weatherSetS: Updates parameter files with weather from a dataset, then...
In pzylstra/frame_r: Fire Research and Modelling Environment

weatherSetS

R Documentation

Updates parameter files with weather from a dataset, then models fire from non-deterministic plant parameters using plantVarS to modify individual species with their own measured variability

Description

Updates parameter files with weather from a dataset, then models fire from non-deterministic plant parameters using plantVarS to modify individual species with their own measured variability

Usage

weatherSetS(
  base.params,
  weather,
  Variation,
  Structure,
  a,
  db.path = "out_mc.db",
  jitters = 10,
  l = 0.1,
  Ms = 0.01,
  Pm = 1,
  Mr = 1.001,
  updateProgress = NULL
)

Arguments

`base.params`	Parameter input table
`weather`	A dataframe with the four fields: tm - Sequential numbering of the records T - Air temperature (deg C) W - Wind velocity (km/h) DFMC - Dead fuel moisture content (proportion ODW)
`Variation`	A database of plant variability in traits, with the fields: record - a unique, consecutively numbered identifier per site species - the name of the species, which will call trait data from 'default.species.params' stratum - numeric value from 1 to 4, counting from lowest stratum Hs - Standard deviation of plant height variations Hr - Truncates plant height variability by +/- Hr * height
`Structure`	A dataframe with the fields: record - a unique, consecutively numbered identifier per site site - a unique identifier per site NS, El, Mid & Can - the mean separation between plants (m) per stratum ns_e, ns_m, e_m, e_c, m_c - Logical field indicating whether plants in the stratum on the left grow directly beneath those in the stratum on the right. Acceptable values are t, f, or blank, where the outcome will be decided by the relative stratum heights. nsR, eR, mR, cR - maximum species richness recorded for each stratum
`a`	A unique identifier for the record being run
`db.path`	Name of the exported database
`jitters`	Number of repetitions
`l`	Variation around input leaf dimensions
`Ms`	Standard deviation of LFMC
`Pm`	Multiplier of mean LFMC
`Mr`	Truncates LFMC variability by +/- Mr * LFMC
`updateProgress`	Progress bar for use in the dashboard