Date: 6th Feb 2025, Thursday (11:00am – 12:00pm)
Presenter: Davide Faranda (CNRS)
Topic: On the Link Between El Niño and Prolonged Dry Conditions in Southeast Asia

Abstract:
Prolonged dry conditions associated with El Niño events have significant socio-economic impacts across Southeast Asia, a region already vulnerable to water scarcity. However, the precise relationship between El Niño and these extended dry spells remains unclear, with only a few strong El Niño events triggering severe dry conditions. Our model captures the stochastic dynamics behind this link. By simulating both chaotic and stable climate states, the model illustrates how atmospheric patterns interact with El Niño to produce persistent dry conditions in a non-systematic way. This understanding is essential for improving drought predictions and preparing effective response strategies as climate change intensifies these events.

Speaker Profiles:
Davide Faranda is a Research Director in Climatology at CNRS, France. His research focuses on understanding extreme weather events, their dynamics, and their links to climate change. Davide’s work aims to bridge fundamental science and societal impacts He has contributed to several international projects, he leads ClimaMeter – an international consortium that realise extreme events attribution studies – and co-leads the COST Action FutureMed, a network exploring Mediterranean climate dynamics.

Date: 18th Feb 2025, Tuesday (11:00am – 12:00pm)
Presenter: Chin-Hsien Cheng (NTU)
Topic: Methane-Climate Feedback is Dominantly Dependent on Rate of Changing Temperature and Precipitation

Abstract:
Rapidly rising atmospheric methane concentration in recent years is alarming. While increasing wetland emission was proposed to be a major driver, we still need a consistent explanation how changing climate affects the methane sources and sinks throughout different timescales. By analyzing data from seasonal, interannual, to multidecadal scales, we classify the instantaneous methane-climate feedback into 8 (23) categories: rate- vs. state-dependent, temperature vs. precipitation dependent, and positively vs. negatively correlated. Seasonal feedback is found to be weakly negative, consistent to the interannual state-dependent feedback. This is mainly driven by the temperature effect on atmospheric methane sink. However, the net interannual and long-term methane-climate feedbacks are positive and stronger than IPCC’s estimate, driven by the changing rate (rate-dependent) instead of the absolute change (state-dependent) of temperature and precipitation. The rate-dependency is mainly due to interactions between sources and sinks. Such interactions should be incorporated into future process-based Earth system models (ESMs).

Speaker Profiles:
Dr. Chin-Hsien Cheng is a research fellow from Nanyang Technological University. His research focus is on biogeochemical Earth system feedbacks, in particular, how climate change affects the methane and carbon cycles. His earlier publication, ‘Impact of interannual and multidecadal trends on methane-climate feedbacks and sensitivity’, revealed the oscillating influence of interannual and multidecadal climate on the rate of rising atmospheric methane. His research highlighted that the oscillating positive feedback with stronger sources during warming years (e.g. El Niño years) followed by negative feedback with weaker sinks during cooling years (e.g. La Niña years), results in stronger positive methane-climate feedback in long term. In addition to research on Earth system feedbacks, he also look into negative emission technologies to draw down atmospheric CO2 or accelerate the atmospheric methane oxidation. His journey on climate change mitigation solutions started decades ago, with experience working on energy efficiency and transboundary haze pollution during his past service in National Environment Agency.

Date: 25th Feb 2025, Tuesday (10:30am – 12:00pm)
Presenter: Cenlin He (NCAR)
Topic: Advancing community models in addressing pressing environmental challenges: Examples from Noah-MP and WRF-Urban (with transition to MPAS)

Abstract:
Noah-MP and WRF-Urban, respectively, are two most widely-used community land surface and urban climate models in the world. This presentation will be divided into two parts. The first part is to present the Noah-MP land model and community efforts in enhancing model developments and applications in addressing key environmental issues, including climate extremes (e.g., drought, fire, flood), human activity impacts (e.g., agriculture management), snowpack and water resources, groundwater and land-atmosphere interactions. The second part is to present the WRF-Urban model and recent advances as well as its applications in addressing issues related to urban climate and extremes as well as adaptation. Finally, I will also briefly discuss the on-going transition from the WRF system to the MPAS system, NCAR’s Earth System Predictability Across Timescales (ESPAT) initiative (particularly on-going efforts in advancing subseasonal-to-seasonal (S2S) predictions), and potential opportunities for CCRS-NCAR collaborations.

Speaker Profiles:
Cenlin He is the land team lead at the Research Applications Laboratory (RAL) in the NSF National Center for Atmospheric Research (NCAR) in the US. His research expertise and interests include land modeling, land-atmosphere interaction, high-resolution climate/weather modeling, subseasonal-to-seasonal (S2S) prediction, air pollution modeling, and climate/weather extremes. He is leading the international effort for the community Noah-MP land model development and activities, leading and coordinating the international community efforts for WRF-Urban model development, co-chairing the international initiative “Urban Air Pollution and Interaction with Climate (U-APIC)”, and co-leading the land-atmosphere interaction working group of GEWEX Regional Hydroclimate Project (H2US). He is also serving on the WRF model code review and release committee, NCAR’s data Assimilation, Infrastructure, and Modeling (AIM) Working Group, and NOAA Unified Forecast System (UFS) land working group. He is a key contributor for NCAR high-resolution regional hydroclimate and air quality modeling efforts.

Date: 28th Feb 2025, Friday (2:00pm – 3:00pm)
Presenter: Xianfeng Wang (NTU)
Topic: Physical mechanisms of scale interactions in the Maritime Continent

Abstract:
Speleothem (secondary cave carbonate) is one of the ideal materials to study paleoclimate change. Speleothem oxygen isotope ratio (d18O) has been used extensively in the past two decades to reconstruct climate history. However, little attention has been paid on the spatial distribution of speleothem (d18O) values. We propose that, by reconstructing spatial and temporal transects (“maps”) of speleothem d18O, we can reveal the underlying physical processes of tropical hydroclimate changes. In this talk, I will use speleothem d18O records from three tropical regions, including the Amazon Basin, Mainland Southeast Asia and the Maritime Continent, to demonstrate what we can learn on regional hydroclimate changes by mapping speleothem (d18O).

Speaker Profiles:
Xianfeng Wang is an Associate Professor at the Asian School of the Environment and a Principal Investigator at the Earth Observatory of Singapore, Nanyang Technological University (NTU), Singapore. Before joining NTU, Xianfeng was a Postdoctoral Research Fellow at the Lamont-Doherty Earth Observatory of Columbia University in USA. He obtained his PhD in Geology from the University of Minnesota, USA and received his BSc and MSc in Earth Sciences from Nanjing University, China. Xianfeng is leading an isotope geochemistry laboratory at NTU. He and his team study Earth’s climate and environmental changes by using elemental and isotopic tracers.

Date: 5th Mar 2025, Wednesday (11:00am – 12:00pm)
Presenter: Rajesh Kumar (CCRS)
Topic: cSINGV: A high resolution coupled atmosphere-ocean-wave model for the Western Maritime Continent

Abstract:
The Centre for Climate Research Singapore (CCRS) has developed cSINGV, a high-resolution (1.5 km × 1.5 km) regional coupled modelling system for the Western Maritime Continent (WMC). cSINGV integrates three key components: the SINGV atmospheric model (based on the Met Office Unified Model), the Nucleus for European Modelling of the Ocean (NEMO) general circulation model, and the WAVEWATCH III (WW3) ocean surface wave model. This system captures complex atmosphere-ocean-wave interactions and improves the simulation of key variables, such as precipitation, with a particular focus on diurnal rainfall variability—a defining feature of the WMC. Results indicate that cSINGV improves diurnal rainfall representation and offshore propagation compared to the standalone SINGV model. The coupled model shows strong agreement with satellite-derived rainfall estimates, especially over oceanic regions, compared to its uncoupled counterpart. Additionally, marine model outputs, such as significant wave heights, align well with reanalysis and satellite observations, reinforcing the reliability of the coupled approach. We present an evaluation of cSINGV, highlighting the importance of atmosphere-ocean-wave coupling for improved weather predictions.

Speaker Profiles:
Dr. Rajesh Kumar is a Deputy Principal Research Scientist at the Centre for Climate Research Singapore (CCRS), where he leads the development of regional coupled atmospheric-ocean-wave modelling capabilities, including the high-resolution (1.5 km) cSINGV model for the Singapore region. He holds a Ph.D. in Ocean Engineering and Naval Architecture from the Indian Institute of Technology Kharagpur and has conducted postdoctoral research in coupled atmosphere-wave modelling at Uppsala University, Sweden. He later served as an NSERC Postdoctoral Fellow at Environment Canada, contributing to coupled wave-ocean modelling efforts at the Canadian Meteorological Centre. Before joining CCRS, he worked as a Research Scientist at New York University, where he developed a polar-COAWST model by integrating sea ice model (CICE) within the COAWST framework.

Date: 18th Mar 2025, Tuesday (11:00am – 12:00pm)
Presenter: Duncan Watson-Parris (UCSD)
Topic: Accelerating climate science with machine learning: Earth system emulation

Abstract:
Uncertainties in estimating Earth’s future climate stem from both inaccuracies in our models and the vast array of possible choices that society will make in the intervening years. One of the most pressing uncertainties in climate modelling is that of the effect of anthropogenic aerosol, particularly through their interactions with clouds. Here I will introduce a general earth system emulation framework which leverages advances in machine learning and describe its application to the emulation of entire climate models for the reduction of this uncertainty. I will also demonstrate how such emulation can be used to better approximate the climate response to different pollutants, in their detection and attribution, and in the exploration of different future emissions pathways
.

Speaker Profiles:
Prof. Duncan Watson-Parris is an Asst. Professor at the Scripps Institution of Oceanography and Halıcıoğlu Data Science Institute, UC San Diego. He is an atmospheric physicist working at the interface of climate research and machine learning. The Climate Analytics Lab (CAL) he leads focuses on harnessing novel data science approaches to understand the interactions between aerosols and clouds and improve their representation within global climate models. Duncan is also keen to foster the application of machine learning to climate science questions more broadly and convenes the Machine Learning for Climate Science EGU session and co-convenes the “AI and Climate Science” discovery series that is part of the United Nations’ AI for Good program.

Date: 25th Mar 2025, Tuesday (4:00pm – 5:00pm)
Presenter: Peter Watson (University of Bristol)
Topic: Machine learning-based weather and climate prediction of rainfall extremes

Abstract:
Precipitation prediction at high resolution with realistic spatial structure is necessary to predict climate impacts such as flooding. For many applications, knowledge is needed about events of extreme intensities, with probabilities of occurrence of around 1% per year (~1-in-100 year events) or less. Few studies on applying machine learning for climate applications have considered performance on such rare and intense events, which are especially challenging due to having relatively small numbers of examples to learn from. This presentation will discuss methods to develop and evaluate machine learning-based systems for such events. Results will be included from three case studies: emulating precipitation simulations from a regional convection-permitting model of the UK, super-resolution of tropical cyclone rainfall and post-processing East African weather forecasts. Each case includes demonstrations of skill at simulating precipitation extremes.

Speaker Profiles:
Dr Peter Watson is Senior Lecturer at the School of Geographical Sciences, University of Bristol. His work primarily focuses on understanding the risks posed to society by extreme climate events and how these are being affected by climate change. A key area of his research has been global atmospheric modelling based on physical laws, including contributing to the development of a new model for large-ensemble simulations within the “climateprediction.net” distributed computing project. In recent years, he has led work on developing machine learning tools to enhance the realism of climate simulations, particularly for rainfall. Another significant aspect of his research interests is improving approaches to representing our overall understanding of extreme weather risks, given the major uncertainties about our climate’s behaviour.