ERA5 data can be used to train, evaluate and forecast phenology models (using CMIP routines). The data used in the download sections is ERA5 land which is re-analysis data at a 10km resolution.
# ERA5 example
pr_dl_era5(
path = "~/Desktop",
user = "2088",
product = "era5",
extent = c(
50.73149477111302,
-7.08887567473501,
40.365567456020266,
12.748594284373073
)
)
# ERA5-land example
pr_dl_era5(
path = "~/Desktop",
user = "2088",
product = "land",
file = "era5-land.nc",
extent = c(
48.345183009475015,
4.782986565238425,
45.64153500799514,
11.44515031394129
)
)
# format ERA5 data for upscaling
data <- pr_fm_era5(
path = "~/Desktop/",
file = "era5-land.nc",
year = 2019
)
# load the included data using
data("phenocam_DB")
# optimize model parameters
# using daymet data for training
set.seed(1234)
optim.par <- pr_fit(
data = phenocam_DB,
cost = rmse,
model = "TT",
method = "GenSA"
)
output <- pr_predict(
optim.par$par,
data = data,
model = "TT"
)
raster::plot(output)
maps::map("world", add = TRUE)