Description Usage Arguments Value Note Author(s) References See Also Examples
View source: R/F_par_calibration.R
Calibrates the monthly parameters for the definition of the interpolation algorithm values of: time of minimum temperature; time of maximum temperature; time of sunset; parameter 'c' (see references for details). It works on more than one series at once. It also calculates an average calibration table, for simulations of series with no calibration.
1 2 3 4 | par_calibration(meas, date.format = "ymd",
cal_period = NULL, missing_value_code = NA,
min_valid_yrs = 1, band_min = 4:9, band_max = 12:16,
band_suns = 14:20, silent = FALSE, aver_series = NULL)
|
meas |
measured hourly values file (table), where the first column is the series' ID |
date.format |
date format in |
cal_period |
calibration period for the series.
Default is |
missing_value_code |
allows to deal missing data if
a code (either numeric or character) is passed. Default
is |
min_valid_yrs |
minimum fraction of year(s) on any series ID necessary for carrying out calibration |
band_min |
(continuous) band of hours to seek day minimum |
band_max |
same for maximum time |
band_suns |
same for sunset time |
silent |
if set to |
aver_series |
set of series IDs (chr) used to
calculate the average calibration (if |
a list of calibration tables, one for each series, plus one average table at the bottom (named "Average")
meas
must be organized as 4-field records, all
series in the same file, no headers. Column order:
station ID, date, time (hour), T, [others fields, if
any...] separated by spaces. This field order is
mandatory.
Default date format is "ymd" (yyyy/mm/dd). Different
combinations can be passed to function with
date.format
, but separator must be "/"
See also: Eccel, E., 2010: What we can ask to hourly temperature recording. Part I: statistical vs. meteorological meaning of minimum temperature. Italian Journal of Agrometeorology XV(2):41-43.
Emanuele Eccel, Emanuele Cordano emanuele.eccel@iasma.it
Eccel, E., 2010: What we can ask to hourly temperature recording. Part II: hourly interpolation of temperatures for climatology and modelling. Italian Journal of Agrometeorology XV(2):45-50 http://www.agrometeorologia.it/documenti/Rivista2010_2/AIAM%202-2010_pag45.pdf,www.agrometeorologia.it
Original algorithm from: Cesaraccio, C., Spano, D., Duce, P., Snyder, R.L., 2001. An improved model for determining degree-day values from daily temperature data. Int. J. Biometeorol. 45: 161-169. http://www.springerlink.com/content/qwctkmlq3tebthek/
1 2 3 4 5 6 7 | data(Trentino_hourly_T)
stations <- c("T0001","T0010","T0129")
calibration_l <- par_calibration(meas = h_d_t[h_d_t$V1 %in% stations,],
missing_value_code = -999.9,
band_min = 4:8, band_max = 13:16,
band_suns = 16:20, cal_period = NULL)
|
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