Snow disappearance timing associated with elevation and vegetation type determines heterogeneity in spring onset in interior Alaska

• Published in: Polar science Vol. 35; p. 100918
• Main Authors: Kawashima, Shihori, Ueyama, Masahito, Harazono, Yoshinobu, Iwata, Hiroki, Kobayashi, Hideki
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2023
• Subjects: Boreal forest; Growing degree days; Satellite remote sensing; Spring phenology; Satellite remote sensing; Boreal forest; Growing degree days; Spring phenology
• ISSN: 1873-9652; 1876-4428
• DOI: 10.1016/j.polar.2022.100918

The spatiotemporal variations in spring onset were evaluated based on a satellite-derived enhanced vegetation index (EVI), land surface temperature, and snow cover from 2000 to 2021 in interior Alaska. Spring onset was determined as a budburst or seasonal green-up of vegetation based on EVI. The analysis showed that snow disappearance date was the key driver of spatiotemporal variations in the spring onset date. These dates for snow disappearance and spring onset varied with elevation, showing importance of elevation to explain the spatial heterogeneity in spring onset. The magnitudes in the heterogeneity in spring onset varied year to year, where the heterogeneity increased in warm spring owing to an increased heterogeneity in snow disappearance. This phenomenon was associated with slower snowmelt under lower shortwave radiation earlier in the season. These results suggest that future warming could increase the heterogeneity in spring onset in this region. Spring onset was further modeled with the growing degree-day model using the Bayesian optimization, which showed that model performance did not deteriorate with coarse-resolution inputs. The results indicate that coarse-resolution models, such as Earth system models, are a reliable tool for predicting spring onset in this region.