P-model data format
In rsofun: The P-Model and BiomeE Modelling Framework

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.align = "center",
  fig.width = 7,
  fig.height = 5
)

library(rsofun)
library(dplyr)
library(ggplot2)

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

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

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.