## 1 Introduction  
Terrestrial ecosystems play a major role in the global carbon cycle and Earth's climate system through regulating the atmospheric carbon dioxide (CO\({}_{2}\)) concentrations [1]. The terrestrial ecosystems net primary production (NPP) relates to the carbon flux by plant photosynthesis and is used for understanding the dynamics of terrestrial ecosystems and their contribution to carbon cycle. The inherent variability of global NPP over space and time cannot be directly observed, therefore, satellite based observations of Normalized Difference Vegetation Index (NDVI) and other proxy measures are commonly used to monitor spatial and temporal changes in land productivity [2; 3; 4]. Understanding the spatial and inter-annual variability of vegetation activity using NDVI assumes that changes in NDVI present evidences about the vegetation's response to climate [5]. However, the response signal of vegetation canopy reflectance is delicate and influenced by non-vegetation effects (e.g., atmospheric conditions, satellite drift and zonal zenith angle). Despite this complexity, the NDVI relationship with ecosystems photosynthetic capacity has proven to be a robust signal under a wide range of environmental conditions, and a reliable observation for studying terrestrial ecosystems. For example, [PERSON] _et al._[3] and [PERSON] _et al._[4] reported NDVI as a proxy to examine the inter-annual and spatial vegetation activities in China and Northern high latitudes, respectively. Similarly, [PERSON] and [PERSON] [6] used NDVI as a mean to quantify the land degradation and desertification associated with vegetation distribution and activities. In another study, [PERSON] _et al._[7] used vegetation indices to examine the relationship between climate constraints (temperature, precipitation and radiation) and vegetation activity. Even though these studies have illustrated the relationship between NDVI and NPP; detailed understanding of their spatial and temporal trends is still lacking [4; 8; 9]. The NPP, _i.e._, the net amount of dry organic matter produced by plants, largely reflects the ability of plants to absorb atmospheric CO\({}_{2}\) and to convert it to biomass through photosynthesis [10]. Thus, understanding the spatial and temporal variations of NPP are of great interest for obtaining reliable estimates of terrestrial ecosystem capacity to serve as a major reservoir for carbon. Spatial variations of global NPP are mainly controlled by climate conditions, vegetation types and their spatial distribution, and factors that contribute to change this distribution such as land-use practices [11; 12]. Similarly, the temporal variations of NPP are mainly controlled by the seasonal phenology of vegetation, and climate conditions [11; 12]. During the last few decades, ecosystem models have become a major tool for studying the NPP dynamics under different climate conditions/scenarios. These models have been repeatedly evaluated for a variety of conditions to test their robustness in capturing the spatial and temporal patterns of change in ecosystems' attributes such as NPP [8; 10; 13]. However, there is significant variability among these models' results due to differences in formulation of ecosystem processes, underlying assumptions for their formulation in these models, and the uncertainties associated with observations used in understanding these processes [14; 15]. For assessing NPP and its spatial and temporal trends, quite often a combination of models and observational proxies (e.g., NDVI) are used [16; 17] to ensure the reliability of the results. The NDVI is largely influenced by both biophysical (e.g., vegetation cover, biomass, plant and soil moisture) and other (satellite drift, calibration uncertainties, atmospheric conditions and volcanic eruptions) factors [18], thus the NDVI trends do not present a monotonic behavior and can change in response to environmental conditions e.g., temperature and precipitation [9].