Dynamically Downscaled Projections of Phenological Changes across the Contiguous United States

Abstract

Abstract Phenological indicators (PI) are used to study changes to animal and plant behavior in response to seasonal cycles, and they can be useful to quantify the potential impacts of climate change on ecosystems. Here, multiple global climate models and emission scenarios are used to drive dynamically downscaled simulations using the WRF model over the CONUS. The wintertime dormancy of plants (chilling units or “CU”), timing of spring onset (Extended Spring Indices or “SI”), and frequency of proceeding false springs are calculated from regional climate simulations covering historical (1995–2005) and future periods (2025–2100). Southern parts of the CONUS show projected CU decreases (inhibiting some plants from flowering or fruiting), while the northern CONUS experiences an increase (possibly causing plants to break dormancy too early, becoming vulnerable to disease or freezing). Spring advancement (earlier SI dates) is projected, with decadal trends ranging from approximately 1 to 4 days per decade over the CONUS, comparable to or exceeding those found in observational studies. Projected changes in risk of false spring (hard freezes following spring onset) vary across members of the ensemble and regions of the CONUS, but generally western parts of the CONUS are projected to experience increased risk of false springs. These projected changes to PI connote significant effects on cycles of plants, animals, and ecosystems, highlighting the importance of examining temperature changes during transitional seasons.