## 3 Results
### The Propagation of Bias in Phenology  
With different remotely sensed phenological metrics used as reference, the parameters of phenological models showed different capabilities of being optimized. For the \"Sequential\" model, the RMSD between modeled and remotely sensed onset was minimized to a range of 4.0-10.2 days. Specific RMSD depended on the combination of method and VI used to retrieve the onset. The RMSD from the \"Delpierre\" model ranged from 3.4-11.8 days. The modeled phenology generally showed a similar pattern of bias as the remotely sensed phenology used for parameterization in terms of whether it is earlier or later than the ground observation (Figure 4). When the onsets derived from NDVI were used as reference to parameterize the \"Sequential\" model, LOGISTIC1, LOGISTIC2, MOVING and DERIVATIVE showed a smaller RMSD (Table 5) than that between the remotely sensed onset and BBRK30 (Table 3), suggesting that the modeled onsets were closer to the ground observation. The correlation was increased for all the methods except CAMELBACK. When the onsets derived from EVI were used for parameterization, LOGISTIC1, LOGISTIC2, MIDPOINT and DERIVATIVE showed a slightly reduced RMSD; and LOGISTIC1, LOGISTIC1 and CAMELBACK showed a decrease in the correlation coefficient. The modeled leaf offsets showed smaller RMSD and higher correlation with the ground observation when the offsets derived from NDVI were used as reference to parameterize the \"Delpierre\" model, regardless of methods (Tables 4 and 6). In contrast, when the offsets derived from EVI were used as reference, increased RMSD was only found for LOGISTIC1. MIDPOINT and MOVING showed lower correlation coefficient, while the other methods showed higher correlation coefficient. Moreover, the leaf onset simulated using the Agro-IBIS algorithm was generally earlier than the ground observation (Figure 4) with an RMSD of 10.9 days. The correlation coefficient was 0.43, suggesting the inter-annual variability is not represented well. The leaf offset simulated using the Agro-IBIS algorithm was constant at DOY280 during the simulation period, which implies that the offset is only controlled by photoperiod, even though low temperature is also considered in the algorithm. \begin{table}
\begin{tabular}{c c c c c} \hline \multirow{2}{*}{**Leaf Offset**} & \multicolumn{2}{c}{**NDVI**} & \multicolumn{2}{c}{**EVI**} \\ \cline{2-5}  & **RMSD** & \(\boldsymbol{\rho}\) & **RMSD** & \(\boldsymbol{\rho}\) \\ \hline LOGISTIC1 & 20.6 & 0.53 & 45.3 & \(-\)0.25 \\ LOGISTIC2 & 21.1 & 0.38 & 5.2 & 0.02 \\ MIDPOINT & 21.8 & 0.32 & 9.8 & 0.17 \\ MOVING & 59.1 & 0.13 & 30.0 & 0.51 \\ DERIVATIVE & 29.4 & 0.03 & 17.0 & \(-\)0.38 \\ CAMELBACK & 36.4 & 0.30 & 39.3 & \(-\)0.33 \\ \hline \end{tabular} The RMSD and \(\boldsymbol{\rho}\) between the offset from MCD12Q2 product and observations are 49.1 days and 0.37, respectively.  
\end{table} 
Table 4: Performance of remotely sensed offset. Figure 4: Ground observed and simulated phenology. Error bars indicate the standard deviation of observation. “Agro-IBIS” is the leaf onset or offset simulated using the original Agro-IBIS algorithm and parameters. Onset was simulated using the “Sequential” model and the parameters were optimized with onset derived from NDVI **(a)**; and EVI **(b)**; offset was simulated using the “Delpierre” model and parameters were optimized with offset derived from NDVI **(c)**; and EVI **(d)**.