QCthresholds | R Documentation |
This function calculate monthly quantiles of daily or subdaily series that can be used as thresholds for Quality Control alerts.
QCthresholds(dat, ndec=1, probs=c(0.,.001,.01,.99,.999,1.), minval=NA,
maxval=NA, homog=TRUE, verb=TRUE)
dat |
Either the name of a *.rda file of |
ndec |
number of decimals of output values [1] (defaults shown between brackets) |
probs |
probabilities of the quantiles to be computed [0., .001, .01, .99, .999, 1.] |
minval |
minimum value to compute runs of constant values [ |
maxval |
maximum value to compute runs of constant values [ |
homog |
use homogenized data if a *.rda file is used as input [ |
verb |
list all calculated values? [ |
minval
and maxval
allow to exclude frequent values that would
result in the report of long runs of identical data. Examples: set
minval=0.1
in daily precipitation to avoid long runs of zeros or set
maxval=97
in relative humidity to avoid long runs of near saturation
values in episodes of persistent fog.
Calculated thresholds are shown in the text output and are also saved in a
binary R file named QCthresholds.Rdat
, which contains the matrices
thr1
, thr2
and thr3
. Load this file and write the
thresholds in the required format for importation into a Climate Data
Management System.
homogen
## Set a temporal working directory and write input files:
wd <- tempdir()
wd0 <- setwd(wd)
data(climatol_data)
## Now run the examples:
QCthresholds(RR3st,minval=0.1) #daily precipitation of three stations
QCthresholds(TX3st) #daily maximum temperatures of three stations
load('QCthresholds.Rdat') #load last calculated thresholds
thr1[1,,] #thresholds with 0% probability to find lower values
thr1[,3,] #monthly thresholds of the third station
thr2 #thresholds of absolute increments between consecutive data
thr3 #thresholds for equal data run lengths
## Return to user's working directory:
setwd(wd0)
## Input and output files can be found in directory:
print(wd)
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