1710 Numerical Simulations and Machine Learning for Micro-Meteorology Predictions and Applications

  • Ryo Onishi, Tokyo Institute Of Technology
  • Kai Schneider, Aix-Marseille University
  • Tomoaki Watanabe, Nagoya University
  • Shaoxiang Qian, JGC corporation
  • Keigo Matsuda, Japan Agency for Marine-Earth Science and Technology

This minisymposium widely accepts simulation- and data-science research relating to micro-meteorology, which is the near-surface microscale meteorology (weather) that is affected by human activities.

Simulation and data sciences have greatly advanced in recent years. Their development will expectedly contribute to the realization of smart society through combining cyber and physical spaces. In such a future society, autonomous systems connected to networks work together to maintain optimal conditions for the society. In realizing this future society, the concept of micro-meteorology plays a critical (crucial?) role, as it links directly with human life. However, the prediction and monitoring technologies for micro-meteorology are yet to be developed, and it is undeniable that the micro-meteorology has been largely untouched in academia. In this minisymposium, we exchange the knowledge on the recent advancement of numerical simulation and machine learning for understanding and predicting micro-meteorology or human activities affected by microscale weather. Example keywords are as follows, but not limited to them.

numerical simulations, data science, scientific computing, optimal control, micro-meteorology, microscale weather, multiphase turbulence, environmental problems, urban heat environment, building flow, atmospheric boundary layer, exhaust heat diffusion, heat-related sickness, drone logistics, urban heat mitigation, etc...

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