**4. Summary**

A climatology of documented blizzard events within Storm Data for the Grand Forks NWSFO CWA for the winter seasons of 1979–1980 and 2017–2018 was presented. The NARR was used to composite and objectively classify patterns. These results are now summarized.


While these results are most relevant to the local populace, the last point has important ramifications for the broader weather and climate communities. Impactful weather events such as blizzards are challenging to forecast/detect over both short and long time-scales due to properties (e.g., visibility) that are not explicitly simulated by weather and climate models. The success of the SOM technique to objectively classify patterns suggests that pattern recognition can be used to address problems such as the predictability of hazardous weather events in NWP ensembles or trends in these events in climate simulations. These subjects are the topics of forthcoming work.

**Author Contributions:** Conceptualization, A.K. and A.T.; Formal analysis, A.T.; Funding acquisition, A.K.; Investigation, A.T.; Methodology, A.K.; Project administration, A.K.; Supervision, T.G. and G.G.; Visualization, A.T.; Writing—original draft, A.K.; Writing—review and editing, A.K., T.G. and G.G.

**Funding:** This research was funded by the National Science Foundation Project IIA-1355466 at the University of North Dakota.

**Acknowledgments:** This paper is dedicated to the late Dave Kellenbenz, a general forecaster at the Grand Forks NWSFO who passed away in 2016 after a courageous battle with Melanoma. Dave maintained the database of blizzards at this o ffice and provided this dataset to the authors prior to his passing that motivated much of this work. The list of named blizzards from the Grand Forks Herald was provided by reporter Tess Williams. NARR data was provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at http://www.esrl.noaa.gov/psd/.

**Conflicts of Interest:** The authors declare no conflict of interest.
