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compute_nino <- function(data, recipe, region, standardised = TRUE,
running_mean = NULL, plot_ts = TRUE, plot_sp = TRUE,
alpha = 0.5, save = 'all', na.rm = TRUE, logo = NULL,
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if (!is.null(data$fcst)) {
warn(recipe$Run$logger, "Nino computed only for hindcast data.")
}
var <- recipe$Analysis$Variables$name
if (!(var %in% c('tos', 'sst'))) {
warn(recipe$Run$logger, "Variable name is not one of the expected sst or tos")
}
var_units <- data$hcst$attrs$Variable$metadata[[var]]$units
nino_hcst <- WeightedMean(data = data$hcst$data,
lon = as.vector(data$hcst$coords$longitude),
lat = as.vector(data$hcst$coords$latitude),
region = region,
londim = 'longitude',
latdim = 'latitude',
na.rm = na.rm,
ncores = ncores)
nino_obs <- WeightedMean(data = data$obs$data,
lon = as.vector(data$hcst$coords$longitude),
lat = as.vector(data$hcst$coords$latitude),
region = region,
londim = 'longitude',
latdim = 'latitude',
na.rm = na.rm,
ncores = ncores)
if (standardised) {
nino_hcst <- Apply(list(nino_hcst), target_dims = c('syear', 'ensemble'),
fun = function(x) {
sd <- sqrt(var(as.vector(x), na.rm = TRUE))
means <- mean(as.vector(x), na.rm = TRUE)
res <- apply(x, c(1,2), function(x) {(x-means)/sd})},
ncores = recipe$Analysis$ncores)$output1
nino_obs <- Apply(list(nino_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)$output1
var_units <- 'adim'
}
if (!is.null(running_mean)) {
nino_hcst <- Smoothing(nino_hcst,
runmeanlen = running_mean,
time_dim = 'time',
ncores = ncores)
nino_obs <- Smoothing(nino_obs,
runmeanlen = running_mean,
time_dim = 'time',
ncores = ncores)
}
if (all(region == c(-90, -80, -10, 0))) {
region_name <- "1+2"
nino_name <- "nino12"
} else if (all(region == c(-150, -90, -5, 5))) {
region_name <- "3"
nino_name <- "nino3"
} else if (all(region == c(-170, -120, -5, 5))) {
region_name <- "3.4"
nino_name <- "nino34"
} else if (all(region == c(160, -150, -5, 5))) {
region_name <- "4"
nino_name <- "nino4"
} else {
stop("Unknown nino region")
}
nino_hcst <- InsertDim(nino_hcst, posdim = 1, lendim = 1, name = 'region')
nino_obs <- InsertDim(nino_obs, posdim = 1, lendim = 1, name = 'region')
dims_dates_not_null <- dim(data$hcst$attrs$Dates)[which(dim(data$hcst$attrs$Dates) > 1)]
hcst_dates <- Subset(data$hcst$attrs$Dates, along = names(dims_dates_not_null),
indices = lapply(dims_dates_not_null, function(x){1:x}),
drop = "non-selected")
if (!("time" %in% names(dim(hcst_dates)))) {
hcst_dates <- InsertDim(hcst_dates, pos = 1, len = 1, name = 'time')
## TODO: recover dates format
hcst_dates <- as.POSIXct(hcst_dates, origin = '1970-01-01', tz = 'UTC')
}
nino <- list(hcst = s2dv_cube(
data = nino_hcst,
varName = nino_name,
metadata = list(
region = list(name = paste("Nino", region_name, "region"),
lats_range = paste(region[3:4]),
lons_range = paste(region[1:2])),
time = data$hcst$attrs$Variable$metadata$time,
nino = list(units = var_units,
longname = paste("El Niño", region_name, "Index"))),
Dates = hcst_dates,
Dataset = recipe$Analysis$Datasets$System$name),
obs = s2dv_cube(
data = nino_obs,
varName = nino_name,
metadata = list(
region = list(name = paste("Nino", region_name, "region"),
lats_range = paste(region[3:4]),
lons_range = paste(region[1:2])),
time = data$obs$attrs$Variable$metadata$time,
nino = list(units = var_units,
longname = paste("El Niño", region_name, "Index"))),
Dates = data$obs$attrs$Dates,
Dataset = recipe$Analysis$Datasets$Reference$name))
file_dest <- paste0(recipe$Run$output_dir, "/outputs/Indices/")
# Use startdates param from SaveExp to correctly name the files:
if (tolower(recipe$Analysis$Horizon) == "seasonal") {
if (length(data$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)
}
nino$hcst$data <- .drop_indices_dims(nino_hcst)
CST_SaveExp(data = nino$hcst,
destination = file_dest,
startdates = as.vector(file_dates),
dat_dim = NULL, sdate_dim = 'syear',
ftime_dim = 'time', var_dim = NULL,
memb_dim = 'ensemble')
res <- .drop_indices_dims(nino_obs)
if (!("time" %in% names(dim(res)))) {
res <- InsertDim(res, pos = 1, len = 1, name = 'time')
}
nino$obs$data <- res
CST_SaveExp(data = nino$obs,
destination = file_dest,
startdates = as.vector(file_dates),
dat_dim = NULL, sdate_dim = 'syear',
ftime_dim = 'time', var_dim = NULL,
memb_dim = NULL)
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nino$hcst$data <- nino_hcst
nino$obs$data <- nino_obs
res <- 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(nino$hcst$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$ftime_min)
obs <- Subset(nino$obs$data, along = 'time', ind = tstep)
exp <- Subset(nino$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$Horizon) == "seasonal") {
toptitle <- paste("Ni\u00F1o", region_name, "SST Index\n",
month.abb[mes],
"/", recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/",
nino_name, "_",
system, "_", recipe$Analysis$Datasets$Reference$name,
"_s", recipe$Analysis$Time$sdate, "_ftime",
sprintf("%02d", tstep - 1 + recipe$Analysis$Time$ftime_min),
".png")
caption <- paste0("Nominal start date: 1st of ",
month.name[as.numeric(substr(recipe$Analysis$Time$sdate, 1,2))],
"\n",
"Forecast month: ", fmonth)
xlabs = as.numeric(substr(file_dates, 1, 4))
} else if (tolower(recipe$Analysis$Horizon) == "decadal") {
toptitle <- paste("Ni\u00F1o", region_name, "SST Index\n",
"Lead time", fmonth,
"/", recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/", nino_name, "_",
system, "_", recipe$Analysis$Datasets$Reference$name,
"_ftime",
sprintf("%02d", tstep - 1 + recipe$Analysis$Time$ftime_min), ".png")
caption <- paste0("Start date month: ",
month.name[get_archive(recipe)$System[[recipe$Analysis$Datasets$System$name]]$initial_month],
"\n",
"Lead time: ", fmonth, "\n")
xlabs <- substr(file_dates, 2,5)
} else {
toptitle <- NULL
warning("The plot title is not defined for this time horizon. ",
"The plots will not have a title.")
}
plot_deterministic_forecast(obs, exp,
time_dim = 'syear',
member_dim = 'ensemble', style = 'boxplot',
xlabs = xlabs,
ylab = var_units,
title = toptitle, fileout = plotfile,
caption = caption,
legend_text = c(
recipe$Analysis$Datasets$Reference$name,
recipe$Analysis$Datasets$System$name))
}
}
if (plot_sp) {
source("modules/Visualization/R/tmp/PlotRobinson.R")
source("modules/Indices/R/correlation_eno.R")
source("modules/Visualization/R/get_proj_code.R")
lons <- data$hcst$coords$longitude
lats <- data$hcst$coords$latitude
# Get code for Robinson projection depending on GEOS/GDAL/PROJ version
projection_code <- get_proj_code("robinson")
# Avoid rewriten longitudes a shift is neeced:
dir.create(paste0(recipe$Run$output_dir, "/plots/Indices/"),
showWarnings = F, recursive = T)
correl_obs <- Apply(list(data$obs$data, nino$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$data, nino$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$data, nino$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$ncores)
for (tstep in 1:dim(nino$obs$data)['time']) {
map <- Subset(correl_obs$r, along = 'time', ind = tstep, drop = T)
sig <- Subset(correl_obs$sig, along = 'time', ind = tstep, drop = T)
if (tolower(recipe$Analysis$Horizon) == "seasonal") {
mes <- as.numeric(substr(recipe$Analysis$Time$sdate, 1,2)) +
(tstep - 1) + (recipe$Analysis$Time$ftime_min - 1)
mes <- ifelse(mes > 12, mes - 12, mes)
fmonth <- sprintf("%02d", tstep - 1 + recipe$Analysis$Time$ftime_min)
toptitle <- paste(recipe$Analysis$Datasets$Reference$name, "\n",
"Ni\u00F1o", region_name, "SST 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/", nino_name,
"_correlation_",
recipe$Analysis$Variable$name, "_",
recipe$Analysis$Datasets$Reference$name,
"_s", recipe$Analysis$Time$sdate,
"_ftime", fmonth, ".png")
caption <- paste0("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$Horizon) == "decadal") {
fmonth <- sprintf("%02d", tstep - 1 + recipe$Analysis$Time$ftime_min)
toptitle <- paste(recipe$Analysis$Datasets$Reference$name, "\n",
"Ni\u00F1o", region_name, "SST 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/",
nino_name, "_correlation_",
recipe$Analysis$Variable$name, "_",
recipe$Analysis$Datasets$Reference$name,
"_ftime", fmonth, ".png")
caption <- paste0("Start date: month ",
month.name[get_archive(recipe)$System[[recipe$Analysis$Datasets$System$name]]$initial_month],
"\n",
"Forecast month: ", fmonth, "\n",
"Pearson correlation; alpha = ", alpha)
} else {
toptitle <- NULL
warning("The plot title is not defined for this time horizon. ",
"The plots will not have a title.")
}
PlotRobinson(map, lon = lons, lat = lats,
target_proj = projection_code, #"ESRI:54030",
lat_dim = 'latitude', lon_dim = 'longitude',
legend = 's2dv', style = 'point',
toptitle = toptitle, bar_extra_margin = c(4,0,4,0),
caption = caption, mask = sig,
fileout = plotfile, width = 8, height = 6,
brks = seq(-1, 1, 0.2), cols = brewer.pal(10, 'PuOr'))
## Ensemble-mean
map <- Subset(correl_hcst$r, along = 'time', ind = tstep)
sig <- Subset(correl_hcst$sig, along = 'time', ind = tstep)
if (gsub(".", "", recipe$Analysis$Datasets$System$name) == "") {
system <- recipe$Analysis$Datasets$System$name
} else {
system <-gsub(".", "", recipe$Analysis$Datasets$System$name)
}
if (tolower(recipe$Analysis$Horizon) == "seasonal") {
toptitle <- paste(recipe$Analysis$Datasets$System$name, "\n",
"Ni\u00F1o", region_name, "SST Index -",var_name, "\n",
"Correlation /",
month.abb[as.numeric(fmonth)],
"/", recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/",
nino_name, "_correlation_",
recipe$Analysis$Variable$name, "_ensmean_",
system,
"_s", recipe$Analysis$Time$sdate,
"_ftime", fmonth, ".png")
caption <- paste0("Ensemble mean\n",
"Nominal start date: 1st of ",
month.name[as.numeric(substr(recipe$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",
"Ni\u00F1o", region_name, "SST 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/",
nino_name, "_correlation_",
recipe$Analysis$Variable$name, "_ensmean_",
system,
recipe$Analysis$Datasets$Reference$name,
"_ftime", fmonth, ".png")
caption <- paste0("Correlation ensemble mean\n",
"Start date month: ",
month.name[get_archive(recipe)$System[[recipe$Analysis$Datasets$System$name]]$initial_month],
"\n",
"Forecast month: ", fmonth, "\n",
"Pearson correlation; alpha = ", alpha)
} else {
toptitle <- NULL
warning("The plot title is not defined for this time horizon. ",
"The plots will not have a title.")
}
PlotRobinson(map, lon = lons, lat = lats,
target_proj = projection_code, #"ESRI:54030",
lat_dim = 'latitude', lon_dim = 'longitude',
legend = 's2dv', style = 'point',
toptitle = toptitle, bar_extra_margin = c(4,0,4,0),
caption = caption, mask = sig,
fileout = plotfile, width = 8, height = 6,
brks = seq(-1, 1, 0.2), cols = brewer.pal(10, 'PuOr'))
# Full hcst corr
map <- Subset(correl_hcst_full$r, along = 'time', ind = tstep)
sig <- Subset(correl_hcst_full$sig, along = 'time', ind = tstep)
if (tolower(recipe$Analysis$Horizon) == "seasonal") {
toptitle <- paste(recipe$Analysis$Datasets$System$name, "\n",
"Ni\u00F1o", region_name, "SST Index -",var_name, "\n",
" Correlation /",
month.abb[as.numeric(fmonth)],
"/", recipe$Analysis$Time$hcst_start, "-",
recipe$Analysis$Time$hcst_end)
plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/",
nino_name, "_correlation_",
recipe$Analysis$Variable$name, "_member_",
system,
"_s", recipe$Analysis$Time$sdate,
"_ftime", fmonth, ".png")
caption <- paste0("Individual members\n",
"Nominal start date: 1st of ",
month.name[as.numeric(substr(recipe$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",
"Ni\u00F1o", region_name, "SST 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/",
nino_name, "_correlation_",
recipe$Analysis$Variable$name, "_ensmean_",
system,
recipe$Analysis$Datasets$Reference$name,
"_ftime", fmonth, ".png")
caption <- paste0("Correlation ensemble mean\n",
"Start date month: ",
month.name[get_archive(recipe)$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, #"ESRI:54030",
lat_dim = 'latitude', lon_dim = 'longitude',
legend = 's2dv', style = 'point',
toptitle = toptitle, bar_extra_margin = c(4,0,4,0),
caption = caption, mask = sig,
fileout = plotfile, width = 8, height = 6,
brks = seq(-1, 1, 0.2), cols = brewer.pal(10, 'PuOr'))
}
}
return(nino)
}