hovmoller-methods: Hovmoller plots

In rasterVis: Visualization Methods for Raster Data

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, ...)

## S4 method for signature 'SpatRaster'
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, or a SpatRaster with a time index.
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.

• https://www2.mmm.ucar.edu/episodes/Hovmoller/noJS/hovm200707.htm

• https://psl.noaa.gov/map/clim/sst.shtml

See Also

levelplot, zonal, panel.2dsmoother

Examples

## Not run: 
library(raster)
library(terra)

dataURL <- "https://raw.github.com/oscarperpinan/bookvis/master/data/"

##Solar irradiation data from CMSAF http://dx.doi.org/10.5676/EUM_SAF_CM/RAD_MVIRI/V001
old <- setwd(tempdir())
download.file(paste0(dataURL, "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

SISmmt <- rast(SISmm)
time(SISmmt) <- getZ(SISmm)

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

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

## Smooth color regions with latticeExtra::panel.2dsmoother
library(latticeExtra)

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)

## 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)

rasterVis documentation built on Nov. 2, 2023, 5:25 p.m.