Column inventories
Jens Daniel Müller
02 June, 2021
Last updated: 2021-06-02
Checks: 7 0
Knit directory: emlr_obs_analysis/
This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
The command set.seed(20210412) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.
Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version 9881e98. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
Ignored: .Rhistory
Ignored: .Rproj.user/
Ignored: data/
Ignored: output/Gruber_2019_comparison/
Ignored: output/publication/
Untracked files:
Untracked: code/Workflowr_project_managment.R
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/column_inventories.Rmd) and HTML (docs/column_inventories.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 9881e98 | jens-daniel-mueller | 2021-06-02 | include GLODAP beta 2021 based results |
| html | 4d8b4e7 | jens-daniel-mueller | 2021-06-02 | Build site. |
| Rmd | 05184e5 | jens-daniel-mueller | 2021-06-02 | include GLODAP beta 2021 based results |
| html | 878aef7 | jens-daniel-mueller | 2021-05-28 | Build site. |
| Rmd | 2c347cd | jens-daniel-mueller | 2021-05-28 | plotted C* rmse, MLR target, vif max |
| html | 92cae2e | jens-daniel-mueller | 2021-05-28 | Build site. |
| Rmd | 87a8c49 | jens-daniel-mueller | 2021-05-28 | plotted Canyon B max |
| html | 998f4a6 | jens-daniel-mueller | 2021-05-28 | Build site. |
| Rmd | 3c6f0f4 | jens-daniel-mueller | 2021-05-28 | including cases 109-116 |
| html | a28ce5c | jens-daniel-mueller | 2021-05-28 | Build site. |
| Rmd | 2f6d0c0 | jens-daniel-mueller | 2021-05-28 | including cases 109-116 |
| html | 3454b72 | jens-daniel-mueller | 2021-05-28 | Build site. |
| Rmd | 1b46b2a | jens-daniel-mueller | 2021-05-28 | including cases 109-116 |
| html | db22706 | jens-daniel-mueller | 2021-05-28 | Build site. |
| Rmd | 9bb2f7a | jens-daniel-mueller | 2021-05-28 | plot global budgets |
| html | 87481da | jens-daniel-mueller | 2021-05-28 | Build site. |
| Rmd | 154a8fc | jens-daniel-mueller | 2021-05-28 | plot global budgets |
| html | bd4af9d | jens-daniel-mueller | 2021-05-28 | Build site. |
| Rmd | cdd2cc8 | jens-daniel-mueller | 2021-05-28 | plot global budgets |
| html | ee5b15d | jens-daniel-mueller | 2021-05-27 | Build site. |
| Rmd | 83f3e37 | jens-daniel-mueller | 2021-05-27 | plot bias maps |
| html | e8bd251 | jens-daniel-mueller | 2021-05-27 | Build site. |
| Rmd | f642ef2 | jens-daniel-mueller | 2021-05-27 | plot bias maps |
| html | ea0153f | jens-daniel-mueller | 2021-05-27 | Build site. |
| Rmd | 8b38db1 | jens-daniel-mueller | 2021-05-27 | plot bias maps |
| html | cf3365a | jens-daniel-mueller | 2021-05-27 | Build site. |
| Rmd | 2eb7603 | jens-daniel-mueller | 2021-05-27 | plot bias maps |
| html | 57ddd1f | jens-daniel-mueller | 2021-05-27 | Build site. |
| Rmd | f403434 | jens-daniel-mueller | 2021-05-27 | sensitivity case comparison included |
1 GLODAPv2.2020
2 Data preparation
2.1 Load data
Version_IDs <- list.files(
path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
pattern = "v_1")
# 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 = "")
cant_inv <-
read_csv(paste(path_version_data,
"cant_inv.csv",
sep = ""))
cant_inv_mod_truth <-
read_csv(paste(path_version_data,
"cant_inv_mod_truth.csv",
sep = ""))
cant_inv <- bind_rows(cant_inv, cant_inv_mod_truth)
cant_inv <- cant_inv %>%
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$MLR_basins,
dup_era1 = str_c(params_local$dup_era1, collapse = "-"),
MLR_target = params_local$MLR_target,
CANYON_B_max = params_local$CANYON_B_max,
c_star_rmse_max = params_local$c_star_rmse_max,
vif_max = params_local$vif_max
)
cant_inv <- full_join(cant_inv, params_local)
tref <- read_csv(paste(path_version_data,
"tref.csv",
sep = ""))
duration <- sort(tref$median_year)[2] - sort(tref$median_year)[1]
cant_inv <- cant_inv %>%
mutate(duration = duration)
if (exists("cant_inv_all")) {
cant_inv_all <- bind_rows(cant_inv_all, cant_inv)
}
if (!exists("cant_inv_all")) {
cant_inv_all <- cant_inv
}
}[1] "v_101"
[1] "v_102"
[1] "v_103"
[1] "v_104"
[1] "v_105"
[1] "v_106"
[1] "v_107"
[1] "v_108"
[1] "v_109"
[1] "v_110"
[1] "v_111"
[1] "v_112"
[1] "v_113"
[1] "v_114"
[1] "v_115"
[1] "v_116"rm(cant_inv)
cant_inv_all <- cant_inv_all %>%
rename(era_duplication = dup_era1) %>%
mutate(era_duplication = if_else(era_duplication == "2009-2009", "non-overlapping eras", "overlapping eras"))2.2 Format column inventories
cant_inv_all <- cant_inv_all %>%
filter(inv_depth == params_global$inventory_depth_standard)cant_inv_all_bias <- cant_inv_all %>%
select(lat, lon, data_source, cant_inv, Version_ID,
era_duplication, MLR_basins,
MLR_target, CANYON_B_max, vif_max, c_star_rmse_max) %>%
pivot_wider(names_from = data_source,
values_from = cant_inv) %>%
mutate(cant_bias = mod - mod_truth) %>%
drop_na()2.3 Calculate budgets
cant_inv_budget <- cant_inv_all %>%
mutate(surface_area = earth_surf(lat, lon),
cant_inv_grid = cant_inv*surface_area,
cant_pos_inv_grid = cant_pos_inv*surface_area) %>%
group_by(basin_AIP, data_source,
Version_ID, MLR_basins,
era_duplication, duration,
MLR_target, CANYON_B_max, vif_max, c_star_rmse_max) %>%
summarise(cant_total = sum(cant_inv_grid)*12*1e-15,
cant_total = round(cant_total,1),
cant_pos_total = sum(cant_pos_inv_grid)*12*1e-15,
cant_pos_total = round(cant_pos_total,1)) %>%
ungroup()
cant_inv_budget %>%
group_by(data_source, Version_ID) %>%
summarise(cant_total = sum(cant_total),
cant_total = round(cant_total,1),
cant_pos_total = sum(cant_pos_total),
cant_pos_total = round(cant_pos_total,1),
cant_total_rate = cant_total / duration,
cant_pos_total_rate = cant_pos_total / duration) %>%
ungroup()# A tibble: 144 x 6
data_source Version_ID cant_total cant_pos_total cant_total_rate
<chr> <chr> <dbl> <dbl> <dbl>
1 mod v_101 14.3 16 1.79
2 mod v_101 14.3 16 1.79
3 mod v_101 14.3 16 1.79
4 mod v_102 19.2 20.3 2.4
5 mod v_102 19.2 20.3 2.4
6 mod v_102 19.2 20.3 2.4
7 mod v_103 18.8 20.1 2.35
8 mod v_103 18.8 20.1 2.35
9 mod v_103 18.8 20.1 2.35
10 mod v_104 17.2 18 2.15
# … with 134 more rows, and 1 more variable: cant_pos_total_rate <dbl>3 MLR regions and era overlap
3.1 Column inventories
cant_inv_all_bias_sub <- cant_inv_all_bias %>%
filter(Version_ID %in% Version_IDs[1:8])
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "obs",
col = "divergent",
subtitle_text = "data_source: observations") +
facet_grid(MLR_basins ~ era_duplication)
| Version | Author | Date |
|---|---|---|
| 998f4a6 | jens-daniel-mueller | 2021-05-28 |
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "cant_bias",
col = "divergent",
subtitle_text = "data_source: mod - mod_truth") +
facet_grid(MLR_basins ~ era_duplication)
rm(cant_inv_all_bias_sub)3.2 Budgets
3.2.1 Regional
cant_inv_budget_sub <- cant_inv_budget %>%
filter(Version_ID %in% Version_IDs[1:8])
cant_inv_budget_sub %>%
ggplot(aes(data_source, cant_total/duration, fill = basin_AIP)) +
scale_fill_brewer(palette = "PuBuGn") +
geom_col(col = "black") +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1}))) +
facet_grid(MLR_basins ~ era_duplication)
3.2.2 Global
cant_inv_budget_sub %>%
filter(data_source == "obs") %>%
group_by(MLR_basins, era_duplication) %>%
summarise(rate = sum(cant_total/duration)) %>%
ungroup() %>%
ggplot(aes(era_duplication, rate, fill=MLR_basins)) +
geom_bar(stat="identity", position=position_dodge(), col="black") +
scale_y_continuous() +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1})),
x = "") +
scale_fill_brewer(palette = "PuBuGn")
| Version | Author | Date |
|---|---|---|
| 998f4a6 | jens-daniel-mueller | 2021-05-28 |
rm(cant_inv_budget_sub)4 CANYON-B threshold
4.1 Column inventories
cant_inv_all_bias_sub <- cant_inv_all_bias %>%
filter(Version_ID %in% Version_IDs[c(1,11,12)])
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "obs",
col = "divergent",
subtitle_text = "data_source: observations") +
facet_grid(CANYON_B_max ~ .)
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "cant_bias",
col = "bias",
subtitle_text = "data_source: mod - mod_truth") +
facet_grid(CANYON_B_max ~ .)
rm(cant_inv_all_bias_sub)4.2 Budgets
4.2.1 Regional
cant_inv_budget_sub <- cant_inv_budget %>%
filter(Version_ID %in% Version_IDs[c(1,11,12)]) %>%
mutate(CANYON_B_max = as.factor(CANYON_B_max))
cant_inv_budget_sub %>%
ggplot(aes(data_source, cant_total/duration, fill = basin_AIP)) +
scale_fill_brewer(palette = "PuBuGn") +
geom_col(col = "black") +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1}))) +
facet_grid(CANYON_B_max ~ .)
| Version | Author | Date |
|---|---|---|
| 92cae2e | jens-daniel-mueller | 2021-05-28 |
4.2.2 Global
cant_inv_budget_sub %>%
filter(data_source == "obs") %>%
group_by(CANYON_B_max) %>%
summarise(rate = sum(cant_total/duration)) %>%
ungroup() %>%
ggplot(aes(NA, rate, fill = CANYON_B_max)) +
geom_bar(stat="identity", position=position_dodge(), col="black") +
scale_y_continuous() +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1}))) +
scale_fill_brewer(palette = "PuBuGn") +
theme(axis.text.x = element_blank(),
axis.title.x = element_blank(),
axis.ticks.x = element_blank())
| Version | Author | Date |
|---|---|---|
| 92cae2e | jens-daniel-mueller | 2021-05-28 |
rm(cant_inv_budget_sub)5 C* RMSE threshold
5.1 Column inventories
cant_inv_all_bias_sub <- cant_inv_all_bias %>%
filter(Version_ID %in% Version_IDs[c(1,13,14)])
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "obs",
col = "divergent",
subtitle_text = "data_source: observations") +
facet_grid(c_star_rmse_max ~ .)
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "cant_bias",
col = "bias",
subtitle_text = "data_source: mod - mod_truth") +
facet_grid(c_star_rmse_max ~ .)
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
rm(cant_inv_all_bias_sub)5.2 Budgets
5.2.1 Regional
cant_inv_budget_sub <- cant_inv_budget %>%
filter(Version_ID %in% Version_IDs[c(1,13,14)]) %>%
mutate(c_star_rmse_max = as.factor(c_star_rmse_max))
cant_inv_budget_sub %>%
ggplot(aes(data_source, cant_total/duration, fill = basin_AIP)) +
scale_fill_brewer(palette = "PuBuGn") +
geom_col(col = "black") +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1}))) +
facet_grid(c_star_rmse_max ~ .)
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
5.2.2 Global
cant_inv_budget_sub %>%
filter(data_source == "obs") %>%
group_by(c_star_rmse_max) %>%
summarise(rate = sum(cant_total/duration)) %>%
ungroup() %>%
ggplot(aes(NA, rate, fill = c_star_rmse_max)) +
geom_bar(stat="identity", position=position_dodge(), col="black") +
scale_y_continuous() +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1}))) +
scale_fill_brewer(palette = "PuBuGn") +
theme(axis.text.x = element_blank(),
axis.title.x = element_blank(),
axis.ticks.x = element_blank())
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
rm(cant_inv_budget_sub)6 VIF max
6.1 Column inventories
cant_inv_all_bias_sub <- cant_inv_all_bias %>%
filter(Version_ID %in% Version_IDs[c(1,15,16)])
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "obs",
col = "divergent",
subtitle_text = "data_source: observations") +
facet_grid(vif_max ~ .)
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "cant_bias",
col = "bias",
subtitle_text = "data_source: mod - mod_truth") +
facet_grid(vif_max ~ .)
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
rm(cant_inv_all_bias_sub)6.2 Budgets
6.2.1 Regional
cant_inv_budget_sub <- cant_inv_budget %>%
filter(Version_ID %in% Version_IDs[c(1,15,16)]) %>%
mutate(vif_max = as.factor(vif_max))
cant_inv_budget_sub %>%
ggplot(aes(data_source, cant_total/duration, fill = basin_AIP)) +
scale_fill_brewer(palette = "PuBuGn") +
geom_col(col = "black") +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1}))) +
facet_grid(vif_max ~ .)
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
6.2.2 Global
cant_inv_budget_sub %>%
filter(data_source == "obs") %>%
group_by(vif_max) %>%
summarise(rate = sum(cant_total/duration)) %>%
ungroup() %>%
ggplot(aes(NA, rate, fill = vif_max)) +
geom_bar(stat="identity", position=position_dodge(), col="black") +
scale_y_continuous() +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1}))) +
scale_fill_brewer(palette = "PuBuGn") +
theme(axis.text.x = element_blank(),
axis.title.x = element_blank(),
axis.ticks.x = element_blank())
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
rm(cant_inv_budget_sub)7 MLR target variable
7.1 Column inventories
cant_inv_all_bias_sub <- cant_inv_all_bias %>%
filter(Version_ID %in% Version_IDs[c(1,9,10)])
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "obs",
col = "divergent",
subtitle_text = "data_source: observations") +
facet_grid(MLR_target ~ .)
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "cant_bias",
col = "bias",
subtitle_text = "data_source: mod - mod_truth") +
facet_grid(MLR_target ~ .)
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
rm(cant_inv_all_bias_sub)7.2 Budgets
7.2.1 Regional
cant_inv_budget_sub <- cant_inv_budget %>%
filter(Version_ID %in% Version_IDs[c(1,9,10)]) %>%
mutate(MLR_target = as.factor(MLR_target))
cant_inv_budget_sub %>%
ggplot(aes(data_source, cant_total/duration, fill = basin_AIP)) +
scale_fill_brewer(palette = "PuBuGn") +
geom_col(col = "black") +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1}))) +
facet_grid(MLR_target ~ .)
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
7.2.2 Global
cant_inv_budget_sub %>%
filter(data_source == "obs") %>%
group_by(MLR_target) %>%
summarise(rate = sum(cant_total/duration)) %>%
ungroup() %>%
ggplot(aes(NA, rate, fill = MLR_target)) +
geom_bar(stat="identity", position=position_dodge(), col="black") +
scale_y_continuous() +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1}))) +
scale_fill_brewer(palette = "PuBuGn") +
theme(axis.text.x = element_blank(),
axis.title.x = element_blank(),
axis.ticks.x = element_blank())
| Version | Author | Date |
|---|---|---|
| 878aef7 | jens-daniel-mueller | 2021-05-28 |
rm(cant_inv_budget_sub)8 GLODAPv2.2021 prerelease
9 Data preparation
9.1 Load data
cant_inv_all <- cant_inv_all %>%
select(-era_duplication) %>%
mutate(GLODAPv2_version = "2020")
Version_IDs <- list.files(
path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
pattern = "v_2")
# 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 = "")
cant_inv <-
read_csv(paste(path_version_data,
"cant_inv.csv",
sep = ""))
cant_inv_mod_truth <-
read_csv(paste(path_version_data,
"cant_inv_mod_truth.csv",
sep = ""))
cant_inv <- bind_rows(cant_inv, cant_inv_mod_truth)
cant_inv <- cant_inv %>%
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,
MLR_target = params_local$MLR_target,
CANYON_B_max = params_local$CANYON_B_max,
c_star_rmse_max = params_local$c_star_rmse_max,
vif_max = params_local$vif_max,
GLODAPv2_version = params_local$GLODAPv2_version
)
cant_inv <- full_join(cant_inv, params_local)
tref <- read_csv(paste(path_version_data,
"tref.csv",
sep = ""))
duration <- sort(tref$median_year)[2] - sort(tref$median_year)[1]
cant_inv <- cant_inv %>%
mutate(duration = duration)
if (exists("cant_inv_all")) {
cant_inv_all <- bind_rows(cant_inv_all, cant_inv)
}
if (!exists("cant_inv_all")) {
cant_inv_all <- cant_inv
}
}[1] "v_201"
[1] "v_202"
[1] "v_203"
[1] "v_204"rm(cant_inv)9.2 Format column inventories
cant_inv_all <- cant_inv_all %>%
filter(inv_depth == params_global$inventory_depth_standard)cant_inv_all_bias <- cant_inv_all %>%
select(lat, lon, data_source, cant_inv, Version_ID,
GLODAPv2_version, MLR_basins,
MLR_target, CANYON_B_max, vif_max, c_star_rmse_max) %>%
pivot_wider(names_from = data_source,
values_from = cant_inv) %>%
mutate(cant_bias = mod - mod_truth) %>%
drop_na()9.3 Calculate budgets
cant_inv_budget <- cant_inv_all %>%
mutate(surface_area = earth_surf(lat, lon),
cant_inv_grid = cant_inv*surface_area,
cant_pos_inv_grid = cant_pos_inv*surface_area) %>%
group_by(basin_AIP, data_source,
Version_ID, MLR_basins,
GLODAPv2_version, duration,
MLR_target, CANYON_B_max, vif_max, c_star_rmse_max) %>%
summarise(cant_total = sum(cant_inv_grid)*12*1e-15,
cant_total = round(cant_total,1),
cant_pos_total = sum(cant_pos_inv_grid)*12*1e-15,
cant_pos_total = round(cant_pos_total,1)) %>%
ungroup()
cant_inv_budget %>%
group_by(data_source, Version_ID) %>%
summarise(cant_total = sum(cant_total),
cant_total = round(cant_total,1),
cant_pos_total = sum(cant_pos_total),
cant_pos_total = round(cant_pos_total,1),
cant_total_rate = cant_total / duration,
cant_pos_total_rate = cant_pos_total / duration) %>%
ungroup()# A tibble: 180 x 6
data_source Version_ID cant_total cant_pos_total cant_total_rate
<chr> <chr> <dbl> <dbl> <dbl>
1 mod v_101 14.3 16 1.79
2 mod v_101 14.3 16 1.79
3 mod v_101 14.3 16 1.79
4 mod v_102 19.2 20.3 2.4
5 mod v_102 19.2 20.3 2.4
6 mod v_102 19.2 20.3 2.4
7 mod v_103 18.8 20.1 2.35
8 mod v_103 18.8 20.1 2.35
9 mod v_103 18.8 20.1 2.35
10 mod v_104 17.2 18 2.15
# … with 170 more rows, and 1 more variable: cant_pos_total_rate <dbl>10 MLR regions and era overlap
10.1 Column inventories
cant_inv_all_bias_sub <- cant_inv_all_bias %>%
filter(Version_ID %in% c("v_101", "v_102", "v_103", "v_104",
"v_201", "v_202", "v_203", "v_204"))
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "obs",
col = "divergent",
subtitle_text = "data_source: observations") +
facet_grid(MLR_basins ~ GLODAPv2_version)
| Version | Author | Date |
|---|---|---|
| 4d8b4e7 | jens-daniel-mueller | 2021-06-02 |
cant_inv_all_bias_sub %>%
p_map_cant_inv(var = "cant_bias",
col = "divergent",
subtitle_text = "data_source: mod - mod_truth") +
facet_grid(MLR_basins ~ GLODAPv2_version)
| Version | Author | Date |
|---|---|---|
| 4d8b4e7 | jens-daniel-mueller | 2021-06-02 |
10.2 Budgets
10.2.1 Regional
cant_inv_budget_sub <- cant_inv_budget %>%
filter(Version_ID %in% unique(cant_inv_all_bias_sub$Version_ID))
cant_inv_budget_sub %>%
ggplot(aes(data_source, cant_total/duration, fill = basin_AIP)) +
scale_fill_brewer(palette = "PuBuGn") +
geom_col(col = "black") +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1}))) +
facet_grid(MLR_basins ~ GLODAPv2_version)
| Version | Author | Date |
|---|---|---|
| 4d8b4e7 | jens-daniel-mueller | 2021-06-02 |
10.2.2 Global
cant_inv_budget_sub %>%
filter(data_source == "obs") %>%
group_by(MLR_basins, GLODAPv2_version) %>%
summarise(rate = sum(cant_total/duration)) %>%
ungroup() %>%
ggplot(aes(GLODAPv2_version, rate, fill=MLR_basins)) +
geom_bar(stat="identity", position=position_dodge(), col="black") +
scale_y_continuous() +
labs(y = expression(Uptake~rate ~ (PgC ~ yr ^ {-1})),
x = "") +
scale_fill_brewer(palette = "PuBuGn")
| Version | Author | Date |
|---|---|---|
| 4d8b4e7 | jens-daniel-mueller | 2021-06-02 |
rm(cant_inv_budget_sub)
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] marelac_2.1.10 shape_1.4.5 metR_0.9.0 scico_1.2.0
[5] patchwork_1.1.1 collapse_1.5.0 forcats_0.5.0 stringr_1.4.0
[9] dplyr_1.0.5 purrr_0.3.4 readr_1.4.0 tidyr_1.1.2
[13] tibble_3.0.4 ggplot2_3.3.3 tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] httr_1.4.2 jsonlite_1.7.1 modelr_0.1.8
[4] assertthat_0.2.1 blob_1.2.1 cellranger_1.1.0
[7] yaml_2.2.1 pillar_1.4.7 backports_1.1.10
[10] lattice_0.20-41 glue_1.4.2 RcppEigen_0.3.3.7.0
[13] digest_0.6.27 RColorBrewer_1.1-2 promises_1.1.1
[16] checkmate_2.0.0 rvest_0.3.6 colorspace_1.4-1
[19] htmltools_0.5.0 httpuv_1.5.4 Matrix_1.2-18
[22] pkgconfig_2.0.3 broom_0.7.5 seacarb_3.2.14
[25] haven_2.3.1 scales_1.1.1 whisker_0.4
[28] later_1.1.0.1 git2r_0.27.1 farver_2.0.3
[31] generics_0.0.2 ellipsis_0.3.1 withr_2.3.0
[34] cli_2.1.0 magrittr_1.5 crayon_1.3.4
[37] readxl_1.3.1 evaluate_0.14 fs_1.5.0
[40] fansi_0.4.1 xml2_1.3.2 RcppArmadillo_0.10.1.2.0
[43] oce_1.2-0 tools_4.0.3 data.table_1.13.2
[46] hms_0.5.3 lifecycle_1.0.0 munsell_0.5.0
[49] reprex_0.3.0 gsw_1.0-5 compiler_4.0.3
[52] rlang_0.4.10 grid_4.0.3 rstudioapi_0.11
[55] labeling_0.4.2 rmarkdown_2.5 testthat_2.3.2
[58] gtable_0.3.0 DBI_1.1.0 R6_2.5.0
[61] lubridate_1.7.9 knitr_1.30 utf8_1.1.4
[64] rprojroot_2.0.2 stringi_1.5.3 parallel_4.0.3
[67] Rcpp_1.0.5 vctrs_0.3.5 dbplyr_1.4.4
[70] tidyselect_1.1.0 xfun_0.18