Spatial data coverage

workflowr

• Summary
• Checks
• Past versions

Last updated: 2024-04-19

Checks: 7 0

Knit directory: bgc_argo_r_argodata/analysis/

This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

---

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

Seed: set.seed(20211008)

The command set.seed(20211008) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Cache: none

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

File paths: relative

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Repository version: c4eb5b4

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version c4eb5b4. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:

Ignored files:
    Ignored:    .Rproj.user/

Untracked files:
    Untracked:  analysis/anomay_SST_2023.Rmd
    Untracked:  analysis/draft.Rmd

Unstaged changes:
    Modified:   analysis/MHWs_categorisation.Rmd
    Modified:   analysis/_site.yml
    Modified:   analysis/coverage_maps_North_Atlantic.Rmd
    Modified:   analysis/load_broullon_DIC_TA_clim.Rmd
    Modified:   analysis/temp_core_SO_cluster_analysis.Rmd
    Modified:   code/Workflowr_project_managment.R
    Modified:   code/start_background_job.R
    Modified:   code/start_background_job_load.R
    Modified:   code/start_background_job_partial.R

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

---

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/coverage_maps.Rmd) and HTML (docs/coverage_maps.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
html	c7ce3b9	mlarriere	2024-04-12	Build site.
html	c076fba	mlarriere	2024-04-12	Build site.
html	91f08a6	mlarriere	2024-04-07	Build site.
html	db21f55	mlarriere	2024-04-06	Build site.
html	324e64f	mlarriere	2024-04-01	Build site.
Rmd	bad6cd3	mlarriere	2024-04-01	coverage_maps building test
html	713ff67	mlarriere	2024-04-01	Build site.
html	f9de50e	ds2n19	2024-01-01	Build site.
html	07d4eb8	ds2n19	2023-12-20	Build site.
html	fa6cf38	ds2n19	2023-12-14	Build site.
Rmd	64fd104	ds2n19	2023-12-14	revised coverage analysis and SO focused cluster analysis.
html	f110b74	ds2n19	2023-12-13	Build site.
Rmd	acb6523	ds2n19	2023-12-12	Added documentation added to tasks section at start of each script.
html	e62fb2c	ds2n19	2023-12-11	Build site.
html	2d8fb44	ds2n19	2023-12-07	Build site.
Rmd	89075e8	ds2n19	2023-12-07	Changes to coverage maps
html	9d9224a	ds2n19	2023-12-07	Build site.
Rmd	6ec79f9	ds2n19	2023-12-07	Revised coverage analysis.
html	e60ebd2	ds2n19	2023-12-07	Build site.
html	80c16c2	ds2n19	2023-11-15	Build site.
html	93b4545	ds2n19	2023-10-18	Build site.
html	c16000b	ds2n19	2023-10-12	Build site.
html	770b125	ds2n19	2023-10-11	Build site.
html	13ae27f	ds2n19	2023-10-09	Build site.
Rmd	fc05391	ds2n19	2023-10-09	Changed core Argo location folders and run for 2013, 2014 and 2022
html	1e972c5	ds2n19	2023-10-02	Build site.
html	6377b31	ds2n19	2023-10-02	Build site.
html	7b3d8c5	pasqualina-vonlanthendinenna	2022-08-29	Build site.
Rmd	8e81570	pasqualina-vonlanthendinenna	2022-08-29	load and add in core-argo data (1 month)
html	bdd516d	pasqualina-vonlanthendinenna	2022-05-23	Build site.
html	4173c20	jens-daniel-mueller	2022-05-12	Build site.
html	dfe89d7	jens-daniel-mueller	2022-05-12	Build site.
html	710edd4	jens-daniel-mueller	2022-05-11	Build site.
html	68eff8b	jens-daniel-mueller	2022-05-11	Build site.
html	6a6e874	pasqualina-vonlanthendinenna	2022-04-29	Build site.
html	2d44f8a	pasqualina-vonlanthendinenna	2022-04-29	Build site.
html	e61c08e	pasqualina-vonlanthendinenna	2022-04-27	Build site.
html	10036ed	pasqualina-vonlanthendinenna	2022-04-26	Build site.
html	c03dd24	pasqualina-vonlanthendinenna	2022-04-20	Build site.
html	8805f99	pasqualina-vonlanthendinenna	2022-04-11	Build site.
html	905d82f	pasqualina-vonlanthendinenna	2022-02-15	Build site.
html	b8a6482	pasqualina-vonlanthendinenna	2022-01-03	Build site.
html	7f3cfe7	pasqualina-vonlanthendinenna	2021-12-17	Build site.
Rmd	c4cce1a	pasqualina-vonlanthendinenna	2021-12-17	updated cache data
html	123e5db	pasqualina-vonlanthendinenna	2021-12-07	Build site.
Rmd	f8abe59	pasqualina-vonlanthendinenna	2021-12-07	suppressed output messages and updated plots
html	930ea26	pasqualina-vonlanthendinenna	2021-11-26	Build site.
html	e09c60b	pasqualina-vonlanthendinenna	2021-11-26	Build site.
html	1305d6b	pasqualina-vonlanthendinenna	2021-11-26	Build site.
html	5e2b8a5	pasqualina-vonlanthendinenna	2021-11-26	Build site.
html	3df4daf	pasqualina-vonlanthendinenna	2021-11-26	Build site.
html	7a01367	pasqualina-vonlanthendinenna	2021-11-12	Build site.
html	284003d	pasqualina-vonlanthendinenna	2021-11-11	Build site.
html	6276d6c	pasqualina-vonlanthendinenna	2021-11-11	Build site.
html	a103f60	pasqualina-vonlanthendinenna	2021-11-05	Build site.
Rmd	31576f9	pasqualina-vonlanthendinenna	2021-11-05	changed QC flag maps
html	fbd5bac	pasqualina-vonlanthendinenna	2021-11-04	Build site.
html	68977a1	pasqualina-vonlanthendinenna	2021-10-26	Build site.
Rmd	062b272	pasqualina-vonlanthendinenna	2021-10-26	added ggsave
html	b57291a	pasqualina-vonlanthendinenna	2021-10-26	Build site.
html	bba33bf	pasqualina-vonlanthendinenna	2021-10-26	Build site.
Rmd	4bc1859	pasqualina-vonlanthendinenna	2021-10-26	run with full data
html	f7ef44f	jens-daniel-mueller	2021-10-22	Build site.
Rmd	ee2b3f3	jens-daniel-mueller	2021-10-22	code revision
html	aa7280d	jens-daniel-mueller	2021-10-22	Build site.
Rmd	ca7ba6b	jens-daniel-mueller	2021-10-22	adding revised code
html	d84c904	pasqualina-vonlanthendinenna	2021-10-22	Build site.
html	8ecdb43	pasqualina-vonlanthendinenna	2021-10-22	Build site.
html	c81f21c	pasqualina-vonlanthendinenna	2021-10-21	Build site.
html	62d8519	pasqualina-vonlanthendinenna	2021-10-20	Build site.
html	b8feac2	pasqualina-vonlanthendinenna	2021-10-20	Build site.
html	701fffa	pasqualina-vonlanthendinenna	2021-10-20	Build site.
Rmd	b88a839	pasqualina-vonlanthendinenna	2021-10-20	adding revised code

---

Task

Map the location of temperature, oxygen, pH, and nitrate observations recorded by core and BGC-Argo floats Categories include core temperature, BGC temperature, ph, disolved oxyge, nitrate, chlorophyll a.

Counts are profiles by profile_range. The profiles have already been check to ensure they only contain good measurements and that the profiles do not contain significant gaps.

Dependencies

temp_core_va.rds - core preprocessed folder created by temp_core_align_climatology.Rmd

temp_bgc_va.rds - bgc preprocessed folder created by temp_align_climatology.Rmd

pH_bgc_va.rds - bgc preprocessed folder created by pH_align_climatology.Rmd

doxy_bgc_va.rds - bgc preprocessed folder created by doxy_vertical_align.Rmd

nitrate_bgc_va.rds - bgc preprocessed folder created by nitrate_vertical_align.Rmd

chla_bgc_va.rds - bgc preprocessed folder created by chla_vertical_align.Rmd

Load data

BGC-Argo data

Read the files created in loading_data.html:

bgc_temp <- read_rds(file = paste0(path_argo_preprocessed, "/temp_bgc_va.rds")) %>%
  filter(!is.na(year))

bgc_ph <- read_rds(file = paste0(path_argo_preprocessed, "/pH_bgc_va.rds")) %>%
  filter(!is.na(year))

bgc_doxy <- read_rds(file = paste0(path_argo_preprocessed, "/doxy_bgc_va.rds")) %>%
  filter(!is.na(year))

bgc_nitrate <- read_rds(file = paste0(path_argo_preprocessed, "/nitrate_bgc_va.rds")) %>%
  filter(!is.na(year))

bgc_chla <- read_rds(file = paste0(path_argo_preprocessed, "/chla_bgc_va.rds")) %>%
  filter(!is.na(year))

Core-Argo data

core_temp <- read_rds(file = paste0(path_argo_core_preprocessed, "/temp_core_va.rds")) %>%
  filter(!is.na(year))

map data

basinmask <-
  read_csv(paste(path_emlr_utilities,
                 "basin_mask_WOA18.csv",
                 sep = ""),
           col_types = cols("MLR_basins" = col_character()))

basinmask <- basinmask %>% 
  filter(MLR_basins == unique(basinmask$MLR_basins)[1]) %>% 
  select(lon, lat, basin_AIP)

map <-
  read_rds(paste(path_emlr_utilities,
                 "map_landmask_WOA18.rds",
                 sep = ""))

Core - temperature

# Number of measurements
core_count <- core_temp %>%
  group_by(year, file_id, lat, lon, profile_range) %>%
  summarise(count_measures = n()) %>%
  ungroup()

# Number of profiles
core_count <- core_count %>%
  group_by(year, lat, lon, profile_range) %>%
  summarise(count_profiles = n()) %>%
  ungroup()

# core_count %>%
#   group_by (year, lat, lon) %>%
#   summarise(n = n()) %>%
#   filter (n == 1)
# 
# core_count <- rbind(
#   core_count %>%
#   filter (year == 2013, lat == -59.5, lon == 141.5),
#   core_count %>%
#   filter (year == 2013, lat == -63.5, lon == 149.5),
#   core_count %>%
#   filter (year == 2013, lat == -68.5, lon == 233.5))

# Aggregate profile range
core_count_agg <- core_count %>%
  group_by(year, lat, lon) %>%
  summarise(count_profiles = sum(count_profiles)) %>%
  mutate(profile_range = 1) %>%
  ungroup()

core_count_agg <- rbind(
  core_count_agg,
  core_count %>%
    filter (profile_range %in% c(2, 3)) %>%
    group_by(year, lat, lon) %>%
    summarise(count_profiles = sum(count_profiles)) %>%
    mutate(profile_range = 2) %>%
    ungroup()
)

core_count_agg <- rbind(
  core_count_agg,
  core_count %>%
    filter (profile_range == 3)
)

# measurement type
core_count_agg <- core_count_agg %>%
  mutate (prof_type = 'temperature')

spatial by year

# map the location of profiles for each profile in each year 
core_count_agg %>%
  group_split(profile_range) %>%
  map(
    ~ map +
    geom_tile(data = .x, aes(
      x = lon, y = lat, fill = count_profiles
    )) +
    scale_fill_gradient(low = "blue", high = "red",
                        trans = "log10") +
    labs(
      x = 'lon',
      y = 'lat',
      fill = 'number of\nprofiles',
      title = paste0('Core temperature by year and location ',
                     ifelse(unique(.x$profile_range) == 1, '600m', ifelse(unique(.x$profile_range) == 2, '1200m', '1500m')),
                     ' profiles')
    ) +
    theme(
      legend.position = "bottom",
      axis.text = element_blank(),
      axis.ticks = element_blank()
    ) +
    facet_wrap(~year, ncol = 3)
  )

[[1]]

Past versions of core_profile_maps_year-1.png

Version	Author	Date
324e64f	mlarriere	2024-04-01
713ff67	mlarriere	2024-04-01
f9de50e	ds2n19	2024-01-01
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07
770b125	ds2n19	2023-10-11
13ae27f	ds2n19	2023-10-09
6377b31	ds2n19	2023-10-02
7b3d8c5	pasqualina-vonlanthendinenna	2022-08-29

[[2]]

Past versions of core_profile_maps_year-2.png

Version	Author	Date
324e64f	mlarriere	2024-04-01
713ff67	mlarriere	2024-04-01
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07
770b125	ds2n19	2023-10-11
13ae27f	ds2n19	2023-10-09
6377b31	ds2n19	2023-10-02
7b3d8c5	pasqualina-vonlanthendinenna	2022-08-29

[[3]]

Past versions of core_profile_maps_year-3.png

Version	Author	Date
324e64f	mlarriere	2024-04-01
713ff67	mlarriere	2024-04-01
f9de50e	ds2n19	2024-01-01
2d8fb44	ds2n19	2023-12-07

spatial all years

# sum across years
core_count_agg <- core_count_agg %>%
  group_by(profile_range, lat, lon) %>%
  summarise(count_profiles = sum(count_profiles)) %>%
  ungroup()

# map the location of profiles for each profile in each year 
core_count_agg %>%
  group_split(profile_range) %>%
  map(
    ~ map +
    geom_tile(data = .x, aes(
      x = lon, y = lat, fill = count_profiles
    )) +
    scale_fill_gradient(low = "blue", high = "red",
                        trans = "log10") +
    labs(
      x = 'lon',
      y = 'lat',
      fill = 'number of\nprofiles',
      title = paste0('Core temperature by location ',
                     ifelse(unique(.x$profile_range) == 1, '600m', ifelse(unique(.x$profile_range) == 2, '1200m', '1500m')),
                     ' profiles')
    ) +
    theme(
      legend.position = "bottom",
      axis.text = element_blank(),
      axis.ticks = element_blank()
    )
  )

[[1]]

Past versions of core_profile_maps-1.png

Version	Author	Date
324e64f	mlarriere	2024-04-01
713ff67	mlarriere	2024-04-01
f9de50e	ds2n19	2024-01-01
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[2]]

Past versions of core_profile_maps-2.png

Version	Author	Date
324e64f	mlarriere	2024-04-01
713ff67	mlarriere	2024-04-01
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[3]]

Past versions of core_profile_maps-3.png

Version	Author	Date
324e64f	mlarriere	2024-04-01
713ff67	mlarriere	2024-04-01
f9de50e	ds2n19	2024-01-01
2d8fb44	ds2n19	2023-12-07

BGC

# ----------------------------------------------------------------------------------------------
# temperature 
# ----------------------------------------------------------------------------------------------

# Number of measurements
bgc_temp_count <- bgc_temp %>%
  group_by(year, file_id, lat, lon, profile_range) %>%
  summarise(count_measures = n()) %>%
  ungroup()

# Number of profiles
bgc_temp_count <- bgc_temp_count %>%
  group_by(year, lat, lon, profile_range) %>%
  summarise(count_profiles = n()) %>%
  ungroup()

# measurement type
bgc_temp_count <- bgc_temp_count %>%
  mutate (prof_order = 1,
          prof_type = 'temperature')

# ----------------------------------------------------------------------------------------------
# ph 
# ----------------------------------------------------------------------------------------------

# Number of measurements
bgc_ph_count <- bgc_ph %>%
  group_by(year, file_id, lat, lon, profile_range) %>%
  summarise(count_measures = n()) %>%
  ungroup()

# Number of profiles
bgc_ph_count <- bgc_ph_count %>%
  group_by(year, lat, lon, profile_range) %>%
  summarise(count_profiles = n()) %>%
  ungroup()

# measurement type
bgc_ph_count <- bgc_ph_count %>%
  mutate (prof_order = 2,
          prof_type = 'pH')

# ----------------------------------------------------------------------------------------------
# doxy
# ----------------------------------------------------------------------------------------------

# Number of measurements
bgc_doxy_count <- bgc_doxy %>%
  group_by(year, file_id, lat, lon, profile_range) %>%
  summarise(count_measures = n()) %>%
  ungroup()

# Number of profiles
bgc_doxy_count <- bgc_doxy_count %>%
  group_by(year, lat, lon, profile_range) %>%
  summarise(count_profiles = n()) %>%
  ungroup()

# measurement type
bgc_doxy_count <- bgc_doxy_count %>%
  mutate (prof_order = 3,
          prof_type = 'dissolved oxygen')

# ----------------------------------------------------------------------------------------------
# nitrate
# ----------------------------------------------------------------------------------------------

# Number of measurements
bgc_nitrate_count <- bgc_nitrate %>%
  group_by(year, file_id, lat, lon, profile_range) %>%
  summarise(count_measures = n()) %>%
  ungroup()

# Number of profiles
bgc_nitrate_count <- bgc_nitrate_count %>%
  group_by(year, lat, lon, profile_range) %>%
  summarise(count_profiles = n()) %>%
  ungroup()

# measurement type
bgc_nitrate_count <- bgc_nitrate_count %>%
  mutate (prof_order = 4,
          prof_type = 'nitrate')

# ----------------------------------------------------------------------------------------------
# chla
# ----------------------------------------------------------------------------------------------

# Number of measurements
bgc_chla_count <- bgc_chla %>%
  group_by(year, file_id, lat, lon, profile_range) %>%
  summarise(count_measures = n()) %>%
  ungroup()

# Number of profiles
bgc_chla_count <- bgc_chla_count %>%
  group_by(year, lat, lon, profile_range) %>%
  summarise(count_profiles = n()) %>%
  ungroup()

# measurement type
bgc_chla_count <- bgc_chla_count %>%
  mutate (prof_order = 5,
          prof_type = 'chlorophyll a')

# combine
bgc_count <- rbind(bgc_temp_count, bgc_ph_count, bgc_doxy_count, bgc_nitrate_count, bgc_chla_count)

# Aggregate profile range
bgc_count_agg <- bgc_count %>%
  group_by(prof_order, prof_type, year, lat, lon) %>%
  summarise(count_profiles = sum(count_profiles)) %>%
  mutate(profile_range = 1) %>%
  ungroup()

bgc_count_agg <- rbind(
  bgc_count_agg,
  bgc_count %>%
    filter (profile_range %in% c(2, 3)) %>%
    group_by(prof_order, prof_type, year, lat, lon) %>%
    summarise(count_profiles = sum(count_profiles)) %>%
    mutate(profile_range = 2) %>%
    ungroup()
)

bgc_count_agg <- rbind(
  bgc_count_agg,
  bgc_count %>%
    filter (profile_range == 3)
)

spatial by year

# map the location of profiles for each profile in each year 
bgc_count_agg %>%
  group_split(prof_order, profile_range) %>%
  map(
    ~ map +
    geom_tile(data = .x, aes(
      x = lon, y = lat, fill = count_profiles
    )) +
    scale_fill_gradient(low = "blue", high = "red",
                        trans = "log10") +
    labs(
      x = 'lon',
      y = 'lat',
      fill = 'number of\nprofiles',
      title = paste0('BGC ',
                     unique(.x$prof_type),
                     ' by year and location ',
                     ifelse(unique(.x$profile_range) == 1, '600/614m', ifelse(unique(.x$profile_range) == 2, '1200/1225m', '1500/1600m')),
                     ' profiles')
    ) +
    theme(
      legend.position = "bottom",
      axis.text = element_blank(),
      axis.ticks = element_blank()
    ) +
    facet_wrap(~year, ncol = 3)
  )

[[1]]

Past versions of bgc_profile_maps_year-1.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[2]]

Past versions of bgc_profile_maps_year-2.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[3]]

Past versions of bgc_profile_maps_year-3.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[4]]

Past versions of bgc_profile_maps_year-4.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[5]]

Past versions of bgc_profile_maps_year-5.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[6]]

Past versions of bgc_profile_maps_year-6.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[7]]

Past versions of bgc_profile_maps_year-7.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
fa6cf38	ds2n19	2023-12-14
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[8]]

Past versions of bgc_profile_maps_year-8.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
fa6cf38	ds2n19	2023-12-14
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[9]]

Past versions of bgc_profile_maps_year-9.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
fa6cf38	ds2n19	2023-12-14
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[10]]

Past versions of bgc_profile_maps_year-10.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[11]]

Past versions of bgc_profile_maps_year-11.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[12]]

Past versions of bgc_profile_maps_year-12.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[13]]

Past versions of bgc_profile_maps_year-13.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[14]]

Past versions of bgc_profile_maps_year-14.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

spatial all years

# sum across years
bgc_count_agg <- bgc_count_agg %>%
  group_by(prof_order, prof_type, profile_range, lat, lon) %>%
  summarise(count_profiles = sum(count_profiles)) %>%
  ungroup()

# map the location of profiles for each profile in each year 
bgc_count_agg %>%
  group_split(prof_order, profile_range) %>%
  map(
    ~ map +
    geom_tile(data = .x, aes(
      x = lon, y = lat, fill = count_profiles
    )) +
    scale_fill_gradient(low = "blue", high = "red",
                        trans = "log10") +
    labs(
      x = 'lon',
      y = 'lat',
      fill = 'number of\nprofiles',
      title = paste0('BGC ',
                     unique(.x$prof_type),
                     ' by location ',
                     ifelse(unique(.x$profile_range) == 1, '600/614m', ifelse(unique(.x$profile_range) == 2, '1200/1225m', '1500/1600m')),
                     ' profiles')
    ) +
    theme(
      legend.position = "bottom",
      axis.text = element_blank(),
      axis.ticks = element_blank()
    )
  )

[[1]]

Past versions of bgc_profile_maps-1.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[2]]

Past versions of bgc_profile_maps-2.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[3]]

Past versions of bgc_profile_maps-3.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[4]]

Past versions of bgc_profile_maps-4.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[5]]

Past versions of bgc_profile_maps-5.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07
9d9224a	ds2n19	2023-12-07

[[6]]

Past versions of bgc_profile_maps-6.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[7]]

Past versions of bgc_profile_maps-7.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
fa6cf38	ds2n19	2023-12-14
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[8]]

Past versions of bgc_profile_maps-8.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
fa6cf38	ds2n19	2023-12-14
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[9]]

Past versions of bgc_profile_maps-9.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
fa6cf38	ds2n19	2023-12-14
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[10]]

Past versions of bgc_profile_maps-10.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[11]]

Past versions of bgc_profile_maps-11.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[12]]

Past versions of bgc_profile_maps-12.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[13]]

Past versions of bgc_profile_maps-13.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

[[14]]

Past versions of bgc_profile_maps-14.png

Version	Author	Date
f9de50e	ds2n19	2024-01-01
f110b74	ds2n19	2023-12-13
2d8fb44	ds2n19	2023-12-07

Session information

sessionInfo()

R version 4.2.2 (2022-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.5

Matrix products: default
BLAS:   /usr/local/R-4.2.2/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.2.2/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] lubridate_1.9.0  timechange_0.1.1 argodata_0.1.0   forcats_0.5.2   
 [5] stringr_1.5.0    dplyr_1.1.3      purrr_1.0.2      readr_2.1.3     
 [9] tidyr_1.3.0      tibble_3.2.1     ggplot2_3.4.4    tidyverse_1.3.2 

loaded via a namespace (and not attached):
 [1] httr_1.4.4          sass_0.4.4          bit64_4.0.5        
 [4] vroom_1.6.0         jsonlite_1.8.3      modelr_0.1.10      
 [7] bslib_0.4.1         assertthat_0.2.1    highr_0.9          
[10] googlesheets4_1.0.1 cellranger_1.1.0    yaml_2.3.6         
[13] pillar_1.9.0        backports_1.4.1     glue_1.6.2         
[16] digest_0.6.30       promises_1.2.0.1    rvest_1.0.3        
[19] colorspace_2.0-3    htmltools_0.5.8.1   httpuv_1.6.6       
[22] pkgconfig_2.0.3     broom_1.0.5         haven_2.5.1        
[25] scales_1.2.1        whisker_0.4         later_1.3.0        
[28] tzdb_0.3.0          git2r_0.30.1        googledrive_2.0.0  
[31] generics_0.1.3      farver_2.1.1        ellipsis_0.3.2     
[34] cachem_1.0.6        withr_2.5.0         cli_3.6.1          
[37] magrittr_2.0.3      crayon_1.5.2        readxl_1.4.1       
[40] evaluate_0.18       fs_1.5.2            fansi_1.0.3        
[43] xml2_1.3.3          tools_4.2.2         hms_1.1.2          
[46] gargle_1.2.1        lifecycle_1.0.3     munsell_0.5.0      
[49] reprex_2.0.2        compiler_4.2.2      jquerylib_0.1.4    
[52] RNetCDF_2.6-1       rlang_1.1.1         grid_4.2.2         
[55] rstudioapi_0.15.0   labeling_0.4.2      rmarkdown_2.18     
[58] gtable_0.3.1        DBI_1.2.2           R6_2.5.1           
[61] knitr_1.41          fastmap_1.1.0       bit_4.0.5          
[64] utf8_1.2.2          workflowr_1.7.0     rprojroot_2.0.3    
[67] stringi_1.7.8       parallel_4.2.2      Rcpp_1.0.10        
[70] vctrs_0.6.4         dbplyr_2.2.1        tidyselect_1.2.0   
[73] xfun_0.35