One thing that jumps to mind would be leaps in the subseasonal-to-seasonal forecasting of high-impact weather events, crossing those blurry lines between weather and climate. Barb Mayes Bousted is a meteorological trainer at the National Weather Service and the developer of the Winter Misery Index: Subseasonal-to-seasonal forecasting is increasingly critical for planning and operations related to industry, public safety, and agriculture. Richard “Heatwave” Berler, CBM#18 Chief Meteorologist KGNS TV, Laredo, Texas I hope to see some skill (now seen 7 days out) extend to 10-12 days out by decade’s end. This, run on ever faster computers will lead to greater resolution of small detail in the first 12 hours of a forecast, and give us a longer horizon on the large scale weather features.
Like a camera with more megapixels, weather observations/forecast models will be taken/run at a higher resolution, be it from more satellite platforms, even from crowd sourcing citizen weather stations and vehicles at the surface.
Texas TV meteorologist Richard “Heatwave” Berler evokes images of something common to all of us, the smartphone camera: (Photo by Orhan Cicek/Anadolu Agency via Getty Images) Anadolu Agency via Getty Images district of Antalya province in Turkey on November 30, 2019. Jason Furtado at the University of Oklahoma (OU), CIRES postdoctoral Sam Lillo, and Brian Etherton at Maxar Technologies strongly affirmed the role of AI in weather - climate science in the next decade.ĪNTALYA, TURKEY - NOVEMBER 30: A waterspout forms over the Mediterranean Sea close to Alanya. Kevin Petty, Head of science and forecasting at The Weather Company In other words, data and analytics will become more accessible to the broader population, leading to new, innovative products and solutions.ĭr. The democratization of data and analytics is something else that will give rise to more participation from individuals and groups not directly immersed in fundamental aspects of weather, water, and climate, but have the knowhow and interest to take advantage of weather-related data. Some populations/businesses are more vulnerable than others. We must stop treating weather equally across the globe. Like Gensini and Nesbitt, he believes we have only scratched the surface. He is also bullish on AI and machine learning. Kevin Petty is head of science and forecasting at The Weather Company, an IBM business. Steve Nesbitt, Professor of Atmospheric Sciences, University of Illinois at Urbana-Champaign It will also improve the mechanics of how computer models are run, reducing complexity and computational cost, enabling better accuracy and spatial resolution"ĭr. It will improve the quality of observations for forecasters and models, improving how information and data is incorporated into model forecasts and decision support systems. My thought is "artificial intelligence will revolutionize how we observe, simulate, and forecast weather and climate. Key themes that emerged from their projections center around: Artificial Intelligence (AI) and Machine Learning, Advances in Prediction, Communication, Societal Risk, Health, and Evolving Technology. The experts that I queried span the public, private and academic sectors of the weather-climate enterprise. Marshall Shepherd, University of Georgia and 2013 AMS President I also worry about continued trends in Arctic Sea Ice loss, sea level rise, and Greenland dynamics that, in some cases, are ahead of projections from decades ago.ĭr. I envision a percentage contribution (%) or likelihood metric attached to future forecasts or post-analyses. Attribution of extreme weather events to climate change will become more reliable. On the forecasting front, we will see the fruit of the Earth Prediction Innovation Center (EPIC) and its community collaboration approach. Satellite systems will continue to evolve beyond “seeing” weather with new data available for model assimilation. Phased-array weather radar systems will also gain traction. Communication, psychology, and sociology will be fully immersed in warning processes. Messaging and its consumption will focus on impacts rather than category or rating levels.