FEMA asteroid impact tabletop exercise simulations
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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.
Procedia Engineering
We describe the computational simulations and damage assessments that we provided in support of a tabletop exercise (TTX) at the request of NASA's Near-Earth Objects Program Office. The overall purpose of the exercise was to assess leadership reactions, information requirements, and emergency management responses to a hypothetical asteroid impact with Earth. The scripted exercise consisted of discovery, tracking, and characterization of a hypothetical asteroid; inclusive of mission planning, mitigation, response, impact to population, infrastructure and GDP, and explicit quantification of uncertainty. Participants at the meeting included representatives of NASA, Department of Defense, Department of State, Department of Homeland Security/Federal Emergency Management Agency (FEMA), and the White House. The exercise took place at FEMA headquarters. Sandia's role was to assist the Jet Propulsion Laboratory (JPL) in developing the impact scenario, to predict the physical effects of the impact, and to forecast the infrastructure and economic losses. We ran simulations using Sandia's CTH hydrocode to estimate physical effects on the ground, and to produce contour maps indicating damage assessments that could be used as input for the infrastructure and economic models. We used the FASTMap tool to provide estimates of infrastructure damage over the affected area, and the REAcct tool to estimate the potential economic severity expressed as changes to GDP (by nation, region, or sector) due to damage and short-term business interruptions.
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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.
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.
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We summarize the results of a project to develop evolutionary computing methods for the design of behaviors of embodied agents in the form of autonomous vehicles. We conceived and implemented a strategy called graduated embodiment. This method allows high-level behavior algorithms to be developed using genetic programming methods in a low-fidelity, disembodied modeling environment for migration to high-fidelity, complex embodied applications. This project applies our methods to the problem domain of robot navigation using adaptive waypoints, which allow navigation behaviors to be ported among autonomous mobile robots with different degrees of embodiment, using incremental adaptation and staged optimization. Our approach to biomimetic behavior engineering is a hybrid of human design and artificial evolution, with the application of evolutionary computing in stages to preserve building blocks and limit search space. The methods and tools developed for this project are directly applicable to other agent-based modeling needs, including climate-related conflict analysis, multiplayer training methods, and market-based hypothesis evaluation.
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.