Weather is the state of a region’s atmosphere at a given time; it encompasses variations (e.g., in temperature, moisture, wind speed and direction, and barometric pressure) over short time periods (hours or weeks). Climate is typical weather conditions over longer periods: how frequently will specific states of the atmosphere, ocean, and land occur?
Climate science examines these relatively long-term patterns, using data from environmental sensors and numerical models of the climate to predict temperature and precipitation, circulation patterns, and ocean and biosphere conditions at the global and more local scales.
Argonne leverages its solid Earth System Science program funded by the U.S. Department of Energy (DOE) to provide the most advanced and up-to-date science to benefit collaborations with private and public entities. Collaborations with world-renowned academic institutions extend the impact of its climate science programs.
For example, Argonne operates one of the three DOE Atmospheric Radiation Measurement (ARM) user facilities (Southern Great Plains Facility) and participates in a number of observational studies around the world that study the broad range of climate conditions. These facilities advance our understanding of cloud, aerosol, precipitation, and radiative processes and provide the data to better represent these phenomena in global-scale models.
Argonne also conducts high-resolution (12 km and 4 km) climate forecast modeling using the Weather Research and Forecasting (WRF) model – a community model based at NCAR – to develop climate projections at spatial scale that are not currently feasible with Global Climate Models (GCM).
Earth supports a breathtaking range of geographies, ecosystems, and environments, each with an equally impressive array of constantly shifting weather patterns and events. Predicting these patterns — and extending those predictions to project longer-term climate patterns — can be extremely challenging.
Argonne uses high-performance computing tools to develop advanced, physics-based models of the Earth’s climate and applies artificial intelligence to analyze large datasets and create visualizations of the results. We leverage the expertise, resources, and facilities from across the Laboratory, using advanced geospatial capabilities to geo-reference models that can be used to support science-based decision making.
The simulations Argonne develops can capture the most detailed dynamics of climate-generating behavior — from the transport of heat through ocean eddies to the formation of storms in the atmosphere.
Argonne is one of seven DOE national laboratories working to advance a high-performance Earth system model designed to work on exascale computers.
Argonne also conducts high-resolution (4 km) climate forecast modeling using the Weather Research and Forecasting (WRF) model to improve accuracy in climate projections, especially in areas of complex geographical terrains.
Environmental Science & Modeling
Extreme storm surge is devastating coastal communities, and more severe wildfire seasons in the western United States are destroying communities and infrastructure, resulting in substantial economic losses, social stresses, environmental destruction, and loss of life. Ongoing sea level rise, storm surge from increased hurricane activity, and greater inland rainfall lead to uncertainty in forecasting and projecting both coastal and inland flooding.
Argonne’s hydrologists and environmental modeling experts focus on modeling local intense precipitation, stream and river flooding, dam failure, and coastal flooding. They are pioneering an approach that could facilitate dynamic high-resolution coastal flooding projections using inputs from atmosphere and ocean circulation models.
Argonne is also developing an innovative scientific approach to assessing future wildfire activity under changing climate conditions, calculating the most commonly used fire index using high-resolution (4-km), high-quality observation data for the last 40 years and projections for the future using dynamically downscaled climate model results. Their dataset demonstrates geographical and seasonal variations in the estimated wildfire danger and risk potential based on the changing conditions over the United States.
Infrastructure systems are complex, interconnected, and distributed networks that integrate both physical and cyber components. Disruption to infrastructure poses risks to the public health and safety of communities, national security, and economic prosperity.
Building on world-class infrastructure assessment capabilities powered by high-performance computing and informed by subject matter experts, Argonne researchers are integrating advanced system modeling, prioritization algorithms, database development and interdependency data analytics to deliver a toolset that allows our partners to anticipate, respond to, adapt to, and recover from infrastructure disruptions, such as those during extreme weather events.
Argonne’s DISrupt approach identifies infrastructure assets that carry the potential to propagate cascading impacts across interdependent infrastructure systems, helping to pinpoint high-priority failure points, such as interconnected coastal infrastructure increasingly vulnerable to major weather events or electric grid systems vulnerable to increasing wildfire activity. The ability to identify these potential failure points within and across infrastructure sectors provides essential information for managing risk.
Emergency & Disaster Analysis
The global community is experiencing disasters of increasing complexity, intensity, and frequency. Urbanization, rapid population growth, climate change, and new technologies all influence the global risk landscape.
Argonne assists emergency managers, planners, and responders in preparing for, responding to, and recovering from natural disasters and other incidents. Our researchers apply comprehensive and multidisciplinary assessment, doctrine development, and planning processes grounded in decades of experience. These processes help emergency planners assess multi-jurisdictional capabilities, anticipate response bottlenecks and breakdowns, understand how people behave in emergencies, and identify ways to enhance resilience.
Our capabilities are especially useful for complex, interactive problems, such as protective action decision making, disaster supply chains, and utility restoration. Argonne is a national leader in developing emergency exercise methods and tools, such as those used to prepare for extreme weather events.The Public Affairs Science and Technology (PAST) Fusion Center integrates social scientists and emergency managers to provide training focused on identifying effective communication strategies during these events.
Social, Behavioral & Decision Science
National and global security issues involve countless complex, interdependent systems that feature myriad political, economic, operational, environmental, technological and behavioral inputs.
Argonne develops and applies innovative modeling strategies to address pressing national challenges in decision science and analysis based on sociological influences and the behavioral dynamics of communities. Our decision science experts employ powerful multidisciplinary analytical expertise and computing resources toward understanding complex social systems, characterizing how they interact and predicting their performance under future conditions. For example, Argonne scientists modeled the spread of COVID19 across communities to aid state and local decision makers in response planning and management.
Our team approaches complex problems as dynamic and interrelated systems to address uncertainty, rapidly changing environments, and imperfect or incomplete data. We apply novel methods for agent-based modeling, complex adaptive system modeling, system dynamics, and complex network analysis to facilitate decision making. We leverage high-performance computing resources, such as those available at the Argonne Leadership Computing Facility, to create software tools that broaden the applicability of and access to modeling and simulation.