generateWeatherSeries: Simulate gridded weather function
In tanerumit/gridwegen: Gridded semi-parametric weather generator

Description goes here....

generateWeatherSeries(
  weather.data = NULL,
  weather.grid = NULL,
  weather.date = NULL,
  variable.names = NULL,
  variable.labels = NULL,
  variable.units = NULL,
  sim.year.num = NULL,
  sim.year.start = 2020,
  month.start = 1,
  realization.num = 5,
  warm.variable = "precip",
  warm.signif.level = 0.9,
  warm.sample.num = 5000,
  warm.subset.criteria = NULL,
  knn.sample.num = 100,
  mc.wet.threshold = 0.3,
  mc.extreme.quantile = 0.8,
  evaluate.model = FALSE,
  evaluate.grid.num = 20,
  output.path = getwd(),
  seed = NULL
)

`weather.data`	list of data frames of daily weather observations per grid cell. Each data frame, columns are weather variables and rows are daily values.
`weather.grid`	Data frame of grid cells. Each grid cell is assigned an id starting from 1, x and y coordinate index value, and x and y coordinates.
`weather.date`	placeholder
`variable.names`	vector of names for the variables to be included in the weather generator
`variable.labels`	vector of labels for the weather variables (optional). If no values provided, it is labels will be same as the names
`variable.units`	vector of units for each of the weather variables (optional). If no values provided, a blank vector is used.
`sim.year.num`	numeric value indicating the desired total number of years of simulated weather realizations
`sim.year.start`	numeric value indicating the starting year of the generated time-series
`month.start`	the first month of the year (default value is 1). Use a value other than 1 for water-year based analyses
`realization.num`	number of natural variability realizations to be generated.
`warm.variable`	the name of the variable for the wavelet autoregressive mode. Default value is precipitation variable.
`warm.signif.level`	the significance level for the warm model.
`warm.sample.num`	number of annual sequeces to be generated from the the warm model
`warm.subset.criteria`	placeholder
`knn.sample.num`	number of knn years to be sampled
`mc.wet.threshold`	placeholder
`mc.extreme.quantile`	placeholder
`evaluate.model`	logical value indicating wether to save model evaluation plots
`evaluate.grid.num`	Number of grid cells to be sampled in the evaluation plots
`output.path`	output path for the weather generator results (string)
`seed`	placeholder