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.