cimp5_1951_2000_sd: Model-Averaging Decadal Standard deviation of Seafloor...

In chihlinwei/SCC85: Seafloor Climate Change Projections from CIMP5

Model-Averaging Decadal Standard deviation of Seafloor Climatic Data during 1951 to 2000

Description

Emsemble average of the decadal Standard deviation of seafloor (bottom-most) projections based on historical scenario of CIMP5 experiment.

Format

A RasterBrick object of 4 raster layers:

epc_sd_1951_to_2000

Standard deviation of export POC flux to seafloor (mg C m^-2 d^-1)

o2_sd_1951_to_2000

Standard deviation of dissolved oxygen concentration at seafloor (mol m^-3)

ph_sd_1951_to_2000

Standard deviation of pH at seafloor (M)

thetao_sd_1951_to_2000

Standard deviation of potential temperature at seafllor (K)

arag_sd_1951_to_2000

Standard deviation of aragonite Concentration (mol m-3)

calc_sd_1951_to_2000

Standard deviation of calcite Concentration (mol m-3)

co3_sd_1951_to_2000

Standard deviation of mole Concentration of Carbonate expressed as Carbon in Sea Water (mol m-3)

co3satarag_sd_1951_to_2000

Standard deviation of carbonate ion concentration for seawater in equilibrium with pure aragonite (mol m-3)

co3satcalc_sd_1951_to_2000

Standard deviation of carbonate ion concentration for seawater in equilibrium with pure calcite (mol m-3)

aragsat_sd_1951_to_2000

Standard deviation of Aragonite Saturation State

calcsat_sd_1951_to_2000

Standard deviation of Calcite Saturation State

Details

Yearly mean projections from 1951 to 2000 were calculated from each of the GFDL-ESM-2G, IPSL-CM5A-MR and MPI-ESM-MR. Decadal Standard deviation was calculated from the yearly mean and than averaged across the three models.

Source

https://esgf-node.llnl.gov/search/esgf-llnl/

Examples

# Mask the raster brick by 200 to 2000 m
r0 <- mask(cimp5_1951_2000_sd, 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
  if(i==2) d <- d*15.9994 # to mg/L
  if(i==3) d <- log10(d)*(-1) # to total scale
  if(i==4) d <- d-273.15 # to degree C
  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="."))
}

chihlinwei/SCC85 documentation built on Sept. 15, 2023, 4:47 a.m.