Publications

Bull, Diana L.; Peterson, Kara J.; Backus, George A.; Hardesty, Jasper O.; Powell, Amy J.; Naugle, Asmeret B.; Hart, William E.

Abstract not provided.

Bull, Diana L.; Backus, George A.; Hardesty, Jasper O.; Naugle, Asmeret B.; Hart, William E.; Brigham, Lawson B.

Abstract not provided.

Ivey, Mark D.; Robinson, David G.; Boslough, Mark B.; Backus, George A.; Peterson, Kara J.; van Bloemen Waanders, Bart G.; Swiler, Laura P.; Desilets, Darin M.; Reinert, Rhonda K.

This study began with a challenge from program area managers at Sandia National Laboratories to technical staff in the energy, climate, and infrastructure security areas: apply a systems-level perspective to existing science and technology program areas in order to determine technology gaps, identify new technical capabilities at Sandia that could be applied to these areas, and identify opportunities for innovation. The Arctic was selected as one of these areas for systems level analyses, and this report documents the results. In this study, an emphasis was placed on the arctic atmosphere since Sandia has been active in atmospheric research in the Arctic since 1997. This study begins with a discussion of the challenges and benefits of analyzing the Arctic as a system. It goes on to discuss current and future needs of the defense, scientific, energy, and intelligence communities for more comprehensive data products related to the Arctic; assess the current state of atmospheric measurement resources available for the Arctic; and explain how the capabilities at Sandia National Laboratories can be used to address the identified technological, data, and modeling needs of the defense, scientific, energy, and intelligence communities for Arctic support.

Backus, George A.; Naugle, Asmeret B.; Bernard, Michael L.; Aamir, Munaf S.; Glickman, Matthew R.; Jeffers, Robert F.; Silva, Austin R.; Trumbo, Derek T.; Verzi, Stephen J.

Abstract not provided.

Naugle, Asmeret B.; Bernard, Michael L.; Backus, George A.; Glickman, Matthew R.; Verzi, Stephen J.

Abstract not provided.

Backus, George A.; Trucano, Timothy G.; Robinson, David G.; Adams, Brian M.; Richards, Elizabeth H.; Siirola, John D.; Boslough, Mark B.; Taylor, Mark A.; Conrad, Stephen H.; Kelic, Andjelka; Roach, Jesse D.; Warren, Drake E.; Ballantine, Marissa D.; Stubblefield, W.A.; Snyder, Lillian A.; Finley, Ray E.; Horschel, Daniel S.; Ehlen, Mark E.; Klise, Geoffrey T.; Malczynski, Leonard A.; Stamber, Kevin L.; Tidwell, Vincent C.; Vargas, Vanessa N.; Zagonel, Aldo A.

Abstract not provided.

Bernard, Michael L.; Backus, George A.; Glickman, Matthew R.; Verzi, Stephen J.

Abstract not provided.

Boslough, Mark B.; Levy, Michael N.; Backus, George A.

Because the potential effects of climate change are more severe than had previously been thought, increasing focus on uncertainty quantification is required for risk assessment needed by policy makers. Current scientific efforts focus almost exclusively on establishing best estimates of future climate change. However, the greatest consequences occur in the extreme tail of the probability density functions for climate sensitivity (the 'high-sensitivity tail'). To this end, we are exploring the impacts of newly postulated, highly uncertain, but high-consequence physical mechanisms to better establish the climate change risk. We define consequence in terms of dramatic change in physical conditions and in the resulting socioeconomic impact (hence, risk) on populations. Although we are developing generally applicable risk assessment methods, we have focused our initial efforts on uncertainty and risk analyses for the Arctic region. Instead of focusing on best estimates, requiring many years of model parameterization development and evaluation, we are focusing on robust emergent phenomena (those that are not necessarily intuitive and are insensitive to assumptions, subgrid-parameterizations, and tunings). For many physical systems, under-resolved models fail to generate such phenomena, which only develop when model resolution is sufficiently high. Our ultimate goal is to discover the patterns of emergent climate precursors (those that cannot be predicted with lower-resolution models) that can be used as a 'sensitivity fingerprint' and make recommendations for a climate early warning system that would use satellites and sensor arrays to look for the various predicted high-sensitivity signatures. Our initial simulations are focused on the Arctic region, where underpredicted phenomena such as rapid loss of sea ice are already emerging, and because of major geopolitical implications associated with increasing Arctic accessibility to natural resources, shipping routes, and strategic locations. We anticipate that regional climate will be strongly influenced by feedbacks associated with a seasonally ice-free Arctic, but with unknown emergent phenomena.

Trucano, Timothy G.; Backus, George A.; Hills, Richard G.

Abstract not provided.

Bernard, Michael L.; Backus, George A.; Glickman, Matthew R.

Abstract not provided.

Boslough, Mark B.; Taylor, Mark A.; Zak, Bernard D.; Backus, George A.

The Arctic region is rapidly changing in a way that will affect the rest of the world. Parts of Alaska, western Canada, and Siberia are currently warming at twice the global rate. This warming trend is accelerating permafrost deterioration, coastal erosion, snow and ice loss, and other changes that are a direct consequence of climate change. Climatologists have long understood that changes in the Arctic would be faster and more intense than elsewhere on the planet, but the degree and speed of the changes were underestimated compared to recent observations. Policy makers have not yet had time to examine the latest evidence or appreciate the nature of the consequences. Thus, the abruptness and severity of an unfolding Arctic climate crisis has not been incorporated into long-range planning. The purpose of this report is to briefly review the physical basis for global climate change and Arctic amplification, summarize the ongoing observations, discuss the potential consequences, explain the need for an objective risk assessment, develop scenarios for future change, review existing modeling capabilities and the need for better regional models, and finally to make recommendations for Sandia's future role in preparing our leaders to deal with impacts of Arctic climate change on national security. Accurate and credible regional-scale climate models are still several years in the future, and those models are essential for estimating climate impacts around the globe. This study demonstrates how a scenario-based method may be used to give insights into climate impacts on a regional scale and possible mitigation. Because of our experience in the Arctic and widespread recognition of the Arctic's importance in the Earth climate system we chose the Arctic as a test case for an assessment of climate impacts on national security. Sandia can make a swift and significant contribution by applying modeling and simulation tools with internal collaborations as well as with outside organizations. Because changes in the Arctic environment are happening so rapidly, a successful program will be one that can adapt very quickly to new information as it becomes available, and can provide decision makers with projections on the 1-5 year time scale over which the most disruptive, high-consequence changes are likely to occur. The greatest short-term impact would be to initiate exploratory simulations to discover new emergent and robust phenomena associated with one or more of the following changing systems: Arctic hydrological cycle, sea ice extent, ocean and atmospheric circulation, permafrost deterioration, carbon mobilization, Greenland ice sheet stability, and coastal erosion. Sandia can also contribute to new technology solutions for improved observations in the Arctic, which is currently a data-sparse region. Sensitivity analyses have the potential to identify thresholds which would enable the collaborative development of 'early warning' sensor systems to seek predicted phenomena that might be precursory to major, high-consequence changes. Much of this work will require improved regional climate models and advanced computing capabilities. Socio-economic modeling tools can help define human and national security consequences. Formal uncertainty quantification must be an integral part of any results that emerge from this work.

Backus, George A.; Strickland, James H.

Globally, there is no lack of security threats. Many of them demand priority engagement and there can never be adequate resources to address all threats. In this context, climate is just another aspect of global security and the Arctic just another region. In light of physical and budgetary constraints, new security needs must be integrated and prioritized with existing ones. This discussion approaches the security impacts of climate from that perspective, starting with the broad security picture and establishing how climate may affect it. This method provides a different view from one that starts with climate and projects it, in isolation, as the source of a hypothetical security burden. That said, the Arctic does appear to present high-priority security challenges. Uncertainty in the timing of an ice-free Arctic affects how quickly it will become a security priority. Uncertainty in the emergent extreme and variable weather conditions will determine the difficulty (cost) of maintaining adequate security (order) in the area. The resolution of sovereignty boundaries affects the ability to enforce security measures, and the U.S. will most probably need a military presence to back-up negotiated sovereignty agreements. Without additional global warming, technology already allows the Arctic to become a strategic link in the global supply chain, possibly with northern Russia as its main hub. Additionally, the multinational corporations reaping the economic bounty may affect security tensions more than nation-states themselves. Countries will depend ever more heavily on the global supply chains. China has particular needs to protect its trade flows. In matters of security, nation-state and multinational-corporate interests will become heavily intertwined.

McNamara, Laura A.; Trucano, Timothy G.; Backus, George A.; Mitchell, Scott A.

Sandia National Laboratories is investing in projects that aim to develop computational modeling and simulation applications that explore human cognitive and social phenomena. While some of these modeling and simulation projects are explicitly research oriented, others are intended to support or provide insight for people involved in high consequence decision-making. This raises the issue of how to evaluate computational modeling and simulation applications in both research and applied settings where human behavior is the focus of the model: when is a simulation 'good enough' for the goals its designers want to achieve? In this report, we discuss two years' worth of review and assessment of the ASC program's approach to computational model verification and validation, uncertainty quantification, and decision making. We present a framework that extends the principles of the ASC approach into the area of computational social and cognitive modeling and simulation. In doing so, we argue that the potential for evaluation is a function of how the modeling and simulation software will be used in a particular setting. In making this argument, we move from strict, engineering and physics oriented approaches to V&V to a broader project of model evaluation, which asserts that the systematic, rigorous, and transparent accumulation of evidence about a model's performance under conditions of uncertainty is a reasonable and necessary goal for model evaluation, regardless of discipline. How to achieve the accumulation of evidence in areas outside physics and engineering is a significant research challenge, but one that requires addressing as modeling and simulation tools move out of research laboratories and into the hands of decision makers. This report provides an assessment of our thinking on ASC Verification and Validation, and argues for further extending V&V research in the physical and engineering sciences toward a broader program of model evaluation in situations of high consequence decision-making.

Backus, George A.; Strip, David R.

As Sandia National Laboratories serves its mission to provide support for the security-related interests of the United States, it is faced with considering the behavioral responses that drive problems, mitigate interventions, or lead to unintended consequences. The effort described here expands earlier works in using healthcare simulation to develop behavior-aware decision support systems. This report focuses on using qualitative choice techniques and enhancing two analysis models developed in a sister project.

Backus, George A.; Strip, David R.; Siirola, John D.; Bastian, Mark S.; Schoenwald, David A.; Braithwaite, Karl R.

This is the final report for a LDRD effort to address human behavior in decision support systems. One sister LDRD effort reports the extension of this work to include actual human choices and additional simulation analyses. Another provides the background for this effort and the programmatic directions for future work. This specific effort considered the feasibility of five aspects of model development required for analysis viability. To avoid the use of classified information, healthcare decisions and the system embedding them became the illustrative example for assessment.

Strip, David R.; Backus, George A.

The need to anticipate the consequences of policy decisions becomes ever more important as the magnitude of the potential consequences grows. The multiplicity of connections between the components of society and the economy makes intuitive assessments extremely unreliable. Agent-based modeling has the potential to be a powerful tool in modeling policy impacts. The direct mapping between agents and elements of society and the economy simplify the mapping of real world functions into the world of computation assessment. Our modeling initiative is motivated by the desire to facilitate informed public debate on alternative policies for how we, as a nation, provide healthcare to our population. We explore the implications of this motivation on the design and implementation of a model. We discuss the choice of an agent-based modeling approach and contrast it to micro-simulation and systems dynamics approaches.

Backus, George A.; Boslough, Mark B.; Taylor, Mark A.; Strickland, James H.

Abstract not provided.

Backus, George A.; Boslough, Mark B.; Strickland, James H.; Taylor, Mark A.

Abstract not provided.

McNamara, Laura A.; Trucano, Timothy G.; Backus, George A.

Since 1998, the Department of Energy/NNSA National Laboratories have invested millions in strategies for assessing the credibility of computational science and engineering (CSE) models used in high consequence decision making. The answer? There is no answer. There's a process--and a lot of politics. The importance of model evaluation (verification, validation, uncertainty quantification, and assessment) increases in direct proportion to the significance of the model as input to a decision. Other fields, including computational social science, can learn from the experience of the national laboratories. Some implications for evaluating 'low cognition agents'. Epistemology considers the question, How do we know what we [think we] know? What makes Western science special in producing reliable, predictive knowledge about the world? V&V takes epistemology out of the realm of thought and puts it into practice. What is the role of modeling and simulation in the production of reliable, credible scientific knowledge about the world? What steps, investments, practices do I pursue to convince myself that the model I have developed is producing credible knowledge?

Boslough, Mark B.; Sprigg, James A.; Backus, George A.; Taylor, Mark A.; McNamara, Laura A.; Murphy, Kathryn M.; Malczynski, Leonard A.

This white paper represents a summary of work intended to lay the foundation for development of a climatological/agent model of climate-induced conflict. The paper combines several loosely-coupled efforts and is the final report for a four-month late-start Laboratory Directed Research and Development (LDRD) project funded by the Advanced Concepts Group (ACG). The project involved contributions by many participants having diverse areas of expertise, with the common goal of learning how to tie together the physical and human causes and consequences of climate change. We performed a review of relevant literature on conflict arising from environmental scarcity. Rather than simply reviewing the previous work, we actively collected data from the referenced sources, reproduced some of the work, and explored alternative models. We used the unfolding crisis in Darfur (western Sudan) as a case study of conflict related to or triggered by climate change, and as an exercise for developing a preliminary concept map. We also outlined a plan for implementing agents in a climate model and defined a logical progression toward the ultimate goal of running both types of models simultaneously in a two-way feedback mode, where the behavior of agents influences the climate and climate change affects the agents. Finally, we offer some ''lessons learned'' in attempting to keep a diverse and geographically dispersed group working together by using Web-based collaborative tools.