#' Wrapper function for calculating mld, density difference between upper and lower water column, and pycnocline depth
#'
#' @dat Data frame containing dat, stationid, cruise, totdepth, latitude, and longitude columns
run_ctd_fns <- function(dat) {
profiles <- unique(dplyr::select(dat, stationid, cruise, totdepth, latitude, longitude))
profiles$mld <- -99
profiles$bld <- -99 ##
profiles$density.diff <- -99
profiles$pycnocline <- -99
profiles$t_above <- -99
profiles$t_below <- -99
profiles$s_above <- -99
profiles$s_below <- -99
profiles$rho_above <- -99
profiles$rho_below <- -99
profiles$t_average <- -99
profiles$s_average <- -99
for(i in 1:nrow(profiles)) {
profile.sel <- subset(dat, cruise == profiles$cruise[i] & stationid == profiles$stationid[i])
print(paste(profiles$cruise[i], profiles$stationid[i]))
profile.sel <- profile.sel[order(profile.sel$bindepth),]
profiles$mld[i] <- calculate_cokelet_mld(rho = profile.sel$sigma_t,
z = profile.sel$bindepth,
totdepth = max(profile.sel$bindepth),
ref.depth = 5)
profiles$bld[i] <- calculate_bld(rho = profile.sel$sigma_t,
z = profile.sel$bindepth,
totdepth = max(profile.sel$bindepth))
profiles$density.diff[i] <- calculate_cokelet_density_diff(mld = profiles$mld[i],
rho = profile.sel$sigma_t,
z = profile.sel$bindepth)
profiles$pycnocline[i] <- calculate_pycnocline(rho = profile.sel$sigma_t,
z = profile.sel$bindepth,
mld = profiles$mld[i])
tsrho.layers <- calculate_tsrho_by_layer(t = profile.sel$temperature,
s = profile.sel$salinity,
rho = profile.sel$sigma_t,
z = profile.sel$bindepth,
mld = profiles$mld[i])
profiles$t_above[i] <- tsrho.layers$t_above
profiles$t_below[i] <- tsrho.layers$t_below
profiles$s_above[i] <- tsrho.layers$s_above
profiles$s_below[i] <- tsrho.layers$s_below
profiles$rho_above[i] <- tsrho.layers$rho_above
profiles$rho_below[i] <- tsrho.layers$rho_below
profiles$t_average[i] <- tsrho.layers$t_average
profiles$s_average[i] <- tsrho.layers$s_average
}
return(profiles)
}
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