Mesoscale Numerical Weather Prediction- Model Implementation and Applications

Anthony Praino


The presentation provides an overview of the importance of mesosccale and local weather modeling and prediction. It provides details on IBM's Deep Thunder weather prediction model as well as the community model which is incorporates. Case study examples are provided of weather events to illustrate the application of local modeling and prediction as well as the role of visualization as a means of communicating weather information.


Photo of Anthony Praino

Anthony Praino is the Chief Engineer and Meteorologist on the Environmental Sciences team at the IBM T.J. Watson Research lab in Yorktown Heights, NY, where he leads the systems and infrastructure engineering as well as develops environmental sensing and modeling applications.

His focus since 2000 has been developing the Business of Weather in IBM. Anthony is one of the founders of Deep Thunder, one of IBM’s 100 icons of progress. Anthony is also a member of the Jefferson Project team which is developing advanced modeling, sensing and IoT capabilities for environmental management.

Overall Anthony’s work has focused on applying cross disciplinary skills in business, environmental science, and engineering in the development and application of advanced analytics and decision support systems for clients and sectors including: environment, energy, government, transportation, agriculture, supply chain logistics and water infrastructure

Requested 2 times

Lecture languages



OtherWeather and Climate

Duration options

1 hour2 hours

Travel/delivery options

In-countryNo travel required: On DemandRemote via video conference


United States

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