Extreme pH Profiles

workflowr

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Last updated: 2022-05-12

Checks: 7 0

Knit directory: bgc_argo_r_argodata/

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---

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---

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/extreme_compound.Rmd) and HTML (docs/extreme_compound.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	dfe89d7	jens-daniel-mueller	2022-05-12	Build site.
html	710edd4	jens-daniel-mueller	2022-05-11	Build site.
Rmd	2f20a76	jens-daniel-mueller	2022-05-11	rebuild all after subsetting AB profiles and code cleaning

---

Task

Explore double extremes in the temp and pH anomaly fields

Load Data

library(tidyverse)
library(lubridate)
library(ggnewscale)

theme_set(theme_bw())

HNL_colors_map <- c('H' = 'red3',
                    'N' = 'gray90',
                    'L' = 'blue3')

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/"

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

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

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


# argo pH data (flag A only)
full_argo <- read_rds(file = paste0(path_argo_preprocessed, "/bgc_merge_flag_AB.rds"))


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

Anomaly maps

pH

pH_extreme %>%
  filter(year >= 2013) %>% 
  group_split(month) %>%
  #head(1) %>%
  map(
    ~map +
      geom_tile(data = .x,
                aes(x = lon_raw,
                    y = lat_raw,
                    fill = ph_extreme))+
      scale_fill_manual(values = HNL_colors_map)+
      facet_wrap(~year, ncol = 2)+
      lims(y = c(-85, -32))+
      labs(title = paste('month:', unique(.x$month)),
           fill = 'pH')
  )

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SST

temp_extreme %>%
  filter(year >= 2013) %>% 
  group_split(month) %>%
  #head(1) %>%
  map(
    ~map +
      geom_tile(data = .x,
                aes(x = lon_raw,
                    y = lat_raw,
                    fill = temp_extreme))+
      scale_fill_manual(values = HNL_colors_map)+
      facet_wrap(~year, ncol = 2)+
      lims(y = c(-85, -32))+
      labs(title = paste('month:', unique(.x$month)),
           fill = 'pH')
  )

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Join data

anomaly_field <- full_join(pH_extreme %>% 
                             select(lon_raw, lat_raw, month, year, date, basin_AIP, biome_name, ph_extreme),
                           temp_extreme %>% 
                             select(lon_raw, lat_raw, month, year, date, basin_AIP, biome_name, temp_extreme))

# chisq.test(anomaly_field$ph_extreme, anomaly_field$temp_extreme, correct = FALSE)

anomaly_field <- anomaly_field %>%
  mutate(
    double_extreme = case_when(
      temp_extreme == 'H' & ph_extreme == 'H' ~ 'warm_HpH',
      temp_extreme == 'L' &
        ph_extreme == 'H' ~ 'cold_HpH',
      temp_extreme == 'H' &
        ph_extreme == 'L' ~ 'warm_LpH',
      temp_extreme == 'L' &
        ph_extreme == 'L' ~ 'cold_LpH',
      temp_extreme == 'H' &
        ph_extreme == 'N' ~ 'warm',
      temp_extreme == 'L' &
        ph_extreme == 'N' ~ 'cold',
      temp_extreme == 'N' &
        ph_extreme == 'H' ~ 'HpH',
      temp_extreme == 'N' &
        ph_extreme == 'L' ~ 'LpH',
      TRUE ~ 'N'
    )
  ) %>%
  mutate(
    double_extreme = fct_relevel(
      double_extreme,
      'warm_HpH',
      'cold_HpH',
      'warm_LpH',
      'cold_LpH',
      'warm',
      'cold',
      'HpH',
      'LpH',
      'N'
    )
  )

Compound extreme maps

HNL_colors_map_temp <- c('H' = "#CD534CFF",
                    'N' = 'transparent',
                    'L' = "#0073C2FF")

HNL_colors_map_ph <- c('H' = "#009E73",
                    'N' = 'transparent',
                    'L' = "#EFC000FF")


anomaly_field %>%
  filter(year >= 2013,
         double_extreme != "N") %>%
  group_split(month) %>%
  # tail(1) %>%
  map(
    ~ map +
      geom_tile(data = .x,
                aes(
                  x = lon_raw,
                  y = lat_raw,
                  fill = ph_extreme
                ), alpha = 0.4) +
      scale_fill_manual(values = HNL_colors_map_ph) +
      new_scale_fill() +
      geom_tile(data = .x,
                aes(
                  x = lon_raw,
                  y = lat_raw,
                  fill = temp_extreme
                ), alpha = 0.4) +
      scale_fill_manual(values = HNL_colors_map_temp) +
      facet_wrap(~ year, ncol = 2) +
      lims(y = c(-85, -32)) +
      labs(title = paste0('month:', unique(.x$month)))
  )

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rm(HNL_colors_map_temp, HNL_colors_map_ph)

anomaly_field %>% 
  filter(year >= 2013) %>% 
  group_split(month) %>% 
  map(
    ~map+
      geom_tile(data = .x,
                aes(x = lon_raw,
                    y = lat_raw,
                    fill = double_extreme))+
      facet_wrap(~year, ncol = 2)+
      scale_fill_manual(values = c('warm_HpH' = 'brown',
                                   'warm_LpH' = 'yellow',
                                   'cold_HpH' = 'beige',
                                   'cold_LpH' = 'cyan',
                                   'cold' = 'blue',
                                   'warm' = 'red',
                                   'LpH' = 'orange',
                                   'HpH' = 'green',
                                   'N' = NA),
                        na.value = NA)+
      lims(y = c(-85, -32))+
      labs(title = paste0('month:', unique(.x$month)),
           fill = 'double extreme')
  )

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Join Argo profile data

anomaly_field <- anomaly_field %>% 
  rename(lat = lat_raw,
         lon = lon_raw) %>% 
  filter(year >= 2013)
  
profile_double_extreme <- inner_join(full_argo %>% 
                                       select(-c(temp_adjusted_error, 
                                                 temp_adjusted_qc,
                                                 ph_in_situ_total_adjusted_error,
                                                 ph_in_situ_total_adjusted_qc,
                                                 profile_temp_qc,
                                                 profile_ph_in_situ_total_qc)),
                                     anomaly_field)

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

anomaly_field %>% 
  filter(year >= 2013) %>% 
  group_split(month) %>% 
  map(
    ~map+
      geom_tile(data = .x,
                aes(x = lon,
                    y = lat,
                    fill = double_extreme))+
      facet_wrap(~year, ncol = 2)+
      scale_fill_manual(values = c('warm_HpH' = 'brown',
                                   'warm_LpH' = 'yellow',
                                   'cold_HpH' = 'beige',
                                   'cold_LpH' = 'cyan',
                                   'cold' = 'blue',
                                   'warm' = 'red',
                                   'LpH' = 'orange',
                                   'HpH' = 'green',
                                   'N' = NA),
                        na.value = NA)+
      geom_point(data = profile_double_extreme, 
                 aes(x = lon,
                     y = lat),
                 size = 0.2)+
      lims(y = c(-85, -32))+
      labs(title = paste0('month:', unique(.x$month)),
           fill = 'double extreme')
  )

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Plot Profiles

Raw

pH

profile_double_extreme %>% 
  group_split(biome_name, basin_AIP, year) %>% 
  map(
    ~ggplot(data = .x,
            aes(x = ph_in_situ_total_adjusted,
                y = depth,
                group = platform_cycle,
                col = double_extreme))+
      geom_path(data = .x %>% filter(double_extreme == 'N'),
                aes(x = ph_in_situ_total_adjusted,
                    y = depth, 
                    group = platform_cycle,
                    col = double_extreme),
                size = 0.3)+
      geom_path(data = .x %>% filter(double_extreme == 'E'),
                aes(x = ph_in_situ_total_adjusted,
                    y = depth, 
                    group = platform_cycle,
                    col = double_extreme),
                size = 0.5)+
      scale_y_reverse()+
      scale_color_manual(values = c('N' = 'gray', 'E' = 'red'))+
      facet_wrap(~month, ncol = 6)+
      labs(title = paste0('biome: ', unique(.x$biome_name), '| ', unique(.x$basin_AIP), '| ', unique(.x$year)),
           col = 'double extreme',
           x = 'Argo pH',
           y = 'depth')
  )

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Temperature

profile_double_extreme %>% 
  group_split(biome_name, basin_AIP, year) %>% 
  map(
    ~ggplot(data = .x,
            aes(x = temp_adjusted,
                y = depth,
                group = platform_cycle,
                col = double_extreme))+
      geom_path(data = .x %>% filter(double_extreme == 'N'),
                aes(x = temp_adjusted,
                    y = depth, 
                    group = platform_cycle,
                    col = double_extreme),
                size = 0.3)+
      geom_path(data = .x %>% filter(double_extreme == 'E'),
                aes(x = temp_adjusted,
                    y = depth, 
                    group = platform_cycle,
                    col = double_extreme),
                size = 0.5)+
      scale_y_reverse()+
      scale_color_manual(values = c('N' = 'gray', 'E' = 'red'))+
      facet_wrap(~month, ncol = 6)+
      labs(title = paste0('biome: ', unique(.x$biome_name), '| ', unique(.x$basin_AIP), '| ', unique(.x$year)),
           col = 'double extreme',
           x = 'Argo temperature',
           y = 'depth')
  )

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Pacific basin, STSS biome, December 2017

Pacific_STSS_2017 <- profile_double_extreme %>% 
  filter(date == '2017-12-15',
         basin_AIP == 'Pacific',
         biome_name == 'STSS')

# pH: 
Pacific_STSS_2017 %>% 
  ggplot()+
  geom_path(data = Pacific_STSS_2017 %>% filter(double_extreme == 'N'),
            aes(x = ph_in_situ_total_adjusted,
                y = depth,
                group = platform_cycle, 
                col = double_extreme),
            size = 0.3)+
  geom_path(data = Pacific_STSS_2017 %>% filter(double_extreme == 'E'),
            aes(x = ph_in_situ_total_adjusted,
                y = depth,
                group = platform_cycle, 
                col = double_extreme),
            size = 0.5)+
  scale_y_reverse()+
  scale_color_manual(values = c('E' = 'red', 'N' = 'grey'))+
  labs(title = 'Pacific, STSS biome, December 2017',
       col = 'double extreme',
       x = 'Argo pH',
       y = 'depth')

Past versions of pacific_STSS_dec_2017-1.png

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710edd4	jens-daniel-mueller	2022-05-11

# Temperature 

Pacific_STSS_2017 %>% 
  ggplot()+
  geom_path(data = Pacific_STSS_2017 %>% filter(double_extreme == 'N'),
            aes(x = temp_adjusted,
                y = depth,
                group = platform_cycle, 
                col = double_extreme),
            size = 0.3)+
  geom_path(data = Pacific_STSS_2017 %>% filter(double_extreme == 'E'),
            aes(x = temp_adjusted,
                y = depth,
                group = platform_cycle, 
                col = double_extreme),
            size = 0.5)+
  scale_y_reverse()+
  scale_color_manual(values = c('E' = 'red', 'N' = 'grey'))+
  labs(title = 'Pacific, STSS biome, December 2017',
       col = 'double extreme',
       x = 'Argo pH',
       y = 'depth')

Past versions of pacific_STSS_dec_2017-2.png

Version	Author	Date
710edd4	jens-daniel-mueller	2022-05-11

rm(Pacific_STSS_2017)

Pacific basin, STSS biome, December 2019

No profiles for December 2019 in SPSS or STSS Pacific

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] ggnewscale_0.4.5 lubridate_1.8.0  forcats_0.5.1    stringr_1.4.0   
 [5] dplyr_1.0.7      purrr_0.3.4      readr_2.1.1      tidyr_1.1.4     
 [9] tibble_3.1.6     ggplot2_3.3.5    tidyverse_1.3.1  workflowr_1.7.0 

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.8       getPass_0.2-2    ps_1.6.0         assertthat_0.2.1
 [5] rprojroot_2.0.2  digest_0.6.29    utf8_1.2.2       R6_2.5.1        
 [9] cellranger_1.1.0 backports_1.4.1  reprex_2.0.1     evaluate_0.14   
[13] highr_0.9        httr_1.4.2       pillar_1.6.4     rlang_1.0.2     
[17] readxl_1.3.1     rstudioapi_0.13  whisker_0.4      callr_3.7.0     
[21] jquerylib_0.1.4  rmarkdown_2.11   labeling_0.4.2   munsell_0.5.0   
[25] broom_0.7.11     compiler_4.1.2   httpuv_1.6.5     modelr_0.1.8    
[29] xfun_0.29        pkgconfig_2.0.3  htmltools_0.5.2  tidyselect_1.1.1
[33] fansi_1.0.2      withr_2.4.3      crayon_1.4.2     tzdb_0.2.0      
[37] dbplyr_2.1.1     later_1.3.0      grid_4.1.2       jsonlite_1.7.3  
[41] gtable_0.3.0     lifecycle_1.0.1  DBI_1.1.2        git2r_0.29.0    
[45] magrittr_2.0.1   scales_1.1.1     cli_3.1.1        stringi_1.7.6   
[49] farver_2.1.0     fs_1.5.2         promises_1.2.0.1 xml2_1.3.3      
[53] bslib_0.3.1      ellipsis_0.3.2   generics_0.1.1   vctrs_0.3.8     
[57] tools_4.1.2      glue_1.6.0       hms_1.1.1        processx_3.5.2  
[61] fastmap_1.1.0    yaml_2.2.1       colorspace_2.0-2 rvest_1.0.2     
[65] knitr_1.37       haven_2.4.3      sass_0.4.0