Slevin, Darren; Tett, Simon; Williams, Mat. (2016). Global GPP simulated by the JULES land surface model for 2001-2010, 2001-2010 [dataset]. University of Edinburgh. School of GeoSciences. https://doi.org/10.7488/ds/1461.
This study evaluates the ability of the Joint UK Land Environment Simulator (JULES) Land Surface Model (LSM), the land surface scheme of the UK Met Office Unified Model (MetUM), to simulate Gross Primary Productivity (GPP) at regional and global
scales for 2001--2010. Model simulations were driven with a variety of meteorological datasets and at various spatial resolutions (0.5x0.5, 1x1, 2x2 degree resolution). The meteorological datasets include:
The WATCH Forcing Data methodology was applied to the ERA-Interim reanalysis data (WFDEI) for the 1979--2012 period (Weedon et al., 2014. https://doi.org/10.1002/2014WR015638 ). WFDEI has two precipitation products, corrected using either CRU (Climate Research Unit at the University of East Anglia) or GPCC (Global Precipitation Climatology Centre) precipitation totals and are referred to as WFDEI-CRU and WFDEI-GPCC, respectively.
The PRINCETON dataset is a global 62 year near-surface meteorological dataset used for driving land surface models and was created by Princeton University's Terrestrial Hydrology Group ( http://hydrology.princeton.edu/home.php ) (Sheffield et al., 2006. https://doi.org/10.1175/JCLI3790.1 ).
JULES GPP was then compared to spatially gridded estimates of GPP from the upscaling of GPP from the FLUXNET network (FLUXNET-MTE), the MODIS sensor and the CARDAMOM framework.
GPP, Gross Primary Productivity, is the total amount of carbon uptake by plants (per unit area in unit time) and used in photosynthesis. All files are in netCDF format. There is metadata in the files. To briefly view information regarding the files, there is software on Linux called ncdump (to read the data and metadata) and ncview (to plot the data without writing computer code).
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