Satellite-observed increasing coupling between vegetation productivity and greenness in the semiarid Loess Plateau of China is not captured by process-based models

Global vegetation has experienced notable changes in greenness and productivity since the early 1980s. However, the changes in the relationship between productivity and greenness, i.e., the coupling, and its underlying mechanisms, are poorly understood. The Loess Plateau (LP) is one of China's most significant areas for vegetation greening. Yet, it remains poorly documented what changes in the coupling between productivity and greenness are and how environmental and anthropogenic factors affect this coupling in the LP over the past four decades. We investigated the interannual trend of coupling between Gross Primary Productivity (GPP) and Leaf Area Index (LAI), i.e., the GPP-LAI coupling, and its response to climate factors and afforestation in the LP using long-term remote-sensed LAI, GPP and Solar-induced Chlorophyll Fluorescence (SIF). We found a monotonically increasing trend in the GPP-LAI coupling in the LP from 1982 to 2018 (0.0043 yr(-1), p < 0.05), in which the significant trend in the northwest LP was driven by increasing soil water and landcover change, e.g., increased grassland and afforestation. An ensemble of 11 state-of-the-art ecosystem models from the TRENDY project failed to capture the observed monotonically increasing trend of the GPP-LAI coupling in the LP. The consistent projection of a decreasing GPP-LAI coupling in LP during 2019-2100 by 22 Earth System Models (ESMs) under various future scenarios should be treated with caution due to the identified inherent uncertainties in the ecosystem component in ESMs and the notable biases in the simulation of future climate conditions. Our study highlights the need to enhance the key mechanisms that regulate the coupling relationships between photosynthesis and canopy structure in indigenized ecosystem models to accurately estimate the ecosystem change in drylands under global climate change.