Abstract: Prediction of PM<sub>10</sub> grades in Seoul, Korea using a neural network model based on synoptic patterns (2016 AGU Fall Meeting)

Prediction of PM₁₀ grades in Seoul, Korea using a neural network model based on synoptic patterns

Sun-Kyong Hur¹, Hye-Ryun Oh¹, Chang-Hoi Ho¹, Jinwon Kim², Chang-Keun Song³, Limseok Chang⁴ and Jae-Bum Lee³, (1)Seoul National University, School of Earth and Environmental Sciences, Seoul, Korea, Republic of (South), (2)Korean Meteorological Administration, Seoguipo, South Korea, (3)National Environment Research, Incheon, Korea, Republic of (South), (4)National Institute of Environmental Research, Environmental Satellite Center, Incheon, South Korea

Back to: Emergence of a Regional to Global Observing System for Air Quality: Integrating Tropospheric Composition Observations, Models, and Uncertainty Characterization I Posters

Prediction of PM10 grades in Seoul, Korea using a neural network model based on synoptic patterns

Prediction of PM₁₀ grades in Seoul, Korea using a neural network model based on synoptic patterns