Investigating Snow and Firn Processes in a Georgian Glacier through Local Data and Modeling

Mountain glaciers in data-scarce regions are particularly sensitive to climate variability, yet their snow and
firn processes remain poorly constrained due to limited long-term observations/analyzes, especially in the
Caucasus region. Caucasus glaciers are highly sensitive to temperature and precipitation variability due to
their mid-latitude location, steep relief, and strong seasonal contrasts.
In this study, we present a preliminary analysis of snow accumulation and melt dynamics for selected
areas in Georgia (Racha Region, Buba glacier), based on in situ meteorological observations and historical
data. The analysis focuses on preparing meteorological input data for the application of a conceptual
snow–firn model, following the framework proposed by Banfi and De Michele (2021). Meteorological and
snow data from selected Georgian glacierized catchments are analyzed to characterize snow
accumulation and melt dynamics and to prepare input datasets for snow–firn modelling. Particular
attention is given to precipitation phase partitioning, seasonal snow persistence, and data harmonization,
as available observations are often heterogeneous and affected by temporal gaps.
Key variables include snow depth, snow bulk density, snow water equivalent (SWE), and meltwater runoff.
While such variables are monitored at several well-instrumented Alpine sites, allowing for extensive multi-
year model evaluation, comparable long-term and structured datasets remain scarce in the Caucasus
region. However, given the similarities between the Caucasus region and the Italian Alps in terms of
geomorphological and hydrological characteristics, the modelling framework is well suited for application
in the Caucasus context.