Redefining seasons: Dynamic meteorological delineation unveils novel patterns in vegetation phenology responses to climate change

Abstract

Vegetation phenology is a sensitive indicator of climate change, and the impact of large-scale meteorological seasonal variations on phenological patterns remains understudied because traditional seasonal divisions fail to capture the dynamics of rapid phenological change. Utilizing CN05 gridded temperature data, we applied a dynamic meteorological model to analyze the spatial distribution and trends of spring and autumn, revealing their influence on regional vegetation phenology. We revealed that the start of spring and end of spring advanced at rates of −0.19 d·yr⁻¹ and −0.15 d·yr⁻¹, respectively, affecting 92.57 % and 82.85 % of the study area. Conversely, the start and end of autumn were delayed by + 0.06 d·yr⁻¹ and + 0.10 d·yr⁻¹, impacting 54.05 % and 89.96 % of the region. The length of spring and length of autumn increased at rates of + 0.05 d·yr⁻¹ and + 0.02 d·yr⁻¹, respectively, across 55.93 % and 53.97 % of the area. These changes exhibited a clear latitudinal gradient, with a decreasing duration from south to north. Significant correlations were observed between seasonal variations and vegetation phenology; earlier spring onset corresponded to an earlier start of the growing season in 71.58 % of the study area, while a later end of autumn correlated with a delayed end of the growing season in 59.72 % of the region. This study systematically demonstrates, for the first time, the extensive influence of climate-driven seasonal changes on vegetation phenology, offering valuable insights for weather forecasting, climate zoning, and phenology management.