CCI                 package:cyclones                 R Documentation

_C_a_l_c_u_l_u_s _C_y_c_l_o_n_e _i_d_e_n_t_i_f_i_c_a_t_i_o_n.

_D_e_s_c_r_i_p_t_i_o_n:

     Identifies cyclones (low pressure systems) in a gridded data set
     using a Calculus Cyclone Identification (CCI) method
     (EMS04-A-00146, Benestad, R.E.; Sorteberg, A.; Chen, D. 'Storm
     statistics derived using a calculus-based cyclone identification
     method', <URL:
     http://www.cosis.net/members/meetings/sessions/oral_programme.php?
     p_id=110&s_id=1845>, European Meteorological Society AC2, Nice,
     Sept 28, 2004). Storms are identified with longitude, latitude,
     and date. Also returned are estimates of local minimum pressure,
     max pressure gradient near storm, max geostrophic windspeed near
     storm, and radius of the storm. The storm location is by means of
     finding where first derivatives of north-south and east-west
     gradients both are zero. The storm radius is estimated from the
     points of inflexion along the latitude and longitude lines running
     trough the centre of the storm. 

     This code is the basis for the analysis carried out by Benestad et
     al. 'The use of a Calculus-based Cyclone Identification method for
     generating storm statistics' submitted to Climate Dynamics (2004).

     'stopCCI' signals the CCI process to stop in a safe manner by
     removing the file '.CCI.run' in the run directory.

     'gradient.wind' estimated the gradient wind of the data produced
     by CCI after Fleagle and Businger (1980) p. 163. (eq 4.27).

_U_s_a_g_e:

     CCI(maxhar=14,lplot=TRUE,nsim=10,fname="data/cyclones.Rdata",
         fielddata="data/nmc_slp.nc",vname="slp",cyclones=TRUE,force365.25=FALSE,
         x.rng=c(-80,40),y.rng=c(5,75),tslice=3652,rad=5,dx=1,dy=1,
         times=NULL,label=NULL,rho=1.293,nc.read.method="retrieve.nc",
         graph.dir="CCI.graphs/",plot.interval=50,EPS=TRUE)
     stopCCI()
     gradient.wind(storms=NULL,icyclone=1)

_A_r_g_u_m_e_n_t_s:

  maxhar: number of harmonics used for fit to profile (Fourier
          truncation)

   lplot: TRUE: produce plots.

    nsim: Number of simultaneous cyclones identified and saved ordered
          according to depth/strength.

   fname: Name of file containing the stats of cyclones (output).

fielddata: Name of file (netCDF) of gridded data (input)

   vname: Variable name of the field in 'fielddata'.

cyclones: TRUE: identifies cyclones, FALSE anticyclones.

force365.25: TRUE - To ensure a 365.25-day year, FALSE evaluates to
          find the best match: 365.25-day or 360-day (model) year.

   x.rng: Longitude region of interest.

   y.rng: Latitude region of interest.

  tslice: Number of maps read per chunk of data (time slice).

     rad: Max radius of cyclone.

      dx: Resolution in longitude (in degrees). NULL skips
          interpolation - uses original grid

      dy: Resolution in latitudes (in degrees). NULL skips
          interpolation - uses original grid

   times: Specify time slices for reading chunks of data.

   label: Label for ID-purposes.

     rho: Density of air for calculation of geostrophic wind.

nc.read.method: Method to read netCDF or other gridded data. Can be set
          to a custom made routine.THe output should be a 'field'-type
          object.

graph.dir: Name of the directory in which to store the graphical
          output.

plot.interval: Interval between the generation of each graphical output

     EPS: TRUE for generation of encapsulated PostScript graphics,
          FALSE for PNG bitmaps. PNG bitmaps are useful for animatio
          (e.g. animate cci*.png; <URL: http://www.imagemagick.org>),
          whereas postscript versions are good for hard copies.

  storms: Data object returned by CCI with cyclone statistics.

icyclone: Decides which cyclone to do the gradient wind estimate for
          (eg 1 is for the deepest cyclone, 2 for the second deepest,
          etc).

_V_a_l_u_e:

     A list: 'list(lon=lon, lat, tim, psl, yy, mm, dd, i, label,
     max.dpsl, max.speed, radius, rad.max.dpsl, dx, dy)'. The
     subobjects 'lon' (longitude: units degrees), 'lat' (latitude:
     units: degrees), 'psl' (local minimum pressure: units hPa),
     'max.dpsl' (pressure gradient: units Pa/m), 'max.speed' 
     (windspeed: units m/s if the units of SLP are in hPa), and
     'radius' (radius of the storm: units km) are
     '[1:nt,1:i.sim]'-matrices. 'v.grad' is the estimated gradient
     wind.

_A_u_t_h_o_r(_s):

     R.E. Benestad

_E_x_a_m_p_l_e_s:

     ## Not run: 
     # Shell script for running in batch (background proccess)
     #! /bin/bash
     cat > paper20e.R << EOF
     library(clim.pact)
     library(cyclones)
     source("cyclones/R/cyclones.R")

     a<- Sys.info()
     dir <- switch(substr(as.character(a[4]),1,9),
                   "saragasso"="/data1/hirham/",
                   "stratonim"="/data1/hirham/",
                   "virvelvin"="/home/rasmusb/data/data1/")

     filname.1 <- "/home/rasmusb/data/ERA40/era40_slp.nc"
     fname.1 <- "data/cyclones_ERA40.Rdata"
     vname.1 <- "msl"

     print("===================<  ERA 15  >===================")
     CCI(fname="data/cyclones_ERA40_r1.Rdata",dx=1,dy=1,fielddata=filname.1,
         vname=vname.1,label="ERA40: slp 1-degree res.",force365.25=TRUE,lplot=FALSE)
     EOF

     nice R CMD BATCH --no-save paper20e.R paper20e.out
     ## End(Not run)

