library(raadtools) library(tabularaster) library(dplyr) ice <- readice(seq(as.Date("1979-02-15"), as.Date("2017-01-15"), by = "1 month"), time.resolution = "monthly") muice <- calc(ice, mean, na.rm = TRUE) #anom <- stackApply(ice - muice, as.integer(format(getZ(ice), "%m")), fun = mean, na.rm = TRUE) anom <- stackApply(ice - muice, as.integer(factor(aes_season(getZ(ice)))), fun = mean, na.rm = TRUE) icetab <- as_tibble(ice, cell = FALSE, dim = TRUE) %>% mutate(year = as.integer(format(dimindex, "%Y"))) %>% ## 25km pixels for NSIDC, 12 months in a year group_by(year) %>% summarize(ice_prop_area = sum((cellvalue/100) * 25000 * 25000, na.rm = TRUE)/12, ncell = sum(cellvalue > 0 & !is.na(cellvalue))) plot(icetab$year, icetab$ice_prop_area, ylim = c(0, max(icetab$ice_prop_area)), type = "l" ) par(new = TRUE) plot(icetab$year, icetab$ncell, axes = FALSE, ylab = "") axis(4) write.csv(icetab, file = "icetab_1979_2016.csv", row.names = FALSE) #Column +1: average area of total extent of sea ice over July-August each year. # This would require on each meridian, taking the northern most pixel which has greater # than or equal to 15% concentration and then including all area to the coastline. This # will mean all polynyas will be included in the calculation. ##Column +2: average area of sea ice in the July-August period each year as per calculation on ## Tuesday but excluding cells with less than 15% concentration. # # # plot(anom, # col = colorRampPalette(c("firebrick", "white", "dodgerblue"))(11), # breaks = seq(-80, 80, length = 12)) # # # # ice <- readice(seq(as.Date("1979-01-15"), as.Date("2016-12-15"), by = "1 month"), time.resolution = "monthly") # icetab <- as_tibble(ice, cell = FALSE, dim = TRUE) %>% # mutate(year = as.integer(format(dimindex, "%Y")))
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