Title:	Quality Control of Climatological Daily Time Series
Version:	2.0.5
Date:	2021-05-19
Description:	Collection of functions for quality control (QC) of climatological daily time series (e.g. the ECA&D station data).
License:	GPL (≥ 3)
URL:	https://github.com/INDECIS-Project/INQC
BugReports:	https://github.com/INDECIS-Project/INQC/issues
Encoding:	UTF-8
RoxygenNote:	7.1.1
Imports:	evd, gdata, suncalc, stats, utils
Suggests:	readr
NeedsCompilation:	no
Packaged:	2021-05-24 13:21:02 UTC; Typhoon
Author:	Enric Aguilar [aut, cre], Oleg Skrynyk [aut]
Maintainer:	Enric Aguilar <enric.aguilar@urv.cat>
Repository:	CRAN
Date/Publication:	2021-05-24 14:00:02 UTC

Computes outliers

Description

This function computes outliers centralized around a day, using a number of days around it

Usage

IQRoutliers(date, value, level = 3, window = 11, exclude = NULL)

Arguments

Value

positions which do not pass this QC test

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
#Read the data file
date<-readecad(input=path2inptfl,missing= -9999)[,3]
value<-readecad(input=path2inptfl,missing= -9999)[,4]
#Find all suspicious positions in the time series
IQRoutliers(date,value,level=3,window=11,exclude=NULL)

Converter from the ClimDex format into the ECA&D format (blended version)

Description

This function will convert station and data files in ClimDex format into corresponding station and data files in the ECA&D format (blended version)

Usage

climdex2ecad(
  homefolder = "./",
  stationlist = "stations.csv",
  countrycode = "DE"
)

Arguments

Value

station and data files in the ECA&D format stored in the subdirectory 'raw'

Examples

#Set a temporal working directory:
wd <- tempdir(); wd0 <- setwd(wd)
#Create subdirectory where raw data files in the ClimDex format have to be located
dir.create(file.path(wd, "raw_ClimDex"))
#Extract the ClimDex data and station files from the example data folder
path2stalist<-system.file("extdata", "stations.csv", package = "INQC")
stalist<-readr::read_lines_raw(path2stalist)
readr::write_lines(stalist,file=paste0(wd,"/raw_ClimDex/stations.csv"))
path2data1<-system.file("extdata", "Deuselbach.txt", package = "INQC")
data1<-readr::read_lines_raw(path2data1)
readr::write_lines(data1, file=paste0(wd,"/raw_ClimDex/Deuselbach.txt"))
path2data2<-system.file("extdata", "Staname.txt", package = "INQC")
data2<-readr::read_lines_raw(path2data2)
readr::write_lines(data2, file=paste0(wd,"/raw_ClimDex/Staname.txt"))
#Call the converter
climdex2ecad(homefolder = "./",stationlist = "stations.csv",countrycode = "DE")
#The results can be found in the directory:
print(wd)
#Return to user's working directory:
setwd(wd0)

QC for Cloud Cover (CC)

Description

This function will centralize temperature-like QC routines. It will create a file in the folder QC with an additional 0/1 column, where "1" means test failed.

Usage

clocov(
  element = "CC",
  maxseq = 8,
  blocksizeround = 20,
  blockmanymonth = 20,
  blockmanyyear = 200,
  inisia = FALSE
)

Arguments

Value

QC results for CC

Examples

#Set a temporal working directory:
wd <- tempdir()
wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, 'raw'))
options("homefolder"='./'); options("blend"=FALSE)
#Extract the ECA&D data and station files from the example data folder
path2cclist<-system.file("extdata", "ECA_blend_source_cc.txt", package = "INQC")
cclist<-readr::read_lines_raw(path2cclist)
readr::write_lines(cclist,'ECA_blend_source_cc.txt')
path2ccdata<-system.file("extdata", "CC_SOUID132727.txt", package = "INQC")
ccdata<-readr::read_lines_raw(path2ccdata)
readr::write_lines(ccdata, file=paste(wd,'/raw/CC_SOUID132727.txt',sep=''))
#Perform QC of Cloud Cover data
clocov(inisia=TRUE)
#Remove some temporary files
list = list.files(pattern = "Rfwf")
file.remove(list)
#Return to user's working directory:
setwd(wd0)
#The QC results can be found in the directory:
print(wd)

Prepares a calendar frame

Description

This function prepares a calendar frame and returns it as year,month,day (i.e., the 3 first columns of the RClimdex format)

Usage

computecal(fy, ly)

Arguments

Value

3 columns containing year,month,day

Examples

fy<-1981
ly<-2020
clndr<-computecal(fy,ly)

Consolidates QC files

Description

This function is not intended to be called as a stand-alone function. It is automatically called each time a file ends its QC. It will write the quality control files. One file will be placed in a subfolder of the homefolder named QCConslidated. It will use the exact ECA&D format (date, value, QC flag). The QC flags include:

0: Passed QC; 1: ERROR; 2: ALMOST CERTAIN, ERROR; 3: OUTLIER, SUSPECT; 4: COLLECTIVELY SUSPECT; 9: Missing value.

A second file is placed in the subfolder QC and includes all date, value and a column for each QC test ran over this file. Values passing/not passing QC are labelled with 0/1. A third file summarizes the number of values falling on each category (0,1,2,3,4,9) and the number of values failing each test

Usage

consolidator(filename, x)

Arguments

Value

It does not return any value. Each time when called, it will create three files: Summary file, placed at ./QCSumamry/SummaryVV_SOUIDXXXXXX.txt; QC consolidated file, placed at ./QCConsolidated/VV_SOUIDXXXXXX.txt; Verbose QC file, placed at ./QC/qc_VV_SOUIDXXXXXX.txt.

Converter from the COST Home format into the ECA&D format (blended version)

Description

This function will convert station and data files in COST Home format into corresponding station and data files in the ECA&D format (blended version)

Usage

cost2ecad(homefolder = "./")

Arguments

Value

station and data files in the ECA&D format stored in the subdirectory 'raw'

Examples

#Set a temporal working directory:
wd <- tempdir(); wd0 <- setwd(wd)
#Create subdirectory where raw data files in the COST format have to be located
dir.create(file.path(wd, "raw_COST"))
#TG: Extract the COST data and station files from the example data folder
path2tglist<-system.file("extdata", "000001stations.txt", package = "INQC")
tglist<-readr::read_lines_raw(path2tglist)
readr::write_lines(tglist,file=paste0(wd,"/raw_COST/000001stations.txt"))
path2tgdata1<-system.file("extdata", "ratmd00000001d.txt", package = "INQC")
tgdata1<-readr::read_lines_raw(path2tgdata1)
readr::write_lines(tgdata1, file=paste0(wd,"/raw_COST/ratmd00000001d.txt"))
path2tgdata2<-system.file("extdata", "ratmd00000005d.txt", package = "INQC")
tgdata2<-readr::read_lines_raw(path2tgdata2)
readr::write_lines(tgdata2, file=paste0(wd,"/raw_COST/ratmd00000005d.txt"))
#PP: Extract the COST data and station files from the example data folder
path2pplist<-system.file("extdata", "000002stations.txt", package = "INQC")
pplist<-readr::read_lines_raw(path2pplist)
readr::write_lines(pplist,file=paste0(wd,"/raw_COST/000002stations.txt"))
path2ppdata1<-system.file("extdata", "rappd00000001d.txt", package = "INQC")
ppdata1<-readr::read_lines_raw(path2ppdata1)
readr::write_lines(ppdata1, file=paste0(wd,"/raw_COST/rappd00000001d.txt"))
path2ppdata2<-system.file("extdata", "rappd00000012d.txt", package = "INQC")
ppdata2<-readr::read_lines_raw(path2ppdata2)
readr::write_lines(ppdata2, file=paste0(wd,"/raw_COST/rappd00000012d.txt"))
#Call the converter
cost2ecad(homefolder = "./")
#The results can be found in the directory:
print(wd)
#Return to user's working directory:
setwd(wd0)

Converter for geographical coordinates from the ECA&D format into decimal degrees

Description

This function takes sexagesimal degrees in the ECA&D format and converts them into decimal degrees. Initial idea was taken from: https://modtools.wordpress.com/2013/09/25/dms2dec/

Usage

decimaldegrees(dms, sep = ":")

Arguments

Value

geographical coordinates (latitude or longitude) in decimal degrees

Examples

dms<-'+48:03:00'
dec<-decimaldegrees(dms)

dms<-'-015:03:00'
dec<-decimaldegrees(dms)

Create QC statistical summary

Description

This function creates two report files (Mystats.txt and CasesSummary.txt) with a statistical summary of QCs performed over the whole data set

Usage

dostats()

Value

files with QC summary

Downloads the latest version of blended data from the ECA&D website

Description

This function will use the default or specified links to download one or several files from ECA&D and place them for their use with INQC. For each variable a data file and a station file will/should be specified.

Usage

downloadator(
  homefolder = "../ecad_updated",
  tx = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_tx.zip",
  tx2 = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_tx.txt",
  tn = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_tn.zip",
  tn2 = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_tn.txt",
  tg = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_tg.zip",
  tg2 = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_tg.txt",
  sd = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_sd.zip",
  sd2 = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_sd.txt",
  ss = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_ss.zip",
  ss2 = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_ss.txt",
  rr = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_rr.zip",
  rr2 = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_rr.txt",
  pp = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_pp.zip",
  pp2 = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_rr.txt",
  cc = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_cc.zip",
  cc2 = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_cc.txt",
  hu = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_hu.zip",
  hu2 = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_hu.txt",
  fg = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_fg.zip",
  fg2 = "http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_fg.txt"
)

Arguments

Value

For each valid link, the corresponding file will be downloaded. Data files will be unzipped to the ./raw folder (as requested by INQC) and station files will be stored at the specified homefolder

Examples

## Not run: 
#Set a temporal working directory:
wd <- tempdir()
wd0 <- setwd(wd)
#Please note, the command below might take a while and will download the ECA&D data
#with a size more than 0.5GB
downloadator('./data',
             tx=NULL,
             tx2=NULL,
             tn=NULL,
             tn2=NULL,
             tg=NULL,
             tg2=NULL,
             sd=NULL,
             sd2=NULL,
             ss='http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_nonblend_ss.zip',
             ss2="http://knmi-ecad-assets-prd.s3.amazonaws.com/download/ECA_blend_source_ss.txt",
             rr=NULL,
             rr2=NULL,
             pp=NULL,
             pp2=NULL,
             cc=NULL,
             cc2=NULL,
             hu=NULL,
             hu2=NULL,
             fg=NULL,
             fg2=NULL)
#Delete the downloaded archive (the zip-file)
file.remove(paste(wd,"/data/raw/","ss.zip",sep=""))
#Return to user's working directory:
setwd(wd0)
#The downloaded files can be found in directory:
print(wd)

## End(Not run)

Detects wet/dry long periods

Description

This function detects episodes of too many consecutive wet or dry days

Usage

drywetlong(x, ret = 300, sueco = 9.9, dry = TRUE, wet = TRUE)

Arguments

Value

list of positions in the input data time series which do not pass QC test

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "RR_SOUID132730.txt", package = "INQC")
#Read the data file
x<-readecad(input=path2inptfl,missing= -9999)[,4:4]
#Find all suspicious positions in the precipitation time series
drywetlong(x,ret=300,sueco=9.9,dry=TRUE,wet=TRUE)

#Introduce the long wet period
x[1:600]<-10
#Find all suspicious positions in the precipitation time series
drywetlong(x,ret=300,sueco=9.9,dry=TRUE,wet=TRUE)

Detects duplicated dates

Description

This function detects duplicated dates in the input time series

Usage

duplas(x)

Arguments

Value

vector with the list of positions which do not pass this QC test. If all positions pass the test, returns NULL

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
#Read the data file
x<-readecad(input=path2inptfl,missing= -9999)[,3]
#Find all duplicated dates in the time series
duplas(x)

#Introduce the duplicated dates
x[31]<-'19610130'
#Find all duplicated dates in the time series
duplas(x) 

Flat sequences

Description

This function detects consecutive equal values (e.g., 15.1, 15.1, 15.1, 15.1...) in a data time series. Also can be used to detect consecutive equal decimal part of the values (e.g., 15.1, 12.1, 13.1, 10.1 ...)

Usage

flat(y, maxseq, exclude = NULL)

Arguments

Value

list of positions which do not pass this QC test. If all positions pass the test, returns NULL

Examples

y<-rnorm(100)
y[10:20]<-10
flat(y,5)

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
#Read the data file
y<-readecad(input=path2inptfl,missing= -9999)[,4]
#Find all consecutive (with a length > 5 elements) equal values in the time series
flat(y,5)

#Introduce the duplicated dates
y[6:12]<-10
#Find all consecutive (with a length > 5 elements) equal values in the time series
flat(y,5)

Flat sequences for sunshine duration (only for "non-blended" ECA&D data)

Description

This function uses flat() and modifies it with "smart" comparison with clouds. If close to 8 and close to 0 clouds, allowed; if close to maxsundur and clouds near 0, allowed

Usage

flatsun(x, maxseq, id, modonube = FALSE)

Arguments

Value

list of positions which do not pass this QC test

Examples

#Set a temporal working directory:
wd <- tempdir(); wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, 'raw'))
#Extract the non-blended ECA&D data and station files from the example data folder
path2cclist<-system.file("extdata", "ECA_blend_source_cc.txt", package = "INQC")
cclist<-readr::read_lines_raw(path2cclist)
readr::write_lines(cclist,'ECA_blend_source_cc.txt')
path2ccdata<-system.file("extdata", "CC_SOUID132727.txt", package = "INQC")
ccdata<-readr::read_lines_raw(path2ccdata)
readr::write_lines(ccdata, file=paste(wd,'/raw/CC_SOUID132727.txt',sep=''))
path2sslist<-system.file("extdata", "ECA_blend_source_ss.txt", package = "INQC")
sslist<-readr::read_lines_raw(path2sslist)
readr::write_lines(sslist,'ECA_blend_source_ss.txt')
path2ssdata<-system.file("extdata", "SS_SOUID132728.txt", package = "INQC")
ssdata<-readr::read_lines_raw(path2ssdata)
readr::write_lines(ssdata, file=paste(wd,'/raw/SS_SOUID132728.txt',sep=''))
#Read the sunshine data
x<-readecad(input=path2ssdata,missing= -9999)[,3:4]
options("homefolder"='./'); options("blend"=FALSE)
listonator(check=TRUE)
#Call flatsun()
flatsun(x,5,"SS_SOUID132728.txt",modonube=FALSE)
#Introduce error values in the sunshine data
x[1:10,2]<-10
#Call flatsun()
flatsun(x,5,"SS_SOUID132728.txt",modonube=FALSE)
#Return to user's working directory:
setwd(wd0)

Creates necessary folders (if not exist)

Description

This function will checks if all necessary folders ('QCSummary, QC and QCConsolidated) exist and if not, creates them. Not intended as a stand-alone function. Called from other routines.

Usage

inithome()

Value

it does not return any values, just creates the described folders if they do not exist

Wrapper for QC'ing all variables

Description

This function calls functions which perform QC for all climate variables

Usage

inqc(homefolder = "./", blend = TRUE)

Arguments

Value

QC results, in both formats (verbose and workable file in exact ECA&D format)

Examples

#Set a temporal working directory:
wd <- tempdir(); wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, 'raw'))
#NON-BLENDED ECA&D SERIES
#Extract the non-blended ECA&D data and station files from the example data folder
#Only TX (maximum air temperature) and CC (cloud cover) data are used in the example
path2txlist<-system.file("extdata", "ECA_blend_source_tx.txt", package = "INQC")
txlist<-readr::read_lines_raw(path2txlist)
readr::write_lines(txlist,'ECA_blend_source_tx.txt')
path2txdata<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
txdata<-readr::read_lines_raw(path2txdata)
readr::write_lines(txdata, file=paste(wd,'/raw/TX_SOUID132734.txt',sep=''))
path2cclist<-system.file("extdata", "ECA_blend_source_cc.txt", package = "INQC")
cclist<-readr::read_lines_raw(path2cclist)
readr::write_lines(cclist,'ECA_blend_source_cc.txt')
path2ccdata<-system.file("extdata", "CC_SOUID132727.txt", package = "INQC")
ccdata<-readr::read_lines_raw(path2ccdata)
readr::write_lines(ccdata, file=paste(wd,'/raw/CC_SOUID132727.txt',sep=''))
#This is the MAIN starting point of the INQC software calculation:
inqc(homefolder='./',blend=FALSE) #Work with non-blended ECA&D data
#Remove some temporary files
list = list.files(pattern = "Rfwf")
file.remove(list)
#The QC results can be found in the directory:
print(wd)
#BLENDED ECA&D SERIES
#Extract the blended ECA&D data and station files from the example data folder
#Only TX (maximum air temperature) and CC (cloud cover) data are used in the example
path2list<-system.file("extdata", "stations.txt", package = "INQC")
list<-readr::read_lines_raw(path2list)
readr::write_lines(list,file=paste(wd,'/raw/stations.txt',sep=''))
path2txdata<-system.file("extdata", "TX_STAID000002.txt", package = "INQC")
txdata<-readr::read_lines_raw(path2txdata)
readr::write_lines(txdata, file=paste(wd,'/raw/TX_STAID000002.txt',sep=''))
path2ccdata<-system.file("extdata", "CC_STAID000001.txt", package = "INQC")
ccdata<-readr::read_lines_raw(path2ccdata)
readr::write_lines(ccdata, file=paste(wd,'/raw/CC_STAID000001.txt',sep=''))
#This is the MAIN starting point of the INQC software calculation:
inqc(homefolder='./',blend=TRUE) #work with blended ECA&D data
#Remove some temporary files
list = list.files(pattern = "Rfwf")
file.remove(list)
#The QC results can be found in the directory:
print(wd)
#Return to user's working directory:
setwd(wd0)

Labels interdiurnal large differences

Description

This function looks for interdiurnal differences considered too large (larger than a threshold value). The threshold can be defined by two different ways: (1) as an absolute value, the same for all differences. It is specified directly through the parameter 'force' (see below); (2) as a quantile in a probability distribution of the interdiurnal differences (built for each month separately). In this case, the threshold is specified indirectly through the parameter 'quanty' (see below). The calculated threshold quantiles can be also modified (increased/decreased) by means of the parameter 'times' (see below).

Consequently, jumps2() can be used in two different modes: 'absolute' and 'quantile'

Usage

jumps2(date, value, quanty = 0.999, times = 1, force = NULL)

Arguments

Value

list of positions which do not pass this QC test

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
#Read the data file
date<-readecad(input=path2inptfl,missing= -9999)[,3]
value<-readecad(input=path2inptfl,missing= -9999)[,4]
#Find all suspicious positions in the time series (in 'quantile' mode)
jumps2(date,value,quanty=0.999,times=1)
#Find all suspicious positions in the time series (in 'absolute' mode)
jumps2(date,value,force=100)

Creates listings for stations ('non-blended' case) linking STAID and SOUID

Description

This function takes all the elements and rbinds them into a single list to process

Usage

listas(country = "all", name = "allstations.txt")

Arguments

Value

data frame and the list file containing all stations for all elements, linking STAID and SOUID and metadata

Examples

#Set a temporal working directory:
wd <- tempdir(); wd0 <- setwd(wd)
#Extract the non-blended ECA&D station files from the example data folder
#Only TX (maximum air temperature) and CC (cloud cover) variables are used in the example
path2txlist<-system.file("extdata", "ECA_blend_source_tx.txt", package = "INQC")
txlist<-readr::read_lines_raw(path2txlist)
readr::write_lines(txlist,'ECA_blend_source_tx.txt')
path2cclist<-system.file("extdata", "ECA_blend_source_cc.txt", package = "INQC")
cclist<-readr::read_lines_raw(path2cclist)
readr::write_lines(cclist,'ECA_blend_source_cc.txt')
options("homefolder"='./')
liston.nb<-listas(country='all',name='allstations.txt')
#The created list file can be found in the directory:
print(wd)
#Return to user's working directory:
setwd(wd0)

Creates a list of blended/non-bladed files for some climate variable

Description

This function creates a list of blended or non-bladed files containing data of a specified element to be QCed.

Usage

lister(element)

Arguments

Value

list of blended or non-bladed files to be QCed

Examples

#Set a temporal working directory:
wd <- tempdir(); wd0 <- setwd(wd)
#Create subdirectory where a station file has to be located
dir.create(file.path(wd, 'raw'))
#NON-BLENDED ECA&D SERIES
#Extract the non-blended ECA&D data and station files from the example data folder
#Only TX (maximum air temperature) and CC (cloud cover) data are used in the example
path2txdata<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
txdata<-readr::read_lines_raw(path2txdata)
readr::write_lines(txdata, file=paste(wd,'/raw/TX_SOUID132734.txt',sep=''))
path2ccdata<-system.file("extdata", "CC_SOUID132727.txt", package = "INQC")
ccdata<-readr::read_lines_raw(path2ccdata)
readr::write_lines(ccdata, file=paste(wd,'/raw/CC_SOUID132727.txt',sep=''))
options("homefolder"='./'); options("blend"=FALSE)
list.nb<-lister('TX')
#BLENDED ECA&D SERIES
#Extract the blended ECA&D data and station files from the example data folder
#Only TX (maximum air temperature) and CC (cloud cover) data are used in the example
path2txdata<-system.file("extdata", "TX_STAID000002.txt", package = "INQC")
txdata<-readr::read_lines_raw(path2txdata)
readr::write_lines(txdata, file=paste(wd,'/raw/TX_STAID000002.txt',sep=''))
path2ccdata<-system.file("extdata", "CC_STAID000001.txt", package = "INQC")
ccdata<-readr::read_lines_raw(path2ccdata)
readr::write_lines(ccdata, file=paste(wd,'/raw/CC_STAID000001.txt',sep=''))
options("blend"=TRUE)
list.b<-lister('TX')
#Return to user's working directory:
setwd(wd0)

Creates a list (as 'Global' variable) of stations to be QCed.

Description

This function creates a list (and makes it 'Global' variable) of stations to be QCed. It can be 'blended' or 'non-blended' stations. Geographical coordinates are converted into decimal degrees

Usage

listonator(check = TRUE)

Arguments

Value

list of stations to be QCed

Examples

#Set a temporal working directory:
wd <- tempdir(); wd0 <- setwd(wd)
#NON-BLENDED ECA&D SERIES
#Extract the non-blended ECA&D station files from the example data folder
#Only TX (maximum air temperature) and CC (cloud cover) variables are used in the example
path2txlist<-system.file("extdata", "ECA_blend_source_tx.txt", package = "INQC")
txlist<-readr::read_lines_raw(path2txlist)
readr::write_lines(txlist,'ECA_blend_source_tx.txt')
path2cclist<-system.file("extdata", "ECA_blend_source_cc.txt", package = "INQC")
cclist<-readr::read_lines_raw(path2cclist)
readr::write_lines(cclist,'ECA_blend_source_cc.txt')
options("homefolder"='./'); options("blend"=FALSE)
listonator(check=TRUE)
liston.nb<-getOption("liston")
#BLENDED ECA&D SERIES
#Create subdirectory where a station file has to be located
dir.create(file.path(wd, 'raw'))
#Extract the blended ECA&D station file from the example data folder
path2list<-system.file("extdata", "stations.txt", package = "INQC")
list<-readr::read_lines_raw(path2list)
readr::write_lines(list,file=paste(wd,'/raw/stations.txt',sep=''))
options("blend"=TRUE)
listonator(check=TRUE)
liston.b<-getOption("liston")
#Return to user's working directory:
setwd(wd0)

Isolates values which are not continuous in the distribution

Description

The function isolates extreme values which are not continuous in the distribution. If the gap is larger (or smaller) than a pre-set big margin, the values above (or below) are flagged

Usage

newfriki(date, value, margina = 0.999, times = 2)

Arguments

Value

positions which do not pass this QC test

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
#Read the data file
date<-readecad(input=path2inptfl,missing= -9999)[,3]
value<-readecad(input=path2inptfl,missing= -9999)[,4]
#Find all suspicious positions in the time series
newfriki(date,value,margina=0.999,times=1)

Finds outliers

Description

This function finds outliers for variables which can be described/evaluated by means of the Pareto distribution (e.g. atmospheric precipitation or wind speed)

Usage

paretogadget(x, ret)

Arguments

Value

list of positions which do not pass this QC test (which can be considered as outliers)

Examples

#Extract the ECA&D precipitation data file from the example data folder
path2inptfl<-system.file("extdata", "RR_SOUID132730.txt", package = "INQC")
#Read the data file
x<-readecad(input=path2inptfl,missing= -9999)[,4]
#Find all suspicious positions in the time series corresponding to the requested return period
paretogadget(x,25)
#Suspicious values
x[paretogadget(x,25)]

Isolates anomalous values

Description

Given a data vector, the function will compare the values to the specified threshold

Usage

physics(x, nyu = 0, compare = 1)

Arguments

Value

list of positions which do not pass this QC test. If all positions pass the test, returns NULL

Examples

x<-rnorm(100)
x[10]<-100
physics(x,5,1)

Peaks over threshold modelling

Description

This function fits the Generalized Pareto distribution for exeedances over a threshold

Usage

potpareto(y, thres = 0.99)

Arguments

Value

list containing results of modelling/fitting the generalized Pareto distribution

Examples

#Extract the ECA&D precipitation data file from the example data folder
path2inptfl<-system.file("extdata", "RR_SOUID132730.txt", package = "INQC")
#Read the data file
y<-readecad(input=path2inptfl,missing= -9999)[,4]
#Fit the Generalized Pareto distribution
pato<-potpareto(y)
#The parameters of the fitted distribution:
location<-pato$threshold
shape<-pato$estimate[2]
scale<-pato$estimate[1]
print(c(location,shape,scale))

QC for Atmospheric Precipitation (RR)

Description

This function will centralize precipitation-like QC routines. It will create a file in the folder QC with an additional 0/1 column, where "1" means test failed.

Usage

precip(
  element = "RR",
  large = 5000,
  small = 0,
  ret = 500,
  retornoracha = 500,
  margin = 20,
  friki = 150,
  blocksizeround = 20,
  blockmanymonth = 15,
  blockmanyyear = 180,
  limit = 1500,
  tolerance = 8,
  maxseq = 3,
  roundmax = 10,
  level = 15,
  window = 30,
  margina = 0.999,
  inisia = FALSE
)

Arguments

Value

results of QC for RR

Examples

#Set a temporal working directory:
wd <- tempdir()
wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, 'raw'))
options("homefolder"='./'); options("blend"=FALSE)
#Extract the ECA&D data and station files from the example data folder
path2rrlist<-system.file("extdata", "ECA_blend_source_rr.txt", package = "INQC")
rrlist<-readr::read_lines_raw(path2rrlist)
readr::write_lines(rrlist,'ECA_blend_source_rr.txt')
path2rrdata<-system.file("extdata", "RR_SOUID132730.txt", package = "INQC")
rrdata<-readr::read_lines_raw(path2rrdata)
readr::write_lines(rrdata, file=paste(wd,'/raw/RR_SOUID132730.txt',sep=''))
#Perform QC of Atmospheric Precipitation data
precip(inisia=TRUE)
#Remove some temporary files
list = list.files(pattern = "Rfwf")
file.remove(list)
#Return to user's working directory:
setwd(wd0)
#The QC results can be found in the directory:
print(wd)

Merges julian days

Description

This function merges julian days to a yyyy,mm,dd and data

Usage

putjulian(x)

Arguments

Value

the same data frame with added 1 column: year, month, day, julian and data

Examples

date<-c('20201230','20201231','20210101')
value<-c(-10,-12,-9)
df<-data.frame(date,value)
year<-as.numeric(substring(date,1,4))
month<-as.numeric(substring(date,5,6))
day<-as.numeric(substring(date,7,8))
x<-data.frame(year,month,day,date,value)
y<-putjulian(x)

Reads an ECA&D data/sources/stations file

Description

This function reads one ECA&D file and puts it in yyyy/mm/dd/value. Data is NOT divided by 10, to transform it into true units

Usage

readecad(input = "SS_STAID000143.txt", missing = -9999)

Arguments

Value

data frame containing data (time series) from the ECA&D file. An introductory part of the ECA&D file with meta data information is skipped

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "CC_SOUID132727.txt", package = "INQC")
#Read the data file
df<-readecad(input=path2inptfl,missing= -9999) 

Reads the header of an ECA&D file

Description

This function reads one ECA&D file and returns the header (an introductory part of the ECA&D file), so it can be written in the same way

Usage

readheader(input = "SS_STAID000143.txt")

Arguments

Value

header of an ECA&D file

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "CC_SOUID132727.txt", package = "INQC")
#Read the data file
head<-readheader(input=path2inptfl)

QC for Relative Humidity (HU)

Description

This function will centralize temperature-like QC routines. Will create a file in the folder QC with an additional 0/1 column, where "1" means test failed.

Usage

relhum(
  element = "HU",
  maxseq = 3,
  blocksizeround = 20,
  blockmanymonth = 15,
  blockmanyyear = 180,
  roundmax = 10,
  inisia = FALSE
)

Arguments

Value

results of QC for HU

Examples

#Set a temporal working directory:
wd <- tempdir()
wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, 'raw'))
options("homefolder"='./'); options("blend"=FALSE)
#Extract the ECA&D data and station files from the example data folder
path2hulist<-system.file("extdata", "ECA_blend_source_hu.txt", package = "INQC")
hulist<-readr::read_lines_raw(path2hulist)
readr::write_lines(hulist,'ECA_blend_source_hu.txt')
path2hudata<-system.file("extdata", "HU_SOUID132735.txt", package = "INQC")
hudata<-readr::read_lines_raw(path2hudata)
readr::write_lines(hudata, file=paste(wd,'/raw/HU_SOUID132735.txt',sep=''))
#Perform QC of Relative Humidity data
relhum(inisia=TRUE)
#Remove some temporary files
list = list.files(pattern = "Rfwf")
file.remove(list)
#Return to user's working directory:
setwd(wd0)
#The QC results can be found in the directory:
print(wd)

Finds repeated values

Description

This function looks for a value which repeats too many times and, given the decaying shape of empirical distribution of precipitation data, is considered too large to happen that many times

Usage

repeatedvalue(x, margin = 20, friki = 150)

Arguments

Value

list of positions which do not pass this QC test. If all positions pass the test, returns NULL

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "RR_SOUID132730.txt", package = "INQC")
#Read the data file
x<-readecad(input=path2inptfl,missing= -9999)[,4]
#Find all suspicious positions in the time series
repeatedvalue(x,margin=10,friki=10)

Threshold percentile for the Pareto outliers

Description

This function returns a value of a threshold percentile for the Pareto outliers

Usage

returnpotpareto(pato, ret, w = 1.65)

Arguments

Value

for a given Pareto distribution, returns the value (the quantile) representing a requested return period

Examples

#Extract the ECA&D precipitation data file from the example data folder
path2inptfl<-system.file("extdata", "RR_SOUID132730.txt", package = "INQC")
#Read the data file
y<-readecad(input=path2inptfl,missing= -9999)[,4]
#Fit the Generalized Pareto distribution
pato<-potpareto(y)
#Define the quantile corresponding to the requested return period 25 years (ret=25)
returnpotpareto(pato,25)
#Define the quantile assuming the existence of 2 precipitation peaks/extreme values 
#every year (on average)
returnpotpareto(pato,25,w=2)

Detects rounded sections

Description

This function splits data by month and looks if a decimal value is repeated too many times

Usage

rounding(y, blocksize = 20)

Arguments

Value

list of positions which do not pass this QC test. If all positions pass the test, returns NULL

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
#Read the data file
y<-readecad(input=path2inptfl,missing= -9999)[,3:4]
#Introduce the rounding errors in first 50 data values
y[1:50,2]<-round((y[1:50,2])/10)*10
#Find all suspicious positions in the time series
rounding(y,blocksize=20)

Rounding in precipitation data

Description

This function splits data by month and looks if a decimal value is repeated too many times

Usage

roundprecip(y, blocksize = 20, exclude = 0)

Arguments

Value

list of positions which do not pass this QC test. If all positions pass the test, returns NULL

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "RR_SOUID132730.txt", package = "INQC")
#Read the data file
y<-readecad(input=path2inptfl,missing= -9999)[,3:4]
#Find all suspicious positions in the precipitation time series
roundprecip(y,blocksize=20,exclude=0) 

QC for Atmospheric Pressure (PP)

Description

This function will centralize temperature-like QC routines. It will create a file in the folder QC with an additional 0/1 column where "1" means test failed.

Usage

selepe(
  element = "PP",
  large = 15000,
  small = 8000,
  maxjump = 2000,
  maxseq = 3,
  margina = 0.999,
  level = 5,
  window = 30,
  roundmax = 10,
  blockmanymonth = 15,
  blockmanyyear = 180,
  blocksizeround = 20,
  qjump = 0.999,
  tjump = 1.5,
  inisia = FALSE
)

Arguments

Value

results of QC for PP

Examples

#Set a temporal working directory:
wd <- tempdir()
wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, 'raw'))
options("homefolder"='./'); options("blend"=FALSE)
#Extract the ECA&D data and station files from the example data folder
path2pplist<-system.file("extdata", "ECA_blend_source_pp.txt", package = "INQC")
pplist<-readr::read_lines_raw(path2pplist)
readr::write_lines(pplist,'ECA_blend_source_pp.txt')
path2ppdata<-system.file("extdata", "PP_SOUID132729.txt", package = "INQC")
ppdata<-readr::read_lines_raw(path2ppdata)
readr::write_lines(ppdata, file=paste(wd,'/raw/PP_SOUID132729.txt',sep=''))
#Perform QC of Atmospheric Pressure data
selepe(inisia=TRUE)
#Remove some temporary files
list = list.files(pattern = "Rfwf")
file.remove(list)
#Return to user's working directory:
setwd(wd0)
#The QC results can be found in the directory:
print(wd)

QC for Snow Depth (SD)

Description

This function will centralize temperature-like QC routines. It will create a file in the folder QC with an additional 0/1 column, where "1" means test failed.

Usage

snowdepth(
  element = "SD",
  maxseq = 20,
  blocksizeround = 20,
  blockmanymonth = 20,
  blockmanyyear = 200,
  large = 5000,
  exclude = 0,
  inisia = FALSE
)

Arguments

Value

results of QC for SD

Examples

#Set a temporal working directory:
wd <- tempdir()
wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, 'raw'))
options("homefolder"='./'); options("blend"=FALSE)
#Extract the ECA&D data and station files from the example data folder
path2sdlist<-system.file("extdata", "ECA_blend_source_sd.txt", package = "INQC")
sdlist<-readr::read_lines_raw(path2sdlist)
readr::write_lines(sdlist,'ECA_blend_source_sd.txt')
path2sddata<-system.file("extdata", "SD_SOUID132731.txt", package = "INQC")
sddata<-readr::read_lines_raw(path2sddata)
readr::write_lines(sddata, file=paste(wd,'/raw/SD_SOUID132731.txt',sep=''))
#Perform QC of Snow Depth data
snowdepth(inisia=TRUE)
#Remove some temporary files
list = list.files(pattern = "Rfwf")
file.remove(list)
#Return to user's working directory:
setwd(wd0)
#The QC results can be found in the directory:
print(wd)

Maximum sunshine hours (only for "non-blended" ECA&D data)

Description

This function compares sunshine data to the maximum theoretical sunshine at an ECA&D station, according the day, lat and lon. Maximum sunshine hours are computed from the "suncalc" package, using "night" and "dawn" parameters. This contrasts quite a lot with other functions computing "daylength". This formulation is more conservative

Usage

sunafterdark(y, code = "991274")

Arguments

Details

depends on either a previous execution of listas() or on a proper execution of listas() to run properly

Value

vector with the list of positions which do not pass this test. If all positions pass the test, returns NULL

See Also

listas()

Examples

#Set a temporal working directory:
wd <- tempdir(); wd0 <- setwd(wd)
#Extract the non-blended ECA&D data and a station file from the example data folder
path2sslist<-system.file("extdata", "ECA_blend_source_ss.txt", package = "INQC")
sslist<-readr::read_lines_raw(path2sslist)
readr::write_lines(sslist,'ECA_blend_source_ss.txt')
path2ssdata<-system.file("extdata", "SS_SOUID132728.txt", package = "INQC")
#Read the sunshine data
y<-readecad(input=path2ssdata,missing= -9999)[,3:4]
options("homefolder"='./'); options("blend"=FALSE)
listonator(check=TRUE)
#Call sunafterdark()
sunafterdark(y,code='132728')
#Introduce error values in the sunshine data
y[1:10,2]<-200
#Call sunafterdark()
sunafterdark(y,code='132728')
#Return to user's working directory:
setwd(wd0)

QC for Sunshine Duration (SS)

Description

This function will centralize temperature-like QC routines. Will create a file in the folder QC with an additional 0/1 column, where "1" means test failed

Usage

sundur(
  element = "SS",
  maxseq = 3,
  blocksizeround = 20,
  blockmanymonth = 15,
  blockmanyyear = 180,
  roundmax = 10,
  inisia = FALSE
)

Arguments

Value

results of QC for SS

Examples

#Set a temporal working directory:
wd <- tempdir()
wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, 'raw'))
options("homefolder"='./'); options("blend"=FALSE)
#Extract the ECA&D data and station files from the example data folder
path2sslist<-system.file("extdata", "ECA_blend_source_ss.txt", package = "INQC")
sslist<-readr::read_lines_raw(path2sslist)
readr::write_lines(sslist,'ECA_blend_source_ss.txt')
path2ssdata<-system.file("extdata", "SS_SOUID132728.txt", package = "INQC")
ssdata<-readr::read_lines_raw(path2ssdata)
readr::write_lines(ssdata, file=paste(wd,'/raw/SS_SOUID132728.txt',sep=''))
#Perform QC of Sunshine Duration data
sundur(inisia=TRUE)
#Remove some temporary files
list = list.files(pattern = "Rfwf")
file.remove(list)
#Return to user's working directory:
setwd(wd0)
#The QC results can be found in the directory:
print(wd)

Detects precipitation values above limit

Description

This function detects values above limit preceded by a number of "non precipitation days", given by tolerance

Usage

suspectacumprec(datos, limit = 2000, tolerance = 10)

Arguments

Value

list of positions which do not pass this QC test

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "RR_SOUID132730.txt", package = "INQC")
#Read the data file
datos<-readecad(input=path2inptfl,missing= -9999)[,3:4]
#Find all suspicious positions in the precipitation time series
suspectacumprec(datos,limit=2000,tolerance=10)

QC for Air Temperature (TX/TN/TG)

Description

This function will centralize temperature-like QC routines. It will QC files for temperature. Reads all the temperature data in the ./raw folder (TX, TN or TG) and quality controls each of them. Notice that ECA&D stores temperature in 1/10th of Celsius degrees when entering new parameter values

Usage

temperature(
  element = "TX",
  large = 500,
  small = -500,
  maxjump = 200,
  maxseq = 3,
  margina = 0.999,
  level = 4,
  window = 11,
  roundmax = 10,
  blockmanymonth = 15,
  blockmanyyear = 180,
  blocksizeround = 20,
  qjump = 0.999,
  tjump = 1.5,
  inisia = FALSE
)

Arguments

Value

results of QC for TX/TN/TG

See Also

consolidator(), duplas(), flat(), IQRoutliers(), jumps2(), newfriki(), physics(), toomany(), rounding(), txtn(), weirdate()

Examples

#Set a temporal working directory:
wd <- tempdir()
wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, 'raw'))
options("homefolder"='./'); options("blend"=FALSE)
#Extract the ECA&D data and station files from the example data folder
path2tnlist<-system.file("extdata", "ECA_blend_source_tn.txt", package = "INQC")
tnlist<-readr::read_lines_raw(path2tnlist)
readr::write_lines(tnlist,'ECA_blend_source_tn.txt')
path2tndata<-system.file("extdata", "TN_SOUID132733.txt", package = "INQC")
tndata<-readr::read_lines_raw(path2tndata)
readr::write_lines(tndata, file=paste(wd,'/raw/TN_SOUID132733.txt',sep=''))
#Perform QC of Air Temperature data
temperature(element='TN',inisia=TRUE)
#Remove some temporary files
list = list.files(pattern = "Rfwf")
file.remove(list)
#Return to user's working directory:
setwd(wd0)
#The QC results can be found in the directory:
print(wd)

Looks if a value is repeated too many times

Description

This function splits data by month and looks if a value is repeated too many times

Usage

toomany(y, blockmany = 15, scope = 1, exclude = NULL)

Arguments

Value

list of positions which do not pass this QC test. If all positions pass the test, returns NULL

Examples

#Extract the ECA&D data file (maximum air temperature) from the example data folder
path2inptfl<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
#Read the data file
y<-readecad(input=path2inptfl,missing= -9999)[,3:4]
#Introduce the errors in first 20 data values
y[1:20,2]<-30
#Find all suspicious positions in the time series
toomany(y,blockmany=15,scope=1,exclude=NULL)

#Extract the ECA&D data file (atmospheric precipitation) from the example data folder
path2inptfl<-system.file("extdata", "RR_SOUID132730.txt", package = "INQC")
#Read the data file
y<-readecad(input=path2inptfl,missing= -9999)[,3:4]
#Introduce the errors in first 20 data values
y[1:20,2]<-10
#Find all suspicious positions in the time series
toomany(y,blockmany=15,scope=1,exclude=0)

Comparison of tx an tn data (for "non-blended" ECA&D data)

Description

This function compares tx an tn data. First it looks for the closest station and then merges both data frames. If one value is flagged, looks at the ecdfs of tx and tn. If the target variable (e.g tx) is central (between quantiles 0.2 and 0.8) and the other variable (e.g. tn) is outside this range, the value is not flagged, assuming the other variable is the culprit

Usage

txtn(y, id)

Arguments

Value

list of positions which do not pass this QC test. If all positions pass the test, returns NULL

Examples

#Set a temporal working directory:
wd <- tempdir(); wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, "raw"))
#Extract the non-blended ECA&D data and station files from the example data folder
path2txlist<-system.file("extdata", "ECA_blend_source_tx.txt", package = "INQC")
txlist<-readr::read_lines_raw(path2txlist)
readr::write_lines(txlist,"ECA_blend_source_tx.txt")
path2txdata<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
txdata<-readr::read_lines_raw(path2txdata)
readr::write_lines(txdata, file=paste(wd,"/raw/TX_SOUID132734.txt",sep=""))
path2tnlist<-system.file("extdata", "ECA_blend_source_tn.txt", package = "INQC")
tnlist<-readr::read_lines_raw(path2tnlist)
readr::write_lines(tnlist,"ECA_blend_source_tn.txt")
path2tndata<-system.file("extdata", "TN_SOUID132733.txt", package = "INQC")
tndata<-readr::read_lines_raw(path2tndata)
readr::write_lines(tndata, file=paste(wd,"/raw/TN_SOUID132733.txt",sep=""))
#Read the tn data
y<-readecad(input=path2tndata,missing= -9999)[,3:4]
options("homefolder"="./"); options("blend"=FALSE)
listonator(check=TRUE)
#Call txtn()
txtn(y,"TN_SOUID132733.txt")
#Introduce error values in the tn data
y[c(1,3),2]<-100
#Call txtn()
txtn(y,"TN_SOUID132733.txt")
#Return to user's working directory:
setwd(wd0)

Comparison of tx an tn data (for "blended" ECA&D data)

Description

This function first looks for the closest station and then merges both data frames. If one value is flagged, looks at the ecdfs of tx and tn. If the target variable (e.g tx) is central (between quantiles 0.2 and 0.8) and the other variable (e.g. tn) is outside this range, the value is not flagged, assuming the other variable is the culprit

Usage

txtnblend(y, id)

Arguments

Value

list of positions which do not pass this QC test. If all positions pass the test, returns NULL

Examples

#Set a temporal working directory:
wd <- tempdir(); wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, "raw"))
#Extract the blended ECA&D data and station files from the example data folder
path2list<-system.file("extdata", "stations.txt", package = "INQC")
list<-readr::read_lines_raw(path2list)
readr::write_lines(list,file=paste(wd,"/raw/stations.txt",sep=""))
path2txdata<-system.file("extdata", "TX_STAID000002.txt", package = "INQC")
txdata<-readr::read_lines_raw(path2txdata)
readr::write_lines(txdata, file=paste(wd,"/raw/TX_STAID000002.txt",sep=""))
path2tndata<-system.file("extdata", "TN_STAID000002.txt", package = "INQC")
tndata<-readr::read_lines_raw(path2tndata)
readr::write_lines(tndata, file=paste(wd,"/raw/TN_STAID000002.txt",sep=""))
#Read the tn data
y<-readecad(input=path2tndata,missing= -9999)[,3:4]
options("homefolder"="./")
#Call txtnblend()
txtnblend(y,"TN_STAID000002.txt")
#Introduce error values in the tn data
y[c(1,3),2]<-100
#Call txtnblend()
txtnblend(y,"TN_STAID000002.txt")
#Return to user's working directory:
setwd(wd0)

Locate impossible dates

Description

This function is intended to flag impossible dates (e.g., 19990230 or 29990112, etc)

Usage

weirddate(x)

Arguments

Value

list of positions which do not pass this QC test. If all positions pass the test, returns NULL

Examples

#Extract the ECA&D data file from the example data folder
path2inptfl<-system.file("extdata", "TX_SOUID132734.txt", package = "INQC")
#Read the data file
x<-readecad(input=path2inptfl,missing= -9999)[,3:4]
#Find all suspicious positions in the time series
weirddate(x)

#Introduce the weird dates
x[31,1]<-'19610132'
#Find all suspicious positions in the time series
weirddate(x) 

QC for Wind Speed (FG)

Description

This function will centralize temperature-like QC routines. It will create a file in the folder QC with an additional 0/1 column, where "1" means test failed.

Usage

windspeed(
  element = "FG",
  maxseq = 3,
  blocksizeround = 20,
  blockmanymonth = 20,
  blockmanyyear = 200,
  large = 3000,
  roundmax = 10,
  level = 5,
  window = 30,
  ret = 500,
  margina = 0.999,
  inisia = FALSE
)

Arguments

Value

results of QC for FG

Examples

#Set a temporal working directory:
wd <- tempdir()
wd0 <- setwd(wd)
#Create subdirectory where raw data files have to be located
dir.create(file.path(wd, 'raw'))
options("homefolder"='./'); options("blend"=FALSE)
#Extract the ECA&D data and station files from the example data folder
path2fglist<-system.file("extdata", "ECA_blend_source_fg.txt", package = "INQC")
fglist<-readr::read_lines_raw(path2fglist)
readr::write_lines(fglist,'ECA_blend_source_fg.txt')
path2fgdata<-system.file("extdata", "FG_SOUID132736.txt", package = "INQC")
fgdata<-readr::read_lines_raw(path2fgdata)
readr::write_lines(fgdata, file=paste(wd,'/raw/FG_SOUID132736.txt',sep=''))
#Perform QC of Wind Speed data
windspeed(inisia=TRUE)
#Remove some temporary files
list = list.files(pattern = "Rfwf")
file.remove(list)
#Return to user's working directory:
setwd(wd0)
#The QC results can be found in the directory:
print(wd)