cond_returnlevel_map: Create conditional return level maps for Austria
In SpatialModelsZAMG: Spatial Modeling of Extreme Events

Description Usage Arguments Value See Also Examples

this function creates a map of Austria with conditional return levels

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cond_returnlevel_map(covariables, cond_rl, q, sd_or_swe,
                     plottitle = NULL, save_name = NULL,
                     save_dir = getwd(), printPlot = TRUE)

`covariables`	a named matrix with the covariables. each row corresponds to one location, columns should include at least `lon` and `lat`
`cond_rl`	a vector with the conditional return level for every location
`q`	the return period – must be a number greater than 1
`sd_or_swe`	a character string; you can either chose snow depth (`"sd"`) or snow water equivalent (`"swe"`)
`plottitle`	a character string defining the title of the plot. default is `plottitle = "sd_or_swe conditional return level map"`, depending on `sd_or_swe`. if no plottitle is wanted, use `plottitle = ""`
`save_name`	a character string defining the saving name of the map.
`save_dir`	a character string defining the directory for the map to be saved. default is the working directory
`printPlot`	logical value; if `TRUE` (default), the plot is printed

a map of Austria with the conditional return levels

cond_returnlevels, cond_returnlevel_plot, returnlevel_map

# get covariables
lon = get(data(lon.at))
lon = as.vector(t(lon))
lat = get(data(lat.at))
lat = as.vector(t(lat))
alt = get(data(alt.at))
alt = as.vector(t(alt))

x = get(data(sample_grid_data))

mdday    = x$mdday
sd_mmax  = x$mmsd
swe_mmax = x$mmswe

# take only locations of the (Austrian) domain
lon = lon[which(!is.na(mdday))]
lat = lat[which(!is.na(mdday))]
alt = alt[which(!is.na(mdday))]
mdday    = mdday[which(!is.na(mdday))]
sd_mmax  = sd_mmax[which(!is.na(sd_mmax))]
swe_mmax = swe_mmax[which(!is.na(swe_mmax))]

# define matrix 'covariables'
covariables = cbind("lon" = lon, "lat" = lat, "alt" = alt,
                    "mdday" = mdday, "sd_mmax" = sd_mmax,
                    "swe_mmax" = swe_mmax)

# load function output from GEVparameters_from_models
sd_GEVparam  = get(data("sd_GEVparam"))

# load function output from optimizer_biv_hr_model
data("optim_hr")

# define coefficients
sd_coeff  = optim_hr$coefficients$sd_coeff
cor_coeff = optim_hr$coefficients$cor_coeff

# define return period (same as in sd_GEVparam)
q = 100

# calculate return levels
sd_rl  = returnlevels(GEVparam = sd_GEVparam,  q = q)

# sd given sd in ibk
ibk = c("lon" = 11.392778, "lat" = 47.267222, "alt" = 574,
        "mdday" = 6.12, "sd_mmax" = 16.8, "swe_mmax" = 29)
sd_GEVparam_ibk  = GEVparameters_from_models(ibk, sd_coeff)
sd_rl_ibk = returnlevels(GEVparam = sd_GEVparam_ibk, q = q)

cond_rl_ibk =
  cond_returnlevels(locations = covariables,
                    GEVparam = sd_GEVparam, q = q,
                    cond_locations = ibk,
                    cond_GEVparam = sd_GEVparam_ibk,
                    same_var = TRUE, cond_B = sd_rl_ibk,
                    cor_coeff = cor_coeff, model = "hr")

# create conditional return level map
cond_returnlevel_map(covariables = covariables,
                     cond_rl = cond_rl_ibk, q = q,
                     sd_or_swe = "sd", printPlot = TRUE)