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• W4200515414 abstract "Earth system models (ESMs) have been widely used to simulate global terrestrial carbon fluxes, including gross primary production (GPP) and net primary production (NPP). Assessment of such GPP and NPP products can be valuable for understanding the efficacy of certain ESMs in simulating the global carbon cycle and future climate impacts. In this work, we studied the model performance of 22 ESMs participating in the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6) by comparing historical GPP and NPP simulations with satellite data from MODIS and further evaluating potential model improvement from CMIP5 to CMIP6. In CMIP6, the average global total GPP and NPP estimated by the 22 ESMs are 16% and 13% higher than MODIS data, respectively. The multi-model ensembles (MME) of the 22 ESMs can fairly reproduce the spatial distribution, zonal distribution and seasonal variations of both GPP and NPP from MODIS. They perform much better in simulating GPP and NPP for grasslands, wetlands, croplands and other biomes than forests. However, there are noticeable differences among individual ESM simulations in terms of overall fluxes, temporal and spatial flux distributions, and fluxes by biome and region. The MME consistently outperforms all individual models in nearly every respect. Even though several ESMs have been improved in CMIP6 relative to CMIP5, there is still much work to be done to improve individual ESM and overall CMIP performance. Future work needs to focus on more comprehensive model mechanisms and parametrizations, higher resolution and more reasonable coupling of land surface schemes and atmospheric/oceanic schemes." @default.
• W4200515414 created "2021-12-31" @default.
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• W4200515414 date "2022-03-01" @default.
• W4200515414 modified "2023-10-07" @default.
• W4200515414 title "Intercomparison of global terrestrial carbon fluxes estimated by MODIS and Earth system models" @default.
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• W4200515414 doi "https://doi.org/10.1016/j.scitotenv.2021.152231" @default.
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