Community Atmosphere-Biosphere-Land Exchange (CABLE) is quite similar to some other land surface models, such as CLM [Oleson et al., 2010] and ORCHIDEE [Krinner et al., 2005] in representing the range of biophysical processes for climate simulations. A study by Abramowitz  showed that the performance of CABLE also is quite similar to CLM and ORCHIDEE for simulating the surface fluxes from a range of sites globally. Some of major differences between CABLE, CLM or ORCHIDEE are: CABLE uses the theory developed by Goudriaan and van Larry  for simulating radiative transfer in plant canopies, where CLM and ORCHIDEE use the two-stream approximation [Sellers et al., 1996]. CABLE uses Ball-Berry-Leuning stomatal model [Leuning, 1995], whereas CLM and ORCHIDEE use the Ball-Berry stomatal model [Ball et al., 1987]. CABLE as used in this study does not simulate dynamics of carbon pools, whereas CLM and ORCHIDEE do. There are also differences in representing the land surface, such as the classification of plant functional types, number of soil layers and soil depth and so on.
 CABLE consists of five submodels: radiation, canopy micrometeorology, surface flux, soil and snow, and ecosystem respiration. The radiation submodel computes the net diffuse and direct beam radiation absorbed by each of two big leaves and by soil surface in the visible, near infrared and thermal radiation, and the surface albedo for visible and near infrared radiation. The canopy micrometeorology submodel computes canopy roughness length, zero-plane displacement height and aerodynamic transfer resistance from the reference height or the height of the lowest layer in a climate model to within canopy air space or soil surface. The surface flux submodel computes fluxes of latent and sensible heat, and net canopy photosynthesis. The soil and snow model computes temperature and moisture at different depths in soil, snow age, snow density and depth, and snow covered surface albedo when snow presents. The ecosystem respiration submodel computes the nonleaf plant tissue respiration, soil respiration and net ecosystem CO2 exchange.
 The structure of CABLE model codes is dictated by the relationship of inputs/outputs between different submodels. A submodel has to be executed first if its outputs are used as inputs to another submodel. In CABLE, the radiation submodel is called first, as it provides the estimates of the absorbed radiation by plant canopies and soil for the surface flux submodel. The surface flux submodel is called before soil and snow submodel, as the surface flux submodel provides the estimates of water extraction and ground heat flux, which are required in the soil and snow submodel. The ecosystem respiration model is called last because soil respiration depends on soil temperature and moisture in the rooting zone.
 Within the surface flux submodel, there are two nested iteration: stability iteration loop and leaf temperature iteration loop. The canopy temperature iteration loop is nested within the stability iteration loop, because calculation of stability of the airflow between the reference height and the air space within the canopy depends on surface (canopy and soil) fluxes of latent and sensible heat, latent and sensible heat fluxes are calculated within the canopy temperature iteration loop.
 At the first stability iteration, neutral conditions are assumed, temperature and specific humidity of the air within the canopy space (Ta, qa) are assumed to be equal to their respective values at the reference height (Tref, qref), and the fluxes of latent heat, sensible and ground heat, and net canopy photosynthesis are calculated in the canopy temperature iteration loop, then the stability parameter is updated using the estimated surface fluxes of latent and sensible heat, and aerodynamic resistance is calculated, and the values of Ta and qa are updated, all the surface fluxes are recalculated with reference to the in-canopy variables in the canopy temperature iteration loop. Iterations are terminated only when the specified convergence criteria are met for both loops.
 Following the calculation of net photosynthesis, latent, sensible and ground heat fluxes and surface temperature, the only prognostic variable within the surface flux submodel, canopy water storage, is updated.
 The soil and snow submodel updates the soil moisture and temperature for all layers using the fluxes calculated in the surface flux submodel. If snow present, snow model will be used to update the density and thickness of each snow layer, and ground surface albedo. Finally the ecosystem respiration model is used to compute respiration by woody tissue and root, soil respiration and net ecosystem CO2 exchange (NEE).
 Details of the model have been presented by Raupach et al. , Wang and Leuning , and Kowalczyk et al. . Only a brief description of each submodel is given below.
A1. Radiation Submodel
 The radiation submodel has been described in detail by Wang and Leuning , only the estimates of the radiation absorbed by vegetation canopy and soil are presented here.
 Absorption of visible (j = 1) or near infrared (j = 2) radiation by sunlit (i = 1) or shaded (i = 2) leaves within the canopy, Qi,j is calculated as
where Ib,j and Id,j are the direct beam and diffuse radiation flux density within wave band j in W m−2, αb,j and αd,j are the canopy reflectance for direct beam and diffuse radiation in wave band j (see Wang  for further details), ωf,j is the leaf scattering coefficient (transmittance + reflectance) in wave band j, kb and kd are the extinction coefficients of direct beam and diffuse radiation of the canopy if all leaves are black, i.e., ωf,j = 0, and k*b,j and k*d,j are the extinction coefficient of direct beam and diffuse radiation for the canopy, and are calculated as kb and kd.
 The function χ(x) is defined as
For thermal radiation (j = 3), the radiation absorbed by the sunlit or shaded leaves are calculated as
where σ is the Stefan-Boltzman constant (5.67 × 10−8 W m−2 K−4), Ls is the incoming long wave radiation from the sky (W m−2) and Lc is the upwelling radiation from the land surface when the vegetation canopy temperature (W m−2), Tc, is equal to the temperature of the air within canopy space (Ta). ɛa and ɛf are the emissivities of the surface air and leaf, respectively.
 The total radiation (short-wave and long-wave radiation) absorbed by the soil, Qsoil, is
where Ts,o is the soil surface temperature in K and ɛs is the emissivity of the soil surface.
A2. Canopy Micrometeorology Submodel
 This submodel computes surface roughness length, zero-plane displacement height and aerodynamic resistance using the theory developed by Raupach  and Raupach [1989a, 1989b] as implemented in SCAM [Raupach et al., 1997].
 The surface roughness length (z0 in m) and zero-plane displacement height (d in m) are two important parameters in the model for estimating the aerodynamic transfer resistance within the canopy. They are calculated as
where h is the canopy height (m), κ is the von Karman constant (=0.4), uh is the mean wind speed at the canopy height, u* is the friction velocity (m s−1), u*/uh is rather constant for many natural surfaces, and is approximated as
where cs is the substrate drag coefficient, cr is element drag coefficient and L is the canopy leaf area index that is not buried by snow [see Raupach et al., 1997]. Parameter a is the maximal value of u*/uh, which is equal to 0.3 in our model. In our model, cs = 0.003, cr = 0.3.
 ψh in equation (A7) is the roughness-sublayer influence function, and is calculated as
where cw is an empirical constant (=2).
 The zero-plane displacement height in equation (A7) is calculated as
where cd is an empirical constant (=15) [see Raupach et al., 1997].
 The friction velocity, u* is related to the wind speed (uref) at the reference height (zref) as
where z0 and d are height of surface roughness length (m) and zero-plane displacement height (m), ΨM is the integral stability function for momentum, LMO is the Monin-Obhukov length (m). The stability parameter, ζ can be estimated as
The stability function, ΨM is calculated using the Businger-Dyer form for unstable cases and the Webb form for stables cases [see Garratt, 1992]. The stability loop is considered to have converged when the estimates of ξ between two successive iterations differ by less than 1%.
 CABLE uses the Localized Near Field (LNF) theory to describe the turbulent transfer within and above the canopy [see Raupach, 1989a, 1989b]. LNF accounts for the fact that eddies responsible for most scalar transfer in a canopy have a vertical length scale close to the canopy height. The scalar (water, heat and CO2) concentration profile as a result of turbulent transfer at height z in the air, C(z), is composed of the “far-field” and “near-field” contributions, i.e., C(z) = Cf + Cn. Two turbulence properties, the vertical velocity standard deviation σw(z) in m s−1, and the Lagrangian timescale, TL(z) in s are used to describe compliance of the “far-field” component with a gradient diffusion relationship between flux and concentration. The aerodynamic transfer resistance from the air space within the canopy to the reference level zref, ra, is derived as:
The aerodynamic resistance from the soil surface to the air space within the canopy, rg (in s m−1), is given by
where z0s is the soil roughness length in m and fsp is the sparseness factor, varying from 0 for bare ground to 1 for medium to high dense canopy (L > 1.1) [see Raupach et al., 1997].
 The aerodynamic transfer resistance, ra, can be used to estimated the temperature (Ta) and specific humidity (qa) of the air within the canopy from the values at the reference height (Tref, qref) if the surface fluxes required for estimating the stability function are given (see Raupach et al.  for further details).
A3. Surface Flux Submodel
 This submodel computes the latent and sensible heat fluxes from canopy (λEc, Hc) and soil (λEs, Hs), ground heat flux (Hg), net canopy photosynthesis (Ac) and updates canopy water storage (Wc) at each time step.
 Based on the principle of energy and mass conservation, we set up two sets of equations, one for the canopy net photosynthesis (Ac,i) and stomatal conductance (Gs,i), and the other for the canopy energy fluxes (λEc, Hc). Further details about the equations are provided by Wang and Leuning . These two sets of equations are solved numerically by iteration for estimating the surface fluxes for a given value of air temperature (Ta) and specific humidity (qa) of the air within the canopy [see Wang and Leuning, 1998; Kowalczyk et al., 2006]. At the first iteration, the canopy temperature (Tc) is set to the value of Ta, and the value of Tc is used to calculate all the temperature-dependent photosynthetic parameters, such as maximum carboxylation rate (vcmax), potential electron transport rate (jmax). Those parameters values are used in solving the first set of equations for net canopy photosynthesis (Ac,i) and stomatal conductance (Gs,i). The estimate of Gs,i is used to solve the second set of equation of energy fluxes and update Tc. The iteration terminates when the difference between the estimates of Tc between two successive iterations is <0.05 K [see Kowalczyk et al., 2006].
 The latent and sensible heat fluxes are calculated as a linear combination of the fluxes from the dry canopy and the wet canopy, i.e.,
where λ is the latent heat of vaporization (J kg−1), λEdry and Hdry are the latent and sensible heat flux of the dry canopy in W m−2. The corresponding λEwet and Hwet are for the wet canopy, all in W m−2. The canopy wet fraction, fwet, is calculated as
where Wc is canopy water storage (mm), and Wcmax is the maximal canopy water storage and is calculated as 0.1L.
 Canopy photosynthesis and transpiration is coupled through stomatal conductance that is modeled using the following model [Ball et al., 1987; Leuning, 1990]:
where G0,i is the residual or cuticular conductance in mol m−2 s−1, Ds,i, Cs,i and Ac,i are the water vapor pressure deficit at the leaf surface (Pa), CO2 concentration at the leaf surface in mol mol−1 and net photosynthesis of leaf i in mol m−2 s−1, respectively; Γ is the CO2 compensation point of photosynthesis in mol m−1 and is a function of canopy temperature (Tc) [see Leuning, 1990], a1 and D0 are two model parameters (a = 4 for C4 plant and = 9 for C3 plants), D0 = 1500 Pa), fwsoil is the influence of soil water limitation on stomatal conductance, and is calculated as
where βv is the model parameter, and froot,m is the fraction of root mass in soil layer m, and θm is the volumetric soil water content of soil layer m, θwilt and θfc are the volumetric soil water contents at wilting point and field capacity, respectively.
 For deciduous forest, the maximal carboxylation rate (vcmax) and the maximal potential electron transport rate of a leaf at the top of the canopy at a leaf temperature of 298 K also depend on leaf phenology that is modeled as a function of soil temperature at 25 cm depth [see Wang et al., 2007]. That is
where vcmax and jmax are maximum carboxylation rate and maximal potential electron transport rate of a mature leaf at the canopy top during the middle of growing season, both in μmol m−2 s−1, Ts,25 is the soil temperature at 25 cm depth from the soil surface (K), and Tminvj and Tmaxvj are two model parameters (K).
 The latent (Es), sensible (Hs) and ground (G) heat fluxes from the soil are calculated as follows:
where ws is the soil wet factor, Δqs is the difference of the specific humidity at soil surface and the air within canopy (kg kg−1), ρa is the density of air (kg m−3), Ts,1 is the surface soil layer temperature (K), Hg is the ground heat flux in Wm−2, and is calculated using the equations as described by Bonan .
 The soil wet factor ws is calculated as
where βs is an empirical model parameter, where θ1 is volumetric soil water content of the surface soil layer.
 For the wet canopy, the amount of the wet canopy, Wc in mm, is calculated as
The term min(0, (1 − fwet)Edry) in equation (A26) represents the amount of dew formed onto the canopy surface, and PI is the canopy interception of atmospheric precipitation (mm s−1) and is calculated as
where P is the liquid rainfall (mm/Δt) and Δt is the time step (s).
A4. Soil Submodel
 The soil is a heterogeneous system composed of three constituent phases, namely the solid, water and air [Hill, 1982]. Water and air compete for the same pore space and change their volume fractions due to precipitation, evapotranspiration, snowmelt and drainage. Soil hydraulic and thermal characteristics depend on the soil type as well as frozen and unfrozen soil moisture content. In this model, soil moisture is assumed to be at ground temperature, so there is no heat exchange between the moisture and the soil due to the vertical movement of water. Volumetric soil moisture, θm, is considered in terms of liquid and ice components, i.e., θm = θm,l + θm,i. Ice decreases soil porosity but liquid moisture can move through remaining unfrozen soil pores.
 Each soil type in our model is described by its saturation content θsat, wilting content θwilt, and field capacity (θfc). θsat is equal to the volume of all the soil pores. Here, an additional variable, actual saturation θas, is used. Actual saturation excludes the pores filled with ice, θas = θsat − θi.
 The one-dimensional conservation equation for soil moisture in the absence of ice is described by
where θ is the volumetric soil moisture content (m3 m−3), and q is the kinematic moisture flux (m s−1, positive downward), Fw(z) is the water uptake by plants from depth z (m s−1), z is depth into the soil (m). From Darcy's law, the moisture flux is given by:
where K is the hydraulic conductivity (m s−1), and D is the soil moisture diffusivity (m2 s−1), and is equal to −K∂ψ/∂θ, where ψ is the water potential of the soil (m).
 Combining equations (A28) and (A29), we have
with the two boundary conditions of
where qin is the water flux infiltrated downward through the soil surface (m s−1), Es is the soil evaporation (m s−1), cdrain is soil drainage coefficient, Z is the depth of the bottom layer (m), Fw(z) is the contribution from soil depth z to dry canopy transpiration (Edry) by root uptake, and is proportional to froot,m(θ − θwilt)dz. When the amount of dry canopy (Edry) cannot be met by root uptake, Edry is reduced within the leaf temperature iteration loop within the surface flux submodel, and the leaf energy balance is recalculated until Edry = ∫0ZFw(z)dz within the loop.
 The relationship between hydraulic conductivity or soil water potential and soil volumetric moisture content are calculated as
Parameter b varies with soil texture [see Campbell, 1974; Clapp and Hornberger, 1978].
 The equation governing heat transport in soil is
where ρs is the density (kg m−3), cs is specific heat (J kg−1 K−1), κs is thermal conductivity (W m−1 K−1) of the soil. The volumetric heat capacity (ρscs) is calculated as the weighted sum of the heat capacity of dry soil, liquid water and ice. The boundary conditions for equation (A35) are:
κs plays a crucial role in determining the depth of freezing/thawing as it varies by about one order of magnitude as the soil approaches saturation point and can increase further when soil ice is present [see Johansen, 1975].
 The presence of water or ice in the soil can alter soil's thermal properties and thus modify soil temperature by several degrees. To take this into account, we calculate soil thermal properties at each time step. The snow model has been described by Kowalczyk et al. .
 To solve equations (A30) and (A35) numerically, the soil is divided into six layers, and the thickness of each layer from the top layer is 0.022 m, 0.058 m, 0.154 m, 1.085 m and 2.872 m. Only the top layer contributes to soil evaporation and plant roots can extract water from all layers, depending on the amount of available soil water and the fraction of plant roots in each layer.
A5. Ecosystem Respiration Submodel
 The ecosystem respiration submodel calculates the respiration of wood and root and soil. They are calculated as
where Cwood and Croot are the amounts of carbon in wood and roots (g C m−2), respectively; rwood, rroot and rsoil are the respiration rates of wood, root and soil (at Ta = 20°C for wood or s = 285K for root and soil) in μmol m−2 s−1 (g C)−1 for wood and root, and in μmol m−2 s−1 for soil; they are biome-specific model parameters [see Kowalczyk et al., 2006]. s is the root-mass weighted mean of soil mean temperature (K) and s is the root-mass weighted mean of soil water content, and is calculated as
where froot,m is the fraction of root mass in soil layer m, θm is the volumetric soil water content of soil layer m, and θwilt and θfc are the volumetric water content at wilting point and field capacity, respectively. The functions f1 and f2 are calculated as
The function f1 is based on the work of Tjoelker et al.  and f2 is based on the work of Reichstein et al. , where b1 is a biome-dependent model parameter (μmol C m−2 s−1), and the empirical constants b2, b3, Ts0 and θs0 are equal to 52.4 (K), 285 (K), 227.2 (K) and 0.16, respectively [see Reichstein et al., 2002]. Tavg is the annual mean soil temperature (K), and is assumed to be equal to the temperature of the deepest soil layer (Ts,6).
 The net ecosystem exchange of CO2, NEE, is then calculated as
Inputs to this submodel are temperature of the air within the canopy (Ta), root-mass weighted mean temperature and moisture of the soil (s, s), and the amount of carbon in root (Croot in g C m−2) and wood (Cwood in g C m−2), and the output of this submodel is NEE.