EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Simulating the surface mass balance at the Monte Sarmiento Massif, Cordillera Darwin, Chile

Franziska Temme1, David Farías-Barahona1, Thorsten Seehaus1, Tobias Sauter2, Ricardo Jaña3, Jorge Arigony-Neto4, Inti Gonzalez5,6, Christoph Schneider2, and Johannes Fürst1
Franziska Temme et al.
  • 1Institut für Geographie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
  • 2Geographisches Institut, Humboldt-Universität zu Berlin, Berlin, Germany
  • 3Instituto Antártico Chileno, Punta Arenas, Chile
  • 4Instituto de Oceanografia, Universidade Federal do Rio Grande, Brazil
  • 5Centro Regional Fundación CEQUA, Punta Arenas, Chile
  • 6Universidad de Magallanes, Punta Arenas, Chile

Together with the Northern and the Southern Patagonian Icefield, the Cordillera Darwin Icefield (CDI) in Tierra del Fuego experienced strong ice loss during the last decades. In some areas the observed glacier retreat contrasts with findings of recent surface mass balance studies, which implies that the observed losses are partly caused by dynamic adjustments. However, the difficult accessibility of Patagonian glaciers and the harsh conditions result in scarce observational data of glacier mass balances, especially for the CDI. In the westernmost region of the CDI, Monte Sarmiento is located. It hosts an 83 km2 icefield, with Schiaparelli Glacier being the largest glacier, terminating in a proglacial lake.

We focus on reproducing the local meteorological conditions using statistical downscaling of atmospheric reanalysis data to the study site as well as a linear model of orographic precipitation. Subsequently, we concentrate on a best representation of the surface mass balance (SMB) conditions on the local glaciers. For this purpose, we apply four melt models of different complexity: i) a positive degree-day model, ii) a simplified energy balance model using potential insolation, iii) a simplified energy balance model using the actual insolation (accounting for cloud cover, shading effects and diffuse radiation) and iv) a fully-fledged surface energy balance model. For the latter, we rely on the “COupled Snowpack and Ice surface energy and mass balance model in PYthon” (COSIPY). These models are calibrated on Schiaparelli Glacier (24.3 km2), which is the largest and best-studied glacier of the Monte Sarmiento Massif. Observational records comprise in-situ stake, thickness and meteorological measurements as well as remotely sensed elevation changes and flow velocities. After the melt model calibration, we apply them to other adjacent glacier basins and assess their performances against geodetic mass changes. This way, we want to answer the question if it is feasible to apply SMB models, calibrated for one single glacier, to surrounding glaciated areas under these unique climatic conditions. If a single-site calibration showed poor transferability properties, further remotely sensed observables will be considered in the calibration. This way we also hope to answer the question, which melt model can best reproduce the spatial variability in remotely sensed specific mass balances over a larger region.

How to cite: Temme, F., Farías-Barahona, D., Seehaus, T., Sauter, T., Jaña, R., Arigony-Neto, J., Gonzalez, I., Schneider, C., and Fürst, J.: Simulating the surface mass balance at the Monte Sarmiento Massif, Cordillera Darwin, Chile, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2054,, 2022.