Unexpected role of winter precipitation in determining heat requirement for spring vegetation green-up at northern middle and high latitudes

Heat requirement, expressed in growing degree days (GDD), is a widely used method to assess and predict the effect of temperature on plant development. Until recently, the analysis of spatial patterns of GDD requirement for spring vegetation green-up onset was limited to local and regional scales, mainly because of the sparse and aggregated spatial availability of ground phenology data. Taking advantage of the large temporal and spatial scales of remote sensing-based green-up onset data, we studied the spatial patterns of GDD requirement for vegetation green-up at northern middle and high latitudes. We further explored the correlations between GDD requirement for vegetation green-up and previous winter season chilling temperatures and precipitation, using spatial partial correlations. We showed that GDD requirement for vegetation green-up onset declines towards the north at a mean rate of 18.8 degrees C-days per degree latitude between 35 degrees N and 70 degrees N, and vary significantly among different vegetation types. Our results confirmed that the GDD requirement for vegetation green-up is negatively correlated with previous winter chilling, which was defined as the number of chilling days from the day when the land surface froze in the previous autumn to the day of green-up onset. This negative correlation is a well-known phenomenon from local studies. Interestingly, irrespective of the vegetation type, we also found a positive correlation between the GDD requirement and previous winter season precipitation, which was defined as the sum of the precipitation of the month when green-up onset occur and the precipitation that occurred during the previous 2months. Our study suggests that GDD requirement, chilling and precipitation may have complex interactions in their effects on spring vegetation green-up phenology. These findings have important implications for improving phenology models and could therefore advance our understanding of the interplay between spring phenology and carbon fluxes.