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Calculation of climate change signal

climate_change_signal.Rd

Automatically computes climate change signal and agreement in the sign of change

Usage

climate_change_signal(
  data,
  uppert = NULL,
  lowert = NULL,
  season,
  consecutive = F,
  duration = "max",
  frequency = F,
  bias.correction = F,
  threshold = 0.6,
  n.sessions = 1,
  method = "eqm",
  percentage = F,
  window = "monthly"
)

Arguments

data

output of load_data

uppert

numeric of length=1, upper threshold

lowert

numeric of length=1, lower threshold

season

list, containing seasons to select. For example, list(1:6, 7:12)

consecutive

logical, to use in conjunction with lowert or uppert

duration

parameter that can be set to either "max" or a specific number. It is relevant only when 'consecutive' is set to TRUE. For instance, to calculate the count of consecutive days with Tmax (maximum temperature) above 35°C, lasting for more than 3 days, you can set 'uppert' to 35, 'consecutive' to TRUE, and 'duration' to 3.

frequency

logical value. This parameter is relevant only when 'consecutive' is set to TRUE and 'duration' is not set to "max". For instance, if you want to determine the count of heatwaves, defined as the number of days with Tmax (maximum temperature) exceeding 35°C for a minimum of 3 consecutive days, set 'uppert' to 35, 'consecutive' to TRUE, 'duration' to 3, and 'frequency' to TRUE.

bias.correction

logical

threshold

numerical value with range 0-1. It indicates the threshold for assigning model agreement. For example, 0.6 indicates that model agreement is assigned when 60 percent of the models agree in the sign of the change

n.sessions

numeric, number of sessions to use, default is one. Parallelisation can be useful when multiple scenarios are used (RCPS, SSPs). However, note that parallelising will increase RAM usage

method

character, bias-correction method to use. One of eqm (Empirical Quantile Mapping), qdm (Quantile Delta Mapping) or scaling. Default to eqm. When using the scaling method, the multiplicative approach is automatically applied only when the variable is precipitation.

percentage

logical, whether the climate change signal is to be calculated as relative changes (in percentage). Default to FALSE

window

character, one of none or monthly. Whether bias correction should be applied on a monthly or annual basis. Monthly is the preferred option when performing bias-correction using daily data

Value

list with SpatRaster. To explore the output run attributes(output)