New Observed Data Sets for the Validation of Hydrology and Land Surface Models in Cold Climates

In a recent WRR paper, Yan et al. (2018, https://doi.org/10.1002/2017WR021290) have derived a simple, elegant, and useful way of reanalyzing quality-controlled SNOTEL data sets to produce quantitative estimates of water reaching the land surface during rain, snowmelt, and rain-on-snow events, and use these data to generate next-generation intensity duration, and frequency curves for these quantities at SNOTEL measurement locations. These new data sets may prove useful as direct inputs to design processes in some cases, but I argue in this commentary that they will probably have much more important application to the validation and refinement of off-line hydrology models and land surface schemes embedded in climate models, which can then be used to extend these data in space and time to create more comprehensive products to guide infrastructure design. If well validated, such tools can be used to extend backward in time to make detailed hindcasts of the historical record with more complete spatial and temporal coverage (which also facilitates more accurate estimation of extremes with longer return intervals) and forward in time to project future conditions that are needed to design long-lived infrastructure in what will likely be a highly nonstationary environment. In addition, there is a need to extend these data sets to include lower elevation areas in mountain environments, and other areas of the United States and Canada with cold winter climates.