# Response of Global Terrestrial Carbon Fluxes to Drought from 1981 to 2016
## 1 Introduction  
Global terrestrial ecosystems play an important role in the carbon cycle and can absorb 25-30% of anthropogenic carbon emitted into the atmosphere [1, 2]. Understanding the trend and variability of the terrestrial carbon fluxes is critical for predicting future climate change. Terrestrial carbon fluxes are affected by a number of factors, including climate [3, 4, 5, 6], cyclones [7], atmospheric CO\({}_{2}\) fertilization [8], nitrogen deposition [9], land cover types, and land use change [10]. The intensity of terrestrial carbon flux is tightly coupled with the water cycle at different spatial and temporal scales [11, 12, 13, 14]. Recent evidence has suggested that global semi-arid ecosystems play a significant role in the trend and variability of the land CO\({}_{2}\) sink [15, 16]. The capacity of terrestrial ecosystems to sequester carbon is often dominated by water availability [17, 18, 19]. In concert with temperature increases, precipitation regimes have also changed since 1950 over a majority of land areas [20, 21]. The impacts of changing precipitation conditions on plant productivity and terrestrial carbon fluxes have attracted considerable attentions from recent studies [22, 23, 24, 25, 26, 27, 28, 29, 30]. For example, based on field flux observations, remote sensing data, and model simulations, [PERSON] et al. [22] declared that the heat and drought observed in 2003 caused a 30% reduction in the continental-scale gross primary productivity (GPP) of Europe. This climatic extreme resulted in a strong anomalous net terrestrial carbon source in the atmosphere, offsetting the accumulation of four years of net ecosystem carbon sequestration by European terrestrial ecosystems. The GPP reductions in Eastern andWestern Europe were caused by rainfall deficit and extreme heat, respectively [31]. Based on the MODIS net primary productivity (NPP) product, [PERSON] and [PERSON] [25] found that drought caused global terrestrial NPP to decrease by 0.55 Pg C yr\({}^{-1}\) over the period from 2000 to 2009. [PERSON] et al. [27] reported that NPP was positively and significantly related to water conditions at the global scale. [PERSON] et al. [28] investigated the impact of drought on carbon sequestration in China's terrestrial ecosystems from 2000 to 2011 using the process-based Boreal Ecosystem Productivity Simulator (BEPS) driven by remotely sensed leaf area index (LAI). They found that national and regional total net ecosystem productivity (NEP) anomalies were correlated with the severity of drought indicated by using the mean annual standard precipitation index (SPI), especially in Northwest China, North China, Central China, and Southwest China. These findings together highlight the importance of understanding the response of the terrestrial carbon cycles to water conditions. However, few studies have focused on the relative response level of terrestrial carbon fluxes to drought. Drought has both immediate and lagged effects on terrestrial carbon fluxes and vegetation growth [18; 29; 32; 33; 34; 35]. Under drought conditions, both carbon assimilation and the amount of carbon released by ecosystem respiration (ER) usually decrease. The direct response of NEP to drought depends on the sensitivity of GPP and ER to the time of onset, severity, and duration of drought. During the initial stage of water depletion, vegetation is able to use deep soil water and maintain GPP at normal levels while ER starts to decrease as superficial soil layers dry out. NEP decreases marginally or even slightly increases. The further depletion of deep soil water significantly limits photosynthesis and results in a larger decrease in GPP than that in ER [31], and therefore in a decrease in NEP [36; 37; 38]. Based on long-term global AVHRR NDVI data, [PERSON] et al. [29] reported that arid and humid biomes responded to drought at shorter time scales, while semi-arid and sub-humid ones responded to drought at longer time scales. A simulation using the BEPS model over the period from 2000 to 2011 by [PERSON] et al.