Red snow algal blooms reduce albedo and increase snowmelt, but little is known of their extent, duration, and radiative forcing. We calibrated an established index by comparing snow algal field spectroradiometer measurements with direct counts of algal cell abundance in British Columbia, Canada. We applied the field calibrated index to Sentinel-2, Landsat-8, and MODIS/Terra images to monitor snow algae on the Vowell and Catamount Glaciers (Purcells, British Columbia) in summer 2020. The maximum extent of snow algal bloom cover was 1.4 and 2.0 km2 respectively, about one third of the total surface area of the two glaciers, making these among the largest contiguous bloom areas yet reported. Blooms were first detected following the onset of above-freezing temperatures in early July and persisted for about two months. Algal abundance increased through July, after which the red snow algal bloom area decreased due to snow cover loss. At their peak in late July the blooms reduced albedo by 0.04 +/- 0.01 on average. Snow algae caused an additional 5.25 & PLUSMN; 1.0 x 10(7) J/m2 of solar energy to be absorbed by the snowpack in July-August, which is enough energy to melt 31.5 cm of snow. This is equivalent to an average snow algal radiative forcing of 8.25 +/- 1.6 W/m2 through July and August. Our results suggest that the extent, duration, and radiative forcing of snow algal blooms are sufficient to enhance glacial melt rates.

The objective of the study was to configure the Hydrological Modeling System (HEC-HMS) in such a way that it could simulate all-important hydrological components (e.g., streamflow, soil moisture, snowmelt water, terrestrial water storage, baseflow, surface flow, and evapotranspiration) in the Three-River Headwater Region. However, the problem we faced was unsatisfactory simulations of these hydrological components, except streamflow. The main reason we found was the auto-calibration method of HEC-HMS because it generated irrational parameters, especially with the inclusion of Temperature Index Method and Soil Moisture Accounting (an advanced and complex loss method). Similar problems have been reported by different previous studies. To overcome these problems, we designed a comprehensive approach to estimate initial parameters and to calibrate the model manually in such a way that the model could simulate all the important hydrological components satisfactorily.

Thermal regime and thickness of the active layer respond rapidly to climate variations, and thus they are important measures of cryosphere changes in polar environments. We monitored air temperature and ground temperature at a depth of 5 cm and modeled active-layer thickness using the Stefan and Kudryavtsev models at the Abernethy Flats site, James Ross Island, Eastern Antarctic Peninsula, in the period March 2006 to February 2016. The decadal average of air and ground temperature was -7.3 and -6.1 degrees C, respectively, and the average modeled active-layer thickness reached 60 cm. Mean annual air temperature increased by 0.10 degrees C y(-1) over the study period, while mean annual ground temperature showed the opposite tendency of -0.05 degrees C y(-1). The cooling took place mainly in summer and caused thawing season shortening and active-layer thinning of 1.6 cm y(-1). However, these trends need to be taken carefully because all were non-significant at p < 0.05. The Stefan and Kudryavtsev models reproduced the active-layer thickness with mean absolute errors of 2.6 cm (5.0%) and 3.4 cm (5.9%), respectively, which is better than in most previous studies, making them promising tools for active-layer modeling over Antarctica.