3. CONCLUSIONS
We have introduced several new snow metrics that can be used alone or in conjunction with existing snow metrics. These new snow metrics are intended to provide a greater understanding of snow’s spatial and temporal variability and be relevant to a wide range of researchers and stakeholders. We have produced three retrospective snow metrics: snow cover frequency (SCF), snow disappearance date (SDD), and storm temperature (ST). Our SCF and SDD metrics are spatially extensive and readily available to augment station data or to provide snow information where none currently exists. In future work, we will expand the SDD metric to the Southern Hemisphere. The ST data from SNOTEL sites provide critical information on snowstorms’ changing characteristics across the western United States. It would be valuable to extend the ST timeseries to better understand trends and to capture some of the recent interannual variability in storms. The SCF and SDD data that are available through SnowCloudMetrics.app (Crumley et al. , 2020) will be annually updated. Still, users who want greater flexibility and near-real-time results can download code to be run through Google Earth Engine. These remote sensing-derived metrics, current produced using the MODIS binary snow cover algorithm have the potential for improvement by instead using fractional snow covered area (Painter et al., 2009; Rittger et al., 2013) or using data from Landsat 8, Sentinel 2 or similar finer resolution sensors.
In addition to the retrospective metrics, we have produced two prospective snow metrics: At-Risk Snow (ARS) and Frequency of a Warm Winter (FWW). The downscaled climate model output used to create ARS and FWW are best they have ever been, and a logical next step is for these two metrics to be expanded globally. As models and downscaling methods continue to improve, these metrics should be updated and produced on a global extent. Previous snow metrics have focused almost exclusively on western US water resources. While this region is important, there is a nationwide need for snow information with broader relevance.
The snow metrics presented here are simple enough to “tell the story” of snowpack changes over space, are spatially extensive (in some cases, global), and are produced in a consistent manner using high-quality data and are not overly complicated in their interpretation. We anticipate and hope that these new snow metrics will serve multiple sectors and stakeholder groups, some of whom have never used such information in the past.