As the global average temperature continues to rise, it leads to a substantial alteration of weather and climate patterns across the world, representing a major challenge and threat for humanity. Research has indicated that events such as heat waves, severe storms, heavy precipitation, and droughts are expected to become more frequent and intense as a result of global climate change. However, the magnitude of the change is not uniform across regions, with some regions experiencing more severe warming or intense precipitation than others; meanwhile, the likelihood of droughts may increase in certain areas. The uneven response of regional climates to global change can be partially attributed to geographical factors such as the variability in land use/cover and topography, which have the capacity to modify the global warming footprint on local climate patterns.
This talk will delve into our current understanding of regional climate change, with a particular focus on cities - which house more than half of the world's population. It will explore how global warming, in conjunction with local factors such as urbanization, is altering extreme weather events, such as heatwaves and precipitation, especially in Asian megacities. Additionally, the talk will showcase practical strategies for mitigating and adapting to climate change, including research on enhancing human health and well-being or the use of renewable energy sources.
Furthermore, this talk will highlight recent developments in numerical modeling, including the innovative creation of a land surface model-based downscaling method. We will also discuss the "paradigm" shift in approach to use big data technologies, data mining, and artificial intelligence in climate change sciences. The discussion will center on how these methods are employed to enhance current weather and climate predictions to aid in planning and policymaking to couple with impacts of the global climate change crisis.
Professor (Assistant) DOAN Quang Van is an atmospheric scientist currently affiliated with the Center for Computational Sciences at the University of Tsukuba, Japan. His research is primarily focused on investigating the effects of global warming and localized land surface modification on regional-scale extreme weather and climate change. Professor Doan's investigations are centered on a variety of atmospheric phenomena, including the urban heat island (UHI), heavy rainfall, land-sea breeze, and planetary boundary layer physics. He is recognized for his contributions to the development of numerical weather prediction models, including a multi-layer urban canopy model coupled with a raytracing method to enable better representation of radiative exchange within urban canyons. Additionally, he is pioneering in the application of Artificial Intelligence/Machine Learning (AI/ML) techniques to climate science, having made notable contributions through the development of the Structural Self Organizing Map (S-SOM) algorithm and the Clustering Uncertainty Evaluation (CUE) framework in climate data mining.
Currently, Professor Doan is a board member of the Board on Urban Environment of the American Meteorological Society and has served as a committee member for several international conferences and symposiums on climate risk. He is the primary founder and chair of the CORDEX SEA Urban Climate initiative, which aims to promote international cooperation and enhance communication between stakeholders regarding climate change information, while building the capacity of local researchers' skills in fine-scale climate prediction.