## 3 Results  
### Comparison of Site-Level VPP Estimates with VPP Observations from FLUXNET GPP  
The SOG and EOG estimates based on the VPPest statistical models were compared with SOG and EOG observations from daily GPP time series. For forest sites, the SOG estimates had a strong relationship with SOG observations (R\({}^{2}\) = 0.80, \(p\) < 0.01), and the RMSE between them was 12.7 days (Figure 3 and Table 1). Agreement between the EOG estimates and EOG observations was relatively lower (R\({}^{2}\) = 0.70, \(p\) < 0.01), but the RMSE between them (10.5 days) was comparable to that of SOG. The R\({}^{2}\) and RMSE values between estimates and observations varied across forest types. The DBF had the highest accuracy, with R\({}^{2}\) = 0.85 and a RMSE of less than a week for SOG, and with R\({}^{2}\) = 0.77 and a RMSE = 7.5 days for EOG, followed by MF and ENF with a RMSE of approximately two weeks for both SOG and EOG.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**PFT**} & \multicolumn{3}{c}{**SOG**} & \multicolumn{3}{c}{**EOG**} \\ \cline{2-7}  & **R\({}^{2}\)** & **Bias** & **RMSE** & **R\({}^{2}\)** & **Bias** & **RMSE** \\  & **(Days)** & **(Days)** & **(Days)** & **(Days)** & **(Days)** & **(Days)** \\ \hline ENF & 0.72 & 0.7 & 15.4 & 0.65 & 0.2 & 12.0 \\ DBF & 0.85 & 0.0 & 6.6 & 0.77 & 0.1 & 7.5 \\ MF & 0.82 & 0.0 & 11.5 & 0.59 & 0.0 & 10.3 \\ All & 0.80 & 0.4 & 12.7 & 0.70 & 0.2 & 10.5 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Accuracy evaluation for starting day of GPP (SOG) and ending day of GPP (EOG) estimates from the statistical models for forest types: evergreen needle-leaf forest (ENF), deciduous broadleaf forest (DBF), and mixed forest (MF).  
The R\({}^{2}\) values (0.78 for SOG and 0.64 for EOG) between VPP estimates and observations in non-forest sites were similar to those of forest sites, but the RMSE values (19.4 days for SOG and 22.9 days for EOG) were relatively higher than those of forest sites (Figure 4 and Table 2). The coefficients of determination between VPP estimates and observations were higher than 0.60 for all non-forest types, but the requirements for RMSE were not satisfied. The RMSE values were between two weeks and three weeks for CRO, GRA, and WET, and over three weeks for shrub sites and SAVA. The RMSE values of EOG estimates for both GRA and WET were relatively low at close to two weeks. The EOG estimates of shrub sites had the lowest R\({}^{2}\) and the largest uncertainty with a RMSE = 39.0 days, followed by SAVA (27.5 days) and CRO (25.3 days). The SOG and EOG of non-forest types were more difficult to estimate than those of forest types.  
Figure 4: Scatter plots between (**a**) starting day of GPP (SOG) observations and SOG estimates, and (**b**) ending day of GPP (EOG) observations and EOG estimates for non-forest types: open shrublands (OSH), closed shrublands (CSH), savannas (SAV), woody savannas (WSA), grasslands (GRA), croplands (CRO), and wetlands (WET). Each point represents one FLUXNET site and one year.  
Figure 3: Scatter plots between (**a**) starting day of GPP (SOG) observations and SOG estimates, and (**b**) ending day of GPP (EOG) observations and EOG estimates for forest types: evergreen needle-leaf forest (ENF), deciduous broadleaf forest (DBF), and mixed forest (MF). Each point represents one FLUXNET site and one year.