World Ocean Atlas 2018
Jens Daniel Müller
20 July, 2020
Last updated: 2020-07-20
Checks: 7 0
Knit directory: Cant_eMLR/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 23220a8 | jens-daniel-mueller | 2020-07-20 | assigned ocean basins and plotted world map |
| html | 27d380d | jens-daniel-mueller | 2020-07-20 | Build site. |
| Rmd | 09f3f73 | jens-daniel-mueller | 2020-07-20 | basin masks read in |
| html | 22b588c | jens-daniel-mueller | 2020-07-18 | Build site. |
| Rmd | 87a4680 | jens-daniel-mueller | 2020-07-18 | added WOA blank script |
library(tidyverse)
library(lubridate)
library(tidync)
library(stars)1 Data source
- Data source: World Ocean Atlas 2018
2 Basin mask
2.1 Read data
basinmask_01 <- read_csv(here::here("data/World_Ocean_Atlas_2018",
"basinmask_01.msk"),
skip = 1)
basinmask_01 <- basinmask_01 %>%
select(Latitude:Basin_0m) %>%
mutate(Basin_0m = as.factor(Basin_0m))2.2 Basin labels
According to WOA FAQ website, number codes in the mask file refer to Ocean basins as follows:
1 - Atlantic Ocean 10 - Southern Ocean, between 63°W and 20°E longitudes
The Pacific: 2 - Pacific Ocean 10 - Southern Ocean, between 147°E and 63°W
The Indian: 3 - Indian Ocean 10 - Southern Ocean, between 20°E and 147°E.
From this, the Atlantik and the Indo-Pcific were labeled.
basinmask_01 <- basinmask_01 %>%
filter(Basin_0m %in% c("1", "2", "3", "10")) %>%
mutate(basin = if_else(Basin_0m == "10" & Longitude >= -63 & Longitude < 20,
"Atlantic", "Indo-Pacific"),
basin = if_else(Basin_0m == "1",
"Atlantic", basin)) %>%
select(-Basin_0m)2.3 Plot world map
mapWorld <- borders("world", colour="gray60", fill="gray60")
basinmask_01 %>%
ggplot(aes(Longitude, Latitude, fill=basin))+
mapWorld+
geom_raster()+
coord_quickmap(expand = 0)
2.4 Write file
basinmask_01 %>%
write_csv(here::here("data/World_Ocean_Atlas_2018/_summarized_files",
"basin_mask_WOA18.csv"))3 Read/plot ncdf files
- read-in not yet started
file_list <- list.files(path= "data/GLODAPv2_2016b_Mappedclimatologies", pattern = "*.nc")
print("files used:")
print(file_list)
#file <- file_list[1]
for (file in file_list) {
clim_stars <- read_stars(here::here("data/GLODAPv2_2016b_Mappedclimatologies",
file))
parameter <- str_split(file, pattern = "6b.", simplify = TRUE)[2]
parameter <- str_split(parameter, pattern = ".nc", simplify = TRUE)[1]
map_clim_stars <- clim_stars %>% select(all_of(parameter))
map_clim_stars <- map_clim_stars %>%
filter(depth_surface %in% c(0,50,100,200,500,1000,2000,3000,5000))
print(
ggplot()+
geom_stars(data = map_clim_stars)+
geom_vline(xintercept = 335, col="white")+
scale_fill_viridis_b()+
labs(title = file)+
facet_wrap(~depth_surface, ncol = 3)+
theme(axis.text = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank())+
coord_quickmap(expand = 0)
)
# clim_tidync <- tidync(here::here("data/GLODAPv2_2016b_Mappedclimatologies",
# file))
# print(clim_tidync)
#
# Atl_sec_clim <- clim_tidync %>% hyper_filter(lon = lon == 335.5)
# Atl_sec_clim_tibble <- Atl_sec_clim %>% hyper_tibble()
#
# Atl_sec_clim_tibble %>%
# ggplot(aes(lat, depth_surface, fill=Cant))+
# geom_point()+
# scale_y_reverse()+
# scale_fill_viridis_b()
}4 Open tasks
- none
5 Questions
- none
sessionInfo()R version 3.6.3 (2020-02-29)
Platform: i386-w64-mingw32/i386 (32-bit)
Running under: Windows 10 x64 (build 18363)
Matrix products: default
locale:
[1] LC_COLLATE=English_Germany.1252 LC_CTYPE=English_Germany.1252
[3] LC_MONETARY=English_Germany.1252 LC_NUMERIC=C
[5] LC_TIME=English_Germany.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] stars_0.4-3 sf_0.9-4 abind_1.4-5 tidync_0.2.4
[5] lubridate_1.7.9 forcats_0.5.0 stringr_1.4.0 dplyr_1.0.0
[9] purrr_0.3.4 readr_1.3.1 tidyr_1.1.0 tibble_3.0.3
[13] ggplot2_3.3.2 tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.5 whisker_0.4 knitr_1.29 xml2_1.3.2
[5] magrittr_1.5 maps_3.3.0 units_0.6-7 hms_0.5.3
[9] rvest_0.3.5 tidyselect_1.1.0 here_0.1 colorspace_1.4-1
[13] R6_2.4.1 rlang_0.4.7 fansi_0.4.1 parallel_3.6.3
[17] broom_0.7.0 xfun_0.15 e1071_1.7-3 ncmeta_0.2.5
[21] dbplyr_1.4.4 modelr_0.1.8 withr_2.2.0 git2r_0.27.1
[25] ellipsis_0.3.1 htmltools_0.5.0 class_7.3-17 assertthat_0.2.1
[29] rprojroot_1.3-2 digest_0.6.25 lifecycle_0.2.0 RNetCDF_2.3-1
[33] haven_2.3.1 rmarkdown_2.3 compiler_3.6.3 cellranger_1.1.0
[37] pillar_1.4.6 scales_1.1.1 backports_1.1.5 generics_0.0.2
[41] classInt_0.4-3 jsonlite_1.7.0 httpuv_1.5.4 pkgconfig_2.0.3
[45] rstudioapi_0.11 munsell_0.5.0 blob_1.2.1 httr_1.4.1
[49] tools_3.6.3 grid_3.6.3 gtable_0.3.0 KernSmooth_2.23-16
[53] DBI_1.1.0 cli_2.0.2 readxl_1.3.1 yaml_2.2.1
[57] lwgeom_0.2-5 crayon_1.3.4 farver_2.0.3 later_1.1.0.1
[61] promises_1.1.1 fs_1.4.2 vctrs_0.3.1 ncdf4_1.17
[65] glue_1.4.1 evaluate_0.14 labeling_0.3 reprex_0.3.0
[69] stringi_1.4.6