ORNL at AGU 2024

The Environmental Sciences Division is an interdisciplinary R&D organization with more than 60 years of achievement in local, regional, national, and international environmental research. Researchers focus on complex challenges such as clean and available water and ecosystem resilience to disturbances like wildfire. We focus on expanding scientific knowledge and developing innovative strategies and technologies that support economic prosperity, energy security, and national competitiveness while sustaining Earth’s natural resources.

Hydropower accounts for almost 7% of total electricity generation and is the largest source of utility-scale energy storage in the country. With millions of miles of rivers and lakes, the nation stands poised to increase domestic energy production through innovative water power technologies. Oak Ridge National Laboratory research and development activities aim to provide solutions for more reliable, resilient, sustainable, and affordable electric power sources, infrastructure, and systems.

The Next-Generation Ecosystem Experiments project in the Arctic, referred to as NGEE Arctic, seeks to improve the representation of critical environmental processes in Earth system models by focusing on systems that are globally important, vulnerable to changing environmental conditions, and understudied or inadequately represented in models.

NGEE Tropics is pursuing a better understanding of the carbon cycle in tropical forests, and its relation to water and energy exchanges with the atmosphere. A better understanding of complex forest-atmosphere exchange processes can improve Earth system models of these valuable biomes that cycle more carbon, water and energy than any other ecosystem.

The SPRUCE experiment enables the assessment of ecological responses across multiple spatial scales—including microbial communities, moss populations, various higher plant types, and some insect groups—to changing environmental conditions.

The Watershed Dynamics and Evolution Science Focus Area, or WaDE, advances predictive understanding of how dominant processes controlling watershed hydro-biogeochemical function operate under a range of hydrologic regimes and vary along stream networks that drain heterogeneous land covers.

The DOE Urban Integrated Field Laboratories are examining infrastructure and population, severe weather, and other factors affecting cities to help decisionmakers better understand risks and identify resilience opportunities. ORNL is providing its modeling and data expertise to support three Urban IFLs in Southeast Texas, Baltimore, Maryland, and Phoenix, Arizona. 

The ARM Data Center at ORNL collects, manages and makes freely accessible to scientists around the world the global observational and experimental data amassed by the DOE Atmospheric Radiation Measurement user facility. ARM’s archive, supported by ORNL’s high-performance computing capabilities, holds atmospheric measurements that cover remote and urban areas on all seven continents and five oceans, including data on clouds, precipitation, solar and infrared energy, particles in the air, and other environmental elements.

This collaborative DOE project leverages data science, machine learning and advanced modeling to better simulate watersheds at scale, supporting the management and protection of water resources. IDEAS is supported by ORNL computational hydrologists pursuing community-driven software and more accurate models to protect water for drinking, energy production, agriculture and ecosystem health.

FACE-MDS is benchmarking models that predict terrestrial ecosystem responses to atmospheric carbon. Scientists are focused on reasons for the model’s behavior to better understand results. The approach identifies potential science questions for further experimental work, while setting a new standard for model intercomparison. 

COMPASS-GLM is enhancing predictive understanding of freshwater coastal ecosystems in the Great Lakes region, centered around the Portage River Basin in northern Ohio. Scientists are working to analyze coastal system responses to short- and long-term changes in land cover, urbanization, and weather-related disturbance, including local feedbacks to atmospheric lake interactions, lake breeze effects on urban heat islands, and strategies for agricultural sector resilience. 

COMPASS-FME is capturing ecosystem control points across space and time, based on drivers such as sea level rise, lake-level change and extreme events, with the goal of better predictive understanding. The team is currently focused on how flood events propagate through water sediments, soils, microbes and plants to change system states.

Our science—a unique integration of human dynamics, location intelligence, geospatial AI, remote sensing, autonomous systems, resilient communications, and high-performance computing—is transforming how we observe, analyze, and visualize landscape and human dynamics across the world to provide decision-makers with novel insights on human populations, the built environment, and critical infrastructures.

With core strengths in machine learning for high-performance computing, geoassurance, probabilistic reasoning, and spatio-temporal analytics, we are developing geospatial artificial intelligence methods.

Extreme weather events and adversarial cyberattacks pose ongoing threats to our nation’s critical infrastructure, potentially putting human lives at risk. Working with industry and government partners, we leverage ORNL’s resources to create tools that empower infrastructure managers, emergency managers, and resource planners to better understand interdependent critical systems and make them more resilient in case of extreme events or attacks.

For nearly 25 years, ORNL’s Geospatial Science and Human Security Division has delivered annual release of global, ambient, highresolution population counts for estimating population at risk. Our capabilities span planet-level population data, neighborhood and settlement patterns, and building-level population densities— providing a full spectrum of population and human location intelligence to support national security partners and the humanitarian community.

The Computing and Computational Sciences Directorate oversees ORNL’s immense store of computing power and its talented staff of computational scientists and mathematicians, conducting state-of-the-art research and development in support of the Department of Energy's missions and programs. The directorate houses the Oak Ridge Leadership Computing Facility, home to the world's first exascale supercomputer, Frontier, as well as the Quantum Science Center and the laboratory’s AI Initiative.

Exascale is the next level of computing performance. By solving calculations more than five times faster than today’s top supercomputers— exceeding a quintillion, or a billion billion, calculations per second—exascale systems will enable scientists to develop critically needed technologies for energy, medicine, materials, and more. The Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory is home to America’s first exascale system, the 2 exaflops HPE Cray EX Frontier supercomputer.

ORNL has a rich tradition of AI research, which dates back more than 40 years and has garnered more than 10 patents. The laboratory’s AI Initiative is dedicated to ensuring safe, trustworthy, and energy efficient AI in the service of scientific research and national security. Through this internal research investment, subject matter experts at ORNL leverage the laboratory’s computing infrastructure and software capabilities to expedite time-to-solution and realize the potential of AI in projects of national and strategic importance.

As Earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation, analysis, and diagnosis of model results. The Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Science Focus Area develops and applies new hypothesis-driven diagnostic approaches for evaluating ESM representations of biogeochemical and hydrological processes at site, regional, and global scales.

The Earth System Grid Federation 2 - US (ESGF2-US) is an advanced data system designed to support global climate research by providing researchers easy access to the full collection of international Earth system models. ESGF2-US ensures that scientific investigation is transparent, collaborative, and reproducible. Data from the system informs special reports that support global initiatives to address environmental challenges.

The Energy Exascale Earth System Model (E3SM) is a high-resolution climate model developed to simulate the complex interactions within the Earth’s climate system. E3SM helps researchers anticipate changes that will critically impact the U.S. energy sector, analyzing factors such as regional temperatures, water availability, sea-level rise and extreme events like floods and droughts, electric grid reliability, and effects on power plants, bioenergy, and infrastructure.