Time of Emergence: A Tool for Exploring When and Where Climate Change Could Matter

Abstract:

Communities and government agencies are increasingly seeking to incorporate climate change information into decision-making to identify effective response actions. The Time of Emergence tool presents a new approach to supporting climate change risk assessment and decision-making by identifying the “time of emergence” (ToE) of the climate change signal for a suite of management-relevant variables. Because natural and human systems tend to be somewhat adapted to historical climate fluctuations, it is when climate change causes local conditions to deviate significantly from the past that ecological and societal disruptions may occur. A key input to deciding and prioritizing actions on climate change, therefore, is information about when and where the distinctive trend due to climate change is projected to emerge from the noise of natural climate variability. Although this information can be gleaned from existing climate change scenarios, it has not been explicitly characterized for variables and spatial scales relevant to local decision-making. Various local climate change projections, based on different emission scenarios, global climate models and downscaling methods, increases the difficulty of identifying when and where the effects of climate change could matter.

Using global and statistically-downscaled climate model outputs from the Coupled Model Intercomparison Project phase 5 (CMIP5) and hydrological model results, management-relevant climatic and environmental variables were analyzed for the US Pacific Northwest (PNW). These variables were selected in consultation with federal, state, and local decision-makers and relate to extreme temperature, precipitation and streamflow events. The web-based interactive system enables user visualization and analysis of ToE for multiple variables across the PNW at varying levels of tolerance for change. The tool also enables users to explore the effects of different sources of uncertainty in the results, e.g., due to greenhouse gas emissions, global climate models, downscaling, statistical estimation of emergence. Identified areas of concern can be combined with information about local sensitivities, design standards or critical thresholds to help identify the relative need and priority for climate change adaptation activities.