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Ken Pomeroy has worked in basketball for 15 years, providing analytics for college basketball teams through his web site and consulting for NBA teams since 2003. His work has been used by coaches, media, and fans, and his ratings are used by the NCAA’s basketball committee to help select teams for its postseason tournament. But his path to the sport began as a grad student in Atmospheric Science at University of Wyoming and then as a meteorologist with the National Weather Service for 12 years, where he learned the science of making predictions. Many principles of weather prediction have direct application to predicting basketball outcomes, both for players and teams. In this talk for the Weather Band, Ken discusses his background in weather prediction and how the lessons he learned there helped him succeed with sports analytics.

Weather service providers around the world offer the public forecasts and warnings to improve decision making and protect life and property. Recent surveys have found that, in the United States, weather news is one of the most popular items in the media (Pew Research Center 2008; Wilson 2008). In fact, it has been estimated that 300 billion forecasts are obtained by U.S. adults on an annual basis (Lazo et al. 2009). But there are very few studies that look at how and why the public gets, reads, and responds to weather information, even though this research is fundamental to the design of weather products and communication strategies.

Watch this presentation from the research team that installed the highest weather stations on earth: at the summit of Mount Everest. 

You'll also learn why there's such a desperate need for more high elevation weather observations and the challenges that the team faced in getting their gear where it needed to be.

Deep hail accumulations, sometimes up to 50 cm in depth, have occurred frequently enough to catch the attention of the National Weather Service (NWS), the general public, and social/digital media outlets.

Despite the extreme nature of these storms, adequate reports or measurements of accumulated hail depth are currently not collected or archived, and products to track or forecast these events do not exist, preventing guidance from being issued to emergency responders, transportation departments, and the general public.

How do we predict the size of hail? What environmental parameters should forecasters be looking at in order to predict hail? These are just some of the questions driving the meteorological research of Professor John Allen and his team at Central Michigan University (CMU).

In this webinar, a panel of distinguished guests discuss Superstorm Sandy's legacy, its lasting impacts, and the lessons we have learned from that remarkable storm. 

Take a step into the studio at a national weather network to see how a 24/7 production of weather forecasts works.

In an average year, high temperatures kill more people in the United States than all other weather-related phenomena combined (NOAA 2016), and in New York City two-thirds of heat-related deaths occur at home. Those most at risk are the ill and elderly, who tend to be home throughout the day. Yet few studies capture indoor residential temperatures in non-air-conditioned homes. 

Meningitis epidemics have a devastating impact on the region and its people. Even with treatment, the fatality rate can exceed 10%, and 10%–20% of survivors experience long-term after effects including brain damage and hearing loss. Meningitis can push a family into severe poverty, which is especially significant in a region where the annual per capita income ranges from US$500 to US$1500. Weather forecasting can play a significant role in vaccination campaigns and prioritize where vaccines should be delivered.