R/RcppExports.R

In meteoland: Landscape Meteorology Tools

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

.dailyEquilibriumPET <- function(Temp, Rn) {
    .Call(`_meteoland_dailyEquilibriumPET`, Temp, Rn)
}

.penmanpoint <- function(latrad, elevation, slorad, asprad, J, Tmin, Tmax, RHmin, RHmax, R_s, u, z = 2.0, z0 = 0.001, alpha = 0.08, windfun = "1956") {
    .Call(`_meteoland_PenmanPETPointSeries`, latrad, elevation, slorad, asprad, J, Tmin, Tmax, RHmin, RHmax, R_s, u, z, z0, alpha, windfun)
}

.penmanmonteithpoint <- function(rc, elevation, Tmin, Tmax, RHmin, RHmax, Rn, u) {
    .Call(`_meteoland_PenmanMonteithPETPointSeries`, rc, elevation, Tmin, Tmax, RHmin, RHmax, Rn, u)
}

.PenmanPETPointsDay <- function(latrad, elevation, slorad, asprad, J, Tmin, Tmax, RHmin, RHmax, R_s, u, z = 2.0, z0 = 0.001, alpha = 0.08, windfun = "1956") {
    .Call(`_meteoland_PenmanPETPointsDay`, latrad, elevation, slorad, asprad, J, Tmin, Tmax, RHmin, RHmax, R_s, u, z, z0, alpha, windfun)
}

.temporalSmoothing <- function(input, numDays, prec) {
    .Call(`_meteoland_temporalSmoothing`, input, numDays, prec)
}

.slope <- function(data, nrows, ncols, cellWidth, cellHeight) {
    .Call(`_meteoland_slope`, data, nrows, ncols, cellWidth, cellHeight)
}

.aspect <- function(data, nrows, ncols, cellWidth, cellHeight) {
    .Call(`_meteoland_aspect`, data, nrows, ncols, cellWidth, cellHeight)
}

#' @describeIn interpolation_temperature Precipitation 
#' @export
interpolation_precipitation <- function(Xp, Yp, Zp, X, Y, Z, P, Psmooth, iniRp = 140000, alpha_event = 6.25, alpha_amount = 6.25, N_event = 20L, N_amount = 20L, iterations = 3L, popcrit = 0.5, fmax = 0.95, debug = FALSE) {
    .Call(`_meteoland_interpolatePrecipitationPoints`, Xp, Yp, Zp, X, Y, Z, P, Psmooth, iniRp, alpha_event, alpha_amount, N_event, N_amount, iterations, popcrit, fmax, debug)
}

.interpolatePrecipitationSeriesPoints <- function(Xp, Yp, Zp, X, Y, Z, P, Psmooth, iniRp = 140000, alpha_event = 6.25, alpha_amount = 6.25, N_event = 20L, N_amount = 20L, iterations = 3L, popcrit = 0.5, fmax = 0.95, debug = FALSE) {
    .Call(`_meteoland_interpolatePrecipitationSeriesPoints`, Xp, Yp, Zp, X, Y, Z, P, Psmooth, iniRp, alpha_event, alpha_amount, N_event, N_amount, iterations, popcrit, fmax, debug)
}

.interpolatePrecipitationEventSeriesPoints <- function(Xp, Yp, Zp, X, Y, Z, Pevent, iniRp = 140000, alpha = 6.25, N = 20L, iterations = 3L, popcrit = 0.5) {
    .Call(`_meteoland_interpolatePrecipitationEventSeriesPoints`, Xp, Yp, Zp, X, Y, Z, Pevent, iniRp, alpha, N, iterations, popcrit)
}

.pseudoRainfall <- function(RainM, daysMonthAll, shape = 2.0, scale = 4.0, firstMonth = 1L) {
    .Call(`_meteoland_pseudoRainfall`, RainM, daysMonthAll, shape, scale, firstMonth)
}

#' Solar radiation utility functions
#'
#' Set of functions used in the calculation of incoming solar radiation and net
#' radiation.
#'
#'
#' @aliases radiation_dateStringToJulianDays radiation_daylength
#' radiation_daylengthseconds radiation_directDiffuseInstant
#' radiation_directDiffuseDay radiation_potentialRadiation radiation_julianDay
#' radiation_skyLongwaveRadiation radiation_outgoingLongwaveRadiation
#' radiation_netRadiation radiation_solarRadiation radiation_solarConstant
#' radiation_solarElevation radiation_solarDeclination radiation_sunRiseSet
#' @param dateStrings A character vector with dates in format "YYYY-MM-DD".
#' @param latrad Latitude (in radians North).
#' @param slorad Slope (in radians).
#' @param asprad Aspect (in radians from North).
#' @param delta Solar declination (in radians).
#' @param solarConstant Solar constant (in kW·m-2).
#' @param hrad Solar hour (in radians).
#' @param R_s Daily incident solar radiation (MJ·m-2).
#' @param clearday Boolean flag to indicate a clearsky day (vs. overcast).
#' @param nsteps Number of daily substeps.
#' @param J Julian day (integer), number of days since January 1, 4713 BCE at
#' noon UTC.
#' @param year,month,day Year, month and day as integers.
#' @param alpha Surface albedo (from 0 to 1).
#' @param Tair Air temperature (in degrees Celsius).
#' @param vpa Average daily vapor pressure (kPa).
#' @param c Proportion of sky covered by clouds (0-1).
#' @param tmin,tmax Minimum and maximum daily temperature (ºC).
#' @param elevation Elevation above sea level (in m).
#' @param precipitation Precipitation (in mm).
#' @param diffTemp Difference between maximum and minimum temperature (ºC).
#' @param diffTempMonth Difference between maximum and minimum temperature,
#' averaged over 30 days (ºC).
#' @return Values returned for each function are: \itemize{
#' \item\code{radiation_dateStringToJulianDays}: A vector of Julian days (i.e.
#' number of days since January 1, 4713 BCE at noon UTC).
#' \item\code{radiation_daylength}: Day length (in hours).
#' \item\code{radiation_daylengthseconds}: Day length (in seconds).
#' \item\code{radiation_directDiffuseInstant}: A vector with instantaneous
#' direct and diffusive radiation rates (for both SWR and PAR).
#' \item\code{radiation_directDiffuseDay}: A data frame with instantaneous
#' direct and diffusive radiation rates (for both SWR and PAR) for each
#' subdaily time step. \item\code{radiation_potentialRadiation}: Daily
#' (potential) solar radiation (in MJ·m-2). \item\code{radiation_julianDay}:
#' Number of days since January 1, 4713 BCE at noon UTC.
#' \item\code{radiation_skyLongwaveRadiation}: Instantaneous incoming (sky)
#' longwave radiation (W·m-2).
#' \item\code{radiation_outgoingLongwaveRadiation}: Daily outgoing longwave
#' radiation (MJ·m-2·day-1).  \item\code{radiation_netRadiation}: Daily net
#' solar radiation (MJ·m-2·day-1).  \item\code{radiation_solarConstant}: Solar
#' constant (in kW·m-2). \item\code{radiation_solarDeclination}: Solar
#' declination (in radians). \item\code{radiation_solarElevation}: Angle of
#' elevation of the sun with respect to the horizon (in radians).
#' \item\code{radiation_solarRadiation}: Daily incident solar radiation
#' (MJ·m-2·day-1). \item\code{radiation_sunRiseSet}: Sunrise and sunset hours
#' in hour angle (radians). }
#' @note Code for \code{radiation_julianDay()},
#' \code{radiation_solarConstant()} and \code{radiation_solarDeclination()} was
#' translated to C++ from R code in package 'insol' (by J. G. Corripio).
#' @author Miquel De \enc{Cáceres}{Caceres} Ainsa, CREAF
#' @seealso \code{\link{interpolate_data}}
#' @references Danby, J. M. Eqn. 6.16.4 in Fundamentals of Celestial Mechanics,
#' 2nd ed. Richmond, VA: Willmann-Bell, p. 207, 1988.
#'
#' Garnier, B.J., Ohmura, A., 1968. A method of calculating the direct
#' shortwave radiation income of slopes. J. Appl. Meteorol. 7: 796-800
#'
#' McMahon, T. A., M. C. Peel, L. Lowe, R. Srikanthan, and T. R. McVicar. 2013.
#' Estimating actual, potential, reference crop and pan evaporation using
#' standard meteorological data: a pragmatic synthesis. Hydrology & Earth
#' System Sciences 17:1331–1363. See also:
#' http://www.fao.org/docrep/x0490e/x0490e06.htm.
#'
#' Reda, I. and Andreas, A. 2003. Solar Position Algorithm for Solar Radiation
#' Applications. 55 pp.; NREL Report No. TP-560-34302, Revised January 2008.
#' http://www.nrel.gov/docs/fy08osti/34302.pdf
#'
#' Spitters, C.J.T., Toussaint, H.A.J.M. and Goudriaan, J. (1986). Separating
#' the diffuse and direct components of global radiation and its implications
#' for modeling canopy photosynthesis. I. Components of incoming radiation.
#' Agricultural and Forest Meteorology, 38, 231–242.
#' @export
radiation_julianDay <- function(year, month, day) {
    .Call(`_meteoland_julianDay`, year, month, day)
}

#' @describeIn radiation_julianDay Date string to julian days
#' @export
radiation_dateStringToJulianDays <- function(dateStrings) {
    .Call(`_meteoland_dateStringToJulianDays`, dateStrings)
}

#' @describeIn radiation_julianDay solar declination
#' @export
radiation_solarDeclination <- function(J) {
    .Call(`_meteoland_solarDeclination`, J)
}

#' @describeIn radiation_julianDay solar constant
#' @export
radiation_solarConstant <- function(J) {
    .Call(`_meteoland_solarConstant`, J)
}

#' @describeIn radiation_julianDay sun rise and set
#' @export
radiation_sunRiseSet <- function(latrad, slorad, asprad, delta) {
    .Call(`_meteoland_sunRiseSet`, latrad, slorad, asprad, delta)
}

#' @describeIn radiation_julianDay solar elevation
#' @export
radiation_solarElevation <- function(latrad, delta, hrad) {
    .Call(`_meteoland_solarElevation`, latrad, delta, hrad)
}

#' @describeIn radiation_julianDay Day length
#' @export
radiation_daylength <- function(latrad, slorad, asprad, delta) {
    .Call(`_meteoland_daylength`, latrad, slorad, asprad, delta)
}

#' @describeIn radiation_julianDay Day length seconds
#' @export
radiation_daylengthseconds <- function(latrad, slorad, asprad, delta) {
    .Call(`_meteoland_daylengthseconds`, latrad, slorad, asprad, delta)
}

#' @describeIn radiation_julianDay Potential radiation
#' @export
radiation_potentialRadiation <- function(solarConstant, latrad, slorad, asprad, delta) {
    .Call(`_meteoland_RpotDay`, solarConstant, latrad, slorad, asprad, delta)
}

#' @describeIn radiation_julianDay solar Radiation
#' @export
radiation_solarRadiation <- function(solarConstant, latrad, elevation, slorad, asprad, delta, diffTemp, diffTempMonth, vpa, precipitation) {
    .Call(`_meteoland_RDay`, solarConstant, latrad, elevation, slorad, asprad, delta, diffTemp, diffTempMonth, vpa, precipitation)
}

#' @describeIn radiation_julianDay Direct diffuse instant
#' @export
radiation_directDiffuseInstant <- function(solarConstant, latrad, slorad, asprad, delta, hrad, R_s, clearday) {
    .Call(`_meteoland_directDiffuseInstant`, solarConstant, latrad, slorad, asprad, delta, hrad, R_s, clearday)
}

#' @describeIn radiation_julianDay Direct diffuse day
#' @export
radiation_directDiffuseDay <- function(solarConstant, latrad, slorad, asprad, delta, R_s, clearday, nsteps = 24L) {
    .Call(`_meteoland_directDiffuseDay`, solarConstant, latrad, slorad, asprad, delta, R_s, clearday, nsteps)
}

#' @describeIn radiation_julianDay Sky longwave radiation
#' @export
radiation_skyLongwaveRadiation <- function(Tair, vpa, c = 0) {
    .Call(`_meteoland_skyLongwaveRadiation`, Tair, vpa, c)
}

#' @describeIn radiation_julianDay Outgoing longwave radiation
#' @export
radiation_outgoingLongwaveRadiation <- function(solarConstant, latrad, elevation, slorad, asprad, delta, vpa, tmin, tmax, R_s) {
    .Call(`_meteoland_outgoingLongwaveRadiation`, solarConstant, latrad, elevation, slorad, asprad, delta, vpa, tmin, tmax, R_s)
}

#' @describeIn radiation_julianDay Net radiation
#' @export
radiation_netRadiation <- function(solarConstant, latrad, elevation, slorad, asprad, delta, vpa, tmin, tmax, R_s, alpha = 0.08) {
    .Call(`_meteoland_netRadiation`, solarConstant, latrad, elevation, slorad, asprad, delta, vpa, tmin, tmax, R_s, alpha)
}

.potentialRadiationSeries <- function(latrad, slorad, asprad, J) {
    .Call(`_meteoland_potentialRadiationSeries`, latrad, slorad, asprad, J)
}

.potentialRadiationPoints <- function(latrad, slorad, asprad, J) {
    .Call(`_meteoland_potentialRadiationPoints`, latrad, slorad, asprad, J)
}

.radiationSeries <- function(latrad, elevation, slorad, asprad, J, diffTemp, diffTempMonth, VP, P) {
    .Call(`_meteoland_radiationSeries`, latrad, elevation, slorad, asprad, J, diffTemp, diffTempMonth, VP, P)
}

.radiationPoints <- function(latrad, elevation, slorad, asprad, J, diffTemp, diffTempMonth, VP, P) {
    .Call(`_meteoland_radiationPoints`, latrad, elevation, slorad, asprad, J, diffTemp, diffTempMonth, VP, P)
}

.meteo <- function(MeteoMonth, landscapeRainfall = as.numeric( c()), ERconv = 0.05, ERsyn = 0.2, shape = 2.0, scale = 4.0, albedo = 0.17, firstMonth = 1L, cyclic = FALSE) {
    .Call(`_meteoland_meteo`, MeteoMonth, landscapeRainfall, ERconv, ERsyn, shape, scale, albedo, firstMonth, cyclic)
}

.vapourPressureFromRH <- function(T, RH) {
    .Call(`_meteoland_vapourPressureFromRH`, T, RH)
}

.dewpointTemperatureFromRH <- function(T, RH) {
    .Call(`_meteoland_dewpointTemperatureFromRH`, T, RH)
}

.temp2SVP <- function(TD) {
    .Call(`_meteoland_temp2SVP`, TD)
}

.relativeHumidityFromMinMaxTemp <- function(Tmin, Tmax) {
    .Call(`_meteoland_relativeHumidityFromMinMaxTemp`, Tmin, Tmax)
}

.relativeHumidityFromDewpointTemp <- function(T, TD) {
    .Call(`_meteoland_relativeHumidityFromDewpointTemp`, T, TD)
}

#' @describeIn interpolation_temperature Dew temperature 
#' @export
interpolation_dewtemperature <- function(Xp, Yp, Zp, X, Y, Z, T, iniRp = 140000, alpha = 3.0, N = 30L, iterations = 3L, debug = FALSE) {
    .Call(`_meteoland_interpolateTdewPoints`, Xp, Yp, Zp, X, Y, Z, T, iniRp, alpha, N, iterations, debug)
}

.interpolateTdewSeriesPoints <- function(Xp, Yp, Zp, X, Y, Z, T, iniRp = 140000, alpha = 3.0, N = 30L, iterations = 3L, debug = FALSE) {
    .Call(`_meteoland_interpolateTdewSeriesPoints`, Xp, Yp, Zp, X, Y, Z, T, iniRp, alpha, N, iterations, debug)
}

#' Low-level interpolation functions
#'
#' Low-level functions to interpolate meteorology (one day) on a set of points.
#'
#' @details
#' This functions exposes internal low-level interpolation functions written in C++
#' not intended to be used directly in any script or function. The are maintained for
#' compatibility with older versions of the package and future versions of meteoland
#' will remove this functions (they will be still accessible through the triple colon
#' notation (\code{:::}), but their use is not recommended)
#'
#'
#' @aliases interpolation_dewtemperature interpolation_temperature
#' interpolation_precipitation interpolation_wind
#' @param Xp,Yp,Zp Spatial coordinates and elevation (Zp; in m.a.s.l) of target
#' points.
#' @param X,Y,Z Spatial coordinates and elevation (Zp; in m.a.s.l) of reference
#' locations (e.g. meteorological stations).
#' @param T Temperature (e.g., minimum, maximum or dew temperature) at the
#' reference locations (in degrees).
#' @param P Precipitation at the reference locations (in mm).
#' @param Psmooth Temporally-smoothed precipitation at the reference locations
#' (in mm).
#' @param WS,WD Wind speed (in m/s) and wind direction (in degrees from north
#' clock-wise) at the reference locations.
#' @param iniRp Initial truncation radius.
#' @param iterations Number of station density iterations.
#' @param debug Boolean flag to show extra console output.
#' @param alpha,alpha_amount,alpha_event Gaussian shape parameter.
#' @param N,N_event,N_amount Average number of stations with non-zero weights.
#' @param popcrit Critical precipitation occurrence parameter.
#' @param fmax Maximum value for precipitation regression extrapolations (0.6
#' equals to a maximum of 4 times extrapolation).
#' @param directionsAvailable A flag to indicate that wind directions are
#' available (i.e. non-missing) at the reference locations.
#' @return All functions return a vector with interpolated values for the
#' target points.
#' @author Miquel De \enc{Cáceres}{Caceres} Ainsa, CREAF
#' @seealso \code{\link{defaultInterpolationParams}}
#' @references Thornton, P.E., Running, S.W., White, M. A., 1997. Generating
#' surfaces of daily meteorological variables over large regions of complex
#' terrain. J. Hydrol. 190, 214–251. doi:10.1016/S0022-1694(96)03128-9.
#'
#' De Caceres M, Martin-StPaul N, Turco M, Cabon A, Granda V (2018) Estimating
#' daily meteorological data and downscaling climate models over landscapes.
#' Environmental Modelling and Software 108: 186-196.
#' @examples
#'
#' Xp <- as.numeric(sf::st_coordinates(points_to_interpolate_example)[,1])
#' Yp <- as.numeric(sf::st_coordinates(points_to_interpolate_example)[,2])
#' Zp <- points_to_interpolate_example$elevation
#' X <- as.numeric(
#'   sf::st_coordinates(stars::st_get_dimension_values(meteoland_interpolator_example, "station"))[,1]
#' )
#' Y <- as.numeric(
#'   sf::st_coordinates(stars::st_get_dimension_values(meteoland_interpolator_example, "station"))[,2]
#' )
#' Z <- as.numeric(meteoland_interpolator_example[["elevation"]][1,])
#' Temp <- as.numeric(meteoland_interpolator_example[["MinTemperature"]][1,])
#' P <- as.numeric(meteoland_interpolator_example[["Precipitation"]][1,])
#' Psmooth <- as.numeric(meteoland_interpolator_example[["SmoothedPrecipitation"]][1,])
#' WS <- as.numeric(meteoland_interpolator_example[["WindSpeed"]][1,])
#' WD <- as.numeric(meteoland_interpolator_example[["WindDirection"]][1,])
#' iniRp <- get_interpolation_params(meteoland_interpolator_example)$initial_Rp
#' alpha <- get_interpolation_params(meteoland_interpolator_example)$alpha_MinTemperature
#' N <- get_interpolation_params(meteoland_interpolator_example)$N_MinTemperature
#' alpha_event <- get_interpolation_params(meteoland_interpolator_example)$alpha_PrecipitationEvent
#' N_event <- get_interpolation_params(meteoland_interpolator_example)$N_PrecipitationEvent
#' alpha_amount <- get_interpolation_params(meteoland_interpolator_example)$alpha_PrecipitationAmount
#' N_amount <- get_interpolation_params(meteoland_interpolator_example)$N_PrecipitationAmount
#' alpha_wind <- get_interpolation_params(meteoland_interpolator_example)$alpha_Wind
#' N_wind <- get_interpolation_params(meteoland_interpolator_example)$N_Wind
#' iterations <- get_interpolation_params(meteoland_interpolator_example)$iterations
#' popcrit <- get_interpolation_params(meteoland_interpolator_example)$pop_crit
#' fmax <- get_interpolation_params(meteoland_interpolator_example)$f_max
#' debug <- get_interpolation_params(meteoland_interpolator_example)$debug
#'
#' interpolation_temperature(
#'   Xp, Yp, Zp,
#'   X[!is.na(Temp)], Y[!is.na(Temp)], Z[!is.na(Temp)],
#'   Temp[!is.na(Temp)],
#'   iniRp, alpha, N, iterations, debug
#' )
#'
#' interpolation_wind(
#'   Xp, Yp,
#'   WS[!is.na(WD)], WD[!is.na(WD)],
#'   X[!is.na(WD)], Y[!is.na(WD)],
#'   iniRp, alpha_wind, N_wind, iterations, directionsAvailable = FALSE
#' )
#'
#' interpolation_precipitation(
#'   Xp, Yp, Zp,
#'   X[!is.na(P)], Y[!is.na(P)], Z[!is.na(P)],
#'   P[!is.na(P)], Psmooth[!is.na(P)],
#'   iniRp, alpha_event, alpha_amount, N_event, N_amount,
#'   iterations, popcrit, fmax, debug
#' )
#'
#' @export
interpolation_temperature <- function(Xp, Yp, Zp, X, Y, Z, T, iniRp = 140000, alpha = 3.0, N = 30L, iterations = 3L, debug = FALSE) {
    .Call(`_meteoland_interpolateTemperaturePoints`, Xp, Yp, Zp, X, Y, Z, T, iniRp, alpha, N, iterations, debug)
}

.interpolateTemperatureSeriesPoints <- function(Xp, Yp, Zp, X, Y, Z, T, iniRp = 140000, alpha = 3.0, N = 30L, iterations = 3L, debug = FALSE) {
    .Call(`_meteoland_interpolateTemperatureSeriesPoints`, Xp, Yp, Zp, X, Y, Z, T, iniRp, alpha, N, iterations, debug)
}

#' Physical utility functions
#'
#' Set of functions used in the calculation of physical variables.
#'
#'
#' @aliases utils_airDensity utils_atmosphericPressure utils_averageDailyVP
#' utils_averageDaylightTemperature utils_latentHeatVaporisation
#' utils_latentHeatVaporisationMol utils_psychrometricConstant
#' utils_saturationVP utils_saturationVaporPressureCurveSlope
#' @param temperature Air temperature (ºC).
#' @param Tmin,Tmax Minimum and maximum daily temperature (ºC).
#' @param RHmin,RHmax Minimum and maximum relative humidity (%).
#' @param Patm Atmospheric air pressure (in kPa).
#' @param elevation Elevation above sea level (in m).
#' @return Values returned for each function are: \itemize{
#' \item{\code{utils_airDensity}: air density (in kg·m-3).}
#' \item{\code{utils_atmosphericPressure}: Air atmospheric pressure (in kPa).}
#' \item{\code{utils_averageDailyVP}: average (actual) vapour pressure (in kPa).}
#' \item{\code{utils_averageDaylightTemperature}: average daylight air
#' temperature (in ºC). \item\code{utils_latentHeatVaporisation}: Latent heat
#' of vaporisation (MJ·kg-1).  \item\code{utils_latentHeatVaporisationMol}:
#' Latent heat of vaporisation (J·mol-1).}
#' \item{\code{utils_psychrometricConstant}: Psychrometric constant (kPa·ºC-1).}
#' \item{\code{utils_saturationVP}: saturation vapour pressure (in kPa).}
#' \item{\code{utils_saturationVaporPressureCurveSlope}: Slope of the saturation
#' vapor pressure curve (kPa·ºC-1).}  }
#' @author Miquel De \enc{Cáceres}{Caceres} Ainsa, CREAF
#' @references McMurtrie, R. E., D. A. Rook, and F. M. Kelliher. 1990.
#' Modelling the yield of Pinus radiata on a site limited by water and
#' nitrogen. Forest Ecology and Management 30:381–413.
#'
#' McMahon, T. A., M. C. Peel, L. Lowe, R. Srikanthan, and T. R. McVicar. 2013.
#' Estimating actual, potential, reference crop and pan evaporation using
#' standard meteorological data: a pragmatic synthesis. Hydrology & Earth
#' System Sciences 17:1331–1363. See also:
#' http://www.fao.org/docrep/x0490e/x0490e06.htm
#' @export
utils_saturationVP <- function(temperature) {
    .Call(`_meteoland_saturationVapourPressure`, temperature)
}

#' @describeIn utils_saturationVP Average daily VP
#' @export
utils_averageDailyVP <- function(Tmin, Tmax, RHmin, RHmax) {
    .Call(`_meteoland_averageDailyVapourPressure`, Tmin, Tmax, RHmin, RHmax)
}

#' @describeIn utils_saturationVP Atmospheric pressure
#' @export
utils_atmosphericPressure <- function(elevation) {
    .Call(`_meteoland_atmosphericPressure`, elevation)
}

#' @describeIn utils_saturationVP Air density
#' @export
utils_airDensity <- function(temperature, Patm) {
    .Call(`_meteoland_airDensity`, temperature, Patm)
}

#' @describeIn utils_saturationVP Daylight temperature
#' @export
utils_averageDaylightTemperature <- function(Tmin, Tmax) {
    .Call(`_meteoland_averageDaylightTemperature`, Tmin, Tmax)
}

#' @describeIn utils_saturationVP latent heat vaporisation
#' @export
utils_latentHeatVaporisation <- function(temperature) {
    .Call(`_meteoland_latentHeatVaporisation`, temperature)
}

#' @describeIn utils_saturationVP Heat vaporisation mol
#' @export
utils_latentHeatVaporisationMol <- function(temperature) {
    .Call(`_meteoland_latentHeatVaporisationMol`, temperature)
}

#' @describeIn utils_saturationVP psychrometric constant
#' @export
utils_psychrometricConstant <- function(temperature, Patm) {
    .Call(`_meteoland_psychrometricConstant`, temperature, Patm)
}

#' @describeIn utils_saturationVP Saturation VP curve slope
#' @export
utils_saturationVaporPressureCurveSlope <- function(temperature) {
    .Call(`_meteoland_saturationVaporPressureCurveSlope`, temperature)
}

#' Potential evapotranspiration
#'
#' Functions to calculate potential evapotranspiration using Penman or
#' Penman-Monteith.
#'
#' The code was adapted from package `Evapotranspiration', which follows
#' McMahon et al. (2013). If wind speed is not available, an alternative
#' formulation for potential evapotranspiration is used as an approximation
#' (Valiantzas 2006)
#'
#' @aliases penman penmanmonteith
#' @param latrad Latitude in radians.
#' @param elevation Elevation (in m).
#' @param slorad Slope (in radians).
#' @param asprad Aspect (in radians from North).
#' @param J Julian day, number of days since January 1, 4713 BCE at noon UTC.
#' @param Tmax Maximum temperature (degrees Celsius).
#' @param Tmin Minimum temperature (degrees Celsius).
#' @param RHmin Minimum relative humidity (percent).
#' @param RHmax Maximum relative humidity (percent).
#' @param R_s Solar radiation (MJ/m2).
#' @param u With wind speed (m/s).
#' @param z Wind measuring height (m).
#' @param z0 Roughness height (m).
#' @param alpha Albedo.
#' @param windfun Wind speed function version, either "1948" or "1956".
#' @param rc Canopy vapour flux (stomatal) resistance (s·m-1).
#' @param Rn Daily net radiation (MJ·m-2·day-1).
#' @return Potential evapotranspiration (in mm of water).
#' @author Miquel De \enc{Cáceres}{Caceres} Ainsa, CREAF
#' @seealso \code{\link{interpolate_data}}
#' @references Penman, H. L. 1948. Natural evaporation from open water, bare
#' soil and grass. Proceedings of the Royal Society of London. Series A.
#' Mathematical and Physical Sciences, 193, 120-145.
#'
#' Penman, H. L. 1956. Evaporation: An introductory survey. Netherlands Journal
#' of Agricultural Science, 4, 9-29.
#'
#' McMahon, T.A., Peel, M.C., Lowe, L., Srikanthan, R., McVicar, T.R. 2013.
#' Estimating actual, potential, reference crop and pan evaporation using
#' standard meteorological data: a pragmatic synthesis. Hydrology & Earth
#' System Sciences 17, 1331–1363. doi:10.5194/hess-17-1331-2013.
#' @export
penman <- function(latrad, elevation, slorad, asprad, J, Tmin, Tmax, RHmin, RHmax, R_s, u, z = 2.0, z0 = 0.001, alpha = 0.08, windfun = "1956") {
    .Call(`_meteoland_PenmanPET`, latrad, elevation, slorad, asprad, J, Tmin, Tmax, RHmin, RHmax, R_s, u, z, z0, alpha, windfun)
}

#' @describeIn penman Penman Monteith method
#' @export
penmanmonteith <- function(rc, elevation, Tmin, Tmax, RHmin, RHmax, Rn, u = NA_real_) {
    .Call(`_meteoland_PenmanMonteithPET`, rc, elevation, Tmin, Tmax, RHmin, RHmax, Rn, u)
}

.getWindFieldIndexAndFactor <- function(windSpeed, windDirection, wfSpeed, wfDirection) {
    .Call(`_meteoland_getWindFieldIndexAndFactor`, windSpeed, windDirection, wfSpeed, wfDirection)
}

#' @describeIn interpolation_temperature Wind 
#' @export
interpolation_wind <- function(Xp, Yp, WS, WD, X, Y, iniRp = 140000, alpha = 2.0, N = 1L, iterations = 3L, directionsAvailable = TRUE) {
    .Call(`_meteoland_interpolateWindStationPoints`, Xp, Yp, WS, WD, X, Y, iniRp, alpha, N, iterations, directionsAvailable)
}

.interpolateWindFieldSeriesPoints <- function(Xp, Yp, WS, WD, X, Y, I, F, iniRp = 140000, alpha = 3.0, N = 30L, iterations = 3L) {
    .Call(`_meteoland_interpolateWindFieldSeriesPoints`, Xp, Yp, WS, WD, X, Y, I, F, iniRp, alpha, N, iterations)
}

.interpolateWindStationSeriesPoints <- function(Xp, Yp, WS, WD, X, Y, iniRp = 140000, alpha = 3.0, N = 30L, iterations = 3L) {
    .Call(`_meteoland_interpolateWindStationSeriesPoints`, Xp, Yp, WS, WD, X, Y, iniRp, alpha, N, iterations)
}

# Register entry points for exported C++ functions
methods::setLoadAction(function(ns) {
    .Call(`_meteoland_RcppExport_registerCCallable`)
})