期刊
GEOSCIENTIFIC MODEL DEVELOPMENT
卷 10, 期 7, 页码 2651-2670出版社
COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/gmd-10-2651-2017
关键词
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资金
- NASA
- Natural Environment Research Council (NERC)
- UK National Centre for Earth Observation (NCEO)
- NERC [nceo020005, NE/K016253/1, nceo020004, NE/K002619/1] Funding Source: UKRI
- Natural Environment Research Council [NE/K002619/1, nceo020005, NE/K016253/1, nceo020004] Funding Source: researchfish
This study evaluates the ability of the JULES land surface model (LSM) to simulate gross primary productivity (GPP) on regional and global scales for 2001-2010. Model simulations, performed at various spatial resolutions and driven with a variety of meteorological datasets (WFDEI-GPCC, WFDEI-CRU and PRINCETON), were compared to the MODIS GPP product, spatially gridded estimates of upscaled GPP from the FLUXNET network (FLUXNET-MTE) and the CARDAMOM terrestrial carbon cycle analysis. Firstly, when JULES was driven with the WFDEI-GPCC dataset (at 0.5 degrees x 0.5 degrees spatial resolution), the annual average global GPP simulated by JULES for 2001-2010 was higher than the observation-based estimates (MODIS and FLUXNET-MTE), by 25 and 8 %, respectively, and CARDAMOM estimates by 23 %. JULES was able to simulate the standard deviation of monthly GPP fluxes compared to CARDAMOM and the observation-based estimates on global scales. Secondly, GPP simulated by JULES for various biomes (forests, grasslands and shrubs) on global and regional scales were compared. Differences among JULES, MODIS, FLUXNET-MTE and CARDAMOM on global scales were due to differences in simulated GPP in the tropics. Thirdly, it was shown that spatial resolution (0.5 degrees x 0.5 degrees, 1 degrees x 1 degrees and 2 degrees x 2 degrees) had little impact on simulated GPP on these large scales, with global GPP ranging from 140 to 142 PgCyear(-1). Finally, the sensitivity of JULES to meteorological driving data, a major source of model uncertainty, was examined. Estimates of annual average global GPP were higher when JULES was driven with the PRINCETON meteorological dataset than when driven with the WFDEI-GPCC dataset by 3 PgCyear(-1). On regional scales, differences between the two were observed, with the WFDEI-GPCC-driven model simulations estimating higher GPP in the tropics (5 degrees N-5 degrees S) and the PRINCETON-driven model simulations estimating higher GPP in the extratropics (30-60 degrees N).
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