Abstract

Abstract. In the last decades terrestrial ecosystems have reabsorbed on average more than one-quarter of anthropogenic emissions (Le Quéré et al., 2018). However, this large carbon sink is modulated by climate and is therefore highly variable in time and space. The magnitude and temporal changes in the sensitivity of terrestrial CO2 fluxes to climate drivers are key factors to determine future atmospheric CO2 concentration and climate trajectories. In the literature, there is so far a strong focus on the climatic controls of daily and long-term variability, while less is known about the key drivers at a seasonal timescale and about their variation over time (Wohlfahrt et al., 2008). This latter temporal scale is relevant to assess which climatic drivers dominate the seasonality of the fluxes and to understand which factors limit the CO2 exchange during the course of the year. Here, we investigate the global sensitivity of net terrestrial CO2 fluxes, derived from atmospheric inversion, to three key climate drivers (i.e. global radiation and temperature from WFDEI and soil water content from ERA-Interim) from weekly to seasonal temporal scales, in order to explore the short-term interdependence between climate and the terrestrial carbon budget. We observed that the CO2 exchange is controlled by temperature during the carbon uptake period over most of the land surface (from 55 % to 52 % of the total surface), while radiation is the most widespread dominant climate driver during the carbon release period (from 64 % to 70 % of the total surface). As expected, soil water content plays a key role in arid regions of the Southern Hemisphere during both the carbon uptake and the carbon release period. Looking at the decadal trend of these sensitivities (1985–2016) we observed that the importance of radiation as a driver is increasing over time, while we observed a decrease in sensitivity to temperature in Eurasia. Overall, we show that flux temporal variation due to a specific driver has been dominated by the temporal changes in ecosystem sensitivity (i.e. the response of ecosystem to climate) rather than to the temporal variability of the climate driver itself over the last decades. Ultimately, this analysis shows that the ecosystem response to climate is significantly changing both in space and in time, with potential repercussion on the future terrestrial CO2 sink and therefore on the role that land may play in climate trajectories.

Highlights

  • Just over one-quarter of the anthropogenic emissions of carbon dioxide (CO2) on average are reabsorbed by terrestrial ecosystems (Le Quéré et al, 2018)

  • The climate driver that controls the fluctuation of net biome productivity (NBP) in most of the Northern Hemisphere is radiation, with an increasing dominance from the weekly to seasonal temporal scale, while in the Southern Hemisphere soil water content controls NBP in the driest regions of Africa and South America, and radiation and temperature dominate elsewhere

  • Looking at the sign of the relationships between NBP and drivers, it is interesting to notice that the global maps are dominated by positive correlations between drivers and NBP, meaning that the terrestrial land sink is larger during periods with higher temperature, radiation and soil water content

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Summary

Introduction

Just over one-quarter of the anthropogenic emissions of carbon dioxide (CO2) on average are reabsorbed by terrestrial ecosystems (Le Quéré et al, 2018) This large sink is influenced by climate and by its short- and long-term variability (Beer et al, 2010; Ciais et al, 2005; Rödenbeck et al, 2018; Sitch et al, 2015). Climate change is affecting the phenological cycle of plants and, the functioning of ecosystems which in turn affect climate (Richardson et al, 2013) Due to this interrelation, model studies show that the response of land CO2 fluxes to climate drivers may heavily determine the future climate trajecto-. The large uncertainty of climate projections could be significantly improved with a better understanding of vegetation response to the climate variability observed in the past (Papagiannopoulou et al, 2017)

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