Man K. Yau wants to predict the behavior of storms, one raindrop at a time. A professor in the department of Atmospheric and Oceanic Sciences at McGill, Yau develops mathematical models that describe the physics of weather events. His models simulate phenomena as small as two raindrops colliding, allowing him to predict the path of a hurricane or the weather in Montreal.
Yau and his team develop mathematical representations of small scale processes within clouds, such as how rain drops form when water particles collide and stick to one another in a cube of air the size of a die. "With these models, we can observe how conditions like air turbulence affect the rate of collisions, improving our understanding of how storms develop," Yau explains.
These small-scale models are used to construct representations of larger weather events. "From these micro-physical processes, we can build weather system models that encompass hundreds of thousands of kilometers," Yau says.
Yau's models consist of mathematical equations describing the behavior of different water species - vapor, cloud water, rain, ice, snow and hail - within the weather system. The equations represent how these particles interact and behave; for example, how water crystallizes into ice or snow.
The models are then simulated using the fastest computers in the world. "For some simulations, we have to use a supercomputer in Japan with 5,000 processors, which is the size of an entire building," Yau says.
Yau enters weather conditions from ground-based sensing sites into his models to simulate how the weather will develop. He also investigates the internal behavior of clouds. "Pilots will actually fly a plane with measurement equipment into a cloud or even a hurricane to obtain data," Yau explains.
These planes are equipped with laser, infrared and sonar equipment that measure wind, humidity, and temperature conditions. The equipment is so sensitive that it can image snowflakes in three-dimensions.
Yau's models will help researchers predict dangerous weather events, reducing their impact; they have also been used to better understand how weather systems transport air-borne pollutants. Anyone who has survived a Montreal winter can appreciate the importance of better weather forecasting.
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