GLODAPv2_2016: Mapped Climatologies
Jens Daniel Müller
23 December, 2021
Last updated: 2021-12-23
Checks: 7 0
Knit directory: emlr_obs_preprocessing/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 513243c | jens-daniel-mueller | 2021-12-23 | plot regional time series and moving average |
| html | 8cc98a8 | jens-daniel-mueller | 2021-12-13 | Build site. |
| Rmd | bab6472 | jens-daniel-mueller | 2021-12-13 | decadal climatology offset added |
| html | b6d0770 | jens-daniel-mueller | 2021-12-13 | Build site. |
| Rmd | cb88dbc | jens-daniel-mueller | 2021-12-13 | decadal climatology added |
| html | d6c2d11 | jens-daniel-mueller | 2021-11-22 | Build site. |
| Rmd | 5d9ebb2 | jens-daniel-mueller | 2021-11-22 | calculate revelle factor historical |
| html | f2871b9 | jens-daniel-mueller | 2021-11-20 | Build site. |
| html | 0908ee5 | jens-daniel-mueller | 2021-11-15 | Build site. |
| html | 002b89c | jens-daniel-mueller | 2021-10-06 | Build site. |
| Rmd | 2f78646 | jens-daniel-mueller | 2021-10-06 | OceanSODA read-in updated |
| html | 767aa26 | jens-daniel-mueller | 2021-10-06 | Build site. |
| Rmd | 5ed301b | jens-daniel-mueller | 2021-10-06 | OceanSODA read-in updated |
| html | 3a99e0b | jens-daniel-mueller | 2021-10-05 | Build site. |
| Rmd | f36c707 | jens-daniel-mueller | 2021-10-05 | OceanSODA read-in updated |
| html | 5db29f4 | jens-daniel-mueller | 2021-10-05 | Build site. |
| Rmd | caf8c9a | jens-daniel-mueller | 2021-10-05 | OceanSODA read-in updated |
| html | e49875a | jens-daniel-mueller | 2021-07-07 | Build site. |
| html | 6312bd4 | jens-daniel-mueller | 2021-07-07 | Build site. |
| html | 58bc706 | jens-daniel-mueller | 2021-07-06 | Build site. |
| html | f600971 | jens-daniel-mueller | 2021-07-02 | Build site. |
| html | ad81465 | jens-daniel-mueller | 2021-06-17 | Build site. |
| Rmd | 3bc04be | jens-daniel-mueller | 2021-06-17 | derive air sea disequilibrium |
| html | 240c1f4 | jens-daniel-mueller | 2021-06-07 | Build site. |
| Rmd | 2730067 | jens-daniel-mueller | 2021-06-07 | write preprocessed file |
| html | 4df00b5 | jens-daniel-mueller | 2021-06-07 | Build site. |
| Rmd | f16f718 | jens-daniel-mueller | 2021-06-07 | added multi parameter analysis global trends |
| html | 8186273 | jens-daniel-mueller | 2021-06-07 | Build site. |
| Rmd | 663eb4d | jens-daniel-mueller | 2021-06-07 | added multi parameter analysis |
| html | efc80ab | jens-daniel-mueller | 2021-06-07 | Build site. |
| Rmd | 0f42222 | jens-daniel-mueller | 2021-06-07 | improved revelle factor analysis |
| html | 265c4ef | jens-daniel-mueller | 2021-06-04 | Build site. |
| Rmd | 00065c8 | jens-daniel-mueller | 2021-06-04 | included OceanSODA |
1 Read source files
basinmask_5 <- basinmask %>%
filter(MLR_basins == "5") %>%
select(lat, lon, basin)
basinmask <- basinmask %>%
filter(MLR_basins == "2") %>%
select(lat, lon, basin_AIP)1.1 OceanSODA
OceanSODA <-
tidync(paste(
path_updata,
"pco2_oceansoda-ethz/OS-ETHZ-GRaCER-v2021a_1982-2020.nc",
sep = ""
))
OceanSODA <- OceanSODA %>%
hyper_tibble()
OceanSODA <- OceanSODA %>%
mutate(date = as.Date(time, origin = '1982-01-15'),
year = year(date))
OceanSODA <- OceanSODA %>%
select(year, date, lat, lon,
sal = salinity, temp = temperature,
tco2 = dic, talk,
rev_fac = revelle_factor,
pCO2 = spco2,
fgco2)1.2 SeaFlux
path_SeaFlux <-
paste0(path_updata,"pco2_seaflux/")
icefrac <-
tidync(paste0(path_SeaFlux,
"SeaFluxV2021.01_icefrac_1988-2018.nc")) %>%
hyper_tibble()
icefrac <- icefrac %>%
mutate(date = as.Date(time, origin = '1988-01-15'),
year = year(date))
kw <-
tidync(paste0(path_SeaFlux,
"SeaFluxV2021.01_kwScaled16.5cmhr_1988-2018.nc"))
kw <- kw %>%
hyper_filter(wind = wind == "ERA5") %>%
hyper_tibble() %>%
select(-wind)
pCO2atm <-
tidync(paste0(path_SeaFlux,
"SeaFluxV2021.01_pCO2atm_NOAAmbl_ERA5mslp_1988-2018.nc")) %>%
hyper_tibble()
sol <-
tidync(paste0(path_SeaFlux,
"SeaFluxV2021.01_solWeis74.nc")) %>%
hyper_tibble()1.3 Join data
all_variables <- full_join(icefrac, kw)
all_variables <- full_join(all_variables, pCO2atm)
all_variables <- full_join(all_variables, sol)
OceanSODA <- inner_join(all_variables,
OceanSODA)
OceanSODA <- OceanSODA %>%
mutate(lon = if_else(lon < 20, lon + 360, lon))
OceanSODA <- inner_join(OceanSODA, basinmask)
OceanSODA <- OceanSODA %>%
select(-time)1.4 Atm pCO2
# Note: this file is only created downstream in read_CO2_atm.Rmd
co2_atm_reccap2 <-
read_csv(paste(path_preprocessing,
"co2_atm_reccap2.csv",
sep = ""))2 Air-sea disequilibrium
all_variables <- OceanSODA %>%
select(
time_mon = date,
lon,
lat,
spco2 = pCO2,
pco2atm = pCO2atm,
fice = ice,
alpha = sol_Weiss74,
Kw = kw_scaled
) %>%
drop_na()
all_variables <- all_variables %>%
mutate(area = earth_surf(lat = lat))
mol_to_g <- 12.011
P <- 1e-15
cm_to_m <- 100
hr_to_yr <- 24 * 365
unit_conversion_to_PgCyr <- mol_to_g * P * hr_to_yr / cm_to_m
all_variables <- all_variables %>%
mutate(
delta_pco2 = spco2 - pco2atm,
scale = area * Kw * alpha * (1 - fice),
fgco2 = delta_pco2 * scale
)
delta_pco2_monthly <- all_variables %>%
group_by(time_mon) %>%
summarise(
scaling_glob = sum(scale),
fgco2_glob = sum(fgco2),
delta_pco2_glob = fgco2_glob / scaling_glob
) %>%
ungroup() %>%
mutate(fgco2_glob = fgco2_glob * unit_conversion_to_PgCyr)
delta_pco2_annual <- delta_pco2_monthly %>%
mutate(year = year(time_mon)) %>%
group_by(year) %>%
summarise(
scaling_glob = mean(scaling_glob),
fgco2_glob = mean(fgco2_glob),
delta_pco2_glob = mean(delta_pco2_glob)
) %>%
ungroup()
delta_pco2_annual <- delta_pco2_annual %>%
mutate(fgco2_glob_roll = zoo::rollmean(fgco2_glob, 10, fill = NA))
ggplot() +
geom_path(data = delta_pco2_monthly,
aes(decimal_date(time_mon), delta_pco2_glob, col = "monthly")) +
geom_path(data = delta_pco2_annual,
aes(year, delta_pco2_glob, col = "annual")) +
scale_color_brewer(palette = "Set1", name = "Average") +
labs(x = "year")
print(
ggplot() +
geom_path(data = delta_pco2_monthly,
aes(decimal_date(time_mon), fgco2_glob, col = "monthly")) +
geom_path(data = delta_pco2_annual,
aes(year, fgco2_glob, col = "annual")) +
geom_path(data = delta_pco2_annual,
aes(year, fgco2_glob_roll, col = "5yr roll ave")) +
scale_color_brewer(palette = "Set1", name = "Average") +
labs(x = "year")
)
print(ggplot() +
geom_path(data = delta_pco2_annual,
aes(
year,
scaling_glob * unit_conversion_to_PgCyr
)))
print(
ggplot() +
geom_path(
data = delta_pco2_annual,
aes(
year,
scaling_glob * delta_pco2_glob * unit_conversion_to_PgCyr,
col = "scaled"
)
) +
geom_path(data = delta_pco2_annual,
aes(year, fgco2_glob, col = "integrated")) +
scale_color_brewer(palette = "Set1", name = "Estimate") +
scale_y_continuous(name = "Air-sea flux [PgC yr-1]") +
labs(x = "year")
)
3 Compute climatologies
# calculate annual averaged fields
OceanSODA_annual_all <- OceanSODA %>%
mutate(tco2_over_pCO2 = tco2 / pCO2) %>%
group_by(year, lat, lon) %>%
summarise_if(is.numeric, mean, na.rm = TRUE) %>%
ungroup() %>%
mutate(grid_area = earth_surf(lat = lat))
# grid data in space and time, remove data outside grid
OceanSODA_annual <- OceanSODA_annual_all %>%
mutate(
grid_area = earth_surf(lat = lat),
lat_bands = cut(lat, seq(-80, 80, 20)),
decade = cut(year,
seq(1990, 2020, 10),
right = FALSE,
labels = c("1990-1999", "2000-2009", "2010-2019"))
) %>%
drop_na()
# calculate climatological fields
OceanSODA_clim <- OceanSODA_annual %>%
select(-c(grid_area)) %>%
group_by(lat, lon) %>%
summarise_if(is.numeric, mean, na.rm = TRUE) %>%
ungroup()
# calculate decadal climatological fields
OceanSODA_clim_decadal <- OceanSODA_annual %>%
select(-c(grid_area)) %>%
group_by(lat, lon, decade) %>%
summarise_if(is.numeric, mean, na.rm = TRUE) %>%
ungroup()
# calculate area-weighted annual mean within latitude band
OceanSODA_annual_lat <- OceanSODA_annual %>%
pivot_longer(sal:tco2_over_pCO2,
names_to = "parameter",
values_to = "value") %>%
mutate(value_area = value * grid_area) %>%
group_by(year, lat_bands, decade, parameter) %>%
summarise(
area_total = sum(grid_area),
value_area_total = sum(value_area),
value_area_ave = value_area_total / area_total
) %>%
ungroup() %>%
select(-c(area_total,value_area_total))
# fit decadel linear trends per latitude band
OceanSODA_annual_lat_trend <- OceanSODA_annual_lat %>%
nest(data = -c(decade, lat_bands, parameter)) %>%
mutate(tidy = map(data,
~tidy(lm(value_area_ave ~ year, data = .x)))) %>%
select(-data) %>%
unnest(tidy)
# calculate area-weighted annual mean globally
OceanSODA_annual_glob <- OceanSODA_annual %>%
pivot_longer(sal:tco2_over_pCO2,
names_to = "parameter",
values_to = "value") %>%
mutate(value_area = value * grid_area) %>%
group_by(year, decade, parameter) %>%
summarise(
area_total = sum(grid_area),
value_area_total = sum(value_area),
value_area_ave = value_area_total / area_total
) %>%
ungroup() %>%
select(-c(area_total,value_area_total))
# fit decadel linear trends globally
OceanSODA_annual_glob_trend <- OceanSODA_annual_glob %>%
nest(data = -c(decade, parameter)) %>%
mutate(tidy = map(data,
~tidy(lm(value_area_ave ~ year, data = .x)))) %>%
select(-data) %>%
unnest(tidy)
#regionall integrated air sea fluxes
OceanSODA_annual_5 <- left_join(basinmask_5,
OceanSODA_annual_all)
# calculate area-weighted annual mean globally
OceanSODA_annual_5 <- OceanSODA_annual_5 %>%
pivot_longer(sal:tco2_over_pCO2,
names_to = "parameter",
values_to = "value") %>%
mutate(value_area = value * grid_area) %>%
group_by(year, parameter, basin) %>%
summarise(
area_total = sum(grid_area, na.rm = TRUE),
value_area_total = sum(value_area, na.rm = TRUE),
value_area_ave = value_area_total / area_total
) %>%
ungroup() %>%
select(-c(area_total,value_area_total))map +
geom_tile(data = OceanSODA_clim,
aes(lon, lat, fill = as.factor(year)))
pco2_atm_2004 <- co2_atm_reccap2 %>%
filter(year == 2004) %>%
pull(pCO2)
co2_atm_reccap2 <- co2_atm_reccap2 %>%
mutate(delta_pCO2_hist = pCO2 - pco2_atm_2004)
co2_atm_reccap2_decade <- co2_atm_reccap2 %>%
filter(year > 1900) %>%
mutate(year = ymd(paste(year, "-06-01"))) %>%
mutate(decade = floor_date(year, years(10))) %>%
group_by(decade) %>%
summarise(delta_pCO2_hist = mean(delta_pCO2_hist)) %>%
ungroup()
co2_atm_reccap2_decade %>%
ggplot(aes(decade, delta_pCO2_hist)) +
geom_point() +
geom_path()
| Version | Author | Date |
|---|---|---|
| d6c2d11 | jens-daniel-mueller | 2021-11-22 |
OceanSODA_revelle_hist <- expand_grid(
co2_atm_reccap2_decade,
OceanSODA_clim
)
OceanSODA_revelle_hist <- OceanSODA_revelle_hist %>%
mutate(pCO2 = pCO2 + delta_pCO2_hist)
map +
geom_tile(data = OceanSODA_revelle_hist,
aes(lon, lat, fill = pCO2)) +
facet_wrap(~ decade) +
scale_fill_viridis_c()
OceanSODA_revelle_hist <- OceanSODA_revelle_hist %>%
mutate(
rev_fac = buffer(
flag = 24,
var1 = pCO2,
var2 = talk * 1e-6,
S = sal,
T = temp,
P = 0,
k1k2 = "l"
)$BetaD
)
map +
geom_tile(data = OceanSODA_revelle_hist,
aes(lon, lat, fill = rev_fac)) +
facet_wrap(~ decade) +
scale_fill_viridis_c()
OceanSODA_revelle_hist_time_series <- OceanSODA_revelle_hist %>%
mutate(area = earth_surf(lat, lon),
rev_fac_scaled = rev_fac * area) %>%
group_by(decade) %>%
summarise(rev_fac = sum(rev_fac_scaled) / sum(area)) %>%
ungroup()
OceanSODA_revelle_hist_time_series %>%
ggplot(aes(decade, rev_fac))+
geom_point() +
geom_path()
4 Write files
OceanSODA_annual_all %>%
write_csv(paste0(path_preprocessing,
"OceanSODA.csv"))
OceanSODA_clim %>%
write_csv(paste0(path_preprocessing,
"OceanSODA_climatology.csv"))
OceanSODA_revelle_hist_time_series %>%
write_csv(paste0(path_preprocessing,
"OceanSODA_revelle_hist_time_series.csv"))
delta_pco2_annual %>%
select(-c(scaling_glob, fgco2_glob)) %>%
write_csv(paste0(path_preprocessing,
"OceanSODA_disequilibrium_annual.csv"))5 Control plots
map +
geom_raster(data = OceanSODA_annual %>%
filter(year == 2010), aes(lon, lat, fill = lat_bands)) +
scale_fill_brewer(palette = "Spectral") +
labs(title = "Year: 2010")
| Version | Author | Date |
|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
| 002b89c | jens-daniel-mueller | 2021-10-06 |
| 767aa26 | jens-daniel-mueller | 2021-10-06 |
| 3a99e0b | jens-daniel-mueller | 2021-10-05 |
| 5db29f4 | jens-daniel-mueller | 2021-10-05 |
| ad81465 | jens-daniel-mueller | 2021-06-17 |
| 4df00b5 | jens-daniel-mueller | 2021-06-07 |
| 8186273 | jens-daniel-mueller | 2021-06-07 |
map +
geom_raster(data = OceanSODA_annual %>%
filter(year == 2010), aes(lon, lat, fill = grid_area)) +
scale_fill_viridis_c() +
labs(title = "Year: 2010")
| Version | Author | Date |
|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
| 002b89c | jens-daniel-mueller | 2021-10-06 |
| 767aa26 | jens-daniel-mueller | 2021-10-06 |
| 3a99e0b | jens-daniel-mueller | 2021-10-05 |
| 5db29f4 | jens-daniel-mueller | 2021-10-05 |
| ad81465 | jens-daniel-mueller | 2021-06-17 |
| 4df00b5 | jens-daniel-mueller | 2021-06-07 |
| 8186273 | jens-daniel-mueller | 2021-06-07 |
6 Maps
6.1 Climatology
unique(OceanSODA_clim$year)[1] 2004.000 2003.786 2011.000 2008.500 2004.400 2003.045OceanSODA_clim %>%
pivot_longer(sal:tco2_over_pCO2,
names_to = "parameter",
values_to = "value") %>%
group_split(parameter) %>%
# head(1) %>%
map( ~ map +
geom_raster(data = .x,
aes(lon, lat, fill = value)) +
scale_fill_viridis_c(name = unique(.x$parameter)))[[1]]
| Version | Author | Date |
|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
[[3]]
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| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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| b6d0770 | jens-daniel-mueller | 2021-12-13 |
[[5]]
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| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
6.2 Decadal climatology
OceanSODA_clim_decadal %>%
pivot_longer(sal:tco2_over_pCO2,
names_to = "parameter",
values_to = "value") %>%
group_split(parameter) %>%
# head(1) %>%
map( ~ map +
geom_raster(data = .x,
aes(lon, lat, fill = value)) +
scale_fill_viridis_c(name = unique(.x$parameter)) +
facet_grid(decade ~ .))[[1]]
| Version | Author | Date |
|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
[[2]]
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|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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| Version | Author | Date |
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| b6d0770 | jens-daniel-mueller | 2021-12-13 |
6.3 Decadal offset climatology
OceanSODA_clim_decadal_offset <- bind_rows(
OceanSODA_clim_decadal,
OceanSODA_clim %>%
mutate(decade = "value_clim")
)
OceanSODA_clim_decadal_offset <- OceanSODA_clim_decadal_offset %>%
pivot_longer(sal:tco2_over_pCO2,
names_to = "parameter",
values_to = "value") %>%
select(lat, lon, decade, parameter, value) %>%
pivot_wider(names_from = decade,
values_from = value) %>%
pivot_longer(4:6,
names_to = "decade",
values_to = "value_decade") %>%
mutate(offset = value_decade - value_clim)
OceanSODA_clim_decadal_offset %>%
group_split(parameter) %>%
# head(1) %>%
map( ~ map +
geom_raster(data = .x,
aes(lon, lat, fill = offset)) +
scale_fill_divergent(name = unique(.x$parameter)) +
facet_grid(decade ~ .))[[1]]
| Version | Author | Date |
|---|---|---|
| 8cc98a8 | jens-daniel-mueller | 2021-12-13 |
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| 8cc98a8 | jens-daniel-mueller | 2021-12-13 |
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| 8cc98a8 | jens-daniel-mueller | 2021-12-13 |
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| 8cc98a8 | jens-daniel-mueller | 2021-12-13 |
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| 8cc98a8 | jens-daniel-mueller | 2021-12-13 |
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| 8cc98a8 | jens-daniel-mueller | 2021-12-13 |
7 Time series
7.1 5 regions
OceanSODA_annual_5 %>%
group_split(parameter) %>%
# head(1) %>%
map(
~ ggplot(data = .x,
aes(year, value_area_ave, col = basin)) +
scale_color_brewer(palette = "Set1") +
geom_path() +
geom_point() +
labs(y = .x$parameter)
)[[1]]
[[2]]
[[3]]
[[4]]
[[5]]
[[6]]
[[7]]
[[8]]
7.2 Lat bands
OceanSODA_annual_lat %>%
group_split(parameter) %>%
# head(1) %>%
map(
~ ggplot(data = .x,
aes(year, value_area_ave, col = lat_bands)) +
scale_color_brewer(palette = "Spectral") +
geom_path() +
geom_point() +
labs(y = .x$parameter)
)[[1]]
[[2]]
[[3]]
[[4]]
[[5]]
[[6]]
[[7]]
[[8]]
| Version | Author | Date |
|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
8 Decadel trends
8.1 Global
OceanSODA_annual_glob %>%
group_split(parameter) %>%
# head(1) %>%
map(
~ ggplot(data = .x,
aes(year, value_area_ave, col = decade)) +
scale_color_brewer(palette = "Set1") +
geom_point() +
labs(y = .x$parameter) +
geom_smooth(method = "lm", se = FALSE)
)[[1]]
[[2]]
[[3]]
[[4]]
[[5]]
[[6]]
[[7]]
[[8]]
OceanSODA_annual_glob_trend %>%
filter(term == "year") %>%
group_split(parameter) %>%
# head(1) %>%
map(
~ ggplot(data = .x,
aes(decade, estimate)) +
scale_fill_brewer(palette = "Spectral") +
geom_point(shape = 21) +
geom_path() +
labs(y = paste(.x$parameter, "annual change"))
)[[1]]
[[2]]
[[3]]
[[4]]
[[5]]
[[6]]
[[7]]
| Version | Author | Date |
|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
[[8]]
| Version | Author | Date |
|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
8.2 Latitude bands
OceanSODA_annual_lat %>%
group_split(parameter) %>%
# head(1) %>%
map(
~ ggplot(data = .x,
aes(year, value_area_ave, col = decade)) +
scale_color_brewer(palette = "Set1") +
geom_point() +
labs(y = .x$parameter) +
geom_smooth(method = "lm", se = FALSE) +
facet_wrap( ~ lat_bands)
)[[1]]
[[2]]
[[3]]
[[4]]
[[5]]
[[6]]
[[7]]
[[8]]
OceanSODA_annual_lat_trend %>%
filter(term == "year") %>%
group_split(parameter) %>%
# head(1) %>%
map(
~ ggplot(data = .x,
aes(decade, estimate, fill = lat_bands)) +
scale_fill_brewer(palette = "Spectral") +
geom_point(shape = 21) +
geom_path() +
labs(y = paste(.x$parameter, "annual change"))
)[[1]]
[[2]]
[[3]]
[[4]]
[[5]]
[[6]]
[[7]]
| Version | Author | Date |
|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
[[8]]
| Version | Author | Date |
|---|---|---|
| b6d0770 | jens-daniel-mueller | 2021-12-13 |
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] zoo_1.8-8 seacarb_3.2.14 oce_1.2-0 gsw_1.0-5
[5] testthat_2.3.2 broom_0.7.9 marelac_2.1.10 shape_1.4.5
[9] lubridate_1.7.9 tidync_0.2.4 ggforce_0.3.3 metR_0.9.0
[13] scico_1.2.0 patchwork_1.1.1 collapse_1.5.0 forcats_0.5.0
[17] stringr_1.4.0 dplyr_1.0.5 purrr_0.3.4 readr_1.4.0
[21] tidyr_1.1.3 tibble_3.1.3 ggplot2_3.3.5 tidyverse_1.3.0
[25] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] nlme_3.1-149 fs_1.5.0 RColorBrewer_1.1-2
[4] httr_1.4.2 rprojroot_2.0.2 tools_4.0.3
[7] backports_1.1.10 bslib_0.2.5.1 utf8_1.1.4
[10] R6_2.5.0 mgcv_1.8-33 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 RNetCDF_2.4-2 xml2_1.3.2
[22] labeling_0.4.2 sass_0.4.0 scales_1.1.1
[25] checkmate_2.0.0 digest_0.6.27 rmarkdown_2.10
[28] pkgconfig_2.0.3 htmltools_0.5.1.1 highr_0.8
[31] dbplyr_1.4.4 rlang_0.4.11 readxl_1.3.1
[34] rstudioapi_0.13 jquerylib_0.1.4 generics_0.1.0
[37] farver_2.0.3 jsonlite_1.7.1 magrittr_1.5
[40] ncmeta_0.3.0 Matrix_1.2-18 Rcpp_1.0.5
[43] munsell_0.5.0 fansi_0.4.1 lifecycle_1.0.0
[46] stringi_1.5.3 whisker_0.4 yaml_2.2.1
[49] MASS_7.3-53 grid_4.0.3 blob_1.2.1
[52] parallel_4.0.3 promises_1.1.1 crayon_1.3.4
[55] lattice_0.20-41 splines_4.0.3 haven_2.3.1
[58] hms_0.5.3 knitr_1.33 pillar_1.6.2
[61] reprex_0.3.0 glue_1.4.2 evaluate_0.14
[64] RcppArmadillo_0.10.1.2.0 data.table_1.14.0 modelr_0.1.8
[67] vctrs_0.3.8 tweenr_1.0.2 httpuv_1.5.4
[70] cellranger_1.1.0 gtable_0.3.0 polyclip_1.10-0
[73] assertthat_0.2.1 xfun_0.25 RcppEigen_0.3.3.7.0
[76] later_1.2.0 viridisLite_0.3.0 ncdf4_1.17
[79] ellipsis_0.3.2