Through orographic forcing, mountains effectively harness water vapor into freshwater in the form of precipitation, a large fraction of which is stored in mountain snowpack during winter and released for water supply through snowmelt in the warmer season. Snow cover in mountains is strongly affected by solar radiation, which is modulated by terrain features, and deposition of light absorbing particles (LAP), which reduces the snow albedo. Liou and his group developed a 3D radiative transfer parameterization to account for the terrain effects on the incoming solar radiation in topographically diverse regions and improved modeling of snow albedo by accounting for non-spherical snow grain shape and internal mixing of dust-snow. Their parameterizations have been implemented in the Energy Exascale Earth System Model (E3SM), along with other advances in modeling subgrid topographic effects and snow radiative transfer processes. Simulations using the E3SM Land Model (ELM) driven by climate projections show significantly reduced black carbon deposition in snowpack and hence, reduction in the LAP-induced radiative forcing in snow over the Northern Hemisphere in the future. By quantifying separately the contributions of climate change and LAP evolution on future snowpack, we demonstrate that the projected LAP changes in snow over the Tibetan Plateau will alleviate future snowpack loss due to warming by 52% and 8% at the end of this century for the SSP126 and SSP585 scenarios, respectively. Our findings highlight a cleaner snow future and its benefit for future water availability from snowmelt. Lastly, from hindcasts and numerical experiments using E3SM with a land coupled data assimilation system, we identified the significant role of Tibetan Plateau snow cover on interannual predictability of the 2003 European summer heatwave by exciting the signature Rossby waves connecting the Tibetan Plateau and European summer temperature. These findings underscore the need for further investigating the role of the Third Pole in providing long-lead predictability of extreme events in remote regions.