Integrated Assessment Research

The goal of the Integrated Assessment Research (IAR) program is to advance scientific understanding of the complex interactions, interdependencies, and co-evolutionary pathways of human and natural systems, including interdependencies among sectors and infrastructures. There is a particular emphasis on understanding the energy-water-land nexus under both realistic and idealized forcing scenarios, including the evaluation of scale-aware processes and probabilistic uncertainties that can lead to instability through thresholds and tipping points. The program additionally considers the role of socio-economics, risk analysis, and complex decision theory, as they pertain to describing the evolution and feedbacks within earth system science.        

Program Description

IAR Workshop Report
Latest IAR sponsored workshop report, centered on an interagency activity involving multi-disciplinary science community input, addresses: Understanding Dynamics and Resilience in Complex Interdependent Systems – Prospects for a Multi-Model Framework and Community of Practice.

The human-Earth system, including settlements, infrastructure, natural resources, socio-economics, and importantly, interdependent sectors and natural systems, is highly complex and continuously changing.   Both strong and weak linkages define the oftentimes non-linear behaviors among components. Stressors, constraints, and other factors affecting change can take many forms and influence the system at varying spatial and temporal scales, oftentimes in unanticipated ways when viewed within the larger system. Consider, for example, the individual and combined effects of changing patterns of weather and its extremes, demographic distributions, economic growth and changes in industrial structure, improvements in technologies (e.g., for producing electricity), depletion of natural resources such as groundwater, or the discovery of new resources or means for resource extraction such as unconventional natural gas, and the evolution of regulatory and other institutional structures. All of these factors influence infrastructures and sectors that in turn can exhibit nonlinear regional responses as part of the earth system.   

One major focus of the IAR program is in understanding the growing interdependencies and risks at the intersection of the energy, water and land sectors. The recent disruptive effects and economic losses associated with the growing intensity, frequency, and persistence of droughts, floods, heat waves, and tropical storms in the United States have highlighted the importance of this research and integrated modeling capability. For example, energy is required for water and wastewater treatment, groundwater pumping, and large-scale inter-basin transfers. Needs, risks, and vulnerabilities of the coupled system are large and growing in the face of shifting weather and precipitation patterns, water supplies that depend on increasingly limited groundwater, transitions in regional economic development (including land use), as well as U.S. population shifts. In contrast, approximately 45% of water withdrawals in America’s rivers and streams are for energy applications, ranging from thermo-electric cooling (e.g., fossil and nuclear power plants) to domestic oil and gas recovery. Hydropower is similarly challenged to respond to increasing competition for limited water supply.

Besides the program focus to understand the system dynamics governing interdependencies within the natural-human system, the program seeks to advance our understanding of system nonlinearity and instability associated with multiple stressors that can lead to cascading failures in connected sectors and systems. An important characteristic of nonlinearity and system failure is the probabilistic interdependence near thresholds associated with extreme weather, severe drought, and infrastructure vulnerability. Consequently, the program supports the development of interoperable tools and methods for integration with agile, flexible earth system modeling frameworks, revealing a basic understanding of different levels of complexity required to analyze interdependency. 

Program Funding Opportunity Announcements

Announcements are posted on the DOE Office of Science Grants and Contracts Website and at Information about preparing and submitting applications, as well as the DOE Office of Science merit review process, is available at the DOE Office of Science Grants and Contracts Website. For current announcements visit BER Funding Opportunities.

The most recently closed Announcement (DE-FOA-0000219) requested applications for a single, coordinated research effort that would: 1) advance progress on a select set of major scientific challenges in the field of Integrated Assessment that are widely recognized and confronting the major Integrated Assessment modeling teams, 2) advance methods and capabilities for inter-model testing and diagnostics, and 3) enhance capabilities for multi-model, "ensemble-like" analyses for improved insights in science studies and science-based analyses.

Why the Program's Research is Important

IAR is necessary to understand the nonlinear science involving natural-human interdependency and feedbacks on the earth system. The program helps shape our fundamental understanding of complex stressors on human systems and infrastructure, vulnerabilities and risks at the energy-water-land nexus, multi-sector dynamics, and more generally, implications for regional and global economic development in the face of changing weather patterns and extremes, advances in technology, availability of natural resources, and feedbacks to natural systems, including regional and global climates.  

Featured Reports

Recent Content

Recent Highlights

This study provides improved quantification of interannual variability (IAV) of power production (AEP) from wind farms over eastern N. America using purpose-performed long-term numerical simulations with WRF. Our analyses indicate it may be appropriate to reduce the IAV applied to preconstruction...
Built a hierarchy of machine-learning models of varying complexity to examine the relative importance of global air temperatures, daily indices of synoptic meteorology & time-averaged soil moisture (SM) to correct characterization of the variability of equivalent potential temperature (θE).
Using year-long high-resolution (4-km) WRF simulations and actual wind turbine (WT) geolocations and aerodynamics we have quantified scale, magnitude & seasonality of the resulting impacts on near-surface climate. Using a Midwest nested domain we show the effects of WT in Iowa on local to...
Using year-long high-resolution (4-km) WRF simulations and actual wind turbine (WT) geolocations and two different approaches to WT aerodynamics we have quantified uncertainty in local/mesoscale climate effects.
We advance new descriptive metrics of wind gusts and their parent probability distributions and lays the foundation for better methods to describe fatigue loading on structures and for downscaling wind gust climates. This research further illustrates substantial departures from the ‘Mexican hat’...


The interannual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in preconstruction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derive in part from variability in wind...
The static energy content of the atmosphere is increasing on a global scale, but exhibits important subglobal and subregional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of the...
Paired simulations are conducted using the Weather Research and Forecasting model applied at convection permitting resolution in order to determine the impact of wind turbines (WTs) on the local to mesoscale climate. Using actual WT locations and a model of the effect of the WT rotor on the flow...
High-resolution regional simulations of the downstream effects of wind turbine arrays are presented. The simulations are conducted with the Weather Research and Forecasting (WRF) model using two different wind turbine parameterizations for a domain centered on the highest density of current wind...
Improved understanding of wind gusts in complex terrain is critically important to wind engineering and specifically the wind energy industry. Observational data from 3D sonic anemometers deployed at 3 and 65 m at a site in moderately complex terrain within the northeastern United States are used...