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Cooperative Institute for Meteorological Satellite Studies / University of Wisconsin-Madison
CIMSS Tropical Cyclone Team
Who We Are

Tropical Cyclone Research Team
Chris Velden    Tim Olander    Dave Stettner
Derrick Herndon    Tony Wimmers    Sarah Griffin

Remote Collaborators
Jeff Hawkins (NRL-Mry)    Jason Dunion (NOAA/HRD)

The main questions facing tropical cyclone (TC) forecasters are accurately determining the current intensity of the storm, the future intensity of the storm, and where the storm will be in the future. Data obtained from satellites are ideal for helping to provide answers to these questions due to their ability to provide nearly constant and total coverage of the tropics in space and time.

The CIMSS Tropical Cyclone webpage helps achieve these goals by providing near real-time imagery, derived atmospheric analysis products, and TC intensity estimates from a variety of different satellite platforms for global analysis of TCs and their surrounding environments. Many of the products from CIMSS are developed specifically for use by TC forecasters worldwide to provide unique information in support of their specific TC forecasting missions.

The CIMSS Tropical Cyclone group does not produce forecasts or warnings for any TCs, instead we provide unique information to the organizations and forecasters who do.

Scroll over tabs below for brief description of each project, the primary investigators, and a link to project homepages

The Advanced Dvorak Technique (ADT) provides real-time TC intensity estimates utilizing geostationary, infrared satellite imagery. The algorithm based on the Subjective Dvorak Technique, utilized at all TC forecasting centers worldwide, but it eliminates the inherent subjectivity of the technique. ADT intensity estimates can be produced in a completely automated manner over the entire TC lifecycle.
Primary Investigators : Tim Olander, Chris Velden
Project Homepage
Atmospheric motion vectors (AMV) are derived from a sequence of satellite imagery. Various channels can be used to calculate wind vectors at different atmospheric levels. The wind vectors can be used qualitatively by TC forecasters help visualize the wind field around TCs, as well as quantitatively within numerical weather prediction models. Atmospheric analysis products, such as wind shear, vorticity, and convergence, can be also be derived from these wind fields.
Primary Investigators :
Chris Velden, Steve Wanzong, Dave Santek, Dave Stettner
Project Homepage
The Morphed Integrated Microwave Imagery at CIMSS (MIMIC) product provides a radar-like visualization of the evolution of TC structure using advanced image morphing algorithms. The final product is a synthetically-derived animation at 15 minute intervals between two authentic passive microwave satellite images. The morphing routines utilize an advection/rotation scheme based on the current reported TC wind speed estimates.
Primary Investigators : Tony Wimmers  Chris Velden
Project Homepage
The MIMIC-TPW product presents total precipitable water over the ocean, retrieved from SSMI and AMSR-E microwave sensors. The final product is an hourly composite of many swaths of TPW retrievals, advected to the required time using 1000-600 hPa winds from the GFS model.

Primary Investigators : Tony Wimmers  Chris Velden
Project Homepage
The CIMSS AMSU algorithm utilizes observed microwave radiation from several different wavelengths to measure storm-related atmospheric warming during TC events at different heights within the storm. The amount of anamolous warming within the TC core is determined, after adjusting for the AMSU scanning geometry and resolution effects, and is then related to a storm intensity.
Primary Investigators : Derrick Herndon, Chris Velden
Project Homepage
The CIMSS Satellite Consensus (SatCon) algorithm blends individual TC intensity estimates derived from the ADT, CIMSS AMSU, and CIRA AMSU routines to produce ensemble TC intensity estimate. The individual intensity estimates are combined using a weighting scheme which effectively maximizes/minimizes the influence of each estimate based upon the strengths/weaknesses of each technique for the currently observed TC environment and structure.
Primary Investigators : Chris Velden, Derrick Herndon, Tim Olander
Project Homepage
The imagery and derived analysis products displayed allow users to identify and track the atmospheric feature called the Saharan Air Layer (SAL). This feature consists of a very dry and dusty low-level layer of air formed over the Saharan Desert of Africa which can spread over large areas the tropical Atlantic Ocean. The air within the SAL can drasitcally affect TC intensity and inhibit formation and/or development of TCs over the entire Atlantic Ocean basin.
Primary Investigators : Jason Dunion, Chris Velden
Project Homepage
This project employs an objective satellite-based tropical overshooting top (TOT) detection algorithm in the tropical Atlantic and Eastern Pacific Oceans. The TOTs are used as a proxy indicator to analyze vigorous convection trends in tropical disturbances that may become incipient tropical cyclones. Preliminary research has indicated some skill in using the TOT product as a predictor of TC genesis and rapid intensification in the Atlantic Ocean.
Primary Investigators : Sarah Griffin, Chris Velden
Project Homepage
Rapid-Scan Atmospheric Motion Vectors provide a unique opportunity to observe high spatial and temporal resolution wind fields in the upper-levels of tropical cyclones. The upper-level analyses are crucial for understanding the storm's outflow and mass flux. Thus, studies are underway to investigate the connection and influence of these upper-level winds to tropical cyclone intensity change.

Primary Investigators : Chris Velden, John Sears
Project Homepage
The ARCHER product and supporting real-time page are designed to aid tropical cyclone forecasters in sifting through the increasing wealth of relevant satellite data to quickly and objectively arrive at key TC characteristics. It is not intended to substitute for the skill of experienced analysts, but rather to increase the efficient use of analysis time.

Primary Investigators : Tony Wimmers  Chris Velden
Project Homepage
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