Albedo Parametrizations for the Laohugou Glacier No.12 in the Qilian Mountains-Previous Models and an Alternative Approach

Accurate estimates of albedo can be crucial for energy balance models of glaciers. A number of algorithms exist which are often site dependent and rely on accurate measurements or estimates of snow depth. Using the well-established COSIMA model we simulate the energy and mass balance of the Laohugou Glacier No.12 in the Qilian Mountains, on the northern fringe of the Qinghai-Tibetan Plateau, a glacier that has been well studied in the past. Using energy flux and mass balance measurements between 2010 and 2015 we were able to validate the model over multiple seasons. Using the original albedo parametrization, the model fails to reproduce the observed mass balance. We show that this is due to the failure to estimate snow depth accurately. We therefore applied two alternative albedo algorithms, one well established example and one new parametrization only dependent on temperature and time since last snow fall. As a result, mass balance simulations improve considerably from a RMSE of 0.53 m w.e. for the original parametrization to 0.39 and 0.19 m w.e. for the uncalibrated established and the new calibrated model respectively. Modelled albedo during the ablation period (NSE = 0.05, R-2 = 0.33) is more accurate than during the accumulation period (NSE = -0.37, R-2 = 0.04). Testing the new model at another glacier on the Tibetan Plateau shows that a local recalibration of parameters remains necessary to achieve satisfying results. Investigations into the effect of impurities in snow, regional moisture sources and changing surface characteristics with rising temperatures will be crucial for accurate projections into the future.

Automated summary

Accurate estimation of albedo is crucial for energy balance models of glaciers. This study uses a well-established model to simulate the energy and mass balance of a glacier in China's Qinghai-Tibetan Plateau, and finds that the original albedo parametrization fails to reproduce observed mass balance. By applying two alternative albedo algorithms, the study improves the mass balance simulations considerably. The researchers also emphasize the importance of investigating impurities in snow, regional moisture sources, and changing surface characteristics for accurate future projections.