Analysis of dcant budgets
Jens Daniel Müller
19 August, 2021
Last updated: 2021-08-19
Checks: 7 0
Knit directory: emlr_obs_v_XXX/
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| html | 2477316 | jens-daniel-mueller | 2021-07-23 | rebuild: surface dcant mapping seperate |
| html | c9ccc00 | jens-daniel-mueller | 2021-07-22 | Build site. |
| Rmd | 6a7f226 | jens-daniel-mueller | 2021-07-22 | surface dcant mapping seperate |
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| html | 971ce87 | jens-daniel-mueller | 2021-07-13 | Build site. |
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| html | 7a8d5f8 | jens-daniel-mueller | 2021-06-15 | Build site. |
| Rmd | 3695731 | jens-daniel-mueller | 2021-06-15 | included budget assesment |
| html | e0660fe | jens-daniel-mueller | 2021-06-15 | Build site. |
| Rmd | 430b829 | jens-daniel-mueller | 2021-06-15 | included budget assesment |
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| html | 2cbe18c | jens-daniel-mueller | 2021-06-10 | added zonal mean section control plots |
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| html | 50290e8 | jens-daniel-mueller | 2021-04-16 | overlapping eras |
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| Rmd | 82df560 | jens-daniel-mueller | 2021-04-16 | corrected tref assignment |
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| Rmd | 296db5c | jens-daniel-mueller | 2021-04-07 | included model data |
1 Version ID
The results displayed on this site correspond to the Version_ID: v_XXX
2 Data sources
dcant estimates from this sensitivity case:
- Mean and SD per grid cell (lat, lon, depth)
- Zonal mean and SD (basin, lat, depth)
- Inventories (lat, lon)
# integrated per basin_AIP
dcant_budget_basin_AIP <-
read_csv(paste(path_version_data,
"dcant_budget_basin_AIP.csv",
sep = "")) %>%
filter(method == "total") %>%
select(-method)
dcant_budget_basin_AIP_mod_truth <-
read_csv(paste(
path_version_data,
"dcant_budget_basin_AIP_mod_truth.csv",
sep = ""
)) %>%
filter(method == "total") %>%
select(-method)
dcant_budget_basin_AIP <- bind_rows(dcant_budget_basin_AIP,
dcant_budget_basin_AIP_mod_truth)
rm(dcant_budget_basin_AIP_mod_truth)
# globally integrated
dcant_budget_global <-
read_csv(paste(path_version_data,
"dcant_budget_global.csv",
sep = "")) %>%
filter(method == "total") %>%
select(-method)
dcant_budget_global_mod_truth <-
read_csv(paste(
path_version_data,
"dcant_budget_global_mod_truth.csv",
sep = ""
)) %>%
filter(method == "total") %>%
select(-method)
dcant_budget_global <- bind_rows(dcant_budget_global,
dcant_budget_global_mod_truth)
rm(dcant_budget_global_mod_truth)
# reference year
tref <-
read_csv(paste(path_version_data,
"tref.csv",
sep = ""))3 Time periods
tref[38;5;246m# A tibble: 2 × 4[39m
era median_year start end
[3m[38;5;246m<chr>[39m[23m [3m[38;5;246m<dbl>[39m[23m [3m[38;5;246m<dbl>[39m[23m [3m[38;5;246m<dbl>[39m[23m
[38;5;250m1[39m 2000-2009 [4m2[24m004 [4m2[24m000 [4m2[24m009
[38;5;250m2[39m 2010-2019 [4m2[24m014 [4m2[24m010 [4m2[24m019duration <- sort(tref$median_year)[2] - sort(tref$median_year)[1]
duration[1] 104 Global
4.1 Standard depth
Results integrated over the upper 3000 m
dcant_budget_global %>%
filter(inv_depth == params_global$inventory_depth_standard) %>%
ggplot(aes(estimate, value, fill = data_source)) +
scale_fill_brewer(palette = "Dark2") +
geom_col(position = position_dodge2())
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
dcant_budget_global %>%
filter(inv_depth == params_global$inventory_depth_standard) %>%
select(-inv_depth) %>%
pivot_wider(names_from = estimate,
values_from = value) %>%
gt(
groupname_col = c("data_source")
) %>%
summary_rows(groups = TRUE,
fns = list(total = "sum"))| dcant | dcant_pos |
|---|---|
| mod | |
| 23.128 | 23.848 |
| obs | |
| 33.247 | 34.330 |
| mod_truth | |
| 20.722 | 20.861 |
dcant_budget_global_bias <- dcant_budget_global %>%
filter(data_source %in% c("mod", "mod_truth")) %>%
select(data_source, inv_depth, estimate, value) %>%
pivot_wider(names_from = data_source,
values_from = value) %>%
mutate(dcant_bias = mod - mod_truth,
dcant_bias_rel = dcant_bias / mod_truth * 100)
dcant_budget_global_bias %>%
filter(inv_depth == params_global$inventory_depth_standard) %>%
ggplot(aes(dcant_bias, estimate)) +
geom_vline(xintercept = 0) +
geom_col() +
scale_fill_brewer(palette = "Dark2")
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
dcant_budget_global_bias %>%
filter(inv_depth == params_global$inventory_depth_standard) %>%
ggplot(aes(dcant_bias_rel, estimate)) +
geom_vline(xintercept = 0) +
geom_col() +
scale_fill_brewer(palette = "Dark2")
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
dcant_budget_global_bias %>%
filter(inv_depth == params_global$inventory_depth_standard) %>%
ggplot() +
geom_col(aes(estimate, mod,
fill = "eMLR")) +
geom_col(aes(estimate, mod_truth,
col = "truth"),
fill = "transparent") +
scale_fill_manual(values = "grey60") +
scale_color_manual(values = c("red", "red")) +
theme(legend.title = element_blank()) +
labs(y = "value")
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
# geom_segment(aes(
# x = estimate,
# y = mod,
# xend = estimate,
# yend = mod_truth,
# col = "truth"
# )) +
# geom_point(aes(x = estimate,
# y = mod_truth,
# col = "truth"))4.2 Other depths
Results integrated over the upper 100, 500, 1000, 3000, 10^{4} m
dcant_budget_global <- dcant_budget_global %>%
mutate(inv_depth = as.factor(inv_depth))
dcant_budget_global %>%
ggplot() +
scale_fill_viridis_d() +
geom_col(aes(data_source, value, fill = inv_depth),
position = position_dodge2()) +
facet_grid(. ~ estimate, scales = "free_y")
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
dcant_budget_global %>%
pivot_wider(names_from = estimate,
values_from = value) %>%
gt(
groupname_col = c("data_source", "inv_depth"),
row_group.sep = " | Depth: "
) %>%
summary_rows(groups = TRUE,
fns = list(total = "sum"))| dcant | dcant_pos |
|---|---|
| mod | Depth: 100 | |
| 4.098 | 4.098 |
| mod | Depth: 500 | |
| 14.034 | 14.046 |
| mod | Depth: 1000 | |
| 18.869 | 18.911 |
| mod | Depth: 3000 | |
| 23.128 | 23.848 |
| mod | Depth: 10000 | |
| 23.849 | 25.046 |
| obs | Depth: 100 | |
| 4.706 | 4.706 |
| obs | Depth: 500 | |
| 16.001 | 16.079 |
| obs | Depth: 1000 | |
| 22.903 | 23.127 |
| obs | Depth: 3000 | |
| 33.247 | 34.330 |
| obs | Depth: 10000 | |
| 37.379 | 39.128 |
| mod_truth | Depth: 100 | |
| 3.710 | 3.710 |
| mod_truth | Depth: 500 | |
| 13.589 | 13.596 |
| mod_truth | Depth: 1000 | |
| 18.322 | 18.338 |
| mod_truth | Depth: 3000 | |
| 20.722 | 20.861 |
| mod_truth | Depth: 10000 | |
| 21.055 | 21.220 |
dcant_budget_global_bias %>%
ggplot(aes(dcant_bias, estimate)) +
geom_vline(xintercept = 0) +
geom_col() +
scale_fill_brewer(palette = "Dark2") +
facet_grid(inv_depth ~ .)
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
dcant_budget_global_bias %>%
ggplot(aes(dcant_bias_rel, estimate)) +
geom_vline(xintercept = 0) +
geom_col(position = "dodge") +
scale_fill_brewer(palette = "Dark2") +
facet_grid(inv_depth ~ .)
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
dcant_budget_global_bias %>%
ggplot() +
geom_vline(xintercept = 0) +
geom_col(aes(mod, estimate, fill = "eMLR"),
position = "dodge") +
geom_col(aes(mod_truth, estimate,
col = "truth"),
fill = "transparent") +
scale_fill_manual(values = "grey60") +
scale_color_manual(values = c("red", "red")) +
theme(legend.title = element_blank()) +
labs(x = "value") +
facet_grid(inv_depth ~ .)
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
5 Basin AIP
5.1 Standard depth
Results integrated over the upper 3000 m
dcant_budget_basin_AIP %>%
filter(inv_depth == params_global$inventory_depth_standard) %>%
ggplot(aes(estimate, value, fill=basin_AIP)) +
scale_fill_brewer(palette = "Dark2") +
geom_col() +
facet_grid(~data_source)
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
dcant_budget_basin_AIP %>%
filter(inv_depth == params_global$inventory_depth_standard) %>%
pivot_wider(names_from = estimate,
values_from = value) %>%
gt(
rowname_col = "basin_AIP",
groupname_col = c("data_source", "inv_depth"),
row_group.sep = " | Depth: "
) %>%
summary_rows(groups = TRUE,
fns = list(total = "sum"))| dcant | dcant_pos | |
|---|---|---|
| mod | Depth: 3000 | ||
| Indian | 6.795 | 6.892 |
| Pacific | 10.696 | 11.117 |
| Atlantic | 5.636 | 5.839 |
| total | 23.13 | 23.85 |
| obs | Depth: 3000 | ||
| Indian | 5.891 | 6.459 |
| Pacific | 17.803 | 18.213 |
| Atlantic | 9.552 | 9.658 |
| total | 33.25 | 34.33 |
| mod_truth | Depth: 3000 | ||
| Indian | 5.604 | 5.621 |
| Pacific | 10.011 | 10.115 |
| Atlantic | 5.108 | 5.126 |
| total | 20.72 | 20.86 |
dcant_budget_basin_AIP_bias <- dcant_budget_basin_AIP %>%
filter(data_source %in% c("mod", "mod_truth")) %>%
select(data_source, basin_AIP, inv_depth, estimate, value) %>%
pivot_wider(names_from = data_source,
values_from = value) %>%
mutate(dcant_bias = mod - mod_truth,
dcant_bias_rel = dcant_bias / mod_truth * 100)
dcant_budget_basin_AIP_bias %>%
filter(inv_depth == params_global$inventory_depth_standard) %>%
ggplot(aes(dcant_bias, estimate, fill=basin_AIP)) +
geom_vline(xintercept = 0) +
geom_col() +
scale_fill_brewer(palette = "Dark2")
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
dcant_budget_basin_AIP_bias %>%
filter(inv_depth == params_global$inventory_depth_standard) %>%
ggplot(aes(dcant_bias_rel, estimate, fill=basin_AIP)) +
geom_vline(xintercept = 0) +
geom_col(position = "dodge") +
scale_fill_brewer(palette = "Dark2")
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
5.2 Other depths
Results integrated over the upper 100, 500, 1000, 3000, 10^{4} m
dcant_budget_basin_AIP %>%
ggplot(aes(data_source, value, fill=basin_AIP)) +
scale_fill_brewer(palette = "Dark2") +
geom_col() +
facet_grid(inv_depth ~ estimate, scales = "free_y")
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
dcant_budget_basin_AIP %>%
pivot_wider(names_from = estimate,
values_from = value) %>%
gt(
rowname_col = "basin_AIP",
groupname_col = c("data_source", "inv_depth"),
row_group.sep = " | Depth: "
) %>%
summary_rows(groups = TRUE,
fns = list(total = "sum"))| dcant | dcant_pos | |
|---|---|---|
| mod | Depth: 100 | ||
| Indian | 0.894 | 0.894 |
| Pacific | 2.157 | 2.157 |
| Atlantic | 1.047 | 1.047 |
| total | 4.10 | 4.10 |
| mod | Depth: 500 | ||
| Indian | 3.219 | 3.227 |
| Pacific | 7.261 | 7.263 |
| Atlantic | 3.554 | 3.555 |
| total | 14.03 | 14.04 |
| mod | Depth: 1000 | ||
| Indian | 4.883 | 4.903 |
| Pacific | 9.391 | 9.410 |
| Atlantic | 4.595 | 4.598 |
| total | 18.87 | 18.91 |
| mod | Depth: 3000 | ||
| Indian | 6.795 | 6.892 |
| Pacific | 10.696 | 11.117 |
| Atlantic | 5.636 | 5.839 |
| total | 23.13 | 23.85 |
| mod | Depth: 10000 | ||
| Indian | 7.004 | 7.161 |
| Pacific | 11.209 | 11.952 |
| Atlantic | 5.635 | 5.933 |
| total | 23.85 | 25.05 |
| obs | Depth: 100 | ||
| Indian | 1.021 | 1.021 |
| Pacific | 2.445 | 2.445 |
| Atlantic | 1.239 | 1.239 |
| total | 4.71 | 4.71 |
| obs | Depth: 500 | ||
| Indian | 3.548 | 3.570 |
| Pacific | 8.112 | 8.157 |
| Atlantic | 4.340 | 4.352 |
| total | 16.00 | 16.08 |
| obs | Depth: 1000 | ||
| Indian | 4.858 | 4.978 |
| Pacific | 11.641 | 11.723 |
| Atlantic | 6.405 | 6.425 |
| total | 22.90 | 23.13 |
| obs | Depth: 3000 | ||
| Indian | 5.891 | 6.459 |
| Pacific | 17.803 | 18.213 |
| Atlantic | 9.552 | 9.658 |
| total | 33.25 | 34.33 |
| obs | Depth: 10000 | ||
| Indian | 6.322 | 7.238 |
| Pacific | 20.258 | 20.803 |
| Atlantic | 10.799 | 11.087 |
| total | 37.38 | 39.13 |
| mod_truth | Depth: 100 | ||
| Indian | 0.796 | 0.796 |
| Pacific | 1.983 | 1.983 |
| Atlantic | 0.930 | 0.930 |
| total | 3.71 | 3.71 |
| mod_truth | Depth: 500 | ||
| Indian | 3.118 | 3.118 |
| Pacific | 7.061 | 7.067 |
| Atlantic | 3.409 | 3.410 |
| total | 13.59 | 13.60 |
| mod_truth | Depth: 1000 | ||
| Indian | 4.652 | 4.652 |
| Pacific | 9.146 | 9.156 |
| Atlantic | 4.523 | 4.530 |
| total | 18.32 | 18.34 |
| mod_truth | Depth: 3000 | ||
| Indian | 5.604 | 5.621 |
| Pacific | 10.011 | 10.115 |
| Atlantic | 5.108 | 5.126 |
| total | 20.72 | 20.86 |
| mod_truth | Depth: 10000 | ||
| Indian | 5.678 | 5.700 |
| Pacific | 10.227 | 10.341 |
| Atlantic | 5.151 | 5.180 |
| total | 21.06 | 21.22 |
dcant_budget_basin_AIP_bias %>%
ggplot(aes(dcant_bias, estimate, fill=basin_AIP)) +
geom_vline(xintercept = 0) +
geom_col() +
scale_fill_brewer(palette = "Dark2") +
facet_grid(inv_depth ~ .)
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
dcant_budget_basin_AIP_bias %>%
ggplot(aes(dcant_bias_rel, estimate, fill=basin_AIP)) +
geom_vline(xintercept = 0) +
geom_col(position = "dodge") +
scale_fill_brewer(palette = "Dark2") +
facet_grid(inv_depth ~ .)
| Version | Author | Date |
|---|---|---|
| 77f4ba7 | jens-daniel-mueller | 2021-08-19 |
| ece96df | jens-daniel-mueller | 2021-08-19 |
| 27c99b8 | jens-daniel-mueller | 2021-08-19 |
| a03f2f0 | jens-daniel-mueller | 2021-08-18 |
| 9335b31 | jens-daniel-mueller | 2021-08-10 |
| 9943b45 | jens-daniel-mueller | 2021-08-10 |
| 0b00a2b | jens-daniel-mueller | 2021-08-09 |
| 755c6b1 | jens-daniel-mueller | 2021-08-09 |
| cd8e0d5 | jens-daniel-mueller | 2021-08-06 |
| 15773a0 | jens-daniel-mueller | 2021-08-06 |
| da61d1a | jens-daniel-mueller | 2021-08-06 |
| 340d731 | jens-daniel-mueller | 2021-08-06 |
| 71546e4 | jens-daniel-mueller | 2021-08-06 |
| 29444a1 | jens-daniel-mueller | 2021-08-05 |
| 42e80c0 | jens-daniel-mueller | 2021-08-04 |
| 48f6eed | jens-daniel-mueller | 2021-08-04 |
| 81a46a4 | jens-daniel-mueller | 2021-08-03 |
| b88c61b | jens-daniel-mueller | 2021-08-03 |
| 0f0d5e5 | jens-daniel-mueller | 2021-08-03 |
6 Write files
dcant_budget_basin_AIP_bias %>%
write_csv(paste(path_version_data,
"dcant_budget_basin_AIP_bias.csv", sep = ""))
dcant_budget_global_bias %>%
write_csv(paste(path_version_data,
"dcant_budget_global_bias.csv", sep = ""))
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] gt_0.2.2 kableExtra_1.3.1 marelac_2.1.10 shape_1.4.5
[5] scales_1.1.1 ggforce_0.3.3 metR_0.9.0 scico_1.2.0
[9] patchwork_1.1.1 collapse_1.5.0 forcats_0.5.0 stringr_1.4.0
[13] dplyr_1.0.5 purrr_0.3.4 readr_1.4.0 tidyr_1.1.3
[17] tibble_3.1.3 ggplot2_3.3.5 tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] fs_1.5.0 lubridate_1.7.9 gsw_1.0-5
[4] RColorBrewer_1.1-2 webshot_0.5.2 httr_1.4.2
[7] rprojroot_2.0.2 tools_4.0.3 backports_1.1.10
[10] utf8_1.1.4 R6_2.5.0 DBI_1.1.0
[13] colorspace_2.0-2 withr_2.3.0 tidyselect_1.1.0
[16] compiler_4.0.3 git2r_0.27.1 cli_3.0.1
[19] rvest_0.3.6 xml2_1.3.2 sass_0.2.0
[22] labeling_0.4.2 checkmate_2.0.0 digest_0.6.27
[25] rmarkdown_2.10 oce_1.2-0 pkgconfig_2.0.3
[28] htmltools_0.5.0 highr_0.8 dbplyr_1.4.4
[31] rlang_0.4.10 readxl_1.3.1 rstudioapi_0.13
[34] farver_2.0.3 generics_0.1.0 jsonlite_1.7.1
[37] magrittr_1.5 Matrix_1.2-18 Rcpp_1.0.5
[40] munsell_0.5.0 fansi_0.4.1 lifecycle_1.0.0
[43] stringi_1.5.3 whisker_0.4 yaml_2.2.1
[46] MASS_7.3-53 grid_4.0.3 blob_1.2.1
[49] parallel_4.0.3 promises_1.1.1 crayon_1.3.4
[52] lattice_0.20-41 haven_2.3.1 hms_0.5.3
[55] seacarb_3.2.14 knitr_1.33 pillar_1.6.2
[58] reprex_0.3.0 glue_1.4.2 evaluate_0.14
[61] RcppArmadillo_0.10.1.2.0 data.table_1.14.0 modelr_0.1.8
[64] vctrs_0.3.8 tweenr_1.0.2 httpuv_1.5.4
[67] testthat_2.3.2 cellranger_1.1.0 gtable_0.3.0
[70] polyclip_1.10-0 assertthat_0.2.1 xfun_0.25
[73] broom_0.7.9 RcppEigen_0.3.3.7.0 later_1.2.0
[76] viridisLite_0.3.0 ellipsis_0.3.2 here_0.1