## 3 Results
### GPP Validation
#### 3.1.2 Seasonal GPP
Autumn (September-November): The MOD_NCEP GPP (R\({}^{2}\) = 0.80, Bias = 0 gC\(\cdot\) m\({}^{-2}\)\(\cdot\) 3-month\({}^{-1}\) and RMSE = 32%) and NCEP_GLASS GPP (R\({}^{2}\) = 0.76, Bias = 1 gC\(\cdot\) m\({}^{-2}\)\(\cdot\) 3-month\({}^{-1}\) and RE = 57%) provided better estimating effectiveness (Figure 6, Table 3). In contrast, the MOD_Tower GPP and Tower_GLASS GPP obviously underestimated the Flux_Tower GPP (\(-102\) gC\(\cdot\) m\({}^{-2}\)\(\cdot\) 3-month\({}^{-1}\)) as a result of the common underestimations for CBS, HB, QYZ, XSBN and YC (Figure 6b,d). * 4. Winter (January-February and December): All four algorithms effectively estimated the Flux_Tower GPP (Figure 7, Table 3). However, the MOD_NCEP GPP and NCEP_GLASS GPP algorithms seriously overestimated the Flux_Tower GPP for DHS and XSBN (Figure 7a,c). The Flux_Tower GPP for QYZ were severely underestimated by the MOD_Tower GPP and Tower_GLASS GPP algorithms (Figure 7b,d). Figure 4. Comparisons of Flux_Tower GPP for spring (March–May) with: (**a**) MOD_NCEP GPP; (**b**) MOD_Tower GPP; (**c**) NCEP_GLASS GPP; and (**d**) Tower_GLASS GPP. Significance levels: **_p_ < 0.01. Figure 5: Comparisons of Flux_Tower GPP for summer (June–August) with: (**a**) MOD_NCEP GPP; (**b**) MOD_Tower GPP; (**c**) NCEP_GLASS GPP; and (**d**) Tower_GLASS GPP. Significance levels: **\(p<0.01\). Figure 6: Comparisons of Flux_Tower GPP for autumn (September–November) with: (**a**) MOD_NCEP GPP; (**b**) MOD_Tower GPP; (**c**) NCEP_GLASS GPP; and (**d**) Tower_GLASS GPP. Significance levels: **\(p<0.01\). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Comparison** & **R\({}^{2}\)** & **Mean (SD)** & **Bias** & **RMSE** & **RE** \\ \hline
**Seasonal** & & **(gC\(\cdot\) m\({}^{-2}\). 3-month\({}^{-1}\))** & **(gC\(\cdot\) m\({}^{-2}\). 3-month\({}^{-1}\))** & **(\%)** & **(\%)** \\ \hline
**Spring (March–May)** & & & & \\ \hline Flux\_Tower _vs._ MOD\_NCEP & 0.64 ** & 322(265) \(\mathrm{vs.}\) 283(229) & \(-\)39 & 50 & 56 \\ Flux\_Tower _vs._ MOD\_Tower & 0.62 ** & 322(265) \(\mathrm{vs.}\) 200(200) & \(-\)122 & 63 & 55 \\ Flux\_Tower _vs._ NCEP\_GLASS & 0.56 ** & 322(265) \(\mathrm{vs.}\) 362(265) & 40 & 58 & 75 \\ Flux\_Tower _vs._ Tower\_GLASS & 0.65 ** & 322(265) \(\mathrm{vs.}\) 242(211) & \(-\)80 & 54 & 44 \\ \hline
**Summer (June–August)** & & & & \\ \hline Flux\_Tower _vs._ MOD\_NCEP & 0.46 ** & 556(266) \(\mathrm{vs.}\) 413(153) & \(-\)143 & 43 & 35 \\ Flux\_Tower _vs._ MOD\_Tower & 0.36 ** & 556(266) \(\mathrm{vs.}\) 302(122) & \(-\)254 & 60 & 50 \\ Flux\_Tower _vs._ NCEP\_GLASS & 0.52 ** & 556(266) \(\mathrm{vs.}\) 546(212) & \(-\)10 & 33 & 33 \\ Flux\_Tower _vs._ Tower\_GLASS & 0.43 ** & 556(266) \(\mathrm{vs.}\) 395(162) & \(-\)161 & 46 & 41 \\ \hline
**Autumnumnumnumn{4}{c}{} & & & \\ \hline Flux\_Tower _vs._ MOD\_NCEP & 0.80 ** & 337(238) \(\mathrm{vs.}\) 337(243) & 0 & 32 & 69 \\ Flux\_Tower _vs._ MOD\_Tower & 0.73 ** & 337(238) \(\mathrm{vs.}\) 235(176) & \(-\)102 & 48 & 62 \\ Flux\_Tower _vs._ NCEP\_GLASS & 0.76 ** & 337(238) \(\mathrm{vs.}\) 338(268) & 1 & 38 & 57 \\ Flux\_Tower _vs._ Tower\_GLASS & 0.71 ** & 337(238) \(\mathrm{vs.}\) 235(193) & \(-\)102 & 48 & 58 \\ \hline
**Winter (January, February and December)** & & & & & \\ \hline Flux\_Tower _vs._ MOD\_NCEP & 0.92 ** & 116(137) \(\mathrm{vs.}\) 137(197) & 21 & 68 & - \\ Flux\_Tower _vs._ MOD\_Tower & 0.87 ** & 116(137) \(\mathrm{vs.}\) 91(141) & \(-\)25 & 48 & - \\ Flux\_Tower _vs._ NCEP\_GLASS & 0.92 ** & 116(137) \(\mathrm{vs.}\) 164(227) & 48 & 98 & - \\ Flux\_Tower _vs._ Tower\_GLASS & 0.88 ** & 116(137) \(\mathrm{vs.}\) 101(155) & \(-\)15 & 48 & - \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of the seasonal and annual GPP derived from the tower estimates with those derived from the MODIS algorithms (MOD_NCEP GPP, MOD_Tower GPP, NCEP_GLASS GPP, and Tower_GLASS GPP). Figure 7: Comparisons of Flux_Tower GPP for winter (January, February and December) with: **(a)** MOD_NCEP GPP; **(b)** MOD_Tower GPP; **(c)** NCEP_GLASS GPP; and **(d)** Tower_GLASS GPP.