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Low-level interpolation functions

Source: R/RcppExports.R
interpolation_temperature.Rd

Low-level functions to interpolate meteorology (one day) on a set of points.

Usage

interpolation_precipitation(
  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
)

interpolation_dewtemperature(
  Xp,
  Yp,
  Zp,
  X,
  Y,
  Z,
  T,
  iniRp = 140000,
  alpha = 3,
  N = 30L,
  iterations = 3L,
  debug = FALSE
)

interpolation_temperature(
  Xp,
  Yp,
  Zp,
  X,
  Y,
  Z,
  T,
  iniRp = 140000,
  alpha = 3,
  N = 30L,
  iterations = 3L,
  debug = FALSE
)

interpolation_wind(
  Xp,
  Yp,
  WS,
  WD,
  X,
  Y,
  iniRp = 140000,
  alpha = 2,
  N = 1L,
  iterations = 3L,
  directionsAvailable = TRUE
)

Arguments

Xp, Yp, Zp

Spatial coordinates and elevation (Zp; in m.a.s.l) of target points.

X, Y, Z

Spatial coordinates and elevation (Zp; in m.a.s.l) of reference locations (e.g. meteorological stations).

P

Precipitation at the reference locations (in mm).

Psmooth

Temporally-smoothed precipitation at the reference locations (in mm).

iniRp

Initial truncation radius.

iterations

Number of station density iterations.

popcrit

Critical precipitation occurrence parameter.

fmax

Maximum value for precipitation regression extrapolations (0.6 equals to a maximum of 4 times extrapolation).

debug

Boolean flag to show extra console output.

T

Temperature (e.g., minimum, maximum or dew temperature) at the reference locations (in degrees).

alpha, alpha_amount, alpha_event

Gaussian shape parameter.

N, N_event, N_amount

Average number of stations with non-zero weights.

WS, WD

Wind speed (in m/s) and wind direction (in degrees from north clock-wise) at the reference locations.

directionsAvailable

A flag to indicate that wind directions are available (i.e. non-missing) at the reference locations.

Value

All functions return a vector with interpolated values for the target 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 (:::), but their use is not recommended)

Functions

  • interpolation_precipitation(): Precipitation

  • interpolation_dewtemperature(): Dew temperature

  • interpolation_wind(): Wind

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.

See also

defaultInterpolationParams

Author

Miquel De Cáceres Ainsa, CREAF

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
)
#>  [1] -2.5259554 -1.2274925  0.4602637 -0.1155003 -9.7153282  2.5290313
#>  [7] -2.4239096 -2.1036076 -1.9277582 -0.8422971 -1.4108765 -2.2973953
#> [13] -0.7649598 -3.5780859  0.2170589

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
)
#>           [,1] [,2]
#>  [1,] 1.980286   NA
#>  [2,] 1.995742   NA
#>  [3,] 0.900000   NA
#>  [4,] 1.613360   NA
#>  [5,] 1.964632   NA
#>  [6,] 6.196058   NA
#>  [7,]       NA   NA
#>  [8,] 2.058176   NA
#>  [9,] 3.356163   NA
#> [10,] 3.221483   NA
#> [11,]       NA   NA
#> [12,] 4.370816   NA
#> [13,] 4.132147   NA
#> [14,]       NA   NA
#> [15,] 3.342795   NA

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
)
#>  [1] 0.0000000 0.0000000 0.1049001 0.1724466 1.8571120 0.1968337 2.0475055
#>  [8] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 2.8098406
#> [15] 0.0000000