Last updated: 2021-11-26

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Knit directory: bgc_argo_r_argodata/

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Task

Explore BGC-Argo oxygen data through timeseries and climatological maps

path_argo <- '/nfs/kryo/work/updata/bgc_argo_r_argodata'
path_emlr_utilities <- "/nfs/kryo/work/jenmueller/emlr_cant/utilities/files/"

Load oxygen data

Load in delayed-mode, adjusted oxygen data from the BGC-Argo synthetic profile files

path_argo_preprocessed <- paste0(path_argo, "/preprocessed_bgc_data")

oxy_merge <-
  read_rds(file = paste0(path_argo_preprocessed, "/bgc_merge.rds")) %>% 
  select(
    -c(nitrate_adjusted_error:ph_in_situ_total_adjusted_error),
    -c(profile_nitrate_qc, profile_ph_in_situ_total_qc)
  )

Southern Ocean surface oxygen

Focus on surface oxygen (top 10 m of the watercolumn) in the Southern Ocean, south of 30ºS

# select only best pH data (with QC flag 1) below 30ºS, for the top 10 m of the watercolumn
oxy_surface <- oxy_merge %>%
  mutate(depth = swDepth(pres_adjusted, latitude = lat), .before = pres_adjusted) %>%
  filter(doxy_adjusted_qc == '1',   # keep only 'good' data
         lat <= -30,                   # keep only data at or south of 30ºS
         depth <= 10) %>%              # keep only data above or at 10 m depth
  mutate(
    year = year(date),     # separate the year and month from the date column
    month = month(date), .after = n_prof
  )

# check the correct latitudes, QC flags, and depth levels have been filtered
# max(oxy_surface$lat)
# min(oxy_surface$lat)
# table(oxy_surface$doxy_adjusted_qc)
# max(oxy_surface$depth)
# max(oxy_surface$date)
# min(oxy_surface$date)

Monthly climatological map

Create a map of climatological monthly oxygen values, from January 2013 to August 2021, for the region south of 30ºS

# average oxygen values in the top 10 m for each month in each 2 x 2º longitude/latitude grid 
oxy_mean <- oxy_surface %>%
  group_by(lat, lon, month) %>%
  summarise(oxy_ave_month = mean(doxy_adjusted))
`summarise()` has grouped output by 'lat', 'lon'. You can override using the `.groups` argument.
# read in the map from updata
map <-
  read_rds(paste(path_emlr_utilities,
                 "map_landmask_WOA18.rds",
                 sep = ""))

# map a monthly climatology of surface oxygen (Jan 2013 - September 2021)
map +
  geom_tile(data = oxy_mean,
            aes(lon, lat, fill = oxy_ave_month)) +
  lims(y = c(-85, -25)) +
  scale_fill_gradientn(colors = oceColorsJet(n = oxy_mean$oxy_ave_month)) +
  labs(x = 'lon',
       y = 'lat',
       fill = 'dissolved oxygen \n(µmol kg-1)',
       title = 'Monthly average surface dissolved oxygen values (Jan 2013-Sep 2021)') +
  theme(legend.position = 'bottom')+
  facet_wrap(~month)
Warning in seq.int(0, 1, length.out = n): first element used of 'length.out'
argument
Warning: Raster pixels are placed at uneven vertical intervals and will be
shifted. Consider using geom_tile() instead.
Warning: Removed 153708 rows containing missing values (geom_raster).

Version Author Date
3df4daf pasqualina-vonlanthendinenna 2021-11-26
284003d pasqualina-vonlanthendinenna 2021-11-11

Monthly timeseries

Plot a timeseries of monthly-mean dissolved oxygen for the region south of 30ºS for the upper 10 m of the watercolumn

# plot a timeseries of monthly values over the whole southern ocean south of 30ºS
oxy_month <- oxy_surface %>%
  group_by(year, month) %>%
  summarise(oxy_ave = mean(doxy_adjusted))
`summarise()` has grouped output by 'year'. You can override using the `.groups` argument.
# timeseries of monthly pH values over 2013-2021 (separate panels for each month)
oxy_month %>%
  ggplot(aes(x = year, y = oxy_ave)) +
  facet_wrap(~month) +
  geom_line() +
  geom_point() +
  scale_x_continuous(breaks = seq(2013, 2021, 2))+
  labs(x = 'year', 
       y = 'dissolved O2 (µmol kg-1)', 
       title = 'monthly mean dissolved oxygen (Jan 2013-Sep 2021, south of 30ºS)')

Version Author Date
284003d pasqualina-vonlanthendinenna 2021-11-11

Monthly average dissolved oxygen, per year (January 2013 - December 2020; plotting only full years), over the whole region south of 30ºS

# timeseries of monthly oxygen values for each year (separate years on the same plot)
oxy_month %>%
  filter(year != 2021) %>%    # keep only years with full data 
  ggplot(aes(x = month, y = oxy_ave, group = year, col = as.character(year)))+
  geom_line()+
  geom_point()+
  scale_x_continuous(breaks = seq(1, 12, 1))+
  labs(x = 'month',
       y = 'dissolved O2 (µmol kg-1)',
       title = 'monthly mean dissolved oxygen (Jan 2013-Dec 2020, south of 30ºS)',
       col = 'year')

Version Author Date
284003d pasqualina-vonlanthendinenna 2021-11-11

Northeast Pacific surface oxygen

Focus on surface oxygen (upper 10 m) in the north-east Pacific (10ºN - 70ºN, -190ºE, -140ºE)

# select only best oxygen data (with QC flag 1) between 10 and 70ºN, and 190 and 140ºW, for the top 10 m of the watercolumn
oxy_nepacific <- oxy_merge %>%
  mutate(depth = swDepth(pres_adjusted, latitude = lat), .before = pres_adjusted) %>%
  filter(doxy_adjusted_qc == '1',   # keep only 'good' data
        between(lat, 10, 70),
        between(lon, 190, 240),                   # keep only data for the NE Pacific
        depth <= 10) %>%              # keep only data above or at 10 m depth
  mutate(
    year = year(date),     # separate the year and month from the date column
    month = month(date), .after = n_prof
  )
# longitudes larger than -180ºE are lon-380 

Monthly climatological map

Create a map of climatological monthly surface oxygen values, in the north-east Pacific ocean (10ºN - 70ºN, -190ºE, -140ºE), for January 2013 - August 2021

# average oxygen values in the top 10 m for each month in each 2 x 2º longitude/latitude grid 
oxy_mean_nepacific <- oxy_nepacific %>%
  group_by(lat, lon, month) %>%
  summarise(oxy_ave_month = mean(doxy_adjusted))
`summarise()` has grouped output by 'lat', 'lon'. You can override using the `.groups` argument.
# map a monthly climatology of surface oxygen (Jan 2013 - August 2021)
map +
  geom_tile(data = oxy_mean_nepacific,
            aes(lon, lat, fill = oxy_ave_month)) +
  lims(y = c(5, 60), 
       x = c(180, 250)) +
  scale_fill_gradientn(colors = oceColorsJet(n = oxy_mean_nepacific$oxy_ave_month)) +
  labs(x = 'lon',
       y = 'lat',
       fill = 'dissolved oxygen \n(µmol kg-1)',
       title = 'Monthly average surface dissolved oxygen (Jan 2013-Aug 2021)') +
  theme(legend.position = 'right')+
  facet_wrap(~month)
Warning in seq.int(0, 1, length.out = n): first element used of 'length.out'
argument
Warning: Removed 219516 rows containing missing values (geom_raster).

Version Author Date
3df4daf pasqualina-vonlanthendinenna 2021-11-26
273ed2c pasqualina-vonlanthendinenna 2021-11-12

Monthly timeseries

Timeseries of monthly mean oxygen for the northeast Pacific from January 2013 to August 2021

# plot a timeseries of monthly values over the whole NE Pacific
oxy_month_nepacific <- oxy_nepacific %>%
  group_by(year, month) %>%
  summarise(oxy_ave = mean(doxy_adjusted))
`summarise()` has grouped output by 'year'. You can override using the `.groups` argument.
# timeseries of monthly pH values over 2013-2021 (separate panels for each month)
oxy_month_nepacific %>%
  ggplot(aes(x = year, y = oxy_ave)) +
  facet_wrap(~month) +
  geom_line() +
  geom_point() +
  scale_x_continuous(breaks = seq(2013, 2021, 2))+
  labs(x = 'year', 
       y = 'dissolved O2 (µmol kg-1)', 
       title = 'monthly mean dissolved oxygen (Jan 2013-Aug 2021, NE Pacific)')

Version Author Date
273ed2c pasqualina-vonlanthendinenna 2021-11-12

Timeseries of monthly surface oxygen, per year, in the NE Pacific

# timeseries of monthly oxygen values for each year (separate years on the same plot)
oxy_month_nepacific %>%
  filter(year != 2021) %>%    # keep only years with full data
  ggplot(aes(x = month, y = oxy_ave, group = year, col = as.character(year)))+
  geom_line()+
  geom_point()+
  scale_x_continuous(breaks = seq(1, 12, 1))+
  labs(x = 'month',
       y = 'dissolved O2 (µmol kg-1)',
       title = 'monthly mean dissolved oxygen (Jan 2013-Dec 2020, NE Pacific)',
       col = 'year')

Version Author Date
273ed2c pasqualina-vonlanthendinenna 2021-11-12

sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.2

Matrix products: default
BLAS:   /usr/local/R-4.0.3/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.0.3/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] oce_1.4-0           testthat_3.0.4      sf_1.0-2           
 [4] gsw_1.0-6           lubridate_1.7.9     argodata_0.0.0.9000
 [7] forcats_0.5.0       stringr_1.4.0       dplyr_1.0.5        
[10] purrr_0.3.4         readr_1.4.0         tidyr_1.1.3        
[13] tibble_3.1.3        ggplot2_3.3.5       tidyverse_1.3.0    
[16] workflowr_1.6.2    

loaded via a namespace (and not attached):
 [1] httr_1.4.2         sass_0.4.0         jsonlite_1.7.2     modelr_0.1.8      
 [5] bslib_0.2.5.1      assertthat_0.2.1   highr_0.8          blob_1.2.1        
 [9] cellranger_1.1.0   yaml_2.2.1         pillar_1.6.2       backports_1.1.10  
[13] glue_1.4.2         digest_0.6.27      promises_1.2.0.1   rvest_0.3.6       
[17] colorspace_2.0-2   htmltools_0.5.1.1  httpuv_1.6.2       pkgconfig_2.0.3   
[21] broom_0.7.9        haven_2.3.1        scales_1.1.1       whisker_0.4       
[25] later_1.3.0        git2r_0.27.1       proxy_0.4-26       generics_0.1.0    
[29] farver_2.1.0       ellipsis_0.3.2     withr_2.4.2        cli_3.0.1         
[33] magrittr_2.0.1     crayon_1.4.1       readxl_1.3.1       evaluate_0.14     
[37] fs_1.5.0           fansi_0.5.0        xml2_1.3.2         class_7.3-17      
[41] tools_4.0.3        hms_0.5.3          lifecycle_1.0.0    munsell_0.5.0     
[45] reprex_0.3.0       compiler_4.0.3     jquerylib_0.1.4    e1071_1.7-8       
[49] RNetCDF_2.4-2      rlang_0.4.11       classInt_0.4-3     units_0.7-2       
[53] grid_4.0.3         rstudioapi_0.13    labeling_0.4.2     rmarkdown_2.10    
[57] gtable_0.3.0       DBI_1.1.1          R6_2.5.1           knitr_1.33        
[61] utf8_1.2.2         rprojroot_2.0.2    KernSmooth_2.23-17 stringi_1.5.3     
[65] Rcpp_1.0.7         vctrs_0.3.8        dbplyr_1.4.4       tidyselect_1.1.0  
[69] xfun_0.25