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Publication Date
10 October 2023

Six EESM Scientists Receive DOE Early Career Awards


The U.S. Department of Energy (DOE) recently announced the selection of 93 scientists from across the nation to receive funding for research as part of the DOE Office of Science’s Early Career Research Program.

“Supporting America’s scientists and researchers early in their careers will ensure the United States remains at the forefront of scientific discovery,” says U.S. Secretary of Energy Jennifer M. Granholm. “The funding announced today gives the recipients the resources to find the answers to some of the most complex questions as they establish themselves as experts in their fields.”

The projects of six awardees concentrate on research emphases of DOE’s Earth and Environmental Systems Modeling (EESM) program. Research will address coastal-urban regions of the United States, home to 128 million people—about 40 percent of the nation’s total population. These regions are disproportionately affected by changing earth systems. The six EESM awards will focus on a key DOE Biological and Environmental Research (BER) program Grand Challenge by simulating coastal-urban systems with an emphasis on the natural and human-mediated components on the coastal-urban environments.

Awarded projects are connected to two EESM program areas, Earth System Model Development (ESMD) and Regional & Global Model Analysis (RGMA). The six awardees include:

Brus’ research project, “Assessing Climate Impacts on Coastal-urban Flooding Through High-resolution Barotropic and Baroclinic Ocean Coupling,” seeks to bridge the divergent scales between the global climate drivers of sea level rise and the local coastal impacts of extreme events within the Energy Exascale Earth System Model (E3SM) by unifying two classes of models: Earth system models (ESM) and barotropic coastal flooding models. By extending the mode-splitting approaches that ESM ocean models currently use to separate fast, barotropic free-surface waves from slower, density-driven baroclinic flow, E3SM will be able to resolve coastal-urban flooding processes due to sea level rise, tides, and storm surge in long-term climate simulations. This will enable comprehensive studies of the effects of climate change on extreme water levels in coastal-urban systems.

Chakraborty’s research project, “A Planetary-Scale Data-Model Integration Framework to Resolve Urban Impacts Across Scales and Examine Weather Extremes over Coastal U.S. Cities,” aims to develop a globally consistent data–model integration framework for E3SM to resolve urbanization and its feedbacks to the atmosphere across multiple spatial and temporal scales with a focus on coastal U.S. cities. This project will work to not only develop an advanced urban parameterization for the next generation of ESMs but also generate tools and data sets that can better assess and advise climate adaptation and mitigation strategies as society prepares for a warmer and more urban future.

Fiorella’s research project, “Probing Water Cycle Processes and Extremes in Coastal and Urban Environments Using Water Isotope Ratio Tracers and Numerical Tags,” will develop a comprehensive water tracking system throughout E3SM. This effort is motivated by a need for ESMs that can represent coastal systems in detail to better understand the risk to and resilience of coastal cities arising from climate change and increased urbanization. By connecting this new tracking system to existing capabilities, the enhanced E3SM can be used to study coastal change, extreme event susceptibility, and urbanization impacts on precipitation and flooding and for potential solutions to increase coastal city resilience. E3SM simulations will be conducted in both idealized coastal-urban settings and will include a case study of Houston, Texas, using data from the Atmospheric Radiation Measurement (ARM) user facility’s TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign.

Lu’s research project, “Integrating Machine Learning Models into E3SM for Understanding Coastal Compound Flooding,” addresses the need to improve understanding and simulation of backwater effects and mitigate the induced floods—a need escalating with increasing coastal development, population growth, and vulnerability of infrastructure to floods. Lu’s work will help fill modeling gaps in coastal-urban regions by extracting information from multi-source, multi-type data. It will develop mesh-free, data-informed, and physics-embedded river models using machine learning methods; and it will couple the river model with E3SM land and ocean models to advance predictive understanding of coastal compound flooding under climate change. Ultimately, the project aims to improve understanding of feedbacks and interactions of extreme events at coastal-urban systems, enhance E3SM capabilities in simulating coastal compound floods with uncertainty quantification, and inform urban planning to mitigate the impact of climate change on communities, infrastructures, and economy.

Moriarty’s research project, “Improving Predictability of Aqueous Coastal Biogeochemistry During Floods, Storms and a Warming Climate,” will combine process-based and statistical machine learning modeling to address the challenge of modeling hydro-biogeochemistry during extreme events in coastal-urban waterways. It will also analyze how floods of coastal infrastructure impact pollutant and nutrient fluxes to local waterways—and their impact on estuarine biogeochemical processes—on subseasonal timescales (days to a couple of months) in modern-day and future climates.

Zheng’s research project, “Using Kilometer-Scale E3SM to Investigate Air Pollution Impacts on Coastal Storms,” will use DOE’s Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) within a hierarchical modeling framework to assess the magnitude of the aerosol invigoration effect on coastal storms and gain a mechanistic understanding of the impacts. A series of observation-informed numerical experiments will be performed to evaluate the fidelity of SCREAM in reproducing observed coastal storms, elucidate the physical mechanisms behind the invigoration effect, and examine how large-scale dynamics modulate this phenomenon. These modeling activities will improve the predictability of coastal-urban systems by advancing a fundamental understanding of air pollution impacts on coastal storms and establishing a well-tested analysis framework for guiding the development of DOE high-resolution models.

The DOE Office of Science’s Early Career Research Program is designed to strengthen the nation’s scientific workforce by supporting exceptional researchers at the outset of their careers—when many scientists do their most formative work.

To be eligible for Early Career Research Program awards, a researcher must be an untenured, tenure-track assistant or associate professor at a U.S. academic institution or a full-time employee at a DOE National Laboratory who received a PhD within the past 12 years.

Funding Program Area(s)