E
Elizabeth N. Cassano
Researcher at Cooperative Institute for Research in Environmental Sciences
Publications - 20
Citations - 739
Elizabeth N. Cassano is an academic researcher from Cooperative Institute for Research in Environmental Sciences. The author has contributed to research in topics: Sea ice & Arctic ice pack. The author has an hindex of 13, co-authored 19 publications receiving 616 citations.
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Journal ArticleDOI
Arctic Cyclones and Their Interactions With the Declining Sea Ice: A Recent Climatology
Journal ArticleDOI
Synoptic Conditions During Wintertime Temperature Extremes in Alaska
John J. Cassano,John J. Cassano,Elizabeth N. Cassano,Mark W. Seefeldt,William J. Gutowski,Justin M. Glisan +5 more
TL;DR: In this article, a large-scale atmospheric state associated with widespread wintertime warm and cold extremes in southern Alaska was identified using 1989 to 2007 European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-I) data.
Journal ArticleDOI
Linkages between Arctic summer circulation regimes and regional sea ice anomalies
Amanda H. Lynch,Mark C. Serreze,Elizabeth N. Cassano,Alex D. Crawford,Julienne Stroeve,Julienne Stroeve +5 more
TL;DR: In this paper, an assessment of linkages between summer atmospheric patterns and sectoral anomalies in the area of maximum open water north of 70°N demonstrates that there is asymmetry in the mechanisms years with low ice extent and high open water fraction are uniformly associated with positive temperature anomalies and southerly flow in both the Atlantic and Pacific sectors.
Journal ArticleDOI
A Factorial Analysis of Storm Surge Flooding in Barrow, Alaska
TL;DR: In this paper, a numerical weather prediction model and a storm surge inundation model have been applied to the 21 case studies identified in National Weather Service data as high wind events, and a reduced-form model that adequately describes the flooding response has been developed.
Journal ArticleDOI
Analysis of WRF extreme daily precipitation over Alaska using self-organizing maps
Justin M. Glisan,William J. Gutowski,John J. Cassano,John J. Cassano,Elizabeth N. Cassano,Mark W. Seefeldt +5 more
TL;DR: In this paper, the authors use self-organizing maps (SOMs) to understand circulation characteristics conducive for extreme precipitation events in Alaska, using an artificial neural network that uses an unsupervised training process to find general patterns of circulation behavior.