Compute ECs based on day-windows of fixed length.

Source: R/compute_EC.R

Compute the environmental covariates based on the daily weather table of an environment (Year x Location), and over day-windows of fixed length. Across all environments, the day-window contain the same number of days. Each EC is computed over this fixed number of days, given by the parameter "duration_time_window_days". The maximum number of time windows (e.g. the total number of ECs) is determined by the parameter number_total_fixed_windows, itself determined based on the minimum growing season length (length_minimum_gs) when considering all environments.

compute_EC_fixed_length_window(
  table_daily_W,
  length_minimum_gs,
  base_temperature = 10,
  method_GDD_calculation = c("method_b"),
  duration_time_window_days = 10,
  capped_max_temperature = F,
  max_temperature = 35,
  ...
)

Arguments

table_daily_W

data.frame Object returned by the function get_daily_tables_per_env()
length_minimum_gs

numeric Length of the shortest growing season length. Used to calculate the maximum number of day-windows to use (is determined based on the shortest growing season length).
base_temperature

numeric Base temperature (crop growth assumed to be null below this value.) Default is 10.
method_GDD_calculation

character Method used to compute the GDD value, with one out of method_a or method_b.
method_a: No change of the value of \(T_{min}\). GDD = \(max (\frac{T_{min}+T_{max}}{2} - T_{base},0)\).
method_b: If \(T_{min}\) < \(T_{base}\), change \(T_{min}\) to \(T_{min}\) = \(T_{base}\).
Default = method_b.
duration_time_window_days

numeric Number of days spanned by a day-window

Value

An object of class data.frame with 10 x number_total_fixed_windows + 1 last column (IDenv):

  1. mean_TMIN: number_total_fixed_windows columns, indicating the average minimal temperature over the respective day-window.

  2. mean_TMAX: number_total_fixed_windows columns, indicating the average maximal temperature over the respective day-window.

  3. mean_TMEAN: number_total_fixed_windows columns, indicating the average mean temperature over the respective day-window.

  4. freq_TMAX_sup30: number_total_fixed_windows columns, indicating the frequency of days with maximum temperature over 30°C over the respective day-window.

  5. freq_TMAX_sup35: number_total_fixed_windows columns, indicating the frequency of days with maximum temperature over 35°C over the respective day-window.

  6. sum_GDD: number_total_fixed_windows columns, indicating the growing degree days over the respective day-window.

  7. sum_PTT: number_total_fixed_windows columns, indicating the accumulated photothermal time over the respective day-window.

  8. sum_P: number_total_fixed_windows columns, indicating the accumulated precipitation over the respective day-window.

  9. sum_et0: number_total_fixed_windows columns, indicating the cumulative reference evapotranspiration over the respective day-window.

  10. freq_P_sup10: number_total_fixed_windows columns, indicating the frequency of days with total precipitation superior to 10 mm over the respective day-window.

  11. sum_solar_radiation: number_total_fixed_windows columns, indicating the accumulated incoming solar radiation over the respective day-window.

  12. mean_vapr_deficit: number_total_fixed_windows columns, indicating the mean vapour pressure deficit over the respective day-window.

  13. IDenv character ID of the environment (Location_Year)

Author

Cathy C. Westhues cathy.jubin@uni-goettingen.de