Abstract/Summary

Snow darkening contaminants, such as black carbon (BC), can significantly shorten the duration of seasonal snow cover. This can have wide ranging impacts on downstream water availability, and hence on regional hydrology and meteorology. Despite the potential impacts, this effect is often disregarded in short and seasonal term weather forecasting. This thesis aims to improve the representation of snow albedo and melt within the Joint UK Land Environment Simulator, (‘JULES’), a commonly used component of weather and climate simulations across all timescales, by introducing a means of calculating BC concentration in snow. Site based tests show that the modified JULES is capable of replicating the observed concentration of BC in snow assuming that accurate BC deposition rates are prescribed and appropriate values are selected for the top snow layer thickness and the BC scavenging efficiency. At the test site in Japan, including BC reduced the snow duration by 15 days, bringing the date of final snow clearance much closer to observations. Though the results in Japan show substantial benefit from introducing BC to the modelled snow, globally the results are more mixed. Using a satellite albedo product to verify model performance across the Northern Hemisphere, it is found that in vegetated areas JULES already underpredicts snow albedo. Consequently, adding BC does not improve albedo prediction in these areas. Areas without much vegetation however, such as the Canadian Shield region, show considerable improvement when BC is introduced to JULES. The addition of BC to snow in JULES is shown to impact the surface energy balance and water cycles leading to a shift in evaporation and surface runoff to earlier in the year. This is especially true in the High Mountain Asia region and has the potential to affect predictions of drought, flooding and monsoon behaviour, highlighting the importance of accurate snow albedo prediction. This thesis is © British Crown Copyright, 2025, Met Office.