R/read_instrum_data.R

In MartinSchobben/timemachine: App for studying past climate and events of climate change

#' The read_cru_hemi function on http://www.cru.uea.ac.uk/cru/data/temperature
#'
#' @param filename file from the website
#'
#' @details Reads a CRU-format hemispheric average file, as provided at
#' http://www.cru.uea.ac.uk/cru/data/temperature
#'
#' Format has two lines for each year.
#  1) monthly mean anomalies plus an annual mean
#  2) coverage percentages
#'
#' Returns a data frame with columns:
#'  year (1850 to final year)
#'  annual (mean annual anomaly)
#'  month.1 ... month.12 (mean monthly anomaly)
#'  cover.1 ... cover.12 (percentage coverage)
#'
#' @return dataframe
#' @export
read_cru_hemi <- function(filename) {
  # read in whole file as table
  tab <- read.table(filename,fill=TRUE)
  nrows <- nrow(tab)
  # create frame
  hemi <- data.frame(
    year=tab[seq(1,nrows,2),1],
    annual=tab[seq(1,nrows,2),14],
    month=array(tab[seq(1,nrows,2),2:13]),
    cover=array(tab[seq(2,nrows,2),2:13])
  )
  # mask out months with 0 coverage
  hemi$month.1 [which(hemi$cover.1 ==0)] <- NA
  hemi$month.2 [which(hemi$cover.2 ==0)] <- NA
  hemi$month.3 [which(hemi$cover.3 ==0)] <- NA
  hemi$month.4 [which(hemi$cover.4 ==0)] <- NA
  hemi$month.5 [which(hemi$cover.5 ==0)] <- NA
  hemi$month.6 [which(hemi$cover.6 ==0)] <- NA
  hemi$month.7 [which(hemi$cover.7 ==0)] <- NA
  hemi$month.8 [which(hemi$cover.8 ==0)] <- NA
  hemi$month.9 [which(hemi$cover.9 ==0)] <- NA
  hemi$month.10[which(hemi$cover.10==0)] <- NA
  hemi$month.11[which(hemi$cover.11==0)] <- NA
  hemi$month.12[which(hemi$cover.12==0)] <- NA
  #
  return(hemi)
}