Date: 5th Mar 2024, Tuesday (11:00am – 12:00pm)
Presenter: Danielle Su (CCRS)
Topic: A Matter of Scale – Modelling physical, biogeochemical and ecosystem ocean processes

Abstract:
The spatial and temporal scales that one decides to model at depends on its application for scale and process representation. Such consideration is crucial for ocean circulation models, since they are a foundational component for earth system, ecosystem and biogeochemical models. In this seminar, Dr Su will present on several coastal and regional ocean model configurations and how they can be applied for case studies addressing the following themes: (i) Coastal adaptation design; (ii) Biogeochemical and ecosystem processes; (iii) Impact of climate modes on sub mesoscale ocean processes.

Speaker Profile:
Dr Danielle Su is part of the Core Modelling Development Branch at CCRS and will be working on the development of a high resolution coupled atmosphere-ocean-wave, cSINGV, for Singapore and Southeast Asia. Prior to joining CCRS, Dr Su worked as an oceanographer for the international consultancy, DHI, where her portfolio covered scenario design for coastal adaption, extreme MetOcean design and biogeochemical modelling for blue carbon ecosystems. She completed her PhD at The University of Western Australia where her research focused on the seasonal and interannual variability of flow topography interactions in the Northern Indian Ocean as part of UNESCO’s Second International Indian Ocean Expedition. After her PhD, Dr Su worked at LOCEAN/CNRS in Paris, France as a postdoctoral scientist investigating physical mechanisms of oceanic carbon subduction.

Date: 12th Mar 2024, Tuesday (11:00am – 12:00pm)
Presenter: Htet Naing (CCRS)
Topic: Machine learning methods for data-driven microscopic traffic simulation modelling and calibration

Abstract:
The progression of machine learning (ML) within the realm of microscopic traffic modelling and simulation presents a unique opportunity to explore the synergy between modern ML methods and traditional microscopic traffic simulation (MTS) models. Thus, this research work aims to enhance MTS models’ accuracy and realism by integrating ML in two critical areas: MTS modelling and calibration. Firstly, it integrates physics-based and learning-based approaches to enhance the modelling and calibration of a central component of the MTS—namely, car-following model. To achieve this purpose, a novel calibration approach based on deep reinforcement learning is employed as well as new physics-guided graph learning-based method is introduced for car-following modelling. Next, a dynamic data-driven simulation framework is proposed for short-term traffic forecasting while adopting physics-guided machine learning paradigm. Finally, it addresses the challenge of fine-grained trajectory reconstruction using MTS combined with surrogate-assisted evolutionary optimization in real-world scenarios. In summary, this research work bridges the gap between ML and MTS models by exploiting their synergies, hence marking a significant step forward in the field of traffic simulation.

Speakers Profiles:
Mr Htet Naing is currently a Research Scientist working on the development of machine/deep learning approaches for weather nowcasting models. He has recently submitted his PhD thesis (Computer Science – Pending oral defense) at Nanyang Technological University. He has five years of extensive research experience in machine learning, simulation, and calibration. His prior research focuses on exploiting the synergy between physics and learning via physics-informed/-guided machine learning approaches with successful applications in data-driven microscopic traffic simulation modelling and calibration.

Date: 26th Mar 2024, Tuesday (11:00am – 12:00pm)
Presenter: Gianmarco Mengaldo (NUS)
Topic: Explainable AI for weather and climate with a focus on extremes

Abstract:
Earth’s climate is changing rapidly under the effect of global warming, leading to more frequent and severe extreme weather events [1,2]. These weather extremes, in turn, are exacting heavy socioeconomic and environmental tolls [3], prompting an urgent need for better understanding and predicting them. In this talk, we present some recent results obtained for the tropical Indo-Pacific region, using methods arising in dynamical system theory. In particular, we show that changes in weather patterns are leading to more weather extremes, namely heatwaves and extreme precipitation. These extremes can only be partially explained by El Niño-Southern Oscillation-driven variability. We then present the use of explainable AI tools to investigate the onset and precursors of these extremes. More specifically, we try to bridge existing human knowledge and “AI knowledge” to better understand their behaviour and predictability.

Speakers Profiles:
Dr Gianmarco Mengaldo is an Assistant Professor in the Department of Mechanical Engineering at National University of Singapore (Singapore), and an Honorary Research Fellow at Imperial College London (United Kingdom). He received his BSc and MSc in Aerospace Engineering from Politecnico di Milano (Italy), and his PhD in Aeronautical Engineering from Imperial College London (United Kingdom). After his PhD he undertook various roles both in industry and academia, including at the European Centre for Medium-Range Weather Forecasts (ECMWF), the California Institute of Technology (Caltech), and Keefe, Bruyette and Woods (KBW). Dr Mengaldo’s adopts an interdisciplinary approach integrating mathematical and computational engineering to study complex systems that arise in applied science. His current research interests involve (i) explainable AI, both theoretical and applied, (ii) the intersection between AI and domain knowledge, (iii) high-fidelity multi-physics simulation tools, and (iv) data-mining technologies for coherent pattern identification. Dr Mengaldo’s main application areas include engineering, geophysics, healthcare, and finance.

Date: 2nd Apr 2024, Tuesday (11:00am – 12:00pm)
Presenter: Yanyan Cheng (CCRS)
Topic: Earth system modelling for Nature-based climate solutions

Abstract:
Bioenergy with carbon capture and storage (BECCS) is a key land-based carbon removal strategy in future Shared Socioeconomic Pathways that are designed to limit global warming to well below 2 °C by the end of the 21st century. It’s crucial to assess the climate and carbon outcomes of such a large-scale projected expansion of bioenergy crops and its impact compared to alternative Nature-based climate solutions, such as reforestation and afforestation. However, most of the current assessments have focused on relatively small domains or have ignored crucial carbon-water-nitrogen interactions. In addition, existing assessments of BECCS either focus on the effectiveness of carbon removal or biophysically-driven climate change impacts. Given that carbon and climate outcomes can diverge, a consensus accounting of the two effects is yet to be done. By using an integrated multisector and multiscale human-natural system modeling framework, this study evaluates the biogeochemical and biogeophysical implications of two alternative land-based mitigation scenarios that aim to achieve the same end-of-the-century radiative forcing. Our findings highlight the need for strategic land use planning to identify suitable regions for bioenergy expansion and re/afforestation, thereby improving the likelihood of achieving the intended climate mitigation outcomes.

Speakers Profiles:
Dr. Yanyan Cheng is currently a Research Scientist at the Core Modelling Development Branch at CCRS. Before joining CCRS, Dr. Cheng is a Senior Research Fellow at NUS. From 2018 to 2020, she was a Postdoc Research Scientist at the Pacific Northwest National Laboratory in the U.S. She received her Ph.D. degree from the University of Wyoming in 2018. She is an Earth System modeler and hydrologist working on the intricate vegetation-water-carbon-land dynamics. Her research interests focus on Nature-based climate solutions, tropical ecohydrology, and hydrological and Earth System model development. She also specializes in the utilization of optimization techniques for Earth system modeling applications.

Date: 13th May 2024, Monday (11:00am – 12:00pm)
Presenter: Gilbert Brunet (Australia’s Bureau of Meteorology)
Topic: On the role of breaking African easterly waves and critical layers in hurricane genesis

Abstract:
This study by Asaadi and colleagues in (JAS, 2016, 2017) sheds new light on the long-standing challenge of understanding hurricane genesis. It focuses on the initial stage, which involves westward-traveling African easterly waves that have the potential to transform into organized cyclonic vortices. The outcome depends on various factors, including their intensity and nonlinear wave-breaking processes. In order to gain a deeper insight into the dynamics underlying hurricane genesis, we explore the flow characteristics and examine the physical and dynamical processes responsible for the formation of cyclonic vortices within easterly waves. To accomplish this, we employ atmospheric reanalysis data and numerical simulations. Our research involves a comprehensive analysis of developing easterly waves during the hurricane seasons spanning from 1998 to 2001, utilizing 6-hourly ERA-Interim reanalysis data. Composite analyses for all named storms reveal a consistent potential vorticity (PV) profile characterized by a steady, unchanging pattern, featuring a weak meridional PV gradient and a cyclonic (located to the south of the easterly jet axis) critical line. This pattern persists over several days leading up to the formation of the cat’s eye. Additionally, when examining the composite of PV anomalies during development, a statistically significant companion wave-packet of non-developing easterly waves becomes evident. This observation allows for the establishment of a geometric criterion to distinguish between developing and non-developing easterly waves (EWs). It suggests that only approximately 25% of the total EWs are associated with a nonlinear critical layer adjacent to a region characterized by a weak meridional PV gradient. We employ a shallow water model to investigate disturbances in both initial value and forced scenarios. The outcomes underscore the important interaction between dynamical and thermodynamical mechanisms. These conclusions align with the analytical theory concerning free and forced disturbances within an easterly parabolic jet, as described by Brunet and Warn in 1990, Brunet and Haynes in 1995, and Choboter et al. in 2000. Furthermore, Tory et al. (2020) establish that our findings are consistent with the results obtained in CMIP5 models, extending their relevance to the broader context of tropical cyclones.

Speakers Profiles:
Dr. Gilbert Brunet – the Chief Scientist at Bureau of Meteorology, Australia, since 2018. Chair, UK Met Office Scientific Advisory Committee (MOSAC) since 2018. Chair, World Meteorological Organization Scientific Advisory Panel since 2020. Director, Meteorological Research Division, Environment and Climate Change Canada, 2006-18. Director, Weather Science, Met Office (2012–15). Head (1999–2006) and research scientist (1993–98) at the Recherche Prévision Numérique Section, ECCC. PhD in meteorology, McGill University, 1989.