SiB3(Simple Biosphere Model 3)

The soil representation is similar to that of CLM (Dai et al.,2003), with 10 soil layers and soil column depth of 10 meters.Root distribution follows Jackson et al. (1996). SiB has been updated to include prognostic calculation of temperature, moisture and trace gases in the canopy air space (Baker et al., 2003; Vidale and Stöckli, 2003). We refer to this version of the code as SiB3.

improved from SiBGPP

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Initial contribute: 2019-04-25

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Detailed Description

English {{currentDetailLanguage}} English

 

The simple biosphere model (SiB) is a land-surface parameterization scheme originally used to simulate biophysical processes in climate models (Sellers et al., 1986), but later adapted to include ecosystem metabolism (Denning etal.,1996;Sellersetal.,1996a). SiB is a model that is useful to meteorologists for its ability to simulate exchanges of mass, energy and momentum between the atmosphere and terrestrial biosphere, and useful to ecologists for its ability to do so in a process-based framework that allows for simulation of explicit biophysical mechanisms. The parameterization of photosynthetic carbon assimilation is based on enzyme kinetics originally developed by Farquhar et.al (1980),that are linked to stomatal conductance and thence to the surface energy budget and atmospheric climate (Collatz et al.,1991, 1992; Sellers et al., 1996a; Randall et al., 1996).

The soil representation is similar to that of CLM (Dai et al.,2003), with 10 soil layers and soil column depth of 10 meters.Root distribution follows Jackson et al. (1996). SiB has been updated to include prognostic calculation of temperature, moisture and trace gases in the canopy air space (Baker et al., 2003; Vidale and Stöckli, 2003). We refer to this version of the code as SiB3.

Model photosynthesis rate is tightly coupled to total latent heat flux through transpirational losses of moisture through stomates. Photosynthesis is calculated as the minimum of rate-limitation by light, enzyme kinetics, and electron transport (Collatz et al., 1991; Sellers et al., 1992). Photosynthesis is further scaled downward from an optimum rate by limitation imposed by temperature, relative humidity and moisture availability in the soil (Sellers et al., 1992). Leaf-level temperature humidity and internal CO 2 concentration are coupled via the Ball–Berryprocess(Balletal.,1987)and solved simultaneously. Moisture availability, defined by the combination of root density and soil water concentration in individual model soil layers, imposes a fundamental constraint on photosynthesis and hence evaporation. Commonly, models have defined water availability in terms of soil depth or root density alone, which is unrealistic when compared to actual plant behaviour. We find that coupling root and reservoir characteristics (Baker et al., 2008) provides a more realistic simulation framework.

For this analysis, we ran a global simulation of SiB on a 1 × 1 degree cartesian grid. Vegetation type is determined by maps as described in DeFries and Townshend (1994), and soil character is specified by IGBP (Global Soil Data Task Group, 2000). In this simulation, SiB3 uses a 10-min timestep forced with 6-hourly regridded meteorological analysis products from the National Centers for Environmental Prediction (NCEP Reanalysis-2; Kalnay et al., 1996; Kanamitsu et al., 2002) interpolated to the model timestep for the years 1983–2006. SiB3 ingests temperature, pressure, precipitation, wind and radiation as forcing variables. Vegetation phenology is provided by the GIMMSg NDVI product (Brown et al., 2004; Tucker et al., 2005; Pinzon et al., 2006) which is used to calculate Leaf Area Index (LAI) and fraction of Photosynthetically Active Radiation absorbed (fPAR) following Sellers et al. (1996b).

Reanalysis products such as NCEP have known biases in precipitation (i.e. Costa and Foley, 1998) and other variables (Zhao and Running, 2006; Zhang et al., 2007a). As precipitation can be expected to have considerable influence on photosynthetic processes, we scale the NCEP precipitation to a data set that incorporates satellite and surface observations, in this case the Global Precipitation Climatology Project (GPCP; Adler et al., 2003). Using monthly precipitation values from GPCP, we scale the NCEP precipitation for consistency. We do not create precipitation events, although we may remove precipitation if the GPCP product indicates no precipitation at alocation foragiven month.

The model was initialized with saturated soil, and the entire 24 yr period (1983–2006) was simulated twice as a spinup, with the model re-initialized with ending (31 December 2006) model state at 1 January 1983. Ecosystem respiration was scaled to obtain annual carbon balance following Denning et al. (1996).Model diagnostics were output as monthly averages on the global grid, and subsampled for NA.

 

 

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wzh (2019). SiB3(Simple Biosphere Model 3), Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/1b2739f0-6194-4706-89ec-4c2f06c5d034
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Contributor(s)

Initial contribute : 2019-04-25

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