| temperature_scenario_baseline_adjustment {chillR} | R Documentation |
Make temperature scenario relative to a particular baseline
Description
When interpreting future (or past) temperature scenarios that provide absolute temperatures, it is important to consider the temperature baseline, i.e. a temperature scenario produced with similar models and methods that corresponds to the current temperature regime. Such baselines are normally available from the same source that provided the future scenarios. This function implements this adjustment. The function can be used for two situations: 1) two absolute temperature scenarios: the output is the difference between the scenarios, i.e. a relative temperature scenario describing the difference between monthly temperature extreme means between the two scenarios. 2) two relative temperature scenarios: the output is a relative temperature scenario that describes the difference between the scenario year of the temperature_scenario and the baseline year of the baseline_temperature_scenario. This only works if the scenario_year of the baseline_temperature_scenario is the same as the reference_year of the temperature_scenario.
Usage
temperature_scenario_baseline_adjustment(
baseline_temperature_scenario,
temperature_scenario,
temperature_check_args = NULL,
warn_me = TRUE,
required_variables = c("Tmin", "Tmax")
)
Arguments
baseline_temperature_scenario |
baseline temperature scenario (e.g. produced with 'extract_temperatures_from_grids'). This is a temperature scenario object, consisting of the following elements: 'data' = data.frame with two columns Tmin and Tmax containing absolute (normally monthly) mean minimum and maximum temperatures; 'reference_year' = the year the scenario refers to (this is normally NA for absolute temperature scenarios, because they don't require considering a reference scenario); 'scenario_type' = the scenario type, normally "absolute" (but can also be "relative" or NA - then the type is automatically assigned); 'labels' = elements attached to the input temperature_scenario. A subset of these elements can also be specified, but 'data' must be present. |
temperature_scenario |
can be one of three 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. 3) a list of elements of type 1 or 2. Then the adjustment is done for all elements. |
temperature_check_args |
list of arguments to be passed to the check_temperature_scenario function. Check documentation of that function for details. |
warn_me |
boolean variable specifying whether warnings should be shown. Defaults to TRUE. |
required_variables |
character vectors containing names of variables that must be included in the scenario. |
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
baseline_temperature_scenario<-list(data=data.frame(Tmin=c(1,1,1,1,1,1,1,1,1,1,1,1),
Tmax=c(1,1,1,1,1,1,1,1,1,1,1,1)),
scenario_year=1990,
reference_year=1975,
scenario_type="relative")
temperature_scenario<-list(data=data.frame(Tmin=c(4,4,4,4,4,4,4,4,4,4,4,4),
Tmax=c(4,4,4,4,4,4,4,4,4,4,4,4)),
scenario_year=2000,
reference_year=1990,
scenario_type="relative")
relative_temperature_scenario<-temperature_scenario_baseline_adjustment(
baseline_temperature_scenario,temperature_scenario,
temperature_check_args=NULL)
baseline_temperature_scenario<-list(data=data.frame(Tmin=c(-5,-2,2,5,10,12,15,15,12,10,5,1),
Tmax=c( 1, 4,7,10,15,18,22,24,17,15,11,6)),
scenario_year=1980,
reference_year=NA,
scenario_type="absolute")
temperature_scenario<-list(data=data.frame(Tmin=c(-3,0,4,7,12,14,17,17,14,12,7,3),
Tmax=c(3,6,9,12,17,20,24,26,19,17,13,8)),
scenario_year=2000,
reference_year=NA,
scenario_type="absolute")
relative_temperature_scenario<-temperature_scenario_baseline_adjustment(
baseline_temperature_scenario,temperature_scenario,
temperature_check_args=NULL)