A Framework for Climate Change-Related Research to Inform Environmental Protection.

A critical charge for science to inform environmental protection is to characterize the risks associated with climate change, to support development of appropriate responses. The nature of climate change, however, presents significant challenges that must be overcome to do so, including the need for integration and synthesis across the many disciplines that contain knowledge relevant for achieving environmental protection goals. This paper describes an interdisciplinary research framework organized around three "Science Challenges" that directly respond to the needs of environmental protection organizations. Broadly, these Science Challenges refer to the research needed to: inform actions to enhance resilience across a broad range of environmental and social stresses to environmental management endpoints; actions to limit GHG emissions and slow the underlying rate of climate change; and the transition to sustainability across the full spectrum of climate change impacts and solutions; all as situated within an overarching risk management perspective. These Challenges span all media and systems critical to effective environmental protection, highlighting the cross-cutting nature of climate change and the need to address its impacts across systems and places. While this framework uses EPA's programs as an illustrative example, the research directions articulated herein are broadly applicable across the spectrum of environmental protection organizations. Going forward, we recommend that climate-related research to inform environmental protection efforts should accelerate its evolution toward research that is inherently cross-media and cross-scale; explicitly considers the social dimensions of change; and focuses on designing solutions to the specific risks climate change poses to the environment and society.

Reframing Future Risks of Extreme Heat in the United States.

The goal of this study is to reframe the analysis and discussion of extreme heat projections to improve communication of future extreme heat risks in the United States. We combine existing data from 31 of the Coupled Model Intercomparison Project Phase 5 models to examine future exposure to extreme heat for global average temperatures of 1.5, 2, 3, and 4 °C above a preindustrial baseline. We find that throughout the United States, historically rare extreme heat events become increasingly common in the future as global temperatures rise and that the depiction of exposure depends in large part on whether extreme heat is defined by absolute or relative metrics. For example, for a 4 °C global temperature rise, parts of the country may never see summertime temperatures in excess of 100 °F, but virtually all of the country is projected to experience more than 4 weeks per summer with temperatures exceeding their historical summertime maximum. All of the extreme temperature metrics we explored become more severe with increasing global average temperatures. However, a moderate climate scenario delays the impacts projected for a 3 °C world by almost a generation relative to the higher scenario and prevents the most extreme impacts projected for a 4 °C world.

Reframing climate change assessments around risk: recommendations for the US National Climate Assessment.

Climate change is a risk management challenge for society, with uncertain but potentially severe outcomes affecting natural and human systems, across generations. Managing climate-related risks will be more difficult without a base of knowledge and practice aimed at identifying and evaluating specific risks, and their likelihood and consequences, as well as potential actions to promote resilience in the face of these risks. We suggest three improvements to the process of conducting climate change assessments to better characterize risk and inform risk management actions.

The effects of downscaling method on the variability of simulated watershed response to climate change in five U.S. basins.

Simulations of future climate change impacts on water resources are subject to multiple and cascading uncertainties associated with different modeling and methodological choices. A key facet of this uncertainty is the coarse spatial resolution of GCM output compared to the finer-resolution information needed by water managers. To address this issue, it is now common practice to apply spatial downscaling techniques, using either higher-resolution regional climate models or statistical approaches applied to GCM output to develop finer-resolution information for use in water resources impacts assessments. Downscaling, however, can also introduce its own uncertainties into water resources impacts assessments. This study uses watershed simulations in five U.S. basins to quantify the sources of variability in streamflow, nitrogen, phosphorus, and sediment loads associated with the underlying GCM compared to the choice of downscaling method (both statistically and dynamically downscaled GCM output). We also assess the specific, incremental effects of downscaling by comparing watershed simulations based on downscaled and non-downscaled GCM model output. Results show that the underlying GCM and the downscaling method each contribute to the variability of simulated watershed responses. The relative contribution of GCM and downscaling method to the variability of simulated responses varies by watershed and season of the year. Results illustrate the potential implications of one key methodological choice in conducting climate change impacts assessments for water - the selection of downscaled climate change information.