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compute_nao <- function(data, recipe, obsproj, plot_ts, plot_sp,
alpha, logo = NULL) {
## TODO: if fcst object in data compute the nao too
if (!is.null(data$fcst)) {
warning("NAO computed only for hindcast data.")
}
# Check if subsetting the data for the region is required
lons <- data$hcst$coords$longitude
lats <- data$hcst$coords$latitude
subset_needed <- FALSE
nao_region <- c(lonmin = -80, lonmax = 40,
latmin = 20, latmax = 80)
if (any(lons < 0)) { #[-180, 180]
if (!(min(lons) > -90 & min(lons) < -70 &
max(lons) < 50 & max(lons) > 30)) {
subset_needed <- TRUE
}
} else { #[0, 360]
if (any(lons >= 50 & lons <= 270)) {
susbset_needed <- TRUE
} else {
lon_E <- lons[which(lons < 50)]
lon_W <- lons[-which(lons < 50)]
if (max(lon_E) < 30 | min(lon_W) > 290) {
subset_needed <- TRUE
}
}
}
if (any(max(lats) > 80 & min(lats) < 20)) {
subset_needed <- TRUE
}
if (subset_needed) {
warning("The data is being subsetted for 20N-80N and 80W-40E region.")
hcst1 <- ClimProjDiags::SelBox(data$hcst$data,
lon = as.vector(lons),
lat = as.vector(lats),
region = nao_region,
londim = "longitude",
latdim = "latitude")
obs1 <- ClimProjDiags::SelBox(data$obs$data,
lon = as.vector(lons),
lat = as.vector(lats),
region = nao_region,
londim = "longitude",
latdim = "latitude")
hcst <- s2dv_cube(data = hcst1$data, lat = hcst1$lat, lon = hcst1$lon,
Variable = c(data$hcst$Variable[1], level = 'surface'),
data$hcst$Va, Datasets = data$hcst$Datasets,
time_dims = c('syear', 'time'),
Dates = data$hcst$Dates)
obs <- s2dv_cube(data = obs1$data, lat = obs1$lat, lon = obs1$lon,
Variable = c(data$obs$Variable[1], level = 'surface'),
Datasets = data$obs$Datasets, time_dims = c('syear', 'time'))
# TODO check and create data object for the next steps
data <- list(hcst = hcst, obs = obs)
lons <- data$hcst$coords$longitude
lats <- data$hcst$coords$latitude
obs1 <- hcst1 <- NULL
gc()
}
nao <- NAO(exp = data$hcst$data, obs = data$obs$data,
lat = data$hcst$coords$latitude,
lon = data$hcst$coords$longitude,
time_dim = 'syear',
memb_dim = 'ensemble', space_dim = c('latitude', 'longitude'),
ftime_dim = 'time', ftime_avg = NULL,
obsproj = obsproj, ncores = recipe$Analysis$ncores)
## Standardisation:
nao$exp <- Apply(list(nao$exp), target_dims = c('syear', 'ensemble'),
fun = function(x) {
sd <- sqrt(var(as.vector(x), na.rm = TRUE))
means <- mean(as.vector(x), na.rm = TRUE)
res <- apply(x, c(1,2), function(x) {(x-means)/sd})},
ncores = recipe$Analysis$ncores)$output1
nao$obs <- Apply(list(nao$obs), target_dims = c('syear', 'ensemble'),
fun = function(x) {
sd <- sqrt(var(as.vector(x), na.rm = TRUE))
means <- mean(as.vector(x), na.rm = TRUE)
res <- apply(x, c(1,2), function(x) {(x-means)/sd})},
ncores = recipe$Analysis$ncores)$output1
nao$exp <- InsertDim(nao$exp, posdim = 1, lendim = 1, name = 'region')
nao$obs <- InsertDim(nao$obs, posdim = 1, lendim = 1, name = 'region')
hcst_dates <- data$hcst$attrs$Dates
hcst_dates <- drop(data$hcst$attrs$Dates)
if (!("time" %in% names(dim(hcst_dates)))) {
if (is.null(dim(hcst_dates))) {
hcst_dates <- array(hcst_dates, c(syear = length(hcst_dates)))
}
hcst_dates <- InsertDim(hcst_dates, pos = 1, len = 1, name = 'time')
hcst_dates <- as.POSIXct(hcst_dates, origin = '1970-01-01', tz = 'UTC')
}
nao <- list(hcst = s2dv_cube(
data = nao$exp,
varName = "nao",
metadata = list(
region = list(name = "NAO region",
lats_range = paste0(range(lats)),
lons_range = paste0(range(lons))),
time = data$hcst$attrs$Variable$metadata$time,
nao = list(units = 'adim',
longname = 'North Atlantic Oscillation')),
Dates = hcst_dates,
Dataset = recipe$Analysis$Datasets$System$name),
obs = s2dv_cube(
data = nao$obs,
varName = "nao",
metadata = list(
region = list(name = "NAO region",
lats_range = paste0(range(lats)),
lons_range = paste0(range(lons))),
time = data$obs$attrs$Variable$metadata$time,
nao = list(units = 'adim',
longname = 'North Atlantic Oscillation')),
Dates = data$obs$attrs$Dates,
Dataset = recipe$Analysis$Datasets$Reference$name))
if (recipe$Analysis$Workflow$Indices$NAO$save == 'all') {
file_dest <- paste0(recipe$Run$output_dir, "/outputs/Indices/")
if (tolower(recipe$Analysis$Horizon) == "seasonal") {
# Use startdates param from SaveExp to correctly name the files:
if (length(data$hcst$attrs$source_files) == dim(data$hcst$data)['syear']) {
file_dates <- Apply(data$hcst$attrs$source_files, target_dim = NULL,
fun = function(x) {
pos <- which(strsplit(x, "")[[1]] == ".")
res <- substr(x, pos-8, pos-1)
})$output1
}
} else if (tolower(recipe$Analysis$Horizon) == "decadal"){
file_dates <- paste0('s',
recipe$Analysis$Time$hcst_start : recipe$Analysis$Time$hcst_end)
}
# need to recover original dimensions after saving to make Skill module work
nao_original_dims_hcst <- nao$hcst$data
nao$hcst$data <- .drop_indices_dims(nao$hcst$data)
CST_SaveExp(data = nao$hcst,
destination = file_dest,
startdates = as.vector(file_dates),
dat_dim = NULL, sdate_dim = 'syear',
ftime_dim = 'time', var_dim = NULL,
memb_dim = 'ensemble')
nao_original_dims_obs <- nao$obs$data
nao$obs$data <- .drop_indices_dims(nao$obs$data)
CST_SaveExp(data = nao$obs, #res,
destination = file_dest,
startdates = as.vector(file_dates),
dat_dim = NULL, sdate_dim = 'syear',
ftime_dim = 'time', var_dim = NULL,
memb_dim = NULL)
nao$hcst$data <- nao_original_dims_hcst
nao$obs$data <- nao_original_dims_obs
nao_original_dims_hcst <- nao_original_dims_obs <- NULL
gc()
}
# Read variable long_name to plot it
conf <- yaml::read_yaml("conf/variable-dictionary.yml")
var_name <- conf$vars[[which(names(conf$vars) ==
recipe$Analysis$Variables$name)]]$long
if (plot_ts) {
dir.create(paste0(recipe$Run$output_dir, "/plots/Indices/"),
showWarnings = F, recursive = T)
source("modules/Indices/R/plot_deterministic_forecast.R")
for (tstep in 1:dim(nao$hcst$data)['time']) {
mes <- as.numeric(substr(recipe$Analysis$Time$sdate, 1,2)) +
(tstep - 1) + (recipe$Analysis$Time$ftime_min - 1)
mes <- ifelse(mes > 12, mes - 12, mes)
fmonth <- sprintf("%02d", tstep - 1 + recipe$Analysis$Time$ftime_min)
obs <- Subset(nao$obs$data, along = 'time', ind = tstep)
exp <- Subset(nao$hcst$data, along = 'time', ind = tstep)
if (gsub(".", "", recipe$Analysis$Datasets$System$name) == "") {
system <- recipe$Analysis$Datasets$System$name
} else {
system <-gsub(".", "", recipe$Analysis$Datasets$System$name)
}
if (tolower(recipe$Analysis$Horizon) == "seasonal") {
toptitle <- paste("NAO Index\n",
month.abb[mes],
"/", recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/NAO_",
system, "_", recipe$Analysis$Datasets$Reference$name,
"_s", recipe$Analysis$Time$sdate, "_ftime",
sprintf("%02d", tstep - 1 + recipe$Analysis$Time$ftime_min), ".png")
caption <- paste0("NAO method: ",
ifelse(recipe$Analysis$Workflow$Indices$NAO$obsproj,
"Pobs", "Pmod"), " (Doblas-Reyes et al., 2003)\n",
"Nominal start date: 1st of ",
month.name[as.numeric(substr(recipe$Analysis$Time$sdate, 1,2))],
"\n",
"Forecast month: ", fmonth, "\n")
xlabs <- as.numeric(substr(file_dates, 1, 4))
} else if (tolower(recipe$Analysis$Horizon) == "decadal"){
toptitle <- paste("NAO Index\n",
"Lead time", fmonth,
" / Start dates", recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
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plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/NAO_",
system, "_", recipe$Analysis$Datasets$Reference$name,
"_ftime",
sprintf("%02d", tstep - 1 + recipe$Analysis$Time$ftime_min), ".png")
caption <- paste0("NAO method: ",
ifelse(recipe$Analysis$Workflow$Indices$NAO$obsproj,
"Pobs", "Pmod"), " (Doblas-Reyes et al., 2003)\n",
"Start date month: ",
month.name[get_archive(recipe)$System[[recipe$Analysis$Datasets$System$name]]$initial_month],
"\n",
"Lead time: ", fmonth, "\n")
xlabs <- file_dates
} else {
toptitle <- NULL
warning("The plot title is not defined for this time horizon. ",
"The plots will not have a title.")
}
plot_deterministic_forecast(obs, exp,
time_dim = 'syear',
member_dim = 'ensemble', style = 'boxplot',
xlabs = xlabs,
title = toptitle, fileout = plotfile,
caption = caption, caption_line = 6.5,
legend_text = c(
recipe$Analysis$Datasets$Reference$name,
recipe$Analysis$Datasets$System$name))
}
}
if (plot_sp) {
## TODO: To be removed when s2dv is released:
source("modules/Visualization/R/tmp/PlotRobinson.R")
source("modules/Indices/R/correlation_eno.R")
source("modules/Visualization/R/get_proj_code.R")
dir.create(paste0(recipe$Run$output_dir, "/plots/Indices/"),
showWarnings = F, recursive = T)
# Get correct code for stereographic projection
projection_code <- get_proj_code(proj_name = "stereographic")
correl_obs <- Apply(list(data$obs$data, nao$obs$data),
target_dims = 'syear', fun = .correlation_eno,
time_dim = 'syear', method = 'pearson', alpha = alpha,
test.type = 'two-sided', pval = FALSE,
ncores = recipe$Analysis$ncores)
correl_hcst <- Apply(list(data$hcst$data, nao$hcst$data),
target_dims = c('syear', 'ensemble'),
fun = function(x, y) {
x <- apply(x, 1, mean, na.rm = TRUE)
y <- apply(y, 1, mean, na.rm = TRUE)
dim(y) <- c(syear = length(y))
dim(x) <- c(syear = length(x))
res <- .correlation_eno(x, y,
time_dim = 'syear', method = 'pearson', alpha = alpha,
test.type = 'two-sided', pval = FALSE)},
ncores = recipe$Analysis$ncores)
correl_hcst_full <- Apply(list(data$hcst$data, nao$hcst$data),
target_dims = c('syear', 'ensemble'),
fun = function(x,y) {
dim(y) <- c(syear = length(y))
dim(x) <- c(syear = length(x))
res <- .correlation_eno(x, y,
time_dim = 'syear', method = 'pearson', alpha = alpha,
test.type = 'two-sided', pval = FALSE)},
ncores = recipe$Analysis$ncores)
for (tstep in 1:dim(nao$obs$data)['time']) {
fmonth <- sprintf("%02d", tstep - 1 + recipe$Analysis$Time$ftime_min)
## Observations
map <- drop(Subset(correl_obs$r, along = 'time', ind = tstep))
sig <- drop(Subset(correl_obs$sign, along = 'time', ind = tstep))
if (tolower(recipe$Analysis$Horizon) == "seasonal") {
mes <- as.numeric(substr(recipe$Analysis$Time$sdate, 1,2)) +
(tstep - 1) + (recipe$Analysis$Time$ftime_min - 1)
mes <- ifelse(mes > 12, mes - 12, mes)
toptitle <- paste(recipe$Analysis$Datasets$Reference$name, "\n",
"NAO Index -",var_name, "\n",
" Correlation /", month.abb[mes],
"/", recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/NAO_correlation_",
recipe$Analysis$Variable$name, "_",
recipe$Analysis$Datasets$Reference$name,
"_s", recipe$Analysis$Time$sdate,
"_ftime", fmonth, ".png")
caption <- paste0("NAO method: ",
ifelse(recipe$Analysis$Workflow$Indices$NAO$obsproj,
"Pobs", "Pmod"), " (Doblas-Reyes et al., 2003)\n",
"Nominal start date: 1st of ",
month.name[as.numeric(substr(recipe$Analysis$Time$sdate, 1,2))],
"\n",
"Forecast month: ", fmonth, "\n",
"Pearson correlation; alpha = ", alpha)
} else if (tolower(recipe$Analysis$Horizon) == "decadal") {
toptitle <- paste(recipe$Analysis$Datasets$Reference$name, "\n",
"NAO Index -",var_name, "\n",
" Correlation / Start dates ",
recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/NAO_correlation_",
recipe$Analysis$Variable$name, "_",
recipe$Analysis$Datasets$Reference$name,
"_ftime", fmonth, ".png")
caption <- paste0("NAO method: ",
ifelse(recipe$Analysis$Workflow$Indices$NAO$obsproj,
"Pobs", "Pmod"), " (Doblas-Reyes et al., 2003)\n",
"Start date: month ",
month.name[get_archive(recipe)$System[[recipe$Analysis$Datasets$System$name]]$initial_month],
"\n",
"Forecast month: ", fmonth, "\n",
"Pearson correlation; alpha = ", alpha)
} else {
toptitle <- NULL
warning("The plot title is not defined for this time horizon. ",
"The plots will not have a title.")
}
if (gsub(".", "", recipe$Analysis$Datasets$System$name) == "") {
system <- recipe$Analysis$Datasets$System$name
} else {
system <- gsub(".", "", recipe$Analysis$Datasets$System$name)
}
PlotRobinson(map, lon = lons, lat = lats, target_proj = projection_code,
lat_dim = 'latitude', lon_dim = 'longitude',
legend = 's2dv', style = 'polygon',
toptitle = toptitle, crop_coastlines = nao_region,
caption = caption, mask = sig, bar_extra_margin = c(4,0,4,0),
fileout = plotfile, width = 8, height = 6,
brks = seq(-1, 1, 0.2), cols = brewer.pal(10, 'PuOr'))
## Ensemble-mean
map <- drop(Subset(correl_hcst$r, along = 'time', ind = tstep))
sig <- drop(Subset(correl_hcst$sign, along = 'time', ind = tstep))
if (tolower(recipe$Analysis$Horizon) == "seasonal") {
toptitle <- paste(recipe$Analysis$Datasets$System$name, "\n",
"NAO Index -", var_name, "\n",
" Correlation /", month.abb[mes],
"/", recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/NAO_correlation_",
recipe$Analysis$Variable$name, "_ensmean_",
system,
"_s", recipe$Analysis$Time$sdate,
"_ftime", fmonth, ".png")
caption <- paste0("NAO method: ",
ifelse(recipe$Analysis$Workflow$Indices$NAO$obsproj,
"Pobs", "Pmod"), " (Doblas-Reyes et al., 2003)\n",
"Correlation ensemble mean\n",
"Nominal start date: 1st of ",
month.name[as.numeric(substr(recipe$Analysis$Time$sdate, 1,2))],
"\n",
"Forecast month: ", fmonth, "\n",
"Pearson correlation; alpha = ", alpha)
} else if (tolower(recipe$Analysis$Horizon) == "decadal"){
toptitle <- paste(recipe$Analysis$Datasets$System$name,"\n",
"NAO Index -",var_name, "\n",
" Correlation / Start dates ",
recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/NAO_correlation_",
recipe$Analysis$Variable$name, "_ensmean_",
system,
recipe$Analysis$Datasets$Reference$name,
"_ftime", fmonth, ".png")
caption <- paste0("NAO method: ",
ifelse(recipe$Analysis$Workflow$Indices$NAO$obsproj,
"Pobs", "Pmod"), " (Doblas-Reyes et al., 2003)\n",
"Correlation ensemble mean\n",
"Start date month: ",
month.name[get_archive(recipe)$System[[recipe$Analysis$Datasets$System$name]]$initial_month],
"\n",
"Forecast month: ", fmonth, "\n",
"Pearson correlation; alpha = ", alpha)
} else {
toptitle <- NULL
warning("The plot title is not defined for this time horizon. ",
"The plots will not have a title.")
}
PlotRobinson(map, lon = lons, lat = lats, target_proj = projection_code,
lat_dim = 'latitude', lon_dim = 'longitude',
legend = 's2dv', bar_extra_margin = c(4,0,4,0),
toptitle = toptitle, style = 'polygon',
caption = caption, mask = sig, crop_coastline = nao_region,
fileout = plotfile, width = 8, height = 6,
brks = seq(-1, 1, 0.2), cols = brewer.pal(10, 'PuOr'))
# Full hcst corr
map <- drop(Subset(correl_hcst_full$r, along = 'time', ind = tstep))
sig <- drop(Subset(correl_hcst_full$sign, along = 'time', ind = tstep))
if (tolower(recipe$Analysis$Horizon) == "seasonal") {
toptitle <- paste(recipe$Analysis$Datasets$System$name,"\n",
"NAO Index -",var_name, "\n",
" Correlation /", month.abb[mes],
"/", recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/NAO_correlation_",
recipe$Analysis$Variable$name, "_member_",
system,
"_s", recipe$Analysis$Time$sdate,
"_ftime", fmonth, ".png")
caption <- paste0("NAO method: ",
ifelse(recipe$Analysis$Workflow$Indices$NAO$obsproj,
"Pobs", "Pmod"), " (Doblas-Reyes et al., 2003)\n",
"Correlation all members\n",
"Nominal start date: 1st of ",
month.name[as.numeric(substr(recipe$Analysis$Time$sdate, 1,2))],
"\n",
"Forecast month: ", fmonth, "\n",
"Pearson correlation; alpha = ", alpha)
} else if (tolower(recipe$Analysis$Horizon) == "decadal"){
toptitle <- paste(recipe$Analysis$Datasets$System$name,"\n",
"NAO Index -",var_name, "\n",
" Correlation / Start dates ",
recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/NAO_correlation_",
recipe$Analysis$Variable$name, "_member_",
system,
recipe$Analysis$Datasets$Reference$name,
"_ftime", fmonth, ".png")
caption <- paste0("NAO method: ",
ifelse(recipe$Analysis$Workflow$Indices$NAO$obsproj,
"Pobs", "Pmod"), " (Doblas-Reyes et al., 2003)\n",
"Correlation all members\n",
"Start date month: ",
month.name[get_archive(recipe)$System[[recipe$Analysis$Datasets$System$name]]$initial_month],
"\n",
"Forecast month: ", fmonth, "\n",
"Pearson correlation; alpha = ", alpha)
} else {
toptitle <- NULL
warning("The plot title is not defined for this time horizon. ",
"The plots will not have a title.")
}
PlotRobinson(map, lon = lons, lat = lats, target_proj = projection_code,
lat_dim = 'latitude', lon_dim = 'longitude',
legend = 's2dv', bar_extra_margin = c(4,0,4,0),
toptitle = toptitle, style = 'polygon',
caption = caption, mask = sig, crop_coastline = nao_region,
fileout = plotfile, width = 8, height = 6,
brks = seq(-1, 1, 0.2), cols = brewer.pal(10, 'PuOr'))
} # end tstep loop
}
return(nao)
}