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Data Description Created by: James Booth Contact: jbooth@ccny.cuny.edu This data is used in the following journal article: Towey, K. L., Booth, J. F., A. Rodríguez Enríquez, T. Wahl, 2022: Tropical cyclone storm surge probabilities for the east coast of the United States: A cyclone-based perspective. Nat. Hazards Earth Syst. Sci., 22, 1287–1300, https://doi.org/10.5194/nhess-22-1287-2022. Brief: Each .mat file contains two variables: alldate - a vector of dates using the Matlab datenum format surgenon – a vector of de-trended storm surge values (units: Meters) De-trending is carried out by removing a 365-day running average. For all time points within the first half-year and the final half-year, the running average centered on the middle of the respective year is removed. A full description of the calculations used in generating the data is in the journal article. If you would like the data in a different file type, contact James Booth at jbooth@ccny.cuny.edu
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Extratropical Cyclone Tracks used in the following publication: Booth, J. F., V. Narinesingh, K. L. Towey, J. Jeyaratnam, 2021: Storm Surge, Blocking, and Cyclones: A Compound Hazards Analysis for the Northeast United States, Journal of Applied Meteorology and Climatology. 60(11), 1531-1544.
The datafiles in this dataset contain tropical or extratropical cyclone track information. Each datafile name includes the name of city. The datafile contains track information (location and time) for all cyclones that pass within 1000 km of the named city. Each datafile contains a single variable, which is a datatype called: structure in Matlab (or, dictionary). Each entry in the dictionary is an cyclone track. The entries in the dictionary are in chronological order, based on the starting date of the track. The relevant fields in the dictionary are the center latitude, center longitude, and date. The extratropical tracks were identified by applying Mike Bauer’s MCMS tracking tool to ERA5 reanalysis data. The tropical cyclone tracks are from HURDAT2. Full details can be found in the Booth et al. (2021) article referenced with this dataset. For more information contact James Booth: jbooth@ccny.cuny.edu
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- Award ID(s):
- 1854773
- PAR ID:
- 10546786
- Publisher / Repository:
- Harvard Dataverse
- Date Published:
- Format(s):
- Medium: X
- Location:
- Harvard Dataverse
- Institution:
- Harvard
- Sponsoring Org:
- National Science Foundation
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