## 4 Discussion
### Modelling of Springtime Development and the Start of Season in JSBACH
This agrees with findings by [PERSON] and [PERSON] for southern Finland [21], but due to the higher temporal resolution of the remote sensing data set used here, we can quantify the bias better and also give results for the northern parts of Finland that were masked out in the study above. As regards other biosphere models from the study by [PERSON] et al. [14], the bias for JSBACH DBF_SOSmod turned out to be relatively small, although direct comparisons are difficult due to differences in the environmental drivers for the model runs. It has to be noted that the definition of DBF_SOSmod does not correspond exactly to DBF_SOSsat. While DBF_SOSmod is defined based on a minimal change in LAI, the visual observation of bud break may indicate a later stage of development. An optimized parameterization of the LoGro-P model for the boreal zone would allow an improvement of the overall bias for DBF_SOSmod; variation in parameter values, such as the alternating temperature (\(T_{alt}\)) and the minimum value of the critical heat sum (\(S_{crit}^{min}\)) can reduce the mean bias (Appendix A, Tables A1 and A2). A proper tuning of the LoGro-P parameters for our area of interest was outside the scope of this study and needs further investigation, but could be performed using satellite observations and Bayesian optimization techniques. Similar to ENF, the bias in DBF_SOSmod showed a regional gradient; that is, the bias decreased from south to north (Figure 7, Supplementary Materials: Table S2). According to field observations, the heat sum requirement for bud break of birch decreases from south to north in the boreal region [94; 95] and also the temperature threshold for the NDVI-based greening-up decreases [28; 77]. This seems to be in contradiction to our results for JSBACH DBF_SOSmod. The same critical temperature and heat sum requirement was used in the LoGro-P model for the whole study area. According to the above, one would expect a gradient with earlier bias in southern areas compared to northern areas. We observed the opposite, except for the northernmost parts of the study area (Figure 8b). Reasons for this could be an insufficient chilling predicted by the LoGro-P model, a regional gradient in bias in the bias-corrected driving temperature, or in the remote sensing estimate of DBF_SOSsat. Under the current climate, the chilling requirement is typically fulfilled in the boreal region [96] and this was also the case in our study area. Therefore, the chilling requirement cannot be used for a better calibration of the south-north gradient, and since the start date of the chilling decay follows a climate gradient, an increase in the decay parameter (\(C_{decay}\)) would further pronounce the delay in the DBF_SOSmod in southern regions. The \(S_{crit}^{min}\) parameter plays a role as well, but while the overall bias could be reduced with a lower parameter value, the regional gradient would still remain and this may suggest that optimal parameters for the boreal region are zone-specific. Despite a very small temperature bias in the start date of the \"growth phase\" of DBF for the whole of Finland (Figure 8c), the slope of the regression line between DBF_SOSsat and the modelled date from LoGro-P was slightly higher (0.9 compared to 0.79) when FMI gridded temperatures were used instead of temperature data from the regional climate model. This indicates a small influence of the driving data to the regional gradient. Likewise, the late bias in DBF_SOSsat for phenological sites in northern, and early bias in southern Finland (Section 3.1) need further investigations and may partly explain differences in bias in JSBACH DBF_SOSmod in the different boreal sub-zones.