Multi‐model analysis of climate impacts on plant photosynthesis in China during 2000–2015

Abstract

Differences, arising from differences in gross primary production (GPP) model structures and driving forces, have fuelled arguments concerning interannual changes of GPP in China since 2000. To better investigate the interannual variability of GPP and its covariance with climate factors in China, this study adopted a multi‐model analysis based on three GPP models (i.e., Terrestrial Ecosystem Carbon flux model [TEC], Breathing Earth System Simulator model [BESS], and MOD17 GPP model). The results show that annual GPP in China increased by 0.021–0.057 Pg C year−1 from 2000 to 2015 attributable to atmospheric‐CO2 fertilization effects and favourable climate change, that is, increasing precipitation (Pr) and temperature (Ta). However, northern China and southern China had a large difference in the amplitude of these GPP changes; annual GPP increased by 0.017–0.039 Pg C year−1 in northern China but only 0.001–0.018 Pg C year−1 in southern China. Northern China and southern China occupy contrasting climate zones and this contrast produced different interannual variability of GPP through different mechanisms. Northern China has a dry climate with GPP changes sensitive to Pr. As a result, more Pr along with higher Ta in northern China produced the strong uptrend of GPP from 2000 to 2015. In contrast, southern China has a wet climate with its GPP sensitive to solar radiation and Ta. For the interval of 2000–2015, decreasing radiation plus drought exerted a negative influence on GPP in southern China. This study highlights the diverse mechanisms in which climate change affects GPP in dry and wet climate zones. A robust multi‐model analysis is preferred to reduce uncertainties arising from a single GPP model and its driving data.

Improving the Gross Primary Production Estimate by Merging and Downscaling Based on Deep Learning

“…In the deserts of the northwest, most areas of the Qinghai-Tibet Plateau, and the grasslands in central and western Inner Mongolia, the plant growing season is relatively short due to water stress and low-temperature constraints, which leads to low productivity and even the lowest GPP. Overall, GPP decreases from southeast to northwest and coastal to inland, consistent with current research results [56][57][58][59]. The spatial distribution of GPP is highly compatible with precipitation in summer, indicating that precipitation is an important factor affecting the distribution of GPP in China.…”

Spatiotemporal variations of water productivity for cropland and driving factors over China during 2001–2015

“…The BESS GPP and ET data have been evaluated and used in many studies (Chen and Zhang, 2019;Stocker et al, 2019;Wei et al, 2019;Yan et al, 2019). 8-day BESS GPP and ET data were comprehensively evaluated by the FLUXNET2015 dataset at global scale (Jiang and Ryu, 2016), which confirmed that both 8-day BESS GPP and ET data showed comparable performance (R 2 = 0.67 and 0.62, respectively) with global FLUXNET observations (113 sites).…”