FALL 2024
Fridays at 11:00 am, Rosenstiel School Auditorium / Virtual Auditorium
Aug 23: NO SEMINAR
Aug 30: NO SEMINAR
Sep 06 (11:15 am, Zoom): Dr. Chandra Venkataraman
Department of Chemical Engineering, Indian Institute of Technology Bombay
Guest of the Department of Chemical, Environmental, and Materials Engineering, College of Engineering,
and the Department of Atmospheric Sciences, Rosenstiel School, University of Miami
Rapid Climate and Clean Air Action in India:
Crucial Emission Sectors and Interventions
Presented at the Law School Auditorium, Room E352
Click to Request Link to Zoom Recording
There is wide agreement on the abatement of greenhouse gas emissions as key to tackling long-term climate change. Less known is the growing scientific evidence for action on short lived climate pollutants (SLCPs), which are responsible for about 45% of present-day global warming. Addressing SLCPs can deliver rapid climate and clean air benefits. This talk will present research evidence linking human activity to the emissions and impacts of carbonaceous aerosols, a key class of SLCPs, on climate and air quality in India. These findings are from the multi-institutional pan-India COALESCE network. Intrinsic aerosol chemical and optical properties will be discussed, vis-à-vis their net cooling or warming nature. A multi-scale emission inventory management system, the Speciated Multi-pollutant Generator (SMoG)-India-COALESCE, with new calculators underpinned by the largest yet primary datasets from pan-India field surveys and field emission factor measurements will be presented. Measurements and modeling evidence will be used to identify source-sectors significantly influencing levels of PM2.5 levels and its climate relevant carbonaceous constituents. The control of air pollution relies heavily on the phase-out of solid fuel combustion. A key question relates to prioritizing interventions, between formal or regulated economic sectors (coal for energy generation and industry) and informal sectors (biomass for residential energy and waste disposal). The talk will emphasize equity and sustainable development at the core of key interventions for delivering both climate and clean-air benefits in India.
Chandra Venkataraman is the Shobha Dixit Chair Professor of Chemical Engineering and Climate Studies at the Indian Institute of Technology Bombay. Her research focuses on the intersection of technology and emissions, aerosol science, climate science, and air pollution. Prof. Venkataraman has built academic and research programs to further climate and air quality studies in South Asia. She was the Founding Head of the Centre for Climate Studies, IIT Bombay, and National Coordinator for the multi-institutional COALESCE network of the Indian Ministry of Environment. Prof. Venkataraman has contributed to policy networks globally and is a member of the Science Advisory Panel of the Climate and Clean Air Coalition of the UNEP. She has authored over 150 widely cited publications, a book, and four patents. She is a fellow of the Indian National Academies of Science and Engineering and recipient of a Fulbright-Nehru Fellowship, the PRL Vikram Sarabhai Award, and teaching and research excellence awards at IIT Bombay. Prof. Venkataraman has strongly mentored students to academic and research positions worldwide. She has worked to address institutional systems to support the advancement of women in STEM.
Sep 13: NO SEMINAR
Sep 20: NO SEMINAR
Sep 27: Dr. Yair Cohen
NVIDIA Research, Santa Clara, CA
Guest of the Department of Atmospheric Sciences, Rosenstiel School
Recent Advances in Applying Machine Learning to Weather Modeling
at NVIDIA and Beyond
Recent years have witnessed a paradigm shift in weather and climate prediction, driven by rapid advancements in Machine Learning (ML). The application of cutting-edge ML architectures such as transformers, Fourier neural operators, and diffusion models to train on state-of-the-art, data-assimilating weather products has shown remarkable promise. As major meteorological institutions like NOAA and ECMWF incorporate ML-based forecasts into their daily operations, these methods are poised to revolutionize weather modeling in several ways. On the global scale, ML models trained on ERA5 reanalysis data (~25 km resolution) have demonstrated forecast skills rivaling those of operational numerical models, while offering an unprecedented four-orders-of-magnitude speedup. This breakthrough unlocks new possibilities for large ensemble forecasts, potentially enhancing our ability to quantify uncertainties and predict extreme events with greater accuracy. Recent research has explored coupling these weather models with parsimonious ocean models, aiming to extend forecast skill beyond the medium range and bridge the gap between weather and seasonal prediction. Concurrently, on regional scales, ML-based downscaling approaches have shown remarkable promise in super-resolving and forecasting kilometer-scale cloud properties, such as radar reflectivity. These downscaling techniques represent a crucial step towards the operational deployment of global ML forecasts. The inherent stochasticity of atmospheric processes at these fine scales necessitates the use of advanced generative ML methods, capable of capturing the probabilistic nature of local weather phenomena. Ultimately, the potential of better and more adaptive, ML-based data assimilation techniques highlights the potential of such models to surpass the skill of their numerical counterparts.
This talk will present a comprehensive overview of recent advancements in ML weather modeling, focusing on three key areas. First, I will present recent works on Ensemble Forecasting using global ML models, discussing their successes challenges and potential pitfalls, biases, and strategies for mitigation. Second, I will discuss two recent weather downscaling works that used generative ML models for regional forecasts. Third, I will discuss the possibility of using generative ML methods (diffusion models) for data assimilation. The presentation will highlight key findings from several groundbreaking studies conducted at NVIDIA and other leading institutions in the field. By synthesizing these recent developments, we aim to provide a comprehensive view of the current state of ML applications in weather and climate science, and offer insights into how these technologies are poised to transform our forecasting capabilities in the near future.
Some relevant publications can be found here:
https://arxiv.org/pdf/2401.15305
https://arxiv.org/abs/2408.03100
https://www.arxiv.org/abs/2408.01581
https://arxiv.org/abs/2309.15214
https://d1qx31qr3h6wln.cloudfront.net/publications/StormCast.pdf
https://arxiv.org/abs/2406.16947
Oct 04: NO SEMINAR
Oct 11: Dr. Claire Paris-Limouzy
Department of Ocean Sciences, Rosenstiel School
A Coupled ESM-Lagrangian Modeling Framework for Quantifying the Exposure
to Solar Radiation in Biotic and Abiotic Particles Moving in the Ocean
Recording Available at COMPASS ON DEMAND
Sunlight irradiance is a source of energy for life on Earth but it can also be a stressor at high doses of UV radiation. Solar radiations also affect chemical pollutants by enhancing the photooxidation of oil and increasing the fragmentation and photodegradation of plastics in the ocean. Irradiance varies spatially, temporally, and with water bio-optical characteristics and is expected to increase with the climate crisis. To better manage solar radiation and predict its effects with climate change, we need to understand how light-related processes affect the ocean ecosystems. The first step is quantifying radiation exposure on living and non-living particles. So far, current irradiance exposure estimates have neglected the advection by the ocean and the movement of particles due to their biological or physicochemical traits. Here we present a novel Irradiance Module developed to quantify the cumulative UV radiation exposure on active particles. The module coupled the open-source Connectivity Modeling System (CMS) to the net surface shortwave radiations from the NAVy Global Environment Model (NAVGEM). Case scenario simulations of zooplankton and microplastics in the global ocean show that the cumulative doses of irradiance received by particles are primarily determined by their 3D pathways rather than by the irradiance reaching the ocean’s surface. With the particles' motion behavior overlooked, the fine scale light-related processes affecting them remains invisible. Several biological, chemical, and physical applications may emerge from this solar irradiance modeling framework.
Claire Paris, professor in the Department of Ocean Sciences of the University of Miami's Rosenstiel School of Marine, Atmospheric, and Earth Science, is a biological oceanographer with interdisciplinary expertise in marine ecology and Lagrangian dynamics. She specializes in the dispersion and fate of larvae and marine pollutants and has developed innovative Lagrangian approaches designed to track inertial particles at sea. Paris has expertise in modeling deep-sea oil spills and served as Lead PI for oil-spill modeling research for the Gulf of Mexico Research Initiative (GOMRI) C-IMAGE Consortium. She served as President of the Early Life History section of the American Fishery Society (AFS), is the 2018 recipient of the prestigious American Geophysical Union (AGU) Rachel Carson Lecturer Award, and is appointed to the Ocean Research Advisory Panel. Paris is regarded as an authority on marine dispersal, as evidenced in her 36 keynotes and invited talks, 138 peer-reviewed publications, and 34 book chapters, and Editor of two Deepwater Horizon Legacy Springer books. Claire Paris has a B.Sc. in Biochemistry from the University of Bordeaux, France, an M.Sc. in Biology and Living Resources from the University of Miami, and a Ph.D. in Coastal Oceanography from the State University of New York (SUNY) at Stony Brook, USA.
Oct 18: Dr. Abhishek Savita
Department of Atmospheric Sciences, Rosenstiel School
Impact of Multidecadal Climate Modes' Variability on the European Climate
in the Recent Decades
Recording Available at COMPASS ON DEMAND
Pronounced negative trends in wintertime surface temperature have been observed over Eurasia during 1993-2013. However, it is unclear whether the negative trends were due to internal atmospheric variability or forced externally from either the ocean surface, solar forcing, or atmospheric composition. In this study, we use ensembles of atmosphere-model integrations for the period 1993-2013 to investigate the mechanisms of the wintertime cooling over Eurasia. We find that the cooling was mostly driven by intrinsic atmospheric variability, specifically the North Atlantic Oscillation (NAO), and to a lesser extent by multidecadal ocean variability such as the Interdecadal Pacific Variability (IPV) and Atlantic Multidecadal Variability (AMV). A dominant role for atmospheric variability as shown by our results implies limited predictability of decadal climate variability over Eurasia.
Oct 25: NO SEMINAR (Rosenstiel School Faculty Meeting)
Nov 01: SPECIAL ATM & OCE FACULTY PRESENTATION SERIES
Dr. Tamay Özgökmen
Department of Ocean Sciences, Rosenstiel School
The Motion of the Ocean at Submesoscales
I will review the main scientific basis, approach, and results from 10-year project CARTHE, which was funded in the aftermath of the Deepwater Horizon oil spill in the Gulf of Mexico. In addition, recent research projects that span out of this project will also be introduced.
Nov 08: STUDENT SEMINARS
Victoria Pizzini (ATM)
Tyler Tatro (ATM)
James Christie (ATM)
Nov 15: STUDENT SEMINARS
Aidan Mahoney (ATM)
Caitlin Martinez (ATM)
Eric Mischell (ATM)
Nov 22: Dr. John van Leer
Department of Ocean Sciences, Rosenstiel School (retired)
Nov 29: NO SEMINAR (Thanksgiving Recess)