Surface energy fluxes on Chilean glaciers: measurements and models

• Published in: The Cryosphere
• Main Authors: Schaefer, Marius, Fonseca-Gallardo, Duilio, Farías-Barahona, David, Casassa, Gino
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2020
• Subjects: article; Verlagsveröffentlichung; Patagonia; The Cryosphere; Tierra del Fuego
• Online Access: https://doi.org/10.5194/tc-14-2545-2020; https://noa.gwlb.de/receive/cop_mods_00052496; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00052149/tc-14-2545-2020.pdf; https://tc.copernicus.org/articles/14/2545/2020/tc-14-2545-2020.pdf

The surface energy fluxes of glaciers determine surface melt, and their adequate parametrization is one of the keys to a successful prediction of future glacier mass balance and freshwater discharge. Chile hosts glaciers in a large range of latitudes under contrasting climatic settings: from 18∘ S in the Atacama Desert to 55∘ S on Tierra del Fuego. Using three different methods, we computed surface energy fluxes for five glaciers which represent the main glaciological zones of Chile. We found the main energy sources for surface melt change from the Central Andes, where the net shortwave radiation is driving the melt, to Patagonia, where the turbulent fluxes are an important source of energy. We inferred higher surface melt rates for Patagonian glaciers as compared to the glaciers of the Central Andes due to a higher contribution of the turbulent sensible heat flux, less negative net longwave radiation and a positive contribution of the turbulent latent heat flux. The variability in the atmospheric emissivity was high and not able to be explained exclusively by the variability in the inferred cloud cover. The influence of the stability correction and the roughness length on the magnitude of the turbulent fluxes in the different climate settings was examined. We conclude that, when working towards physical melt models, it is not sufficient to use the observed melt as a measure of model performance; the model parametrizations of individual components of the energy balance have to be validated individually against measurements.