impossible_values: Gross Errors Test for Cloud Cover and Relative Humidity.

In dataresqc: C3S Quality Control Tools for Historical Climate Data

Gross Errors Test for Cloud Cover and Relative Humidity.

Description

Applicable to a series (daily or sub-daily) of relative humidity (rh) in percent or to a series of cloud cover (n) in percent or oktas.

Usage

impossible_values(series, meta = NULL, outpath)

Arguments

series	A character string giving the path of the SEF file, or a five or seven-column (daily or subdaily) data frame with the series.
meta	A character vector with 6 elements: station ID, latitude, longitude, altitude, variable code, units. If series is a path, meta is ignored.
outpath	Character string giving the path for the QC results.

Details

Input:

• A SEF file or a data frame and metadata. The observations data frame must have five or seven columns: variable code, year (YYYY), month (MM), day (DD), (hour (HH), minute (MM)), observation.

Output:

• A text file of flagged observations with six or eight columns: variable code, year (YYYY), month (MM), day (DD), (hour (HH), minute (MM)), observation, test. The test column has the description "gross_errors".

• The flagged observations correspond to values that don't belong to the integer interval (0, 100) if the unit is percent or that don't belong to the integer interval (0, 9) if the unit is oktas.

Author(s)

Clara Ventura, Yuri Brugnara

Examples

impossible_values(series = Rosario$n, meta = Meta$n, outpath = tempdir())
impossible_values(series = Rosario$rh, meta = Meta$rh, outpath = tempdir())

dataresqc documentation built on April 3, 2023, 5:08 p.m.