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Pushing the Limits of Sub-seasonal to Seasonal (S2S) Weather Forecasting

Dates: June 20 - 24, 2022 

Time: 9:00 a.m. - 4:00 p.m. 

Location: Virtual

Application Deadline: June 6th

How do scientists predict weather two weeks to two months in advance?  Forecasting at these lead times is often regarded as the next frontier in forecasting, and if successful will have numerous society benefits. As stated by the National Science Foundation, sub-seasonal to seasonal (S2S) forecasts “will be as widely used a decade from now as weather forecasts today”. What scientific questions need to be addressed to improve these forecasts?  And how can understanding these processes help educators teach their STEM courses? Join Meteorology and Atmospheric Science professors and researchers Drs. Steven Feldstein and Sukyoung Lee, in collaboration with CSATS science educators, in this NSF funded grant in Climate and Large-Scale Dynamics. Teachers will become immersed into the practices that scientists use to understand the underlying science and perform S2S weather forecasts.  Gaining relevant research experience along with collaborating with science educators, teachers will be able to translate this information into classroom lessons aligned with the Next Generation Science Standards that emphasize student learning about the practices of scientists.

This workshop will help educators learn how to apply important physics concepts to various phenomena. Through this one-week workshop, teachers will get a firsthand opportunity to learn about:

  • diagnostic and modeling strategies utilized by researchers
  • relationships between daily and longer lead-time probabilistic S2S weather forecasts
  • data sites utilized by researchers for S2S weather forecasts and how to use them in your classroom 

Increase content knowledge related to S2S weather forecasts, including the following concepts:

  • tropical convection
  • wave propagation from the tropics to midlatitudes
  • probabilistic weather forecasts
  • the utilization of physics principles to explain weather phenomena