We are adopting a tropical cyclone intensity classification scheme for use with thousands of people
Tropical cyclones (TCs) are poorly observed since they develop and spend most of their lifetimes over open ocean and away from
dense observing networks. In order to provide an estimate of TC intensity in the absence of observation, an objective algorithm
called the Dvorak technique was developed in the 1970s. The technique returned an estimate of maximum TC wind speeds
based on the analysis of a single Infrared (IR) satellite picture. Although the Dvorak technique has been improved and adopted by
all of the global TC forecast centers, it is well known that there can be large differences interagency differences in storm
intensities (e.g. see IBTraCS).
Some Dvorak-related reasons for these differences include the subjective application of certain Dvorak rules, different
interpretations of the cloud patterns, and/or the application of modified Dvorak rules for particular basins.
The end result is a heterogeneous tropical cyclone intensity record that cannot be used with confidence for trend detection. The goal
of this project is to provide new estimates and uncertainties of intensity in the recent TC record through the use of crowd
sourcing. Loosely defined, crowd sourcing is the participation of the general public in research projects that are too large in scope
to be completed by specialized scientists in a reasonable amount of time. In order to reanalyze TC intensities from 1978-2009, it would
take a team of 5 people working 8 hours a day about 23 years. If 5,000 people work on the problem, it can be done in 1-2 years.
In collaboration with the Citizen Science Alliance, we have transformed a version of the Dvorak technique into a web interface that presents
users with a simple set of questions. The user responses to these questions (e.g. "What color surrounds the eye?") will allow us
to determine an intensity estimate of the TC at that particular time. The application of a modified version of the Dvorak rules post-experiment will yield a
homogeneous TC intensity dataset complete with information about each storm including the uncertainty in the intensity (based on the
variance of the public classifications). Give it a try at Cyclone Center.
Related Links (Project Participants):
Related Journal Articles:
Related Conference Papers/Web Articles:
- Knapp, K.R., J. Matthews, J.P. Kossin, and C.C. Hennon, 2016:
of Tropical Cyclone Storm Types Using Crowd Sourcing. Monthly Weather Review,
- Hennon, C.C., K.R. Knapp, C.J. Schreck III, S.E. Stevens, J.P. Kossin,
P.W. Thorne, P.A. Hennon, M.C. Kruk, J. Rennie, J-M Gadea, M. Striegl, and
I. Carley, 2015:
Cyclone Center: Can Citizen Scientists Improve Tropical Cyclone Intensity Records?
Bulletin of the American Meteorological Society, 96, 591-607.
- Hennon, C.C., 2012:
Citizen Scientists Analyzing Tropical Cyclone Intensities.
EOS, 93, No. 40, 2 October 2012, pp. 285, 287.
- Hennon, C.C., 2014:
Crowd Sourcing Science.
International Workshop on Tropical Cyclones-VIII, World Meteorological
Organization, Special Focus Session 1c, Jeju, South Korea.
- Hennon, C.C., 2013: Improving the Tropical Cyclone Climate Record", available
- Hennon, C.C.,K.R. Knapp, C.J. Schreck III, S.E. Stevens, and J.P. Kossin,
CycloneCenter.org: Crowd Sourcing Hurricane Intensity. Poster 634,
20th Conference on Satellite Meteorology and Oceanography, American
Meterological Society, Phoenix, AZ.
- Hennon, C.C., K.R. Knapp, C.J. Schreck III, S.E. Stevens, and J.P. Kossin, 2013:Cyclone Center: Using
Crowd Sourcing to Determine Tropical Cyclone Intensity. Poster IN23B-1426,
American Geophysical Union Annual Meeting, San Francisco, CA.
- Hennon, C.C.,K.R. Knapp, P.A. Hennon, J. Kossin, M. Kruk, J. Rennie,
C. Schreck, L. Stevens, S. Stevens, and P. Thorne, 2012:
CycloneCenter.org: Crowd Sourcing to Improve the Global Tropical Cyclone Record