Three‐dimensional change in temperature sensitivity of northern vegetation phenology

Understanding how the temperature sensitivity of phenology changes with three spatial dimensions (altitude, latitude, and longitude) is critical for the prediction of future phenological synchronization. Here we investigate the spatial pattern of temperature sensitivity of spring and autumn phenology with altitude, latitude, and longitude during 1982–2016 across mid‐ and high‐latitude Northern Hemisphere (north of 30°N). We find distinct spatial patterns of temperature sensitivity of spring phenology (hereafter “spring ST”) among altitudinal, latitudinal, and longitudinal gradient. Spring ST decreased with altitude mostly over eastern Europe, whereas the opposite occurs in eastern North America and the north China plain. Spring ST decreased with latitude mainly in the boreal regions of North America, temperate Eurasia, and the arid/semi‐arid regions of Central Asia. This distribution may be related to the increased temperature variance, decreased precipitation, and radiation with latitude. Compared to spring ST, the spatial pattern of temperature sensitivity of autumn phenology (hereafter “autumn ST”) is more heterogeneous, only showing a clear spatial pattern of autumn ST along the latitudinal gradient. Our results highlight the three‐dimensional view to understand the phenological response to climate change and provide new metrics for evaluating phenological models. Accordingly, establishing a dense, high‐quality three‐dimensional observation system of phenology data is necessary for enhancing our ability to both predict phenological changes under changing climatic conditions and to facilitate sustainable management of ecosystems. This study explored spatial pattern of temperature sensitivity of land surface phenology in spring and autumn phenology (spring and autumn ST) based on three geographical dimensions of altitude, latitude, and longitude. Across mid‐ and high‐latitude Northern Hemisphere during 1982–2016, we found distinct spatial patterns of spring and autumn ST along altitudinal, latitudinal, and longitudinal gradients. Geographical gradient of temperature, temperature variance, precipitation, and radiation were possible drivers to the patterns of ST. Our results highlight the three‐dimensional view to understand phenological response to climate change, providing basis for improving phenological observation network and new metrics to evaluate phenology models.