temporal_coherence: Daily temporal coherence test

In C3S-Data-Rescue-Lot1-WP3/C3S-QC: C3S quality control tools for historical climate data

Description

Find those records where daily maximum or minimum temperature, mean wind speed, snow depth, snow cover, or fresh snow differences with previous day are too large.

Usage

temporal_coherence(dailydata, meta = NULL, outpath = getwd(),
  temp_jumps = 20, windspeed_jumps = 15, snowdepth_jumps = 50)

Arguments

dailydata	A character string giving the path of the input file, or a 5-column matrix with following columns: variable code, year, month, day, and the daily value.
meta	A character vector with 6 elements: station ID, latitude, longitude, altitude, variable code, units. If dailydata is a path, meta is ignored.
outpath	Character string giving the path for the QC results. By default this is the working directory.
temp_jumps	given a daily maximum or minimum temperature values of two consecutive days, maximum difference in degrees Celsius. By default, temp_jumps = 20 C.
windspeed_jumps	given a daily mean wind speed value of two consecutive days, maximum difference in metres per second. By default, wind_jumps = 15 m/s.
snowdepth_jumps	given a daily snow depth of two consecutive days, maximum difference in centimetres. By default, snowdepth_jumps = 50 cm.

Details

The input file must follow the Copernicus Station Exchange Format (SEF).

Author(s)

Alba Gilabert, Yuri Brugnara

Examples

temporal_coherence(Rosario$Tx, Meta$Tx, temp_jumps = 10)

C3S-Data-Rescue-Lot1-WP3/C3S-QC documentation built on Jan. 15, 2020, 10:36 p.m.