Li et al., 2016 <sup>[[#fn:r64|64]]</sup> ; Zhang et al., 2018 <sup>[[#fn:r65|65]]</sup> ) and South America (Molina et al., 2015 <sup>[[#fn:r66|66]]</sup> ).

Projected changes of mountain snow cover are studied based on climate model experiments, either directly from GCM or RCM output, or following downscaling and the use of snowpack models. These projections generally do not specifically account for future changes in the deposition rate of light absorbing particles on snow (or, if so, simple approaches have been used hitherto; e.g., Deems et al., 2013), so that future changes in snow conditions are mostly driven by changes in meteorological drivers assessed in Section 2.2.1. Evidence from regional studies is provided in Table SM2.7. Although existing studies in mountain regions do not use homogenous reference periods and model configurations, common future trends can be summarised as follows. At lower elevation in many regions such as the European Alps, Western North America, Himalaya and subtropical Andes, the snow depth or mass is projected to decline by 25% ( ''likely'' range between 10 and 40%), between the recent past period (1986 – 2005) and the near future (2031 – 2050), regardless of the greenhouse gas emission scenario (Cross-Chapter Box 1 in Chapter 1). This corresponds to a continuation of the ongoing decrease in annual snow cover duration (on average 5 days per decade, with a ''likely'' range from 0 to 10). By the end of the century (2081 – 2100), reductions of up to 80% ( ''likely'' range from 50 to 90%) are expected under RCP8.5, 50% ( ''likely'' range from 30 to 70%) under RCP4.5 and 30% ( ''likely'' range from 10 to 40%) under RCP2.6. At higher elevations, projected reductions are smaller ( ''high confidence'' ), as temperature increases at higher elevations affect the ablation component of snow mass evolution, rather than both the onset and accumulation components. The projected increase in winter snow accumulation may result in a net increase in winter snow mass ( ''medium confidence'' ). All elevation levels and mountain regions are projected to exhibit sustained interannual variability of snow conditions throughout the 21st century ( ''high confidence'' ). Figure 2.3 provides projections of temperature and snow cover in mountain areas in Europe, High Mountain Asia (Hindu Kush, Karakoram and Himalaya), North America (Rocky Mountains) and South America (sub-tropical Central Andes), illustrating how changes vary with elevation, season, region, future time period and climate scenario.

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'''Figure 2.3'''

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'''Figure 2.3 | Projected change (1986–2005 to 2031–2050 and 2080–2099) of mean winter (December to May; June to August in Subtropical Central Andes) snow water equivalent, winter air temperature and summer air temperature (June to August; December to February in Subtropical Central Andes) in five high mountain regions for RCP8.5 (all regions) and RCP2.6 (European […]'''
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Figure 2.3 | Projected change (1986–2005 to 2031–2050 and 2080–2099) of mean winter (December to May; June to August in Subtropical Central Andes) snow water equivalent, winter air temperature and summer air temperature (June to August; December to February in Subtropical Central Andes) in five high mountain regions for RCP8.5 (all regions) and RCP2.6 (European Alps and Subtropical Central Andes). Changes are averaged over 500 m (a,b,c) and 1,000 m (d,e) elevation bands. The numbers in the lower right of each panel reflect the number of simulations (note that not all models provide snow water equivalent). For the Rocky Mountains, data from NA-CORDEX RCMs (25 km grid spacing) driven by Coupled Model Intercomparison Project Phase 5 (CMIP5) General Circulation Models (GCMs) were used (Mearns et al., 2017 <sup>[[#fn:r44|44]]</sup> ). For the European Alps, data from EURO-CORDEX RCMs (12 km grid spacing) driven by CMIP5 GCMs were used (Jacob et al., 2014 <sup>[[#fn:r45|45]]</sup> ). For the other regions, CMIP5 GCMs were used: Zazulie (2016) <sup>[[#fn:r56|56]]</sup> and Zazulie et al. (2018) for the Subtropical Central Andes, and Terzago et al. (2014) and Palazzi et al. (2017) <sup>[[#fn:r48|48]]</sup> for the Hindu Kush and Karakoram and Himalaya. The list of models used is provided in Table SM2.8.

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