## 2 Materials and Methods
### Parameter Calibration and Model Validation at the Site Level
During calibration, each PFT-specific parameter for DBF, EBF, ENF, and GRS was increased or decreased by 10% until: (1) the correlation coefficient between hourly flux tower estimate (\(GPP_{tower}\)) and modeled \(GPP\) was as close to 1 as possible and this change in parameter did not conflict with (2) or (3); (2) the root mean square error (RMSE) between hourly \(GPP_{tower}\) and modeled \(GPP\) was as low as possible and this change in parameter did not conflict with (1) or (3); (3) the standard deviations of hourly \(GPP_{tower}\) and modeled \(GPP\) were as similar as possible and this change in parameter did not conflict with (1) or (2). Table 2 presents the calibrated parameters used to calculate hourly \(GPP\). After calibration, hourly \(GPP\) values at the validation sites were also calculated and compared with \(GPP_{tower}\). Without the screening limitation of \(PPFD\) in the \(GPP\) module, more FFNet DB and FLUXNET2015 data (extraction periods expanded to 2003-2011 at API, 2003-2011 at FY and 2006-2014 at SAP) were obtained to calibrate and validate hourly \(R_{e}\) and \(NEE\). Validation experiments using YMS [113; 114; 115] data were also added, and flux tower estimates of the mixed broadleaf forest with both deciduous and evergreen species were compared against DBF modeling results and EBF modeling results, respectively. Half-hourly \(GPP\), \(R_{e}\), and \(NEE\) data with complete air temperature record were selected in each FFNet DB data subset. Only the best quality half-hourly \(GPP\), \(R_{e}\), \(NEE\), and air temperature data (quality flag = 0) were selected in each FLUXNET2015 data subset. Hourly averages were then calculated for \(R_{e}\) modeling calibration and validation at the site level. Additional required variables such as \(LAI\), \(\theta_{k}\), soil temperature \(T_{k}\textsuperscript{soil}\), and fractions of the respective soil components in the 0-7 and 7-28 cm soil layers were assumed with grid values of the \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Dataset**} & \multirow{2}{*}{**Site**} & \multirow{2}{*}{**Site Code**} & \multirow{2}{*}{**Longitude**} & \multirow{2}{*}{**Latitude**} & \multicolumn{2}{c}{**Plant**} & **Modeling** & **Extraction** \\  & & & & & & **Functional Type** & **Group** & **Period** \\ \hline \multirow{5}{*}{FLUXNET2015} & Changeling & CNG & 123.5092E & 44.5934N & GRS & Calibration & 2007–2010 \\  & Dinghushan & DIN & 112.5361E & 23.1733N & EBF & Calibration & 2003–2005 \\  & Duolun & DU2 & 116.2836E & 42.0467N & GRS & Validation & 2006–2008 \\  & Pasoh forest reserve & PSO & 102.3062E & 2.9730N & EBF & Validation & 2003–2009 \\  & Qianyazhou & QLA & 115.0581E & 26.7414N & ENF & Validation & 2003–2005 \\ \hline \multirow{5}{*}{FFNet DB} & Appi & API & 140.9375E & 40.001N & DBF & Validation & 2010–2011 \\  & Fuji Yoshida & FJY & 138.76225E & 35.45454N & ENF & Calibration & 2010–2011 \\  & Sapporo & SAP & 141.3853E & 42.9868N & DBF & Calibration & 2010–2014 \\  & Yamashiro & YMS & 135.840884E & 34.7940252N & Mixed Forest & Validation & 2003–2011 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: List of FFNet DB and FLUXNET2015 sites used for parameter calibration and model validation.