#' Model-Averaging of Decadal Mean Seafloor Climatic Data during 1951 to 2000
#'
#' Ensemble average of the decadal mean seafloor (bottom-most) projections based on historical scenario of CIMP5 experiment.
#'
#' @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 mean was calculated from the yearly mean and than averaged across the three models.
#' @docType data
#' @keywords datasets
#' @format A RasterBrick object of 4 raster layers:
#' \describe{
#' \item{epc_av_1951_to_2000}{Mean export POC flux to seafloor (mg C m^-2 d^-1)}
#' \item{o2_av_1951_to_2000}{Mean dissolved oxygen concentration at seafloor (mol m^-3)}
#' \item{ph_av_1951_to_2000}{Mean pH at seafloor}
#' \item{thetao_av_1951_to_2000}{Mean potential temperature at seafllor (K)}
#' \item{arag_av_1951_to_2000}{Aragonite Concentration (mol m-3)}
#' \item{calc_av_1951_to_2000}{Calcite Concentration (mol m-3)}
#' \item{co3_av_1951_to_2000}{Mole Concentration of Carbonate expressed as Carbon in Sea Water (mol m-3)}
#' \item{co3satarag_av_1951_to_2000}{Carbonate ion concentration for seawater in equilibrium with pure aragonite (mol m-3)}
#' \item{co3satcalc_av_1951_to_2000}{Carbonate ion concentration for seawater in equilibrium with pure calcite (mol m-3)}
#' \item{aragsat_av_1951_to_2000}{Aragonite Saturation State}
#' \item{calcsat_av_1951_to_2000}{Calcite Saturation State}
#' }
#' @source \url{https://esgf-node.llnl.gov/search/esgf-llnl/}
#' @name cimp5_1951_2000_av
#' @examples
#' # Mask the raster brick by 200 to 2000 m
#' r0 <- mask(cimp5_1951_2000_av, 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){
#' if(i==1|i==4) cols <- jet.col.log(100) else cols <- jet.colors(100)
#' plotKML(subset(r, i), folder.name=names(r)[i],
#' colour_scale = cols,
#' raster_name = paste(names(r)[i], "png", sep="."))
#' }
NULL
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