Philosophy
Overall, the package uses the {tidyverse} data paradigm (Wickham, 2017), using nested data frames (tibbles) to store model input and output, and validation data. Where possible the package uses a consistent ontogeny in terms of variables and data structures used.
Drivers data (inputs)
A drivers object is used as unique input to the models, consisting of
a list of sites. Each site (i.e. row) contains the following data: -
sitename: site name - site_info: location
specific site information (nested tibble) - params_soil:
soil characteristics for BiomeE model (nested tibble) -
params_siml: simulation parameter settings (nested tibble)
- forcing: environmental forcing data (nested tibble)
Each of the provided demo drivers contain only one sample site:
# call to the included p-model demo drivers
rsofun::p_model_drivers
#> # A tibble: 1 × 4
#> sitename params_siml site_info forcing
#> <chr> <list> <list> <list>
#> 1 FR-Pue <tibble [1 × 11]> <tibble [1 × 4]> <tibble [2,190 × 13]>
# call to the included BiomeE (p-model) demo drivers
rsofun::biomee_p_model_drivers
#> # A tibble: 1 × 9
#> sitename site_info params_siml params_tile params_species params_soil
#> <chr> <list> <list> <list> <list> <list>
#> 1 CH-Lae <tibble [1 × 14]> <tibble> <tibble> <tibble> <tibble>
#> # ℹ 3 more variables: init_cohort <list>, init_soil <list>, forcing <list>
# call to the included BiomeE (gs leuning) demo drivers
rsofun::biomee_gs_leuning_drivers
#> # A tibble: 1 × 9
#> sitename site_info params_siml params_tile params_species params_soil
#> <chr> <list> <list> <list> <list> <list>
#> 1 CH-Lae <tibble [1 × 14]> <tibble> <tibble> <tibble> <tibble>
#> # ℹ 3 more variables: init_cohort <list>, init_soil <list>, forcing <list>Nested data structures can be accessed like this:
# Accessing the site information for the first site
rsofun::biomee_gs_leuning_drivers$site_info[[1]]
#> # A tibble: 1 × 14
#> sitename lon lat elv year_start year_end classid c4 whc
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <lgl>
#> 1 CH-Lae 8.36 47.5 700 2004 2014 NA FALSE NA
#> # ℹ 5 more variables: koeppen_code <lgl>, igbp_land_use <chr>,
#> # plant_functional_type <chr>, date_start <date>, date_end <date>Specific data for each model
Each model has its own specificities when it comes to the set of simulation parameters and forcing data. Please refer to the documentation for each model for an exhaustive list of parameters and data required by the model.
- P-model:
?run_pmodel_f_bysite - BiomeE:
?run_biomee_f_bysite
Forcing data
The forcing data contains environmental variables commonly available at fluxnet (reference) or ICOS atmospheric gas exchange measurement locations or gathered from various gridded or re-analysis sources. Forcing data are expected to be sequences of complete years (each starting on January 1st and ending on december 31st), where leap days are excluded (February 29th should not be present).
Each model has a specific forcing data resolution: - P-model: daily - BiomeE (p-model): daily - BiomeE (gs leuning): hourly
Forcing data present in the demo drivers can be used as examples:
# Detailed look at the forcing data for the P-model
rsofun::p_model_drivers$forcing[[1]]
#> # A tibble: 2,190 × 13
#> date temp vpd ppfd netrad patm snow rain tmin tmax fapar
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2007-01-01 10.0 183. 1.06e-4 4.17 9.99e4 0 2.55e-5 7.12 13.0 0.605
#> 2 2007-01-02 8.42 417. 1.92e-4 -22.2 1.00e5 0 6.94e-6 6.79 9.33 0.603
#> 3 2007-01-03 9.13 566. 1.87e-4 -16.6 1.00e5 0 0 4.21 11.2 0.600
#> 4 2007-01-04 10.1 375. 8.28e-5 -16.8 9.93e4 0 0 3.96 12.2 0.598
#> 5 2007-01-05 10.7 508. 1.83e-4 -6.60 9.94e4 0 0 9.26 11.4 0.596
#> 6 2007-01-06 13.6 656. 1.88e-4 -11.2 9.95e4 0 0 8.96 15.4 0.596
#> 7 2007-01-07 13.7 567. 1.55e-4 7.32 9.93e4 0 0 9.55 15.6 0.597
#> 8 2007-01-08 10.7 273. 7.17e-5 -3.00 9.89e4 0 0 7.04 12.0 0.597
#> 9 2007-01-09 16.4 682. 1.88e-4 9.94 9.91e4 0 0 9.46 19.0 0.598
#> 10 2007-01-10 11.4 26.0 2.77e-5 -6.41 9.94e4 0 0 8.98 12.0 0.598
#> # ℹ 2,180 more rows
#> # ℹ 2 more variables: co2 <dbl>, ccov <dbl>Output data
The output of the model contains one line per site found in the
drivers: - sitename: site name - data: output
data for the site (nested tibble)
The data structure for the output data is specific for
each model.
P-model
For detailed information about the content of data, see
?run_pmodel_f_bysite.
BiomeE
data contains the following tables: -
output_daily_tile: Daily output during the simulated period
- output_annual_cohorts: Annual output at the cohort level
during the simulated period - output_annual_tile: Yearly
output during the spin-up and simulated periods.
For detailed information about each table, see
?run_biomee_f_bysite.