R: Hovmoller plots

hovmoller-methods {rasterVis}

R Documentation

Hovmoller plots

Description

Hovmoller plots of Raster objects.

Usage

## S4 method for signature 'RasterStackBrick'
hovmoller(object, dirXY=y, FUN=mean, 
digits=2, xlab='Direction', ylab='Time',
par.settings=rasterTheme(), xscale.components=xscale.raster,
add.contour=FALSE, labels=FALSE, region=TRUE, ...)

Arguments

`object`	A RasterStackBrick with a non-empty `z` slot.
`dirXY`	A direction as a function of the coordinates (see `xyLayer`).
`FUN`	A function to be applied to the zones calculated with `dirXY` and `zonal`.
`digits`	An integer, number of digits for `zonal`.
`xlab, ylab`	Labels of the axis.
`par.settings`	Customization of lattice. See `levelplot` and `rasterTheme` for details.
`xscale.components`	See `xscale.raster`.
`labels, region`	Customization of `contourplot` when `add.contour` is TRUE.
`add.contour`	Logical, if TRUE a contourplot with filled regions is drawn.
`...`	Additional arguments for the `contourplot` and `levelplot` functions.

Details

Extracted from wikipedia: "A Hovmöller diagram is a commonly used way of plotting meteorological data to highlight the role of waves. The axes of a Hovmöller diagram are typically longitude or latitude (abscissa or x-axis) and time (ordinate or y-axis) with the value of some field represented through color or shading." The direction defined by dirXY and the function FUN allows for a variety of diagrams with this method.

Author(s)

Oscar Perpiñán Lamigueiro

References

Hovmoller, E. 1949. The trough and ridge diagram. Tellus 1, 62–66.
http://www2.mmm.ucar.edu/episodes/Hovmoller/noJS/hovm200707.htm
http://www.esrl.noaa.gov/psd/map/clim/sst.shtml

Examples

## Not run: 
##Solar irradiation data from CMSAF http://dx.doi.org/10.5676/EUM_SAF_CM/RAD_MVIRI/V001
old <- setwd(tempdir())
download.file('https://raw.github.com/oscarperpinan/spacetime-vis/master/data/SISmm2008_CMSAF.zip',
   'SISmm2008_CMSAF.zip', method='wget')
unzip('SISmm2008_CMSAF.zip')

listFich <- dir(pattern='\\.nc')
stackSIS <- stack(listFich)
stackSIS <- stackSIS*24 ##from irradiance (W/m2) to irradiation Wh/m2

idx <- seq(as.Date('2008-01-15'), as.Date('2008-12-15'), 'month')

SISmm <- setZ(stackSIS, idx)
names(SISmm) <- month.abb

## Latitude as default
hovmoller(SISmm, xlab='Latitude')

## With contour lines and labels
hovmoller(SISmm, labels=TRUE, add.contour=TRUE,
          xlab='Latitude')

## Smooth color regions with latticeExtra::panel.2dsmoother
hovmoller(SISmm, panel=panel.2dsmoother, n=1000,
          labels=FALSE, add.contour=TRUE,
          xlab='Latitude')

## Using a function of coordinates
hovmoller(SISmm, dirXY=sqrt(x^2+y^2))

## End(Not run)

## Not run: 
library(zoo)
library(rasterVis)

## DESCRIPTION: http://iridl.ldeo.columbia.edu/SOURCES/.CAC/.sst/
setwd(tempdir())
download.file('http://iridl.ldeo.columbia.edu/SOURCES/.CAC/.sst/data.nc', destfile = 'SST.nc')
SST <- stack('SST.nc')
idx <- seq(as.Date('1970-01-01'), as.Date('2003-03-01'), by='month')
tt <- as.yearmon(idx)
SST <- setZ(SST, tt)
names(SST) <- as.character(tt)

## Extract month value from a Date or yearmon object
month <- function(x)format(x, '%m')
## Compute anomaly using monthly grouping with ave  
anomaly <- function(x){
    ## Monthly means
    mm <- ave(x, month(tt), FUN = mean)
    ## Monthly standard deviation
    msd <- ave(x, month(tt), FUN = sd)
    ## anomaly
    (x - mm)/msd
}
## Use anomaly with calc
SSTanom <- calc(SST, anomaly)
SSTanom <- setZ(SSTanom, tt)

## Ok, let's see the result
hovmoller(SSTanom,
          at = seq(-3, 3, .25),
          panel = panel.levelplot.raster,
          interpolate = TRUE,
          yscale.components = yscale.raster.subticks,
          par.settings = BuRdTheme)

## End(Not run)

[Package rasterVis version 0.44 Index]