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. Each site is defined by a site name (sitename), location specific site information (site_info), soil characteristics (params_soil), simulation parameter settings (params_siml) and environmental forcing data (forcing). Sites are grouped by row in a nested tibble.
# call to the included p-model demo data
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]>Here, 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. Data are provided at a daily time step and for complete years.
# detailed look at the forcing data
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>To create your own driver data it should be arranged into a tibble with the same structure as the example drivers objects. Within {rsofun} optional checks are executed to ensure that the required variables are present in the used dataset using the ‘check’ argument in the runread_pmodel_f() function calls. Throughout the package verbose output is provided (if desired) as to evaluate errors or progress when running the model on a particular dataset.