Ice motion of the Patagonian Icefields of South America: 1984–2014

Mouginot, J.; Rignot, Eric

doi:10.1002/2014gl062661

Cited by 89 publications

(115 citation statements)

References 39 publications

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“…Those are most likely caused by dynamic adjustments to the fast retreat of their glacier fronts. The retreat and acceleration had been reported by various authors [43][44][45][46][47]. For Upsala glacier the retreat has accelerated between 2008 and 2011 remaining stable since then [46,[48][49][50].…”

Section: Elevation and Mass Changes Of The Entire Spimentioning

confidence: 68%

Elevation and Mass Changes of the Southern Patagonia Icefield Derived from TanDEM-X and SRTM Data

et al. 2018

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Abstract: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 km 2 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.

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Section: Elevation and Mass Changes Of The Entire Spimentioning

confidence: 68%

Elevation and Mass Changes of the Southern Patagonia Icefield Derived from TanDEM-X and SRTM Data

et al. 2018

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“…We find approximately the same volume loss rate between 2000 and 2013, but with lower frontal thinning rates that match the lack of retreat between 1999 and 2013. The effect of these lower rates is nullified by thinning and high flow speeds that extend far inland suggesting that changing terminus ice dynamics are able to affect even the highest elevation parts of the glacier, deep within the drainage basin, as observed in Patagonia (e.g., Mouginot and Rignot, 2015).…”

Section: Dem Vs Lidar-based Estimates Of Mass Changementioning

confidence: 99%

Stikine Icefield Mass Loss between 2000 and 2013/2014

Melkonian¹,

Willis

Pritchard

2016

Front. Earth Sci.

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We calculate thinning rates ( dh ) at the 5800 km 2 Stikine Icefield of southeast dt Alaska from stacked digital elevation models (DEMs) acquired between 2000 and 2013/2014, and glacier velocities between 1985 and 2014 from feature tracking on optical image pairs. We find a mass change rate of −3.3 ± 1.1 Gt yr −1 between 2000 and 2014, equivalent to an area-averaged elevation change rate of −0.57 ± 0.18 m w.e. yr −1 . In 2014, land-terminating glaciers are 50% of the Stikine Icefield's glaciated area and contribute −0.9 ± 0.4 Gt yr −1 of mass change (27% of the total), while marine-terminating glaciers are only 30% of the total glaciated area, but contribute 1.5−1 − ± 0.3 Gt yr (or 45% of total mass change, with the remaining mass loss from lacustrine-terminating glaciers). We estimate the frontal ablation flux between 2000 and 2014 at the four largest marine-terminating glaciers on the Stikine Icefield (covering 90-95% of the marine-terminating glaciated area) using our glacier velocities and maps of fjord bathymetry to estimate terminus cross sections and glacier thicknesses. The combined 2014 frontal ablation flux of these four glaciers is 1.18 ± 0.14 Gt yr −1 , which may account for the difference in average mass loss between marine-and land-terminating glaciers on the Stikine Icefield. The Stikine and adjacent Juneau Icefields have very different mass loss contributions from marine-terminating glaciers (45% vs. effectively 0%), but both have area-averaged elevation change rates that are less negative than Alaska-wide estimates, which is surprising for these southernmost icefields in Alaska.

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“…Mouginot and Rignot (2015) In the same study authors report that between 2005 and 2010, the glacier sped up yet again by 50% before decreasing again in 2014 (3.56 md -1 ). In addition, Sakakibara and Sugiyama (2014) found velocities higher than 3,000 my 1 (8.22 md 1 ) near the calving front for 2010 year, when most freshwater glaciers in the SPI had a general deceleration trend.…”

Section: Surface Velocities Of Upsala Glaciermentioning

confidence: 86%

“…Estimation of surface velocities studies in the Upsala catchment have been carry out by different techniques, such as aerial photogrammetry (Aniya and Skvarca, 1992), topographic surveys (Naruse and Aniya, 1992;Skvarca et al, 1995) and both optical (Skvarca et al, 2003;Sakakibara et al, 2013;Sakakibara and Sugiyama, 2014;Mouginot and Rignot, 2015) and SAR satellite images (Floricioiu et al, 2008;Floricioiu et al, 2009;Muto and Furuya, 2013;Mouginot and Rignot, 2015). These studies have estimated the evolution of glacier velocities from 1968 to 2011, considering different time scales (years or decades) and using various sensors and techniques (Table 1).…”

Section: Introductionmentioning

confidence: 99%

Velocidades superficiales del glaciar Upsala, Andes Patagónicos Sur, mediante el uso de correlación cruzada en imágenes satelitales: periodo 2013-2014.

Moragues

Lenzano

Vecchio

et al. 2017

andgeo

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ABSTRACT. In this study we present surface velocities estimation for the Upsala glacier catchment, South Patagonian Ice Field (SPI) during the summer season of years 2013 (January-March) and 2014 (March-April), including the Bertacchi, Cono, and Murallón tributaries using satellite images from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The Cross-Correlation method was applied by COSI-Corr technique with sub-pixel accuracy. In general, it should be noted that the SPI glaciers, and Upsala glacier in particular, are fast-flowing ice bodies, which makes the technique works properly. Results of surface velocities estimation ranged from 0.22 to 2.93 md -1 for January-March 2013 and 0.12 to 5.8 md -1 for March-April 2014. In summary, COSI-Corr can achieved accurate and reliable results for glacier displacements and surface velocities estimation, also contributing in the better knowledge of the velocities change processes in time, taking into account Upsala is one of the most dynamic temperate glaciers of the SPI. RESUMEN. Velocidades superficiales del glaciar Upsala, Andes Patagónicos Sur, mediante el uso de correlación cruzada en imágenes satelitales: periodo 2013-2014. En este estudio se presentan las estimaciones de velocidades superficiales de la cuenca del glaciar Upsala, Campo de Hielo Patagónico Sur (CHPS) durante la temporada de verano de los años 2013 (enero-marzo) y 2014 (marzo-abril), incluyendo los glaciares tributarios Bertacchi, Cono y Murallón utilizando imágenes satelitales ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer). El método de correlación cruzada se aplicó mediante la implementación de la técnica COSI-Corr, con una precisión a nivel de subpixel. Cabe destacar que los glaciares del CHPS, en general, y el glaciar Upsala, en particular, son cuerpos de hielo de flujo rápido, lo que hace que la técnica funcione correctamente. Los resultados de las velocidades superficiales oscilaron entre 0,22 a 2,93 md -1 para el periodo enero-marzo de 2013 y de 0,12 a 5,8 md -1 para el periodo marzo-abril de 2014. En resumen, COSI-Corr alcanzó resultados precisos y confiables para la estimación de desplazamientos y velocidades superficiales de los glaciares, contribuyendo al mejor conocimiento de los procesos de cambio de velocidades en el tiempo, teniendo en cuenta que Upsala es uno de los glaciares templados más dinámicos del CHPS.

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Ice motion of the Patagonian Icefields of South America: 1984–2014

Cited by 89 publications

References 39 publications

Elevation and Mass Changes of the Southern Patagonia Icefield Derived from TanDEM-X and SRTM Data

Elevation and Mass Changes of the Southern Patagonia Icefield Derived from TanDEM-X and SRTM Data

Stikine Icefield Mass Loss between 2000 and 2013/2014

Velocidades superficiales del glaciar Upsala, Andes Patagónicos Sur, mediante el uso de correlación cruzada en imágenes satelitales: periodo 2013-2014.

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