HURDAT2 — LLMpedia

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HURDAT2

HURDAT2 is the Atlantic basin tropical cyclone best-track dataset maintained by the National Hurricane Center, serving as the canonical archive for storm tracks, intensities, and metadata used by agencies such as the National Oceanic and Atmospheric Administration, National Weather Service, NASA, NOAA Hurricane Research Division, and research institutions including Woods Hole Oceanographic Institution, Scripps Institution of Oceanography, and University of Miami. The dataset underpins operational decision-making at organizations like the Federal Emergency Management Agency, historical analyses at the Smithsonian Institution and Library of Congress, and modeling efforts at centers such as European Centre for Medium-Range Weather Forecasts and National Center for Atmospheric Research.

Overview

HURDAT2 provides best-track time series for North Atlantic tropical cyclones including position, intensity, and categorical attributes used by National Hurricane Center forecasters, NOAA analysts, and researchers at Imperial College London and Massachusetts Institute of Technology. Entries are referenced by storm name and date ranges used in climatologies at Intergovernmental Panel on Climate Change assessments and global databases maintained by World Meteorological Organization and Joint Typhoon Warning Center. The file format is a plain-text, comma-separated layout consumed by software such as R Project for Statistical Computing, Python (programming language), and modeling systems developed at Princeton University and Columbia University.

The archive traces origins to 19th-century ship logs collated by agencies like the U.S. Coast Survey, maritime records curated at the National Archives and Records Administration, and early 20th-century compilations by researchers at Brown University and Yale University. Formalization into a standardized database occurred under the National Hurricane Center and the Hydrometeorological Prediction Center with contributions from historical climatologists at Florida State University and NOAA Atlantic Oceanographic and Meteorological Laboratory. Major reanalyses were carried out through collaborative projects involving NOAA Hurricane Research Division, the University of South Florida, and international partners at UK Met Office and University of the West Indies to reconcile records from the Hurricane of 1899, Great Hurricane of 1780 reappraisals, and mid-century storm events.

Each best-track record includes six-hourly entries for position and intensity, with fields reflecting coordinates, wind speed, pressure, and status categories aligned to the Saffir–Simpson hurricane wind scale and classifications used by American Meteorological Society publications. Metadata rows capture storm identifiers, start and end dates, and notes referencing observational sources such as HURDAT ship reports, C-MAN stations, Reconnaissance aircraft missions conducted by Air Force Reserve, and buoy and satellite products from Geostationary Operational Environmental Satellite and Joint Polar Satellite System. The archive catalogs named storms including historically significant events like Hurricane Katrina (2005), Hurricane Sandy (2012), and Hurricane Andrew (1992), and links to basin-wide summaries used by International Best Track Archive for Climate Stewardship.

Reanalysis procedures combine contemporary observational networks—meteorological balloon ascents, radiosonde profiles, Doppler radar returns, and scatterometer winds—with historical sources such as ship logs, Lighthouse Service records, and archival newspaper reports preserved at institutions like the Library of Congress. Revision cycles have been coordinated by panels including scientists from NOAA Atlantic Oceanographic and Meteorological Laboratory, National Hurricane Center, University of Oxford reanalysis collaborators, and international researchers from Nanjing University and Australian Bureau of Meteorology. Quality-control uses statistical methods from National Center for Atmospheric Research and visualization via tools developed at University of California, Berkeley.

HURDAT2 underlies risk assessments at Federal Emergency Management Agency, storm surge modeling at United States Army Corps of Engineers, catastrophe modeling by firms such as Munich Re and Swiss Re, and climate-change attribution studies reported to the Intergovernmental Panel on Climate Change. Emergency planners in municipalities like New Orleans, Louisiana, Miami, Florida, and San Juan, Puerto Rico use HURDAT2-derived climatologies for zoning, evacuation planning, and infrastructure design referenced in guidance from the American Society of Civil Engineers and Federal Highway Administration. Academic research at Massachusetts Institute of Technology, Princeton University, and University of Reading employs the dataset for trend detection, downscaling in coupled models at NOAA Geophysical Fluid Dynamics Laboratory, and paleotempestology validation with data from National Centers for Environmental Information.

Critiques highlight undercount biases in the pre-satellite era noted by researchers at University of Miami and Florida State University and uncertainties in intensity estimates discussed in studies from National Center for Atmospheric Research and European Centre for Medium-Range Weather Forecasts. Limitations include uneven observational coverage before systematic satellite monitoring instituted by NOAA and potential inconsistencies stemming from methodological shifts implemented by the National Hurricane Center and international reanalysis efforts. Users have raised concerns in literature by authors at Columbia University and Imperial College London about temporal homogenization, sample selection in trend studies, and attribution challenges when integrating HURDAT2 with model reanalyses at Climate Research Unit. Ongoing updates by NOAA Hurricane Research Division aim to mitigate these issues through peer-reviewed reanalyses and interdisciplinary collaboration with institutions such as Rutgers University and University of Colorado Boulder.

Category:Atlantic hurricane databases