## 3 Results
### Comparison of Regional Scale Modeling Results and Satellite Data
\begin{table}
\begin{tabular}{c c c c c c} \hline \multirow{2}{*}{**Plant Functional**} & \multirow{2}{*}{**Total Area 1**} & **Annual** & **Annual** & **Integrated** & **Integrated** \\  & & **Averaged _GPP_** & **Averaged \(R_{e}\)** & **Annual GPP** & **Annual \(R_{e}\)** \\ \cline{2-6}  & **km2** & **gC m\({}^{-2}\) Year 1** & **gC m\({}^{-2}\) Year 1** & **10\({}^{6}\) tonCO2 Year 1** & **10\({}^{6}\) tonCO2 Year 1** & **10\({}^{6}\) tonCO2 Year 1** \\ \hline DBF & 3131.06 \(\pm\) 100.40 & 1254.42 \(\pm\) 67.63 & 667.66 \(\pm\) 73.21 & 14.39 \(\pm\) 0.78 & 7.66 \(\pm\) 0.84 \\ EBF & 3669.55 \(\pm\) 72.73 & 1484.26 \(\pm\) 22.22 & 801.43 \(\pm\) 82.38 & 19.96 \(\pm\) 0.30 & 10.78 \(\pm\) 1.11 \\ ENF & 3337.77 \(\pm\) 48.05 & 1834.27 \(\pm\) 38.60 & 1035.43 \(\pm\) 105.79 & 22.43 \(\pm\) 0.47 & 12.66 \(\pm\) 1.29 \\ GRS & 159.22 \(\pm\) 14.04 & 1409.33 \(\pm\) 185.44 & 1308.89 \(\pm\) 280.83 & 0.82 \(\pm\) 0.11 & 0.76 \(\pm\) 0.16 \\ Partially vegetated & 1374.62 \(\pm\) 134.05 & 1020.77 \(\pm\) 93.59 & 393.85 \(\pm\) 38.41 & 5.14 \(\pm\) 0.47 & 1.98 \(\pm\) 0.19 \\ URBAN (0 \(<\) _LAI_) & & & & & \\ \hline \end{tabular}  
* Total area of each plant functional type (PFT) was estimated based on the number of 500 m \(\times\) 500 m grid cells in the MODIS land cover type product (MCD12Q1) and the vegetated cover fraction per grid cell in the MODIS vegetation continuous fields product (MOD44B).  
\end{table} 
Table 3: Annual averaged and integrated _GPP_ and \(R_{e}\) estimates in deciduous broadleaf forest (DBF), evergreen broadleaf forest (EBF), evergreen needleleaf forest (ENF), grassland (GRS), and partially vegetated urban area of the Greater Tokyo Area (139\({}^{\circ}\)E-141\({}^{\circ}\)E, 35\({}^{\circ}\)N-36.33\({}^{\circ}\)N) during the period 2010–2018. winter and 10.0-30.0 gC m\({}^{-2}\) 8-day\({}^{-1}\) in summer in the highly urbanized areas next to the Tokyo bay, which both our model and the MODIS _GPP_ dataset considered non-vegetated. In terms of _NPP_, our annual modeled _NPP_ (Figure 8a) was about 0.6-2.0 kgC m\({}^{-2}\) year\({}^{-1}\) in forests and up to 0.6 kgC m\({}^{-2}\) year\({}^{-1}\) in urban vegetated land in 2018. Evergreen forests in particular presented high _NPP_, 1.2-2.0 kgC m\({}^{-2}\) year\({}^{-1}\), by virtue of a longer photosynthetic active period. Our modeled _NPP_ was larger compared to annual MODIS _NPP_ (Figure 8b,c) values, especially in evergreen forests in the northeast and west of the study area. This was probably because of lower estimates of autotrophic respiration and growth respiration rate of plants in particular, considering that the modeled _GPP_ showed good agreement with MODIS _GPP_ and that the algorithm of maintenance respiration in this study was similar to the MODIS method. Because of limited space, comparisons of 8-day _GPP_ and annual _NPP_ to satellite data in 2010-2017 are not presented, but were very similar to those obtained for cases of 2018. Figure 7: Seasonal variation examples of (**a–d**) modeled 8-day _GPP_, (**e–h**) difference between modeled and MODIS (MOD17A2 HGF) 8-day _GPP_, and (**i–l**) difference between modeled and GOSIF 8-day _GPP_ in 2018; the average (**m**) and standard deviations (**o**) of the difference between modeled and MODIS (MOD17A2 HGF) 8-day _GPP_ during the period 2010–2018; the average (**n**) and standard deviations (**p**) of the difference between modeled and GOSIF 8-day _GPP_ during the period 2010–2018.