Argo pH Variability

workflowr

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• Checks
• Past versions

Last updated: 2022-05-11

Checks: 7 0

Knit directory: bgc_argo_r_argodata/

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---

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File	Version	Author	Date	Message
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	6dd0945	pasqualina-vonlanthendinenna	2022-03-25	Build site.
html	e12a216	pasqualina-vonlanthendinenna	2022-03-15	Build site.
Rmd	e4d1d1e	pasqualina-vonlanthendinenna	2022-03-15	updated to new only flag A data
html	c8451b9	pasqualina-vonlanthendinenna	2022-03-14	Build site.
Rmd	0da56b4	pasqualina-vonlanthendinenna	2022-03-14	added variability pages

---

Task

Explore the spatial variability of Argo pH profiles

theme_set(theme_bw())

Load data

path_argo <- '/nfs/kryo/work/updata/bgc_argo_r_argodata'
path_argo_preprocessed <- paste0(path_argo, "/preprocessed_bgc_data")
path_emlr_utilities <- "/nfs/kryo/work/jenmueller/emlr_cant/utilities/files/"
path_updata <- '/nfs/kryo/work/updata'

region_masks_all_1x1 <- read_rds(file = paste0(path_argo_preprocessed,
                                               "/region_masks_all_1x1.rds"))

region_masks_all_1x1 <- region_masks_all_1x1 %>%
  rename(biome = value) %>% 
  mutate(coast = as.character(coast))

# WOA 18 basin mask

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(-c(MLR_basins, basin))

# full argo data
# original_argo <- read_rds(file = paste0(path_argo_preprocessed, "/bgc_merge_pH_qc_1.rds"))

# change the date format for compatibility with OceanSODA data
# original_argo <- full_argo %>%
#   mutate(year = year(date),
#          month = month(date)) %>%
#   mutate(date = ymd(format(date, "%Y-%m-15")))

full_argo <- read_rds(file = paste0(path_argo_preprocessed, '/bgc_merge_flag_A.rds')) %>% 
  select(-c(temp_adjusted:temp_adjusted_error, profile_temp_qc))

full_argo <- full_argo %>%
  mutate(year = year(date),
         month = month(date)) %>%
  mutate(date = ymd(format(date, "%Y-%m-15")))

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

Regions

Biomes

# keep only southern ocean biomes 

region_masks_all_1x1 <- region_masks_all_1x1 %>%
  filter(region == 'southern',
         biome != 0) %>% 
  select(-region)

# remove coastal data 

region_masks_all_1x1 <- region_masks_all_1x1 %>% 
  filter(coast == "0")

map +
  geom_tile(data = region_masks_all_1x1, 
            aes(x = lon, 
                y = lat, 
                fill = biome))+
  lims(y = c(-85, -30))+
  scale_fill_brewer(palette = 'Dark2')

Past versions of map_of_biomes-1.png

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Basins

basinmask <- basinmask %>%
  filter(lat < -30)

map +
  geom_tile(data = basinmask, 
            aes(x = lon, 
                y = lat, 
                fill = basin_AIP))+
  lims(y = c(-85, -30))+
  scale_fill_brewer(palette = 'Dark2')

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Southern Ocean Argo pH

full_argo_SO <- inner_join(full_argo, region_masks_all_1x1)

full_argo_SO <- inner_join(full_argo_SO, basinmask)

full_argo_SO <- full_argo_SO %>%
  unite('platform_cycle', platform_number:cycle_number, sep = '_', remove = FALSE)

# original_argo_SO <- inner_join(original_argo, region_masks_all_1x1)
# 
# original_argo_SO <- inner_join(original_argo_SO, basinmask)
# 
# original_argo_SO <- original_argo_SO %>% 
#   unite('platform_cycle', platform_number:cycle_number, sep = '_', remove = FALSE)

Profiles by longitude

# plot the argo temperature profiles according to their longitude, in each biome, basin, and year

full_argo_SO %>% 
  group_split(biome, basin_AIP, year) %>% 
  # head(2) %>% 
  map(
    ~ ggplot(data = .x,
             aes(x = ph_in_situ_total_adjusted,
                 y = depth,
                 group = platform_cycle,
                 col = lon))+
      geom_path(data = .x,
                aes(x = ph_in_situ_total_adjusted,
                    y = depth,
                    group = platform_cycle,
                    col = lon), 
                size = 0.3)+
      scale_y_reverse()+
      scale_color_viridis_c()+
      facet_wrap(~month, ncol = 6)+
      labs(title = paste0('biome: ', unique(.x$biome), '| basin: ', unique(.x$basin_AIP), ' |', unique(.x$year)),
           x = 'Argo pH',
           y = 'depth (m)',
           col = 'longitude')
  )

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Profiles by latitude

# color the argo profiles according to their latitude, for each biome, basin, and year 

full_argo_SO %>% 
  group_split(biome, basin_AIP, year) %>% 
  # head(6) %>% 
  map(
    ~ ggplot(data = .x,
             aes(x = ph_in_situ_total_adjusted,
                 y = depth,
                 group = platform_cycle,
                 col = lat))+
      geom_path(data = .x,
                aes(x = ph_in_situ_total_adjusted,
                    y = depth,
                    group = platform_cycle,
                    col = lat), 
                size = 0.3)+
      scale_y_reverse()+
      scale_color_viridis_c()+
      facet_wrap(~month, ncol = 6)+
      labs(title = paste0('biome: ', unique(.x$biome), '| basin: ', unique(.x$basin_AIP), ' |', unique(.x$year)),
           x = 'Argo pH',
           y = 'depth (m)',
           col = 'latitude')
  )

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Session information

sessionInfo()

R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.3

Matrix products: default
BLAS:   /usr/local/R-4.1.2/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.1.2/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] ggforce_0.3.3     metR_0.11.0       scico_1.3.0       ggOceanMaps_1.2.6
 [5] ggspatial_1.1.5   broom_0.7.11      lubridate_1.8.0   forcats_0.5.1    
 [9] stringr_1.4.0     dplyr_1.0.7       purrr_0.3.4       readr_2.1.1      
[13] tidyr_1.1.4       tibble_3.1.6      ggplot2_3.3.5     tidyverse_1.3.1  
[17] workflowr_1.7.0  

loaded via a namespace (and not attached):
 [1] fs_1.5.2           sf_1.0-5           bit64_4.0.5        RColorBrewer_1.1-2
 [5] httr_1.4.2         rprojroot_2.0.2    tools_4.1.2        backports_1.4.1   
 [9] bslib_0.3.1        utf8_1.2.2         rgdal_1.5-28       R6_2.5.1          
[13] KernSmooth_2.23-20 rgeos_0.5-9        DBI_1.1.2          colorspace_2.0-2  
[17] raster_3.5-11      withr_2.4.3        sp_1.4-6           tidyselect_1.1.1  
[21] processx_3.5.2     bit_4.0.4          compiler_4.1.2     git2r_0.29.0      
[25] cli_3.1.1          rvest_1.0.2        xml2_1.3.3         labeling_0.4.2    
[29] sass_0.4.0         checkmate_2.0.0    scales_1.1.1       classInt_0.4-3    
[33] callr_3.7.0        proxy_0.4-26       digest_0.6.29      rmarkdown_2.11    
[37] pkgconfig_2.0.3    htmltools_0.5.2    highr_0.9          dbplyr_2.1.1      
[41] fastmap_1.1.0      rlang_1.0.2        readxl_1.3.1       rstudioapi_0.13   
[45] farver_2.1.0       jquerylib_0.1.4    generics_0.1.1     jsonlite_1.7.3    
[49] vroom_1.5.7        magrittr_2.0.1     Rcpp_1.0.8         munsell_0.5.0     
[53] fansi_1.0.2        lifecycle_1.0.1    terra_1.5-12       stringi_1.7.6     
[57] whisker_0.4        yaml_2.2.1         MASS_7.3-55        grid_4.1.2        
[61] parallel_4.1.2     promises_1.2.0.1   crayon_1.4.2       lattice_0.20-45   
[65] haven_2.4.3        hms_1.1.1          knitr_1.37         ps_1.6.0          
[69] pillar_1.6.4       codetools_0.2-18   reprex_2.0.1       glue_1.6.0        
[73] evaluate_0.14      getPass_0.2-2      data.table_1.14.2  modelr_0.1.8      
[77] tweenr_1.0.2       vctrs_0.3.8        tzdb_0.2.0         httpuv_1.6.5      
[81] cellranger_1.1.0   polyclip_1.10-0    gtable_0.3.0       assertthat_0.2.1  
[85] xfun_0.29          e1071_1.7-9        later_1.3.0        viridisLite_0.4.0 
[89] class_7.3-20       units_0.7-2        ellipsis_0.3.2