Predicting the Timing of Cherry Blossoms in Washington, DC and Mid-Atlantic States in Response to Climate Change

Abstract

Cherry blossoms, an icon of spring, are celebrated in many cultures of the temperate region. For its sensitivity to winter and early spring temperatures, the timing of cherry blossoms is an ideal indicator of the impacts of climate change on tree phenology. Here, we applied a process-based phenology model for temperate deciduous trees to predict peak bloom dates (PBD) of flowering cherry trees (Prunus×yedoensis ‘Yoshino’ and Prunus serrulata ‘Kwanzan’) in the Tidal Basin, Washington, DC and the surrounding Mid-Atlantic States in response to climate change. We parameterized the model with observed PBD data from 1991 to 2010. The calibrated model was tested against independent datasets of the past PBD data from 1951 to 1970 in the Tidal Basin and more recent PBD data from other locations (e.g., Seattle, WA). The model performance against these independent data was satisfactory (Yoshino: r2 = 0.57, RMSE = 6.6 days, bias = 0.9 days and Kwanzan: r2 = 0.76, RMSE = 5.5 days, bias = −2.0 days). We then applied the model to forecast future PBD for the region using downscaled climate projections based on IPCC's A1B and A2 emissions scenarios. Our results indicate that PBD at the Tidal Basin are likely to be accelerated by an average of five days by 2050 s and 10 days by 2080 s for these cultivars under a mid-range (A1B) emissions scenario projected by ECHAM5 general circulation model. The acceleration is likely to be much greater (13 days for 2050 s and 29 days for 2080s ) under a higher (A2) emissions scenario projected by CGCM2 general circulation model. Our results demonstrate the potential impacts of climate change on the timing of cherry blossoms and illustrate the utility of a simple process-based phenology model for developing adaptation strategies to climate change in horticulture, conservation planning, restoration and other related disciplines.

An Improved Method for Phenology Model Parameterization Using Sequential Optimization

“…(Table 1). On the other hand, our R c and R h were slightly larger by 14.52 and 17.03 respectively than those from Chung et al (2011). Interestingly, the entire heat requirements (R h -R c ) were still very close to each other.…”

“…Instead of a time-consuming grid search fitting all parameters simultaneously (Chung et al, 2011), a sequential algorithm is applied for fitting each parameter separately, using other parameters discovered in the previous steps. Sequential parameter estimation is often preferred over simultaneous procedure when phenology parameters have no known interdependencies (Wallach et al, 2014).…”

“…The starting year was set to 1992 because the detailed records have been only available since then. The end year was chosen to be 2010 for comparison with previous research (Chung et al, 2011). (Table 1).…”

“…While this approach was able to estimate peak bloom dates of flowering cherry trees in the Tidal Basin, Washington D.C., with reasonable accuracy (Chung et al, 2011), adapting the model for new location and variety required an arduous parameterization process through extensive grid search. This brute-force method has several shortcomings.…”

Local-scale adaptation to climate change: the village flower festival

“…Some (more famous) flower festivals, such as the cherry blossom festivals in Kyoto, Japan (Aono & Kazui 2008) and Washington, DC, USA (Chung et al 2011), are triggered by the flowering of the plants themselves. Other flower festivals may be held on fixed dates (e.g.…”