Budgets

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Last updated: 2021-11-01

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Knit directory: emlr_obs_analysis/

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---

1 Bias thresholds

global_bias_rel_max <- 10
regional_bias_rel_max <- 20

2 Basins

MLR_basins_in <- c("1", "2", "AIP", "SO_2", "5", "SO_AIP", "SO")

3 Read files

# identify required version IDs

Version_IDs_1 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
                            pattern = "v_18")

Version_IDs_2 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
                            pattern = "v_28")

# Version_IDs_3 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
#                             pattern = "v_30")

Version_IDs <- c(Version_IDs_1, Version_IDs_2)
# Version_IDs <- c(Version_IDs_1, Version_IDs_2, Version_IDs_3)
# rm(Version_IDs_1, Version_IDs_2)
# rm(Version_IDs_1, Version_IDs_2, Version_IDs_3)

3.1 Global

for (i_Version_IDs in Version_IDs) {
  # i_Version_IDs <- Version_IDs[1]
  
  print(i_Version_IDs)
  
  path_version_data     <-
    paste(path_observations,
          i_Version_IDs,
          "/data/",
          sep = "")
  
  # load and join data files
  
  dcant_budget_global <-
    read_csv(paste(path_version_data,
                   "dcant_budget_global.csv",
                   sep = ""))
  
  dcant_budget_global_mod_truth <-
    read_csv(paste(
      path_version_data,
      "dcant_budget_global_mod_truth.csv",
      sep = ""
    ))
  
  dcant_budget_global_bias <-
    read_csv(paste(path_version_data,
                   "dcant_budget_global_bias.csv",
                   sep = ""))
  
  dcant_budget_global <- bind_rows(dcant_budget_global,
                                      dcant_budget_global_mod_truth)
  
  dcant_budget_global <- dcant_budget_global %>%
    mutate(Version_ID = i_Version_IDs)
  
  dcant_budget_global_bias <- dcant_budget_global_bias %>%
    mutate(Version_ID = i_Version_IDs)

  params_local <-
    read_rds(paste(path_version_data,
                   "params_local.rds",
                   sep = ""))
  
  params_local <- bind_cols(
    Version_ID = i_Version_IDs,
    MLR_basins = params_local$MLR_basins,
    tref1 = params_local$tref1,
    tref2 = params_local$tref2,
    gap_filling = params_local$gap_filling,
    rarefication = params_local$rarefication,
    rarefication_threshold = params_local$rarefication_threshold,
    MLR_predictors = str_c(params_local$MLR_predictors, collapse = "+"),
    vif_max = params_local$vif_max
  )
  
  tref <- read_csv(paste(path_version_data,
                         "tref.csv",
                         sep = ""))
  
  params_local <- params_local %>%
    mutate(
      median_year_1 = sort(tref$median_year)[1],
      median_year_2 = sort(tref$median_year)[2],
      duration = median_year_2 - median_year_1,
      period = paste(median_year_1, "-", median_year_2)
    )
  
  if (exists("dcant_budget_global_all")) {
    dcant_budget_global_all <-
      bind_rows(dcant_budget_global_all, dcant_budget_global)
  }
  
  if (!exists("dcant_budget_global_all")) {
    dcant_budget_global_all <- dcant_budget_global
  }
  
  if (exists("dcant_budget_global_bias_all")) {
    dcant_budget_global_bias_all <-
      bind_rows(dcant_budget_global_bias_all,
                dcant_budget_global_bias)
  }

  if (!exists("dcant_budget_global_bias_all")) {
    dcant_budget_global_bias_all <- dcant_budget_global_bias
  }
  
  if (exists("params_local_all")) {
    params_local_all <- bind_rows(params_local_all, params_local)
  }
  
  if (!exists("params_local_all")) {
    params_local_all <- params_local
  }
  
  
}

[1] "v_1801"
[1] "v_1802"
[1] "v_1803"
[1] "v_1804"
[1] "v_1805"
[1] "v_1806"
[1] "v_2801"
[1] "v_2802"
[1] "v_2803"
[1] "v_2804"
[1] "v_2805"
[1] "v_2806"

params_local_all <-
  params_local_all %>%
  mutate(period = factor(period, c("1994 - 2004", "2004 - 2014", "1994 - 2014")))

rm(
  dcant_budget_global,
  dcant_budget_global_bias,
  dcant_budget_global_mod_truth,
  params_local,
  tref
)

dcant_budget_global_all <- full_join(dcant_budget_global_all,
                                     params_local_all)

dcant_budget_global_bias_all <-
  full_join(dcant_budget_global_bias_all,
            params_local_all)

dcant_budget_global_all <- dcant_budget_global_all %>%
  filter(estimate == "dcant", 
         method == "total") %>% 
  select(-c(estimate, method)) %>% 
  rename(dcant = value)

dcant_budget_global_all_depth <- dcant_budget_global_all

dcant_budget_global_all <- dcant_budget_global_all %>%
  filter(inv_depth == params_global$inventory_depth_standard)

dcant_budget_global_bias_all <- dcant_budget_global_bias_all %>%
  filter(estimate == "dcant") %>%
  select(-c(estimate))

dcant_budget_global_bias_all_depth <- dcant_budget_global_bias_all

dcant_budget_global_bias_all <- dcant_budget_global_bias_all %>%
  filter(inv_depth == params_global$inventory_depth_standard)

dcant_budget_global_all <- dcant_budget_global_all %>% 
  filter(MLR_basins %in% MLR_basins_in)

dcant_budget_global_bias_all <- dcant_budget_global_bias_all  %>% 
  filter(MLR_basins %in% MLR_basins_in)

3.2 Regional

# Version_IDs <- Version_IDs[1:length(Version_IDs)-1]

for (i_Version_IDs in Version_IDs) {
  # i_Version_IDs <- Version_IDs[1]
  
  print(i_Version_IDs)
  
  path_version_data     <-
    paste(path_observations,
          i_Version_IDs,
          "/data/",
          sep = "")
  
  # load and join data files
  
  dcant_budget_basin_AIP <-
    read_csv(paste(path_version_data,
                   "dcant_budget_basin_AIP.csv",
                   sep = ""))
  
  dcant_budget_basin_AIP_mod_truth <-
    read_csv(paste(
      path_version_data,
      "dcant_budget_basin_AIP_mod_truth.csv",
      sep = ""
    ))
  
    
  dcant_budget_basin_AIP <- bind_rows(dcant_budget_basin_AIP,
                                      dcant_budget_basin_AIP_mod_truth)
  
  dcant_budget_basin_AIP_bias <-
    read_csv(paste(path_version_data,
                   "dcant_budget_basin_AIP_bias.csv",
                   sep = ""))
  
  dcant_slab_budget_bias <-
    read_csv(paste0(path_version_data,
                    "dcant_slab_budget_bias.csv"))

  dcant_slab_budget <-
    read_csv(paste0(path_version_data,
                    "dcant_slab_budget.csv"))

  dcant_budget_basin_AIP <- dcant_budget_basin_AIP %>%
    mutate(Version_ID = i_Version_IDs)
  
  dcant_budget_basin_AIP_bias <- dcant_budget_basin_AIP_bias %>%
    mutate(Version_ID = i_Version_IDs)
  
  dcant_slab_budget <- dcant_slab_budget %>%
    mutate(Version_ID = i_Version_IDs)
  
  dcant_slab_budget_bias <- dcant_slab_budget_bias %>%
    mutate(Version_ID = i_Version_IDs)
  
  if (exists("dcant_budget_basin_AIP_all")) {
    dcant_budget_basin_AIP_all <-
      bind_rows(dcant_budget_basin_AIP_all, dcant_budget_basin_AIP)
  }
  
  if (!exists("dcant_budget_basin_AIP_all")) {
    dcant_budget_basin_AIP_all <- dcant_budget_basin_AIP
  }
  
  if (exists("dcant_budget_basin_AIP_bias_all")) {
    dcant_budget_basin_AIP_bias_all <-
      bind_rows(dcant_budget_basin_AIP_bias_all,
                dcant_budget_basin_AIP_bias)
  }
  
  if (!exists("dcant_budget_basin_AIP_bias_all")) {
    dcant_budget_basin_AIP_bias_all <- dcant_budget_basin_AIP_bias
  }
  
  if (exists("dcant_slab_budget_all")) {
    dcant_slab_budget_all <-
      bind_rows(dcant_slab_budget_all, dcant_slab_budget)
  }
  
  if (!exists("dcant_slab_budget_all")) {
    dcant_slab_budget_all <- dcant_slab_budget
  }
  
  if (exists("dcant_slab_budget_bias_all")) {
    dcant_slab_budget_bias_all <-
      bind_rows(dcant_slab_budget_bias_all,
                dcant_slab_budget_bias)
  }
  
  if (!exists("dcant_slab_budget_bias_all")) {
    dcant_slab_budget_bias_all <- dcant_slab_budget_bias
  }
  
}

[1] "v_1801"
[1] "v_1802"
[1] "v_1803"
[1] "v_1804"
[1] "v_1805"
[1] "v_1806"
[1] "v_2801"
[1] "v_2802"
[1] "v_2803"
[1] "v_2804"
[1] "v_2805"
[1] "v_2806"

rm(
  dcant_budget_basin_AIP,
  dcant_budget_basin_AIP_bias,
  dcant_budget_basin_AIP_mod_truth,
  dcant_slab_budget,
  dcant_slab_budget_bias
)

dcant_budget_basin_AIP_all <- full_join(dcant_budget_basin_AIP_all,
                                        params_local_all)

dcant_budget_basin_AIP_bias_all <-
  full_join(dcant_budget_basin_AIP_bias_all,
            params_local_all)

dcant_slab_budget_all <- full_join(dcant_slab_budget_all,
                                        params_local_all)

dcant_slab_budget_bias_all <-
  full_join(dcant_slab_budget_bias_all,
            params_local_all)

dcant_budget_basin_AIP_all <- dcant_budget_basin_AIP_all %>%
  filter(estimate == "dcant", 
         method == "total") %>% 
  select(-c(estimate, method)) %>% 
  rename(dcant = value)

dcant_budget_basin_AIP_all_depth <- dcant_budget_basin_AIP_all

dcant_budget_basin_AIP_all <- dcant_budget_basin_AIP_all %>%
  filter(inv_depth == params_global$inventory_depth_standard)

dcant_budget_basin_AIP_bias_all <- dcant_budget_basin_AIP_bias_all %>%
  filter(estimate == "dcant") %>% 
  select(-c(estimate))

dcant_budget_basin_AIP_bias_all_depth <- dcant_budget_basin_AIP_bias_all

dcant_budget_basin_AIP_bias_all <- dcant_budget_basin_AIP_bias_all %>%
  filter(inv_depth == params_global$inventory_depth_standard)

dcant_budget_basin_AIP_all <- dcant_budget_basin_AIP_all %>% 
  filter(MLR_basins %in% MLR_basins_in)

dcant_budget_basin_AIP_bias_all <- dcant_budget_basin_AIP_bias_all  %>% 
  filter(MLR_basins %in% MLR_basins_in)

dcant_slab_budget_all <- dcant_slab_budget_all %>% 
  filter(MLR_basins %in% MLR_basins_in)

dcant_slab_budget_bias_all <- dcant_slab_budget_bias_all  %>% 
  filter(MLR_basins %in% MLR_basins_in)

3.3 Steady state

for (i_Version_IDs in Version_IDs) {
  # i_Version_IDs <- Version_IDs[1]
  
  print(i_Version_IDs)
  
  path_version_data     <-
    paste(path_observations,
          i_Version_IDs,
          "/data/",
          sep = "")
  
  # load and join data files
  
  dcant_obs_budget <-
    read_csv(paste0(path_version_data,
                    "anom_dcant_obs_budget.csv"))
  
  dcant_obs_budget <- dcant_obs_budget %>%
    mutate(Version_ID = i_Version_IDs)
  
  if (exists("dcant_obs_budget_all")) {
    dcant_obs_budget_all <-
      bind_rows(dcant_obs_budget_all, dcant_obs_budget)
  }
  
  if (!exists("dcant_obs_budget_all")) {
    dcant_obs_budget_all <- dcant_obs_budget
  }
  
}

[1] "v_1801"
[1] "v_1802"
[1] "v_1803"
[1] "v_1804"
[1] "v_1805"
[1] "v_1806"
[1] "v_2801"
[1] "v_2802"
[1] "v_2803"
[1] "v_2804"
[1] "v_2805"
[1] "v_2806"

rm(dcant_obs_budget)

dcant_obs_budget_all <- full_join(dcant_obs_budget_all,
                             params_local_all)

4 Global

4.1 Individual cases

4.1.1 Absoulte values

legend_title = expression(atop(Delta * C[ant],
                               (mu * mol ~ kg ^ {
                                 -1
                               })))

dcant_budget_global_all %>%
  ggplot(aes(period, dcant, col = MLR_basins)) +
  geom_jitter(width = 0.05, height = 0) +
  scale_color_brewer(palette = "Dark2", name = "basin\nseparation") +
  facet_grid(. ~ data_source) +
  ylim(0,NA) +
  theme(axis.text.x = element_text(angle = 45, hjust=1),
        axis.title.x = element_blank())

Past versions of cases_absolute_global-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

4.1.2 Biases

dcant_budget_global_bias_all %>%
  ggplot(aes(period, dcant_bias, col = MLR_basins)) +
  geom_hline(yintercept = 0) +
  scale_color_brewer(palette = "Dark2", name = "basin\nseparation") +
  labs(y = expression(atop(Delta * C[ant] ~ bias,
                               (mu * mol ~ kg ^ {-1})))) +
  geom_point()

Past versions of cases_bias_global-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

p_global_bias <- 
  dcant_budget_global_bias_all %>%
  ggplot() +
  geom_hline(yintercept = global_bias_rel_max * c(-1,1),
             linetype = 2) +
  geom_hline(yintercept = 0) +
  scale_color_brewer(palette = "Dark2", name = "basin\nseparation") +
  labs(y = expression(Delta * C[ant] ~ bias ~ ("%")),
       title = "Model-based assesment") +
  theme(axis.title.x = element_blank()) +
  geom_point(aes(period, dcant_bias_rel, col = MLR_basins),
             alpha = 0.7) +
    theme(axis.text.x = element_text(angle = 45, hjust=1),
        axis.title.x = element_blank())

p_global_bias

Past versions of cases_bias_global-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

5 Regional

5.1 Individual cases

5.1.1 Absoulte values

dcant_budget_basin_AIP_all %>%
  ggplot(aes(period, dcant, col = MLR_basins)) +
  geom_jitter(width = 0.05, height = 0) +
  scale_color_brewer(palette = "Dark2", name = "basin\nseparation") +
  facet_grid(basin_AIP ~ data_source) +
  ylim(0,NA) +
  theme(axis.text.x = element_text(angle = 45, hjust=1),
        axis.title.x = element_blank())

Past versions of cases_absolute-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

5.1.2 Biases

dcant_budget_basin_AIP_bias_all %>%
  ggplot(aes(period, dcant_bias, col=MLR_basins)) +
  geom_hline(yintercept = 0) +
  geom_point() +
  facet_grid(basin_AIP ~ .)

Past versions of cases_bias-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

dcant_budget_basin_AIP_bias_all %>%
  ggplot() +
  geom_tile(aes(y = 0, height = regional_bias_rel_max * 2,
                x = "2004 - 2014", width = Inf,
                fill = "bias\nthreshold"), alpha = 0.5) +
  geom_hline(yintercept = 0) +
  scale_fill_manual(values = "grey70", name = "") +
  scale_color_brewer(palette = "Dark2", name = "basin\nseparation") +
  labs(y = expression(Delta ~ C[ant] ~ bias)) +
  theme(axis.title.x = element_blank()) +
  geom_jitter(aes(period, dcant_bias_rel, col = MLR_basins),
              width = 0.05, height = 0) +
  facet_grid(basin_AIP ~ .)

Past versions of cases_bias-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

p_regional_bias <- 
  dcant_budget_basin_AIP_bias_all %>%
  ggplot() +
  geom_hline(yintercept = regional_bias_rel_max * c(-1,1),
             linetype = 2) +
  geom_hline(yintercept = 0) +
  scale_color_brewer(palette = "Dark2", name = "basin\nseparation") +
  labs(y = expression(Delta * C[ant] ~ bias ~ ("%")),
       title = "Model-based assesment") +
  theme(axis.title.x = element_blank()) +
  geom_point(aes(period, dcant_bias_rel, col = MLR_basins),
             alpha = 0.7) +
    theme(axis.text.x = element_text(angle = 45, hjust=1),
        axis.title.x = element_blank()) +
  facet_grid(. ~ basin_AIP) +
  theme(
  strip.background = element_blank(),
  strip.text.x = element_blank()
)

p_regional_bias

Past versions of cases_bias-3.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

5.2 Slab budgets

dcant_slab_budget_all %>%
  filter(data_source == "obs",
         period != "1994 - 2014") %>% 
  ggplot(aes(MLR_basins, dcant, fill = gamma_slab)) +
  geom_hline(yintercept = 0, col = "red") +
  geom_col() +
  scale_fill_scico_d(direction = -1) +
  facet_grid(basin_AIP ~ period)

Past versions of slab_budgets-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

dcant_slab_budget_all %>%
  filter(data_source == "obs",
         period != "1994 - 2014") %>%
  group_by(basin_AIP) %>%
  group_split() %>%
  map(
    ~ ggplot(data = .x,
             aes(MLR_basins, dcant, fill = gamma_slab)) +
      geom_hline(yintercept = 0) +
      geom_col() +
      scale_fill_scico_d(direction = -1) +
      labs(title = paste("data_source:", unique(.x$basin_AIP))) +
      facet_grid(gamma_slab ~ period)
  )

[[1]]

Past versions of slab_budgets_individual-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[2]]

Past versions of slab_budgets_individual-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[3]]

Past versions of slab_budgets_individual-3.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

dcant_slab_budget_bias_all %>%
  filter(period != "1994 - 2014") %>%
  group_by(basin_AIP) %>%
  group_split() %>%
  # head(1) %>% 
  map(
    ~ ggplot(data = .x,
             aes(gamma_slab, dcant_bias, fill = gamma_slab)) +
      geom_col() +
      coord_flip() +
      scale_x_discrete(limits = rev) +
      scale_fill_scico_d(direction = -1) +
      facet_grid(period ~ MLR_basins) +
      labs(title = paste("data_source:", unique(.x$basin_AIP)))
    )

[[1]]

Past versions of slab_budgets_bias-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[2]]

Past versions of slab_budgets_bias-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[3]]

Past versions of slab_budgets_bias-3.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

6 Ensemble

6.1 Members

ensemble_MLR_basins_global <- dcant_budget_global_bias_all %>% 
  filter(abs(dcant_bias_rel) < global_bias_rel_max) %>% 
  count(MLR_basins) %>% 
  filter(n == 2) %>% 
  pull(MLR_basins)

print("Global criterion")

[1] "Global criterion"

ensemble_MLR_basins_global

[1] "1"      "SO_2"   "SO_AIP"

ensemble_MLR_basins_regional <- dcant_budget_basin_AIP_bias_all %>% 
  filter(abs(dcant_bias_rel) < regional_bias_rel_max) %>% 
  count(MLR_basins) %>% 
  filter(n == 6) %>% 
  pull(MLR_basins)

print("Regional criterion")

[1] "Regional criterion"

ensemble_MLR_basins_regional

[1] "1"      "SO_2"   "SO_AIP"

ensemble_MLR_basins <-
  intersect(ensemble_MLR_basins_global, ensemble_MLR_basins_regional)


print("Both criteria")

[1] "Both criteria"

ensemble_MLR_basins

[1] "1"      "SO_2"   "SO_AIP"

rm(ensemble_MLR_basins_global, ensemble_MLR_basins_regional)

6.2 Global

dcant_budget_global_all_in <- dcant_budget_global_all %>% 
  filter(data_source %in% c("mod", "obs"),
         MLR_basins %in% ensemble_MLR_basins)

dcant_budget_global_ensemble <- dcant_budget_global_all_in %>% 
  group_by(data_source, period) %>% 
  summarise(dcant_mean = mean(dcant),
            dcant_sd = sd(dcant),
            dcant_range = max(dcant)- min(dcant)) %>% 
  ungroup()

6.2.1 Mean

legend_title = expression(Delta * C[ant]~(PgC))

ggplot() +
  geom_col(data = dcant_budget_global_ensemble,
           aes(x = period,
               y = dcant_mean),
           fill = "darkgrey") +
  geom_errorbar(
    data = dcant_budget_global_ensemble,
    aes(
      x = period,
      y = dcant_mean,
      ymax = dcant_mean + dcant_sd,
      ymin = dcant_mean - dcant_sd
    ),
    width = 0.1
  ) +
  geom_point(
    data = dcant_budget_global_all,
    aes(period, dcant, col = MLR_basins),
    alpha = 0.7,
    position = position_jitter(width = 0.2, height = 0)
  ) +
  scale_y_continuous(limits = c(0,70), expand = c(0,0)) +
  scale_color_brewer(palette = "Dark2", name = "basin\nseparation") +
  facet_grid(. ~ data_source) +
  labs(y = legend_title) +
  theme(axis.text.x = element_text(angle = 45, hjust=1),
        axis.title.x = element_blank())

Past versions of ensemble_mean_global-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

p_global_dcant <- ggplot() +
  geom_col(data = dcant_budget_global_ensemble %>% 
             filter(data_source == "obs"),
           aes(x = period,
               y = dcant_mean),
           fill = "darkgrey") +
    geom_point(
    data = dcant_budget_global_all %>% 
             filter(data_source == "obs"),
    aes(period, dcant, col = MLR_basins),
    alpha = 0.7,
    position = position_jitter(width = 0.1, height = 0)
  ) +
  geom_errorbar(
    data = dcant_budget_global_ensemble %>% 
             filter(data_source == "obs"),
    aes(
      x = period,
      y = dcant_mean,
      ymax = dcant_mean + dcant_sd,
      ymin = dcant_mean - dcant_sd
    ),
    width = 0.1
  ) +
  scale_y_continuous(limits = c(0,70), expand = c(0,0)) +
  scale_color_brewer(palette = "Dark2", name = "basin\nseparation") +
  labs(y = legend_title,
       title = "Observation-based results") +
  theme(axis.text.x = element_blank(),
        axis.title.x = element_blank())

p_global_dcant_bias <-
p_global_dcant / p_global_bias +
  plot_layout(guides = 'collect',
              heights = c(2,1))

p_global_dcant_bias

Past versions of ensemble_mean_global-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

ggsave(plot = p_global_dcant_bias,
       path = "output/publication",
       filename = "global_dcant.png",
       height = 5,
       width = 5)

rm(p_global_bias, p_global_dcant, p_global_dcant_bias)

6.2.2 Sum decades

dcant_budget_global_all_in_sum <-
  dcant_budget_global_all_in %>%
  filter(period != "1994 - 2014") %>%
  arrange(tref1) %>%
  group_by(data_source, MLR_basins) %>%
  mutate(dcant = dcant + lag(dcant)) %>% 
  ungroup() %>%
  drop_na() %>% 
  mutate(estimate = "sum")

dcant_budget_global_all_in_sum <-
  bind_rows(
    dcant_budget_global_all_in_sum,
    dcant_budget_global_all_in %>%
      filter(period == "1994 - 2014") %>%
      mutate(estimate = "direct")
  )

ggplot() +
  geom_point(
    data = dcant_budget_global_all_in_sum,
    aes(estimate, dcant, col = MLR_basins),
    alpha = 0.7,
    position = position_jitter(width = 0, height = 0)
  ) +
  scale_y_continuous(limits = c(0,70), expand = c(0,0)) +
  scale_color_brewer(palette = "Dark2", name = "basin\nseparation") +
  facet_grid(. ~ data_source) +
  theme(axis.text.x = element_text(angle = 45, hjust=1),
        axis.title.x = element_blank())

Past versions of summed_decades-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

6.2.3 Mean bias

dcant_budget_global_ensemble_bias <- full_join(
  dcant_budget_global_ensemble %>%
    filter(data_source == "mod") %>% 
    select(period, dcant_mean, dcant_sd),
  dcant_budget_global_all %>%
    filter(data_source == "mod_truth",
           MLR_basins == "2") %>% 
    select(period, dcant)
)

dcant_budget_global_ensemble_bias <- dcant_budget_global_ensemble_bias %>% 
  mutate(dcant_mean_bias = dcant_mean - dcant,
         dcant_mean_bias_rel = 100 * dcant_mean_bias / dcant)

dcant_budget_global_ensemble_bias %>%
  ggplot(aes(period, dcant_mean_bias)) +
  geom_hline(yintercept = 0) +
  geom_point()

Past versions of ensemble_mean_bias_global-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

dcant_budget_global_ensemble_bias %>%
  ggplot(aes(period, dcant_mean_bias_rel)) +
  geom_hline(yintercept = 0) +
  geom_point()

Past versions of ensemble_mean_bias_global-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

6.2.4 SD vs bias

dcant_budget_global_ensemble_bias %>% 
  ggplot(aes(dcant_mean_bias, dcant_sd, col = period)) +
  geom_point() +
  xlim(0, NA) +
  ylim(0, NA)

Past versions of ensemble_sd_vs_bias_global-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

6.2.5 Vertical patterns

6.2.5.1 Absoulte values

dcant_budget_global_all_depth %>%
  filter(MLR_basins %in% ensemble_MLR_basins) %>% 
  group_by(data_source) %>%
  group_split() %>%
  # head(1) %>%
  map(
    ~  ggplot(data = .x,
              aes(dcant, MLR_basins, fill=period)) +
      geom_vline(xintercept = 0) +
      geom_col(position = "dodge") +
      scale_fill_brewer(palette = "Dark2") +
      facet_grid(inv_depth ~ .) +
      labs(title = paste("data_source:", unique(.x$data_source)))
  )

[[1]]

Past versions of cases_absolute_depth_global-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[2]]

Past versions of cases_absolute_depth_global-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[3]]

Past versions of cases_absolute_depth_global-3.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

6.2.5.2 Biases

dcant_budget_global_bias_all_depth %>%
  filter(MLR_basins %in% ensemble_MLR_basins) %>%
  ggplot(aes(dcant_bias, MLR_basins, fill = period)) +
  geom_vline(xintercept = 0) +
  geom_col(position = "dodge") +
  scale_fill_brewer(palette = "Dark2") +
  facet_grid(inv_depth ~ .)

Past versions of cases_bias_depth_global-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

dcant_budget_global_bias_all_depth %>%
    filter(MLR_basins %in% ensemble_MLR_basins) %>% 
  ggplot(aes(dcant_bias_rel, MLR_basins, fill = period)) +
  geom_vline(xintercept = 0) +
  geom_col(position = "dodge") +
  scale_fill_brewer(palette = "Dark2") +
  facet_grid(inv_depth ~ .)

Past versions of cases_bias_rel_depth_global-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

rm(dcant_budget_global_all,
   dcant_budget_global_all_depth,
   dcant_budget_global_bias_all,
   dcant_budget_global_bias_all_depth,
   dcant_budget_global_ensemble,
   dcant_budget_global_ensemble_bias,
   params_local_all)

6.3 Regional

dcant_budget_basin_AIP_ensemble <- dcant_budget_basin_AIP_all %>% 
  filter(data_source %in% c("mod", "obs"),
         MLR_basins %in% ensemble_MLR_basins) %>% 
  group_by(basin_AIP, data_source, period) %>% 
  summarise(dcant_mean = mean(dcant),
            dcant_sd = sd(dcant),
            dcant_range = max(dcant)- min(dcant)) %>% 
  ungroup()

6.3.1 Mean

dcant_budget_basin_AIP_ensemble %>%
  ggplot(aes(period, dcant_mean, col=basin_AIP)) +
  geom_pointrange(aes(ymax = dcant_mean + dcant_sd,
                      ymin = dcant_mean - dcant_sd),
                  shape = 21) +
  facet_grid(. ~ data_source)

Past versions of ensemble_mean-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

p_regional_dcant <- ggplot() +
  geom_col(
    data = dcant_budget_basin_AIP_ensemble %>%
      filter(data_source == "obs"),
    aes(x = period,
        y = dcant_mean),
    fill = "darkgrey"
  ) +
  geom_point(
    data = dcant_budget_basin_AIP_all %>%
      filter(data_source == "obs"),
    aes(period, dcant, col = MLR_basins),
    position = position_jitter(width = 0.1, height = 0),
    alpha = 0.7
  ) +
  geom_errorbar(
    data = dcant_budget_basin_AIP_ensemble %>%
      filter(data_source == "obs"),
    aes(
      x = period,
      y = dcant_mean,
      ymax = dcant_mean + dcant_sd,
      ymin = dcant_mean - dcant_sd
    ),
    width = 0.1
  ) +
  scale_y_continuous(limits = c(0, 35), expand = c(0, 0)) +
  scale_color_brewer(palette = "Dark2", name = "basin\nseparation") +
  labs(y = legend_title,
       title = "Observation-based results") +
  theme(axis.text.x = element_blank(),
        axis.title.x = element_blank()) +
  facet_grid(. ~ basin_AIP)

p_regional_dcant_bias <-
p_regional_dcant / p_regional_bias +
  plot_layout(guides = 'collect',
              heights = c(2,1))

p_regional_dcant_bias

Past versions of ensemble_mean-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

ggsave(plot = p_regional_dcant_bias,
       path = "output/publication",
       filename = "regional_dcant.png",
       height = 5,
       width = 10)

rm(p_regional_bias, p_regional_dcant, p_regional_dcant_bias)

6.3.2 Mean bias

dcant_budget_basin_AIP_ensemble_bias <- full_join(
  dcant_budget_basin_AIP_ensemble %>%
    filter(data_source == "mod") %>% 
    select(basin_AIP, period, dcant_mean, dcant_sd),
  dcant_budget_basin_AIP_all %>%
    filter(data_source == "mod_truth",
           MLR_basins == "2") %>% 
    select(basin_AIP, period, dcant)
)

dcant_budget_basin_AIP_ensemble_bias <- dcant_budget_basin_AIP_ensemble_bias %>% 
  mutate(dcant_mean_bias = dcant_mean - dcant,
         dcant_mean_bias_rel = 100 * dcant_mean_bias / dcant)


dcant_budget_basin_AIP_ensemble_bias %>%
  ggplot(aes(period, dcant_mean_bias, col = basin_AIP)) +
  geom_hline(yintercept = 0) +
  geom_point()

Past versions of ensemble_mean_bias-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

dcant_budget_basin_AIP_ensemble_bias %>%
  ggplot(aes(period, dcant_mean_bias_rel, col = basin_AIP)) +
  geom_hline(yintercept = 0) +
  geom_point()

Past versions of ensemble_mean_bias-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

6.3.3 SD vs bias

dcant_budget_basin_AIP_ensemble_bias %>% 
  ggplot(aes(dcant_mean_bias, dcant_sd, col=basin_AIP)) +
  geom_point() +
  facet_grid(. ~ period) +
  xlim(0, NA) +
  ylim(0, NA)

Past versions of ensemble_sd_vs_bias-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

6.3.4 Vertical patterns

6.3.4.1 Absoulte values

dcant_budget_basin_AIP_all_depth %>%
  filter(
    MLR_basins %in% ensemble_MLR_basins,
    MLR_basins %in% ensemble_MLR_basins
  ) %>%
  group_by(data_source) %>%
  group_split() %>%
  # head(1) %>%
  map(
    ~  ggplot(data = .x,
              aes(dcant, MLR_basins, fill = basin_AIP)) +
      geom_vline(xintercept = 0) +
      geom_col() +
      scale_fill_brewer(palette = "Dark2") +
      facet_grid(inv_depth ~ period) +
      labs(title = paste("data_source:", unique(.x$data_source)))
  )

[[1]]

Past versions of cases_absolute_depth-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[2]]

Past versions of cases_absolute_depth-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[3]]

Past versions of cases_absolute_depth-3.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

6.3.4.2 Biases

dcant_budget_basin_AIP_bias_all_depth %>%
  filter(
    MLR_basins %in% ensemble_MLR_basins,
    MLR_basins %in% ensemble_MLR_basins
  ) %>%
  ggplot(aes(dcant_bias, MLR_basins, fill = basin_AIP)) +
  geom_vline(xintercept = 0) +
  geom_col() +
  scale_fill_brewer(palette = "Dark2") +
  facet_grid(inv_depth ~ period)

Past versions of cases_bias_depth-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

dcant_budget_basin_AIP_bias_all_depth %>%
  filter(
    MLR_basins %in% ensemble_MLR_basins,
    MLR_basins %in% ensemble_MLR_basins
  ) %>%
  ggplot(aes(dcant_bias_rel, MLR_basins, fill = basin_AIP)) +
  geom_vline(xintercept = 0) +
  geom_col(position = "dodge") +
  scale_fill_brewer(palette = "Dark2") +
  facet_grid(inv_depth ~ period)

Past versions of cases_bias_rel_depth-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

7 Steady state

dcant_obs_budget_all %>%
  group_by(inv_depth) %>%
  group_split() %>%
  # head(1) %>% 
  map(
    ~ ggplot(data = .x,
             aes(estimate, dcant_pos, fill = basin_AIP)) +
      scale_fill_brewer(palette = "Dark2") +
      geom_col() +
      facet_grid(MLR_basins ~ period) +
      labs(title = paste("inventory depth:",unique(.x$inv_depth)))
  )

[[1]]

Past versions of steady_state_comparison-1.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[2]]

Past versions of steady_state_comparison-2.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[3]]

Past versions of steady_state_comparison-3.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[4]]

Past versions of steady_state_comparison-4.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

[[5]]

Past versions of steady_state_comparison-5.png

Version	Author	Date
a7af62f	jens-daniel-mueller	2021-10-06

8 Write ensemble members

ensemble_MLR_basins %>% 
  write_rds("data/ensemble_members_no_p.rds")

MLR_basins_in %>% 
  write_rds("data/MLR_basins_in_no_p.rds")

Session information

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] ggforce_0.3.3   metR_0.9.0      scico_1.2.0     patchwork_1.1.1
 [5] collapse_1.5.0  forcats_0.5.0   stringr_1.4.0   dplyr_1.0.5    
 [9] purrr_0.3.4     readr_1.4.0     tidyr_1.1.3     tibble_3.1.3   
[13] ggplot2_3.3.5   tidyverse_1.3.0 workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] httr_1.4.2               sass_0.4.0               jsonlite_1.7.1          
 [4] modelr_0.1.8             bslib_0.2.5.1            assertthat_0.2.1        
 [7] highr_0.8                blob_1.2.1               cellranger_1.1.0        
[10] yaml_2.2.1               pillar_1.6.2             backports_1.1.10        
[13] lattice_0.20-41          glue_1.4.2               RcppEigen_0.3.3.7.0     
[16] digest_0.6.27            RColorBrewer_1.1-2       promises_1.1.1          
[19] polyclip_1.10-0          checkmate_2.0.0          rvest_0.3.6             
[22] colorspace_2.0-2         htmltools_0.5.1.1        httpuv_1.5.4            
[25] Matrix_1.2-18            pkgconfig_2.0.3          broom_0.7.9             
[28] haven_2.3.1              scales_1.1.1             tweenr_1.0.2            
[31] whisker_0.4              later_1.2.0              git2r_0.27.1            
[34] farver_2.0.3             generics_0.1.0           ellipsis_0.3.2          
[37] withr_2.3.0              cli_3.0.1                magrittr_1.5            
[40] crayon_1.3.4             readxl_1.3.1             evaluate_0.14           
[43] fs_1.5.0                 fansi_0.4.1              MASS_7.3-53             
[46] xml2_1.3.2               RcppArmadillo_0.10.1.2.0 tools_4.0.3             
[49] data.table_1.14.0        hms_0.5.3                lifecycle_1.0.0         
[52] munsell_0.5.0            reprex_0.3.0             compiler_4.0.3          
[55] jquerylib_0.1.4          rlang_0.4.11             grid_4.0.3              
[58] rstudioapi_0.13          labeling_0.4.2           rmarkdown_2.10          
[61] gtable_0.3.0             DBI_1.1.0                R6_2.5.0                
[64] lubridate_1.7.9          knitr_1.33               utf8_1.1.4              
[67] rprojroot_2.0.2          stringi_1.5.3            parallel_4.0.3          
[70] Rcpp_1.0.5               vctrs_0.3.8              dbplyr_1.4.4            
[73] tidyselect_1.1.0         xfun_0.25