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diff --git a/DESCRIPTION b/DESCRIPTION
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+Package: bigleaf
+Type: Package
+Version: 0.3.0
+Date: 2018-01-24
+Title: Physical and Physiological Ecosystem Properties from Eddy
+        Covariance Data
+Authors@R: c( person("Juergen", "Knauer", role=c("aut","cre"), email="jknauer@bgc-jena.mpg.de"),
+              person("Soenke", "Zaehle", role=c("ctb"), email="szaehle@bgc-jena.mpg.de"),
+			  person("Tarek", "El-Madany", role=c("ctb"), email="telmad@bgc-jena.mpg.de"),
+			  person("Mirco", "Migliavacca", role=c("ctb"), email="mmiglia@bgc-jena.mpg.de")
+			)	
+Maintainer: Juergen Knauer <jknauer@bgc-jena.mpg.de>
+Description: Calculation of physical (e.g. aerodynamic conductance, surface temperature), 
+             and physiological (e.g. canopy conductance, water-use efficiency) ecosystem properties
+			 from eddy covariance data and accompanying meteorological measurements. Calculations
+			 assume the land surface to behave like a 'big-leaf' and return bulk ecosystem/canopy variables.
+URL: https://bitbucket.org/juergenknauer/bigleaf/overview
+Depends: R (>= 2.10)
+Imports: robustbase
+License: GPL (>= 2)
+LazyData: yes
+RoxygenNote: 6.0.1
+NeedsCompilation: no
+Packaged: 2018-01-25 14:31:18 UTC; jknauer
+Author: Juergen Knauer [aut, cre],
+  Soenke Zaehle [ctb],
+  Tarek El-Madany [ctb],
+  Mirco Migliavacca [ctb]
+Repository: CRAN
+Date/Publication: 2018-01-25 15:16:34 UTC
diff --git a/MD5 b/MD5
@@ -0,0 +1,77 @@
+e4df586eb4b6d7defde22e4d88731046 *DESCRIPTION
+84ec224aa5e343a280270f915cf7fe68 *NAMESPACE
+104a65fde34091bd0738b5a6b49980ed *R/WUE_metrics.r
+0385125ced5dccc39d208683b40cfddb *R/aerodynamic_conductance.r
+34ba2135e7ea0356d554f10ed35e1da9 *R/bigleaf_constants.r
+70f7131a624bb04be63d412431f49205 *R/bigleaf_physiology.r
+e35f1be56044f46d5f7697a310385546 *R/boundary_layer_conductance.r
+8b867f3ed66f89b7191c67cc497c4300 *R/check_input.r
+9f83625fbdb84cc48f275381d6ff93d7 *R/datasets_description.r
+867953fd6c1123618e7b9d1676eb3b5d *R/decoupling.r
+5f4bea86d84a7b7fd149e24db49d32c7 *R/energy_balance.r
+5dc025918438ce48caf11fe67180b1a1 *R/evapotranspiration.r
+da49ff396279f0fa441dc29ab3b610c4 *R/filter_data.r
+99aaa64f0832f7d2235e5c6c9a5618ad *R/meteorological_variables.r
+b4f2df65775944c5ff922db423141a18 *R/stability_correction.r
+678cf4c66ef5cf48423a6e954be224ef *R/surface_conditions.r
+414c6b5011a0fffe807cdbe76827e324 *R/surface_conductance.r
+85a07a2cdf2b03f404a0085dd0e1e31b *R/surface_roughness.r
+bb7b587e71672f95b8bf85bec4266726 *R/unit_conversions.r
+afe33cf05751fdb6471396e344d4e87e *data/AT_Neu_Jul_2010.rda
+1c2a7ce4ae65849e4a53411217906af4 *data/DE_Tha_Jun_2014.rda
+c69db5fcea09412b25d1dd2a3f5f5258 *data/FR_Pue_May_2012.rda
+79345a5188b0afcd9fa07843a7cbf56f *man/AT_Neu_Jul_2010.Rd
+ae9553698e02d653ee4ead85e8bb2043 *man/Arrhenius.temp.response.Rd
+cf678bbeb84cc6b0d37c9577769af17e *man/DE_Tha_Jun_2014.Rd
+044d3989bb04d55c25e6a5de7c2aad74 *man/Esat.slope.Rd
+67aea5d44315a3c3c950f62f7cbd28b9 *man/FR_Pue_May_2012.Rd
+59b8d581ed7d66c0e71490277c6823f7 *man/Gb.Choudhury.Rd
+fc9a80d6684939379453d15718dbbfd9 *man/Gb.Su.Rd
+7e17dbf16eca2adf1b8e8b76dd0ac8ff *man/Gb.Thom.Rd
+3dd6cdd399f92f3a3b73fd54d7bb5cd0 *man/LE.to.ET.Rd
+7659799f655bbe0876952e73881c73fc *man/Monin.Obukhov.length.Rd
+17a996dc1b4f40c7ee75827115abb601 *man/Reynolds.Number.Rd
+cf3589109b828b0a37c900e8897e8241 *man/Rg.to.PPFD.Rd
+abdf1f4b6802b123884fb032dc4ac54c *man/VPD.to.rH.Rd
+08b19ed1c83c7fd2eceef0cc6a7746ea *man/WUE.metrics.Rd
+58e72e261545fc4f9df4e36f2872a77e *man/aerodynamic.conductance.Rd
+33b08341fb1a2b0c4e3bb99449d17d2f *man/air.density.Rd
+83cffa29135357853796fd1abd701b28 *man/bigleaf.constants.Rd
+e00d83fb0e46858754401e6d8fbe835a *man/biochemical.energy.Rd
+9041470134033a721fa0b59aacf35605 *man/check.input.Rd
+cea5407ac444d3127c22fa68516c1ce8 *man/check.length.Rd
+e198cfa472db8069995829ee93da382d *man/decoupling.Rd
+872fc65034f721fc07ef7765b00f687c *man/dew.point.Rd
+7bbdfe3e9be38c3215e604e7da820945 *man/dew.point.solver.Rd
+407a9cccc4b91e6995b8f88aa81ed223 *man/energy.closure.Rd
+a6c9250fbc34a7bab05fce15bd2b0cd4 *man/energy.use.efficiency.Rd
+a633ead285a15addf5e971b30a961b3a *man/equilibrium.imposed.ET.Rd
+05fd47945c525e22c565afd7849a3f75 *man/filter.data.Rd
+7823670692dae256a819eb756d07bb5f *man/filter.growing.season.Rd
+d613000069be302ad541eab217c4c738 *man/intercellular.CO2.Rd
+2c5654480c02681ecc27309237f1d4b6 *man/isothermal.Rn.Rd
+028f2c5d4e4cb2344e3a0806f06285cf *man/kinematic.viscosity.Rd
+9dc96fd464cedf12e2c225ac524e9ce7 *man/latent.heat.vaporization.Rd
+0811767321bd2ec902456f9f981e8951 *man/light.response.Rd
+b011c947d448ad72a0767795f98a1c1a *man/light.use.efficiency.Rd
+b8f465c91d2790e627aa241a14bd0f0f *man/longwave.conductance.Rd
+a38c87be677f72685b5674fbca431ed9 *man/ms.to.mol.Rd
+2638ed15d9ea39346820c6b1c5e74799 *man/photosynthetic.capacity.Rd
+5278e74e46aecb6e702213ab18664b97 *man/potential.ET.Rd
+60f0a8b0bfd3e681cd33f032953861da *man/pressure.from.elevation.Rd
+8596c6504633bd326e1187e749f88508 *man/psychrometric.constant.Rd
+c13828925a01580f1e04d73249861ac9 *man/radiometric.surface.temp.Rd
+fc7a93ca7422b2a8a14630d23595c431 *man/reference.ET.Rd
+324708d7e23426d452071984cbb54a0b *man/roughness.parameters.Rd
+39d2c19e67df57f228a4b8436cb014de *man/stability.correction.Rd
+29f07825a985ca57989f0ed24384ebdd *man/stability.parameter.Rd
+c01f5878296704e901c4a787e399c97a *man/stomatal.sensitivity.Rd
+868e86f97a96d8bd26824b5941994283 *man/stomatal.slope.Rd
+0076d28809e69a9adb127ad772981da8 *man/surface.CO2.Rd
+cc5b99cc2dd31acaec24d6af83cb97c8 *man/surface.conditions.Rd
+f8c93f0496ad1570219e9751a4c7cebf *man/surface.conductance.Rd
+745b726b538f3d01ea22ccb4e2b8d96e *man/umolCO2.to.gC.Rd
+221b0e19794621b29f37062911c1e2f3 *man/virtual.temp.Rd
+7d43512699bb34537796f7a3555c35af *man/wetbulb.solver.Rd
+32fdf58d62e0eee46407598f2cbbb230 *man/wetbulb.temp.Rd
+359f90194142790c5d76ab98df828297 *man/wind.profile.Rd
diff --git a/NAMESPACE b/NAMESPACE
@@ -0,0 +1,73 @@
+# Generated by roxygen2: do not edit by hand
+
+export(Arrhenius.temp.response)
+export(ET.to.LE)
+export(Esat.slope)
+export(Gb.Choudhury)
+export(Gb.Su)
+export(Gb.Thom)
+export(LE.to.ET)
+export(Monin.Obukhov.length)
+export(PPFD.to.Rg)
+export(Reynolds.Number)
+export(Rg.to.PPFD)
+export(VPD.to.e)
+export(VPD.to.q)
+export(VPD.to.rH)
+export(WUE.metrics)
+export(aerodynamic.conductance)
+export(air.density)
+export(bigleaf.constants)
+export(biochemical.energy)
+export(decoupling)
+export(dew.point)
+export(e.to.VPD)
+export(e.to.q)
+export(energy.closure)
+export(energy.use.efficiency)
+export(equilibrium.imposed.ET)
+export(filter.data)
+export(filter.growing.season)
+export(gC.to.umolCO2)
+export(intercellular.CO2)
+export(isothermal.Rn)
+export(kinematic.viscosity)
+export(latent.heat.vaporization)
+export(light.response)
+export(light.use.efficiency)
+export(longwave.conductance)
+export(mol.to.ms)
+export(ms.to.mol)
+export(photosynthetic.capacity)
+export(potential.ET)
+export(pressure.from.elevation)
+export(psychrometric.constant)
+export(q.to.VPD)
+export(q.to.e)
+export(rH.to.VPD)
+export(radiometric.surface.temp)
+export(reference.ET)
+export(roughness.parameters)
+export(stability.correction)
+export(stability.parameter)
+export(stomatal.sensitivity)
+export(stomatal.slope)
+export(surface.CO2)
+export(surface.conditions)
+export(surface.conductance)
+export(umolCO2.to.gC)
+export(virtual.temp)
+export(wetbulb.temp)
+export(wind.profile)
+importFrom(robustbase,nlrob)
+importFrom(stats,D)
+importFrom(stats,aggregate)
+importFrom(stats,complete.cases)
+importFrom(stats,filter)
+importFrom(stats,lm)
+importFrom(stats,median)
+importFrom(stats,na.exclude)
+importFrom(stats,nls)
+importFrom(stats,optimize)
+importFrom(stats,quantile)
+importFrom(stats,sd)
diff --git a/R/WUE_metrics.r b/R/WUE_metrics.r
@@ -0,0 +1,88 @@
+###############################
+### WUE metrics calculation ###
+###############################
+
+#' Water-Use Efficiency Metrics
+#' 
+#' @description Calculation of various water use efficiency (WUE) metrics.
+#' 
+#' @param data      Data.frame or matrix containing all required variables
+#' @param GPP       Gross primary productivity (umol CO2 m-2 s-1)
+#' @param NEE       Net ecosystem exchange (umol CO2 m-2 s-1)
+#' @param LE        Latent heat flux (W m-2)
+#' @param VPD       Vapor pressure deficit (kPa)
+#' @param Tair      Air temperature (deg C)
+#' @param constants Cmol - molar mass of carbon (kg mol-1)
+#'
+#' @details the following metrics are calculated:
+#' 
+#'          Water-use efficiency (WUE):
+#'          
+#'            \deqn{WUE = GPP / ET}
+#'          
+#'          Water-use efficiency based on NEE (WUE_NEE):
+#'          
+#'            \deqn{WUE_NEE = NEE / ET}
+#'          
+#'          Inherent water-use efficiency (IWUE; Beer et al. 2009):
+#'          
+#'            \deqn{IWUE = (GPP * VPD) / ET}
+#'          
+#'          Underlying water-use efficiency (uWUE; Zhou et al. 2014):
+#'          
+#'            \deqn{uWUE= (GPP * sqrt(VPD)) / ET}
+#'          
+#'          All metrics are calculated based on the median of all values. E.g.
+#'          WUE = median(GPP/ET,na.rm=TRUE)
+#' 
+#' @return a named vector with the following elements:
+#'         \item{WUE}{Water-use efficiency (gC (kg H20)-1)}
+#'         \item{WUE_NEE}{Water-use efficiency based on NEE (gC (kg H20)-1)}
+#'         \item{IWUE}{Inherent water-use efficiency (gC kPa (kg H20)-1)}
+#'         \item{uWUE}{Underlying water-use efficiency (gC kPa (kg H20)-1)}
+#' 
+#' @note Units for VPD can also be hPa. Units change accordingly.
+#'       WUE_NEE is calculated based on the absolute value of NEE (the sign convention does not matter here).
+#' 
+#' @references Beer, C., et al., 2009: Temporal and among-site variability of inherent
+#'             water use efficiency at the ecosystem level. Global Biogeochemical Cycles 23, GB2018.
+#'             
+#'             Zhou, S., et al., 2014: The effect of vapor pressure deficit on water
+#'             use efficiency at the sub-daily time scale. Geophysical Research Letters 41.
+#'     
+#' @seealso \code{\link{stomatal.slope}} for a measure of intrinsic WUE          
+#'                             
+#' @examples 
+#' ## filter data for dry periods and daytime at DE-Tha in June 2014
+#' 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"),
+#'                                  filter.vals.min=c(5,200,0.2),
+#'                                  filter.vals.max=c(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 WUE metrics in the filtered periods
+#' WUE.metrics(DE_Tha_Jun_2014_2)
+#'                         
+#' @importFrom stats median                                     
+#' @export
+WUE.metrics <- function(data,GPP="GPP",NEE="NEE",LE="LE",VPD="VPD",Tair="Tair",
+                        constants=bigleaf.constants()){
+
+  check.input(data,list(GPP,NEE,LE,VPD,Tair))
+
+  ET  <- LE.to.ET(LE,Tair)                 # kg H2O s-1
+  GPP <- (GPP/1e06 * constants$Cmol)*1000  # gC m-2 s-1
+  NEE <- (NEE/1e06 * constants$Cmol)*1000  # gC m-2 s-1
+
+  WUE     <- median(GPP/ET,na.rm=TRUE)
+  WUE_NEE <- median(abs(NEE)/ET,na.rm=TRUE)
+  IWUE    <- median((GPP*VPD)/ET,na.rm=TRUE)
+  uWUE    <- median((GPP*sqrt(VPD))/ET,na.rm=TRUE)
+
+  return(c(WUE=WUE,WUE_NEE=WUE_NEE,IWUE=IWUE,uWUE=uWUE))
+}