ReadInputs(climatedata, constants, stopmissing, timestep, interp_missing_days = F, interp_missing_entries = F, interp_abnormal = F, missing_method = NULL, abnormal_method = NULL)ET for the specific data requirements for different formulations.
T or F, indicating if missing days (within the date data) should be interpolated, with a default of F which assigns NA to data at the missing days.
T or F, indicating if missing data entries within individual climate variables should be interpolated, with a default of F which assigns NA to the missing entries.
T or F, if abnormal values within individual climate variables should be interpolated, with a default of F which leaves the abnormal values unchanged.
Abnormal values are defined differently according to the input variable, as following:
- Tmax.daily > 100 degree Celcius
- Tmin.daily > Tmax.daily
- Temp.subdaily > 100 degree Celcius
- Tdew.daily/Tdew.subdaily > 100 degree Celcius
- RHmax.daily > 100 per cent
- RHmin.daily > RHmax.daily
- RH.subdaily > 100 per cent
- Rs.daily/Rs.subdaily < 0 MJ.m^2
- n.daily < 0 hour
- Cd.daily < 0 Okta
- Precip.daily < 0 mm
- uz.daily/uz.subdaily < 0 m/s
- u2.daily/u2.subdaily < 0 m/s
- Epan.daily < 0 mm
- Vp.daily/Vp.subdaily < 0 hPa
monthly average - replacement with same-month average (adapted from Narapusetty et al., 2009);
seasonal average - replacement with same-season average (adapted from Narapusetty et al., 2009);
DoY average - replacement with same day-of-the-year average (Narapusetty et al., 2009);
neighbouring average - interpolation between the two bounding values, which is only suitable for time increments in which values are available at adjacent increments (McMahon et al., 2013). When there is more than one consecutive missing entry, this interpolation fails, with a warning given.
monthly average - replacement with same-month average (adapted from Narapusetty et al., 2009);
seasonal average - replacement with same-season average (adapted from Narapusetty et al., 2009);
DoY average - replacement with same day-of-the-year average (Narapusetty et al., 2009);
neighbouring average - interpolation between the two bounding values, which is only suitable for time increments in which non-abnormal values are available at adjacent increments (McMahon et al., 2013). When there is more than one consecutive abnormal entry, this interpolation fails, with a warning given.
daily or subdaily to specify the time step of raw climate data used.
zoo which have been processed from the raw data, including:
zoo object containing the date in daily step in the format of yyyy-mm-dd.
zoo object containing the date in daily step in the format of mmm-yyyy.
zoo object containing the Julian Day for every day during the period that the data spans.
zoo object containing the month number for every day during the period that the data spans.
zoo object containing the number of days for every month during the period that the data spans.
zoo object containing the daily maximum temperatures in degree Celcius.
zoo object containing the daily minimum temperatures in degree Celcius.
zoo object containing the daily wind speed at 2m from the ground in m/s.
zoo object containing the daily wind speed measured at the height of wind instrument in m/s.
zoo object containing the daily solar radiation in MJ/m^2/day.
zoo object containing the daily sunshine hours.
zoo object containing the daily cloud cover in oktas.
zoo object containing the daily precipitation in mm.
zoo object containing the daily Class-A pan evaporation in mm.
zoo object containing the daily maximum relative humidity in percentage.
zoo object containing the daily minimum relative humidity in percentage.
zoo object containing the average daily dew temperatures in degree Celcius.
NULL when the corresponding input variable cannot be found in the raw data (i.e. "climatedata").
Chiew, F. H. & McMahon, T. A. 1991. The applicability of Morton's and Penman's evapotranspiration estimates in rainfall-runoff modeling1. JAWRA Journal of the American Water Resources Association, 27, 611-620.
Narapusetty, B., DelSole, T.Tippett, M.K. 2009, Optimal Estimation of the Climatological Mean. Journal of Climate, vol. 22, no. 18, pp. 4845-4859.
ET,climatedata,data
# ReadInputs climate data
data("climatedata")
data("constants")
data <- ReadInputs(climatedata, constants,
stopmissing=c(10,10,3),
timestep="subdaily",
interp_missing_days = TRUE,
interp_missing_entries = TRUE,
interp_abnormal = TRUE,
missing_method = "DoY average",
abnormal_method = "DoY average")
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