LTmodel: Run the Linear Theory model. THis is the function that calls...

In dschneiderch/LinearTheoryOrographicPrecip: Linear Theory of Orographic Precipitation

Description

Run the Linear Theory model. THis is the function that calls the others.

Usage

LTmodel(h, dx, dy, Pinf, tauc, tauf, windspeed, winddir, trunc = TRUE,
  method = "smith", trunc_value = 0, saveInt = FALSE, Intfn = NULL)

Arguments

h	matrix of elevation
dx	horizontal resolution (m)
dy	vertical resolution (m)
Pinf	background precip (mm/hr)
tauc	condensation time delay (s)
tauf	fallout time delay (s)
windspeed	windspeed (m/s)
winddir	wind direction (m/s)
trunc	should the result truncate negative values (default=TRUE)
method	default = 'smith' (as the method is described in Smith and Barstad 2004); decides whether truncation should happen before or after adding background precip. If 'smith', truncation happens after adding background precip. If otherwise, truncation happens before adding background precip. For 'smith', you will have a lot of zeros if background precip is low whereas with the other method those grid cells will have the value of the background precip
trunc_value	value below which modeled precip rates should go to zero. This will only make a difference if 'method=LEM'
saveInt	logical. save fft of dem to 'int' directory of your project. speeds up parameter search 2x-3x
Intfn	filename (relative to wd) where to save intermediate FFT matrix

Details

returns a matrix the same size as h with precip mm/hr Prepare Fourier transform of the topography —- Do 2D FFT of Topography —- Prepare precipitation transfer function relating the Fourier transforms of the terrain hhat(k,l) and the precipitiation field Phat(k,l) (Eq 49) Transfer function relating the Fourier transforms of the terrain hhat(k,l) and the precipitiation field Phat(k,l) (Eq 49) Perform the inverse Fourier transform on Phat Should background precip be added before or after truncation (if truncation happens)? Add the background precipitation rate Apply the positive cutoff Apply the positive cutoff Add the background precipitation rate library(tidyverse) tbl <- tibble(x=as.numeric(dem_list$x),y=as.numeric(dem_list$y),p=Ppad) Return to matrix

dschneiderch/LinearTheoryOrographicPrecip documentation built on May 19, 2019, 1:43 a.m.