Abstract
Scenario planning has emerged as a widely used planning process for resource management in situations of consequential, irreducible uncertainty. Because it explicitly incorporates uncertainty, scenario planning is regularly employed in climate change adaptation. An early and essential step in developing scenarios is identifying “climate futures”—descriptions of the physical attributes of plausible future climates that could occur at a specific place and time. Divergent climate futures that describe the broadest possible range of plausible conditions support information needs of decision makers, including understanding the spectrum of potential resource responses to climate change, developing strategies robust to that range, avoiding highly consequential surprises, and averting maladaptation. Here, we discuss three approaches for generating climate futures: a Representative Concentration Pathway (RCP)-ensemble, a quadrant-average, and an individual-projection approach. All are designed to capture relevant uncertainty, but they differ in utility for different applications, complexity, and effort required to implement. Using an application from Big Bend National Park as an example of numerous similar efforts to develop climate futures for National Park Service applications over the past decade, we compare these approaches, focusing on their ability to capture among-projection divergence during early-, mid-, and late-twenty-first century periods to align with near-, mid-, and long-term planning efforts. The quadrant-average approach and especially the individual-projection approach captured a broader range of plausible future conditions than the RCP-ensemble approach, particularly in the near term. Therefore, the individual-projection approach supports decision makers seeking to understand the broadest potential characterization of future conditions. We discuss tradeoffs associated with different climate future approaches and highlight suitable applications.
Highlights
Resource management planning in the face of rapid anthropogenic climate change is fundamentally challenging due to irreducible uncertainties in climate projections and responses by ecological and social systems
Given the multitude of global climate models (GCMs) projections, here we review three approaches to capture the range of projections with a more tractable set of representative CFs
The quadrant and individual-projection approaches begin by plotting deviations of projected climate metrics from a historical-period average, with each point representing a projection from a GCM-Representative Concentration Pathway (RCP) combination (Fig. 2c, d)
Summary
Resource management planning in the face of rapid anthropogenic climate change is fundamentally challenging due to irreducible uncertainties in climate projections and responses by ecological and social systems In this planning environment, a decision maker’s goal is often to minimize failure, rather than maximize success. This goal applies especially to avoiding costly and often catastrophic “surprises” (negative outcomes that were not considered; Terando et al 2020) driven by climate change and complex interactions between nature and humans (Kopp et al 2017) In these circumstances, scenario planning has emerged as a widely used planning process that acknowledges and incorporates this uncertainty and provides a way to identify and avoid potential surprises (Brekke et al 2009a; Gross et al 2016; Lempert et al 2003; Peterson et al 2003; Star et al 2016). Many climate assessments have relied on RCP-based scenarios (Jantz et al 2016; Monahan et al 2013; Ryan et al 2020; van Hooidonk et al 2015; Whitlock et al 2017)— including those conducted to support US National Park Service (NPS) resource
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