Microorganisms are present in snow/ice of the Antarctic Plateau, but their biogeography and metabolic state under extreme local conditions are poorly understood. Here, we show the diversity and distribution of microorganisms in air (1.5 m height) and snow/ice down to 4 m depth at three distant latitudes along a 2578 km transect on the East Antarctic Plateau on board an environmentally friendly, mobile platform. Results demonstrate the widespread distribution of microorganisms in the ice down to at least 4 m depth. Data point to geochemical and bacterial geographic distribution that correlate with wind trajectory and speed, modulated by local gathering and recirculation of microorganisms through snow drifting. Reservoir effects and community selection appear to occur over time, favoring microorganisms best adapted to hypothermal and hyperarid conditions. A new cyanobacterial species (Gloeocapsopsis sp) was isolated from 3 to 4 m depth. Our findings suggest that some microorganisms could exhibit transient, basal metabolic activity when associated to high salt particles, contributing to set biodiversity patterns and biogeographic compartmentalization on Antarctic Plateau ice. WindSled, a zero-emission mobile science platform, is capable of traveling thousands of kilometers and doing valuable science on the Antarctic Plateau. Wind-driven aerosols condition the biogeographic distribution of bioburden from air to 4 m depth.

We present a unique atmospheric chemistry record from the highest ice core ever recovered (8020 m, South Col Glacier (SCG), Mt. Everest), that captures ~400 years of deposition during the latter half of the first millennium BCE. Due to recent glacier thinning, the upper ~2000 years of accumulation have been lost, however, this is the only ice core record ever recovered from the “Death Zone (>8000 m)” and likely the only record that can be attained. Insights from this 10m deep record and comparison with an ice core we recovered on the north side of Mt. Everet include: an estimated lapse rate of water isotopes at extreme elevations; the influence of southerly and northerly source air masses on precipitation, dusts and overall atmospheric chemistry over Mt. Everest; and possibly the earliest influences of human activity on the chemistry of the atmosphere in this region.

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Refractory black carbon (rBC) has great potential to increase melting when deposited on snow and ice surfaces. Previous studies attributed sources and impacts of rBC in the northern Antarctic Peninsula region by investigating long-range atmospheric transport from South Hemisphere biomass burning and industrial regions or by assessing impacts from local tourism and research activities. We used high-resolution measurements of refractory rBC in a firn core collected near the northern tip of the Antarctic Peninsula, as well as atmospheric rBC from Modern-Era Retrospective Analysis for Research and Applications, Version 2, satellite measurements, modeling, burned area data, and tourism statistics, to assess combined impacts of both long-range transported rBC and locally emitted rBC. Our findings suggest that tourism activities have a regional rather than local impact and the increase in rBC concentrations during late spring-summer, influenced by tourism activities and fires in the Southern Hemisphere, can enhance ice melt. This highlights the need for strategies to reduce local and distant rBC emissions.

<p>We report interlaboratory comparisons of a methodology to measure and calculate concentrations of impurities in ice core samples using the Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) system developed at the W. M. Keck Laser Ice Facility at the Climate Change Institute, University of Maine (UMaine). Here, we will summarize results of measured artificial samples with known levels of  Ca, Al, Fe, Mg, Na, Cu, Pb. We adapted a method for LA-ICP-MS analysis of the frozen standard that was developed in the laboratory at Ca’ Foscari University of Venice, and we tested its applicability to the UMaine system. This work will help to measure and interpret very old and highly compressed ice core records from the Allan Hills Blue Ice Area, Antarctica, sampled with different analytical tools.  </p>

WeatherEarly View Short ArticleOpen Access Insights from the first winter weather observations near Mount Everest's summit Tenzing Chogyal Sherpa, Corresponding Author Tenzing Chogyal Sherpa [email protected] orcid.org/0000-0003-4512-2194 International Centre for Integrated Mountain Development, Kathmandu, Nepal Correspondence to: T. C. Sherpa [email protected]Search for more papers by this authorTom Matthews, Tom Matthews orcid.org/0000-0001-6295-1870 Department of Geography, King's College London, UKSearch for more papers by this authorL. Baker Perry, L. Baker Perry orcid.org/0000-0003-0598-6393 Appalachian State University, Boone, North Carolina, USASearch for more papers by this authorAmrit Thapa, Amrit Thapa International Centre for Integrated Mountain Development, Kathmandu, Nepal Geophysical Institute, University of Alaska Fairbanks, Fairbanks, Alaska, USASearch for more papers by this authorPraveen Kumar Singh, Praveen Kumar Singh Indian Institute of Technology Roorkee, Uttarakhand, IndiaSearch for more papers by this authorArbindra Khadka, Arbindra Khadka orcid.org/0000-0002-8564-1477 International Centre for Integrated Mountain Development, Kathmandu, Nepal University of Grenoble Alpes, CNRS, IRD, IGE, Grenoble, FranceSearch for more papers by this authorInka Koch, Inka Koch Department of Geosciences, University of Tübingen, GermanySearch for more papers by this authorMauri Pelto, Mauri Pelto Department of Environmental Science, Nichols College, Dudley, Massachusetts, USASearch for more papers by this authorPrajjwal Panday, Prajjwal Panday Department of Environmental Science, Nichols College, Dudley, Massachusetts, USASearch for more papers by this authorDeepak Aryal, Deepak Aryal Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur, NepalSearch for more papers by this authorDibas Shrestha, Dibas Shrestha Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur, NepalSearch for more papers by this authorShichang Kang, Shichang Kang State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaSearch for more papers by this authorPaul Andrew Mayewski, Paul Andrew Mayewski Climate Change Institute, University of Maine, Orono, Maine, USASearch for more papers by this author Tenzing Chogyal Sherpa, Corresponding Author Tenzing Chogyal Sherpa [email protected] orcid.org/0000-0003-4512-2194 International Centre for Integrated Mountain Development, Kathmandu, Nepal Correspondence to: T. C. Sherpa [email protected]Search for more papers by this authorTom Matthews, Tom Matthews orcid.org/0000-0001-6295-1870 Department of Geography, King's College London, UKSearch for more papers by this authorL. Baker Perry, L. Baker Perry orcid.org/0000-0003-0598-6393 Appalachian State University, Boone, North Carolina, USASearch for more papers by this authorAmrit Thapa, Amrit Thapa International Centre for Integrated Mountain Development, Kathmandu, Nepal Geophysical Institute, University of Alaska Fairbanks, Fairbanks, Alaska, USASearch for more papers by this authorPraveen Kumar Singh, Praveen Kumar Singh Indian Institute of Technology Roorkee, Uttarakhand, IndiaSearch for more papers by this authorArbindra Khadka, Arbindra Khadka orcid.org/0000-0002-8564-1477 International Centre for Integrated Mountain Development, Kathmandu, Nepal University of Grenoble Alpes, CNRS, IRD, IGE, Grenoble, FranceSearch for more papers by this authorInka Koch, Inka Koch Department of Geosciences, University of Tübingen, GermanySearch for more papers by this authorMauri Pelto, Mauri Pelto Department of Environmental Science, Nichols College, Dudley, Massachusetts, USASearch for more papers by this authorPrajjwal Panday, Prajjwal Panday Department of Environmental Science, Nichols College, Dudley, Massachusetts, USASearch for more papers by this authorDeepak Aryal, Deepak Aryal Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur, NepalSearch for more papers by this authorDibas Shrestha, Dibas Shrestha Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur, NepalSearch for more papers by this authorShichang Kang, Shichang Kang State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaSearch for more papers by this authorPaul Andrew Mayewski, Paul Andrew Mayewski Climate Change Institute, University of Maine, Orono, Maine, USASearch for more papers by this author First published: 20 March 2023 https://doi.org/10.1002/wea.4374 The views and interpretations in this publication are those of the authors and are not necessarily attributable to their organisations. AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Graphical Abstract The highest reaches of our planet experience some of the most extreme weather on Earth and hold very significant supplies of freshwater for communities downstream. However, we know very little of the meteorological detail about this high-altitude frontier. We address this here with new winter weather observations from the upper reaches of Mount Everest (2019–2021). We show that substantial sublimation rates are possible, with losses up to 2.5mm day−1. Wind chill plunging to −83°C and frostbite possible in less than one minute also attest to the severe cold stress facing mountaineers attempting winter ascents of this most iconic peak. Reaching up to 8849m above mean sea level (asl), the upper slopes of Mount Everest provide one of the most climatically extreme environments on the planet. It is also an environment likely to be warming rapidly, due to the tendency for temperature increases to amplify at greater elevations in the troposphere under climate change (Pepin et al., 2015). However, our understanding of high-altitude climates has been severely limited by an understandable lack of basic in situ observations (Matthews, 2020a). The logistical demands associated with climbing to such heights challenges the initial installation of automatic weather stations (AWSs). Those AWSs which do get deployed must then withstand extreme cold and severe winds if they are to remain operational. Mountain regions that are hardest to reach, at those times of year when the weather is most extreme, have therefore been monitored least, meaning winter conditions on the planet's highest peaks remain largely a mystery. Through necessity, insights have mostly been taken from relatively coarse reanalysis data (Moore and Semple, 2011; Matthews et al., 2021). Not only does this monitoring gap represent a technical blind spot in the understanding of our planet's climate envelope, but the practical impacts for society may also be substantial. For example, the mountains of the Hindu Kush Himalayan region store the largest mass of ice outside the poles (Bolch et al., 2012), and the ongoing retreat is a major concern for regional freshwater security (Immerzeel et al., 2020; Nie et al., 2021). The potential future losses inferred by modelling studies is, therefore, of much relevance for resource management and hazard planning (Huss and Hock, 2018). However, such outlooks are underpinned by an understanding of glacier–climate interactions that is biased towards more accessible regions and seasons in the same way the observations are. Temperature index models, for example, are widely used for glacier mass balance projections (Hock et al., 2019), but they appear unsuited to capture the important role of sublimation, which is amplified at higher altitudes (Stigter et al., 2018; Litt et al., 2019) and in the winter season (Wagnon et al., 2013). In this short article, we address the issues raised above by assessing the first observations from winter recorded by the one of the world's highest weather station networks on Mount Everest. We include the most-constrained estimate yet of air temperatures and cold stress on the summit, and we consider mechanisms of mass loss from the highest glacier on Earth. Data and methods We use meteorological data from the weather station network installed by the 2019 National Geographic and Rolex Everest Expedition, which is described by Matthews et al. (2020a,b) and summarised in Table 1. We summarise the weather across the full (>4500m) elevational range using simple descriptive statistics. For the summit – which sits ~400m above the Balcony AWS – we estimate air temperatures and cold stress using the temperature lapse rate and the assumption that wind speeds are the same as at the South Col AWS (which is situated in a less sheltered location than the Balcony). The temperature lapse rates were calculated as a linear regression of hourly temperature at the AWSs against elevation (cf. Immerzeel et al., 2014; Heynen et al., 2016), after first smoothing all temperatures with a running 24-hour mean to reduce the impact of solar heating which may affect measurements during brief spells of light winds (Matthews et al., 2020a,b). Table 1. Specifications of all the automatic weather stations installed across the slopes of Mount Everest. Phortse Base Camp Camp II South Col Balcony Latitude (°N) 27.8456 27.9952 27.9810 27.9719 27.9826 Longitude (°E) 86.7472 86.8406 86.9023 86.9295 86.9292 Elevation (m asl) 3810 5315 6464 7945 8430 Operation 24 April 2019 to present 10 October 2019 to present 9 June 2019 to present 22 May 2019–18 July 2021 23 May 2019– 1 January 2020 Abbreviation: m asl, metres above mean sea level. Wind chill temperature (WCT) and facial frostbite time (FFT) were then computed with the estimated summit air temperature and wind speed following Moore and Semple (2011): WCT = 13.12 + 0.621 T − 11.37 V 0.16 + 0.3965 T V 0.16 (1) FFT = − 24.5 0.667 V + 4.8 + 2111 − 4.8 − T − 1.688 (2)in which T is the air temperature (°C) and V is the wind speed (kmh−1). Strictly, the latter refers to a reference height of 10m above the surface, whereas the Everest weather stations' wind sensors are at approximately two metres above ground, a height at which wind speeds are likely slower due to friction with the land surface. Hence, this should lead to a high (warm) bias in WCT. However, the equation is also strictly valid for an air density between two and three times higher than at the summit of Everest, translating to a low (cold) bias in our application. Following Moore and Semple (2011), we assume that these biases approximately cancel. To explore point surface mass balance during the winter of the world's highest glacier (South Col Glacier, hereafter the SCG), we use data from the South Col AWS (7945m asl). This station was the highest of the network installed in 2019 that was equipped with all the sensors required to resolve the surface energy balance (SEB) and is separated from the SCG by a horizontal distance of only a few hundred metres. We use COSIPY (the COupled Snowpack and Ice surface energy and mass balance model in PYthon: Sauter & Schneider, 2015) to infer the SEB for the SCG, with mass input via snowfall estimated from the precipitation recorded at Phortse (3810m asl). We set all COSIPY model parameters (e.g. roughness lengths) as in Potocki et al. (2022). We fill brief periods of missing data at the South Col with ERA5 reanalysis data (Hersbach et al., 2020) downscaled to the AWS using machine learning (see Potocki et al., 2022 for details). The initial snow depth (0.94m) for the COSIPY simulation model was taken from the 1km2 Sentinel-1 snow depth product for 13 May 2019 (Lievens et al., 2019), which is 10 days prior to the installation of the AWS (and the beginning of the COSIPY model run). Given the highly variable topography, the accuracy of this Sentinel product for the SCG is questionable; however, it is the highest resolution snow depth product, and preliminary analysis (not shown) indicated low sensitivity to initial snow depth in the COSIPY simulations. Results Winter stands distinct from the other seasons, with air temperatures and insolation plunging to their lowest values and wind speeds reaching their peak (Figure 1). The highest (3s) gust recorded by the network (66ms−1; not shown) was indeed recorded at the South Col during January 2020 – immediately before the wind sensors went offline. The change to colder, conditions at the onset of winter generally magnifies with elevation, as the lapse rate steepens in this season meaning air temperatures fall more rapidly with height (Figures 1a and e). Relative humidity is noteworthy in winter because of its very high variability at synoptic timescales (Figure 1a). Although not quite as pronounced, the same high-frequency variance is evident in the air temperatures (Figure 1b). We attribute this wintertime peak in transitions between warmer, moister air masses and cooler, drier circulations, to the arrival of the Subtropical Jet over the Himalaya. The passage of waves in this westerly flow drives the variation in air mass character; and wind speeds peak when the jet axis crosses Everest (Matthews et al., 2020b). Figure 1Open in figure viewerPowerPoint Mean daily values of selected variables from the automatic weather stations (AWSs). (a) Relative humidity; blue line in the panel represents cumulative precipitation at Phortse, (b) daily temperature, (c) average wind speed, (d) incoming solar radiation and (e) lapse rates across all stations. The lapse rates were calculated as the slope coefficient from regressing running 24-h mean air temperature at the AWSs against their elevations. The dashed line in all the plots represents data filled from ERA5 reanalysis data at South Col. For all the panels, the blue shaded region represents the winter season (DJF). The elevation-enhanced drop in air temperature with the arrival of winter, combined with the amplification of winds, compound to generate extreme conditions of profound cold stress for the summit. The mean winter WCT is −61.2°C (Table 2), whilst the lowest daily mean observed during the period of observation was −77°C (on 31 December 2020) (Figure 2). The individual hour with the lowest WCT on the other hand reached −83°C, when the mean wind speed was 36ms−1 and the temperature was −48°C (in 19 January 2020). The FFT tells a similar story, indicating a mean exposure time in winter of less than two minutes before uncovered skin would be at high risk of frostbite (Table 2). Values much less than one minute in Figure 2 underscore the dangers of exposing skin for even the briefest of periods on Mount Everest during extreme winter cold events. We note that the monthly mean WCT and FFT shown in Figure 2 are in reasonably good agreement with the National Centers for Environmental Prediction (NCEP) reanalysis-based assessment by Moore and Semple (2011), but we find a less severe cold hazard during the monsoon. Table 2. Seasonal daily mean values estimated at the summit. The standard deviation values are represented by the plus/minus terms. Season T (°C) WS (ms−1) WCT (°C) FFT (min) Monsoon (JJAS) −18.8 ± 2.7 5.2 ± 2.6 −28.1 ± 4.8 9.8 ± 3.6 Post-monsoon (ON) −30.1 ± 4.7 13.9 ± 6.7 −48.4 ± 9.1 2.7 ± 2.1 Spring (MAM) −32.1 ± 5.7 9.6 ± 4.7 −48.5 ± 8.8 3 ± 1.6 Winter (DJF) −37.3 ± 4.4 18 ± 6.5 −61.2 ± 8.5 1.3 ± 0.8 Abbreviations: FFT, facial frostbite time; WCT, wind chill temperature; WS, wind speed JJAS: June, July, August, September; WS: Wind speed; MAM: March, April, May; DJF: December, January, February; ON: October, November Figure 2Open in figure viewerPowerPoint Boxplot of daily mean air temperature, wind chill temperatures (WCTs) and facial frostbite time (FFT) estimated at the summit. The FFT is plotted on the right y-axis. The horizontal line within the box denotes the median, whereas the first and third quartile are represented by the top and bottom of the box, respectively. The whiskers indicate the range (minimum and maximum values), and the points indicate values that are greater than 1.5 times the upper quartile and are often regarded as outliers. The blue shaded region represents winter season. Owing to the high levels of insolation, our COSIPY simulation suggests that the net shortwave radiation flux is the largest energy source for the SCG (Figure 3a). Most of this energy is then dispersed by the net longwave radiation, followed by the turbulent (sensible and latent) heat fluxes, and finally energy for melting. The model results indicate that some meltwater may be generated in the monsoon season, despite the air temperature staying well below 0°C. The majority of the ablation, however, is as sublimation (Figure 3), with cumulative losses of 539mm w.e. in between 23 May 2019 and 30 June 2021: more than nine times the amount of surface melt during the same period (60mm w.e.) (Figure 3b). Temporal variations in sublimation show that although the highest mean rate is in the post-monsoon (October–November), peak rates occur in the winter season, reaching up to 2.5mm w.e. day−1. To put such losses into context, integrating the total sublimation from the colder, windier, and drier months of the post-monsoon and winter (Figure 3d) through the ~150 days of that period indicates that 0.28m w.e. could be ablated during that time. If that figure is also representative of conditions at the summit, and if snow density there is in the region of 300–500kgm−3, then the peak could be expected to 'shrink' by up to 0.5–0.9m during this period (assuming no input of snow via precipitation or wind re-distribution). Given this potential for mass loss, and the considerable efforts expended in measuring the height of Mount Everest (Adhikari and Slater, 2020), we suggest that examining inter-annual variability in the mass balance of the summit could be an interesting direction for future research. Figure 3Open in figure viewerPowerPoint (a) Mean daily energy fluxes at South Col. (b) Cumulative surface melt and sublimation. The secondary axis represents the snow depth over the simulation period. (c) Temperature and wind speed (secondary axis) at South Col. (d) Bar plot of total sublimation in each season and boxplot of seasonal variation of daily sublimation rates in each season. The bar plot is plotted on the left y-axis, whereas the box plots are plotted against the right y-axis. The horizontal line within the box denotes the median, whereas the first and third quartile are represented by the top and bottom of the box, respectively. The whiskers indicate the range (minimum and maximum values), and the points indicate values that are greater than 1.5 times the upper quartile and are often regarded as outliers. From panels (a)–(c), the blue shaded region represents the winter season (DJF). Conclusions In this short article, we provided the first assessment of wintertime weather measured by in situ stations on Mount Everest. The assessment highlighted the extent of the severe cold hazard on the upper mountain in more detail than has previously been possible, identifying hourly wind chills as low as −83°C and daily means reaching −77°C. This cold hazard amplifies more with the onset of winter than at lower elevations because the lapse rate also steepens in this season. Our investigation also reveals that the combination of strong winds and low relative humidity during the wintertime is enough to drive significant sublimation (2.5mm w.e. day−1) on the upper reaches of Mount Everest. Quantifying mass loss from such previously unexplored seasons and locations is important to understand the impact of climate change on water resources in High Mountain Asia. In the case of Mount Everest, it has additional symbolic value, as it helps illuminate the extent to which the height of Earth's highest mountain is subject to change. Exploring this more could be an interesting avenue for future research. Conflict of interest statement The authors declare no conflicts of interest. References Adhikari A, Slater J. 2020, December 8. Its official: Mount Everest just got a little higher. The Washington Post. https://www.washingtonpost.com/world/asia_pacific/mount-everest-height-nepal-china/2020/12/08/a7b3ad1e-389a-11eb-aad9-8959227280c4_story.html. Bolch T, Kulkarni A, Kääb A et al. 2012. The state and fate of Himalayan glaciers. Science 336(6079): 310– 314. Heynen M, Miles E, Ragettli S et al. 2016. Air temperature variability in a high-elevation Himalayan catchment. Ann. Glaciol. 57(71): 212– 222. Hersbach H, Bell B, Berrisford P et al. 2020. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146(730): 1999– 2049. Hock R, Bliss A, Marzeion BEN et al. 2019. GlacierMIP – a model intercomparison of global-scale glacier mass-balance models and projections. J. Glaciol. 65(251): 453– 467. Huss M, Hock R. 2018. Global-scale hydrological response to future glacier mass loss. Nat. Clim. Chang. 8(2): 135– 140. Immerzeel WW, Lutz AF, Andrade M et al. 2020. Importance and vulnerability of the world's water towers. Nature. 577(7790): 364– 369. Immerzeel WW, Petersen L, Ragettli S et al. 2014. The importance of observed gradients of air temperature and precipitation for modeling runoff from a glacierized watershed in the Nepalese Himalayas. Water Resour. Res. 50(3): 2212– 2226. Lievens H, Demuzere M, Marshall HP et al. 2019. Snow depth variability in the Northern Hemisphere mountains observed from space. Nat. Commun. 10(1): 4329. Litt M, Shea J, Wagnon P et al. 2019. Glacier ablation and temperature indexed melt models in the Nepalese Himalaya. Sci. Rep. 9(1): 5264. Matthews T, Perry LB, Koch I et al. 2020a. Going to extremes: installing the world's highest weather stations on Mount Everest. Bull. Am. Meteorol. Soc. 101(11): E1870– E1890. Matthews T, Perry LB, Koch I et al. 2021. Himalayan high: weather stations on Mount Everest reach new heights. Bull. Am. Meteorol. Soc. 102(5): 422– 428. Matthews T, Perry LB, Lane TP et al. 2020b. Into thick(er) air? Oxygen availability at humans' physiological frontier on Mount Everest. Iscience 23(12): 101718. Moore GWK, Semple JL. 2011. Freezing and frostbite on Mount Everest: new insights into wind chill and freezing times at extreme altitude. High Alt. Med. Biol. 12(3): 271– 275. Nie Y, Pritchard HD, Liu Q et al. 2021. Glacial change and hydrological implications in the Himalaya and Karakoram. Nat. Rev. Earth Environ. 2(2): 91– 106. Pepin N, Bradley RS, Diaz HF et al. 2015. Elevation-dependent warming in mountain regions of the world. Nat. Clim. Chang. 5: 424– 430. Potocki M, Mayewski PA, Matthews T et al. 2022. Mt. Everest's highest glacier is a sentinel for accelerating ice loss. npj Clim. Atmos. Sci. 5(1): 7. Sauter T, Schneider C. 2015. COupled Snowpack and Ice surface energy and MAss balance model. Geosci. Model Dev. 47(3): gmd-8- 3911- 2015. Stigter EE, Litt M, Steiner JF et al. 2018. The importance of snow sublimation on a Himalayan glacier. Front. Earth Sci. 6: 108. Wagnon P, Vincent C, Arnaud Y et al. 2013. Seasonal and annual mass balances of Mera and Pokalde glaciers (Nepal Himalaya) since 2007. Cryosphere 7(6): 1769– 1786. Early ViewOnline Version of Record before inclusion in an issue FiguresReferencesRelatedInformation

Abstract High-resolution ice core records from coastal Antarctica are particularly useful to inform our understanding of environmental changes and their drivers. Here, we present a decadally resolved record of sea-salt sodium (a proxy for open-ocean area) and non-sea salt calcium (a proxy for continental dust) from the well-dated Roosevelt Island Climate Evolution (RICE) core, focusing on the time period between 40–26 ka BP. The RICE dust record exhibits an abrupt shift towards a higher mean dust concentration at 32 ka BP. Investigating existing ice-core records, we find this shift is a prominent feature across Antarctica. We propose that this shift is linked to an equatorward displacement of Southern Hemisphere westerly winds. Subsequent to the wind shift, data suggest a weakening of Southern Ocean upwelling and a decline of atmospheric CO2 to lower glacial values, hence making this shift an important glacial climate event with potentially important insights for future projections.

Abstract Shallow firn cores, in addition to a near-basal ice core, were recovered in 2018 from the Quelccaya ice cap (5470 m a.s.l) in the Cordillera Vilcanota, Peru, and in 2017 from the Nevado Illimani glacier (6350 m a.s.l) in the Cordillera Real, Bolivia. The two sites are ~450 km apart. Despite meltwater percolation resulting from warming, particle-based trace element records (e.g. Fe, Mg, K) in the Quelccaya and Illimani shallow cores retain well-preserved signals. The firn core chronologies, established independently by annual layer counting, show a convincing overlap indicating the two records contain comparable signals and therefore capture similar regional scale climatology. Trace element records at a ~1–4 cm resolution provide past records of anthropogenic emissions, dust sources, volcanic emissions, evaporite salts and marine-sourced air masses. Using novel ultra-high-resolution (120 μm) laser technology, we identify annual layer thicknesses ranging from 0.3 to 0.8 cm in a section of 2000-year-old radiocarbon-dated near-basal ice which compared to the previous annual layer estimates suggests that Quelccaya ice cores drilled to bedrock may be older than previously suggested by depth-age models. With the information collected from this study in combination with past studies, we emphasize the importance of collecting new surface-to-bedrock ice cores from at least the Quelccaya ice cap, in particular, due to its projected disappearance as soon as the 2050s.

Mountain glacier systems are decreasing in volume worldwide yet relatively little is known about their upper reaches (>5000 m). Here we show, based on the world’s highest ice core and highest automatic weather stations, the significant and increasing role that melting and sublimation have on the mass loss of even Mt. Everest’s highest glacier (South Col Glacier, 8020 m). Estimated contemporary thinning rates approaching ~2 m a −1 water equivalent (w.e.) indicate several decades of accumulation may be lost on an annual basis now that glacier ice has been exposed. These results identify extreme sensitivity to glacier surface type for high altitude Himalayan ice masses and forewarn of rapidly emerging impacts as Mt. Everest’s highest glacier appears destined for rapid retreat.

Mt. Everest (Qomolangma or Sagarmatha), the highest mount on Earth and located in the central Himalayas between China and Nepal, is characterized by highly concentrated glaciers and diverse landscapes, and is considered to be one of the most sensitive area to climate change. In this paper, we comprehensively synthesized the climate and environmental changes in the Mt. Everest region, including changes in air temperature, precipitation, glaciers and glacial lakes, atmospheric environment, river and lake water quality, and vegetation phenology. Historical temperature reconstruction from ice cores and tree rings revealed the distinct features of 20th century warming in the Mt. Everest region. Meteorological observations further proved that the Mt. Everest region has been experiencing significant warming (approximately 0.33 °C/decade) but relatively stable precipitation during 1961−2018 AD. Projected results (during 2006−2099 AD) under different representative concentration pathway scenarios showed a general warming trend in the region, with larger warming occurring in winter than in summer. Meanwhile, the precipitation projections varied spatially with no significant trends over the region. Intensive glacier shrinkage was characterized by decreasing glacier areas, while glacier-fed river runoff increased. Glacial lakes expanded with increasing glacial lake areas and numbers. These findings indicated a clear regional hydrological response to climate warming. Owing to the remote location of Mt. Everest, the present atmospheric environment remained relatively clean; however, long-range transport of atmospheric pollutants from South Asia and West Asia may have substantially influenced the Mt. Everest region, resulting in increasing concentrations of pollutants since the Industrial Revolution. Anthropogenic activities have been shown to influence river and lake water quality in this remote region, especially in the downstream. The end of the vegetation growing season advanced in the northern slope and did not change in southern slope region of the Mt. Everest, and there was no significant change in start date of the growing season in the region. This review will enhance our understanding of climate and environmental changes in the Mt. Everest region under global warming.

Trace elements are emitted to the atmosphere from natural and anthropogenic sources. The increase in industrialization and mining occurring from the late 19th century released large quantities of toxic trace elements into the Earth's atmosphere. Here we investigate the variability of concentrations of bismuth, cadmium, chromium, and lead in two Mount Johns - MJ (79°55'28"S, 94°23'18"W, 2100 m a.s.l) ice cores over 132 years (1883-2015). Trace element concentrations were determined using inductively coupled plasma mass spectrometry (CCI/UMaine). The data show evidence of pollution for these elements in Antarctica as early as the 1883. Several maxima concentrations were observed: first at the beginning of the 20th century and the last from 1970s to 1990s, with a clear decrease during recent years. Emissions occur from different anthropogenic sources and appear to be variable throughout the record. The main source of these elements is attributed to mining and smelting of non-ferrous metals in South America, Africa, and Australia. As well as a probable lead enrichment due to the use of fossil fuels. The MJ ice core record also reflects changes in atmospheric circulation and transport processes, probably associated with a strengthening of the westerlies.

Since the early 2000s, the northeastern region of the United States (USNE) has received increased total annual precipitation along with more frequent extreme precipitation events. Although previous work has discussed the contribution to increased extreme precipitation from tropical cyclones, the large‐scale driver(s) of summer precipitation increases in the extratropics has received little attention. Here, we show that the summer‐season rainfall surpluses across the USNE are related to the increased frequency of atmospheric blocking over Greenland and the negative phase of the North Atlantic Oscillation. The occurrence of these patterns in summer has been previously connected with southward shifted storm tracks and wet conditions across the eastern North Atlantic. Over the USNE, the circulation shifts are also related to enhanced rainfall due to southerly wind anomalies and increased moisture transport into and vertical motion over the region. It is important to note that the current generation of climate models used for future projections is unable to reproduce the observed tendency towards increased atmospheric blocking over Greenland. Thus, clarifying the association between Greenland blocking and recent precipitation changes across the USNE may help inform future climate projections of summer season rainfall for the region.

Net accumulation records derived from alpine ice cores provide the most direct measurement of past precipitation. However, quantitative reconstruction of accumulation for past millennia remains challenging due to the difficulty in identifying annual layers in the deeper sections of ice cores. In this study, we propose a quantitative method to reconstruct annual accumulation from alpine ice cores for past millennia, using as an example an ice core drilled at the Chongce ice cap in the northwestern Tibetan Plateau (TP). First, we used laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) technology to develop ultra-high-resolution trace element records in three sections of the ice core and identified annual layers in each section based on seasonality of these elements. Second, based on nine 14C ages determined for this ice core, we applied a two-parameter flow model to established the thinning parameter of this ice core. Finally, we converted the thickness of annual layers in the three sample sections to past accumulation rates based on the thinning parameter derived from the ice flow model. Our results show that the mean annual accumulation rates for the three sample sections are 109 mm yr−1 (2511–2541 years BP), 74 mm yr−1 (1682–1697 years BP), and 68 mm yr−1 (781–789 years BP), respectively. For comparison, the Holocene mean precipitation is 103 mm yr−1. This method has the potential to reconstruct continuous high-resolution precipitation records covering millennia or even longer time periods.

Dust particle studies in ice cores from the tropical Andes provide important information about climate dynamics. We investigated dust concentrations from a 22.7 m ice-core recovered from the Quelccaya Ice Cap (QIC) in 2018, representing 14 years of snow accumulation. The dust seasonality signal was still preserved with homogenization of the record due to surface melting and percolation. Using a microparticle counter, we measured the dust concentration from 2 to 60 µm and divided the annual dust concentration into three distinct groups: fine particle percentage (FPP, 2–10 µm), coarse particle percentage (CPP, 10–20 μm), and giant particle percentage (GPP, 20–60 μm). Increased dust was associated with the warm stage of the Pacific Decadal Oscillation index (PDO) after 2013 with significant increases in FPP and a relative decrease in CPP and GPP. There was a positive correlation between PDO and FPP (r = 0.70, p -value < 0.005). CPP and GPP were dominant during the mainly PDO cold phase (2003–2012). The FPP increase record occurs during the positive phase of PDO and snow accumulation decrease. We also revealed a potential link between QIC record and Madeira River during the wet season through two relationships: between QIC snow accumulation and runoff during transitional season, QIC dust, and suspended sediments during high-water discharge. The snow accumulation (during September-November) and runoff (during November-January) relationship present similar variability using a time-lag (60 days) while total dust and FPP group are associated with average suspended sediments concentration during February-April. Assessing dust record variability by distinct size groups can help to improve our knowledge of how the Pacific ocean influence dust record in the QIC. In addition, the association of snow accumulation and dust variability with dynamic changes in suspended sediments load and runoff in the Madeira River system demonstrates the potential for future investigation of linkages between QIC record and Amazon basin rivers.

Nitrate (NO3-), an abundant aerosol in polar snow, is a complex environmental proxy to interpret owing to its diverse sources and susceptibility to post-depositional processes. During the last glacial period, when dust concentrations in the Antarctic ice were upto similar to 50 times than today, mineral dust appears to have a stabilizing effect on the NO3- concentration in snow. However, the mechanism leading to the stabilization remains unclear. Here, we present the new and highly resolved records of NO3- and non-sea salt calcium (nssCa(2+), a proxy for mineral dust) from the Roosevelt Island Climate Evolution (RICE) ice core. We focus on the glacial period from 83 to 26 kilo years Before Present (ka BP). The data show a statistically significant correlation between NO3- and nssCa(2+) over this period. To put our findings into a spatial context, we compare RICE data with existing records from east Antarctica (EPICA Dome C [EDC], Vostok and central Dome Fuji) and West Antarctica (West Antarctic Ice Sheet Divide Ice Core [WDC]). Spatial analysis suggests that nssCa(2+) is contributing to the effective scavenging of NO3- from the atmosphere perhaps through the formation of calcium nitrate (Ca(NO3)(2)). The geographic pattern implies that the process of Ca(NO3)(2) formation occurs during the long-distance transport of mineral dust from mid-latitude source regions by Southern Hemisphere Westerly Winds (SHWW). The data also suggest that the correlation observed at various Antarctic locations may depend on the level of dust reaching the sites from the mid-latitude sources.

Ice core records provide a robust tool for reconstructing past climate variability and for improving our understanding of the relative contributions of natural and anthropogenic emissions into the atmosphere. In particular, heavy metal pollution from anthropogenic emissions poses a significant health and environmental risk. We present a sub-annually dated, continuously sampled Tupungatito ice core (TPG-12) data set that documents change in atmospheric pollution in Central Chile. Results from our well-preserved environmental record display a significant change in atmospheric pollutant concentrations coincident with anthropogenic activities in this region, notably from Chile. TPG-12 Enrichment factors (EFs) for Cd, As, Pb, Cu, and Ag exhibit values in excess of natural inputs over the last one hundred years, with increases beginning around 1930. Terrestrial source dust elements such as Ce, La, Pr, and Ti do not exhibit similarly increased EF values, demonstrating an anthropogenic source for Cd, As, Pb, Cu, and Ag. Our results also capture a decrease in As and Pb starting in the early 2000s, in concert with new environmental regulations in Chile (Caldentey and Mondschein, 2003).

Pleistocene glacial–interglacial cycles are hypothesized to be modulated by Earth’s orbital parameters through their influence on the Northern Hemisphere summer insolation. Changes in obliquity—Earth’s axial tilt—can explain the 41,000-year glacial cycles in the Early Pleistocene. However, the absence of 19,000- and 23,000-year frequencies corresponding to Earth’s precession of the rotation axis from those cycles remains enigmatic. Here we investigate how these orbital forcings may have changed by developing an insolation proxy based on the oxygen-to-nitrogen ratio of gases trapped in ice core samples collected from the Allan Hills Blue Ice Area in East Antarctica. We find that East Antarctic temperature was positively correlated with local, Southern Hemisphere summer insolation in the Early Pleistocene, while this correlation became negative in the late Pleistocene, with only the latter being consistent with the previous findings that Northern Hemisphere insolation paced Antarctic climate. If Early Pleistocene ice volume and local Antarctic temperature co-varied, our result supports the hypothesis that attributes the absence of precession in the 41,000-year glacial cycles to cancellation of precession frequencies in hemispheric ice volume changes that are responding to local insolation, suggesting a more dynamic East Antarctic Ice Sheet in the Early Pleistocene than in the past 800,000 years.

Abstract This study compares temperature, precipitation, and other climate variables from six widely used climate reanalysis products to inform ice‐core climate proxy record calibration in the Altiplano region of the central Andes. The reanalyzes are the European Reanalysis version 5 (ERA5), European Reanalysis Interim, Modern‐Era Retrospective analysis for Research and Applications (MERRA2), Japanese 55‐year Reanalysis, Climate Forecast System Reanalysis and version 2 extension, and NCEP/NCAR Reanalysis version 1. These data products are validated against observations from automatic weather stations on the Quelccaya Ice Cap, Peru (5,650 m a.s.l) and Chacaltaya, Bolivia (5,238 m a.s.l), in addition to lower sites ranging in elevation 2,500–4,900 m a.s.l. Our results suggest that ERA5 provides the most robust overall depiction of temperature and precipitation across the study domain, and the data set is particularly useful for its back‐extension to 1950. However, MERRA2 produces lower precipitation error scores owing to a gaged‐based bias correction. An examination of ERA5 vertical atmospheric profiles for a latitudinal transect over Quelccaya shows considerable variability, including across major El Niño events, suggesting the need for caution when interpreting isotopic signatures in ice cores.

It is estimated that the explosive Hudson volcano eruption in Southern Chile injected approximately 2.7 km3 of basalt and trachyandesite tephra into the troposphere between August 8-15, 1991. The Hudson signal has been detected in Antarctica at the eastern sector and in South Pole snow. In this work, we track the Hudson volcanic plume using a dispersion model, remote sensing, and a re-analysis of a high-resolution ice core analysis from the Detroit Plateau in the Antarctic Peninsula and sedimentary records from shallow lakes from King George Island (KGI). The Hudson eruption imprint in these records is confirmed by using a weekly resolved aerosol concentration database from KGI demonstrating that the regional impact of Hudson eruption predominates over the Mount Pinatubo/Phillippines volcanic signal, dated from June 1991, in terms of particulate matter depositions. The aerosol elemental composition of Ca, Fe, Ti, Si, Al, Zn, and Pb increases from 2 to 3 orders of magnitude in background level during the days following the eruption of the Hudson volcano.