Ablation measurement and modeling on the Sygyktinsky Glacier (the Kodar Ridge)

High-resolution data from an automatic weather station (for 45 days in July–August 2021) installed at the level of the perrenial snowline of the Sygyktinsky Glacier (Kodar Ridge, south of the Eastern Siberia) were used to simulate ablation with daily resolution. Ablation was measured conventionally (using snow stakes and ultrasonic sensor) and calculated basing on a surface heat balance (SHB). The average and total values of measured and calculated ablation are in a good agreement with each other, while daily fluctuations in the ablation may differ due to changes in the surface density. It was found that the calculation of ablation based on thermal balance is the most accurate and physically justified. The average magnitude of energy spent on melting the glacier was 81 W/m2. The greatest contribution to melting is made by the radiation balance (70 W/m2, 86%), and especially by the shortwave radiation balance (76 W/m2, 94%). The long-wave radiation balance was slightly negative (–7 W/m2) that means that the glacier was losing heat. The turbulent fluxes of latent and sensible heat were positive on all days, but their total contribution was insignificant (10 W/m2, 13% of the melting energy). The reason for the low values of turbulent heat is the weak wind speeds which are typical for the Kodar region in summer. Significant statistical correlations of ablation with the cloudiness, precipitation, atmospheric pressure, air temperature and relative humidity were found. The relationship of the melting rate with meteorological parameters is controlled mainly by the short-wave radiation balance, and not by the turbulent heat flows. Two the T-index models (regression and “degree-day” ones) were tested using the meteorological data. Both models reproduce the mean and total ablation well (deviation ≤ 9%), but the daily fluctuations in ablation are simulated with significant error (standard error of about 50%). The use of different “degree-day factor” (DDF) coefficients for snow and ice allows improving the model accuracy up to 44%. The T-index models best estimate ablation for snow surface (standard error ≤26%), and they may be improved by taking into account shortwave radiation and weather conditions.