Optimizing phenological parameters for bridging remote sensing and QUINCY model in permafrost regions

Vegetation leaf phenology (i.e. the timing of leaf onset and offset) determines the temporal bounds of the growing season. Thereby leaf phenology strongly influences the exchanges of energy and CO₂ between the atmosphere and the biosphere. However, accurate parameterization of leaf phenology processes in terrestrial biosphere models is challenging due to a poor understanding of the physical drivers of leaf recovery and senescence and their co-variance in space. Vegetation phenology in Northern Hemisphere permafrost regions is affected by more complex permafrost processes compared with the other terrestrial ecosystems. Yet the heterogeneity of vegetation response within permafrost regions is often overlooked in global simulations that treat the region as a whole. Further, PFT-based biogeochemistry models set phenological parameters as simply constants, but do not take into account the vegetation heterogeneity within the same plant functional type. 

Here, we derive optimal heat-related phenological parameters within the QUINCY model by inversing remote sensing information. Compared to the model’s default parameters, these optimized parameters significantly improve the prediction of the growing season start and ending in more than 70% and 80% of Northern Hemisphere permafrost regions, respectively. Our results reveal significant variability in vegetation phenological responses across different permafrost regions covered by herbaceaous vegetation types. This suggests that phenological parameters in terrestrial biosphere models must be tailored to local environmental conditions. This implication is further verified by QUINCY model. This study provides insights into the potential for enhancing model performance with the help of remote sensing information, and emphasizes the necessity for local parameterization across different ecosystems within Northern Hemisphere permafrost regions by terrestrial biosphere models.