SPRING 2025
Wednesdays at 3:00 pm, Seminar Room SLAB 103 / Virtual SLAB 103
(unless stated otherwise)
Jan 08 (2:45 pm): Dr. Sophia Brumer
Aerology Laboratory (LAERO), Toulouse, France
Guest of Milan Curcic, Department of Ocean Sciences
On Sub-Mesoscale Air-Sea Interactions in Extratropical Windstorms
Recording Available at COMPASS ON DEMAND
Windstorms associated with extratropical cyclones are destructive natural hazards. We are interested in elucidating the processes involved in the formation of near-surface extreme winds, and my focus is on wave and wave-breaking related processes. Though crucial for their societal impact, these processes are not well understood and too small-scale to be explicitly represented in numerical weather prediction models. Waves modulate air-sea exchanges, mix the upper ocean, and inject sea spray into the atmosphere when breaking. Air-sea fluxes of enthalpy and momentum greatly influence the dynamics of the marine atmospheric boundary layer (MABL). Waves increase the surface roughness but sea spray loading may act as a buffer layer reducing drag and stabilizing the MABL. Larger droplets increase air-sea enthalpy and decrease momentum transfers, thus promoting the intensification of tropical cyclones, but what of extratropical cyclones?
In this talk, I will give an overview of ongoing and planned work at the Laboratoire d'Aérologie (LAERO) in Toulouse, France, on sub-mesoscale ocean-wave-atmosphere interactions in extratropical cyclones. Ongoing work will be illustrated through three case studies: 1) the Mediterranean cyclone Adrian, where sub-mesoscale wind rolls show strong sensitivity to air-sea fluxes; 2) the North Atlantic storm Alex, where wave coupling influences mesoscale jets and the downward momentum transport; and 3) the cold wake producing medicane (Mediterranean Hurricane) Ianos, where the ocean induces a negative feedback similar to that seen in certain tropical cyclones.
Future work aims at establishing a coherent air-sea coupled framework for numerical weather predictions, which includes the impact of waves on roughness, of sea spray on the MABL, and takes into account relative alignment between the wind and wave systems. For this purpose, we are designing realistic coupled simulations with horizontal resolutions approaching those of Large Eddy Simulations. These will allow gauging the scale of impacts of non-resolved and poorly constrained processes, such as sea spray generation and subsequent heat and momentum exchanges within the MABL. Field measurements needed to evaluate these simulations will include the NAWDIC field campaign, which will sample North Atlantic storms over the winter of 2025/2026. Future campaigns in the Mediterranean / Ionian Sea and the south Indian Ocean are also under consideration.
Sophia Brumer is a CNRS researcher specialized in ocean-wave-atmosphere interactions at the Aerology Laboratory (LAERO) in Toulouse, France. She obtained her BSc degree from the University of Miami and her PhD from Columbia University, where she investigated the role of waves and wave breaking on air-sea gas transfer based on shipborne measurements. She then joined the Laboratoire d’Océanographie Physique et Spatiale (LOPS, Brest, France) for a series of postdocs revolving around the role of waves on an ocean tidal temperature front and the impact of sea spray on the marine atmospheric boundary layer using coupled models. Since September 2023, she is at the LAERO where her work seeks to understand and quantify the role of sea state, wave breaking, and sea spray on wind and rain extremes in low-pressure systems.
Jan 15: NO SEMINAR
Jan 22: Dr. Alina Nathanaël Dossa
Department of Ocean Sciences, Rosenstiel School
Global Analysis of Coastal Gradients of Sea Surface Salinity
Recording Available at COMPASS ON DEMAND
Sea surface salinity (SSS) is a key variable for ocean-atmosphere interactions and the water cycle. Due to its climatic importance, increasing efforts have been made for its global in-situ observation, and dedicated satellite missions have been launched more recently to allow homogeneous coverage at higher resolution. Cross-shore SSS gradients can bear the signature of different coastal processes such as river plumes, upwelling, or boundary currents, as we illustrate in a few regions. However, satellite performances are questionable in coastal regions. Here, we assess the skill of four gridded products derived from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellites and the GLORYS global model reanalysis at capturing cross-shore SSS gradients in coastal bands up to 300 km wide. These products are compared with thermosalinography (TSG) measurements, which provide continuous data from the open ocean to the coast along ship tracks. The comparison shows various skills from one product to the other, decreasing as the coast gets closer. The bias in reproducing coastal SSS gradients is unrelated to how the SSS biases evolve with the distance to the coast. Despite limited skill, satellite products generally agree better with collocated TSG data than a global reanalysis and show a large range of coastal SSS gradients with different signs. Moreover, satellites reveal a global dominance of coastal freshening, primarily related to river runoff over shelves. This work shows a great potential of SSS remote sensing to monitor coastal processes, which would, however, require a jump in the resolution of future SSS satellite missions to be fully exploited.
Jan 29: SPECIAL ATM & OCE FACULTY PRESENTATION SERIES
Dr. Mariana Bernardi Bif
Department of Ocean Sciences, Rosenstiel School
From Rosenstiel School to Rosenstiel School: The Path of a Marine Biogeochemist
Leveraging BGC-Argo Data to Constrain Our Changing Oceans
Recording Available at COMPASS ON DEMAND
In this talk, I will begin by sharing my academic journey in oceanography, from starting at a federal university in Brazil to completing the PhD program in Ocean Sciences at the University of Miami's Rosenstiel School. I will then reflect on the lessons learned during six years outside academia at the Monterey Bay Aquarium Research Institute (MBARI), a cutting-edge non-profit research institute specializing in engineering innovations for ocean applications. At MBARI, I focused on developing chemical sensors for BGC-Argo floats and analyzing their global dataset. The deployment of thousands of these robotic floats equipped with chemical sensors in the global oceans is revolutionizing how we study and constrain biogeochemical cycles. To date, this technology has collected more profiles of nitrate – a key nutrient for ocean productivity – than all oceanographic cruises combined. These profiles are gathered at an unprecedented spatiotemporal resolution: every few days and every few meters of depth. I will provide an overview of BGC-Argo floats, the current state of the global array, and the potential of a multi-platform approach to observing marine biogeochemical cycles – particularly in systems sensitive to extreme events. Finally, I will outline my vision for my new role as faculty at the Rosenstiel School, where I will investigate marine systems using BGC-Argo floats and train the next generation of professionals to harness Argo data in combination with other large-scale ocean datasets.
Feb 05: NO SEMINAR
Feb 12: Dr. Yixin "Berry" Wen
Department of Geography, University of Florida, Gainesville
Guest of Brian Mapes, Department of Atmospheric Sciences
Taming AI for Meteorological Research: The Role of Interpretable AI in the AI Era
Recording Available at COMPASS ON DEMAND
As we enter the AI era, domain scientists face a critical question: What can we do to harness AI effectively for scientific discovery? AI has demonstrated remarkable capabilities, from accelerating simulations to uncovering hidden patterns in complex datasets. While these advancements offer unprecedented opportunities, they also raise concerns – AI models often function as "black boxes", making it difficult to connect their outputs to established scientific principles. This lack of interpretability can undermine trust and limit adoption, particularly in fields like meteorology where physical understanding is critical.
In this talk, I will explore how interpretable AI can bridge this gap, highlighting its potential to generate explicit, physically meaningful equations rather than opaque neural networks. Through three case studies from my lab, I will showcase how interpretable AI can enhance scientific understanding:
Satellite Precipitation Retrieval: Using AI-based approaches to interpret precipitation retrieval algorithms from AMSU data, we identified critical microwave channels (89 and 150 GHz) that directly link to physical processes in the atmosphere.
Quantitative Precipitation Estimation (QPE): By applying symbolic regression models to polarimetric radar data, we derived mathematical expressions that outperform traditional Z-R relationships and existing QPE algorithms, offering new insights into rainfall microphysics.
Tornado Probability Prediction: Leveraging reinforcement learning-based symbolic deep learning models, we developed interpretable equations that outperform the traditional Significant Tornado Parameter (STP) index, providing a clearer understanding of the relationships between key atmospheric variables and tornado risk.
Through these examples, I hope to spark discussion on the evolving role of domain scientists in the AI era and inspire new ways to integrate AI with physical understanding in atmospheric research.
Feb 19: NO SEMINAR (SLAB 103 not available)
Feb 26: Elizabeth Yanuskiewicz
Department of Ocean Sciences, Rosenstiel School
(one-hour OCE student seminar)
Sources and Transformation of Particulate Organic Matter
in the North Atlantic Spring Bloom
The transport of particulate organic matter (POM) from the upper ocean to depth dominates carbon export and carbon sequestration. Various mechanisms affect the transport of POM to depth, making it difficult to quantify and accurately model carbon export on a global scale. In May 2021, the EXPORTS (EXport Processes in the Ocean from RemoTe Sensing) program sampled a declining phytoplankton bloom in the North Atlantic to understand the mechanisms controlling carbon export in a productive oceanic environment. Together, amino acids and carbohydrates constitute a major proportion of POM, and these organic compounds can provide information on the sources and transformation of POM. We measured the concentrations of carbohydrate monomers and the concentrations, nitrogen isotope ratios, and carbon isotope ratios of individual amino acids across various particle size classes collected from the surface to mid-mesopelagic (30-500 m) depths and over time during the bloom decline. In the euphotic zone, patterns in the isotope ratios of amino acids indicated that POM derived predominantly from phytoplankton, with specific phytoplankton groups influencing POM composition across the different particle size fractions. This phytoplankton-derived POM was transported from the upper ocean to depth, however, microbial and metazoan-related mechanisms altered POM with increasing depth. Results from this study highlight a significant contribution to sinking POM from microbial reworking / biomass, which is a degradative pathway absent from models.
Mar 05: Hope Elliott
Department of Atmospheric Sciences, Rosenstiel School
(one-hour OCE student seminar)
Mar 12: NO SEMINAR (Spring Recess)
Mar 19: Dr. Lorenzo Polvani
Department of Applied Physics and Applied Mathematics, Columbia University, New York
Guest of Brian Soden, Department of Atmospheric Sciences
Mar 26: Victoria Schoenwald
Department of Atmospheric Sciences, Rosenstiel School
(one-hour ATM student seminar)
Apr 02: Samantha Medina
Department of Ocean Sciences, Rosenstiel School
(one-hour OCE student seminar)
Apr 09: Karen Papazian
Department of Atmospheric Sciences, Rosenstiel School
(one-hour ATM student seminar)
Apr 16: Dr. Milan Curcic
Department of Ocean Sciences, Rosenstiel School
A Theoretical Model for Wave Tearing by Wind
Apr 23: AVAILABLE
