Plots the time-mean of a variable stored in NetCDF model output on a regular grid
This function plots the time-mean, spatial-mean, zonal mean, and seasonal cycle of variable stored in NetCDF model output. The function expects model data to be on a regular grid.
plotNc(long.name, nc.mod, mod.id, unit.conv.mod, variable.unit, timePeriod, outlier.factor = 1000, my.xlim = c(-180, 180), my.ylim = c(-60, 85), plot.width = 8, plot.height = 3.8, outputDir = FALSE)
long.name |
A string that gives the full name of the variable, e.g. 'Gross primary productivity' |
nc.mod |
A string that gives the path and name of the netcdf file that contains the model output, e.g. '/home/model_gpp.nc' |
mod.id |
A string that identifies the source of the reference data set, e.g. 'CLASSIC' |
unit.conv.mod |
A number that is used as a factor to convert the unit of the model data, e.g. 86400 |
variable.unit |
A string that gives the final units using LaTeX notation, e.g. 'gC m$^-2$ day$^-1$' |
timePeriod |
A string that gives the time period over which to average the data, e.g. c('1980-01', '2017-12') |
outlier.factor |
A number that is used to define outliers, e.g. 10. Plotting raster objects that contain extreme outliers lead to figures where most grid cells are presented by a single color since the color legend covers the entire range of values. To avoid this, the user may define outliers that will be masked out and marked with a red dot. Outliers are all values that exceed the interquartile range multiplied by the outlier factor defined here. |
my.xlim |
An R object that gives the longitude range that you wish to plot, e.g. c(-180, 180) |
my.ylim |
An R object that gives the longitude range that you wish to plot, e.g. c(-90, 90) |
plot.width |
Number that gives the plot width, e.g. 8 |
plot.height |
Number that gives the plot height, e.g. 4 |
outputDir |
A string that gives the output directory, e.g. '/home/project/study'. The output will only be written if the user specifies an output directory |
Figures in PDF format that show the time-mean, spatial-mean, zonal mean, and seasonal cycle.
library(amber)
library(classInt)
library(doParallel)
library(foreach)
library(Hmisc)
library(latex2exp)
library(ncdf4)
library(parallel)
library(raster)
library(rgdal)
library(rgeos)
library(scico)
library(sp)
library(stats)
library(utils)
library(viridis)
library(xtable)
long.name <- 'Gross primary productivity'
nc.mod <- system.file('extdata/modelRegular', 'gpp_monthly.nc', package = 'amber')
mod.id <- 'CLASSIC' # define a model experiment ID
unit.conv.mod <- 86400*1000 # optional unit conversion for model data
variable.unit <- 'gC m$^{-2}$ day$^{-1}$' # unit after conversion (LaTeX notation)
timePeriod <- c('1980-01', '2017-12')
outlier.factor <- 1
plotNc(long.name, nc.mod, mod.id, unit.conv.mod, variable.unit, timePeriod, outlier.factor)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.