meteoEVT (version 0.1.0)

frontid: Front Identification und Statistics

Description

Calculates frontal zones based on a chosen method (TFP, F diagnostic, DSI) and provides statistics of the distribution of meteorological quantities inside the determined frontak zones.

Usage

frontid(
  t_fld,
  u_fld = NULL,
  v_fld = NULL,
  w_fld = NULL,
  phi_fld = NULL,
  lev_p,
  lat = NULL,
  method = "tfp",
  threshold = 2 * 10^-10,
  dx = 0.25,
  dy = 0.25,
  fronts_only = FALSE,
  mode = "lonlat"
)

Value

list containing the used method and used threshold, field with logicals containing the detected frontal zones and numerics of temperature, u-wind, v-wind, w-wind, geopotential, vorticity, PV and DSI inside the determined frontal zones

Arguments

t_fld

temperature field [K]

u_fld

zonal velocity field [m/s]

v_fld

meridional velocity field [m/s]

w_fld

vertical velocity field [m/s]

phi_fld

geopotential height [gpm]

lev_p

vector containing pressure levels [Pa]

lat

only for lonlat mode: vector containing latitude

method

character containing the method, use 'tfp' for TFP method, 'f' for F diagnostic and 'dsi' for DSI method

threshold

scalar containing a suitable threshold (e.g., 2*10^-10 for TFP method, 1 or for F diagnostic, 10^-16 for DSI method)

dx

x resolution in the corresponding unit (e.g. 0.25 degree for ERA5 with mode='lonlat' or e.g. 1000 m in cartesian coordinates with mode='cartesian')

dy

y resolution in the corresponding unit (e.g. 0.25 degree for ERA5 with mode='lonlat' or e.g. 1000 m in cartesian coordinates with mode='cartesian')

fronts_only

if you only want to calculate the frontal regions and not their properties (default FALSE)

mode

the horizontal coordinate system, options are lonlat for a longitude-latitude-grid (default), or cartesian for an equidistant cartesian grid

Examples

myfile=system.file("extdata", "era5_storm-zeynep.nc", package = "meteoEVT")
data = readin_era5(myfile)

#front identification using the thermic front parameter (example without front statistic)
tfp_fronts=frontid(data$temp,lev_p=data$lev,lat=data$lat,fronts_only=TRUE)

#front identification using F diagnostic (example with front statistic)
f_fronts=frontid(data$temp,data$u,data$v,data$w,data$z,lev_p=data$lev,lat=data$lat,
method='f',threshold=2,fronts_only=FALSE)

#front identification using the dynamic state index (example with statistic)
dsi_fronts=frontid(data$temp,data$u,data$v,data$w,data$z,lev_p=data$lev,lat=data$lat,
method='dsi',threshold=4*10^-16,fronts_only=FALSE)