Relative performance of empirical and physical models in assessing the seasonal and annual glacier surface mass balance of Saint-Sorlin Glacier (French Alps)
This study focuses on simulations of the seasonal and annual surface mass balance (SMB) of Saint-Sorlin Glacier (French Alps) for the period 1996–2015 using the detailed SURFEX/ISBA-Crocus snowpack model. The model is forced by SAFRAN meteorological reanalysis data, adjusted with automatic weath...
Main Authors: | , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2018-04-01
|
Series: | The Cryosphere |
Online Access: | https://www.the-cryosphere.net/12/1367/2018/tc-12-1367-2018.pdf |
Summary: | This study focuses on simulations of the seasonal and annual surface
mass balance (SMB) of Saint-Sorlin Glacier (French Alps) for the
period 1996–2015 using the detailed SURFEX/ISBA-Crocus snowpack
model. The model is forced by SAFRAN meteorological reanalysis data,
adjusted with automatic weather station (AWS) measurements to ensure that simulations of all the energy balance components, in particular turbulent fluxes, are accurately represented with respect to the measured energy
balance. Results indicate good model performance for the simulation
of summer SMB when using meteorological forcing adjusted with
in situ measurements. Model performance however strongly decreases
without in situ meteorological measurements. The sensitivity of the
model to meteorological forcing indicates a strong sensitivity to
wind speed, higher than the sensitivity to ice albedo. Compared to
an empirical approach, the model exhibited better performance for
simulations of snow and firn melting in the accumulation area and
similar performance in the ablation area when forced with
meteorological data adjusted with nearby AWS measurements. When such
measurements were not available close to the glacier, the empirical
model performed better. Our results suggest that simulations of the
evolution of future mass balance using an energy balance model
require very accurate meteorological data. Given the uncertainties in the temporal evolution of the relevant meteorological variables and glacier
surface properties in the future, empirical approaches based on
temperature and precipitation could be more appropriate for
simulations of glaciers in the future. |
---|---|
ISSN: | 1994-0416 1994-0424 |