@article{4388f63d58a9497997ebd27dc054fad4,
title = "Projecting Changes in Societally Impactful Northeastern U.S. Snowstorms",
abstract = "The northeastern United States is vulnerable to many impacts from snowfall-producing winter cyclones that are amplified by the proximity of population centers to storm tracks. Historically, climatic snowfall assessments have centered around seasonal means even though local impacts typically occur at scales of hours to days. To detect snowstorms at the event level, an objective algorithm is defined based on the Regional Snowfall Index. The metric collocates storm snowfall with population to produce statistics of snowstorms with societal impacts. When applied to the Community Earth System Model Large Ensemble, broad declines in snowstorm frequency are projected by the later 21st century. These decreases are primarily due to a warmer atmosphere less conducive to snowfall as the predominant precipitation type. However, reductions are less significant for major events, since more hostile thermodynamic environments are partially offset by increased precipitation associated with cyclones that dynamically drive high-impact snowstorms.",
author = "Zarzycki, {C. M.}",
note = "Funding Information: The National Center for Atmospheric Research (NCAR) is sponsored by the National Science Foundation. This work was primarily supported by the U.S. Department of Energy Office of Science grant DE-SC0016605. Additional support was provided by NASA award NNX16AG62G and NCAR{\textquoteright}s Advanced Study Program. The author would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) and Cheyenne (https://doi.org/10.5065/D6RX99HX) provided by NCAR{\textquoteright}s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. C. M. Z. thanks Alan Rhoades for providing useful feedback on a draft of this letter and Jen Kay for answering questions regarding the LENS experimental design. The feedback from two anonymous reviewers greatly improved this manuscript. The TempestExtremes feature tracker can be downloaded from https://github.com/ ClimateGlobalChange/tempestextremes. Custom scripts for tracking and categorizing snowstorms in LENS data are publicly available at https://github.com/zarzycki/esta. Processed storm trajectories and RSI/RPI statistics that can be used to reproduce the results of this letter are provided as gzip data sets in the supporting information. Funding Information: The National Center for Atmospheric Research (NCAR) is sponsored by the National Science Foundation. This work was primarily supported by the U.S. Department of Energy Office of Science grant DE-SC0016605. Additional support was provided by NASA award NNX16AG62G and NCAR's Advanced Study Program. The author would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) and Cheyenne (https://doi.org/10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. C.?M.?Z. thanks Alan Rhoades for providing useful feedback on a draft of this letter and Jen Kay for answering questions regarding the LENS experimental design. The feedback from two anonymous reviewers greatly improved this manuscript. The TempestExtremes feature tracker can be downloaded from https://github.com/ClimateGlobalChange/tempestextremes. Custom scripts for tracking and categorizing snowstorms in LENS data are publicly available at https://github.com/zarzycki/esta. Processed storm trajectories and RSI/RPI statistics that can be used to reproduce the results of this letter are provided as gzip data sets in the supporting information. Publisher Copyright: {\textcopyright}2018. American Geophysical Union. All Rights Reserved.",
year = "2018",
month = nov,
day = "16",
doi = "10.1029/2018GL079820",
language = "English (US)",
volume = "45",
pages = "12,067--12,075",
journal = "Geophysical Research Letters",
issn = "0094-8276",
publisher = "John Wiley and Sons Inc.",
number = "21",
}