AMS Short Course on AI in Weather Radars
12 January 2020, Boston, MA
The AMS Short Course on AI (Artificial Intelligence) applications in Weather Radars will be held on 12 January 2019 preceding the 100th AMS Annual Meeting in Boston, MA. Preliminary programs, registration, hotel, and general information will be posted on the AMS Web site (www.ametsoc.org).
Modern ground based weather radars are mostly dual-polarized and they are rich in information content in multiple dimensions and are ideal candidates for effective AI applications. There are a large number of dual-polarization radars around the world. In addition, space borne weather radars such as Tropical rainfall Measuring Mission and Global precipitation mission have also produced rich observations, that are great to be analyzed using AI. AI has already been used with weather radar information long before it came popular in mainstream, such as use of neural networks for ingesting vertical profiles and using neuro fuzzy systems for hydrometeor classification.
The primary goal of this course is to familiarize participants with fundamentals of AI and machine learning, for applications related to weather radars. The course is targeted to students, researchers, and practitioners in the public and private sector. The course will introduce fundamentals of Artificial Intelligence, machine learning as well as ground and space borne weather radars. The course will introduce basic principles of Dual-polarization weather radars beyond imagery and show the link to AI. The course will then immerse students into three different weather radar applications namely, Quantitative precipitation Estimation, Nowcasting and Storm Classification, each covering different aspects of AI.
The overarching goal is to introduce users to techniques and applications to improve the radar products forecasting and warnings in a new and efficient manner. The method of instruction is divide into two formats namely lecture and laboratory session. The morning session is dedicated to lectures whereas the afternoon session will be lab exercises.
Instructors: The lead instructor for this course is Prof V.Chandrasekar, of Colorado State University and the co-instructor is Dr Joseph Hardin of Pacific Northwest National Laboratory. There will be additional guest speakers. Participants are expected to bring their own laptops to be able to participate in the hands-on exercises.
For more information please contact firstname.lastname@example.org
All short course/workshop attendees must register and wear a badge/ribbon. Short course/workshop registration is not included in the 99th Annual Meeting registration, and short course/workshop registration does not include registration for the 99th AMS Annual Meeting.