Nothing
R/calculate_cwt.R
In jcext: Extended Classification of Weather Types
#' @title calculate_cwt
#'
#' @description Applies the rules to obtain the weather types.
#' (more details, see Jones et al. 1997)
#'
#' @param Z Data frame with the total shear vorticity and dates.
#' @param TF Data frame with resultant flow and dates.
#' @param directionflow Data frame with the direction of the flow and dates.
#' @param G Data frame with Gale days and dates.
#' @param thr Numeric threshold used for Unclassified days.
#' @param Gth Numeric threshold used for Gale days.
#' @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.
#' \itemize{
#' \item The appropriate direction is calculated on an eight-point compass allowing 45° per sector.
#' \item If abs(Z) is less than TF, flow is essentially pure directional type.
#' \item If |Z| is greater than 2TF, then the pattern is strongly cyclonic (Z > 0) or anticyclonic (Z < 0).
#' \item 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.
#' \item If TF is less than 6 and |Z| is less than 6, there is light indeterminate flow corresponding to Lamb’s
#' unclassified type U.
#' }
#' @return A list with two objects:
#' \itemize{
#' \item 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.
#' \itemize{
#' \item LWT_D: 8 directional types.
#' \item LWT_C: 1 anticyclonic and 1 cyclonic.
#' \item LWT_CH: 16 hybrid types.
#' \item LWT_U: 1 unclassified type.
#' }
#'\item 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).
#'}
#'
#'@seealso
#'\code{\link{classification_jc}}
#'
#' @export
calculate_cwt <- function(Z, TF, directionflow, G, thr = 6, Gth = 30){
# Function calculate_cwt:
# main function with the rules to do the CWT classification
# (Jones et al.1993)
# Input arguments: Indices
# Output arguments: A list with 2 list:
# 1.list: Weather types (data frame structures, with Z values and date)
# 2.list: Logical values with every CWTs
# appropiate direction is calculated on an eight-point compass.
# There will be eigth directional types
NE <- (directionflow$value > 22.5 & directionflow$value < 67.5)
E <- (directionflow$value >= 67.5 & directionflow$value <= 112.5)
SE <- (directionflow$value > 112.5 & directionflow$value < 157.5)
S <- (directionflow$value >= 157.5 & directionflow$value <= 202.5)
SW <- (directionflow$value > 202.5 & directionflow$value < 247.5)
W <- (directionflow$value >= 247.5 & directionflow$value <= 292.5)
NW <- (directionflow$value > 292.5 & directionflow$value < 337.5)
N <- (directionflow$value >= 337.5 | directionflow$value <= 22.5)
# get pure and non pure types
# If TF is greater than thr=6 (original threshold)
# or Z is greater than 6 then we classify the types
# Basic condition
clas_condition <- (TF$value > thr | abs(Z$value) > thr)
# Gale days:
# threshold values G>30, G>30 for low wind G<10,G<5
# Gale condition Gth =30 This can be changed.
gale_l <- (G$value > Gth)
gale <- data.frame("date" = Z$date[gale_l])
# Pure condition: corresponds to Lamb’s pure cyclonic and anticyclonic
temp_purecyclo <- (clas_condition & (abs(Z$value) > 2 * TF$value))
cyclo_l <- (temp_purecyclo & (Z$value > 0))
cyclo <- data.frame("date" = Z$date[cyclo_l])
# Merging Gale days with cyclo character
C_Ga <- merge(cyclo, gale, by = "date", all.x = TRUE)
anticyclo_l <- (temp_purecyclo & (Z$value < 0))
anticyclo <- data.frame("date" = Z$date[anticyclo_l])
# Merging Gale days with anticyclo character
A_Ga <- merge(anticyclo, gale, by = "date", all.x = TRUE)
# Condition: Directional types
# To get the right directional, it is calculated the direction
# If abs(Z) is less than TF, flow is essentially straight.
# It would correspond to pure directional
condition_puredirectional <- (clas_condition & (abs(Z$value) < TF$value))
N_l <- (condition_puredirectional & N)
D_N <- data.frame("date" = Z$date[N_l])
# Merging Gale days with N directional character
N_Ga <- merge(D_N, gale, by = "date", all.x = TRUE)
NE_l <- (condition_puredirectional & NE)
D_NE <- data.frame("date" = Z$date[NE_l])
# Merging Gale days with NE directional character
NE_Ga <- merge(D_NE, gale, by = "date", all.x = TRUE)
E_l <- (condition_puredirectional & E)
D_E <- data.frame("date" = Z$date[E_l])
# Merging Gale days with NE directional character
E_Ga <- merge(D_E, gale, by = "date", all.x = TRUE)
SE_l <- (condition_puredirectional & SE)
D_SE <- data.frame("date" = Z$date[SE_l])
# Merging Gale days with NE directional character
SE_Ga <- merge(D_SE, gale, by = "date", all.x = TRUE)
S_l <- (condition_puredirectional & S)
D_S <- data.frame("date" = Z$date[S_l])
# Merging Gale days with South directional character
S_Ga <- merge(D_S, gale, by = "date", all.x = TRUE)
SW_l <- (condition_puredirectional & SW)
D_SW <- data.frame("date" = Z$date[SW_l])
# Merging Gale days with SW directional character
SW_Ga <- merge(D_SW, gale, by = "date", all.x = TRUE)
W_l <- (condition_puredirectional & W)
D_W <- data.frame("date" = Z$date[W_l])
# Merging Gale days with W directional character
W_Ga <- merge(D_W, gale, by = "date", all.x = TRUE)
NW_l <- (condition_puredirectional & NW)
D_NW <- data.frame("date" = Z$date[NW_l])
# Merging Gale days with NW directional character
NW_Ga <- merge(D_NW, gale, by = "date", all.x = TRUE)
# Condition: Hybrid type classification
# If F < |Z| < 2*F , then it's hybrid type
condition_hybrid <- (clas_condition &
(TF$value < abs(Z$value) &
abs(Z$value) < 2 * TF$value ))
hibrid_cyclo <- (condition_hybrid & (Z$value >= 0))
hibrid_anticyclo <- (condition_hybrid & (Z$value < 0))
# Classification into hybrid directional types
# Hybrid Cyclonic types:
hyb_CN_l <- (hibrid_cyclo & N)
hyb_CN <- data.frame("date" = Z$date[hyb_CN_l])
# Merging Gale days with hybrid flow character, cyclonic N
CN_Ga <- merge(hyb_CN, gale, by = "date", all.x = TRUE)
hyb_CNE_l <- (hibrid_cyclo & NE)
hyb_CNE <- data.frame("date" = Z$date[hyb_CNE_l])
# Merging Gale days with hybrid flow character, cyclonic NE
CNE_Ga <- merge(hyb_CNE, gale, by = "date", all.x = TRUE)
hyb_CE_l <- (hibrid_cyclo & E)
hyb_CE <- data.frame("date" = Z$date[hyb_CE_l])
# Merging Gale days with hybrid flow character, cyclonic E
CE_Ga <- merge(hyb_CE, gale, by = "date", all.x = TRUE)
hyb_CSE_l <- (hibrid_cyclo & SE)
hyb_CSE <- data.frame("date" = Z$date[hyb_CSE_l])
# Merging Gale days with hybrid flow character, cyclonic SE
CSE_Ga <- merge(hyb_CSE, gale, by = "date", all.x = TRUE)
hyb_CS_l <- (hibrid_cyclo & S)
hyb_CS <- data.frame("date" = Z$date[hyb_CS_l])
# Merging Gale days with hybrid flow character, cyclonic S
CS_Ga <- merge(hyb_CS, gale, by = "date", all.x = TRUE)
hyb_CSW_l <- (hibrid_cyclo & SW)
hyb_CSW <- data.frame("date" = Z$date[hyb_CSW_l])
# Merging Gale days with hybrid flow character, cyclonic SW
CSW_Ga <- merge(hyb_CSW, gale, by = "date", all.x = TRUE)
hyb_CW_l <- (hibrid_cyclo & W)
hyb_CW <- data.frame("date" = Z$date[hyb_CW_l])
# Merging Gale days with hybrid flow character, cyclonic W
CW_Ga <- merge(hyb_CW, gale, by = "date", all.x = TRUE)
hyb_CNW_l <- (hibrid_cyclo & NW)
hyb_CNW <- data.frame("date" = Z$date[hyb_CNW_l])
# Merging Gale days with hybrid flow character, cyclonic NW
CNW_Ga <- merge(hyb_CNW, gale, by = "date", all.x = TRUE)
# Hybrid Anticyclonic types
hyb_AN_l <- (hibrid_anticyclo & N)
hyb_AN <- data.frame("date" = Z$date[hyb_AN_l])
# Merging Gale days with hybrid flow character, anticyclonic N
AN_Ga <- merge(hyb_AN, gale, by = "date", all.x = TRUE)
hyb_ANE_l <- (hibrid_anticyclo & NE)
hyb_ANE <- data.frame("date" = Z$date[hyb_ANE_l])
# Merging Gale days with hybrid flow character, anticyclonic NE
ANE_Ga <- merge(hyb_ANE, gale, by = "date", all.x = TRUE)
hyb_AE_l <- (hibrid_anticyclo & E)
hyb_AE <- data.frame("date" = Z$date[hyb_AE_l])
# Merging Gale days with hybrid flow character, anticyclonic E
AE_Ga <- merge(hyb_AE, gale, by = "date", all.x = TRUE)
hyb_ASE_l <- (hibrid_anticyclo & SE)
hyb_ASE <- data.frame("date" = Z$date[hyb_ASE_l])
# Merging Gale days with hybrid flow character, anticyclonic SE
ASE_Ga <- merge(hyb_ASE, gale, by = "date", all.x = TRUE)
hyb_AS_l <- (hibrid_anticyclo & S)
hyb_AS <- data.frame("date" = Z$date[hyb_AS_l])
# Merging Gale days with hybrid flow character, anticyclonic S
AS_Ga <- merge(hyb_AS, gale, by = "date", all.x = TRUE)
hyb_ASW_l <- (hibrid_anticyclo & SW)
hyb_ASW <- data.frame("date" = Z$date[hyb_ASW_l])
# Merging Gale days with hybrid flow character, anticyclonic SW
ASW_Ga <- merge(hyb_ASW, gale, by = "date", all.x = TRUE)
hyb_AW_l <- (hibrid_anticyclo & W)
hyb_AW <- data.frame("date" = Z$date[hyb_AW_l])
# Merging Gale days with hybrid flow character, anticyclonic W
AW_Ga <- merge(hyb_AW, gale, by = "date", all.x = TRUE)
hyb_ANW_l <- (hibrid_anticyclo & NW)
hyb_ANW <- data.frame("date" = Z$date[hyb_ANW_l])
# Merging Gale days with hybrid flow character, anticyclonic NW
ANW_Ga <- merge(hyb_ANW, gale, by = "date", all.x = TRUE)
# Condition: Unclassified types
# condition_unclassified_l (flow and vorticity <6)
# Using other threshold for undefined days
condition_unclassified_l <- (TF$value < thr & abs(Z$value) < thr)
unclassified <- data.frame("date" = Z$date[condition_unclassified_l])
# Gale days with U
U_Ga <- merge(unclassified, gale, by = "date", all.x = TRUE)
# End Classification
# Returns a list with all weather types
LWT_D <- list("N" = N_Ga,
"NE" = NE_Ga,
"E" = E_Ga,
"SE" = SE_Ga,
"S" = S_Ga,
"SW" = SW_Ga,
"W" = W_Ga,
"NW" = NW_Ga)
LWT_C <- list("A" = A_Ga,
"C" = C_Ga)
LWT_CH <- list("CN" = CN_Ga,
"CNE" = CNE_Ga,
"CE" = CE_Ga,
"CSE" = CSE_Ga,
"CS" = CS_Ga,
"CSW" = CSW_Ga,
"CW" = CW_Ga,
"CNW" = CNW_Ga,
"AN" = AN_Ga,
"ANE" = ANE_Ga,
"AE" = AE_Ga,
"ASE" = ASE_Ga,
"AS" = AS_Ga,
"ASW" = ASW_Ga,
"AW" = AW_Ga,
"ANW" = ANW_Ga)
LWT_U <- list("U" = U_Ga)
LWT_G <- list("G" = gale)
logical_vals <- list("N_l" = N_l,
"NE_l" = NE_l,
"E_l" = E_l,
"SE_l" = SE_l,
"S_l" = S_l,
"SW_l" = SW_l,
"W_l" = W_l,
"NW_l" = NW_l,
"cyclo_l" = cyclo_l,
"anticyclo_l" = anticyclo_l,
"hyb_CN_l" = hyb_CN_l,
"hyb_CNE_l" = hyb_CNE_l,
"hyb_CE_l" = hyb_CE_l,
"hyb_CSE_l" = hyb_CSE_l,
"hyb_CS_l" = hyb_CS_l,
"hyb_CSW_l" = hyb_CSW_l,
"hyb_CW_l" = hyb_CW_l,
"hyb_CNW_l" = hyb_CNW_l,
"hyb_AN_l" = hyb_AN_l,
"hyb_ANE_l" = hyb_ANE_l,
"hyb_AE_l" = hyb_AE_l,
"hyb_ASE_l" = hyb_ASE_l,
"hyb_AS_l" = hyb_AS_l,
"hyb_ASW_l" = hyb_ASW_l,
"hyb_AW_l" = hyb_AW_l,
"hyb_ANW_l" = hyb_ANW_l
)
CWT <- list("LWT_D" = LWT_D,
"LWT_C" = LWT_C,
"LWT_CH" = LWT_CH,
"LWT_U" = LWT_U,
"LWT_G" = LWT_G)
list <- list("Total_CWT" = CWT,
"logical_days" = logical_vals)
}
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#' @title calculate_cwt
#'
#' @description Applies the rules to obtain the weather types.
#' (more details, see Jones et al. 1997)
#'
#' @param Z Data frame with the total shear vorticity and dates.
#' @param TF Data frame with resultant flow and dates.
#' @param directionflow Data frame with the direction of the flow and dates.
#' @param G Data frame with Gale days and dates.
#' @param thr Numeric threshold used for Unclassified days.
#' @param Gth Numeric threshold used for Gale days.
#' @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.
#' \itemize{
#' \item The appropriate direction is calculated on an eight-point compass allowing 45° per sector.
#' \item If abs(Z) is less than TF, flow is essentially pure directional type.
#' \item If |Z| is greater than 2TF, then the pattern is strongly cyclonic (Z > 0) or anticyclonic (Z < 0).
#' \item 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.
#' \item If TF is less than 6 and |Z| is less than 6, there is light indeterminate flow corresponding to Lamb’s
#' unclassified type U.
#' }
#' @return A list with two objects:
#' \itemize{
#' \item 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.
#' \itemize{
#' \item LWT_D: 8 directional types.
#' \item LWT_C: 1 anticyclonic and 1 cyclonic.
#' \item LWT_CH: 16 hybrid types.
#' \item LWT_U: 1 unclassified type.
#' }
#'\item 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).
#'}
#'
#'@seealso
#'\code{\link{classification_jc}}
#'
#' @export
calculate_cwt <- function(Z, TF, directionflow, G, thr = 6, Gth = 30){
# Function calculate_cwt:
# main function with the rules to do the CWT classification
# (Jones et al.1993)
# Input arguments: Indices
# Output arguments: A list with 2 list:
# 1.list: Weather types (data frame structures, with Z values and date)
# 2.list: Logical values with every CWTs
# appropiate direction is calculated on an eight-point compass.
# There will be eigth directional types
NE <- (directionflow$value > 22.5 & directionflow$value < 67.5)
E <- (directionflow$value >= 67.5 & directionflow$value <= 112.5)
SE <- (directionflow$value > 112.5 & directionflow$value < 157.5)
S <- (directionflow$value >= 157.5 & directionflow$value <= 202.5)
SW <- (directionflow$value > 202.5 & directionflow$value < 247.5)
W <- (directionflow$value >= 247.5 & directionflow$value <= 292.5)
NW <- (directionflow$value > 292.5 & directionflow$value < 337.5)
N <- (directionflow$value >= 337.5 | directionflow$value <= 22.5)
# get pure and non pure types
# If TF is greater than thr=6 (original threshold)
# or Z is greater than 6 then we classify the types
# Basic condition
clas_condition <- (TF$value > thr | abs(Z$value) > thr)
# Gale days:
# threshold values G>30, G>30 for low wind G<10,G<5
# Gale condition Gth =30 This can be changed.
gale_l <- (G$value > Gth)
gale <- data.frame("date" = Z$date[gale_l])
# Pure condition: corresponds to Lamb’s pure cyclonic and anticyclonic
temp_purecyclo <- (clas_condition & (abs(Z$value) > 2 * TF$value))
cyclo_l <- (temp_purecyclo & (Z$value > 0))
cyclo <- data.frame("date" = Z$date[cyclo_l])
# Merging Gale days with cyclo character
C_Ga <- merge(cyclo, gale, by = "date", all.x = TRUE)
anticyclo_l <- (temp_purecyclo & (Z$value < 0))
anticyclo <- data.frame("date" = Z$date[anticyclo_l])
# Merging Gale days with anticyclo character
A_Ga <- merge(anticyclo, gale, by = "date", all.x = TRUE)
# Condition: Directional types
# To get the right directional, it is calculated the direction
# If abs(Z) is less than TF, flow is essentially straight.
# It would correspond to pure directional
condition_puredirectional <- (clas_condition & (abs(Z$value) < TF$value))
N_l <- (condition_puredirectional & N)
D_N <- data.frame("date" = Z$date[N_l])
# Merging Gale days with N directional character
N_Ga <- merge(D_N, gale, by = "date", all.x = TRUE)
NE_l <- (condition_puredirectional & NE)
D_NE <- data.frame("date" = Z$date[NE_l])
# Merging Gale days with NE directional character
NE_Ga <- merge(D_NE, gale, by = "date", all.x = TRUE)
E_l <- (condition_puredirectional & E)
D_E <- data.frame("date" = Z$date[E_l])
# Merging Gale days with NE directional character
E_Ga <- merge(D_E, gale, by = "date", all.x = TRUE)
SE_l <- (condition_puredirectional & SE)
D_SE <- data.frame("date" = Z$date[SE_l])
# Merging Gale days with NE directional character
SE_Ga <- merge(D_SE, gale, by = "date", all.x = TRUE)
S_l <- (condition_puredirectional & S)
D_S <- data.frame("date" = Z$date[S_l])
# Merging Gale days with South directional character
S_Ga <- merge(D_S, gale, by = "date", all.x = TRUE)
SW_l <- (condition_puredirectional & SW)
D_SW <- data.frame("date" = Z$date[SW_l])
# Merging Gale days with SW directional character
SW_Ga <- merge(D_SW, gale, by = "date", all.x = TRUE)
W_l <- (condition_puredirectional & W)
D_W <- data.frame("date" = Z$date[W_l])
# Merging Gale days with W directional character
W_Ga <- merge(D_W, gale, by = "date", all.x = TRUE)
NW_l <- (condition_puredirectional & NW)
D_NW <- data.frame("date" = Z$date[NW_l])
# Merging Gale days with NW directional character
NW_Ga <- merge(D_NW, gale, by = "date", all.x = TRUE)
# Condition: Hybrid type classification
# If F < |Z| < 2*F , then it's hybrid type
condition_hybrid <- (clas_condition &
(TF$value < abs(Z$value) &
abs(Z$value) < 2 * TF$value ))
hibrid_cyclo <- (condition_hybrid & (Z$value >= 0))
hibrid_anticyclo <- (condition_hybrid & (Z$value < 0))
# Classification into hybrid directional types
# Hybrid Cyclonic types:
hyb_CN_l <- (hibrid_cyclo & N)
hyb_CN <- data.frame("date" = Z$date[hyb_CN_l])
# Merging Gale days with hybrid flow character, cyclonic N
CN_Ga <- merge(hyb_CN, gale, by = "date", all.x = TRUE)
hyb_CNE_l <- (hibrid_cyclo & NE)
hyb_CNE <- data.frame("date" = Z$date[hyb_CNE_l])
# Merging Gale days with hybrid flow character, cyclonic NE
CNE_Ga <- merge(hyb_CNE, gale, by = "date", all.x = TRUE)
hyb_CE_l <- (hibrid_cyclo & E)
hyb_CE <- data.frame("date" = Z$date[hyb_CE_l])
# Merging Gale days with hybrid flow character, cyclonic E
CE_Ga <- merge(hyb_CE, gale, by = "date", all.x = TRUE)
hyb_CSE_l <- (hibrid_cyclo & SE)
hyb_CSE <- data.frame("date" = Z$date[hyb_CSE_l])
# Merging Gale days with hybrid flow character, cyclonic SE
CSE_Ga <- merge(hyb_CSE, gale, by = "date", all.x = TRUE)
hyb_CS_l <- (hibrid_cyclo & S)
hyb_CS <- data.frame("date" = Z$date[hyb_CS_l])
# Merging Gale days with hybrid flow character, cyclonic S
CS_Ga <- merge(hyb_CS, gale, by = "date", all.x = TRUE)
hyb_CSW_l <- (hibrid_cyclo & SW)
hyb_CSW <- data.frame("date" = Z$date[hyb_CSW_l])
# Merging Gale days with hybrid flow character, cyclonic SW
CSW_Ga <- merge(hyb_CSW, gale, by = "date", all.x = TRUE)
hyb_CW_l <- (hibrid_cyclo & W)
hyb_CW <- data.frame("date" = Z$date[hyb_CW_l])
# Merging Gale days with hybrid flow character, cyclonic W
CW_Ga <- merge(hyb_CW, gale, by = "date", all.x = TRUE)
hyb_CNW_l <- (hibrid_cyclo & NW)
hyb_CNW <- data.frame("date" = Z$date[hyb_CNW_l])
# Merging Gale days with hybrid flow character, cyclonic NW
CNW_Ga <- merge(hyb_CNW, gale, by = "date", all.x = TRUE)
# Hybrid Anticyclonic types
hyb_AN_l <- (hibrid_anticyclo & N)
hyb_AN <- data.frame("date" = Z$date[hyb_AN_l])
# Merging Gale days with hybrid flow character, anticyclonic N
AN_Ga <- merge(hyb_AN, gale, by = "date", all.x = TRUE)
hyb_ANE_l <- (hibrid_anticyclo & NE)
hyb_ANE <- data.frame("date" = Z$date[hyb_ANE_l])
# Merging Gale days with hybrid flow character, anticyclonic NE
ANE_Ga <- merge(hyb_ANE, gale, by = "date", all.x = TRUE)
hyb_AE_l <- (hibrid_anticyclo & E)
hyb_AE <- data.frame("date" = Z$date[hyb_AE_l])
# Merging Gale days with hybrid flow character, anticyclonic E
AE_Ga <- merge(hyb_AE, gale, by = "date", all.x = TRUE)
hyb_ASE_l <- (hibrid_anticyclo & SE)
hyb_ASE <- data.frame("date" = Z$date[hyb_ASE_l])
# Merging Gale days with hybrid flow character, anticyclonic SE
ASE_Ga <- merge(hyb_ASE, gale, by = "date", all.x = TRUE)
hyb_AS_l <- (hibrid_anticyclo & S)
hyb_AS <- data.frame("date" = Z$date[hyb_AS_l])
# Merging Gale days with hybrid flow character, anticyclonic S
AS_Ga <- merge(hyb_AS, gale, by = "date", all.x = TRUE)
hyb_ASW_l <- (hibrid_anticyclo & SW)
hyb_ASW <- data.frame("date" = Z$date[hyb_ASW_l])
# Merging Gale days with hybrid flow character, anticyclonic SW
ASW_Ga <- merge(hyb_ASW, gale, by = "date", all.x = TRUE)
hyb_AW_l <- (hibrid_anticyclo & W)
hyb_AW <- data.frame("date" = Z$date[hyb_AW_l])
# Merging Gale days with hybrid flow character, anticyclonic W
AW_Ga <- merge(hyb_AW, gale, by = "date", all.x = TRUE)
hyb_ANW_l <- (hibrid_anticyclo & NW)
hyb_ANW <- data.frame("date" = Z$date[hyb_ANW_l])
# Merging Gale days with hybrid flow character, anticyclonic NW
ANW_Ga <- merge(hyb_ANW, gale, by = "date", all.x = TRUE)
# Condition: Unclassified types
# condition_unclassified_l (flow and vorticity <6)
# Using other threshold for undefined days
condition_unclassified_l <- (TF$value < thr & abs(Z$value) < thr)
unclassified <- data.frame("date" = Z$date[condition_unclassified_l])
# Gale days with U
U_Ga <- merge(unclassified, gale, by = "date", all.x = TRUE)
# End Classification
# Returns a list with all weather types
LWT_D <- list("N" = N_Ga,
"NE" = NE_Ga,
"E" = E_Ga,
"SE" = SE_Ga,
"S" = S_Ga,
"SW" = SW_Ga,
"W" = W_Ga,
"NW" = NW_Ga)
LWT_C <- list("A" = A_Ga,
"C" = C_Ga)
LWT_CH <- list("CN" = CN_Ga,
"CNE" = CNE_Ga,
"CE" = CE_Ga,
"CSE" = CSE_Ga,
"CS" = CS_Ga,
"CSW" = CSW_Ga,
"CW" = CW_Ga,
"CNW" = CNW_Ga,
"AN" = AN_Ga,
"ANE" = ANE_Ga,
"AE" = AE_Ga,
"ASE" = ASE_Ga,
"AS" = AS_Ga,
"ASW" = ASW_Ga,
"AW" = AW_Ga,
"ANW" = ANW_Ga)
LWT_U <- list("U" = U_Ga)
LWT_G <- list("G" = gale)
logical_vals <- list("N_l" = N_l,
"NE_l" = NE_l,
"E_l" = E_l,
"SE_l" = SE_l,
"S_l" = S_l,
"SW_l" = SW_l,
"W_l" = W_l,
"NW_l" = NW_l,
"cyclo_l" = cyclo_l,
"anticyclo_l" = anticyclo_l,
"hyb_CN_l" = hyb_CN_l,
"hyb_CNE_l" = hyb_CNE_l,
"hyb_CE_l" = hyb_CE_l,
"hyb_CSE_l" = hyb_CSE_l,
"hyb_CS_l" = hyb_CS_l,
"hyb_CSW_l" = hyb_CSW_l,
"hyb_CW_l" = hyb_CW_l,
"hyb_CNW_l" = hyb_CNW_l,
"hyb_AN_l" = hyb_AN_l,
"hyb_ANE_l" = hyb_ANE_l,
"hyb_AE_l" = hyb_AE_l,
"hyb_ASE_l" = hyb_ASE_l,
"hyb_AS_l" = hyb_AS_l,
"hyb_ASW_l" = hyb_ASW_l,
"hyb_AW_l" = hyb_AW_l,
"hyb_ANW_l" = hyb_ANW_l
)
CWT <- list("LWT_D" = LWT_D,
"LWT_C" = LWT_C,
"LWT_CH" = LWT_CH,
"LWT_U" = LWT_U,
"LWT_G" = LWT_G)
list <- list("Total_CWT" = CWT,
"logical_days" = logical_vals)
}
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