Plant Canopy Parameters

Overview

The plant canopy model (PCM) embedded in PALM can be used to simulate the effect of vegetation canopies on a turbulent flow.
Thereby, the canopy is modeled as a porous viscous medium that removes momentum from the flow (Shaw & Schumann, 1992; Watanabe, 2004), and acts as source/sink for heat, humidity, or passive scalar. The presentation Canopy model provides detailed information on canopy-flow theory and the functionality of the canopy model.

The PCM is enabled by adding the NAMELIST plant_canopy_parameters with appropriate parameters to the INPUT parameter file (<jobname>_p3d). Available parameters are listed below.

With enabled PCM, the plant canopy by default covers the surface of the entire computational domain (parameter canopy_mode = 'homogeneous'). The minimum set of parameters to be used with this mode are:

to prescribe the vertical distribution of leaf area density.
Alternatively, the plant canopy can be three-dimensionally customized, by either providing:

  • a NetCDF input file (<jobname>_static, in same location as <jobname>_p3d, available from r2746) with 3D information of leaf area density or
  • user-defined code (see user interface guide, and subroutine user_init_plant_canopy.f90 under trunk/SOURCE directory)

The attached test_canopy example includes:

  • INPUT
    • test_canopy_p3d: ASCII parameter file
    • test_canopy_static: NetCDF static-information file with leaf area information (so-called static driver that could also include other information, e.g. topography data)
  • create_basic_static_driver.py: Simple python script that was used to generate the NetCDF file test_canopy_static.

This simulation setup (canopy_mode = 'block' or 'read_from_file_3d') reproduces the results of Shaw & Schumann (1992).


CAUTION: Independently of the method, PALM does not appropriately represent plant canopy on a vertically stretched grid, since this is not intended. We strongly recommend to use grid stretching well above the plant canopy!



Parameter list

NAMELIST group name: plant_canopy_parameters

Parameter Name FORTRAN Type Default Value Explanation

alpha_lad

R

9999999.9

Dimensionless coefficient required for constructing the leaf area density (LAD) profile, using following beta probability density function (following Markkanen et al. (2003)):

\[ f_{PDF}(\frac{z}{H},\alpha,\beta) = \frac{(\frac{z}{H})^{\alpha-1}\;(1-\frac{z}{H})^{\beta-1}}{\int_{0}^{1}\;(\frac{z}{H})^{\alpha-1}\;(1-\frac{z}{H})^{\beta-1}\;d(\frac{z}{H})}, \]

where z is the height above ground, H is the canopy height, and alpha (alpha_lad) and beta (beta_lad) are the coefficients to be prescribed. The actual leaf area density values follow from:

\[ LAD(z,\alpha,\beta) = LAI * f_{PDF}(\frac{z}{H},\alpha,\beta) * H, \]

with the leaf area index LAI (LAI is the vertical integral over the LAD profile) being prescribed by canopy parameter lai_beta.

lai_beta has to be set to a non-zero value in order to use the beta probability density function for the LAD-profile construction. alpha_lad steers together with beta_lad the vertical distribution of leaf area within the canopy volume. Values for alpha_lad must be greater than zero. Increasing alpha_lad moves the leaf area more towards the canopy top.

Note:
The LAD profile can also be constructed by prescribing vertical gradients (lad_vertical_gradient_level, lad_vertical_gradient) of the leaf area density, starting from the prescribed surface value lad_surface.

beta_lad

R

9999999.9

Dimensionless coefficient required for constructing the leaf area density (LAD) profile, using a beta probability density function (see alpha_lad for details).

beta_lad steers together with alpha_lad the vertical distribution of leaf area within the canopy volume. Values for beta_lad must be greater than zero. Increasing beta_lad moves the leaf area more towards the canopy floor.

Note:
The LAD profile can also be constructed by prescribing vertical gradients (lad_vertical_gradient_level, lad_vertical_gradient) of the leaf area density, starting from the prescribed surface value lad_surface.

canopy_drag_coeff

R

0.0

Drag coefficient used in the plant_canopy_model.

This parameter has to be greater than zero for the simulation of a plant canopy. A typical value is 0.15, used e.g. by Shaw & Schumann (1992).

canopy_mode

C*20

'homogeneous'

The user can choose between the following modes:

'homogeneous'

Horizontally homogeneous plant canopy extending over the total horizontal dimensions of the model domain.

'read_from_file' (available from r2746)

Requires a NetCDF input file (<jobname>_static) with 3D information of leaf area density (see wiki:doc/app/iofiles/pids/static#lad static input file).

'user_defined' (Or any other string that matches case in user code)

According to user settings in subroutine user_init_plant_canopy.f90.

In any case, the simulation of a plant canopy requires the setting of a non-zero canopy_drag_coeff.

cthf

R

0.0

Average heat flux that is prescribed at the top of the plant canopy.

The user can prescribe a heat flux at the top of the plant canopy. It is assumed that solar radiation penetrates the canopy and warms the foliage which, in turn, warms the air in contact with it. Based on cthf, the heat fluxes inside the canopy down to the canopy floor are determined by a decaying exponential function that is dependent on the cumulative leaf_area_index (Shaw and Schumann, 1992, BLM 61, 47-64). At surface grid points without canopy, the surface heat flux is given by parameter surface_heatflux.

lad_surface

R

0.0

Surface value of the leaf area density (in m2/m3).

This parameter assigns the value of the leaf area density (LAD) at the surface (k=0). Starting from this value, the LAD profile is constructed with lad_vertical_gradient and lad_vertical_gradient_level.

Note:
The LAD profile can also be constructed using a beta probability density function by prescribing values for parameters alpha_lad, beta_lad, and lai_beta.

lad_type_coef

R(11)

1.0

Multiplicative coefficients for different types of plant canopy, e.g. to account for deciduous tree during wintertime. Please note, this is only active when data is read from ASCII file.

lad_vertical_gradient

R(10)

10 * 0.0

Gradient(s) of the leaf area density (in m2/m4).

This leaf area density gradient holds starting from the height level defined by lad_vertical_gradient_level (precisely: for all uv levels k where zu(k) > lad_vertical_gradient_level, lad(k) is set: lad(k) = lad(k-1) + dzu(k) * lad_vertical_gradient) up to the level defined by pch_index. Above that level, lad(k) will automatically be set to 0.0. A total of 10 different gradients for 11 height intervals (10 intervals if lad_vertical_gradient_level(1) = 0.0) can be assigned. The leaf area density at the surface is assigned via lad_surface.

lad_vertical_gradient_level

R(10)

10 * 0.0

Height level from which on the gradient of the leaf area density defined by lad_vertical_gradient is effective (in m).

The height levels have to be assigned in ascending order. The default values result in a leaf area density that is constant with height up to the top of the plant canopy layer defined by pch_index. For the piecewise linear construction of an LAD profile see lad_vertical_gradient.

lai_beta

R

0.0

Leaf area index used in the plant_canopy_model to construct the vertical profile of the leaf area density (lad) with a beta function (see alpha_lad for details).

lai_beta has to be set to a non-zero value, and parameters alpha_lad and beta_lad have to be given.

leaf_scalar_exch_coeff

R

0.0

Scalar exchange coefficient for a "bulk" leaf (dimensionless).

This parameter is only of importance in cases where passive_scalar = .T.. The value of the scalar exchange coefficient is required for the parametrization of the sources and sinks of scalar concentration due to the canopy.

leaf_surface_conc

R

0.0

Concentration of a passive scalar at the surface of a "bulk" leaf (in kg m-3 (particles) or ppm (gas)).

This parameter is only of importance in cases where passive_scalar = .T.. The value of the concentration of a passive scalar at the surface of a leaf is required for the parametrization of the sources and sinks of scalar concentration due to the canopy.

pch_index

I

0

Grid point index (w-grid) of the upper boundary of the plant canopy layer.

Above pch_index the leaf area density (LAD) is automatically set to zero. Up to pch_index a leaf area density profile can be prescribed in two possible ways:

1) Creating a piecewise linear LAD-profile by prescribing the parameters lad_surface, lad_vertical_gradient, and lad_vertical_gradient_level.

2) Employing a beta probability density function for the vertical leaf area distribution, prescribing coefficients alpha_lad, beta_lad and lai_beta (see e.g. Markkanen et al. (2003)).

plant_canopy_transpiration

L

.F.

Enables calculation of evapotranspiration and corresponding latent heat flux of the resolved plant canopy which utilizes SW and LW radiation fluxes calculated in RTM. The calculation of transpiration rate is based on the Jarvis-Stewart model with parametrizations described in Daudet et al. (1999) and Ngao, Adam and Saudreau (2017) with some modifications according to Stewart (1988).

switch_off_module

L

.F.


References

Daudet, F. A., Sinoquet, H., Le Roux, X., Adam, B. (1999): Wind speed and leaf boundary layer conductance variation within tree crown. Consequences on leaf-to-atmosphere coupling and tree functions, Agricultural and Forest Meteorology, 97, 171-185, https://doi.org/10.1016/S0168-1923(99)00079-9.

Markkanen, T., Rannik, Ü., Marcolla, B. et al. (2003): Footprints and Fetches for Fluxes over Forest Canopies with Varying Structure and Density, Boundary-Layer Meteorology, 106, 437-459, https://doi.org/10.1023/A:1021261606719.

Ngao, J., Adam, B., Saudreau, M. (2017): Intra-crown spatial variability of leaf temperature and stomatal conductance enhanced by drought in apple tree as assessed by the RATP model, Agricultural and Forest Meteorology, 237-238, 340-354, https://doi.org/10.1016/j.agrformet.2017.02.036.

Shaw, R. H. and Schumann, U. (1992): Large-eddy simulation of turbulent flow above and within a forest, Boundary-Layer Meteorology, 61, 47-64, https://doi.org/10.1007/BF02033994.

Stewart, J. B. (1988): Modelling surface conductance of pine forest, Agricultural and Forest Meteorology, 43, 19-35, https://doi.org/10.1016/0168-1923(88)90003-2.

Watanabe, T. (2004): Large-Eddy Simulation of Coherent Turbulence Structures Associated with Scalar Ramps Over Plant Canopies, Boundary-Layer Meteorology, 112, 307-341, https://doi.org/10.1023/B:BOUN.0000027912.84492.54.

Last modified 3 years ago Last modified on Feb 26, 2021 5:23:53 PM

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