check_temperature_scenario: Check temperature scenario for consistency

In chillR: Statistical Methods for Phenology Analysis in Temperate Fruit Trees

Check temperature scenario for consistency

Description

chillR's temperature generation procedures require absolute or relative temperature scenarios. This function checks these scenarios for consistency, regarding the data format, the reference year, and whether they are relative or absolute scenarios (based on specified criteria).

Usage

check_temperature_scenario(
  temperature_scenario,
  n_intervals = 12,
  check_scenario_type = TRUE,
  scenario_check_thresholds = c(-5, 10),
  update_scenario_type = TRUE,
  warn_me = TRUE,
  required_variables = c("Tmin", "Tmax")
)

Arguments

temperature_scenario	can be one of two options: 1) a data.frame with two columns Tmin and Tmax and n_intervals (default: 12) rows containing temperature changes for all time intervals, or absolute temperatures for these intervals. 2) a temperature scenario object, consisting of the following elements: 'data' = a data frame with n_intervals elements containing the absolute or relative temperature information (as in input option 1); 'scenario_year' = the year the scenario is representative of; 'reference_year' = the year the scenario is representative of; 'scenario_type' = the scenario type ('absolute' or 'relative' - if NA, this is assigned automatically); 'labels' = and elements attached to the input temperature_scenario as an element names 'labels'. A subset of these elements can also be specified, but 'data' must be present.
n_intervals	the number of time intervals specified in the temperature scenarios. This is often the number of months in a year, so the default is 12. If the temperature scenario is specified for a different number of time intervals, this should be adjusted.
check_scenario_type	boolean variable indicating whether the specified (or unspecified) scenario type should be verified, i.e. whether the scenario is a relative or absolute temperature scenario.
scenario_check_thresholds	vector with two numeric elements specifying the thresholds for checking whether the scenario is an absolute or relative temperature scenario. These are the minimum (first value) and maximum (second value) plausible changes in a relative temperature scenario. The test only works in settings where either the lowest mean minimum temperature across all time intervals is below the stated minimum threshold or the highest mean maximum temperature across all time intervals is above the maximum threshold. With the default values c(-5,10), this should be the case for most locations on Earth, but in extreme cases (either for extreme change scenarios or where all monthly minimum and maximum temperatures are between -5 and 10 degrees), this may need adjustment. This is only used if check_scenario_type==TRUE.
update_scenario_type	boolean variable stating whether, if scenario type is found to be inconsistent with the numbers, the scenario_type should be updated. Defaults to TRUE and is only used if check_scenario_type==TRUE.
warn_me	boolean variable specifying whether warnings should be shown. Defaults to TRUE.
required_variables	character vector containing the names of columns that are required. This defaults to c("Tmin","Tmax").

Details

Besides being able to validate classic temperature scenarios consisting of "Tmin" and "Tmax" data, the function can also validate other datasets (e.g. outputs of the getClimateWizardData function). To do this, the required variables should be provided as "required_variables" parameter. If there is no column "GCM" in the data element of the scenario, then the check_scenario_type parameter should be set to FALSE.

Value

temperature scenario object, consisting of the following elements: 'data' = a data frame with n_intervals elements containing the absolute or relative temperature information. 'reference_year' = the year the scenario is representative of. 'scenario_type' = the scenario type ('absolute' or 'relative'); 'labels' = and elements attached to the input temperature_scenario as an element names 'labels'.

The function also returns warnings, where elements are missing or the scenario_type appears to be wrong, and it stops with an error, if the scenario isn't specified in a format that is usable by chillR.

Author(s)

Eike Luedeling

Examples

temperature_scenario <- list(data = data.frame(Tmin = c(-5, -2, 0, 4, 9, 12,
                                                        15, 13, 12, 9, 4, 0),
                                               Tmax = c(0, 4, 8, 12, 15, 18,
                                                        21, 19, 17, 14, 11, 5)),
                             reference_year = 1975,
                             scenario_type = "absolute",
                             labels = list(GCM = "none",
                                           RCM = "none",
                                           Time = "1950-2000"))

checked_temperature_scenario <- 
        check_temperature_scenario(temperature_scenario,
                                   n_intervals = 12,
                                   check_scenario_type = FALSE,
                                   scenario_check_thresholds = c(-5, 10),
                                   update_scenario_type = FALSE)
                                            
checked_temperature_scenario <-
        check_temperature_scenario(temperature_scenario,
                                   n_intervals = 12,
                                   check_scenario_type = TRUE,
                                   scenario_check_thresholds = c(-5, 10),
                                   update_scenario_type = FALSE)
                                            
checked_temperature_scenario <-
        check_temperature_scenario(temperature_scenario,
                                   n_intervals = 12,
                                   check_scenario_type = TRUE,
                                   scenario_check_thresholds = c(-5, 10),
                                   update_scenario_type = TRUE)                                             
                                            
 

chillR documentation built on Nov. 28, 2023, 1:09 a.m.