cimp5_1951_2000_cv | R Documentation |
Coefficient variation of the mean historical export POC flux to seafloor, bottom dissolved oxygen concentration, hydrogen ion concentration and temperature were averaged from the Geophysical Fluid Dynamics Laboratory’s ESM 2G (GFDL-ESM-2G), Institut Pierre Simon Laplace’s CM6-MR (IPSL-CM5A-MR) and Max Planck Institute’s ESM-MR (MPI-ESM-MR) within the Coupled Models Intercomparison Project Phase 5 (CIMP5).
A RasterBrick object of 4 raster layers:
Coefficient variation of the mean export POC flux to seafloor (%)
Coefficient variation of the mean dissolved oxygen concentration at seafloor (%)
Coefficient variation of the mean pH at seafloor (%)
Coefficient variation of the mean potential temperature at seafllor (%)
Coefficient variation of aragonite Concentration (%)
Coefficient variation of calcite Concentration (%)
Coefficient variation of mole Concentration of Carbonate expressed as Carbon in Sea Water (%)
Coefficient variation of mole Concentration of Aragonite expressed as Carbon in Sea Water at Saturation (%)
Coefficient variation of mole Concentration of Calcite expressed as Carbon in Sea Water at Saturation (%)
Yearly mean from 1951 to 2000 (historical) were calculated for the GFDL-ESM-2G, IPSL-CM5A-MR and MPI-ESM-MR respectively. Coefficient variation of the mean
was calculated among the three models for the periods of 1951 to 2000. The export POC flux at seafloor was computed from the
export production at 100 m (epc100) using the Martin curve (Martin et al., 1987) following the quation:
Flux = epc100*(depth/export depth)^-0.858
. The depth use etopo1
and export depth was set to 100 m.
All CIMP5 data were download from
https://esgf-node.llnl.gov/search/esgf-llnl/.
https://esgf-node.llnl.gov/search/esgf-llnl/
# Mask the raster brick by 200 to 2000 m
r0 <- mask(cimp5_1951_2000_cv, mask2000)
# Only show color between 1 to 99 percentile
r <- raster()
for(i in 1:4){
d <- subset(r0, i)
ma <- quantile(d, 0.99)
mi <- quantile(d, 0.01)
d[d>ma] <- ma
d[d<mi] <- mi
r <- addLayer(r, d)
}
names(r) <- names(r0)
# plot on google earth
library(plotKML)
for(i in 1:4){
plotKML(subset(r, i), folder.name=names(r)[i],
colour_scale = jet.col.log(100),
raster_name = paste(names(r)[i], "png", sep="."))
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.