Skillfully forecasting hydrologic outcomes of rain-on-snow (ROS) events is critical for water management and flood mitigation not only in the western U.S. but globally. This study applies methods for a Snowpack Runoff Decision Support System (SR-DSS) to the unimpaired Upper Carson watershed in the eastern Sierra Nevada of California and Nevada by leveraging hourly Natural Resource Conservation Service SNOw TELemetry (SNOTEL) data and compares results to observed soil moisture, streamflow, and an existing operational snowpack-runoff model framework used by the National Oceanic and Atmospheric Administration’s River Forecast Centers. Information provided by the SR-DSS can be disseminated to forecasters in real-time to adjust the SNOW-17 model as conditions change in ways that the model alone might not capture. Our results indicate that SR-DSS can enhance situational awareness by providing detailed snowpack and weather conditions in a time-relevant manner for forecasting and decision-making. We provide case studies to demonstrate how the SR-DSS alone captures the onset of terrestrial water input and how it can help assess the performance of operational models (SNOW-17 and SAC-SMA). The study suggests that the SR-DSS can be a valuable tool for operational hydrologists by helping to refine flood forecasts by identifying specific aspects of models that can be improved or adjusted and enhance decision-making during ROS events by providing additional situational awareness. Further development and testing of the SR-DSS could lead to its adoption in operational forecasting, enhancing the resilience of water management systems in the face of growing extreme precipitation concerns.

The 1997 New Year’s flood event was the most costly in California’s history. This compound extreme event was driven by a category 5 atmospheric river that led to widespread snowmelt. Extreme precipitation, snowmelt, and saturated soils produced heavy runoff causing widespread inundation in the Sacramento Valley. This study recreates the 1997 flood using the Regionally Refined Mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) under prescribed ocean conditions. Understanding the processes causing extreme events inform practical efforts to anticipate and prepare for such events in the future, and also provides a rich context to evaluate model skill in representing extremes. Three California-focused RRM grids, with horizontal resolution refinement of 14km down to 3.5km, and six forecast lead times, 28 December 1996 at 00Z through 30 December 1996 at 12Z, are assessed for their ability to recreate the 1997 flood. Planetary to synoptic scale atmospheric circulations and integrated vapor transport are weakly influenced by horizontal resolution refinement over California. Topography and mesoscale circulations, such as the Sierra barrier jet, are prominently influenced by horizontal resolution. The finest resolution RRM-E3SM simulation best represents storm total precipitation and storm duration snowpack changes. Traditional time-series and causal analysis frameworks are used to examine runoff sensitivities state-wide and above major reservoirs. These frameworks show that horizontal resolution plays a more prominent role in shaping reservoir inflows, namely the magnitude and time-series shape, than forecast lead time, 2-to-4 days prior to the 1997 flood onset.

Increasing wildfire and declining snowpacks in mountain regions threaten water availability. We combine satellite-based fire detection with snow seasonality classifications to examine fire activity in California’s seasonal and ephemeral snow areas. We find a nearly tenfold increase in fire activity during 2020 and 2021 compared to 2001-2019 as measured by satellite data. Accumulation season snow albedo declined 17-77% in two burned sites as measured by in-situ data relative to un-burned conditions, with greater declines associated with increased soil burn severity. By enhancing snowpack susceptibility to melt, decreased snow albedo drove mid-winter melt during a multi-week midwinter dry spell in 2022. Despite similar meteorological conditions in 2013 and 2022, which we link to persistent high pressure weather regimes, minimal melt occurred in 2013. Post-fire differences are confirmed with satellite measurements. Our findings suggest larger areas of California’s snowpack will be increasingly impacted by the compounding effects of dry spells and wildfire.