We investigate the sensitivity of a distributed enhanced temperature-index (ETI) melt model, in order to understand which parameters have the largest influence on model outputs and thus need to be accurately known. We use melt and meteorological data from two Alpine glaciers and one glacier in the Andes of Chile. Sensitivity analysis is conducted in a systematic way in terms of parameters and the different conditions (day, night, clear-sky, overcast), melt seasons and glaciers examined. The sensitivity of total melt to changes in individual parameters is calculated using a local method around the optimal value of the parameters. We verify that the parameters are optimal at the distributed scale and assess the model uncertainty induced by uncertainty in the parameters using a Monte Carlo technique. Model sensitivity to parameters is consistent across melt seasons, glaciers, different conditions and the daily statistics examined. The parameters to which the model is most sensitive are the shortwave-radiation factor, the temperature lapse rate for extrapolation of air temperature, the albedo parameters, the temperature threshold and the cloud transmittance factor parameters. A parameter uncertainty of 5% results in a model uncertainty of 5.6% of mean melt on Haut Glacier d’Arolla, Switzerland.