This loads data from FluxDataKit.
df <- read_rds("~/data/FluxDataKit/rsofun_driver_data_clean.rds")
df_fr_pue <- df |>
filter(sitename == "FR-Pue") |>
select(forcing) |>
unnest(forcing)
GPP in years 2013 and 2014 is ominously low.
ggplot(data = df_fr_pue) +
geom_line(
aes(
date,
gpp
),
colour = "black"
) +
theme_classic() +
theme(panel.grid.major.y = element_line()) +
labs(
x = 'Date',
y = expression(paste("GPP (g C m"^-2, "s"^-1, ")"))
)
… or due to anomalously low MODIS FPAR?
Derive average light use efficiency per month.
df_lue <- df_fr_pue |>
filter(temp > 5) |>
mutate(yr = lubridate::year(date),
mo = lubridate::month(date),
apar = fapar * ppfd) |>
group_by(yr, mo) |>
summarise(gpp = mean(gpp),
apar = mean(apar)) |>
mutate(lue = gpp/apar) |>
mutate(date = lubridate::ymd(
paste0(
as.character(yr),
"-",
as.character(mo),
"-15"
)
))
## `summarise()` has grouped output by 'yr'. You can override using the `.groups`
## argument.
ggplot(data = df_lue) +
geom_vline(xintercept = seq(ymd('2000-01-01'),ymd('2015-01-01'), by = '1 year'),
color = "grey80") +
geom_line(
aes(
date,
lue
),
colour = "black"
) +
theme_classic() +
theme(panel.grid.major.y = element_line()) +
labs(
x = 'Date',
y = expression(paste("LUE (g C m mol"^-1,")"))
)
More data for years 2021-2022 here. How to get data for years in between, such that we would have 2000-2022? Then, there is more data from release ICOS release 2023-1.