Models for canopy turbulence by Katul et al (2004).
Usage
wind_canopyTurbulenceModel(zm, Cx, hm, d0, z0, model = "k-epsilon")
wind_canopyTurbulence(
zmid,
LAD,
canopyHeight,
u,
windMeasurementHeight = 200,
model = "k-epsilon"
)Arguments
- zm
A numeric vector with height values (m).
- Cx
Effective drag = Cd x leaf area density.
- hm
Canopy height (m).
- d0
Zero displacement height (m).
- z0
Momentum roughness height (m).
- model
Closure model.
- zmid
A numeric vector of mid-point heights (in cm) for canopy layers.
- LAD
A numeric vector of leaf area density values (m3/m2).
- canopyHeight
Canopy height (in cm).
- u
Measured wind speed (m/s).
- windMeasurementHeight
Height of wind speed measurement with respect to canopy height (cm).
Value
Function wind_canopyTurbulenceModel returns a data frame of vertical profiles for variables:
z1: Height values.U1: U/u*, where U is mean velocity and u* is friction velocity.dU1: dUdz/u*, where dUdz is mean velocity gradient and u* is friction velocity.epsilon1: epsilon/(u^3/h) where epsilon is the turbulent kinetic dissipation rate, u* is friction velocity and h is canopy height.k1: k/(u*^2), where k is the turbulent kinetic energy and u* is friction velocity.uw1: uw/(u*^2), where uw is the Reynolds stress and u* is friction velocity.Lmix1: Mixing length.
Function wind_canopyTurbulence returns a data frame of vertical profiles for transformed variables:
zmid: Input mid-point heights (in cm) for canopy layers.u: Wind speed (m/s).du: Mean velocity gradient (1/s).epsilon: Turbulent kinetic dissipation rate.k: Turbulent kinetic energy.uw: Reynolds stress.
Details
Implementation in Rcpp of the K-epsilon canopy turbulence models by Katul et al (2004) originally in Matlab code (https://nicholas.duke.edu/people/faculty/katul/k_epsilon_model.htm).
References
Katul GG, Mahrt L, Poggi D, Sanz C (2004) One- and two-equation models for canopy turbulence. Boundary-Layer Meteorol 113:81–109. https://doi.org/10.1023/B:BOUN.0000037333.48760.e5
Examples
#Default species parameterization
data(SpParamsMED)
#Load example plot plant data
data(exampleforest)
#Canopy height (in m)
h= max(exampleforest$treeData$Height/100)
d0 = 0.67*h
z0 = 0.08*h
#Height values (cm)
z = seq(50,1000, by=50)
zm = z/100 # (in m)
# Leaf area density
lad = vprofile_leafAreaDensity(exampleforest, SpParamsMED, draw = FALSE,
z = c(0,z))
# Effective drag
Cd = 0.2
Cx = Cd*lad
# canopy turbulence model
wind_canopyTurbulenceModel(zm, Cx,h,d0,z0)
#> z1 U1 dU1 epsilon1 k1 uw1 Lmix1
#> 1 0.5 0.7506036 0.01611031 0.002184125 0.1697988 -0.002669998 1.056
#> 2 1.0 0.7578532 0.01611031 0.002859429 0.1780338 -0.002669998 1.056
#> 3 1.5 0.7707260 0.02713846 0.003724363 0.1914893 -0.004672562 1.056
#> 4 2.0 0.7833098 0.02655020 0.004517893 0.2098024 -0.004791237 1.056
#> 5 2.5 0.7956052 0.02597262 0.005214342 0.2339515 -0.004954432 1.056
#> 6 3.0 0.8091031 0.02833618 0.005845081 0.2646464 -0.005752844 1.056
#> 7 3.5 0.8383893 0.05946380 0.007365186 0.3090357 -0.013045314 1.056
#> 8 4.0 0.8984498 0.12024976 0.010973156 0.3780062 -0.029145794 1.056
#> 9 4.5 0.9988562 0.20013962 0.018023315 0.4839961 -0.054784431 1.056
#> 10 5.0 1.1495492 0.29999743 0.030962972 0.6458571 -0.094631728 1.056
#> 11 5.5 1.3597602 0.41854076 0.053751538 0.8887614 -0.154499332 1.056
#> 12 6.0 1.6364288 0.55128712 0.091766039 1.2410790 -0.239983876 1.056
#> 13 6.5 1.9824795 0.69022606 0.150479788 1.7265353 -0.353859041 1.056
#> 14 7.0 2.3956389 0.82488644 0.232484440 2.3525175 -0.493164134 1.056
#> 15 7.5 2.8536979 0.91540151 0.327260616 3.0632852 -0.624197144 1.056
#> 16 8.0 3.3497381 0.99188362 0.424989344 3.8257576 -0.755673218 1.056
#> 17 8.5 3.8762609 1.05319400 0.509242413 4.5922802 -1.045511476 1.256
#> 18 9.0 4.2961137 0.84049330 0.534498864 5.0647502 -1.015857598 1.456
#> 19 9.5 4.6482246 0.70512898 0.539495761 5.3894102 -1.000000000 1.656
#> 20 10.0 4.9525037 0.60947693 0.538793103 5.6312500 -1.000000000 1.856