dd2m: Compute monthly data from daily series
In climatol: Climate Tools (Series Homogenization and Derived Products)

Description Usage Arguments Details Value See Also Examples

View source: R/depurdat.R

Daily series are aggregated into total, mean, maximum, or minimum monthly values, and saved to files for further processing.

1 2	dd2m(varcli, anyi, anyf, anyip=anyi, anyfp=anyf, ndec=1, suf=NA, valm=2, namax=10, na.strings="NA", homog=FALSE, ini=NA)

`varcli`	Acronym of the name of the studied climatic variable, as in the data file name.
`anyi`	Initial year of the data present in the file.
`anyf`	Final year of the data present in the file.
`anyip`	First year of the output period. (Defaults to `anyi`).
`anyfp`	Last year of the output period. (Defaults to `anyf`).
`ndec`	Number of decimal places to be saved in the output file.
`suf`	Optional suffix to be added (by a hyphen) to the acronym of the variable to form the name of the input data.
`valm`	Monthly value to compute: 1: Sum, 2: Mean, 3: Maximum, 4: Minimum.
`namax`	Maximum number of missing data in any month to compute its monthly value. (10 by default)
`na.strings`	Missing data code in the original daily data.
`homog`	If `TRUE`, monthly aggregation will be performed on daily adjusted from a previous monthly homogenization.
`ini`	Initial date of the daily data, with format `"YYYY-MM-DD"`. Its default `NA` value assume it to be the first day of the period of study.

This function can be applied to either raw or homogenized daily data.

Raw data are read from files ‘VAR_YEAR-YEAR.dat’ and ‘VAR_YEAR-YEAR.est’, and monthly data will be saved to files ‘VAR-m_YEAR-YEAR.dat’ and ‘VAR-m_YEAR-YEAR.est’.

Homogenized data are read from ‘VAR_YEAR-YEAR.rda’. In this case monthly data will be saved to files named ‘VAR-mh_YEAR-YEAR.dat’ and ‘VAR-mh_YEAR-YEAR.est’.

This function does not return any value.

homogen, dahstat, dahgrid

## Not run: 
#First we must generate the input files from example data:
data(Ttest)
write(dat,'Ttest_1981-2000.dat')
write.table(est.c,'Ttest_1981-2000.est',row.names=FALSE,col.names=FALSE)
rm(dat,est.c) #remove loaded data from memory space
#Now we can apply this function to these monthly precipitation data:
#
dd2m('Ttest',1981,2000)

## End(Not run)