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Abstract In the mountainous headwaters of the Colorado River episodic dust deposition from adjacent arid and disturbed landscapes darkens snow and accelerates snowmelt, impacting basin hydrology. Patterns and impacts across the heterogenous landscape cannot be inferred from current in situ observations. To fill this gap daily remotely sensed retrievals of radiative forcing and contribution to melt were analyzed over the MODIS period of record (2001–2023) to quantify spatiotemporal impacts of snow darkening. Each season radiative forcing magnitudes were lowest in early spring and intensified as snowmelt progressed, with interannual variability in timing and magnitude of peak impact. Over the full record, radiative forcing was elevated in the first decade relative to the last decade. Snowmelt was accelerated in all years and impacts were most intense in the central to southern headwaters. The spatiotemporal patterns motivate further study to understand controls on variability and related perturbations to snow water resources. 

Abstract Dust transported from rangelands of the Southwestern United States (US) to mountain snowpack in the Upper Colorado River Basin during spring (March‐May) forces earlier and faster snowmelt, which creates problems for water resources and agriculture. To better understand the drivers of dust events, we investigated large‐scale meteorology responsible for organizing two Southwest US dust events from two different dominant geographic locations: (a) the Colorado Plateau and (b) the northern Chihuahuan Desert. High‐resolution Weather Research and Forecasting coupled with Chemistry model (WRF‐Chem) simulations with the Air Force Weather Agency dust emission scheme incorporating a MODIS albedo‐based drag‐partition was used to explore land surface‐atmosphere interactions driving two dust events. We identified commonalities in their meteorological setups. The meteorological analyses revealed that Polar and Sub‐tropical jet stream interaction was a common upper‐level meteorological feature before each of the two dust events. When the two jet streams merged, a strong northeast‐directed pressure gradient upstream and over the source areas resulted in strong near‐surface winds, which lifted available dust into the atmosphere. Concurrently, a strong mid‐tropospheric flow developed over the dust source areas, which transported dust to the San Juan Mountains and southern Colorado snowpack. The WRF‐Chem simulations reproduced both dust events, indicating that the simulations represented the dust sources that contributed to dust‐on‐snow events reasonably well. The representativeness of the simulated dust emission and transport in different geographic and meteorological conditions with our use of albedo‐based drag partition provides a basis for additional dust‐on‐snow simulations to assess the hydrologic impact in the Southwest US. 

Abstract Seasonal snowpacks in mountain drainages of the Great Salt Lake Basin (GSLB), western United States, are the primary surface water supply to regional agriculture, the metropolitan Wasatch Front, and the terminal Great Salt Lake. Spring dust emissions from the eastern Great Basin result in a dust‐darkened GSLB snowpack, locally accelerating snowmelt relative to dust‐free conditions. Such acceleration has been linked to streamflow forecasting errors in the adjacent Colorado River Basin, but snow darkening impacts within the GSLB are largely uninvestigated. To quantify the dust impact, we analyzed patterns in dust radiative forcing (RF_dust) over the MODIS record (2001–2023) using spatially and temporally complete RF_dustand fractional snow‐covered area products. For validation, retrievals were cross‐referenced with in situ RF_dustobservations. Results showed that RF_dustwas present every year and had no significant trend over the record. Spatially, RF_dustwas similar across all three subbasins. Temporally, RF_dustexhibited high interannual variability (−30 to +40 Wm⁻²from record means) and has declined slightly in regions of the eastern GSLB. Controls of RF_dustmay be linked to seasonal meteorology and drought conditions, but drivers remain uncertain. Further understanding of the distribution and controls of RF_dustin the GSLB during changing climate and weather patterns may allow us to predict snowmelt more accurately.