VDM+ Dataset | About the VDM+ Dataset

About the Enhanced Vortex Data Messages (VDM+) Dataset

The first phase of this RPI-funded project updated an expansive dataset of structure and intensity parameters obtained from Vortex Data Messages (VDM) and other sources. The resulting Enhanced Vortex Data Message (VDM+) Dataset is now available to the public for a wide variety of academic, educational, research, and internal operational uses.

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The current page provides acknowledgments and copyright/sponsorship notice for the VDM+ Dataset. On the other pages in this section, the reader can learn more about the data sources for the dataset, download the dataset and accompanying documentation, view visualizations of these data, learn how other people have used the dataset, and review relevant references that can be cited when the dataset is used.

Acknowledgments

People who assisted in the development of the VDM+ Dataset:

I owe an enormous debt to the brave flight crews of the 53rd Weather Reconnaissance Squadron, NOAA's Aircraft Operation Center, and the Hurricane Research Division scientists who put themselves at risk each time they collect these vital data. Without their dedication and diligence, this dataset would not exist.

I also thank the National Hurricane Center for making the vast majority of the VDMs freely available in their reconnaissance archive. I thank Steve Feuer, A. Barry Damiano, John Pavone, Chris Sisko, Christopher Juckins, Mark Zimmer, Christopher Landsea, and Neal Dorst for their assistance in helping to track down some of the remaining VDM messages. They, along with Eric Blake, Jonathan Talbot, Jack Parrish, John Beven, and Nicholas Carrasco, graciously answered my many questions about the VDM contents, history, and usage.

I thank my former advisor, Dr. Wayne Schubert, for graciously and patiently allowing me to spend an inordinate amount of time on this project during my doctoral research.

I thank Ray Zehr, John Knaff, and Mark DeMaria for their insightful suggestions. I also thank Mark for allowing the Extended Best Track and SHIPS Developmental datasets to be included in the VDM+ Dataset.

Buck Sampson, James Franklin, Michael Brennan, and Chris Landsea provided helpful information about the Automated Tropical Cyclone Forecast (ATCF) System b-decks and the Hurricane Database (HURDAT2).

I gratefully acknowledge the awesome support of the NCAR Command Language (NCL) Team, including Mary Haley, David Brown, Wei Wang, Richard Brownrigg, Dennis Shea, and others, for their expert programming advice. They often went above and beyond the call of duty to assist in troubleshooting difficult issues that were encountered.

Saji N. Hameed provided a programming suggestion that proved particularly helpful in overcoming a crucial obstacle in the aggregation of the VDM+ Dataset

Daniel Stern and Christopher Williams provided insightful comments that led to important improvements to the metadata and documentation.

Finally, I thank the technical support provided by the Research Applications Laboratory sysadmins and web developers, especially Tor Mohling and Adam Carhedan. Lara Ziady designed the template used for the TCGP web site.


Software used in the development of the VDM+ Dataset:

The NCAR Command Language (Version 6.6.2) [Software]. (2019). Boulder, Colorado: UCAR/NCAR/CISL/TDD. http://dx.doi.org/10.5065/D6WD3XH5


Funding:

I gratefully acknowledge the support of NASA and the National Science Foundation, which supported the bulk of the VDM+ Dataset creation during my tenure as a graduate student at Colorado State University. Specifically, this work was supported by NASA/TCSP Grant NNG06GA54G and by NSF Grants ATM-0332197 and ATM-0837932.

The NCAR Advanced Study Program, along with the NCAR Earth Systems Laboratory and the Mesoscale and Microscale Meteorology Division, provided support during my tenure as an Advanced Study Program Postdoctoral Fellow in 2010-2011.

Completion of this project, including the final stages of dataset and documentation preparation, and the development of the TCDP web page, has been made possible due to substantial funding support from the Bermuda Institute of Ocean Sciences (BIOS) Risk Prediction Initiative (RPI2.0), funded collectively by the RPI member (re)insurance companies.


Copyright and Sponsorship Notice

This product was created by the Research Applications Laboratory of the National Center for Atmospheric Research (NCAR), which is operated by the University Corporation for Atmospheric Research (UCAR) pursuant to a Cooperative Agreement with the National Science Foundation.

Copyright © 2023, UCAR

 

This page was last updated 31 July 2023 by Jonathan Vigh.