climatrends (version 0.5)

crop_sensitive: Crop sensitive indices

Description

Compute crop sensitive indices. These indices are designed to capture the changes in temperature extremes during key phenological stages (e.g. anthesis), but can also be applied to other phenological stages.

Usage

crop_sensitive(object, ...)
# S3 method for default
crop_sensitive(object, tmin, ...)
# S3 method for data.frame
crop_sensitive(object, day.one, ...)
# S3 method for array
crop_sensitive(object, day.one, ...)
# S3 method for sf
crop_sensitive(object, day.one, ..., as.sf = TRUE)

Value

A dataframe with crop sensitive indices with n colunms depending on the number of thresholds passed to each index:

hts_mean

high temperature stress using daily MEAN temperature, and given as percentage number of days a certain threshold is exceeded

hts_max

high temperature stress using daily MAX temperature, and given as percentage number of days a certain threshold is exceeded

hse

heat stress event, and given as percentage number of days a a certain threshold is exceeded for at least two consecutive days

hse_ms

heat stress event, and given the maximum number of days a certain threshold is exceeded for at least two consecutive days

cdi_mean

crop duration index using daily MEAN temperature, and given as max(Tmean - threshold, 0)

cdi_max

crop duration index using daily MAX temperature, and given as max(Tmax - threshold, 0)

lethal

lethal temperatures, defined as percentage of days during the timeseries where daily MEAN temperature exceeds a given threshold

Arguments

object

a numeric vector with the maximum temperature, or a data.frame with geographical coordinates (lonlat), or an object of class sf with geometry 'POINT' or 'POLYGON', or an array with two dimensions containing the maximum and minimum temperature, in that order. See details

...

additional arguments passed to methods. See details

tmin

a numeric vector with the minimum temperature

day.one

a vector of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the starting day to capture the climate data

as.sf

logical, to return an object of class 'sf'

Details

The function uses pre-defined threshold to compute the indices. For hts_mean (32, 35, 38 Celsius), for hts_max (36, 39, 42 Celsius), for hse (31 Celsius), for cdi_mean (22, 23, 24 Celsius), for cdi_max (27, 28, 29 Celsius) and for lethal (43, 46, 49 Celsius).

Additional arguments:

The thresholds can be adjusted using the arguments hts_mean.threshold, hts_max.threshold, hse.threshold, cdi_mean.threshold, cdi_max.threshold and lethal.threshold which are a numeric (or vector of numeric)

last.day: an object (optional to span) of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the last day of the time series. For data.frame, array and sf methods

span: an integer (optional to last.day) or a vector with integers (optional if last.day is given) for the length of the time series to be captured. For data.frame, array and sf methods

References

Challinor et al. (2016). Nature Climate Change 6(10):6954-958 tools:::Rd_expr_doi("https://doi.org/10.1038/nclimate3061")

Trnka et al. (2014). Nature Climate Change 4(7):637–43. tools:::Rd_expr_doi("https://doi.org/10.1038/nclimate2242")

See Also

Other temperature functions: ETo(), GDD(), temperature()

Examples

# the default method
set.seed(78)
tmax <- runif(50, 37, 47)
set.seed(79)
tmin <- runif(50, 31, 34)

crop_sensitive(tmax, tmin)

###############################################

# the array method
data("temp_dat", package = "climatrends")

# use the default thresholds
crop_sensitive(temp_dat,
               day.one = "2013-10-27",
               last.day = "2013-11-04")

# or change the thresholds based on the crop physiology
crop_sensitive(temp_dat,
               day.one = "2013-10-27",
               last.day = "2013-11-04",
               hts_mean.threshold = c(24),
               hts_max.threshold = c(31, 33))