kgc {climetrics}

Koggen Geiger climate classification

Description

Given the monthly mean (12 months) of Precipitation, minimum, maximum, and mean temperature datasets, this function identify climate zones following Koppen Geiger climate classification rules.

Usage

  kgc(p,tmin, tmax, tmean)

Arguments

p

A Raster object contains 12 months precipitation

tmin

A Raster object contains 12 months minimum temperature

tmax

A Raster object contains 12 months maximum temperature

tmean

A Raster object contains 12 months mean temperature

Details

If the input object is not a 12 month Raster object but a time series, the function first calls the apply.months to get the 12 month raster object.

Value

A single Raster layer (RasterLayer or SpatRaster depending on the input)

Author(s)

Shirin Taheri; Babak Naimi

[e-mail]; [e-mail]

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'))
tmin <- rast(paste0(filePath,'/tmin.tif'))
tmax <- rast(paste0(filePath,'/tmax.tif'))
tmean <- rast(paste0(filePath,'/tmean.tif'))

pr # has 360 layers corresponds to months of the years 1991-2020

n <- readRDS(paste0(filePath,'/dates.rds')) # read corresponding dates

class(n)
length(n)

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) 
tmin.t <- rts(tmin,n)
tmax.t <- rts(tmax,n)
tmean.t <- rts(tmean,n)
#------

pr.t # see the summary report of the raster time series object


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

# To generate Koppen Geiger climate classification, we need the monthly average of 
# climate variables (over years for each month):

# you can use apply.months function to take the average of climate variables for each month
# over different years that generates 12 layers corresponds to 12 months:

p12 <- apply.months(pr.t[['1991/2000']],'mean')


p12

# plot(p12)

#--
tmin12 <- apply.months(tmin.t[['1991/2000']],'mean')

tmax12 <- apply.months(tmax.t[['1991/2000']],'mean')

tmean12 <- apply.months(tmean.t[['1991/2000']],'mean')


##-------- now, the kgc function can be used to generate the climate classification map:
k1 <- kgc(p=p12,tmin = tmin12,tmax=tmax12, tmean = tmean12)

k1

plot(k1)