Using this script to create a summer Southern Ocean climatology for MODISA using Johnson 2013:
https://github.com/mdsumner/roc/blob/master/inst/examples/calc_L3_SO.R
That script results in a large data frame of bin-values, the aggregated mean of ~1300 days of MODISA between 21 December and day 080.
The plot below was created with this code. Here the bins are all aggregated up into a 15km polar map, but we can easily bin it into a different grid.
## now the map
library(raster)
library(feather)
library(dplyr)
x <- read_feather("inst/examples/MODISA_SO_summer_355_080.feather")
map <- raster(extent(-9e6, 9e6, -9e6, 9e6), crs = "+proj=laea +ellps=WGS84 +lat_0=-90 +no_defs", res = 15e3)
bin_to_gridcell <- function(bins, gridmap, nrow = 4320) {
xy <- do.call(cbind, roc::bin2lonlat(bins, nrows = nrow))
cellFromXY(gridmap, rgdal::project(xy, projection(gridmap)))
}
#
summ <- x %>% mutate(grid_cell = bin_to_gridcell(bin_num, map)) %>% group_by(grid_cell) %>%
summarize(count = sum(count), chl_sum = sum(sum)) %>% mutate(mean_chl = chl_sum/count)
summ <- summ %>% filter(!is.na(grid_cell))
map <- setValues(map, NA_real_)
map[summ$grid_cell] <- summ$mean_chl
library(palr)
pal <- chlPal(palette = TRUE)
plot(map, col =pal$cols, breaks = pal$breaks, legend = FALSE)
writeRaster(map, "L3_SO_summer.nc")
Using this script to create a summer Southern Ocean climatology for MODISA using Johnson 2013:
https://github.com/mdsumner/roc/blob/master/inst/examples/calc_L3_SO.R
That script results in a large data frame of bin-values, the aggregated mean of ~1300 days of MODISA between 21 December and day 080.
The plot below was created with this code. Here the bins are all aggregated up into a 15km polar map, but we can easily bin it into a different grid.