Assessing present and future vegetation dynamics on the Qinghai–Tibet Plateau using CMIP6 Earth System Models

Abstract

Vegetation dynamics on the Qinghai–Tibet Plateau (TP) regulate energy, water, and carbon fluxes and are closely linked to the stability of fragile alpine ecosystems. Evaluating the ability of Coupled Model Intercomparison Project Phase 6 (CMIP6) Earth System Models (ESMs) to simulate TP vegetation dynamics is therefore essential for interpreting future ecosystem responses to climate change. Here, we evaluated historical vegetation simulations from 33 CMIP6 ESMs during 1982–2014 using GLASS vegetation products, MODIS-derived vegetation-cover data, and CN05.1 meteorological observations. Based on a reproducible ranking that integrated historical LAI scalar performance and spatial-pattern skill, the 10 highest-ranked models with complete future LAI, GPP, and NPP outputs under all three SSP scenarios were selected to construct a performance-screened multi-model ensemble mean (MME 10 ). Results show that CMIP6 models generally reproduce the seasonal cycle and broad southeast–northwest spatial gradient of LAI across the TP. However, the full 33-model ensemble overestimates regional mean growing-season LAI by 146.8% relative to GLASS during 1982–2014, and most models delay the seasonal LAI peak by 1–2 months. Historical evaluation against the GLASS GPP and NPP products reveals that MME 10 reduces the spatial root mean square error (RMSE) by 17.5% for GPP and 13.2% for NPP relative to the corresponding full available ensembles. MME 10 projections indicate consistent increases in growing-season LAI, GPP, and NPP across all SSPs, with the strongest enhancement under SSP5-8.5. Under this scenario, the ensemble-mean values are projected to increase by 120.3%, 119.8%, and 135.0%, respectively, over 2081–2100, relative to the 1982–2014 historical means. This study provides a region-specific benchmark for evaluating CMIP6 simulations of vegetation dynamics and productivity over the TP and supports the interpretation of future ecosystem changes in fragile high-altitude environments.