Charles E. Konrad
University of North Carolina at Chapel Hill
39 Papers
250 Citations
Charles E. Konrad is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Tropical cyclone & Storm. The author has an hindex of 18, co-authored 39 publications.
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Papers
Synoptic-Scale Features Associated with Warm Season Heavy Rainfall over the Interior Southeastern United States
TL;DR: In this paper, the authors used synoptic features and parameters to identify 312 heavy rainfall events over the southeastern United States and used them to construct a Synoptic Climatology.
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Impact of Extreme Heat Events on Emergency Department Visits in North Carolina (2007-2011).
TL;DR: Data on emergency department visits for heat-related illness and other selected diseases were analyzed during three heat events across North Carolina from 2007 to 2011 to provide insight into the specific pathophysiological mechanisms and underlying health conditions associated with exposure to extreme heat.
Relationships between tropical cyclones and heavy rainfall in the Carolina region of the USA
Charles E. Konrad,L. Baker Perry +1 more
TL;DR: In this article, a 55-year precipitation events climatology is constructed that quantifies the influence of tropical cyclones on precipitation events with varying return intervals, showing that the majority of the heavy precipitation events in the eastern three-quarters of the USA are associated with tropical cyclone.
The Most Extreme Precipitation Events over the Eastern United States from 1950 to 1996: Considerations of Scale
TL;DR: In this article, a heavy-rain climatological description is constructed that identifies all precipitation events for the period of 1950-96 and estimates the heaviest mean 2-day precipitation totals over a range of spatial scales (i.e., circular regions from 2500 to 500 000 km2).
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Area-level risk factors for heat-related illness in rural and urban locations across North Carolina, USA
TL;DR: In this article, the authors identify area-level risk factors for heat-related illness (HRI) at the ZIP code level for urban and rural locations, and apply a spatial error regression model to identify risk factors with a significant relationship with HRI.
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