Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2016-214
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Model evaluation paper
21 Sep 2016
Review status
A revision of this discussion paper was accepted for the journal Geoscientific Model Development (GMD) and is expected to appear here in due course.
Global Evaluation of Gross Primary Productivity in the JULES Land Surface Model
Darren Slevin1, Simon F. B. Tett1, Jean-François Exbrayat1,2, A. Anthony Bloom1,2,3, and Mathew Williams1,2 1School of GeoSciences, The University of Edinburgh, Crew Building, Alexander Crum Brown Road, Edinburgh, EH9 3FF, UK
2National Centre for Earth Observation, The University of Edinburgh, Crew Building, Alexander Crum Brown Road, Edinburgh, EH9 3FF, UK
3Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Abstract. This study evaluates the ability of the JULES Land Surface Model (LSM) to simulate Gross Primary Productivity (GPP) at 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, JULES was found to simulate interannual variability (IAV) at global scales. When JULES was driven with the WFDEI-GPCC dataset (at 0.5º × 0.5º spatial resolution), it was found that 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 %. Secondly, GPP fluxes simulated by JULES for various biomes (forests, grasslands and shrubs) at global and regional scales were compared. It was found that differences between JULES, FLUXNET-MTE, MODIS and CARDAMOM at global scales were mostly due to differences in the tropics with CARDAMOM performing better than JULES in this region. Thirdly, it was shown that spatial resolution (0.5º × 0.5º, 1º × 1º and 2º × 2º) had no impact on simulated GPP on these large scales. 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 4 PgC year−1. At regional scales, differences between two were observed with the WFDEI-GPCC driven model simulations estimating higher GPP in the tropics (at 5º N–5º S) and the PRINCETON driven model simulations estimating higher GPP in the extratropics (at 30º N–60º N).

Citation: Slevin, D., Tett, S. F. B., Exbrayat, J.-F., Bloom, A. A., and Williams, M.: Global Evaluation of Gross Primary Productivity in the JULES Land Surface Model, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-214, in review, 2016.
Darren Slevin et al.
Darren Slevin et al.

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