Snow and glacier melt—a distributed energy balance model within a flood forecasting system

Author(s):  
J Asztalos ◽  
R Kirnbauer ◽  
H Escher-Vetter ◽  
L Braun
2021 ◽  
Vol 35 (2) ◽  
Author(s):  
Akansha Patel ◽  
Ajanta Goswami ◽  
Jaydeo K. Dharpure ◽  
Meloth Thamban ◽  
Parmanand Sharma ◽  
...  

2010 ◽  
Vol 4 (4) ◽  
pp. 2143-2167 ◽  
Author(s):  
A. H. MacDougall ◽  
B. A. Wheler ◽  
G. E. Flowers

Abstract. Transferability of glacier melt models is necessary for reliable projections of melt over large glacierized regions and over long time-scales. The transferability of such models has been examined for individual model types, but inter-comparison has been hindered by the diversity of validation statistics used to quantify transferability. We apply four common types of melt models – the classical degree-day model, an enhanced temperature-index model, a simplified energy-balance model and a full energy-balance model – to two glaciers in the same small mountain range. The transferability of each model is examined in space and over two melt seasons. We find that the full energy balance model is consistently the most transferable, with deviations in estimated glacier-wide surface ablation of ≤ 35% when the model is forced with parameters derived from the other glacier and/or melt season. The other three models have deviations in glacier-wide surface ablation of ≥ 100% under the same forcings. In addition, we find that there is no simple relationship between model complexity and model transferability.


Climate ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 143
Author(s):  
María Fernanda Lozano Gacha ◽  
Manfred Koch

A distributed energy balance model (DEBAM) is applied to estimate the mass balance of the Artesonraju glacier in the Cordillera Blanca (CB), Peru, and to simulate the ensuing discharge into its respective basin, Artesoncocha. The energy balance model calibrations show that, by using seasonal albedos, reasonable results for mass balances and discharge can be obtained, as witnessed by annually aggregated Nash Sutcliffe coefficients (E) of 0.60–0.87 for discharge and of 0.58–0.71 for mass measurements carried out in the period 2004–2007. Mass losses between −1.42 and −0.45 m.w.e. are calculated for that period. The elevation line altitudes (ELAs), which lie between 5009 and 5050 m.a.s.l., are also well simulated, compared to those measured by the Unidad Glaciologica de Recursos Hídricos del Perú (UGRH). It is demonstrated that the net radiation which drives the energy balance and melting processes is mainly affected by the amount of reflected shortwave radiation from the different surfaces. Moreover, the longwave radiation sinks between 63 and 73% of solar radiative energy in the dry season. Further sensitivity studies indicate that the assumed threshold temperature T0 is crucial in mass balance simulations, as it determines the extension of areas with different albedos. An optimal T0 between 2.6 and 3.8 °C is deduced from these simulations.


1990 ◽  
Vol 36 (123) ◽  
pp. 217-221 ◽  
Author(s):  
Roger J. Braithwaite ◽  
Ole B. Olesen

AbstractDaily ice ablation on two outlet glaciers from the Greenland ice sheet, Nordbogletscher (1979–83) and Qamanârssûp sermia (1980–86), is related to air temperature by a linear regression equation. Analysis of this ablation-temperature equation with the help of a simple energy-balance model shows that sensible-heat flux has the greatest temperature response and accounts for about one-half of the temperature response of ablation. Net radiation accounts for about one-quarter of the temperature response of ablation, and latent-heat flux and errors account for the remainder. The temperature response of sensible-heat flux at QQamanârssûp sermia is greater than at Nordbogletscher mainly due to higher average wind speeds. The association of high winds with high temperatures during Föhn events further increases sensible-heat flux. The energy-balance model shows that ablation from a snow surface is only about half that from an ice surface at the same air temperature.


2009 ◽  
Vol 28 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Luis Octavio Lagos ◽  
Derrel L. Martin ◽  
Shashi B. Verma ◽  
Andrew Suyker ◽  
Suat Irmak

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