## 3 Results
### Satellite-Based Re estimations  
We used the most instrumental satellite-based GPP estimation methods, GPP_VPM and GPP_MOD, as compared to GPP_EC and GPP_EC together with MOD11A2 LST products to estimate Re and its components (Ra and Rm) recorded as VPMM, MODM and ECM, respectively (Equation (15) and Figure 1). The temporal variation of Re_EC could be well explained by these three modeled Re values (\(R^{2}>0.9\), \(p<0.0001\)) (Figure 6). In addition, the slopes of the linear regression between Re_EC and modeled Re estimations are quite close to 1.0 (mostly from 0.98 to 1.02) (Figure 6b-d), which indicated Re_EC could be effectively estimated by modeled Re estimations. Daily Re_EC were 0.86, 0.93 and 0.77 g C m\({}^{-2}\) in GS and 0.33, 0.28 and 0.17 g C m\({}^{-2}\) in NG from 2009 to 2011 (Table 3). All satellite-based daily Re estimations had a small RMSE less than 0.12 g C m\({}^{-2}\) day\({}^{-1}\) in GS and 0.08 g C m\({}^{-2}\) day\({}^{-1}\) in NG, which actually did not show significant (\(p>0.1\)) differences compared to Re_EC regardless of in GS or NG (paired \(t\)-test, \(\alpha=0.05\)) (Table 3). Thus, both of the cumulative Re estimations in GS and NG calculated from these three satellite-based models also failed to generate significant (\(p>0.1\)) differences with cumulative Re_EC, which showed an average CO\({}_{2}\) emission of 143.74 g C m\({}^{-2}\) in GS and 51.36 g C m\({}^{-2}\) in NG from 2009 to 2011 (Table 3). Figure 6: Seasonal variations of ecosystem respiration (Re) estimations from different methods (**a**); and comparison with eddy covariance partitioned Re (Re_EC) from: 2009 (**b**); 2010 (**c**); and 2011 (**d**). \(k\) values and dashed lines in (**b–d**) are the linear slope between Re_EC and modeled Re, and the reference lines of 1:1, respectively. All linear regressions are extremely significant (\(p<0.0001\)). Colors in (**b–d**) are one-to-one corresponding with different Re estimations in (**a**), respectively. Different Re estimations based on the diverse GPP estimation models are identical to the Figure 1. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**Daily Re Estimations (g C m\({}^{-2}\) 8 days\({}^{-1}\))**} & \multicolumn{6}{c}{**Cumulative Re Estimations (\(\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{ \boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{ \boldsymbol{ \boldsymbol{ \boldsymbol{  }}}}}}}}}}}}\))**} \\ \cline{3-13} \multirow{2}{*}{**Period**} & \multirow{2}{*}{**Method * [FOOTNOTE:*]Footnote *: Satellite-based daily Re estimations do not show significant (\(p>0.1\)) differences with R\({}_{\text{e,IC}}\) (paired +test, \(\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{ \boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{ \boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{ \boldsymbol{ \boldsymbol{ }}}}}}}}}}}}}}\) = 0.05). Re is eight-day composited and the different methods are identical to the Figure. 1. CS and NC are growing season and non-growing season. In NG, all satellite-based \(\mathcal{R}\) estimations, showed as “model,” are identical that are derived from the exponential relationship with land surface temperature (IST) (Equation (15)). SD is standard deviation of the average eight-day composited Re estimations. Most of RPEs are smaller than 1% and approximate to zero, thus we do not showed here. Columns with the same alphabets indicate that insignificant difference existed among diverse cumulative Re estimations (\(\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{ \boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{ \boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{\boldsymbol{ \boldsymbol{\boldsymbol{\boldsymbol{ \boldsymbol{ \boldsymbol{ \boldsymbol{ }}}}}}}}}}}}}}}} }\) = 0.05, \(p>0.1\)). & \\ \hline \hline \end{tabular}
\end{table}