climatology: Climatology of a satin object

In satin: Visualisation and Analysis of Ocean Data Derived from Satellites

Climatology of a satin object

Description

This function calculates the percent coverage, mean, standard deviation, minimum and maximum for every pixel in a set of images stored in a single satin data object.

Usage

climatology(X, depth = NULL)

Arguments

X	a satin object as returned by read.nasaoc, read.ghrsst, read.osunpp, or read.cmems.
depth	an integer referring to a given depth level. Only meaningful for Copernicus data that includes variables at different depths.

Details

For Copernicus data files containing more than one variable, the read.cmems function returns a named list, with elements corresponding to each variable. In order to use these objects with climatology the appropriate indexing should be applied (see examples below).

Value

An object of class "satin" (see satin-class for details) where the third dimension in the data array accomodates coverage, mean, standard deviation, minimum and maximum. Also, an extra element (label) is included in the slot attribs to summarize the start and end times used for the climatology.

Author(s)

Héctor Villalobos and Eduardo González-Rodríguez

Examples

if(interactive()){
csst <- climatology(sst) # sst is a satin object with 12 monthly images 
                         # of sea surface temperature

# -- plots --

# coverage
plot(csst, period = 1)

# mean
plot(csst, period = 2)

# standard deviation
plot(csst, period = 3)

# minimum
plot(csst, period = 4)

# maximum
plot(csst, period = 5)
}
# For Copernicus data

data(dcmems) # load sample data
names(dcmems) # available variables 

# mean potential temperature (thetao) at 0.49 m
# using labels stored in slot period
cthetao1 <- climatology(dcmems$thetao, depth = 1)
plot(cthetao1, period = 2, main = cthetao1@period$label[2])

# standard deviation of thetao at 318 m
cthetao2 <- climatology(dcmems$thetao, depth = 5)
plot(cthetao2, period = 3, main = cthetao1@period$label[3])

satin documentation built on Sept. 23, 2022, 1:06 a.m.