add_date

Description

Adds dates in wich the weather types are obtained

Usage

add_date(f, d)

Arguments

calculate_constant

Description

Calculates constants required to apply the rules

Usage

calculate_constant(lon, lat)

Arguments

calculate_cwt

Description

Applies the rules to obtain the weather types. (more details, see Jones et al. 1997)

Usage

calculate_cwt(Z, TF, directionflow, G, thr = 6, Gth = 30)

Arguments

Details

As defined in the original scheme, the threshold to determine unclassified days is 6. Gale days are estimated by using a threshold of 30. If Gale days with a greater intensity (e.g. 40 or 50) is wanted, Gth must be changed. The airflow indices are used within the following rules to define the appropriate Lamb weather types.

• The appropriate direction is calculated on an eight-point compass allowing 45° per sector.

• If abs(Z) is less than TF, flow is essentially pure directional type.

• If |Z| is greater than 2TF, then the pattern is strongly cyclonic (Z > 0) or anticyclonic (Z < 0).

• If |Z| lies between TF and 2TF then the flow is partly (anti-) cyclonic and this corresponds to one of Lamb’s synoptic/direction hybrid types, e.g. AE.

• If TF is less than 6 and |Z| is less than 6, there is light indeterminate flow corresponding to Lamb’s unclassified type U.

Value

A list with two objects:

• Total_CWT with five groups of weather types: LWT_D, LWT_C, LWT_CH, LWT_U and LWT_G The main four groups contain the total of 27 weather types and the five list LWT_G refers to the gale days.

  • LWT_D: 8 directional types.

  • LWT_C: 1 anticyclonic and 1 cyclonic.

  • LWT_CH: 16 hybrid types.

  • LWT_U: 1 unclassified type.

• Logical values of daily occurrence of each type. The user might want to use these values to get composites with specific atmospheric fields (e.g. pressure, temperature).

See Also

classification_jc

calculate_frequency

Description

Computes the frequency of weather types, after dividing the frequency of the hybrid types

Usage

calculate_frequency(datalist, purelist, let)

Arguments

classification_jc

Description

Calculates the classification of the main weather types for one central point that is surrounded by 16-points (grid16). Wind-flow characteristics are computed for the daily pressure field according to the rules proposed by the original Jenkinson and Collison classification (see Jones et al. 1993, Jones et al. 2016).

Usage

classification_jc(mslp, grid16, centralp, loni, lati, times, gale)

Arguments

Value

Daily frequencies of Weather Types and airflow indices.

References

Jones, P. D., Hulme M., Briffa K. R. (1993) A comparison of Lamb circulation types with an objective classification scheme Int. J. Climatol. 13: 655–663.

Jones, P. D., Harpham C, Briffa K. R. (2013) Lamb weather types derived from Reanalysis products Int. J. Climatol. 33: 1129–1139.

See Also

calculate_cwt

Examples

# Load data
data(press)
mslp  <- press$msl
loni  <- press$loni
lati  <- press$lati
times <- press$dates
# Define a central point
centralp <- c(10,50)
# Get the scheme for the  central point
grid16 <- get_jcpoints(10,50)[1:16]
classification_jc(mslp, grid16, centralp, loni, lati, times, gale=FALSE)

create_ncdfcwt

Description

Converts 3D arrays with daily frequencies of weather types to NETCDF files.

Usage

create_ncdfcwt(cwt_out, times, centralp, onefile = TRUE, path = NULL)

Arguments

Value

A netcdf file with all weather types or one file per type.

See Also

createindex_ncdfextended_jc

Examples

# This is a long running example
cwtGlobal <- extended_jc(press$msl, press$loni, press$lati, press$dates, gale=FALSE, num_cores=2)
# Create ncdf file (one file with all types)
create_ncdfcwt(cwtGlobal, press$dates, cwtGlobal$centralp, onefile = TRUE, path = NULL)

createindex_ncdf

Description

Converts 3D arrays with daily values of airflow indices to NETCDF files.

Usage

createindex_ncdf(cwt_out, times, centralp, path = NULL)

Arguments

Value

A ncdf file with the airflow indices.

See Also

create_ncdfcwtextended_jc

Examples

# This is a long running example
cwtGlobal <- extended_jc(press$msl, press$loni, press$lati, press$dates, gale=FALSE, num_cores=2)
# Create ncdf file (one file with all types)
createindex_ncdf(cwtGlobal, press$dates, cwtGlobal$centralp, path = NULL)

extended_jc

Description

Gets daily classification of weather types at every grid-point over the map or selected area of interest according to the Jenkison and Collison scheme.

Usage

extended_jc(mslp, loni, lati, times, gale = FALSE, num_cores = 2)

Arguments

Value

A list with two objects:

• A list of eleven matrix of daily frequencies of weather types ("wtypes"). Each matrix is a 3D array [loni,lati,times] and it refers to each weather type (N,NE,E,SE,S,SW,W,A,C and U).

• A list of six matrix of daily frequency of airflow indices ("indices"). Each matrix is a 3D array [loni,lati,times] and it refers to each airflow index (W,S,TF,ZW,ZS,Z and D).

• A list with the central points for which the classification is applied.

References

Otero, N., Sillmann, J. & Butler, T. Assessment of an extended version of the Jenkinson–Collison classification on CMIP5 models over Europe Climate Dynamics. https://doi.org/10.1007/s00382-017-3705-y

See Also

classification_jc calculate_cwt

Examples

# Load data
data(press)
# Get coordinates
longitudes <- press$loni
latitudes  <- press$lati
times      <- press$dates

# Example when the classification is restricted to an area
# Select longitudes and latitudes within the European domain: -10W,40E, 40N,70N
ilon  <- which(longitudes>(-10)&longitudes<40)
loni  <- longitudes[ilon]
ilat  <- which(latitudes>40&latitudes<70)
lati  <- latitudes[ilat]
cwtEU <- extended_jc(press$msl[ilon,ilat,], loni, lati, times, gale=FALSE, num_cores=2)
 ## Not run: 
# Not run
# This is a long running example
# Get the classification for the whole map, all longitudes and latitudes
cwtGlobal <- extended_jc(press$msl, longitudes, latitudes, times, gale=FALSE, num_cores=2)

## End(Not run)

get_div

Description

Divides the frequency of the hybrid type according to the rules # TODO: which rules?

Usage

get_div(fr, nam)

Arguments

get_jcpoints

Description

Computes the 16-grid points that determine the JC-scheme, based on the coordinates of the central point.

Usage

get_jcpoints(lon, lat)

Arguments

Details

The function excludes the poles and the equatorial areas between 25S-25N.

Value

A data frame with the coordinates of the 16-grid points and the central point.

See Also

plot_jcscheme

getmat_cwt

Description

Puts in a matrix the resulting list

Usage

getmat_cwt(cwt_out, centralp, times, out = c("CWT", "indices"))

Arguments

getname_hyb

Description

Gets the name of the hybrid types to account for the rest of the types

Usage

getname_hyb(hybrid_div)

Arguments

isnot_validcp

Description

Checks if the central point used is valid.

Usage

isnot_validcp(grid16, loni, lati)

Arguments

plot_freqmap_wtypes

Description

Visualises absolute frequencies of the 11 main types from the extended_jc over the period.

Usage

plot_freqmap_wtypes(mat, loni, lati, all.types = TRUE, mytype = NULL,
  center = TRUE)

Arguments

Value

A ggplot2 map

See Also

extended_jc

Examples

## Not run: 
library(jcext)
# This is a long running example for plotting results for all types globally
cwtGlobal <- extended_jc(press$msl, press$loni,press$lati, press$dates, gale=FALSE, num_cores=2)
wtypesGlobal <- cwtGlobal$wtypes
plot_freqmap_wtypes(wtypesGlobal,press$loni, press$lati, all.types = TRUE,mytype = NULL ,center = T)
# Plot the global results only for one type
plot_freqmap_wtypes(wtypesGlobal,press$loni, press$lati, all.types = FALSE,mytype = "C" ,center = T)

## End(Not run)

Plot the classification scheme

Description

Visualises the original Jenkinson & Collison scheme for one given central point surrounded by the 16-points.

Usage

plot_jcscheme(centralp, loni, lati, fullmap = TRUE)

Arguments

Details

The map shows the scheme over the whole map, or either it shows the scheme over the selected region. For that, the maximum and mininum coordinates are defined as: Maximum longitude, by default defined by the points: x6, x10 or 14. Minimum longitude, by default defined by the points: x3, x7 or 11. Maximum latitude, by default defined by the points: x1 or x2. Minimum latitude, by default defined by the points: x15 or 16.

Value

A plot device

See Also

get_jcpoints

Examples

# Visualise the scheme for one point
library(jcext)
# Define a central point
mycentral <- c(10,50)
# load the data to get coordinates
data(press)
# Visualise the whole map
plot_jcscheme(mycentral,press$loni,press$lati,fullmap=TRUE)
# Visualise the region
plot_jcscheme(mycentral,press$loni,press$lati,fullmap=FALSE)

Mean Sea Level pressure files

Description

Data from a ERA-Interim reanalysis data set downloaded from ECMWF (http://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/). This data corresponds to global daily values of mean sea level pressure with 2.5 x 2.5 resolution for January 2000.

Usage

data(press)

Format

A list with values of pressure and coordinates (longitude, latitude, time)

msl

mean sea level pressure values, "Pa"

longitude

144

latitude

73

times

366, one year (2000)

References

Dee et al. (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553–597. doi:10.1002/qj.828

Examples

data(press)
mslp  <- press$msl
loni  <- press$loni
lati  <- press$lati
times <- press$dates

read_ncdata

Description

Reads a ncdf input file to extract the input for the classification: pressure field, longitudes, latitudes and dates. Absolute time is required to read the dates properly.

Usage

read_ncdata(ncinput, nam_coor, units)

Arguments

Value

A list with:

• A 3D-array of mean sea level (or pressure field) as [lon,lat,times]. The units returned as hPa.

• A numeric with longitudes values.

• A numeric with latitudes values.

• A numeric with dates values.