OceanSODA-Argo pH

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Last updated: 2022-08-29

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Knit directory: bgc_argo_r_argodata/

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Task

Compare BGC-Argo pH data to pH from the OceanSODA surface data product

theme_set(theme_bw())

Load data

Load in surface Argo pH and the OceanSODA pH, gridded to 1x1º

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/"

# load in OceanSODA data and Argo pH
OceanSODA <- read_rds(file = paste0(path_argo_preprocessed, "/OceanSODA.rds"))


argo <-
  read_rds(file = paste0(path_argo_preprocessed, "/bgc_merge_flag_AB.rds")) %>%
  filter(between(depth, 0, 20)) %>%
  mutate(year = year(date),
         month = month(date)) %>%
  select(-c(
    temp_adjusted,
    temp_adjusted_qc,
    temp_adjusted_error,
    profile_temp_qc
  ))

# for plotting later, load in region and coastline information  
# region_masks_all_seamask_2x2 <- read_rds(file = paste0(
#   path_argo_preprocessed, "/region_masks_all_seamask_2x2.rds"))
# 
# region_masks_all_2x2 <- read_rds(file = paste0(path_argo_preprocessed, "/region_masks_all_2x2.rds"))
# 
# region_masks_all_1x1 <- read_rds(file = paste0(path_argo_preprocessed, "/region_masks_all_1x1.rds"))

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

# read in the map from updata
map <-
  read_rds(paste(path_emlr_utilities,
                 "map_landmask_WOA18.rds",
                 sep = ""))

Harmonise the two datasets

Calculate monthly average pH for Argo pH for each lon/lat grid, centered on the 15th of each month, to match the format of OceanSODA

argo_monthly <- argo %>%
  mutate(year_month = format_ISO8601(date, precision = "ym"), .after = 'date') %>%
  group_by(year, month, year_month, date, lat, lon) %>%
  summarise(
    argo_ph_month = mean(ph_in_situ_total_adjusted, na.rm = TRUE)
  ) %>%
  ungroup() %>%
  select(
    date,
    year_month,
    year,
    month,
    lon,
    lat,
    argo_ph_month
  )

Join the two datasets

OceanSODA <- OceanSODA %>% 
  mutate(year_month = format_ISO8601(date, precision = "ym")) %>% 
  rename(date_OceanSODA = date) 
  # change date format in OceanSODA to match argo date (yyyy-mm)

argo_OceanSODA <- left_join(argo_monthly, OceanSODA) %>%
  rename(OceanSODA_ph = ph_total,
         OceanSODA_ph_error = ph_total_uncert) 

argo_OceanSODA %>%
  write_rds(file = paste0(path_argo_preprocessed, "/argo_OceanSODA.rds"))

Southern Ocean surface pH

The focus here is on Southern Ocean surface pH, south of 30ºS, as defined in the RECCAP biome regions

# region_masks_all_1x1_SO <- region_masks_all_1x1 %>%
#   filter(region == 'southern',
#          value != 0)

# keep only Southern Ocean data 
argo_OceanSODA_SO <- inner_join(argo_OceanSODA, nm_biomes)

Monthly climatological OceanSODA pH

Map monthly mean pH from the OceanSODA data product

Climatological OceanSODA pH

# calculate average monthly pH between April 2014 and August 2021 
argo_OceanSODA_SO_clim <- argo_OceanSODA_SO %>%
  group_by(lon, lat, month) %>%
  summarise(
    clim_OceanSODA_ph = mean(OceanSODA_ph, na.rm = TRUE),
    clim_argo_ph = mean(argo_ph_month, na.rm = TRUE),
    offset_clim = clim_OceanSODA_ph - clim_argo_ph
  ) %>%
  ungroup()

# regrid to a 2x2 grid for mapping 
argo_OceanSODA_SO_clim_2x2 <- argo_OceanSODA_SO_clim %>%
  mutate(
    lat = cut(lat, seq(-90, 90, 2), seq(-89, 89, 2)),
    lat = as.numeric(as.character(lat)),
    lon = cut(lon, seq(20, 380, 2), seq(21, 379, 2)),
    lon = as.numeric(as.character(lon))
  ) %>%
  group_by(lon, lat, month) %>%
  summarise(
    clim_OceanSODA_ph = mean(clim_OceanSODA_ph, na.rm = TRUE),
    clim_argo_ph = mean(clim_argo_ph, na.rm = TRUE),
    offset_clim = mean(offset_clim, na.rm = TRUE)
  ) %>%
  ungroup()

map +
  geom_tile(data = argo_OceanSODA_SO_clim_2x2,
            aes(lon, lat, fill = clim_OceanSODA_ph)) +
  lims(y = c(-85, -25)) +
  scale_fill_viridis_c() +
  labs(x = 'lon',
       y = 'lat',
       fill = 'pH',
       title = 'Monthly climatological \nOceanSODA pH (Apr 2014 - Aug 2021)') +
  theme(legend.position = 'right') +
  facet_wrap(~month, ncol = 2)

Past versions of climatological_map-1.png

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

# plot the climatological monthly OceanSODA pH on a polar projection 
basemap(limits = -32, data = argo_OceanSODA_SO_clim_2x2) +   # change to polar projection
  geom_spatial_tile(data = argo_OceanSODA_SO_clim_2x2,
                    aes(x = lon,
                        y = lat,
                        fill = clim_OceanSODA_ph),
                    linejoin = 'mitre',
                    col = 'transparent',
                    detail = 60)+
  scale_fill_viridis_c()+
  theme(legend.position = 'right')+
  labs(x = 'lon',
       y = 'lat',
       fill = 'pH',
       title = 'monthly climatological \nOceanSODA pH (Apr 2014 - Aug 2021)')+
  facet_wrap(~month, ncol = 2)

Climatological monthly Argo pH

Climatological Argo pH

map +
  geom_tile(data = argo_OceanSODA_SO_clim_2x2,
            aes(lon, lat, fill = clim_argo_ph)) +
  lims(y = c(-85, -25)) +
  scale_fill_viridis_c() +
  labs(x = 'lon',
       y = 'lat',
       fill = 'pH',
       title = 'Monthly climatological \nArgo pH (Apr 2014 - Aug 2021)') +
  theme(legend.position = 'right') +
  facet_wrap(~month, ncol = 2)

Past versions of clim_map_argo_pH-1.png

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

basemap(limits = -32, data = argo_OceanSODA_SO_clim_2x2) +   # change to polar projection
  geom_spatial_tile(data = argo_OceanSODA_SO_clim_2x2,
                    aes(x = lon,
                        y = lat,
                        fill = clim_argo_ph),
                    linejoin = 'mitre',
                    col = 'transparent',
                    detail = 60)+
  scale_fill_viridis_c()+
  theme(legend.position = 'right')+
  labs(x = 'lon',
       y = 'lat',
       fill = 'pH',
       title = 'monthly climatological \nArgo pH (Apr 2014 - Aug 2021)')+
  facet_wrap(~month, ncol = 2)

Timeseries of monthly OceanSODA pH

Evolution of monthly surface pH, for the three Southern Ocean RECCAP regions

map +
  geom_raster(data = nm_biomes,
              aes(x = lon,
                  y = lat,
                  fill = biome_name)) +
  labs(title = 'Southern Ocean Mayot biomes',
       fill = 'biome')

Past versions of southern_ocean_biomes-1.png

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

# plot timeseries of monthly OceanSODA pH
argo_OceanSODA_SO_clim_regional <- argo_OceanSODA_SO %>%
  select(year, month, biome_name, OceanSODA_ph, argo_ph_month) %>% 
  pivot_longer(c(OceanSODA_ph,argo_ph_month),
               values_to = "ph",
               names_to = "data_source") %>% 
  group_by(year, month, biome_name, data_source) %>%  # compute regional mean OceanSODA pH for the three biomes
  summarise(ph = mean(ph, na.rm = TRUE)) %>%
  ungroup()

argo_OceanSODA_SO_clim_regional %>%   
  ggplot(aes(x = year,
             y = ph,
             col = biome_name)) +
  facet_grid(month ~ data_source) +
  geom_line() +
  geom_point() +
  labs(x = 'year',
       y = 'pH in situ (total scale)',
       title = 'monthly mean pH (Apr 2014-Aug 2021, Southern Ocean)',
       col = 'region')

argo_OceanSODA_SO_clim_regional %>%   
  # filter(year != 2014,
  #        year != 2021) %>%
  ggplot(aes(x = month,
             y = ph,
             group = year,
             col = as.character(year)))+
  geom_line()+
  geom_point()+
  scale_x_continuous(breaks = seq(1, 12, 2))+
  facet_grid(biome_name~data_source)+
  labs(x = 'month',
       y = 'pH in situ (total scale)',
       title = 'monthly mean OceanSODA pH (Jan 2015-Dec 2020, Southern Ocean)',
       col = 'year')

Past versions of yearly_timeseries_monthly_oceanSODA_pH-1.png

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

Comparison between Argo and OceanSODA pH

Calculate the difference between Argo and OceanSODA pH values

Offset between in-situ monthly pH:

argo_OceanSODA_SO <- argo_OceanSODA_SO %>%
  mutate(offset = OceanSODA_ph - argo_ph_month)

argo_OceanSODA_SO %>%
  drop_na() %>%
  ggplot() +
  geom_hline(yintercept = 0, size = 1)+
  geom_point(aes(x = year_month, y = offset, col = biome_name), size = 0.7, pch = 19) +
  scale_x_discrete(breaks = c('2014-01', '2015-01', '2016-01', '2017-01', '2018-01', '2019-01', '2020-01'))+
  labs(title = 'oceanSODA pH - Argo pH',
       x = 'date',
       y = 'offset (pH units)',
       col = 'region')

Past versions of calculate_in_situ_offset-1.png

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

argo_OceanSODA_SO %>% 
  drop_na() %>% 
  ggplot(aes(x = OceanSODA_ph, y = argo_ph_month))+
  # geom_point(pch = 19, size = 0.7)+
  geom_bin2d(aes(x = OceanSODA_ph, y = argo_ph_month), size = 0.3, bins = 60)+
  scale_fill_viridis_c()+
  lims(x = c(7.8, 8.25), 
       y = c(7.8, 8.25)) +
  geom_abline(slope = 1, intercept = 0)+
  facet_wrap(~biome_name)+
  labs(x = 'OceanSODA pH (total scale)',
       y = 'Argo pH (total scale)',
       title = 'Southern Ocean regional pH')

Past versions of oceanSODA_vs_argo_ph_plot-1.png

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

Mean offset between in-situ OceanSODA pH and in-situ Argo pH

mean_insitu_offset <- argo_OceanSODA_SO %>%
  group_by(year_month, biome_name) %>% 
  summarise(mean_offset = mean(offset, na.rm = TRUE),
            std_offset = sd(offset, na.rm = TRUE))

mean_insitu_offset %>%
  drop_na() %>%
  ggplot() +
  geom_hline(yintercept = 0, size = 1, col = 'red')+
  geom_point(aes(x = year_month, y = mean_offset, group = biome_name, col = biome_name),
             size = 0.7, pch = 19) +
  geom_line(aes(x = year_month, y = mean_offset, group = biome_name, col = biome_name))+
  geom_ribbon(aes(x = year_month, 
                  ymin = mean_offset-std_offset, 
                  ymax = mean_offset+std_offset, 
                  group = biome_name, 
                  fill = biome_name),
              alpha = 0.2)+
  scale_x_discrete(breaks = c('2014-01', '2015-01', '2016-01', '2017-01', '2018-01', '2019-01', '2020-01'))+
  # facet_wrap(~year)+
  labs(title = 'Mean offset (in situ oceanSODA pH - in situ Argo pH)',
       x = 'date',
       y = 'offset (pH units)',
       col = 'region',
       fill = '± 1 std')

Past versions of mean_in_situ_offset-1.png

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

Offset between climatological Argo and climatological OceanSODA pH:

# Offset between climatological argo and climatological OceanSODA pH 

argo_OceanSODA_SO_clim <- inner_join(argo_OceanSODA_SO_clim, nm_biomes)

argo_OceanSODA_SO_clim %>% 
  drop_na() %>%
  ggplot() +
  geom_point(aes(x = month, y = offset_clim, col = biome_name), size = 0.7, pch = 19) +
  geom_hline(yintercept = 0, size = 1, col = 'red')+
  scale_x_continuous(breaks = seq(1, 12, 1))+
  labs(title = 'clim oceanSODA pH - clim Argo pH',
       x = 'month',
       y = 'offset (pH units)',
       col = 'region')

Mean offset between climatological OceanSODA pH and climatological Argo pH

mean_clim_offset <- argo_OceanSODA_SO_clim %>% 
  group_by(month, biome_name) %>% 
  summarise(mean_offset_clim = mean(offset_clim, na.rm = TRUE),
            std_offset_clim = sd(offset_clim, na.rm = TRUE))

mean_clim_offset %>% 
  ggplot()+
  geom_point(aes(x = month, y = mean_offset_clim, col = biome_name))+
  geom_line(aes(x = month, y = mean_offset_clim, col = biome_name))+
  geom_hline(yintercept = 0, col = 'red') +
  geom_ribbon(aes(x = month, 
                  ymin = mean_offset_clim - std_offset_clim, 
                  ymax = mean_offset_clim + std_offset_clim,
                  group = biome_name, 
                  fill = biome_name), 
              alpha = 0.2) +
  scale_x_continuous(breaks = seq(1, 12, 1)) +
  labs(x = 'month',
       y = 'mean offset (pH units)',
       title = 'Mean offset (clim OceanSODA pH - clim Argo pH)', 
       col = 'region',
       fill = '± 1 std') 

Past versions of climatological_offset_all_years-1.png

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

Mapped offset between climatological OceanSODA pH and climatological Argo pH

# bin the offsets for better plotting  
# plot the offsets on a map of the Southern Ocean

argo_OceanSODA_SO_clim_2x2 <- argo_OceanSODA_SO_clim_2x2 %>% 
  mutate(offset_clim_binned = 
           cut(offset_clim, 
               breaks = c(-Inf, -0.025, -0.005, 0.000, 0.005, 0.025, 0.035, 0.05, Inf))) %>%    # bin the offsets into intervals (create a discrete variable instead of continuous)
         # offset_clim_binned = as.factor(as.character(offset_clim_binned))) %>% 
  drop_na()

map +
  geom_tile(data = argo_OceanSODA_SO_clim_2x2,
            aes(lon, lat, fill = offset_clim_binned)) +
  lims(y = c(-85, -30)) +
  scale_fill_brewer(palette = 'RdBu', drop = FALSE) +
  labs(x = 'lon',
       y = 'lat',
       fill = 'offset (pH units)',
       title = 'clim OceanSODA ph - clim Argo pH') +
  theme(legend.position = 'right')+
  facet_wrap(~month, ncol = 2)

Past versions of map_climatological_offset-1.png

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

basemap(limits = -32, data = argo_OceanSODA_SO_clim_2x2) +   # change to polar projection
  geom_spatial_tile(data = argo_OceanSODA_SO_clim_2x2,
                    aes(x = lon,
                        y = lat,
                        fill = offset_clim_binned),
                    linejoin = 'mitre',
                    col = 'transparent',
                    detail = 60)+
  scale_fill_brewer(palette = 'RdBu', drop = FALSE)+
  theme(legend.position = 'right')+
  labs(x = 'lon',
       y = 'lat',
       fill = 'offset (pH units)',
       title = 'clim Ocean SODA pH - clim Argo pH')+
  facet_wrap(~month, ncol = 2)

Basin separation

Using full OceanSODA data (even where there is no Argo data) Each RECCAP biome (1, 2, 3) is separated into basins (Atlantic, Pacific, Indian)

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)

OceanSODA_SO <- inner_join(OceanSODA, nm_biomes)

OceanSODA_SO <- inner_join(OceanSODA_SO, basinmask) %>% 
  mutate(year = year(date_OceanSODA),
         month = month(date_OceanSODA)) %>% 
  mutate(date = format_ISO8601(date_OceanSODA, precision = 'ym')) %>% 
  filter(year >= 2013)

# plot timeseries of monthly OceanSODA pH

OceanSODA_SO_clim_subregional <- OceanSODA_SO %>%
  group_by(year, month, biome_name, basin_AIP) %>%  # compute regional mean OceanSODA pH for the three biomes
  summarise(ph = mean(ph_total, na.rm = TRUE)) %>%
  ungroup()

# plot a timeseries of monthly average OceanSODA pH, per region and per basin
OceanSODA_SO_clim_subregional %>% 
  ggplot(aes(x = month,
             y = ph,
             group = year,
             col = as.character(year)))+
  geom_line()+
  geom_point()+
  scale_x_continuous(breaks = seq(1, 12, 2))+
  facet_grid(biome_name~basin_AIP)+
  labs(x = 'month',
       y = 'pH in situ (total scale)',
       title = 'monthly mean OceanSODA pH (Jan 2013-Dec 2020, Southern Ocean basins)',
       col = 'year')

Past versions of monthly_OceanSODA_basin-1.png

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

OceanSODA_SO_clim_subregional %>%  
  ggplot(aes(x = year,
             y = ph,
             col = biome_name)) +
  facet_grid(month ~ basin_AIP) +
  geom_line() +
  geom_point() +
  labs(x = 'year',
       y = 'pH in situ (total scale)',
       title = 'monthly mean pH (Jan 2013-Dec 2020, Southern Ocean basins)',
       col = 'region')

Past versions of monthly_OceanSODA_basin_per_year-1.png

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

Longitudinal separation

Bin the pH data into 20º longitude bins (20º - 380º)

OceanSODA_SO_lon_binned <- OceanSODA_SO %>%
  mutate(lon = cut(lon, seq(20, 380, 20), seq(30, 370, 20)),
         lon = as.numeric(as.character(lon))
  ) %>%
  group_by(lon, year, month, biome_name) %>%
  summarise(
    OceanSODA_ph_binned = mean(ph_total, na.rm = TRUE)
  ) %>%
  ungroup()

OceanSODA_SO_lon_binned %>%
  drop_na() %>% 
  ggplot(aes(x = month, y = OceanSODA_ph_binned, group = lon, col = as.factor(lon))) +
  geom_line()+
  geom_point()+
  scale_x_continuous(breaks = seq(1, 12, 2))+
  facet_grid(year~biome_name)+
  labs(x = 'month',
       y = 'OceanSODA pH',
       col = 'longitude bin')

Past versions of plot_lon_binned_data-1.png

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

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] metR_0.11.0       ggOceanMaps_1.2.6 ggspatial_1.1.5   lubridate_1.8.0  
 [5] argodata_0.1.0    forcats_0.5.1     stringr_1.4.0     dplyr_1.0.7      
 [9] purrr_0.3.4       readr_2.1.1       tidyr_1.1.4       tibble_3.1.6     
[13] ggplot2_3.3.5     tidyverse_1.3.1   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        rgdal_1.5-28       utf8_1.2.2         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        RNetCDF_2.5-2      xml2_1.3.3        
[29] labeling_0.4.2     sass_0.4.0         checkmate_2.0.0    scales_1.1.1      
[33] classInt_0.4-3     callr_3.7.0        proxy_0.4-26       digest_0.6.29     
[37] rmarkdown_2.11     pkgconfig_2.0.3    htmltools_0.5.2    highr_0.9         
[41] dbplyr_2.1.1       fastmap_1.1.0      rlang_1.0.2        readxl_1.3.1      
[45] rstudioapi_0.13    farver_2.1.0       jquerylib_0.1.4    generics_0.1.1    
[49] jsonlite_1.7.3     vroom_1.5.7        magrittr_2.0.1     Rcpp_1.0.8        
[53] munsell_0.5.0      fansi_1.0.2        lifecycle_1.0.1    terra_1.5-12      
[57] stringi_1.7.6      whisker_0.4        yaml_2.2.1         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] vctrs_0.3.8        tzdb_0.2.0         httpuv_1.6.5       cellranger_1.1.0  
[81] gtable_0.3.0       assertthat_0.2.1   xfun_0.29          broom_0.7.11      
[85] e1071_1.7-9        later_1.3.0        viridisLite_0.4.0  class_7.3-20      
[89] units_0.7-2        ellipsis_0.3.2