Climate and Related Uncertainties Influencing Research and Development Priorities

Abstract

Sources of risk and uncertainty are key drivers of R&D priorities for infrastructure assets, projects, and policies. This paper describes risk factoring, which is a quantification of which climate and other diverse factors most influence the priorities of large industry and government facilities. The uncertainties addressed herein include temperature, storm intensity and frequencies, precipitation, coastal populations, sea--level rise, other environmental stressors, and factors deemed relevant by agency stakeholders. This process engages planners in four aspects: (i) a baseline multicriteria decision analysis of agency mission priorities; (ii) building of scenarios from uncertain factors including sea rise, storm frequency, erosion, land--use regulation, ecology, hydrology, etc.; (iii) priority evaluation of agency initiatives including projects, assets, geographical zones, policies, follow on studies, etc.; and (iv) concept for elicitation that supports dialogue in adaptive iterations. The results of the process have implications for a research and development roadmap for environment and ecology and other external stressors that impact the resilience of large-scale systems. The roadmap benefits from understanding which factors and combinations Headquarters 441 G St NW Washington, DC 20314 of factors are demonstrating relatively greater needs of additional investigation and modeling.

Resilience Analytics of a Future Supply Chain for Aviation Biofuels

“…Scenario-based preference analysis has been suggested for prioritizing research and development needs (25). This methodology is founded on two analytical techniques: (a) multicriteria analysis for strategic decision making and (b) scenario analysis for investigating the impact of changing conditions on priorities.…”

Stress tests for a road network using fragility functions and functional capacity loss functions

“…For example, Li, Yu [5] and Mercier, Crozet [6] applied stress tests to estimate the sufficiency of network flow capacities and changes in mobility behavior. Furthermore, Lambert, Tsang [7], You, Connelly [8], Hamilton, Lambert [9] and Thorisson, Lambert [10] applied various types of stress tests to:…”

Rule-Based Filtering of Risk Scenarios by the Disruption of Management Priorities

“…In volatile regions of the world "deep" uncertainties, without reliable knowledge of probability and severity, and changeable societal and governance conditions call for special consideration. Hamilton et al (2015) address the above challenge with scenario-based preferences though with impractical requirements of stakeholder input and with strong assumptions about the underlying form of stakeholder preferences.…”

“…The quantification of disruptiveness is useful in filtering sources of risk. The method has been successfully applied to energy security (Hamilton et al, 2012;, development of a biofuel industry (Connelly et al, 2015), disaster management (Lambert et al, 2013;Parlak et al, 2012), and impacts of climate change to infrastructure investment (Hamilton et al, 2015;You et al, 2014;.…”

“…This is especially true in the case in this thesis, since for scenarios sc2-sc6, the rules used for the prioritization correlate the scenario priorities to baseline priorities. In previous research addressing the disruption of scenarios to priorities (Connelly et al, 2015;Hamilton et al, 2015;Thekdi & Lambert, 2014) the prioritization of initiatives is developed by the usage of a linear additive value function (Keeney & Von Winterfeldt, 2011;Keeney, 2007). Weights are assigned to the criteria, and the impact assessments, significant and marginal (or similar), are quantified.…”