Combined influence of temperature forcing and lapse rate on empirical melt-model performance
Abstract
Temperature-index models are popular tools for glacier melt-modeling at a variety of scales and are widely used in projections of glacier mass change. Though minimal input data are required to drive these models, the necessary data may only exist distal from the area of interest. Here we explore the combined effects of temperature forcing provenance and surface lapse rate on the performance of an empirical melt model. The model is applied to a polythermal glacier in the St. Elias Mountains of northwestern Canada over five melt seasons. Air temperature records come from three different environments: (1) glacier surfaces, (2) glacier-proximal locations, and (3) low elevation valleys, and are combined with constant lapse rates spanning the range of measured values from the temperature stations to the study site. Model performance is assessed by comparing measured and modeled cumulative summer ablation at a network of stakes and by evaluating the transferability of the model to a second site. We find that the temperature forcings and lapse rates have a modest impact on model performance, relative to the inter-annual variability of model performance due to melt-season conditions and calibration data quality. Despite < 30% variation in estimated summer ablation arising from the combined influences of temperature forcing and lapse rate, the resulting variations in estimated annual mass balance are >100% in some cases. We hypothesize that the quality and quantity of mass-balance data available for model calibration may play a larger role than the combined temperature forcing and lapse rate in dictating empirical melt-model performance.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2013
- Bibcode:
- 2013AGUFM.C34A..05F
- Keywords:
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- 0720 CRYOSPHERE Glaciers;
- 0776 CRYOSPHERE Glaciology;
- 0798 CRYOSPHERE Modeling;
- 0762 CRYOSPHERE Mass balance 0764 Energy balance