#' readCarbonLTS
#'
#' Read-in an Long term carbon storage data for historical period.
#'
#' @param subtype data subtype.
#' @return magpie object of the FRA 2015 data
#' @author Abhijeet Mishra
#' @seealso [readSource()]
#' @examples
#' \dontrun{
#' a <- readSource("CarbonLTS", "Lauk_et_al")
#' }
#' @importFrom readxl read_xlsx
#' @importFrom zoo na.locf
readCarbonLTS <- function(subtype) {
if (subtype == "Lauk_et_al") {
## Source file name
location <- "erl431725data.xlsx"
## Read file
x <- read_xlsx(path = location, sheet = "figure1c", skip = 6)
## General cleanup
x <- x[-1, -2] # Remove empty row and unit column
x <- x[1, ] # Only need wood data
colnames(x)[1] <- "category"
## Convert to magpie object and convert to GtC
x <- as.magpie(x) ## Convert
x <- x / 1e3 ## Division by 10e3 to convert from ktC to MtC
x <- x * 44 / 12 ## Multiplication by 44/12 to convert from MtC to MtCO2e/yr
getNames(x) <- "Emission"
x <- add_dimension(x, dim = 3.1, add = "type", nm = "Annual (MtCO2/yr)")
out <- x
} else if (subtype == "Johnston_Radeloff") {
## Source file name
location <- "pnas.1904231116.sd01.xlsm"
cumulative <- read_xlsx(path = location, sheet = "Figures", skip = 50, n_max = 6)[, -2]
colnames(cumulative) <- paste0("y", colnames(cumulative))
colnames(cumulative)[1] <- "Emission"
annual <- read_xlsx(path = location, sheet = "Figures", skip = 58, n_max = 6)[, -2]
colnames(annual) <- paste0("y", colnames(annual))
colnames(annual)[1] <- "Emission"
## Filling Historical SSP values
cumulative <- na.locf(cumulative, na.rm = FALSE)
annual <- na.locf(annual, na.rm = FALSE)
out <- mbind(add_dimension(as.magpie(annual), dim = 3.1, add = "type", nm = "Annual (MtCO2/yr)"),
add_dimension(as.magpie(cumulative), dim = 3.1, add = "type", nm = "Cumulative (GtCO2)"))
} else {
stop("Cannot handle this subtype, select Lauk_et_al or Johnston_Radeloff.")
}
return(out)
}
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