Description Usage Arguments Value Examples
View source: R/dynamics_sweq.R
Simulate a time series of states and observations at a given frequency from the modified SWEQ model. The parameters and options follow the original implementation of the author in Python. Here the model is implemented in fortran90 for better performance.
1 2 3 4 5 6 | sweq_simulate(duration, freq, ndim, umean = 0, unoise = FALSE, topo = 1,
noiseswitch = 1, kh = 25000, ku = kh, kr = 200, noisefreq = 1,
thres.rain = 0.005, sigr = 0.0025, sigu = 0.01, alpha = 1/4000,
beta = 3, norain = TRUE, aircraft = 0, rgauss = FALSE,
R.sigr = sigr, R.sigu = sigu, seed = sample.int(1000, 1), hc = 90.02,
hr = 90.4, state0 = NA)
|
duration |
the total integration time |
freq |
the frequency at which the process is recorded and observed |
ndim |
dimension of the 1-dim domain |
umean |
Initial wind field |
topo |
1=nothing, 2=one mountain, 3=5mountains |
kh, ku, kr |
diffusion parameters |
thres.rain |
threshold over which rain is observed |
sigr, sigu |
standard deviation of r and u observations |
alpha, |
beta model parameters |
R.sigr, |
R.sigu are used to create the R matrix (not necessarily equal to sigr and sigu) |
seed |
random seed (pass as NA if set externally) |
hc, hr |
critical heights for clouds and rain formation |
state0 |
possible initial state at time 0 |
unoise: |
TRUE/FALSE wind perturbation |
noiseswitch=1 |
for adding random plumes |
noisefreq=1 |
probability of random plume at each integration cycle |
norain: |
should no-rain observations be created |
a list with everything needed for assimilation and plotting
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ndim <- 300
freq <- 60
duration <- 12*freq
kh <- 25000; ku<- 25000; kr<- 200
alpha <- 1/4000; beta <- 3; hr <- 90.4; hc <- 90.02
train <- 0.005;
sigr <- 0.1
sigu <- 0.0025
R.sigu <- sigu
R.sigr <- 0.025
norain <- TRUE ## TRUE=assimilate norain observations
set.seed(1)
sweq_run <- sweq_simulate(duration, freq, ndim,
alpha=alpha, beta=beta,
noisefreq = 1, umean = 0,
hr=hr, hc=hc,
sigr=sigr, sigu=sigu,
R.sigr=R.sigr, R.sigu=R.sigu,
norain=norain,
thres.rain=train)
sweq_ggplot(sweq_run$state.ts[1,], obs=sweq_run$y.ts[[1]])
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