## 3 Results
### Growing Season  
The growing season onset derived from LAI is broadly consistent across the models, with high correlations compared to the satellite data (\(>\)0.5) (Figure 5). In general the satellite observations show a later onset as latitude increases, remarkably similar to the thermal gradient. CLM, LPJ-GUESS, LPJ, SDGVM and, to a lesser extent, OCN, ORCHIDEE and VEGAS correctly reproduce this spatial pattern, as shown by the RSME and spatial correlations. This is not surprising as those models include a thermal limitation to photosynthesis and a snow scheme. TRIFFID shows no detectable onset above 50 \(\mathrm{\SIUnitSymbolNelsius}\) but has later values compared to the satellite below that threshold, likely due to the distribution of the evergreen PFT over the whole NH. Models that have the highest correlations with the satellite on the SA also show very similar values to the satellite on the onset, as shown by RSME (Figure 5). Figure 4: Seasonal Amplitude in LAI for 8 LSMs and satellite observations for the Northern Hemisphere (30\({}^{\circ}\)–90 \(\mathrm{\SIUnitSymbolNelsius}\)) for the period 1986–2005. Root mean square errors and spatial correlations between each model and the observations are given in the white boxes. The discrepancies between the models and satellite observations are larger when considering the end of the growing season or dormancy (Figure 6). While the satellite data shows a latitudinal gradient, with the dormancy occurring earlier at higher latitudes, most models overestimate the dormancy day (RSME = 31-63). Out of the eight models, LPJ-GUESS, LPJ, ORCHIDEE and VEGAS have a similar dormancy distribution with minor discrepancies over the taiga and boreal forest, as shown by the spatial correlations. CLM, OCN and TRIFFID have patchy areas of agreement, while SDGVM has a much later dormancy than the satellite data. In some regions, particularly boreal deciduous forest, modeled dormancy can happen after the end of the year (DOY higher than 365). However, over these months the snow corrupts the satellite signal, leading to an underestimation of LAI. This partially explains why the dormancy date errors are larger than those of the onset. All of the models predict a later dormancy date (day), particularly over the northern temperate region (30 \(\circ\)-50 \(\aleph\)N) (Figure 6). This means that leaves in the models remain for longer than they should. However, the late dormancy is not in line with the vegetation photosynthetic activity. When the same methodology used to calculate the LAI-growing period was applied to gross primary productivity (GPP), we found that the dormancy began at 277 \(\pm\) 7 days in the models, which is remarkably earlier than previously predicted by LAI (315 \(\pm\)10 days), even on the low-north latitudes  
Figure 5: Mean (1986–2005) growing season onset (day) for 8 LSMs and satellite observations over the Northern Hemisphere (30 \(\circ\)-90 N). Spatial correlations and root mean square errors between each model and the observations are given in the white boxes. (287 \(\pm\)18). It is evident that all of the models keep inactive leaves for longer than they should, which does not have an impact on the C cycle but could potentially modify radiation and turbulent fluxes, therefore affecting planetary boundary layer dynamics. There is a higher level of agreement in growing season length between the satellite data and the models than for dormancy dates (Figure 7). Surprisingly, the satellite observations display a very homogeneous length over regions \(>\) 50 N, with values between 120-150 days. Similar to the previous patterns, LPJ, LPJ-GUESS, CLM, ORCHIDEE and VEGAS have the highest agreement with the satellite data, as shown by the RSME and spatial correlations. Interestingly, the disagreement between models and observations occurs mostly over the lower latitudes of the Northern Hemisphere. OCN displays the same patchy agreement that shows on the onset and SDGVM displays the least agreement with an opposite GSL distribution.