| velocity {climetrics} | R Documentation |
Velocity of Climate Change
Description
The method is developed based on the method represented in the paper Hamnan et al. (2015). Two additional functions including Distance-based (dVelocity) and Gradiant-based velocity (gVelocity) are also implemented and available in the package.
- Hamann, A., Roberts, D.R., Barber, Q.E., Carroll, C. and Nielsen, S.E. (2015). Velocity of climate change algorithms for guiding conservation and management. Global Change Biology, 21(2), pp.997-1004.
Usage
velocity(x1,x2,t1, t2,...)
Arguments
x1 |
The first input climate variable that can be a RasterStack or RasterBrick, or a raster time series |
x2 |
The second input climate variable that can be a RasterStack or RasterBrick, or a raster time series |
t1 |
a chanracter or a numeric vector, specifying the index of raster layers for time 1 |
t2 |
a chanracter or a numeric vector, specifying the index of raster layers for time 2 |
... |
not implemented |
Value
A single Raster layer (RasterLayer or SpatRaster depending on the input)
Author(s)
Shirin Taheri; Babak Naimi
taheri.shi@gmail.com; naimi.b@gmail.com
Examples
filePath <- system.file("external/", package="climetrics") # path to the dataset folder
# read the climate variables using the terra package (you can use the raster package as well):
pr <- rast(paste0(filePath,'/precip.tif'))
tmax <- rast(paste0(filePath,'/tmax.tif'))
pr # has 360 layers corresponds to months of the years 1991-2020
n <- readRDS(paste0(filePath,'/dates.rds')) # read corresoinding dates
head(n) # Dates corresponds to the layers in climate variables (pr, tmin, tmax, tmean)
####################
# use rts function in the rts package to make a raster time series:
pr.t <- rts(pr,n)
tmax.t <- rts(tmax,n)
###########################
# test of the metric:
# The extreme argument corresponds to the first and second climate variables
# (i.e., x1 and x2; precipitation and temperature) that specify the percentile of the extreme
# condition in climate variable; here, 0.05 is used for precipitation; and 0.95 for temperature
ve <- velocity(x1=pr.t,x2=tmax.t,t1='1991/2000',t2='2010/2020')
# plot(ve, main='Velocity of Climate Change')