Urban land patterns can moderate population exposures to climate extremes over the 21st century.

Climate change and global urbanization have often been anticipated to increase future population exposure (frequency and intensity) to extreme weather over the coming decades. Here we examine how changes in urban land extent, population, and climate will respectively and collectively affect spatial patterns of future population exposures to climate extremes (including hot days, cold days, heavy rainfalls, and severe thunderstorm environments) across the continental U.S.

Growing convergence research: Coproducing climate projections to inform proactive decisions for managing simultaneous wildfire risk.

We apply a convergence research approach to the urgent need for proactive management of long-term risk associated with wildfire in the United States. In this work we define convergence research in accordance with the US National Science Foundation-as a means of addressing a specific and compelling societal problem for which solutions require deep integration across disciplines and engagement of stakeholders. Our research team brings expertise in climate science, fire science, landscape ecology, and decision science to address the risk from simultaneous and impactful fires that compete for management resources, and leverages climate projections for decision support.

Assessing climate change impacts on greenhouse gas emissions, N losses in drainage and crop production in a subsurface drained field.

Future climate change-driven alterations in precipitation patterns, increases in temperature, and rises in atmospheric carbon dioxide concentration ([CO]) are expected to alter agricultural productivity and environmental quality, while high latitude countries like Canada are likely to face more challenges from global climate change. However, potential climate change impact on GHG emissions from tile-drained fields is poorly documented. Accordingly, climate change impacts on GHG emissions, N losses to drainage and crop production in a subsurface-drained field in Southern Quebec, Canada were assessed using calibrated and validated RZWQM2 model.