Modeling and Prediction
| Overview |
People and Interests |
Research Topics |
Related Projects |
The Modeling and Prediction theme involves research aimed at developing and improving both numerical and statistical-dynamical models for use in real-time tropical cyclone (TC) track and intensity forecasting.
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Name
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Interests
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| Stanley B. Goldenberg | Numerical TC model verification, climate factors influencing Atlantic hurricane activity on intraseasonal to multi-decadal time scales
| | Sundararaman G. Gopalakrishnan | Numerical weather prediction of TCs, scale interactions, convection and planetary boundary layer modeling
| | John Kaplan | Statistical-dynamical intensity model development, rapid intensification, genesis, vortex/environment interaction studies, post-landfall decay
| | Paul A. Leighton | Software development and support for TC modeling and other TC research activities
| | Thiago S. Quirino | Applied evolutionary search and optimization, data mining, machine learning, distributed memory programming, numerical modeling
| | Xuejin Zhang | Numerical modeling and model development, TC forecasts, land-air-sea interaction, numerical weather prediction, parallel computing
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- Develop the next generation TC forecast system that is capable of ingesting global- to vortex-scale observations and accurately representing multi-scale interactions using novel high-resolution movable nesting algorithm
- Advance our understanding of TC processes by using high-resolution numerical modeling of both real and idealized storms
- Perform statistical-dynamical TC rapid intensification, genesis, and post-landfall decay model development and evaluation and implement model updates into operations
- Improve physical parameterizations in HWRF model through use of observations collected by HRD's Hurricane Field Program
- Transition promising developments at HRD into operational HWRF modeling system at NCEP’s EMC
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