surface.conductance: Surface Conductance to Water Vapor

In bigleaf: Physical and Physiological Ecosystem Properties from Eddy Covariance Data

Surface Conductance to Water Vapor

Description

Calculates surface conductance to water vapor from the inverted Penman-Monteith equation (by default) or from a simple flux-gradient approach.

Usage

surface.conductance(
  data,
  Tair = "Tair",
  pressure = "pressure",
  Rn = "Rn",
  G = NULL,
  S = NULL,
  VPD = "VPD",
  LE = "LE",
  Ga = "Ga_h",
  missing.G.as.NA = FALSE,
  missing.S.as.NA = FALSE,
  formulation = c("Penman-Monteith", "Flux-Gradient"),
  Esat.formula = c("Sonntag_1990", "Alduchov_1996", "Allen_1998"),
  constants = bigleaf.constants()
)

Arguments

data	Data.frame or matrix containing all required input variables
Tair	Air temperature (deg C)
pressure	Atmospheric pressure (kPa)
Rn	Net radiation (W m-2)
G	Ground heat flux (W m-2); optional
S	Sum of all storage fluxes (W m-2); optional
VPD	Vapor pressure deficit (kPa)
LE	Latent heat flux (W m-2)
Ga	Aerodynamic conductance to heat/water vapor (m s-1)
missing.G.as.NA	if TRUE, missing G are treated as NAs, otherwise they are set to 0. Only used if formulation = "Penman-Monteith".
missing.S.as.NA	if TRUE, missing S are treated as NAs, otherwise they are set to 0. Only used if formulation = "Penman-Monteith".
formulation	Formulation used. Either "Penman-Monteith" (the default) using the inverted Penman-Monteith equation, or "Flux-Gradient", for a simple flux-gradient approach requiring ET, pressure, and VPD only.
Esat.formula	Optional: formula to be used for the calculation of esat and the slope of esat. One of "Sonntag_1990" (Default), "Alduchov_1996", or "Allen_1998". Only used if formulation = "Penman-Monteith". See Esat.slope.
constants	cp - specific heat of air for constant pressure (J K-1 kg-1) eps - ratio of the molecular weight of water vapor to dry air (-) Rd - gas constant of dry air (J kg-1 K-1) Rgas - universal gas constant (J mol-1 K-1) Kelvin - conversion degree Celsius to Kelvin Mw - molar mass of water vapor (kg mol-1) Pa2kPa - conversion pascal (Pa) to kilopascal (kPa)

Details

If formulation = "Penman-Monteith" (the default), surface conductance (Gs) in m s-1 is calculated from the inverted Penman-Monteith equation:

Gs = ( LE * Ga * γ ) / ( Δ * A + ρ * cp * Ga * VPD - LE * ( Δ + γ ) )

Where γ is the psychrometric constant (kPa K-1), Δ is the slope of the saturation vapor pressure curve (kPa K-1), and ρ is air density (kg m-3). Available energy (A) is defined as A = Rn - G - S. If G and/or S are not provided, A = Rn.

By default, any missing data in G and S are set to 0. If missing.S.as.NA = TRUE or missing.S.as.NA = TRUE, Gs will give NA for these timesteps.

If formulation="Flux-Gradient", Gs (in mol m-2 s-1) is calculated from VPD and ET only:

Gs = ET/pressure * VPD

where ET is in mol m-2 s-1. Note that this formulation assumes fully coupled conditions (i.e. Ga = inf). This formulation is equivalent to the inverted form of Eq.6 in McNaughton & Black 1973:

Gs = LE * γ / (ρ * cp * VPD)

which gives Gs in m s-1. Note that Gs > Gc (canopy conductance) under conditions when a significant fraction of ET comes from interception or soil evaporation.

If pressure is not available, it can be approximated by elevation using the function pressure.from.elevation

Value

a dataframe with the following columns:

Gs_ms	Surface conductance in m s-1
Gs_mol	Surface conductance in mol m-2 s-1

References

Monteith, J., 1965: Evaporation and environment. In Fogg, G. E. (Ed.), The state and movement of water in living organisms (pp.205-234). 19th Symp. Soc. Exp. Biol., Cambridge University Press, Cambridge

McNaughton, K.G., Black, T.A., 1973: A study of evapotranspiration from a Douglas Fir forest using the energy balance approach. Water Resources Research 9, 1579-1590.

Examples

## filter data to ensure that Gs is a meaningful proxy to canopy conductance (Gc)
DE_Tha_Jun_2014_2 <- filter.data(DE_Tha_Jun_2014,quality.control=FALSE,
                                 vars.qc=c("Tair","precip","VPD","H","LE"),
                                 filter.growseas=FALSE,filter.precip=TRUE,
                                 filter.vars=c("Tair","PPFD","ustar","LE"),
                                 filter.vals.min=c(5,200,0.2,0),
                                 filter.vals.max=c(NA,NA,NA,NA),NA.as.invalid=TRUE,
                                 quality.ext="_qc",good.quality=c(0,1),
                                 missing.qc.as.bad=TRUE,GPP="GPP",doy="doy",
                                 year="year",tGPP=0.5,ws=15,min.int=5,precip="precip",
                                 tprecip=0.1,precip.hours=24,records.per.hour=2)

# calculate Gs based on a simple gradient approach
Gs_gradient <- surface.conductance(DE_Tha_Jun_2014_2,Tair="Tair",pressure="pressure",
                                   VPD="VPD",formulation="Flux-Gradient")
summary(Gs_gradient)

# calculate Gs from the the inverted PM equation (now Rn, and Ga are needed),
# using a simple estimate of Ga based on Thom 1972
Ga <- aerodynamic.conductance(DE_Tha_Jun_2014_2,Rb_model="Thom_1972")[,"Ga_h"]

# if G and/or S are available, don't forget to indicate (they are ignored by default).
# Note that Ga is not added to the data.frame 'DE_Tha_Jun_2014'
Gs_PM <- surface.conductance(DE_Tha_Jun_2014_2,Tair="Tair",pressure="pressure",
                             Rn="Rn",G="G",S=NULL,VPD="VPD",Ga=Ga,
                             formulation="Penman-Monteith")
summary(Gs_PM)

                              
# now add Ga to the data.frame 'DE_Tha_Jun_2014' and repeat
DE_Tha_Jun_2014_2$Ga <- Ga
Gs_PM2 <- surface.conductance(DE_Tha_Jun_2014_2,Tair="Tair",pressure="pressure",
                              Rn="Rn",G="G",S=NULL,VPD="VPD",Ga="Ga",
                              formulation="Penman-Monteith")
# note the difference to the previous version (Ga="Ga")
summary(Gs_PM2)

bigleaf documentation built on Aug. 22, 2022, 9:09 a.m.