scores.site.notime: Scores for site-level reference data that do not vary in time
In amber: Automated Model Benchmarking R Package

Description Usage Arguments Value Examples

This function compares model output against site-level measurements such as carbon stocks. The performance of a model is expressed through scores that range from zero to one, where increasing values imply better performance. Contrary to the function scores.grid.time, only two scores are computed (bias score S_{bias} and spatial distribution score, S_{dist}) since the reference data do not vary with time. Contrary to scores.grid.time, the bias is relative to the absolute reference mean value rather than the reference standard deviation. Again, this is because the reference data do not vary with time:

(i) \ bias(λ, φ)=\overline{v_{mod}}(λ, φ)-\overline{v_{ref}}(λ, φ)

(ii) \ \varepsilon_{bias}=|bias(λ, φ)|/|\overline{v_{ref}}(λ, φ)|

(iii) \ s_{bias}(λ, φ)=e^{-\varepsilon_{bias}(λ, φ)}

(iv) \ S_{bias}=\overline{\overline{s_{bias}}}

scores.site.notime(long.name, nc.mod, ref.csv, mod.id, ref.id,
  unit.conv.mod, unit.conv.ref, variable.unit, score.weights = c(1, 2, 1,
  1, 1), rotate.me = TRUE, irregular = FALSE,
  my.projection = "+proj=longlat +ellps=WGS84",
  shp.filename = system.file("extdata/ne_110m_land/ne_110m_land.shp",
  package = "amber"), my.xlim = c(-180, 180), my.ylim = c(-60, 85),
  plot.width = 8, plot.height = 3.8, numCores = 2,
  period = c("1980-01", "2017-12"), outputDir = FALSE,
  variable.name = FALSE, meanPerGridCell = TRUE, myCex = 0.5,
  subcaption = "")

`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'
`ref.csv`	A string that gives the path and name of the csv file that contains the reference data output, e.g. '/home/reference_biomass.csv'. The columns must be in the following order: Plot ID, longitude, latitude, data values.
`mod.id`	A string that identifies the source of the reference data set, e.g. 'CanESM2'
`ref.id`	A string that identifies the source of the reference data set, e.g. 'MODIS'
`unit.conv.mod`	A number that is used as a factor to convert the unit of the model data, e.g. 86400
`unit.conv.ref`	A number that is used as a factor to convert the unit of the reference data, e.g. 86400
`variable.unit`	A string that gives the final units using LaTeX notation, e.g. 'gC m$^-2$ day$^-1$'
`score.weights`	R object that gives the weights of each score (S_{bias}, S_{rmse}, S_{phase}, S_{iav}, S_{dist}) that are used for computing the overall score, e.g. c(1,2,1,1,1)
`rotate.me`	logical: TRUE if you want longitudes to range from -180 to 180 degrees and FALSE if you want longitudes to range from 0 to 360 degrees
`irregular`	logical: TRUE if data is on an irregular grid and FALSE if data is on a regular grid
`my.projection`	A string that gives the projection of the irregular grid
`shp.filename`	A string that gives the coastline shapefile
`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
`numCores`	An integer that defines the number of cores, e.g. 2
`period`	An R obect that gives the period over which to average the model data, e.g. c('1980-01', '2017-12')
`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.
`variable.name`	A string with the variable name, e.g. 'GPP'. If FALSE, the variable name stored in the NetCDF file will be used instead. Default is FALSE.
`meanPerGridCell`	Logical. If TRUE, then values from different sites that are located in the same grid cell are averaged. Default is set to TRUE.
`myCex`	A number that determines the size of the dots in the Figure. Default is set to 0.7.
`subcaption`	A string that defines the subcaption of the figure, e.g. '(a)'.

(1) Figures in PDF format that show maps of the model mean, reference mean, and bias. (2) Four text files: (i) score values and (ii) score inputs for each individual site, and (iii) score values and (iv) score inputs averaged across sites.

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)

# (1) Global plots on a regular grid
long.name <- 'soil carbon'
nc.mod <- system.file('extdata/modelRegular', 'cSoil_monthly.nc', package = 'amber')
ref.csv <- system.file('extdata/siteLevelRefData', 'siteLevelDataNoTime.csv', package = 'amber')
mod.id <- 'CLASSIC' # define a model experiment ID
ref.id <- 'ABC' # give reference dataset a name
unit.conv.mod <- 1 # optional unit conversion for model data
unit.conv.ref <- 1 # optional unit conversion for reference data
variable.unit <- 'kgC m$^{-2}$' # unit after conversion (LaTeX notation)

# Short version using default settings:
scores.site.notime(long.name, nc.mod, ref.csv, mod.id, ref.id,
unit.conv.mod, unit.conv.ref, variable.unit)

# To zoom into a particular region:
scores.site.notime(long.name, nc.mod, ref.csv, mod.id, ref.id, unit.conv.mod,
unit.conv.ref, variable.unit, score.weights = c(1, 2, 1, 1, 1),
my.xlim = c(-150, -60), my.ylim = c(20, 60), plot.width = 6, plot.height = 3.8)

# (2) Regional plots on a rotated grid
nc.mod <- system.file('extdata/modelRotated', 'cSoil_monthly.nc', package = 'amber')
ref.csv <- system.file('extdata/siteLevelRefData', 'siteLevelDataNoTime.csv', package = 'amber')
mod.id <- 'CLASSIC' # define a model experiment ID
ref.id <- 'ABC' # give reference dataset a name
unit.conv.mod <- 1 # optional unit conversion for model data
unit.conv.ref <- 1 # optional unit conversion for reference data
variable.unit <- 'kgC m$^{-2}$' # unit after conversion (LaTeX notation)
rotate.me <- FALSE
irregular <- TRUE
my.projection <-'+proj=ob_tran +o_proj=longlat +o_lon_p=83. +o_lat_p=42.5 +lon_0=263.'
# shp.filename <- system.file('extdata/ne_50m_admin_0_countries/ne_50m_admin_0_countries.shp',
#  package = 'amber')
shp.filename <- system.file("extdata/ne_110m_land/ne_110m_land.shp", package = "amber")
my.xlim <- c(-171, 0) # longitude range that you wish to plot
my.ylim <- c(32, 78) # latitude range that you wish to plot
plot.width <- 7
plot.height <- 3.8
numCores <- 2

scores.site.notime(long.name, nc.mod, ref.csv, mod.id, ref.id,
unit.conv.mod, unit.conv.ref, variable.unit, rotate.me = TRUE, irregular = TRUE,
my.projection = my.projection, shp.filename = shp.filename,
my.xlim = my.xlim,  my.ylim = my.ylim, plot.width = plot.width, plot.height = plot.height)
 #donttest