EGU2020-18265, updated on 12 Jan 2021
EGU General Assembly 2020
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Towards elaboration of a surface mass balance model of a mountain glacier using a stochastic weather generator

Taisiya Dymova1,2,6, Oleg Rybak3,4,5, and Viktor Popovnin1
Taisiya Dymova et al.
  • 1Department of Geography, Lomonsov Moscow State University, Moscow, Russian Federation (
  • 2Kotelnikov Institute of Radio Engineering and Electronics of RAS, Moscow, Russian Federation (
  • 3Sochi Research Center of RAS, Sochi, Russian Federation (
  • 4Water Problems Institute of RAS, Moscow, Russian Federation (
  • 5Earth System Science and Department of Geography, Vrije Universiteit Brussel Brussels, Belgium (
  • 6Department of Physical Geography, Stockholm University, Sweden (

Mathematical modeling of surface mass balance (SMB) of mountain glaciers requires appropriate climatic forcing. Normally, meteorological records from the weather stations located as close as possible to the glacier are used for this purpose. In the ideal case, a weather station is located directly on the glacier. Even then, weather records are comparatively short and are hardly applicable for transient simulation of glacier dynamics. Thus, the lack of observations is an obvious obstacle for obtaining reliable simulation results. To overcome it, we suggest to apply a simple stochastic weather generator to emulate synthetic records of surface air temperature, precipitation and other meteorological variables required for calculation SMB by an energy-balance model.

Weather generators have been applied in many geophysical applications for decades, except, paradoxically, for glaciological ones. This is a powerful tool enabling generation of synthetic records which are statistically similar to observations (including probability distribution, standard deviations, autocorrelations etc.).

We report about the work in progress, which aims at elaboration of a reliable methodology for SMB calculation in diverse environmental conditions.

The study was supported by Russian Foundation of Basic Research RFBR (grant Nos. 18-05-00420 and 18-05-60080).

How to cite: Dymova, T., Rybak, O., and Popovnin, V.: Towards elaboration of a surface mass balance model of a mountain glacier using a stochastic weather generator, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18265,, 2020

This abstract will not be presented.