## 3 Results  
### Spatial Trends of Observed NDVI and Modeled NPP  
We used a combination of global and regional estimates of terrestrial ecosystems' NPP based on five land-surface models [28] and GIMMS version 3g NDVI data [23] for the period 1982-2012 in this study. The TRENDY models captured the spatial pattern of input climate data in simulated NPP, and global trend of NPP is consistent with previously reported NDVI for the same period [7]. We found about 67% of the global land regions having positive NDVI values with a maximum increasing trend of 0.028 y\({}^{-1}\). Similarly, about 80% of the global land regions had positive NPP values based on the models' ensemble, with a maximum increasing trend of 0.012 Pg C\(\cdot\) y\({}^{-1}\). y\({}^{-1}\); however, we found differences among the five models (not shown). The JULES simulations resulted in about 68% of global land area with positive NPP values of \(>\)0, which corresponds closely to the 67% land area with positive NDVI values. The % of statistically significant pixels is shown in Table 2, where, VEGAS showed the highest number of significant pixels followed by MME and OCN. The spatial distribution of the NDVI trends for the study period is presented in Figure 1. The regions with greatest increase in NDVI are predominantly located in the Northern Hemisphere (e.g., Western Europe, India, China and Sahel region), followed by those in the Southern Hemisphere \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Models/Data** & **Fraction (\%) \textgreater{} 0** & **Fraction (\%) \textless{} 0** & **\% of Statistically Significant** \\  & & **Land Pixels (\textgreater{} 0.05)** \\ \hline MME & 79.46 & 20.54 & 50 \\ CLM4.5 & 80.35 & 19.65 & 36 \\ JULES & 67.82 & 32.18 & 44 \\ LPJ & 71.66 & 28.34 & 30 \\ OCN & 83.35 & 16.65 & 48 \\ VEGAS & 78.82 & 21.18 & 58 \\ _NDVI_ & 67.15 & 32.85 & 48 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Some statistics of global simulated net primary productivity (NPP) and observed Normalized Difference Vegetation Index (NDVI) trends at every land pixels for the 1982–2012 period. Land pixels were defined using five models mean ensemble (MME) for land area as a reference, excluding Antarctica and part of Greenland. (e.g., Amazonian region and Eastern Australia). Despite these general increasing trends, some regions of Northern Hemisphere also showed significant decrease in NDVI, mainly in the Boreal region of North America and Northern China. The major decrease in the Southern Hemisphere was found in South America (e.g., Argentina, and Chile). Generally, the global NPP spatial trends based on models' ensemble did not consistently follow the spatial trends of NDVI (Figure 1). This became obvious in some parts of the globe including Alaska, Africa, Angola, Zambia and Congo, and Oceania. Similarly, we did not find a consistent corresponding decreasing trend between the NPP and NDVI, except for a few regions (e.g., South America and Boreal region of North America). The main regions showing consistent deceasing trends were Eurasia, Sahel region of Africa, India, and China. Some similar inconsistencies were found between NDVI trends and individual TRENDY simulations (Figure 2). Across all the models, the trend of NPP (both magnitude and spatial pattern) was different than the NDVI trend, particularly in the Amazon, Africa, Oceania and Eurasia. In general, NPP trends simulated by some models were in better agreement with NDVI trends than others. For example, the modeled NPP trend by LPJ was in closer agreement to NDVI trend as compared with other four models. In contrast, JULES showed significantly higher NPP trends for the Eurasia and Africa regions when compared with NDVI trends for these regions. Two of the five models, namely VEGAS and CLM4.5, did not show any trend in NPP they simulated for major parts of the globe. Overall, the mismatch between TRENDY models' NPP and NDVI values were also evident from their spatial correlations (Figure 3).