Budgets

workflowr

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Last updated: 2022-01-06

Checks: 7 0

Knit directory: emlr_obs_analysis/analysis/

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html	5ba7fc6	jens-daniel-mueller	2022-01-06	Build site.
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html	bc2c182	jens-daniel-mueller	2021-12-23	Build site.
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Rmd	d675dd9	jens-daniel-mueller	2021-11-03	updated plots
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html	e534f51	jens-daniel-mueller	2021-11-02	Build site.
Rmd	31cbfae	jens-daniel-mueller	2021-11-02	rebuild with revised IO tests
html	57cfc36	jens-daniel-mueller	2021-11-01	Build site.
html	4331a22	jens-daniel-mueller	2021-10-29	Build site.
html	a162b7e	jens-daniel-mueller	2021-10-28	Build site.
Rmd	ebaf3bd	jens-daniel-mueller	2021-10-28	cleaned output
html	cd1e165	jens-daniel-mueller	2021-10-27	Build site.
Rmd	a18d99e	jens-daniel-mueller	2021-10-27	tcant vs atm pco2 plot created
html	ae5ae64	jens-daniel-mueller	2021-10-26	Build site.
html	8c9fa17	jens-daniel-mueller	2021-10-22	Build site.
html	968fe94	jens-daniel-mueller	2021-10-18	Build site.
html	581baa0	jens-daniel-mueller	2021-10-07	Build site.
html	a7af62f	jens-daniel-mueller	2021-10-06	Build site.
html	f9b4f93	jens-daniel-mueller	2021-10-05	Build site.
html	f59a35e	jens-daniel-mueller	2021-10-04	Build site.
Rmd	ddf84c2	jens-daniel-mueller	2021-10-04	slab budgets included
html	8b1336c	jens-daniel-mueller	2021-10-04	Build site.
Rmd	251b435	jens-daniel-mueller	2021-10-04	slab budgets included
html	19c82b0	jens-daniel-mueller	2021-10-04	Build site.
Rmd	34386f7	jens-daniel-mueller	2021-10-04	slab budgets included
html	960d158	jens-daniel-mueller	2021-09-29	Build site.
html	0573621	jens-daniel-mueller	2021-09-29	Build site.
Rmd	f5cf35e	jens-daniel-mueller	2021-09-29	rebuildt with vif results
html	57ebd7c	jens-daniel-mueller	2021-09-28	Build site.
Rmd	09fc062	jens-daniel-mueller	2021-09-28	include steady state data
html	f51dcb9	jens-daniel-mueller	2021-09-28	Build site.
Rmd	056c790	jens-daniel-mueller	2021-09-28	new MLR_basin added
html	55d2059	jens-daniel-mueller	2021-09-28	Build site.
Rmd	9307c46	jens-daniel-mueller	2021-09-28	new MLR_basin added
html	3a9319e	jens-daniel-mueller	2021-09-28	Build site.
Rmd	78424ad	jens-daniel-mueller	2021-09-28	update budget plots
html	b95f078	jens-daniel-mueller	2021-09-27	Build site.
Rmd	6c51b25	jens-daniel-mueller	2021-09-27	compare direct and summed two decadel changes
html	a9bf202	jens-daniel-mueller	2021-09-27	Build site.
Rmd	3ee96bc	jens-daniel-mueller	2021-09-27	compare direct and summed two decadel changes
html	f2cfccc	jens-daniel-mueller	2021-09-27	Build site.
Rmd	6ec79a6	jens-daniel-mueller	2021-09-27	update ensemble calculation
html	d0dbf3e	jens-daniel-mueller	2021-09-27	Build site.
Rmd	f8ae9b3	jens-daniel-mueller	2021-09-27	filter MLR basins with both criteria
html	09002a7	jens-daniel-mueller	2021-09-26	Build site.
Rmd	b93e153	jens-daniel-mueller	2021-09-26	filter MLR_basins
html	23cc3a7	jens-daniel-mueller	2021-09-26	Build site.
Rmd	ed88932	jens-daniel-mueller	2021-09-26	filter MLR basins
html	0c6be7e	jens-daniel-mueller	2021-09-24	Build site.
Rmd	6a79fd0	jens-daniel-mueller	2021-09-24	consider ensemble selection across all analysis
html	a324ace	jens-daniel-mueller	2021-09-24	Build site.
Rmd	c43a6a9	jens-daniel-mueller	2021-09-24	revised ensemble selection
html	f54d5db	jens-daniel-mueller	2021-09-24	Build site.
Rmd	76c942b	jens-daniel-mueller	2021-09-24	1990 as start year 1 for classic runs
html	31c33cb	jens-daniel-mueller	2021-09-23	Build site.
Rmd	9b1df4d	jens-daniel-mueller	2021-09-23	1994 vs 2014 added
html	ec4f702	jens-daniel-mueller	2021-09-22	Build site.
html	6525680	jens-daniel-mueller	2021-09-21	Build site.
html	6bf38c9	jens-daniel-mueller	2021-09-21	Build site.
html	63911d0	jens-daniel-mueller	2021-09-21	Build site.
html	499c9d5	jens-daniel-mueller	2021-09-21	Build site.
html	271a3ac	jens-daniel-mueller	2021-09-21	Build site.
html	35ad8b5	jens-daniel-mueller	2021-09-20	Build site.
Rmd	919f74b	jens-daniel-mueller	2021-09-20	rebuildt with canyon b cleaning analysis

---

1 Bias thresholds

global_bias_rel_max <- 12.5
global_bias_rel_max

[1] 12.5

regional_bias_rel_max <- 30
regional_bias_rel_max

[1] 30

2 Read files

# identify required version IDs

Version_IDs_1 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
                            pattern = paste0("v_1", 0))

Version_IDs_2 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
                            pattern = paste0("v_2", 0))

Version_IDs_3 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
                            pattern = paste0("v_3", 0))

Version_IDs <- c(Version_IDs_1, Version_IDs_2, Version_IDs_3)

print(Version_IDs)

 [1] "v_1001" "v_1002" "v_1003" "v_1004" "v_1005" "v_1006" "v_2001" "v_2002"
 [9] "v_2003" "v_2004" "v_2005" "v_2006" "v_3001" "v_3002" "v_3003" "v_3004"
[17] "v_3005" "v_3006"

2.1 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 := str_c(params_local$MLR_basins, collapse = "+"),
    tref1 = params_local$tref1,
    tref2 = params_local$tref2)
  
  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_1001"
[1] "v_1002"
[1] "v_1003"
[1] "v_1004"
[1] "v_1005"
[1] "v_1006"
[1] "v_2001"
[1] "v_2002"
[1] "v_2003"
[1] "v_2004"
[1] "v_2005"
[1] "v_2006"
[1] "v_3001"
[1] "v_3002"
[1] "v_3003"
[1] "v_3004"
[1] "v_3005"
[1] "v_3006"

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)

2.2 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_1001"
[1] "v_1002"
[1] "v_1003"
[1] "v_1004"
[1] "v_1005"
[1] "v_1006"
[1] "v_2001"
[1] "v_2002"
[1] "v_2003"
[1] "v_2004"
[1] "v_2005"
[1] "v_2006"
[1] "v_3001"
[1] "v_3002"
[1] "v_3003"
[1] "v_3004"
[1] "v_3005"
[1] "v_3006"

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)

2.3 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_1001"
[1] "v_1002"
[1] "v_1003"
[1] "v_1004"
[1] "v_1005"
[1] "v_1006"
[1] "v_2001"
[1] "v_2002"
[1] "v_2003"
[1] "v_2004"
[1] "v_2005"
[1] "v_2006"
[1] "v_3001"
[1] "v_3002"
[1] "v_3003"
[1] "v_3004"
[1] "v_3005"
[1] "v_3006"

rm(dcant_obs_budget)

dcant_obs_budget_all <- full_join(dcant_obs_budget_all,
                             params_local_all)

2.4 Atm CO2

co2_atm <-
  read_csv(paste(path_preprocessing,
                 "co2_atm.csv",
                 sep = ""))

3 Global

3.1 Individual cases

3.1.1 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") +
  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
b16a8b5	jens-daniel-mueller	2022-01-06
33d5577	jens-daniel-mueller	2022-01-06
d549e76	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

3.1.2 Biases

dcant_budget_global_bias_all %>%
  ggplot(aes(period, dcant_bias, col = MLR_basins)) +
  geom_hline(yintercept = 0) +
  scale_color_brewer(palette = "Dark2") +
  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
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

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") +
  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
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
b95f078	jens-daniel-mueller	2021-09-27
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

4 Regional

4.1 Individual cases

4.1.1 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") +
  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
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
72dd8ed	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
f2cfccc	jens-daniel-mueller	2021-09-27
d0dbf3e	jens-daniel-mueller	2021-09-27
09002a7	jens-daniel-mueller	2021-09-26
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

4.1.2 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
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
09002a7	jens-daniel-mueller	2021-09-26
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

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") +
  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
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
72dd8ed	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
f2cfccc	jens-daniel-mueller	2021-09-27
d0dbf3e	jens-daniel-mueller	2021-09-27
09002a7	jens-daniel-mueller	2021-09-26
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

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") +
  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
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
b95f078	jens-daniel-mueller	2021-09-27
f2cfccc	jens-daniel-mueller	2021-09-27
d0dbf3e	jens-daniel-mueller	2021-09-27
09002a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24

4.2 Slab budgets

4.2.1 Absolute values

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
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
8b1336c	jens-daniel-mueller	2021-10-04
19c82b0	jens-daniel-mueller	2021-10-04

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
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f59a35e	jens-daniel-mueller	2021-10-04

[[2]]

Past versions of slab_budgets_individual-2.png

Version	Author	Date
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f59a35e	jens-daniel-mueller	2021-10-04

[[3]]

Past versions of slab_budgets_individual-3.png

Version	Author	Date
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f59a35e	jens-daniel-mueller	2021-10-04

4.2.2 Bias

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
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
19c82b0	jens-daniel-mueller	2021-10-04

[[2]]

Past versions of slab_budgets_bias-2.png

Version	Author	Date
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
8b1336c	jens-daniel-mueller	2021-10-04

[[3]]

Past versions of slab_budgets_bias-3.png

Version	Author	Date
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
8b1336c	jens-daniel-mueller	2021-10-04

4.2.3 Spread

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

[[1]]

Past versions of slab_budgets_spread-1.png

Version	Author	Date
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28

[[2]]

Past versions of slab_budgets_spread-2.png

Version	Author	Date
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28

[[3]]

Past versions of slab_budgets_spread-3.png

Version	Author	Date
5ba7fc6	jens-daniel-mueller	2022-01-06
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28

5 Ensemble

5.1 Global

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

dcant_budget_global_ensemble <- dcant_budget_global_all_in %>% 
  group_by(data_source, period, tref2) %>% 
  summarise(dcant_mean = mean(dcant),
            dcant_sd = sd(dcant),
            dcant_range = max(dcant)- min(dcant)) %>% 
  ungroup()

5.1.1 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") +
  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
5ec57f9	jens-daniel-mueller	2022-01-06
72dd8ed	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
b95f078	jens-daniel-mueller	2021-09-27
f2cfccc	jens-daniel-mueller	2021-09-27
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

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") +
  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
5ec57f9	jens-daniel-mueller	2022-01-06
72dd8ed	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
b95f078	jens-daniel-mueller	2021-09-27

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

rm(p_global_bias, p_global_dcant, p_global_dcant_bias)

5.1.2 Mean vs atm CO2

dcant_ensemble <- dcant_budget_global_ensemble %>% 
  filter(data_source == "obs",
         period != "1994 - 2014") %>% 
  select(year = tref2, dcant_mean, dcant_sd)

tcant_S04 <- bind_cols(year = 1994, dcant_mean = 118, dcant_sd = 19)

tcant_ensemble <- full_join(dcant_ensemble, tcant_S04)

tcant_ensemble <- left_join(tcant_ensemble, co2_atm)

co2_atm_pi <- bind_cols(pCO2 = 280, dcant_mean = 0, year = 1750, dcant_sd = 0)

tcant_ensemble <- full_join(tcant_ensemble, co2_atm_pi)

tcant_ensemble <- tcant_ensemble %>% 
  arrange(year) %>% 
  mutate(tcant = cumsum(dcant_mean),
         tcant_sd = cumsum(dcant_sd))

tcant_ensemble %>% 
  ggplot(aes(pCO2, tcant, ymin = tcant - tcant_sd, ymax = tcant + tcant_sd)) +
  geom_ribbon(fill = "grey80") +
  geom_point() +
  geom_line() +
  geom_text(aes(label = year), nudge_x = -5, nudge_y = 5) +
  labs(x = expression(Atmospheric~pCO[2]~(µatm)),
       y = expression(Total~oceanic~C[ant]~(PgC)))

Past versions of mean_tcant_over_atm_co2-1.png

Version	Author	Date
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
cd1e165	jens-daniel-mueller	2021-10-27

# ggsave(path = "output/publication",
#        filename = "Fig_global_dcant_budget_vs_atm_pCO2.png",
#        height = 4,
#        width = 7)

5.1.3 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") +
  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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
a9bf202	jens-daniel-mueller	2021-09-27

5.1.4 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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

5.1.5 Vertical patterns

5.1.5.1 Absoulte values

dcant_budget_global_all_depth %>%
  filter(data_source != "mod_truth") %>% 
  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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

[[2]]

Past versions of cases_absolute_depth_global-2.png

Version	Author	Date
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

5.1.5.2 Biases

dcant_budget_global_bias_all_depth %>%
  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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

dcant_budget_global_bias_all_depth %>%
  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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

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)

5.2 Regional

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

5.2.1 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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

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") +
  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
5ec57f9	jens-daniel-mueller	2022-01-06
bb02de1	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
b95f078	jens-daniel-mueller	2021-09-27

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

rm(p_regional_bias, p_regional_dcant, p_regional_dcant_bias)

5.2.2 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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24

5.2.3 Vertical patterns

5.2.3.1 Absoulte values

dcant_budget_basin_AIP_all_depth %>%
  filter(data_source != "mod_truth") %>%
  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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

[[2]]

Past versions of cases_absolute_depth-2.png

Version	Author	Date
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
b95f078	jens-daniel-mueller	2021-09-27

5.2.3.2 Biases

dcant_budget_basin_AIP_bias_all_depth %>%
  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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

dcant_budget_basin_AIP_bias_all_depth %>%
  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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
bc2c182	jens-daniel-mueller	2021-12-23
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
e534f51	jens-daniel-mueller	2021-11-02
a162b7e	jens-daniel-mueller	2021-10-28
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
f51dcb9	jens-daniel-mueller	2021-09-28
55d2059	jens-daniel-mueller	2021-09-28
3a9319e	jens-daniel-mueller	2021-09-28
d0dbf3e	jens-daniel-mueller	2021-09-27
23cc3a7	jens-daniel-mueller	2021-09-26
a324ace	jens-daniel-mueller	2021-09-24
f54d5db	jens-daniel-mueller	2021-09-24
31c33cb	jens-daniel-mueller	2021-09-23
35ad8b5	jens-daniel-mueller	2021-09-20

6 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
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
57ebd7c	jens-daniel-mueller	2021-09-28

[[2]]

Past versions of steady_state_comparison-2.png

Version	Author	Date
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
57ebd7c	jens-daniel-mueller	2021-09-28

[[3]]

Past versions of steady_state_comparison-3.png

Version	Author	Date
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
57ebd7c	jens-daniel-mueller	2021-09-28

[[4]]

Past versions of steady_state_comparison-4.png

Version	Author	Date
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
57ebd7c	jens-daniel-mueller	2021-09-28

[[5]]

Past versions of steady_state_comparison-5.png

Version	Author	Date
5ec57f9	jens-daniel-mueller	2022-01-06
030836b	jens-daniel-mueller	2022-01-06
e55f868	jens-daniel-mueller	2021-12-23
db09d70	jens-daniel-mueller	2021-12-10
8c9fa17	jens-daniel-mueller	2021-10-22
968fe94	jens-daniel-mueller	2021-10-18
57ebd7c	jens-daniel-mueller	2021-09-28

Session information

sessionInfo()

R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.3

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] here_0.1                 modelr_0.1.8             bslib_0.2.5.1           
 [7] assertthat_0.2.1         highr_0.8                blob_1.2.1              
[10] cellranger_1.1.0         yaml_2.2.1               pillar_1.6.2            
[13] backports_1.1.10         lattice_0.20-41          glue_1.4.2              
[16] RcppEigen_0.3.3.7.0      digest_0.6.27            RColorBrewer_1.1-2      
[19] polyclip_1.10-0          promises_1.1.1           checkmate_2.0.0         
[22] rvest_0.3.6              colorspace_2.0-2         htmltools_0.5.1.1       
[25] httpuv_1.5.4             Matrix_1.2-18            pkgconfig_2.0.3         
[28] broom_0.7.9              haven_2.3.1              scales_1.1.1            
[31] tweenr_1.0.2             whisker_0.4              later_1.2.0             
[34] git2r_0.27.1             farver_2.0.3             generics_0.1.0          
[37] ellipsis_0.3.2           withr_2.3.0              cli_3.0.1               
[40] magrittr_1.5             crayon_1.3.4             readxl_1.3.1            
[43] evaluate_0.14            fs_1.5.0                 fansi_0.4.1             
[46] MASS_7.3-53              xml2_1.3.2               RcppArmadillo_0.10.1.2.0
[49] tools_4.0.3              data.table_1.14.0        hms_0.5.3               
[52] lifecycle_1.0.0          munsell_0.5.0            reprex_0.3.0            
[55] compiler_4.0.3           jquerylib_0.1.4          rlang_0.4.11            
[58] grid_4.0.3               rstudioapi_0.13          labeling_0.4.2          
[61] rmarkdown_2.10           gtable_0.3.0             DBI_1.1.0               
[64] R6_2.5.0                 lubridate_1.7.9          knitr_1.33              
[67] utf8_1.1.4               rprojroot_2.0.2          stringi_1.5.3           
[70] parallel_4.0.3           Rcpp_1.0.5               vctrs_0.3.8             
[73] dbplyr_1.4.4             tidyselect_1.1.0         xfun_0.25