Black Carbon and Other Light-Absorbing Impurities in Snow in the Chilean Andes

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OPEN Black carbon and other light- absorbing impurities in snow in the Chilean Andes Received: 20 July 2018 Penny M. Rowe 1,2, Raul R. Cordero1, Stephen G. Warren3, Emily Stewart4, Accepted: 16 January 2019 Sarah J. Doherty5, Alec Pankow4, Michael Schrempf6, Gino Casassa7,8, Jorge Carrasco7, Published: xx xx xxxx Jaime Pizarro1, Shelley MacDonell9, Alessandro Damiani1,10, Fabrice Lambert 11,13, Roberto Rondanelli12,13, Nicolas Huneeus12,13, Francisco Fernandoy 14 & Steven Neshyba4

Vertical profles of black carbon (BC) and other light-absorbing impurities were measured in seasonal snow and permanent snowfelds in the Chilean Andes during Austral winters 2015 and 2016, at 22 sites between latitudes 18°S and 41°S. The samples were analyzed for spectrally-resolved visible light absorption. For surface snow, the average mass mixing ratio of BC was 15 ng/g in northern Chile (18– 33°S), 28 ng/g near Santiago (a major city near latitude 33°S, where urban pollution plays a signifcant role), and 13 ng/g in southern Chile (33–41°S). The regional average vertically-integrated loading of BC was 207 µg/m2 in the north, 780 µg/m2 near Santiago, and 2500 µg/m2 in the south, where the snow season was longer and the snow was deeper. For samples collected at locations where there had been no new snowfall for a week or more, the BC concentration in surface snow was high (~10–100 ng/g) and the sub-surface snow was comparatively clean, indicating the dominance of dry deposition of BC. Mean albedo reductions due to light-absorbing impurities were 0.0150, 0.0160, and 0.0077 for snow grain radii of 100 µm for northern Chile, the region near Santiago, and southern Chile; respective mean radiative forcings for the winter months were 2.8, 1.4, and 0.6 W/m2. In northern Chile, our measurements indicate that light-absorption by impurities in snow was dominated by dust rather than BC.

Chile is a long and narrow country spanning 38 degrees of latitude; it is therefore characterized by varied climate and varied response to climate drivers. Te Andes act as a critical “water tower”, providing the main source of freshwater for Chile from snowpack and glacier runof, wetlands and groundwater sources1–5 Climate warming along the Chilean Andes6,7 has resulted in the rapid loss of glaciers from the tropical Andes in the north8 to Patagonia and Tierra del Fuego in the South9. In central Chile, persistent drought in 2010–2015 reduced the snowpack, resulting in declines in river fow10. About half of the observed decline in precipitation since the 1970s in central Chile has been attributed to anthropogenic climate change11. Furthermore, general circulation models suggest that warming rates at higher elevations in the central Andes will outpace those for surrounding areas2,12,13 Te past few decades have seen a regional enhancement of mid-tropospheric warming in the central Andes13 but the cause of the enhancement is unclear. Such warming increases the fraction of precipitation that falls as rain rather than snow, leading to earlier melting and peaks in river runof1. For Chile, where the snowpack acts as a signifcant water reservoir, this can result in fooding in winter and spring, followed by water shortages in late

1Universidad de Santiago de Chile, Santiago, Chile. 2NorthWest Research Associates, Redmond, WA, USA. 3Department of Atmospheric Sciences, University of Washington, Seattle, WA, USA. 4University of Puget Sound, Department of Chemistry, Tacoma, WA, USA. 5Joint Institute for the Study of Atmosphere and Ocean, University of Washington, Seattle, Washington, USA. 6Leibniz Universität Hannover, Institute of Meteorology and Climatology, Hannover, Germany. 7Unidad de Glaciología y Nieves, Dirección General de Aguas (DGA), Ministerio de Obras Públicas (MOP), Santiago, Chile. 8Centro de Investigación GAIA Antártica, Universidad de Magallanes, Punta Arenas, Chile. 9Centro de Estudios Avanzados en Zonas Áridas (CEAZA), La Serena, Chile. 10Center for Environmental Remote Sensing, Chiba University, Chiba, Japan. 11Department of Physical Geography, Pontifca Universidad Catolica de Chile, Santiago, Chile. 12Universidad de Chile, Santiago, Chile. 13Center for Climate and Resilience Research CR2, Universidad de Chile, Santiago, Chile. 14Laboratorio de Análisis Isotópico, Facultad de Ingeniería, Universidad Nacional Andrés Bello, Viña del Mar, Chile. Correspondence and requests for materials should be addressed to P.M.R. (email: [email protected])

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spring and summer. Furthermore, model simulations predict a climatic trend of decreasing precipitation over the central and southern Andes, from 10°S to 45°S, even under strong reduction of greenhouse gas emissions14, with important implications for Chile’s water supply, particularly in central Chile (30–37°S) where 78% of the population is concentrated. Because of the importance of snowpack as a source of freshwater for Chile, quantitative estimates of radiative forcing are key to predicting changes in runof timing of snowpacks due to deposition of light-absorbing aerosol in snowpacks15. An important light-absorbing aerosol to quantify is black carbon (BC), an anthropogenic pollutant emitted during combustion, such as by coal-burning power plants, vehicles (particularly diesel), wood-burning stoves, agricultural fres, and forest fres16. Light-absorbing organic carbon (“brown carbon”) is ofen co-emitted with the BC as a component of carbonaceous aerosol. In the atmosphere, this carbonaceous particulate material contributes to respiratory problems and can interact with sunlight to afect climate16. When deposited on snow, light-absorbing carbonaceous particles reduce the albedo, leading to increased absorption of solar radiation. Tis triggers a positive feedback whereby the warmer snowpack ages more rapidly, further lowering albedo (through grain-size growth), ultimately accelerating surface snowmelt. Surface snowmelt then leads to the accumulation of particulate impurities at the snow surface17, further lowering albedo and accelerating melt. Te darker underlying surface then becomes exposed earlier, leading to more absorption of sunlight and more melt18. Deposition of mineral dust similarly reduces snow albedo, with the same feedback processes, but scaled down by a factor of about 200 at visible wavelengths, by mass19. At high enough concentrations, the reduction of snow albedo by BC and mineral dust can signifcantly afect glacier mass balance and snow cover18,20. When dust thickness exceeds a critical depth of about 15 to 50 mm, it acts as an insulating layer and melting rates become lower than that of dust-free snow21. It is expected that the main source of BC in northern Chile is emissions from diesel engines that power the mining industry and major astronomical observatories. Near Santiago (latitude 33.3°S), sources include emissions from transport (e.g. diesel), industrial pollution and residential heating. Tese emissions are trapped by the topography and the persistent wintertime temperature inversion22. In southern Chile (from 35°S to 47°S), the main source of heating is wood stoves, and thus the main source of particulate pollution is expected to be emissions from wood burning. Surveys of BC in snow have been conducted in a variety of locations with various techniques, including thermo-optical methods and the SP2 instrument16, as well as flter-based methods, including the Light Absorption Heating Method23 and the Integrating Sphere Integrating SandWich (ISSW) spectrophotometer method24–26. Te ISSW uses the wavelength dependence of measured light absorption to estimate the concentration of BC as well as the absorption Angstrom exponent (Åtot) of all light-absorbing insoluble particles. Te latter is used to estimate the non-BC fraction of light absorption. Light-absorbing impurities in snow have been measured with the ISSW spectrophotometer in the Arctic24,26, northern China27,28 and central North America29. Median BC content was found to range from 3 ng/g in Greenland26 to 1220 ng/g in northeast China28. Here, we present measurements of BC and other light-absorbing impurities made in the Chilean Andes using the ISSW spectrophotometer during two winters, one in northern Chile in 2015, and the other in central and southern Chile in 2016. As a frst step toward quantifying the infuence of BC in the Chilean Andes on snowmelt, we present albedo reductions and radiative forcings for a variety of snowpacks in the Chilean Andes. Te paper is organized as follows: Section 2 details the feld campaigns and describes the methods of sample collection, fltration, and analysis. Sections 3–5 present results, discussion, and conclusions. Methods Sample sites. Snow was sampled at 22 locations between Putre (S 18°, W 69°) and Osorno (S 41°, W 72°). Te sampling sites are assigned to one of three groups: northern Chile (18.1–32.9°S, Table 1 and Fig. 1a); the Santiago area (33.3–33.8°S, Table 2 and Fig. 2); and southern Chile (35.1–41.1°S, Table 3 and Fig. 1b). Topographic maps showing the sample sites are given in Figs S1–S2 of the Supplemental. Sampling in the north occurred in one north-south transect from 4 to 27 July 2015. Sampling in the south occurred during two north-south transects in 2016: 13–21 July and 19 August – 1 September. Sampling near Santiago was done in both winters 2015 and 2016. Te individual sample sites are described below; photographs of some of the sites are shown in Fig. 3. Date of sampling, latitude, longitude, elevation and total snow depth are given for each site in Tables 1–3. Sites are listed in latitude order; for each site where sampling occurred more than once, sequential samples are listed in order of date.

Sites in northern Chile. Te Andes of northern Chile are bordered to the west by the Atacama Desert, and are characterized by being dry and dusty, with minimal vegetation. During our sampling in the far north of Chile the snow was thin and present only at higher altitude. Moving south, the snow cover and snow depth generally increased and the snow line generally dropped in altitude, allowing sampling to occur at lower altitudes, as indicated in Table 1. Sites are marked in the map in Fig. 1a. As indicated in Table 1, northern sites were visited sequentially from 4 July to 20 July 2015.

Sites near Santiago. Snow was sampled at fve sites near Santiago, all within 1 degree of latitude of each other. Santiago is by far the largest city in Chile, with a large fraction of the country’s population (6.5 million people out of 17.9 million people in Chile as of 2017). Te topography and persistent wintertime temperature inversion traps urban pollution and leads to smog, along with high levels of PM 2.5 and PM1022. During winter, the mixing layer height can drop to 100 m in early morning and has an average height of 200 m at local noon30. Within the daytime temperature inversion, the temperature increase is 3–6 K with an inversion top of 600 to 900 m31. Accumulations of soot particles are visible on balconies in the city. As shown in Table 2, sites near Santiago were visited in July 2015, and June, July and August 2016. Sites are marked in the map in Fig. 1b.

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Longitude Elevation Depth Site Location Date Latitude (°S) (°W) (m) (cm) 1a Putre 2015/07/04 18.0904 69.5368 4707 1 1b Putre 2015/07/05 18.1024 69.5206 5318 15* 2a San Pedro 2015/07/10 22.9526 67.7773 5370 80* 2b San Pedro 2015/07/10 22.9989 67.7580 5062 15 3a La Ola 2015/07/14 26.4593 69.0579 3578 13 3b La Ola 2015/07/14 26.4593 69.0579 3578 8 3c La Ola 2015/07/14 26.4547 69.0502 3624 35 4a Elqui 2015/07/17 29.9452 70.078 2341 22 4b Elqui 2015/07/17 29.9630 70.0857 2190 14 5 Las Ramadas 2015/07/19 30.9606 70.5559 1757 8 6a Choapa 2015/07/20 32.0795 70.5927 1919 6 6b Choapa 2015/07/20 32.0637 70.5951 1902 9

Table 1. Snow sampling sites in northern Chile. Depth indicates the total depth of the snowpack, except as noted. *Tese two sites were on glaciers or permanent snowfelds, so for them we give the sampling depth rather than the total depth.

Sites in southern Chile. In contrast to northern and central Chile, southern Chile has frequent precipitation and abundant vegetation. Concentrations of mineral dust in snow are therefore expected to be low, relative to northern Chile. Southern Chile is considerably colder in winter (the average temperature in June is 17 °C in Arica and 7 °C in Osorno). Residential wood combustion is the main source of pollution for many cities in southern Chile32. Tus, a high incidence of black carbon is expected in snow in southern Chile, particularly relative to mineral dust. Sites are indicated on the map in Fig. 1.

Sample Collection and Filtration. Sample collection and fltration follows the methodology of Doherty et al.17,26,29. Samples were collected at vertical intervals of 5 to 8 cm depth from the surface (exposed to the air) down to the solid ground. Typically, two parallel vertical profles were collected, separated by a horizontal distance of 1 to 2 m. To minimize pollution due to nearby sources of transportation, sites were chosen to be approximately 1 km away from any roads when possible. Samples were collected with a metal spatula into plastic food-handling bags, which were then packed in plastic Whirlpak bags. Food-handling bags were used for the inner bags because prior work indicated that BC adheres least to them, compared to other types of plastic26,28. To minimize the amount of particulates that adhered to the plastic bag with melting, the snow was stored in freezers or insulated containers, when possible, until immediately before fltration. Te depth profle of snow density was also measured at each site. Filtering was performed on a clean table or lab bench, pre-cleaned for dust and dirt. Gloves and lab coats were worn. Snow from Putre and San Pedro was fltered in temporary laboratories set up in local accommodations; snow from other locations was fltered in University laboratories. In southern Chile and near Santiago in 2016, bagged snow samples were stored in Styrofoam coolers to keep them at near-freezing temperatures during transportation to a freezer in a University; samples were thereafer kept frozen until they could be fltered in the University laboratory. Because particulate matter adheres to glass less than it adheres to plastic, the snow was transferred to a glass beaker for melting, then the beaker was covered with a plastic bag to prevent external contamination. Te snow was heated in a microwave oven until just melted, to avoid heating of the meltwater. A 0.4-µm Nuclepore flter was placed in a flter holder mounted on top of a side-arm fask. A stainless-steel funnel was clamped above the flter holder. Te meltwater was then vacuum-fltered with a hand pump or electric pump through the flter. Afer fltering, flters were carefully placed in sterile petri dishes. Te petri dishes were opened slightly to allow the flters to air dry, afer which the petri dish lid was kept closed until optical analysis was performed. Te mass of snow fltered was adjusted with the goal of producing flters with loadings within approximately 0.4 to 40 µg/cm2, to stay within the measurement-sensitivity range of the spectrophotometer (described in Section 2.3); flters determined to be outside the spectrophotometer measurement range were discarded. Te meltwater volume was measured. Te funnel, flter holder, and beaker were cleaned afer each fltration with ultrapure water.

Optical Analysis. Optical analysis of flters is performed with the ISSW spectrophotometer described by Doherty et al.29, which is a modifed version of the instrument developed by Grenfell et al.25. Te ISSW confgura- tion includes a sample flter sandwiched between two integrating spheres, positioned above and below the sample flter. Input light is fed via fber optics through a side port into the lower sphere, and light exits through a side port in the upper sphere to the spectrometer via a fber optic. Bafes prevent direct light from passing through the flter and prevent light from the flter from passing directly out through the side port; thus, only difuse light is transmitted to the detector. Te ISSW has a spectral range of 450–750 nm and has a measurement resolution of 1 nm which is then averaged to 10 nm. Te spectrum of light attenuation recorded by the spectrometer needs to be calibrated in order to convert the measured signal to a loading of BC on the flter. Tis is done using a set of standards with a range of known loadings of fullerene, a synthetic black carbon (Alfa Aesar, Inc., Ward Hill, MA, USA), as described by Grenfell et al.25. Te calibration curves express the light attenuation as a function of fullerene loading in µg/cm2. Assuming fullerene is a reasonable proxy for ambient black carbon, comparison of the light attenuation by a sample flter to the light

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Figure 1. Sample sites in northern Chile (a) and southern Chile (b). Site numbers for the Santiago region are given in an expanded view in Fig. 2.

attenuation by the synthetic standards yields the BC-equivalent loading of the sample flter. Calibration is done sep- arately for each 10-nm bin, based on separate calibration curves made from the fullerene standards. Tis is necessary because the sample flter usually contains non-BC light-absorbing particles as well as BC particles, and the spectral shapes of non-BC and BC particles difer. Tus the BC-equivalent loading generally varies with wavelength. Starting from the wavelength-dependent BC-equivalent loading, we calculate the quantities given in Table 4. Tese are described below in turn (afer ref.29). max CBC is the average BC-equivalent concentration, calculated by assuming all absorption in the 650–700 nm wavelength band is due to BC. To convert from the measured fullerene-equivalent loading (µg BC-equivalent per cm2) to concentration, the average 650–700 nm loading is multiplied by the exposed area on the flter (cm2) and divided by the mass of snow water fltered (g), yielding µg/g. Tis is converted to ng/g, giving the mixing ratio as max ng BC per g of snow water. CBC represents the maximum possible black carbon in the sample. Also of interest is the amount of absorption due to non-BC particulate components. Here we use the absorption angstrom coefcient, Åtot, to discriminate between BC and non-BC components. Åtot is defned as:

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Longitude Elevation Depth Site Location Date Latitude (°S) (°W) (m) (cm) 7 Portillo 2015/07/21 32.8337 70.1331 2800 60 8a Juncal 2015/07/22 32.8709 70.1461 2249 28 8b Juncal 2015/07/22 32.8744 70.1430 2285 25 8c Juncal 2015/07/22 32.8810 70.1383 2277 20 8d Juncal 2015/07/22 32.8937 70.1264 2322 19 9a Yerba Loca 2016/06/18 33.2820 70.3030 2413 40 9b Yerba Loca 2016/07/25 33.3329 70.3278 1822 10 9c Yerba Loca 2016/07/26 33.3329 70.3278 1822 5 10a Valle Nevado 2015/07/24 33.3545 70.3120 2435 17 10b Valle Nevado 2015/07/24 33.3594 70.2635 2636 45 10c Valle Nevado 2015/07/24 33.3557 70.3108 2366 32 10d Valle Nevado 2015/07/24 33.3597 70.2528 2802 12 10e Valle Nevado 2015/07/24 33.3661 70.2551 2554 30 10f Valle Nevado 2016/08/18 33.3662 70.2545 2635 40 11a Valle Maipo 2015/07/26 33.4961 70.2765 2302 30 11b Valle Maipoa 2015/07/26 33.4961 70.2765 2308 15 11c Valle Maipo 2015/07/26 33.4968 70.2743 2236 15 11d Valle Maipo 2015/07/27 33.8074 70.0122 2392 >60

Table 2. Snow sampling sites near Santiago, Chile. Note that locations are given in order of latitude, rather than by date. Depth indicates the total depth of the snowpack. aSite 11b was about 20 m away, and about 6 m uphill, from 11a.

Figure 2. Sample sites in the region near Santiago.

−τln[(abs1λτ)/ abs2()λ ] Åtot = ln(/λλ12) (1)

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Longitude Depth Site Location Date Latitude (°S) (°W) Elevation (m) (cm) 12 Curicó 2016/08/19 35.1363 70.479 1860 60 13 Maulea 2016/08/20 35.9888 70.5625 1860 90 14a Chillán 2016/08/22 36.9073 71.3999 1963 40 14b Chillán 2016/07/13 36.9216 71.4916 1554 25 15 Antuco 2016/08/23 37.3679 71.3826 1494 20 16 Collaqui 2016/08/24 37.8764 71.4741 1142 10 17 Corralco 2016/08/27 38.4059 71.5595 1601 80 18 Lonquimay 2016/08/26 38.4255 71.4604 1652 50 19 Llaima 2016/08/28 38.5272 71.7957 1830 40 20a Villarrica 2016/07/21 39.3882 71.9618 1357 65 20b Villarrica 2016/08/29 39.3964 71.9647 1450 90 21a Antillanca 2016/07/19 40.7726 72.2121 1093 26 21b Antillanca 2016/09/01 40.7861 72.1921 1349 60 22 Osorno 2016/08/31 41.1200 72.5299 1326 50

Table 3. Snow sampling sites in southern Chile. Note that locations are given in order of latitude, rather than by date. aLaguna del Maule.

Figure 3. Pictures of snow sampling sites in the North (a,b), near Santiago (c,d), and in the South (e,f). Photographs were taken by the authors.

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Quantity Units Description Maximum BC mass concentration (assuming all light absorption at max ng/g CBC 650–700 nm is due to BC).

Åtot — Absorption Angstrom exponent 450–600 nm for all insoluble particles Estimated BC mass concentration (based on light absorption fractionated by est ng/g CBC Angstrom coefcient, assuming a value of 1 for BC and 5 for non-BC) Equivalent BC mass concentration (mass of BC that would be needed to cause equiv ng/g CBC the 300–750 nm light absorption by all insoluble particles in the sample) Estimated fraction of 300–750 nm sunlight absorption due to non-BC est — f NBC constituents Integrated BC µg/m2 Column-integrated BC mass in snowpack

Table 4. Quantities calculated from ISSW measurements. Te wavelength range given is that used to calculate the quantity, as described in the text. Mass ratios are ratios with respect to snow water mass.

Herein, Åtot is calculated as a linear ft to absorption vs. wavelength in log-log space between the wavelengths λ1 = 450 nm and λ2 = 600 nm. Te absorption optical depth τabs is the mass absorption coefcient of fullerene multiplied by the BC-equivalent loading. Te mass absorption coefcient of fullerene is 8.9 m2/g at 450 nm and 2 6.5 m /g at 600 nm. Pure BC has ÅBC = 1.1. For non-BC, we assume that ÅNBC = 5, based on prior work by Grenfell 25 26 et al. and Doherty et al. . Te deviation of Åtot from 1.1 is therefore an indication of the amount of absorption by non-BC components in the snow. est 25 CBC is calculated following the method of Grenfell et al. :  est  τ  est max BC 650−700  CCBC = BC  ,  τMAX   BC 650−700  (2) where

est τλBC()0B=λr(C0)(×τtot0λ.) (3)

Te value rBC (λ0) is the fraction of absorption due to BC at a given wavelength λ0, and it is determined by assuming that

ÅrtotB=+CBÅ(CB1r− CN)Å BC, (4)

where Åtot is the measured absorption Angstrom exponent of all particles on the flter and, as given above, ÅBC = 1.1 and ÅNBC = 5.0, with rBC defned over the same wavelength range as the values of Åtot. Rearranging Eq. (4) yields rBC. Te value for τtot(λ0) is L0 β0, where L0 is the BC-equivalent loading and β0 is the mass absorption efciency of fullerene at the given wavelength. Furthermore, τ as a function of wavelength is given by

 est est −ABC τλBC()=τBC()λ×00(/λλ) . (5) max To calculate τBC ()λ the frst term on the right is replaced with τtot(λ0). equiv CBC is the mass of BC that would be needed to account for the integrated 300–750 nm solar absorption by all particulates on the flter. It is calculated by weighting the spectral, all-component (total) absorption by the down- 29 equiv max max welling solar irradiance spectrum . CBC difers from CBC in that CBC represents the maximum mass of BC equiv possible, whereas CBC represents the amount of absorbing material present, whether BC or not, expressed as an max equiv equivalent BC mass. CBC is quantifed at 650–700 nm, whereas CBC is quantifed for 300–750 nm; since non-BC equiv max components will absorb more strongly at shorter wavelengths, CBC is always greater than or equal to CBC . est Te fraction of solar absorption integrated across 300–750 nm by non-BC particles, f NBC, is calculated by “(1) extrapolating the absorption spectra linearly from 450 nm down to 300 nm25,26; (2) weighting the non-BC absorp- tot est tion spectra (τBC()λ − τBC()λ ) and all-component (total) absorption spectra (τtot(λ0)) by a downwelling solar irradiance spectrum appropriate for clear-sky, mid-latitude winter; (3) integrating these weighted spectra across the visible range; and (4) taking the ratio of the two integrals”29. In addition to reporting concentrations in given snow layers, the vertically-integrated BC mass, “Int BC”, was calculated as follows: First, the snow water equivalent is calculated in each sample layer by multiplying the snow density (g/cm3) by the layer depth (cm). Te BC amount within each sampled layer of snow is then calculated by est 2 2 multiplying CBC (ng/g) by the snow water equivalent (g/cm ), yielding a BC mass per unit area (ng/cm ). Tis is done for each sampled layer, and the BC mass from all layers summed together to give integrated BC for the snow column, which is reported in µg/m2. Because it is difcult to sample all the way to the ground without contamina- est tion by soil, the BC amount for the last few centimeters is typically estimated from CBC and the density of the layer sampled immediately above. For a given sample site, measurements within a few hundred meters, if made on the same day, are averaged. In such cases, a nearby measurement may be used to fll in missing values (e.g. in a case where flter loading from one sample was too high for an accurate measurement).

Estimating albedo reduction and radiative forcing. Te albedo reduction and radiative forcing due to light-absorbing impurities in snow were calculated using the method of Dang et al.33, and making use of the

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parameterization of Dang, Brandt, and Warren19, as follows. Te all-sky broadband albedo reduction was calculated according to

δα =×CF δαcloudy +−(1 CF),δαclear (6) where CF is the cloud fraction. Monthly mean cloud fraction was determined from the CERES Terra + Aqua Edition 4A34. Monthly means for each of the three winter months (June, July, August) were averaged from 2000 to 2017 (Fig. 4a). Te albedo reduction was determined from the parameterization of Dang et al.19, which gives the albedo reduction for clear and overcast skies for a range of BC mass mixing ratios and snow grain radii. To get the albedo reduction due to BC, the albedo reduction was interpolated to the BC mass mixing ratio for a given value est of CBC. Tis was done for cloudy skies (yielding δαcloudy) and for clear skies (yielding δαclear), afer which Eq. (6) equiv was applied. Tese steps were repeated for CBC to calculate the albedo reduction for all light-absorbing impurities. Albedo reductions due to BC and due to all light-absorbing impurities were calculated for the months of June-July and for snow grain radii of 100 and 1000 µm. Te radiative forcing is calculated as the albedo reduction times the all-sky shortwave fux, where the latter is also taken from CERES (see above and Fig. 4b) and averaged over the years 2000 to 2017. Albedo reductions and radiative forcings were not calculated for every site given in Tables 1–3, but rather for est equiv median values of CBC and CBC for each location (e.g. the median for all the Putre sites, etc.), except when the locations were separated by a large altitude diference or when the site was revisited on diferent days. Results est est Latitude dependence of light-absorbing impurities. CBC, Å, f NBC, and Integrated BC (Int BC) are shown as functions of latitude in Fig. 5. Sampling sites are color-coded and listed in the legend, from north to south; the color coding is the same as for the site labels in the maps shown in Figs 1 and 2. One point is plotted for each layer sampled; typically these are averages of two samples made for the same layer, although sometimes more or fewer samples were taken of a given layer. At some sites, samples were taken at diferent locations within the site area, or the site was revisited on a diferent date, as indicated in Tables 1–3. For Fig. 5d (lower right), which shows the estimate of snow-column-integrated black carbon mass, values for sites within a few hundred meters and at a similar altitude were averaged. Multiple points are due to sample collections separated by a considerable distance, altitude, or for diferent conditions at the same site (e.g. La Ola, where one set of samples was made in a snow drif) or due to revisiting the site at a later date (e.g. Valle Nevado). Points are missing where snow density was not measured (e.g. Putre) or where there was no surface measurement.

est max equiv Surface snow. Table 5 gives values for Åtot, CBC, CBC , and CBC for surface samples at each location. Te layer thickness of the surface sample is also shown in the table. Medians were calculated across all surface samples from a given location, except when the locations were separated by a large altitude diference or when the site was revisited on diferent days. (Tese values are given for each layer in each sampling site in Tables S1–S3 of the Supplemental).

Regional results. Regional averages and standard deviations for measurements in northern Chile, the Santiago region, and southern Chile are given in Table 6. In northern and southern Chile, where there were sometimes large distances between sites, the average and standard deviation for each site were geographically weighted by the increment of latitude that the site was judged to represent. Values shown in the table include surface meas- est max equiv est urements of Åtot, CBC, CBC , and CBC (as well as the subsurface values for C)BC , the total snow depth, snow water equivalent, integrated black carbon, and average black carbon. For subsurface and snowpack measurements, averages in the north exclude Putre, where snow density was not measured. Also shown in Table 6 are the albedo reductions due to light-absorbing impurities in snow for BC alone and for all light-absorbing impurities and the resulting radiative forcing; these are discussed below.

Albedo reduction and radiative forcing. Figure 4a,b show the cloud fraction and shortwave fux for the Austral winter months June, July, and August. While cloud fraction does not change much with month, it increases substantially from north to south. Shortwave fux changes considerably with both latitude and month. Figure 4c shows the albedo reduction due to all light-absorbing impurities in snow for each site shown in equiv Table 5 (for the values of CBC given in the table) assuming snow grain radii r = 100 µm (small symbols) and r = 1000 µm (large symbols). The choice of these representative grain sizes is explained by Wiscombe and Warren 35 and Warren36. Because new snow is typically fne-grained, the albedo reduction is plotted for r = 100 µm for the beginning of winter (June in the north; July in the south). By contrast, melting snow is typically coarse-grained; thus the albedo reduction is plotted for r = 1000 µm for the melt season (July in the north, August in the south). Te albedo reduction and radiative forcing are greatest in the far north and in the Santiago region. Albedo reductions and radiative forcings for regional averages are given in Table 6 for 100 and 1000 µm snow grains and for BC-only and all light-absorbing impurities. Discussion Latitude dependence of non-BC light-absorbing impurities. Te contribution of non-black carbon constituents to particulate absorption shows a trend with latitude, decreasing southward. Te fraction of absorption from non-BC decreases from around 0.9 near San Pedro to 0.1 at the southern-most site of Osorno (Fig. 5c). Te far north is a desert where large amounts of dust may be lofed into the air by natural and human causes (see, e.g. Fig. 6). In contrast, the southern region is characterized by frequent precipitation and the atmosphere is therefore less dusty.

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Figure 4. (a) Monthly mean cloud fraction and (b) Downwelling shortwave all-sky fux at the surface (CERES Terra + Aqua Edition 4 A; https://ceres.larc.nasa.gov/products-info.php?product=SYN1deg) averaged over 2000–2017. (c) Te albedo reduction and (d) the radiative forcing due to light-absorbing impurities for snow- grain sizes of 100 µm (small symbols; plotted for June in the north, July in the south) and 1000 µm (large symbols; plotted for July in the north and August in the south).

How much the Angstrom exponent, Åtot, deviates from 1.1 is an indication of the relative contribution of non-BC particles to the light-absorption. Starting at the north end of Chile and moving south, Åtot frst increases from about 2.5 at Putre (Site 1), to a maximum of ~5 at La Ola (Site 3; Fig. 5b), then decreases to a minimum of 1.1–1.9 at Osorno (Site 22), indicating minor contribution from non-BC at Osorno. Tis geographic trend in Åtot holds for samples from all layers (Fig. 5b). For surface samples, the trend is also the same, except that Åtot peaks at Site 2 above San Pedro (Åtot = 4.5; Table 5). Particles with Åtot near 1.0 are essentially black, indicating their light-absorbing component is nearly all 16 black carbon (Bond et al. ), indicating a combustion source for particulate matter. Te low values of Åtot at our southern sites are consistent with a combustion source for the snow particulate matter. Added to the knowl- edge that wood-burning is the main source of heating in this region and the lack of dust sources we infer that light-absorbing particles in snow are dominated by carbonaceous aerosols. To the north, the high values of Åtot of 3 to >5 indicate a much larger contribution from non-BC sources. Previous measurements with the ISSW 26,28,29 coupled with chemical analyses (refs ) indicate that these high values of Åtot could be due to very high brown carbon to black carbon ratios in combustion-sourced aerosol or, more likely for the highest values seen here (>3), due to dust. Dust as the dominant source of light-absorbing particles to snow in northern Chile is consistent with the low population density, the proximity of dust sources and the low snow-cover fraction. Precise attribution of absorption to sources using Åtot is not possible. We have assumed that ÅNBC is 5.0. If the particulate absorption at Site 3 is in fact essentially all due to non-BC (e.g. dust), this supports the validity of using ÅNBC = 5.0 for this region. If, in fact, there is a signifcant contribution to absorption by BC even at Site 3, ÅNBC

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Figure 5. (a) Concentration of black carbon, (b) the absorption angstrom exponent, (c) fraction of absorption due to non-black-carbon light-absorbing impurities, and (d) vertically integrated black-carbon loading. Black bars to the right in each panel separate northern Chile, the Santiago region and southern Chile.

est should be higher; in this case, our reported values of CBC will be too low and, correspondingly, our attribution of absorption to brown carbon and dust will be too high. Regardless, trends in Åtot are strongly indicative of compo- sitional trends in light-absorbing particulate matter in snow.

est Latitude dependence of black carbon. As shown in Fig. 5a, CBC decreased southward to a minimum above Elqui (Site 4), then increased continuing south to the Santiago area (Sites 7–11), and fnally decreased gradually southward to Osorno (Site 22). In the north, this trend is consistent with the trend for non-BC, suggest- ing that the snow becomes overall cleaner moving south from the far north of Chile (Putre) to Elqui. est est Te trend for CBC described above is in keeping with the regional averages, for which CBC is highest near est Santiago. Near Santiago there is a lot of variation in CBC from site to site, which may be linked to the infuence of dry deposition, as will be discussed below. Te integrated black carbon is a metric for total BC deposition over the period of snowpack accumulation. For est regional averages, both integrated black carbon and snow depth increased southward. CBC for surface samples in the Santiago region is higher than the value for southern Chile; however Santiago has considerably less integrated BC. Te values for average BC are the same. Te explanation is that there can be high BC concentrations but low column-integrated BC mass if the snowpack is thin.

Wet vs. dry deposition. Te above observations alone do not permit unambiguous identifcation of the dominant mechanism of BC deposition (dry deposition, in which BC settles onto snow from the atmosphere, or wet deposition, in which BC is transferred to snow via precipitation), because of a number of complicating fac- est tors. One complication is that the sets of numbers used to compute CBC, the integrated BC, and the subsurface BC

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est max equiv Latitude Elevation Sample CBC CBC CBC Dates Location (°S) (m) Depth (cm) Åtot (ng/g) (ng/g) (ng/g) 2015/07/04 Putre 18.1 4700 0–5 2.8 25 34 50 2015/07/05 Putre 18.1 5300 0–5 2.3 74 93 121 2015/07/10 San Pedro 23.0 5200 0–5 4.5 15 81 166 2015/07/14 La Ola 26.5 3600 0–7 4.1 5 12 23 2015/07/17 Elqui 29.9 2300 0–5 4.0 2 5 10 2015/07/19 Las Ramadas 31.0 1800 0–4 3.5 5 8 15 2015/07/20 Choapa 32.1 1900 0–5 2.8 9 13 19 2015/07/21 Portillo 32.8 2800 0–5 2.6 6 8 11 2015/07/22 Juncal 32.9 2300 0–5 2.4 15 21 25 2016/06/18 Yerba Loca 33.3 2400 0–8 2.0 15 17 21 2016/07/25 Yerba Loca 33.3 1800 0–5 1.0 1 1 1 2016/07/26 Yerba Loca 33.3 1800 0–5 2.0 9 10 13 2015/07/24 Nevado 33.4 2500 0–10 3.3 91 153 279 2015/07/26 Maipo 33.5 2300 0–5 3.7 30 72 121 2015/07/27 Maipo 33.8 2400 0–5 3.1 21 32 50 2016/08/19 Curicó 35.1 1860 0–10 2.8 27 31 50 2016/08/20 Maule 36.0 1860 0–10 2.1 17 19 26 2016/07/13 Chillán 36.9 1600 0–5 1.5 5 6 6 2016/08/22 Chillán 36.9 2000 0–10 1.7 15 16 20 2016/08/23 Antuco 37.4 1500 0–5 1.8 12 13 15 2016/08/24 Collaqui 37.9 1100 0–5 1.6 5 6 6 2016/08/27 Corralco 38.4 1600 0–10 1.5 5 5 5 2016/08/26 Lonquimay 38.4 1700 0–5 1.5 6 6 6 2016/08/28 Llaima 38.5 1800 0–5 2.1 7 9 12 2016/07/21 Villarrica 39.4 1400 0–5 1.7 10 10 12 2016/08/29 Villarrica 39.4 1500 0–5 2.0 11 13 17 2016/07/19 Antillanca 40.8 1100 0–5 1.5 11 12 12 2016/09/01 Antillanca 40.8 1300 0–5 1.1 7 7 7 2016/08/31 Osorno 41.1 1300 0–5 1.2 5 5 5

Table 5. Median values at each location for the surface layer of snow.

vary slightly due to missing data and variations in snow depth (e.g. there was not always a subsurface layer to sample). Tis is particularly important for the Santiago area (as well as in the north), where snow depth was typ- est ically thinner and where there were large variations in CBC (110%) and integrated BC (66%). In southern Chile the variations were smaller, 70% and 52%, respectively, indicating a more uniform snowpack. It is furthermore worth noting that if snow cover is intermittent at a given location, then the column-integrated BC mass will not refect total BC deposition for the winter, whereas if there is no loss of snow particulate matter to melting, the column-integrated BC will refect the total BC deposition since snowfall started. Tere are, however, situational factors that help constrain this distinction; an exploration of wet vs. dry deposition using a few case studies follows. Meteorological data and observations suggest a lack of snowfall in northern and central Chile from 1 to 6 July 2015, with the exception of a light snowfall on 4 July at Site 1, Putre (observed by the sampling group). On 5 and 6 July a cold front may have resulted in some snowfall in the mountainous region east of Santiago. Another front brought snowfall to the Santiago area on 11 and 12 July and to Elqui on 13 July. Blizzard conditions with snow and wind were experienced at La Ola on 13 July, the day before sampling was performed. On 16 July a less intense front brought some snowfall to the mountains east of Site 4, Elqui, but no precipitation was measured at the station near the Elqui sampling site. Tere was no evidence of additional snowfall for the remainder of the 2015 feld season. Further details are given in the Supplemental. Based on the above as well as reports from locals near the feld sites, Table 7 gives estimates of days since last est snowfall, CBC for both the surface and sub-surface snow, and integrated BC for many of the sites for the 2015 feld season. In northern Chile and the Santiago area, the date of the most recent snowfall could be estimated from observations and weather reports. As shown in Table 7 and in Fig. 7, the contamination of the surface layer and the integrated black carbon mass both generally increased with time. Given that the subsurface samples are relatively clean everywhere, proximity to Santiago seems unlikely to be a major factor. Instead, the relative dirtiness of the surface snow suggests that dry deposition plays a major role. In addition, consolidation of BC in the surface layer with snow melt17 may be playing a role, as well as sublimation of the surface snow at high elevations in the dry Andes37.

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Northern Santiago Southern Chile Region Chile Latitude (°S) 18.1–32.1 32.8–33.5 35.1–41.1

Åtot 3.8 ± 0.2 2.6 ± 0.7 1.9 ± 0.2 est CBC (ng/g) 15 ± 4 28 ± 35 13 ± 3 max CBC (ng/g) 40 ± 9 45 ± 61 15 ± 3 equiv ± ± ± CBC (ng/g) 72 17 75 115 20 6 est CBC, subsurf (ng/g) 15 ± 5 7 ± 3 11 ± 1 Deptha (cm) 12 ± 1 38 ± 21 54 ± 9 SWEb (kg/m2) 100 ± 21 98 ± 71 330 ± 110 Int BCc (µg/m2) 207 ± 46 780 ± 510 2500 ± 440 Ave BCd (ng/g) 6 ± 1 11 ± 11 12 ± 1 e −4 δαBC, 100 µm (10 ) 54 92 60 −4 δαBC, 1000 µm (10 ) 170 280 190 δα,f 100 µm (10−4) 150 160 77 δα, 1000 µm (10−4) 440 480 240 g 2 RBC, 100 µm (W/m ) 1.0 0.8 0.5 2 RBC, 1000 µm (W/m ) 3.3 2.7 1.9 R,h 100 µm (W/m2) 2.8 1.4 0.6 R, 1000 µm (W/m2) 8.6 4.6 2.4

Table 6. Regional averages and standard deviations. Standard deviations represent the deviations among the est max equiv est diferent sample sites. Åtot, CBC, CBC , and CBC represent measurements made for the surface layer; CBC, subsurf is for subsurface layers; and the fnal rows are for all layers. Te values of albedo-reduction and radiative forcing (bottom 8 lines) are given for two snow-grain radii, 100 and 1000 µm. For 100 µm radii they are given for June at latitudes north of 33.5°S and July for the south. For 1000 µm radii they are given for July at latitudes north of 33.5°S and August for the south. aDepth of snowpack. bSnow water equivalent (SWE), integrated through the snowpack. cIntegrated black carbon (Int BC) estimate for snow pack. dAverage black carbon (Ave BC) estimate for snowpack, as Int BC/SWE. eAlbedo reduction for BC-only. fAlbedo reduction for all light- absorbing particles in snow. gRadiative forcing, BC-only. hRadiative forcing, all light-absorbing particles.

Figure 6. Dust trail from a truck in northern Chile. Photograph was taken by the authors.

Data from meteorological stations suggest that most of the precipitation from 27.2 to 33.4°S was due to the passage of a front on 12 July, with small amounts of precipitation in this latitude range the following day for stations from 33.3 to 33.4°S. However, precipitation was measured at Santo Domingo at 33.39°S on 5 July. Tus it is possible some of the subsurface snow sampled at Valle Nevado and Valle Maipo was seven days older, consistent with the dirtier subsurface snow observed there. Near Santiago, measurements made on sequential days more clearly indicate the importance of dry deposition. At Yerba Loca, near Santiago, the full column of the snowpack was sampled two days in a row (25 and 26 July 2016) at nearby locations, allowing for determination of the dry-deposition rate. Te snow was melting and the depth decreased from 10 to 5 cm, while the snow density increased from 0.19 to 0.44 g/cm3. Te snow-column-integrated BC increased from 31 to 200 µg/m2, indicating that the new snowfall in the Santiago area was relatively clean, and light-absorbing impurities arose mainly from dry deposition.

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Days since est est Date Location snowfall CBC surface (ng/g) CBC subsurface (ng/g) 2015/07/14 La Ola 1 5 0 2015/07/17 Elqui 4 2 1 2015/07/19 Las Ramadas 6 5 — 2015/07/20 Choapa 7 9 1 2015/07/21 Portillo 8 6 7 2015/07/22 Juncal 9 14–18 6 2015/07/24 Valle Nevado 11 46–110 12 2015/07/26 Valle Maipo 13 21–31 6 2016/07/25 Yerba Loca 0 1 — 2016/07/26 Yerba Loca 1 9 —

Table 7. Estimated number of days since the last snowfall before sampling, and median surface and subsurface black carbon concentration s, in northern and central Chile.

Figure 7. Vertical profles of BC. Te four sites all experienced snowfall in the same storm. Te sampling progressed from north to south over 9 days; the estimated number of days since snow fell (4–13 days) is given for each site.

Aerosol deposition rate near Santiago. Te freshly fallen snow of 25 July 2016 at Yerba Loca was quite clean both in terms of the BC concentration and in terms of the non-BC contribution to absorption, which was negligible. On 26 July particulate absorption included a signifcant contribution by non-BC components, as Åtot est increased from ~1.1 to 2.0 and f NBC increased from a negligible value to 0.3. Since no snow fell between these two days, this contribution must have been via dry deposition. The deposition rate is estimated as the difference in integrated BC mass divided by the time difference, or 17.3 ng/cm2-day. This is equivalent to 5.2 mg/m2-month, which is roughly comparable to the estimated inter-monsoon dry-deposition rate of BC in the Himalayas (see Fig. 3a in Menegoz et al.38).

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Trend in BC with distance from a major highway. To determine whether signifcantly more BC is deposited close to major highways, measurements were made at varying distances from the Trans-Andean highway to the southeast of Juncal, in the Juncal National Park. Measurements were made 3.64 km, 1.89 km, 1.05 km, and 0.561 km from the highway (Sites 8a-d). Moving along this transect toward the highway, the surface black-carbon estimate was 15, 15, 14, and 18 ng/g. Tus black carbon from vehicles does not seem to be preferen- tially deposited near the road.

Albedo reduction and radiative forcing. Albedo reduction and radiative forcing due to impurities in snow in the Chilean Andes are found to be greatest in the far north and in the Santiago region. For example, under all-sky conditions, mean albedo reductions due to light-absorbing impurities in snow in the Chilean Andes are estimated to be 0.0150, 0.0160, and 0.0077 for northern Chile (in June), the region near Santiago (in June), and southern Chile (in July), respectively, for snow grain radii of 100 µm (representative of new snow). Likewise, mean radiative forcings are estimated to be 2.8, 1.4, and 0.6 W/m2, respectively. In northern Chile, BC plays a smaller role in albedo reduction than non-BC. For example, albedo reduction for 100 µm snow grains due to BC alone is only about 43% of that for all light-absorbing impurities. By comparison, these albedo reductions are 53% and 82% near Santiago and in southern Chile, where a greater share of light absorption is due to BC.

equiv Comparison to other measurements. Te regional means and standard deviations of CBC for northern Chile measured in this work (refer back to Tables 5 and 6) are higher than values for measurements made in the Cordillera Blanca in Peru23. At an altitude of ~4900 m, Schmitt et al.23 measured mean efective black carbon values of 10 ± 7 ng/g and 17 ± 12 ng/g. By contrast, for the three sample sites at around 5000 m for this work, the equiv mean value of CBC was 112 ± 29 ng/g. Te mean for northern Chile, corresponding to altitudes of 1800–5300 m, was 72 ± 17 ng/g. est Regional averages of CBC in the top 5 cm of snow in the Arctic and North America were 27 ng/g and 29 ng/g (ref.33). Tis is comparable to the regional average near Santiago (28 ng/g; refer to Table 6), but is about twice as large as the regional averages for northern and southern Chile (~14 ng/g). Te subsurface snow was clean in the Andes (7 to 15 ng/g) compared to snow in the Arctic and North America (21 and 30 ng/g; ref.33). In northern Chile, a large fraction of the computed albedo reduction is due to non-BC. When only black carbon is considered, the albedo reduction due to BC is about 43% of that for all light-absorbing impurities (Table 6). Tis value and the value for snow near Santiago (53%) are roughly comparable to values for the Arctic, western North America, and China (53%, 49 to 78%, and 41%). By contrast, in southern Chile, black carbon accounts for a greater share of the albedo reduction (82%). Conclusions Based on snow-sampling measurements made in 2015 and 2016, the black-carbon mass-mixing ratio in snow in the Chilean Andes decreased southward from Putre (18.1°S) to the Elqui Valley above La Serena (29.9°S), afer which it increased continuing southward to the Santiago area (33.3°S), then again decreased from the Santiago area south to Osorno (41.1°S). Te contribution of non-BC light-absorbing components to particulate absorption in snow decreased dramat- ically from north to south, as expected given the transition from the dusty, vegetation-sparse Atacama Desert to the wetter, vegetation-rich south of Chile. Regional results for Chile are as follows: for surface snow, the average mass mixing ratio of BC was 15 ± 4 ng/g in the north, 28 ± 35 ng/g near Santiago, and 13 ± 3 ng/g in the south. Te regional average vertically-integrated loading of BC was 207 ± 46 µg/m2 in the north, 780 ± 510 µg/m2 near Santiago, and 2500 ± 440 µg/m2 in the south, where the snow season was longer and the snow was deeper. Te estimated black carbon mass mixing ratio in surface snow generally increased with time since the last snowfall for a transect from northern to central Chile from 26.5 to 33.5°S, indicating that dry deposition plays a larger role than wet deposition. Sampling on two consecutive days near Santiago indicated a dry deposition rate of 5.2 mg/m2-month, which is roughly comparable to the inter-monsoon dry deposition rate in the Himalayas. Mean albedo reductions due to light-absorbing impurities in snow in the Chilean Andes are estimated to be 0.0150, 0.0160, and 0.0077 for northern Chile (in June), the region near Santiago (in June), and southern Chile (in July), respectively, for snow grain radii of 100 µm (representative of new snow). Corresponding mean radiative forcings are 2.8, 1.4, and 0.6 W/m2, respectively. In the north, BC plays a smaller role than non-BC; for example, the albedo reduction for 100 µm snow grains due to BC alone is only about 43% of that for all light-absorbing impurities. By comparison, these albedo reductions are 53% and 82% near Santiago and in southern Chile, where a greater share of light absorption is due to BC. Data Availability Te datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. Correspondence and requests for data should be addressed to P.M.R. References 1. Barnett, T. P., Adam, J. C. & Lettenmaier, D. P. Potential impacts of a warming climate on water availability in snow-dominated regions. Nat. Rev. 438, 303–309 (2005). 2. Masiokas, M. H., Villalba, R. & Luckman, B. H. Snowpack variations in the central Andes of Argentina and Chile, 1951–2005: Large- scale atmospheric infuences and implications for water resources in the region. J. Climate. 19, 6334–6352 (2006). 3. Muñoz, E. et al. Unraveling complex hydrogeological processes in Andean basins in south-central Chile: An integrated assessment to understand hydrological dissimilarity. Hydrol. Process. 30(26), 4934–4943 (2016).

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Clouds and the Earth’s Radiant Energy System (CERES): an Earth Observing System Experiment. B. Am. Meteorol. Soc. 77(5), 853–68 (1996). 35. Wiscombe, W. J. & Warren, S. G. A model for the spectral albedo of snow, I: Pure snow. J. Atmos. Sci. 37, 2712–2733 (1980). 36. Warren, S. G. Optical properties of snow. Rev. Geophys. Space Phys. 20, 67–89 (1982). 37. Ginot, P. et al. Glacier mass balance reconstruction by sublimation induced enrichment of chemical species on Cerro Tapado (Chilean Andes). Clim. Past. 2, 21–30 (2016). 38. Ménégoz, M. et al. Snow cover sensitivity to black carbon deposition in the Himalayas: from atmospheric and ice core measurements to regional climate simulations. Atmos. Chem, Phys. 14(8), 4237–4249, https://doi.org/10.5194/acp-14-4237-2014 (2014). Acknowledgements S.N. was supported by NSF grant CHE-1306366, by a Lantz Senior Sabbatical Fellowship from the University of Puget Sound, and by the Fulbright Scholar program. E.S. acknowledges support from the University of Puget Sound. Te support of the Consejo Nacional de Ciencias y Tecnología (CONICYT, Preis ANILLO ACT1410, 1161460, and 1151034), and the Universidad de Santiago de Chile (USACH, Preis USA1555) is gratefully acknowledged. We are grateful to Edgardo Sepúlveda, Francisca Quiroz, Juan Rayas, Camilo Guzman, Christian Brahm, Catalina Pino, Pedro Marconi, Nicole Torres, José Jorquera, Marta Caballero, and Andrea Sepúlveda, who participated in snow sampling or fltering, and to Dr. Delia Rodríguez for help with fltering and for the generous use of her lab. Maps of the cold fronts were generously provided by the weather service of Chile (Direccion Meteorologica de Chile).

Scientific Reports | (2019)9:4008 | https://doi.org/10.1038/s41598-019-39312-0 15 www.nature.com/scientificreports/ www.nature.com/scientificreports

Author Contributions S.N. and R.R.C. conceived of the experiment. P.R., S.N., R.R.C., S.G.W., A.P. planned the feld experiment in northern and central Chile in 2015. P.R., S.N., R.R.C., G.C., J.C., J.P., S.M., F.L., R.R., N.H. and F.F. participated in planning and coordinating the feld experiment in central and southern Chile in 2016. P.R., R.R.C., S.G.W., E.S., A.P, G.C., M.S., F.F., S.M., F.L. and S.N. participated in snow sampling campaigns. P.R., R.R.C., S.G.W., E.S., A.P., M.S., J.P., N.H., S.M. and S.N. participated in snow fltering. A.D. analyzed satellite images to help identify feld sites. S.J.D. analyzed flters to determine estimates of light-absorbing impurities. M.S., R.R. and J.C. provided weather information. P.R. wrote the manuscript with input from all authors. Additional Information Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-019-39312-0. Competing Interests: Te authors declare no competing interests. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional afliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Cre- ative Commons license, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Scientific Reports | (2019)9:4008 | https://doi.org/10.1038/s41598-019-39312-0 16 Black carbon and other light-absorbing impurities in snow in the Chilean Andes

Penny M Rowe1,2, Raul R. Cordero1, Stephen G. Warren3, Emily Stewart4, Sarah J. Doherty5, Alec Pankow4, Michael Schrempf6, Gino Casassa7,8, Jorge Carrasco7, Jaime Pizarro1, Shelley MacDonell9, Alessandro Damiani1,10, Fabrice Lambert11,13, Roberto Rondanelli12,13, Nicolas Huneeus12,13, Francisco Fernandoy14 and Steven Neshyba4

Supplemental Information

S1 Site descriptions Sampling sites are shown on a topographic map of Chile in Figure S1. Site numbers for the Santiago region are given in an expanded view in Figure S2.

Sites in Northern Chile. These sites refer to Figure 1a and Figure S1. Site 1: Taapacá, in the Nevados de Putre, northeast of Arica (blue marker). The snow level was above 5300 m on 2 July 2015. However, a light snowfall occurred on the evening of 3 July; the next day we sampled the thin layer of new snow on the mountain of Taapacá at 4700 m (Site 1a). This snow was therefore known to be fresh snowfall. Because the snow was too thin for us to collect surface snow without contamination by the underlying soil, we collected it instead from the surfaces of a hard plant called Llaretta, shown in Figure S3a. The following day we climbed to the nearby permanent snowfield at 5370 m (Site 1b), shown in Figure S3b. We sampled a thin upper layer of soft new snow from the recent snowfall, as well as the layer below, which was hard-packed ice-like snow, probably from melting and refreezing.

Site 2: Cerro Toco and the ALMA astronomical observatory, above San Pedro de Atacama (green marker). Site 2a. At Cerro Toco, snow was sampled on a permanent snowfield on the side of a mountain, down to a depth of 80 cm. The first 10 cm was new snow that had fallen 2 days earlier, according to the observatory team stationed at Cerro Toco. Below 10 cm the snow was crusty. Site 2b: Snow was sampled on a flat plain near the ALMA observatory; total depth was 15 cm.

Site 3: La Ola, northeast of Copiapó (yellow marker). Snow was sampled just following a snowstorm with strong wind. Sites 3a and 3b were 660 m from the road, where the snow was 13 cm deep. Site 3c was 1.6 km from the road.

Site 4: Valle del Elqui, east of La Serena (orange markers). Snow was four days old (from the same snowfall event we had experienced at La Ola), 22 cm deep, and melting. Site 4b: snow crystals were larger than at site 4a, and the snow was harder.

Site 5: Las Ramadas, in the Limarí province (red marker). The snow was thin (8 cm) and melting. According to local weather reports, the snow apparently fell in the same snowfall event as at Sites 3-4, six days prior.

Site 6: Valle Choapa, east of Salamanca (purple maker). This snow was apparently from the same snowfall event we had experienced at La Ola, and would therefore be 7 days

1 old. Site 6a was on a dry lake bed; the snow was melting, and human footprints were visible. Site 6b was farther from the road on a sloping pasture, but no animal footprints were visible; the snow was wet.

Sites near Santiago. These sites refer to Figure 2 and Figure S2. Site 7: Portillo, northeast of Santiago (blue marker) at 2800 m. This site was on a spit of land protruding into an unfrozen lake by a major ski resort. Snow was 8 days old according to personnel at the resort. The ski season had just begun; the area had been devoid of snow until this recent snowfall, apparently the same one we had experienced at La Ola.

Site 8: Juncal, near the Trans-Andean Highway just below Portillo (black markers). Expecting to find soot-pollution from the exhaust of diesel trucks in the nearby snow, we carried out a transect up the Juncal valley, collecting samples at distances 0.6, 1.1, 1.9, and 3.6 km from the highway.

Site 9: Yerba Loca, east and slightly north of Santiago (red markers). Site 9a was located on the eastern slope of a valley, ~300 m before Los Hornitos, at 2413 m, and was visited on 18 June 2016. Site 9b was located at 1822 m, ~150 m from the hillside road, and was visited five weeks later, on 25 July 2016. Snow was falling shortly before sampling. Site 9c was at the same location as site 9b, one day later (26 July 2016); the intent was to compare the previous fresh snowfall to day-old snowfall. The snow temperature was 0 C both days and the snow compacted from 10 cm to 5 cm.

Site 10: Valle Nevado (brown markers). Snow was sampled off the road to the ski resorts just east of Santiago, to investigate the effect of pollution coming from the large city. For Sites 10a and b sampling took place just below the Valle Nevado ski resort, 210 m from the road, ~300 m below a cliff. Black specks were visible on the snow surface. For Sites 10c and 10d sampling was near Farellones, 144 m from the road, ~100 m away from nearby houses. The snow surface was melting. Sites 10a-d were all visited on 24 July 2015. Site 10e was visited over a year later, in August 2016. At Site 10e, samples were collected at the top of a hill south of the Valle Nevado ski resort. The snow surface was smooth and dense (feet did not sink completely). Snow was homogeneous with depth, with no changes in texture observed.

Site 11. Valle Maipo, east of Santiago (green markers). For sites 11a-c, sampling was done in Valle Maipo and Rio Colorado at ~2300 m. The weather was warm and cloudy, and the snow was melting. Sites 11a and b were near each other; 11c was a short distance down the road (the green markers for 11a-c overlap in Figure 2). At site 11d, snow was sampled the following day off the Termas road at the southeast end of the Maipo valley at 2392m (this site is just off the map in Figure 2, and is indicated by the second green marker in Figure 1b). There was traffic on the nearby dirt road.

Sites in Southern Chile. Sites refer to Figure 1b and Figure S1. Site 12: Curicó (blue marker south of Rancagua). Sampling was done on the ledge of a hill. The snow surface was smooth, fairly homogeneous, and dense.

Site 13: Laguna del Maule (green marker north of Chillan): The sampling area was on the slope of a hill northeast of Lake Maule, ~200 m from the main road. The snow surface was a breakable crust over low-density snow. Within the snow column were three distinct snow textures: 0-35 cm was irregular particles and/or crowned columns, 35-80 cm was larger pellet crystals that could be differentiated with the naked eye, and 80-100 cm was smaller pellet crystals.

Site 14: Las Trancas, near Termas de Chillan (yellow markers). Site 14a, sampled on 13 July 2016, was in a clearing on a slope, surrounded by trees. Site 14b was sampled 6 weeks later, on 22 August 2016, in a valley next to a slope of the volcano southeast of the Nevados de Chillan. A river was ~20 m from the site, and trees ~10 m away. The snow surface was rough, with concave grooves, but no apparent color. The surface was brittle (poor load-bearing capacity). Below 15 cm the grains became larger and more translucent.

Site 15: Antuco (orange marker). The samples were taken in a valley northeast of the Antuco Volcano, between the volcano and the Velluda mountain range. The surface was rough, with convex grooves, and brittle.

Site 16: Volcan Collaqui (red marker). The sampling area was located in a valley by the road that ascends the Collaqui volcano.

Site 17: Corralco (purple marker). Samples were collected on a low slope (~10) northwest of the Corralco Ski Center, ~3.6 km from Lonquimay Volcano. Snow depth was 80 cm, with varying texture, hardness and impurities. In the first 10 cm, the snow appeared clean, but not fresh, since it compacted only ~3 cm when walking on it. Between 10 and 40 cm, the snow was harder, with coarser grains and isolated visible impurities. Between 40 and 45 cm was a layer of dark snow, with a high concentration of impurities; snow grain size was similar to the layer above. Between 50 and 60 cm a second layer of accumulated impurities was visually evident, separated by ~10 cm from the previous one. At the bottom of the snow column, the grain size was larger.

Site 18: Lonquimay (black marker). The site was at the top of a small hill, ~1000 m southwest of the Arenales Ski Center, which was inactive during sampling, and ~150 m from the R-89 road. The surface snow was smooth and brittle. The first 10 cm was snow that had fallen the previous night. Between 15 and 45 cm were pellets of smaller size and from 45 to 60 cm were larger pellets.

Site 19: Volcan Llaima (green marker). The snow, collected on a slight slope, was stratified, with a very thin surface layer (~1 cm) of compacted, coarse-grained snow. Immediately below was ~4 cm of soft, fine-grained snow, probably fairly fresh. The snow below was harder and coarse-grained.

Site 20 Villarica (yellow marker): Site 20a was at a resort on Volcan Villarica outside the Pucon area, close to a ski lift at ~1357 m. The snow was old, icy, 65 cm deep. Eight samples were collected down to 35 cm. Site 20b was located near a canyon oriented approximately North-South, a few meters above the vegetation line at the southern 3 hillside of the volcano. The sample site was away from the ski track, immediately south of the ski lifts, where the slope was slight and the snow was compacted.

Site 21: Antillanca ski resort in Parque Nacional Puyehue (orange marker). Site 21a: ~1093 m. Samples were collected on the side of a ski slope facing south up the mountain. There were animal tracks and footprints nearby. The snow was 26 cm deep, but samples were collected only down to 10 cm. Site 21b: Samples were collected from the west sector of the Antillanca mountain range, ~400 m from the road near the Rayhuen crater. To the west Puyehue Lake was visible, and to the south the Puntiagudo Volcano was visible. The snow was very dense in the first 10 cm, almost ice, making the extraction process difficult. Below this layer the snow was less compacted; from 10 to 15 cm, the snow was soft and fresh, from the recent precipitation event (1 or 2 days ago).

Site 22: Volcan Osorno in Parque Nacional Puyehue (red marker). The site was on the west side of the volcano, ~500 m northeast of the ski center, on a 20-30 slope, within sight of Llanquihue Lake and Calbuco Volcano to the west. Total depth was typically about 40 cm, but the snow was deeper at the sampling point (~70 cm). Stratification was apparent, with a 10-cm-thick surface layer of thin, fine-grained snow. Impurities were visible in the bottom 5 cm of this layer. Below this, the snow was thicker and compacted, probably from to an older deposition event.

S2 Measurements of light-absorbing impurities in snow est max Tables S1-S3 give the median values for measurements of for Åtot, CBC , CBC , and equiv CBC at each location for each layer of snow. Medians were calculated for multiple samples made within the same layer (typically two measurements were made within each layer) at a given site.

S3 Visual estimates of BC equivalent loading In our field laboratories, as soon as the filters are dry they are compared visually to a set of calibration standards containing known loadings of Fullerene, so as to help in planning for our subsequent days’ sampling, as was done on previous expeditions (see e.g. ref 27). In this work, comparison is done in two ways: (1) with filters held against a white background (the light reflection method), and (2) by viewing artificial light through the filter, by placing measured and standard filters on a light table (the light transmission method). While the light reflection method was used in prior work, the transmission method is new to this work. Figure S4a shows the error in our visual estimates, by reference to the measured BC equivalent determined using the ISSW. The reflection method typically underestimates the BC-equivalent loading by about 50% (blue points in S2b). This is in agreement with some previous work,29 while other work found a smaller bias.26 (Note that we plot the equivalent BC loading in g/cm2 rather than converting to ng/g as in previous work, and we restrict our values to <11 g/cm2, above which the filters are so dark that loadings cannot be distinguished visually). Figure S4 shows that visual estimates using transmitted light have a smaller bias than using reflected light.

S4. Meteorology of Northern Chile From 1 to 6 July 2015 no distinctive pressure systems were present in northern and central Chile, with sea-level pressure varying between 1010 and 1020 hPa. (Note, however, that a light snowfall was observed by the sampling group at Site 1, Putre, on 4 July). On 5 and 6 July a cold front from the Pacific crossed central Chile, which brought rainfall to the region west and south of Santiago (e.g. 18.4 mm for Santo Domingo, 2.4 mm for Santiago, based on meteorological station data; http://explorador.cr2.cl) and this may have resulted in some snowfall in the mountainous region east of Santiago so that the 0C isotherm was around 2500 m asl at 12 UTC on 5 July (local mountain weather stations registered 1.0 - 5.5 mm).

Following this, more rain and snow fell in central Chile due to a more distinctive front that was part of a low-pressure system, which moved from southwest of the Pacific coast towards the northeast and passed Santiago around noon on 12 July. Passage of the front is shown in Figures S5-S6. In the Santiago area and the regions south and west of it, most of the rain fell between 11 and 12 July. On 13 July the front brought rainfall to the region north of Santiago (e.g. Elqui). The front passed through Site 3, La Ola, on 13 July, bringing blizzard conditions with snow and wind the day before sampling was performed, as well as bringing snowfall to the mountainous regions in the east to the north of Santiago. On 16 July a second less intense front brought some snowfall in the mountains east of Site 4, Elqui. There were no further distinctive pressure systems and no additional rain or snowfall for the remainder of the 2015 field season.

Table S1. Median values for each layer of snow at each location in northern Chile. Sample Latitude Elevation Cest Cmax Cequiv Site Dates Location Depth Å BC BC BC (oS) (m) tot (ng/g) (ng/g) (cm) (ng/g) 1a 2015/07/04 Putre 18.1 4707 0-1 2.8 25 34 50 1b 2015/07/05 Putre 18.1 5318 0-5 2.3 74 93 121 5-15 2.3 48 59 72 2a 2015/07/10 San Pedro 23.0 5370 0-5 4.3 19 64 123 5-10 4.7 13 83 168 10-15 5.3 6 225 313 15-20 4.4 48 183 404 20-30 3.5 32 55 95 30-40 2.7 17 23 31 40-50 2.6 22 29 39 50-60 2.8 20 26 37 2b 2015/07/10 San Pedro 23.0 5062 0-5 4.8 12 98 210 3a 2015/07/14 La Ola 26.5 3578 0-13 - 5 - - 3b 2015/07/14 La Ola 26.5 3578 0-7 4.1 5 12 20 3c 2015/07/14 La Ola 26.5 3624 0-5 4.1 5 12 25 5-10 5.7 - 40 - 10-15 5.6 - 44 - 15-20 5.2 - 40 - 20-25 5.0 - 40 - 4a 2015/07/17 Elqui 29.9 2341 0-5 4.6 1 5 12 5-10 3.3 1 2 4 10-15 3.1 1 2 2 15-20 3.2 2 3 5 4b 2015/07/17 Elqui 30.0 2190 0-5 3.5 2 4 7 5-10 4.0 1 3 5 5 2015/07/19 Las Ramadas 31.0 1757 0-4 3.5 5 8 15 6a 2015/07/20 Choapa 32.1 1919 0-3 3.1 10 16 26 6b 2015/07/20 Choapa 32.1 1902 0-5 2.5 7 10 13 4-9 2.9 1 2 3

Table S2. Median values for each layer of snow at each location in the Santiago area. Sample Latitude Elevation Cest Cmax Cequiv Site Dates Location Depth Å BC BC BC (oS) (m) tot (ng/g) (ng/g) (cm) (ng/g) 7 2015/07/21 Portillo 32.8 2800 0-5 2.6 6 8 11 5-10 3.1 3 5 7 10-15 3.2 5 8 13 15-20 3.3 3 5 8 20-30 3.3 6 9 15 30-40 3.1 18 27 43 40-50 2.5 6 8 11 8a 2015/07/22 Juncal 32.9 2249 0-5 2.1 18 21 25 8b 2015/07/22 Juncal 32.9 2285 0-5 2.1 14 16 19 5-10 3.0 5 7 11 8c 2015/07/22 Juncal 32.9 2277 0-5 2.6 15 20 27 5-10 3.2 10 14 21 8d 2015/07/22 Juncal 32.9 2322 0-5 2.7 15 21 29 5-10 4.3 3 11 24 10-15 3.8 4 8 16 9a 2016/06/18 Yerba Loca 33.3 2413 0-8 2.0 15 17 21 9-16 1.1 4 4 3 17-24 1.2 7 7 8 24-32 1.0 6 6 6 9b 2016/07/25 Yerba Loca 33.3 1822 0-5 1.0 1 1 1 5-7 1.1 2 2 2 9c 2016/07/26 Yerba Loca 33.3 1822 0-5 2.0 9 10 13 10a 2015/07/24 Valle Nevado 33.4 2435 5-10 2.5 5 7 9 10b 2015/07/24 Valle Nevado 33.4 2636 0-5 3.1 91 153 227 5-10 2.4 8 11 14 10-20 2.4 3 4 6 20-30 2.8 6 8 12 10c 2015/07/24 Valle Nevado 33.4 2366 0-10 3.4 66 130 204 10-20 2.5 12 16 20 20-30 2.5 4 5 7 10d 2015/07/24 Valle Nevado 33.4 2802 0-5 3.7 112 257 467 5-10 3.3 27 47 77 10e 2015/07/24 Valle Nevado 33.4 2554 0-10 3.3 46 93 144 10-20 2.4 3 3 4 20-30 2.4 4 5 6 10f 2016/08/18 Valle Nevado 33.4 2635 5-15 2.3 28 32 43 15-25 2.6 31 38 56 25-35 1.8 7 8 9 11a 2015/07/26 Maipo 33.5 2302 0-5 3.8 31 81 140 5-10 2.9 4 5 8 10-15 3.4 3 7 14 15-20 3.0 9 13 20 11b 2015/07/26 Maipo 33.5 2308 5-10 2.8 9 12 18 10-15 2.9 8 11 16 11c 2015/07/26 Maipo 33.5 2236 0-5 3.5 29 62 103 5-10 2.9 7 10 15 11d 2015/07/27 Maipo 33.8 2392 0-5 3.1 21 32 50 5-10 2.6 7 9 13 10-15 2.8 6 8 12 15-20 2.7 4 5 7 20-30 2.8 5 7 10 30-40 2.6 4 5 6 40-50 2.6 2 2 3

Table S3. Median values for each layer of snow at each location in southern Chile. Sample Latitude Elevation Cest Cmax Cequiv Site Dates Location Depth Å BC BC BC (oS) (m) tot (ng/g) (ng/g) (cm) (ng/g) 12 2016/08/19 Curicó 35.1 1860 0-10 2.8 27 31 50 10-20 1.8 13 13 16 20-30 1.8 18 18 22 30-40 1.9 19 20 25 40-50 2.0 10 11 14 50-60 2.4 7 7 10 13 2016/08/20 Maule 36.0 1860 0-10 2.1 17 19 26 10-20 1.8 12 12 15 20-30 2.7 24 33 54 30-40 1.7 14 15 18 40-50 1.6 10 11 12 50-60 1.4 7 7 7 60-70 1.4 8 8 8 70-80 1.7 7 7 8 80-90 1.7 8 8 9 14a 2016/08/22 Chillán 37.0 1963 0-10 1.7 15 16 20 10-20 2.1 8 9 13 30-40 2.3 10 14 20 14b 2016/07/13 Chillán 37.0 1554 0-5 1.5 13 6 6 5-10 1.4 5 6 6 10-15 1.3 6 8 8 15-20 1.4 7 7 7 15 2016/08/23 Antuco 37.4 1494 0-5 1.8 12 13 15 5-10 2.1 15 16 22 10-15 2.0 15 16 21 15-20 1.6 7 7 8 16 2016/08/24 Collaqui 37.9 1142 0-5 1.6 5 6 6 5-10 1.8 8 9 11 17 2016/08/27 Corralco 38.4 1601 0-10 1.5 5 5 5 10-20 2.0 7 8 10 20-30 1.8 10 10 12 30-40 2.1 7 8 10 40-50 3.2 20 27 50 50-60 2.8 17 21 36 60-70 2.1 9 9 12 70-80 2.4 8 8 12 18 2016/08/26 Lonquimay 38.4 1652 0-5 1.5 6 6 6 5-10 2.3 12 14 19 10-20 2.1 12 13 17 20-30 2.2 10 11 15 30-40 2.3 11 12 17 40-50 1.9 7 7 9 19 2016/08/28 Llaima 38.5 1830 0-5 2.1 7 9 12 5-10 2.4 11 14 20 10-10 1.4 12 12 13 20-30 1.3 7 7 7 30-40 1.3 7 7 7

Table S3 (continued). Median values for each layer of snow at each location in southern Chile. Sample Latitude Elevation Cest Cmax Cequiv Site Dates Location Depth Å BC BC BC (oS) (m) tot (ng/g) (ng/g) (cm) (ng/g) 20a 2016/07/21 Villarrica 39.4 1357 0-5 1.7 10 10 12 5-15 1.6 7 7 8 15-25 1.3 5 5 6 25-35 1.5 7 7 8 20b 2016/08/29 Villarrica 39.4 1450 0-5 2.0 11 13 17 5-10 1.7 17 18 22 10-20 1.2 12 12 12 20-30 1.3 8 8 8 30-40 1.5 16 16 18 40-50 1.5 8 8 9 50-60 1.3 10 10 11 60-70 1.3 15 15 16 70-80 1.4 16 16 18 80-90 1.3 13 13 13 21a 2016/07/19 Antillanca 40.8 1093 0-5 1.5 11 12 12 5-10 1.2 10 10 10 21b 2016/09/01 Antillanca 40.8 1349 0-5 1.1 7 7 7 5-10 1.3 6 6 6 10-20 1.4 11 11 12 20-30 1.2 7 7 7 30-40 1.2 7 7 7 40-50 1.2 8 8 8 50-60 1.4 9 9 10 22 2016/08/31 Osorno 41.1 1326 0-5 1.2 5 5 5 5-10 1.1 5 5 4 10-20 1.9 14 14 18 20-30 1.5 5 5 5 30-40 1.3 4 4 4 40-50 1.3 6 6 6

Supplemental Figures

Figure S1. Sample sites.

a) b)

3000 32.8 Portillo Valle Nevado

Juncal 2500 33.0

e 2000

D 33.2 t

a e 1500

d Yerba Loca

L 33.4 Valle Nevado 1000 Santiago Maipo Santiago 500 33.6

0 71.0 70.8 70.6 70.4 70.2 70.0 72.0 71.5 71.0 70.5 Longitude Degrees Longitude Degrees Figure S2. a) Sample sites in the region near Santiago. b) Elevation along latitude 33°27’S.

a. Putre, site 1a.

b. Putre, site 1b.

Figure S3. Snow sampling sites at Putre for (a) Site 1a, and (b) Site 1b.

Figure S4. (a) Visual estimates compared to measured BC equivalent. (b) Bias in visual estimate.

a) 12 July 06 UTC

b) 12 July 12 UTC

Figure S5. Maps of the cold front on 12 July 2015 from the weather service of Chile (Dirección Meteorológica de Chile). The blue “A” stands for Alta (high), indicating a high-pressure system, while the red “B” stands for Baja (low), indicating a low- pressure system.

a) 12 July 18 UTC

b) 13 July 06 UTC

Figure S6. Maps of the cold front on 12 July 2015 from the weather service of Chile (Dirección Meteorológica de Chile).