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Drought risk of global terrestrial gross primary productivity in recent 40 years detected by a remote sensing-driven process model

Citation

He, Qiaoning et al. (2020), Drought risk of global terrestrial gross primary productivity in recent 40 years detected by a remote sensing-driven process model, Dryad, Dataset, https://doi.org/10.5061/dryad.q573n5tgb

Abstract

Gross primary productivity (GPP) is the largest flux in the global terrestrial carbon cycle and affected by multiple factors. In recent decades, drought has significantly impacted global terrestrial GPP and been projected to occur with increasing frequency and intensity. However, the drought risk of global terrestrial GPP has not been well investigated. In this study, global terrestrial GPP over the period from 1981 to 2016 was simulated with the process-based Boreal Ecosystem Productivity Simulator (BEPS) model. Then, the drought risk of terrestrial GPP was quantified as the product of frequency of drought and reduction of GPP caused by drought, which were determined using the standardized precipitation evapotranspiration index (SPEI). During the study period, the drought risk of terrestrial GPP exhibited detectable spatial heterogeneity, high in southeastern United States, most of South America, southern Europe, central and eastern Africa, eastern and southeastern Asia, and eastern Australia. In these regions, the maximum reduction of GPP might be above 30% in drought years relative to that in normal years. The drought risk of GPP was low at high latitudes of the Northern Hemisphere, in which terrestrial GPP increased slightly in drought years. The spatial pattern of the drought risk of GPP simulated by the BEPS model was close to that of FLUXCOM GPP, which was scaled from tower observations with a machine learning algorithm forced by remote sensing and meteorological data. This study advances our understanding on the impact of drought on terrestrial GPP over the globe.