The contribution to sea level rise from Patagonian icefields is one of the largest mass losses outside the large ice sheets of Antarctica and Greenland. However, only a few studies have provided large-scale assessments in a spatially detailed way to address the reaction of individual glaciers in Patagonia and hence to better understand and explain the underlying processes. In this work, we use repeat radar interferometric measurements of the German TerraSAR-X-Add-on for Digital Elevation Measurements (TanDEM-X) satellite constellation between 2011/12 and 2016 together with the digital elevation model from the Shuttle Radar Topography Mission (SRTM) in 2000 in order to derive surface elevation and mass changes of the Southern Patagonia Icefield (SPI). Our results reveal a mass loss rate of −11.84 ± 3.3 Gt·a⁻¹ (corresponding to 0.033 ± 0.009 mm·a⁻¹ sea level rise) for an area of 12573 km² in the period 2000–2015/16. This equals a specific glacier mass balance of −0.941 ± 0.19 m w.e.·a⁻¹ for the whole SPI. These values are comparable with previous estimates since the 1970s, but a magnitude larger than mass change rates reported since the Little Ice Age. The spatial pattern reveals that not all glaciers respond similarly to changes and that various factors need to be considered in order to explain the observed changes. Our multi-temporal coverage of the southern part of the SPI (south of 50.3° S) shows that the mean elevation change rates do not vary significantly over time below the equilibrium line. However, we see indications for more positive mass balances due to possible precipitation increase in 2014 and 2015. We conclude that bi-static radar interferometry is a suitable tool to accurately measure glacier volume and mass changes in frequently cloudy regions. We recommend regular repeat TanDEM-X acquisitions to be scheduled for the maximum summer melt extent in order to minimize the effects of radar signal penetration and to increase product quality.

The Cordillera Darwin Icefield loses mass at a similar rate as the Northern and Southern Patagonian Icefields, showing contrasting individual glacier responses, particularly between the north-facing and south-facing glaciers, which are subject to changing climate conditions. Detailed investigations of climatic mass balance processes on recent glacier behavior are not available for glaciers of the Cordillera Darwin Icefield and surrounding icefields. We therefore applied the coupled snow and ice energy and mass balance model in Python (COSIPY) to assess recent surface energy and mass balance variability for the Schiaparelli Glacier at the Monte Sarmiento Massif. We further used COSIPY to simulate steady-state glacier conditions during the Little Ice Age using information of moraine systems and glacier areal extent. The model is driven by downscaled 6-hourly atmospheric data and high resolution precipitation fields, obtained by using an analytical orographic precipitation model. Precipitation and air temperature offsets to present-day climate were considered to reconstruct climatic conditions during the Little Ice Age. A glacier-wide mean annual climatic mass balance of −1.8 ± 0.36 m w.e. a ${}^{-1}$ was simulated between between April 2000 and March 2017. An air temperature decrease between −0.9 $°$ C and −1.7 $°$ C in combination with a precipitation offset of up to +60% to recent climate conditions is necessary to simulate steady-state conditions for Schiaparelli Glacier in 1870.

O testemunho de firn IC-02 (88°01’21,3"S e 82°04’21,7"W), atingindo 41,82 m de profundidade, foi coletado no manto de gelo da Antártica Oriental, durante uma travessia científica chileno-brasileira no verão austral de 2004/2005. Este estudo visou à determinação da variabilidade sazonal das razões isotópicas de oxigênio e hidrogênio (ẟ18O e ẟD) e da taxa anual de acumulação de neve. O testemunho foi subamostrado em um sistema de fusão contínua e o conteúdo isotópico determinado por espectrometria a laser de cavidade ressonante do tipo ring-down (WS-CRDS, sistema Picarro). A série de ẟ18O varia entre ‑50,77‰ e ‑41,40‰ (média -46,39 ± 1,37‰), enquanto o ẟD varia entre -408,18‰ e ‑323,85‰ (média -367,43 ± 12,51‰). O excesso de deutério (d) tem média de 4,36 ± 2,66‰. O testemunho representa 85 ± 3 anos de acumulação de neve, ou seja, uma taxa média de 152 ± 64 mm ano‑1 em equivalente d'água. A partir da década de 1990 ocorreu a diminuição da média anual de δD concomitante com o aumento da taxa de acumulação de neve (17% entre 1974 e 2003). O aumento desta acumulação poderia estar associado à maior mobilização de neve à deriva (drift snow) até o sítio de deposição, associada à maior advecção de massas de ar oceânicas vindas dos mares antárticos (Amundsen, Bellingshausen, Weddell e Lazarev). Tal interpretação é apoiada pelo aumento da velocidade dos ventos zonais, conforme observado nos campos de anomalias de altura geopotencial, vento zonal e temperatura em 500 mb da reanálise NCEP/NCAR.

Seasonal snow cover is a fundamental component of both the global energy budget and the water cycle. Its properties such as fractional snow cover or albedo are particularly affected by climate change. Several methods based on satellite data products are available to estimate these properties, each one with its pros and cons. This work presents a novel methodology that integrates three indexes applied to MODIS satellite data (Spectral Mixture Analysis (SMA), Normalized Difference Snow Index (NDSI) and Melt Area Detection Index (MADI)), to perform a spatio-temporal reconstruction of the fractional snow cover and albedo at 250 m spatial resolution in the Brunswick Peninsula, southwest Patagonia during the cold season (April-October) for the period 2000-2020. Three main steps are included: (1) the increase of the spatial resolution of MODIS (MOD09) data to 250 m using a spectral fusion technique; (2) the snow-cloud discrimination; (3) the daily spatio-temporal reconstruction of snow extent and its albedo signature with subpixel detection using the endmembers extraction and spectral mixture analysis. The results show a 98% agreement between MODIS snow detection and ground-based snow measurement at the automatic weather station Tres Morros (53.3174 °S, 71.2790 °W), with fractional snow cover values between 20% and 50%, showing a close relationship between snow and vegetation type. The number of snow days compiled from the MODIS data indicates a good performance (Pearson correlation of 0.9) compared with the number of skiing days at Cerro Mirador ski centre near Punta Arenas. Although the number of seasonal snow days show a significant increase trend of 0.54 days/year in Brunswick Peninsula during the 2000-2020 period a significant decreasing trend of -4.64 days/year was detected during 2010-2020, and also below the 400 m a.s.l. elevation, which is the most affected area. A reconstruction of the monthly mean temperature using the ERA5 Land reanalysis product shows a significant warming trend in May (0.068 ºC/year) and October (0.098 ºC/year) in the 2000-2020 period. Under the future emission scenario RCP8.5, the regional climate model RegCM4 predicts further warming during 2020-2050 of 0.059 ºC/year in July, 0.088 ºC/year in August, and 0.019 ºC/year in October, which will further reduce snow cover.