Last updated: 2022-06-23

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1 Version ID

The results displayed on this site correspond to the Version_ID: v_XXX

2 Required data

  • tcant 3D fields at tref1 and tref2 for variable and constant climate model runs
tref  <-
  read_csv(paste(path_version_data,
                 "tref.csv",
                 sep = ""))

tcant_tref_1 <-
  read_csv(
    paste0(
      path_model_preprocessing,
      "Cant_AD_annual_all_models/",
      unique(tref$median_year[1]),
      "_",
      params_local$gobm,
      ".csv"
    )
  )

tcant_tref_1 <- tcant_tref_1 %>%
  rename(tcant_tref_1 = tcant) %>%
  select(-year)

tcant_tref_2 <-
  read_csv(
    paste0(
      path_model_preprocessing,
      "Cant_AD_annual_all_models/",
      unique(tref$median_year[2]),
      "_",
      params_local$gobm,
      ".csv"
    )
  )

tcant_tref_2 <- tcant_tref_2 %>%
  rename(tcant_tref_2 = tcant) %>%
  select(-year)
tcant_cc_tref_1 <-
  read_csv(
    paste0(
      path_model_preprocessing,
      "Cant_CB_annual_all_models/",
      unique(tref$median_year[1]),
      "_",
      params_local$gobm,
      ".csv"
    )
  )

tcant_cc_tref_1 <- tcant_cc_tref_1 %>%
  rename(tcant_tref_1 = tcant) %>%
  select(-year)

tcant_cc_tref_2 <-
  read_csv(
    paste0(
      path_model_preprocessing,
      "Cant_CB_annual_all_models/",
      unique(tref$median_year[2]),
      "_",
      params_local$gobm,
      ".csv"
    )
  )

tcant_cc_tref_2 <- tcant_cc_tref_2 %>%
  rename(tcant_tref_2 = tcant) %>%
  select(-year)
cstar_tref_1 <-
  read_csv(
    paste0(
      path_model_preprocessing,
      "Cstar_A_annual_all_models/",
      unique(tref$median_year[1]),
      "_",
      params_local$gobm,
      ".csv"
    )
  )

cstar_tref_1 <- cstar_tref_1 %>%
  select(lon, lat, depth, cstar_no3, cstar_po4) %>% 
  pivot_longer(cstar_no3:cstar_po4,
               names_to = "data_source",
               names_prefix = "cstar_",
               values_to = "cstar_tref_1")

cstar_tref_2 <-
  read_csv(
    paste0(
      path_model_preprocessing,
      "Cstar_A_annual_all_models/",
      unique(tref$median_year[2]),
      "_",
      params_local$gobm,
      ".csv"
    )
  )

cstar_tref_2 <- cstar_tref_2 %>%
  select(lon, lat, depth, cstar_no3, cstar_po4) %>% 
  pivot_longer(cstar_no3:cstar_po4,
               names_to = "data_source",
               names_prefix = "cstar_",
               values_to = "cstar_tref_2")
climatology <-
  read_csv(
    paste0(
      path_model_preprocessing,
      "Climatology_A_2007_all_models/",
      params_local$gobm,
      "_climatology_runA_2007.csv"
    )
  )
mean_gamma_offset_Atl  <-
  read_rds(paste(path_version_data,
                  "mean_gamma_offset_Atl.rds",
                  sep = ""))

mean_gamma_offset_Indo_Pac  <-
  read_rds(paste(path_version_data,
                  "mean_gamma_offset_Indo_Pac.rds",
                  sep = ""))
climatology <- inner_join(climatology, basinmask_AIP)

climatology <- climatology %>%
  mutate(
    gamma = if_else(
      basin_AIP %in% c("Indian", "Pacific"),
      gamma - mean_gamma_offset_Indo_Pac,
      gamma
    ),
    gamma = if_else(
      basin_AIP %in% c("Atlantic"),
      gamma - mean_gamma_offset_Atl,
      gamma
    )
  )

climatology <- climatology %>%
  select(lon, lat, depth, gamma)

3 dcant calculation

dcant_3d <- left_join(tcant_tref_1, tcant_tref_2) %>%
  mutate(dcant = tcant_tref_2 - tcant_tref_1)

rm(tcant_tref_1, tcant_tref_2)

dcant_3d <- dcant_3d %>%
  mutate(dcant_pos = if_else(dcant <= 0, 0, dcant))

dcant_3d <- full_join(dcant_3d, climatology)

dcant_3d <- dcant_3d %>%
  mutate(
    method = "surface",
    method = if_else(
      depth > params_local$depth_mapping,
      "eMLR",
      method
    )
  )

dcant_3d <- m_cut_gamma(dcant_3d, "gamma")

dcant_3d_vc <- dcant_3d %>% 
  mutate(data_source = "mod_truth") %>% 
  select(lon, lat, depth, basin_AIP, data_source, method,
            tcant_tref_1, dcant, dcant_pos,
            gamma, gamma_slab)
dcant_3d <- left_join(tcant_cc_tref_1, tcant_cc_tref_2) %>%
  mutate(dcant = tcant_tref_2 - tcant_tref_1)

rm(tcant_cc_tref_1, tcant_cc_tref_2)

dcant_3d <- dcant_3d %>%
  mutate(dcant_pos = if_else(dcant <= 0, 0, dcant))

dcant_3d <- full_join(dcant_3d, climatology)

dcant_3d <- dcant_3d %>%
  mutate(
    method = "surface",
    method = if_else(
      depth >= params_local$depth_min | gamma >= params_local$gamma_min,
      "eMLR",
      method
    )
  )

dcant_3d <- m_cut_gamma(dcant_3d, "gamma")

dcant_3d_cc <- dcant_3d %>% 
  mutate(data_source = "mod_truth_cc") %>% 
  select(lon, lat, depth, basin_AIP, data_source, method,
            tcant_tref_1, dcant, dcant_pos,
            gamma, gamma_slab)

rm(dcant_3d)
dcant_3d <- bind_rows(
  dcant_3d_cc,
  dcant_3d_vc
)

rm(
  dcant_3d_cc,
  dcant_3d_vc
)
surface_data <- nrow(dcant_3d %>% filter(method == "surface")) > 0
dcant_3d_cstar <- left_join(cstar_tref_1, cstar_tref_2) %>%
  mutate(dcant = cstar_tref_2 - cstar_tref_1)

rm(cstar_tref_1, cstar_tref_2)

dcant_3d_cstar <- dcant_3d_cstar %>%
  mutate(dcant_pos = if_else(dcant <= 0, 0, dcant))

dcant_3d_cstar <- full_join(dcant_3d_cstar, climatology)

dcant_3d_cstar <- dcant_3d_cstar %>%
  mutate(
    method = "surface",
    method = if_else(
      depth > params_local$depth_mapping,
      "eMLR",
      method
    )
  )


dcant_3d_cstar <- inner_join(
  dcant_3d_cstar,
  basinmask_AIP
) 

dcant_3d_cstar <- m_cut_gamma(dcant_3d_cstar, "gamma")


dcant_3d_cstar <- dcant_3d_cstar %>% 
  select(lon, lat, depth, basin_AIP, data_source, method,
            cstar_tref_1, cstar_tref_2, dcant, dcant_pos,
            gamma, gamma_slab)

4 Maps

dcant_3d %>%
  group_split(data_source) %>%
  # head(1) %>%
  map(~ p_map_climatology(
    df = .x,
    var = "dcant",
    subtitle_text = paste("Climate: ", .x$data_source)
  ))
[[1]]

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
3992e41 jens-daniel-mueller 2021-10-27
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
bf149ea jens-daniel-mueller 2021-08-09
cd8e0d5 jens-daniel-mueller 2021-08-06
15773a0 jens-daniel-mueller 2021-08-06
340d731 jens-daniel-mueller 2021-08-06
71546e4 jens-daniel-mueller 2021-08-06
88f7356 jens-daniel-mueller 2021-08-02
127b801 jens-daniel-mueller 2021-07-24
912d90e jens-daniel-mueller 2021-07-23
2477316 jens-daniel-mueller 2021-07-23
8d6c6c2 jens-daniel-mueller 2021-07-09 

[[2]]

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
3992e41 jens-daniel-mueller 2021-10-27
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
bf149ea jens-daniel-mueller 2021-08-09
cd8e0d5 jens-daniel-mueller 2021-08-06
15773a0 jens-daniel-mueller 2021-08-06
340d731 jens-daniel-mueller 2021-08-06
71546e4 jens-daniel-mueller 2021-08-06
88f7356 jens-daniel-mueller 2021-08-02
127b801 jens-daniel-mueller 2021-07-24
912d90e jens-daniel-mueller 2021-07-23
2477316 jens-daniel-mueller 2021-07-23
8d6c6c2 jens-daniel-mueller 2021-07-09 
dcant_3d_cstar %>%
  group_split(data_source) %>%
  # head(1) %>%
  map(~ p_map_climatology(
    df = .x,
    var = "dcant",
    subtitle_text = paste("data_source: ", .x$data_source)
  ))
[[1]]

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
ae253e2 jens-daniel-mueller 2022-05-20
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
3992e41 jens-daniel-mueller 2021-10-27
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
17518ad jens-daniel-mueller 2021-08-09
00fc082 jens-daniel-mueller 2021-08-09
bf149ea jens-daniel-mueller 2021-08-09 

[[2]]

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
ae253e2 jens-daniel-mueller 2022-05-20
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
3992e41 jens-daniel-mueller 2021-10-27
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
17518ad jens-daniel-mueller 2021-08-09
00fc082 jens-daniel-mueller 2021-08-09
bf149ea jens-daniel-mueller 2021-08-09 
dcant_3d %>%
  group_split(data_source) %>%
  # head(1) %>%
  map(~ p_section_climatology_regular(
    df = .x,
    var = "dcant",
    subtitle_text = paste("Climate: ", .x$data_source)
  ))
[[1]]

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
bf149ea jens-daniel-mueller 2021-08-09
cd8e0d5 jens-daniel-mueller 2021-08-06
15773a0 jens-daniel-mueller 2021-08-06
340d731 jens-daniel-mueller 2021-08-06
71546e4 jens-daniel-mueller 2021-08-06
88f7356 jens-daniel-mueller 2021-08-02
127b801 jens-daniel-mueller 2021-07-24
912d90e jens-daniel-mueller 2021-07-23
2477316 jens-daniel-mueller 2021-07-23
8d6c6c2 jens-daniel-mueller 2021-07-09 

[[2]]

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
bf149ea jens-daniel-mueller 2021-08-09
cd8e0d5 jens-daniel-mueller 2021-08-06
15773a0 jens-daniel-mueller 2021-08-06
340d731 jens-daniel-mueller 2021-08-06
71546e4 jens-daniel-mueller 2021-08-06
88f7356 jens-daniel-mueller 2021-08-02
127b801 jens-daniel-mueller 2021-07-24
912d90e jens-daniel-mueller 2021-07-23
2477316 jens-daniel-mueller 2021-07-23
971ce87 jens-daniel-mueller 2021-07-13 
dcant_3d_cstar %>%
  group_split(data_source) %>%
  # head(1) %>%
  map(~ p_section_climatology_regular(
    df = .x,
    var = "dcant",
    subtitle_text = paste("data_source: ", .x$data_source)
  ))
[[1]]

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
ae253e2 jens-daniel-mueller 2022-05-20
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
17518ad jens-daniel-mueller 2021-08-09
00fc082 jens-daniel-mueller 2021-08-09
bf149ea jens-daniel-mueller 2021-08-09 

[[2]]

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
ae253e2 jens-daniel-mueller 2022-05-20
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
17518ad jens-daniel-mueller 2021-08-09
00fc082 jens-daniel-mueller 2021-08-09
bf149ea jens-daniel-mueller 2021-08-09

5 Averaging and integration

5.1 Zonal sections

dcant_zonal <- dcant_3d %>%
  group_by(data_source) %>%
  nest() %>%
  mutate(zonal = map(.x = data, ~m_zonal_mean_sd(.x))) %>%
  select(-data) %>%
  unnest(zonal)

dcant_zonal <- m_cut_gamma(dcant_zonal, "gamma_mean")

dcant_zonal_method <- dcant_3d %>%
  group_by(data_source, method) %>%
  nest() %>%
  mutate(zonal = map(.x = data, ~m_zonal_mean_sd(.x))) %>%
  select(-data) %>%
  unnest(zonal)

dcant_zonal_method <- m_cut_gamma(dcant_zonal_method,
                                   "gamma_mean")

dcant_zonal <- dcant_zonal %>% 
  rename(dcant = dcant_mean,
         dcant_pos = dcant_pos_mean)

dcant_zonal_method <- dcant_zonal_method %>% 
  rename(dcant = dcant_mean,
         dcant_pos = dcant_pos_mean)
dcant_zonal_cstar <- dcant_3d_cstar %>%
  group_by(data_source) %>%
  nest() %>%
  mutate(zonal = map(.x = data, ~m_zonal_mean_sd(.x))) %>%
  select(-data) %>%
  unnest(zonal)

dcant_zonal_cstar <- m_cut_gamma(dcant_zonal_cstar, "gamma_mean")

dcant_zonal_method_cstar <- dcant_3d_cstar %>%
  group_by(data_source, method) %>%
  nest() %>%
  mutate(zonal = map(.x = data, ~m_zonal_mean_sd(.x))) %>%
  select(-data) %>%
  unnest(zonal)

dcant_zonal_method_cstar <- m_cut_gamma(dcant_zonal_method_cstar,
                                   "gamma_mean")

dcant_zonal_cstar <- dcant_zonal_cstar %>% 
  rename(dcant = dcant_mean,
         dcant_pos = dcant_pos_mean)

dcant_zonal_method_cstar <- dcant_zonal_method_cstar %>% 
  rename(dcant = dcant_mean,
         dcant_pos = dcant_pos_mean)

5.2 Profiles

For each basin, the mean (+ min and max) dcant profile is calculated, again for all vs positive only values. Likewise, sd is calculated for the averaging of the mean basin fields.

dcant_profile <- dcant_3d %>%
  mutate(area = earth_surf(lat, lon),
         dcant_scaled = dcant * area) %>% 
  group_by(data_source, basin_AIP, depth) %>% 
  summarise(dcant_sd = sqrt(
              Hmisc::wtd.var(dcant, area, na.rm = TRUE)),
            dcant = sum(dcant_scaled) / sum(area)) %>% 
  ungroup()
dcant_profile_cstar <- dcant_3d_cstar %>%
  mutate(area = earth_surf(lat, lon),
         dcant_scaled = dcant * area) %>% 
  group_by(data_source, basin_AIP, depth) %>% 
  summarise(dcant_sd = sqrt(
              Hmisc::wtd.var(dcant, area, na.rm = TRUE)),
            dcant = sum(dcant_scaled) / sum(area)) %>% 
  ungroup()

5.3 Inventories

To calculate dcant column inventories, we:

  1. Convert Cant concentrations to volumetric units
  2. Multiply layer thickness with volumetric Cant concentration to get a layer inventory
  3. For each horizontal grid cell and era, sum cant layer inventories for different inventory depths (100, 500, 1000, 3000, 10^{4} m)

Step 2 is performed separately for all Cant and positive Cant values only.

5.3.1 Full water column

dcant_inv <- dcant_3d %>%
  group_by(data_source) %>%
  nest() %>%
  mutate(inv = map(.x = data, ~m_dcant_inv(.x))) %>%
  select(-data) %>%
  unnest(inv)

p_map_cant_inv(df = dcant_inv,
               var = "dcant",
               subtitle_text = "for predefined integration depths") +
  facet_grid(inv_depth ~ data_source)

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
3992e41 jens-daniel-mueller 2021-10-27
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
cd8e0d5 jens-daniel-mueller 2021-08-06
15773a0 jens-daniel-mueller 2021-08-06
340d731 jens-daniel-mueller 2021-08-06
71546e4 jens-daniel-mueller 2021-08-06
88f7356 jens-daniel-mueller 2021-08-02
127b801 jens-daniel-mueller 2021-07-24
912d90e jens-daniel-mueller 2021-07-23
2477316 jens-daniel-mueller 2021-07-23
f3c0d7a jens-daniel-mueller 2021-07-22
971ce87 jens-daniel-mueller 2021-07-13
8d6c6c2 jens-daniel-mueller 2021-07-09 
if (surface_data == FALSE){
  dcant_inv <- dcant_inv %>% 
    mutate(method = "total")
}
dcant_inv_cstar <- dcant_3d_cstar %>%
  group_by(data_source) %>%
  nest() %>%
  mutate(inv = map(.x = data, ~m_dcant_inv(.x))) %>%
  select(-data) %>%
  unnest(inv)

p_map_cant_inv(df = dcant_inv_cstar,
               var = "dcant",
               subtitle_text = "for predefined integration depths") +
  facet_grid(inv_depth ~ data_source)

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
ae253e2 jens-daniel-mueller 2022-05-20
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
3992e41 jens-daniel-mueller 2021-10-27
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
17518ad jens-daniel-mueller 2021-08-09
00fc082 jens-daniel-mueller 2021-08-09 
if (surface_data == FALSE){
  dcant_inv_cstar <- dcant_inv_cstar %>% 
    mutate(method = "total")
}

5.3.2 Surface layer

dcant_inv_surface <- dcant_3d %>%
  filter(method == "surface") %>% 
  group_by(data_source) %>%
  nest() %>%
  mutate(inv = map(.x = data, ~m_dcant_inv(.x))) %>%
  select(-data) %>%
  unnest(inv)

p_map_cant_inv(
  df = dcant_inv_surface %>%
    filter(inv_depth < 1000),
  var = "dcant_pos",
  subtitle_text = "for predefined integration depths",
  breaks = c(-Inf, seq(0, 4, 0.5), Inf)
) +
  facet_grid(inv_depth ~ data_source)
dcant_inv_surface_cstar <- dcant_3d_cstar %>%
  filter(method == "surface") %>% 
  group_by(data_source) %>%
  nest() %>%
  mutate(inv = map(.x = data, ~m_dcant_inv(.x))) %>%
  select(-data) %>%
  unnest(inv)

p_map_cant_inv(
  df = dcant_inv_surface_cstar %>%
    filter(inv_depth < 1000),
  var = "dcant_pos",
  subtitle_text = "for predefined integration depths",
  breaks = c(-Inf, seq(0, 4, 0.5), Inf)
) +
  facet_grid(inv_depth ~ data_source)

5.3.3 eMLR only

dcant_inv <- full_join(
  dcant_inv %>% rename(dcant_total = dcant,
                       dcant_pos_total = dcant_pos),
  dcant_inv_surface %>% rename(dcant_surface = dcant,
                               dcant_pos_surface = dcant_pos)
)

dcant_inv <- dcant_inv %>%
  mutate(dcant_eMLR = dcant_total -
           replace(dcant_surface, is.na(dcant_surface), 0),
         dcant_pos_eMLR = dcant_pos_total -
           replace(dcant_pos_surface, is.na(dcant_pos_surface), 0))

dcant_inv_all <- dcant_inv %>% 
  select(-starts_with("dcant_pos")) %>% 
  pivot_longer(starts_with("dcant_"),
               names_to = "method",
               names_prefix = "dcant_",
               values_to = "dcant")

dcant_inv_pos <- dcant_inv %>% 
  select(data_source, lon, lat, basin_AIP, inv_depth,
         starts_with("dcant_pos_")) %>% 
  pivot_longer(starts_with("dcant_pos_"),
               names_to = "method",
               names_prefix = "dcant_pos_",
               values_to = "dcant_pos")

dcant_inv <- full_join(
  dcant_inv_all,
  dcant_inv_pos
)

rm(dcant_inv_all, dcant_inv_pos, dcant_inv_surface)

dcant_inv %>%
  group_by(inv_depth) %>%
  group_split() %>% 
  # tail(1) %>%
  map(
    ~ p_map_cant_inv(df = .x,
                     var = "dcant",
                     subtitle_text = paste("Integration depth",
                                           unique(.x$inv_depth))) +
      facet_grid(method ~ data_source)
  )
dcant_inv_cstar <- full_join(
  dcant_inv_cstar %>% rename(dcant_total = dcant,
                       dcant_pos_total = dcant_pos),
  dcant_inv_surface_cstar %>% rename(dcant_surface = dcant,
                               dcant_pos_surface = dcant_pos)
)

dcant_inv_cstar <- dcant_inv_cstar %>%
  mutate(dcant_eMLR = dcant_total -
           replace(dcant_surface, is.na(dcant_surface), 0),
         dcant_pos_eMLR = dcant_pos_total -
           replace(dcant_pos_surface, is.na(dcant_pos_surface), 0))

dcant_inv_all_cstar <- dcant_inv_cstar %>% 
  select(-starts_with("dcant_pos")) %>% 
  pivot_longer(starts_with("dcant_"),
               names_to = "method",
               names_prefix = "dcant_",
               values_to = "dcant")

dcant_inv_pos_cstar <- dcant_inv_cstar %>% 
  select(data_source, lon, lat, basin_AIP, inv_depth,
         starts_with("dcant_pos_")) %>% 
  pivot_longer(starts_with("dcant_pos_"),
               names_to = "method",
               names_prefix = "dcant_pos_",
               values_to = "dcant_pos")

dcant_inv_cstar <- full_join(
  dcant_inv_all_cstar,
  dcant_inv_pos_cstar
)

rm(dcant_inv_all_cstar, dcant_inv_pos_cstar, dcant_inv_surface_cstar)

dcant_inv_cstar %>%
  group_by(inv_depth) %>%
  group_split() %>% 
  # tail(1) %>%
  map(
    ~ p_map_cant_inv(df = .x,
                     var = "dcant",
                     subtitle_text = paste("Integration depth",
                                           unique(.x$inv_depth))) +
      facet_grid(method ~ data_source)
  )

5.4 Budgets

Global dcant budgets were estimated in units of Pg C. Please note that here we added dcant (all vs postitive only) values and do not apply additional corrections for areas not covered.

dcant_budget_global <- m_dcant_budget(dcant_inv)

dcant_budget_global %>%
  filter(inv_depth == params_global$inventory_depth_standard,
         method == "total") %>%
  ggplot(aes(estimate, value)) +
  scale_fill_brewer(palette = "Dark2") +
  geom_col() +
  facet_grid(~data_source)

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
3992e41 jens-daniel-mueller 2021-10-27
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
cd8e0d5 jens-daniel-mueller 2021-08-06
15773a0 jens-daniel-mueller 2021-08-06
340d731 jens-daniel-mueller 2021-08-06
71546e4 jens-daniel-mueller 2021-08-06
88f7356 jens-daniel-mueller 2021-08-02
127b801 jens-daniel-mueller 2021-07-24
912d90e jens-daniel-mueller 2021-07-23
2477316 jens-daniel-mueller 2021-07-23
f3c0d7a jens-daniel-mueller 2021-07-22
971ce87 jens-daniel-mueller 2021-07-13 
dcant_budget_global_cstar <- m_dcant_budget(dcant_inv_cstar)

dcant_budget_global_cstar %>%
  filter(inv_depth == params_global$inventory_depth_standard,
         method == "total") %>%
  ggplot(aes(estimate, value)) +
  scale_fill_brewer(palette = "Dark2") +
  geom_col() +
  facet_grid(~data_source)

Version Author Date
a28c3f7 jens-daniel-mueller 2022-06-16
0c2ca93 jens-daniel-mueller 2022-06-15
fa647ea jens-daniel-mueller 2022-05-25
b7ca0f3 jens-daniel-mueller 2022-05-25
ae253e2 jens-daniel-mueller 2022-05-20
745619a jens-daniel-mueller 2022-04-11
1ba3eba jens-daniel-mueller 2022-04-07
707b5ac jens-daniel-mueller 2022-03-24
6c38fc4 jens-daniel-mueller 2022-03-14
23582a4 jens-daniel-mueller 2022-01-23
dfed6a1 jens-daniel-mueller 2022-01-05
f39db85 jens-daniel-mueller 2022-01-04
4fa937d jens-daniel-mueller 2022-01-03
2fe7f8e jens-daniel-mueller 2021-12-08
a768c5d jens-daniel-mueller 2021-12-07
bc1edbd jens-daniel-mueller 2021-12-07
6cfccf7 jens-daniel-mueller 2021-12-06
2ca1313 jens-daniel-mueller 2021-12-05
6a78608 jens-daniel-mueller 2021-12-02
3992e41 jens-daniel-mueller 2021-10-27
bfe90e6 jens-daniel-mueller 2021-10-21
78a956e jens-daniel-mueller 2021-10-21
0bd4ea2 jens-daniel-mueller 2021-10-07
6969c18 jens-daniel-mueller 2021-10-07
06afaca jens-daniel-mueller 2021-09-23
c0bbbe4 jens-daniel-mueller 2021-09-22
9eac969 jens-daniel-mueller 2021-08-30
3a584b7 jens-daniel-mueller 2021-08-30
deb425c jens-daniel-mueller 2021-08-24
27c99b8 jens-daniel-mueller 2021-08-19
a03f2f0 jens-daniel-mueller 2021-08-18
17518ad jens-daniel-mueller 2021-08-09
00fc082 jens-daniel-mueller 2021-08-09 
dcant_budget_global %>%
  filter(inv_depth == params_global$inventory_depth_standard,
         method %in% c("surface", "eMLR")) %>%
  ggplot(aes(estimate, value, fill=method)) +
  scale_fill_brewer(palette = "Dark2") +
  geom_col() +
  facet_grid(.~data_source)
dcant_budget_global_cstar %>%
  filter(inv_depth == params_global$inventory_depth_standard,
         method %in% c("surface", "eMLR")) %>%
  ggplot(aes(estimate, value, fill=method)) +
  scale_fill_brewer(palette = "Dark2") +
  geom_col() +
  facet_grid(.~data_source)
dcant_budget_basin_AIP <- dcant_inv %>% 
  group_by(basin_AIP) %>%
  nest() %>% 
  mutate(budget = map(.x = data, ~m_dcant_budget(.x))) %>% 
  select(-data) %>%
  unnest(budget)
dcant_budget_basin_AIP_cstar <- dcant_inv_cstar %>% 
  group_by(basin_AIP) %>%
  nest() %>% 
  mutate(budget = map(.x = data, ~m_dcant_budget(.x))) %>% 
  select(-data) %>%
  unnest(budget)
dcant_budget_basin_AIP %>%
  filter(inv_depth == params_global$inventory_depth_standard,
         method %in% c("surface", "eMLR")) %>%
  ggplot(aes(basin_AIP, value, fill=method)) +
  scale_fill_brewer(palette = "Dark2") +
  geom_col() +
  facet_grid(estimate~data_source)
dcant_budget_basin_AIP_cstar %>%
  filter(inv_depth == params_global$inventory_depth_standard,
         method %in% c("surface", "eMLR")) %>%
  ggplot(aes(basin_AIP, value, fill=method)) +
  scale_fill_brewer(palette = "Dark2") +
  geom_col() +
  facet_grid(estimate~data_source)
dcant_budget_basin_MLR <-
  full_join(dcant_inv, basinmask) %>%
  group_by(basin, MLR_basins) %>%
  nest() %>%
  mutate(budget = map(.x = data, ~ m_dcant_budget(.x))) %>%
  select(-data) %>%
  unnest(budget)
dcant_budget_basin_MLR_cstar <-
  full_join(dcant_inv_cstar, basinmask) %>%
  group_by(basin, MLR_basins) %>%
  nest() %>%
  mutate(budget = map(.x = data, ~ m_dcant_budget(.x))) %>%
  select(-data) %>%
  unnest(budget)
dcant_budget_basin_MLR %>%
  filter(inv_depth == params_global$inventory_depth_standard,
         method %in% c("surface", "eMLR")) %>%
  group_by(MLR_basins) %>%
  group_split() %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(basin, value, fill = method)) +
      scale_fill_brewer(palette = "Dark2") +
      geom_col() +
      facet_grid(estimate ~ data_source) +
      labs(title = paste("MLR_basins:", unique(.x$MLR_basins)))
  )
dcant_budget_basin_MLR_cstar %>%
  filter(inv_depth == params_global$inventory_depth_standard,
         method %in% c("surface", "eMLR")) %>%
  group_by(MLR_basins) %>%
  group_split() %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(basin, value, fill = method)) +
      scale_fill_brewer(palette = "Dark2") +
      geom_col() +
      facet_grid(estimate ~ data_source) +
      labs(title = paste("MLR_basins:", unique(.x$MLR_basins)))
  )
dcant_budget_lat_grid <- 
  dcant_inv %>% 
  m_grid_horizontal_coarse() %>%
  group_by(lat_grid, basin_AIP) %>% 
  nest() %>%
  mutate(budget = map(.x = data, ~ m_dcant_budget(.x))) %>%
  select(-data) %>%
  unnest(budget)
dcant_budget_lat_grid_cstar <- 
  dcant_inv_cstar %>% 
  m_grid_horizontal_coarse() %>%
  group_by(lat_grid, basin_AIP) %>% 
  nest() %>%
  mutate(budget = map(.x = data, ~ m_dcant_budget(.x))) %>%
  select(-data) %>%
  unnest(budget)
dcant_budget_lat_grid %>%
  filter(inv_depth == params_global$inventory_depth_standard,
         method %in% c("surface", "eMLR")) %>%
  group_by(basin_AIP) %>%
  group_split() %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(lat_grid, value, fill = method)) +
      scale_fill_brewer(palette = "Dark2") +
      geom_col() +
      coord_flip() +
      facet_grid(estimate ~ data_source) +
      labs(title = paste("MLR_basins:", unique(.x$basin_AIP)))
  )
dcant_budget_lat_grid_cstar %>%
  filter(inv_depth == params_global$inventory_depth_standard,
         method %in% c("surface", "eMLR")) %>%
  group_by(basin_AIP) %>%
  group_split() %>%
  # head(1) %>%
  map(
    ~ ggplot(data = .x,
             aes(lat_grid, value, fill = method)) +
      scale_fill_brewer(palette = "Dark2") +
      geom_col() +
      coord_flip() +
      facet_grid(estimate ~ data_source) +
      labs(title = paste("MLR_basins:", unique(.x$basin_AIP)))
  )

6 Write csv

dcant_3d <- dcant_3d %>%
  select(-c(tcant_tref_1))

dcant_3d %>%
  filter(data_source == "mod_truth") %>%
  write_csv(paste(path_version_data,
                  "dcant_3d_mod_truth.csv", sep = ""))

dcant_3d %>%
  filter(data_source == "mod_truth_cc") %>%
  write_csv(paste(path_version_data,
                  "dcant_3d_mod_truth_cc.csv", sep = ""))


dcant_zonal %>%
  filter(data_source == "mod_truth") %>%
  write_csv(paste(path_version_data,
                  "dcant_zonal_mod_truth.csv", sep = ""))

dcant_profile %>%
  filter(data_source == "mod_truth") %>%
  write_csv(paste(path_version_data,
                  "dcant_profile_mod_truth.csv", sep = ""))

dcant_zonal_method %>%
  filter(data_source == "mod_truth") %>%
  write_csv(paste(path_version_data,
                  "dcant_zonal_mod_truth_method.csv", sep = ""))

dcant_zonal %>%
  filter(data_source == "mod_truth_cc") %>%
  write_csv(paste(path_version_data,
                  "dcant_zonal_mod_truth_cc.csv", sep = ""))

dcant_profile %>%
  filter(data_source == "mod_truth_cc") %>%
  write_csv(paste(path_version_data,
                  "dcant_profile_mod_truth_cc.csv", sep = ""))

dcant_zonal_method %>%
  filter(data_source == "mod_truth_cc") %>%
  write_csv(paste(path_version_data,
                  "dcant_zonal_mod_truth_cc_method.csv", sep = ""))


dcant_inv %>%
  filter(data_source == "mod_truth",
         method == "total") %>%
  write_csv(paste(path_version_data,
                  "dcant_inv_mod_truth.csv", sep = ""))

dcant_inv %>%
  filter(data_source == "mod_truth_cc",
         method == "total") %>%
  write_csv(paste(path_version_data,
                  "dcant_inv_mod_truth_cc.csv", sep = ""))

dcant_inv %>%
  filter(data_source == "mod_truth",
         method != "total") %>%
  write_csv(paste(path_version_data,
                  "dcant_inv_mod_truth_method.csv", sep = ""))

dcant_inv %>%
  filter(data_source == "mod_truth_cc",
         method != "total") %>%
  write_csv(paste(path_version_data,
                  "dcant_inv_mod_truth_cc_method.csv", sep = ""))



dcant_budget_global %>%
  filter(data_source == "mod_truth") %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_global_mod_truth.csv", sep = ""))

dcant_budget_global %>%
  filter(data_source == "mod_truth_cc") %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_global_mod_truth_cc.csv", sep = ""))

dcant_budget_basin_AIP %>%
  filter(data_source == "mod_truth") %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_basin_AIP_mod_truth.csv", sep = ""))

dcant_budget_basin_AIP %>%
  filter(data_source == "mod_truth_cc") %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_basin_AIP_mod_truth_cc.csv", sep = ""))

dcant_budget_basin_MLR %>%
  filter(data_source == "mod_truth") %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_basin_MLR_mod_truth.csv", sep = ""))

dcant_budget_basin_MLR %>%
  filter(data_source == "mod_truth_cc") %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_basin_MLR_mod_truth_cc.csv", sep = ""))

dcant_budget_lat_grid %>%
  filter(data_source == "mod_truth") %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_lat_grid_mod_truth.csv", sep = ""))

dcant_budget_lat_grid %>%
  filter(data_source == "mod_truth_cc") %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_lat_grid_mod_truth_cc.csv", sep = ""))
dcant_3d_cstar %>%
  write_csv(paste(path_version_data,
                  "dcant_3d_cstar.csv", sep = ""))

dcant_zonal_cstar %>%
  write_csv(paste(path_version_data,
                  "dcant_zonal_cstar.csv", sep = ""))

dcant_profile_cstar %>%
  write_csv(paste(path_version_data,
                  "dcant_profile_mod_truth_cstar.csv", sep = ""))

dcant_zonal_method_cstar %>% 
  write_csv(paste(path_version_data,
                  "dcant_zonal_method_cstar.csv", sep = ""))

dcant_inv_cstar %>%
  filter(method == "total") %>%
  write_csv(paste(path_version_data,
                  "dcant_inv_cstar.csv", sep = ""))

dcant_inv_cstar %>%
  filter(method != "total") %>%
  write_csv(paste(path_version_data,
                  "dcant_inv_method_cstar.csv", sep = ""))

dcant_budget_global_cstar %>%
  filter(data_source == "mod_truth") %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_global_cstar.csv", sep = ""))


dcant_budget_basin_AIP_cstar %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_basin_AIP_cstar.csv", sep = ""))


dcant_budget_basin_MLR_cstar %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_basin_MLR_cstar.csv", sep = ""))


dcant_budget_lat_grid_cstar %>%
  write_csv(paste(path_version_data,
                  "dcant_budget_lat_grid_cstar.csv", sep = ""))

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] colorspace_2.0-2 marelac_2.1.10   shape_1.4.6      ggforce_0.3.3   
 [5] metR_0.11.0      scico_1.3.0      patchwork_1.1.1  collapse_1.7.0  
 [9] forcats_0.5.1    stringr_1.4.0    dplyr_1.0.7      purrr_0.3.4     
[13] readr_2.1.1      tidyr_1.1.4      tibble_3.1.6     ggplot2_3.3.5   
[17] tidyverse_1.3.1  workflowr_1.7.0 

loaded via a namespace (and not attached):
  [1] ellipsis_0.3.2      rprojroot_2.0.2     htmlTable_2.4.0    
  [4] base64enc_0.1-3     fs_1.5.2            rstudioapi_0.13    
  [7] farver_2.1.0        bit64_4.0.5         fansi_1.0.2        
 [10] lubridate_1.8.0     xml2_1.3.3          splines_4.1.2      
 [13] knitr_1.37          polyclip_1.10-0     Formula_1.2-4      
 [16] jsonlite_1.7.3      gsw_1.0-6           broom_0.7.11       
 [19] cluster_2.1.2       dbplyr_2.1.1        png_0.1-7          
 [22] compiler_4.1.2      httr_1.4.2          backports_1.4.1    
 [25] assertthat_0.2.1    Matrix_1.4-0        fastmap_1.1.0      
 [28] cli_3.1.1           later_1.3.0         tweenr_1.0.2       
 [31] htmltools_0.5.2     tools_4.1.2         gtable_0.3.0       
 [34] glue_1.6.0          Rcpp_1.0.8          cellranger_1.1.0   
 [37] jquerylib_0.1.4     vctrs_0.3.8         xfun_0.29          
 [40] ps_1.6.0            rvest_1.0.2         lifecycle_1.0.1    
 [43] oce_1.5-0           getPass_0.2-2       MASS_7.3-55        
 [46] scales_1.1.1        vroom_1.5.7         hms_1.1.1          
 [49] promises_1.2.0.1    parallel_4.1.2      RColorBrewer_1.1-2 
 [52] yaml_2.2.1          gridExtra_2.3       sass_0.4.0         
 [55] rpart_4.1-15        latticeExtra_0.6-29 stringi_1.7.6      
 [58] highr_0.9           checkmate_2.0.0     rlang_1.0.2        
 [61] pkgconfig_2.0.3     evaluate_0.14       lattice_0.20-45    
 [64] SolveSAPHE_2.1.0    htmlwidgets_1.5.4   labeling_0.4.2     
 [67] bit_4.0.4           processx_3.5.2      tidyselect_1.1.1   
 [70] here_1.0.1          seacarb_3.3.0       magrittr_2.0.1     
 [73] R6_2.5.1            generics_0.1.1      Hmisc_4.6-0        
 [76] DBI_1.1.2           pillar_1.6.4        haven_2.4.3        
 [79] whisker_0.4         foreign_0.8-82      withr_2.4.3        
 [82] survival_3.2-13     nnet_7.3-17         modelr_0.1.8       
 [85] crayon_1.4.2        utf8_1.2.2          tzdb_0.2.0         
 [88] rmarkdown_2.11      jpeg_0.1-9          grid_4.1.2         
 [91] readxl_1.3.1        isoband_0.2.5       data.table_1.14.2  
 [94] callr_3.7.0         git2r_0.29.0        reprex_2.0.1       
 [97] digest_0.6.29       httpuv_1.6.5        munsell_0.5.0      
[100] viridisLite_0.4.0   bslib_0.3.1