continuity_ratio {RMAWGEN} | R Documentation |
Calculates the continuity ratio of a set of precipitation measured or generated data in several sites as defined by Wilks, 1998 (see reference link)
Description
Calculates the continuity ratio of a set of precipitation measured or generated data in several sites as defined by Wilks, 1998 (see reference link)
Usage
continuity_ratio(data, lag = 0, valmin = 0.5)
Arguments
data |
containing daily precipitation time series for several gauges (one gauge time series per column) |
lag |
numeric lag (expressed as number of days) used for computation for "cross" continuity ratio and joint probability of prercipitation (no)occurrence. |
valmin |
threshold precipitation value [mm] for wet/dry day indicator.
If precipitation is lower than |
Value
A list containing the following matrices:
continuity_ratio
: lag
-day lagged continuity ratio ,
occurrence
: joint probability of lag
-day lagged precipitation occurrence
nooccurrence
: joint probability of lag
-day lagged no precipitation occurrence.
nooccurrence_occurrence
: joint probability of lag
-day lagged no precipitation and precipitation occurrence respectively.
occurrence_nooccurrence
: joint probability of lag
-day lagged precipitation and no precipitation occurrence respectively.
probability_continuity_ratio
: lag
-day lagged ratio about precipitation probability contitioned to no precipitation/preciitation occurrence in the other site
Note
If lag==0
the function returns the continuity ratio and joint probability as described by Wilks, 1998. Otherwise the precipitation values for each couple of rain gauges are taken with lag
-day lag.
References
Mhanna, M. and Bauwens, W. (2012), A stochastic space-time model for the generation of daily rainfall in the Gaza Strip. Int. J. Climatol., 32: 1098-1112. doi:10.1002/joc.2305
D.S. Wilks (1998),Multisite generalization of a daily stochastic precipitation generation model,Journal of Hydrology, doi:10.1016/S0022-1694(98)00186-3
Examples
data(trentino)
year_min <- 1961
year_max <- 1990
origin <- paste(year_min,1,1,sep="-")
period <- PRECIPITATION$year>=year_min & PRECIPITATION$year<=year_max
station <- names(PRECIPITATION)[!(names(PRECIPITATION) %in% c("day","month","year"))]
prec_mes <- PRECIPITATION[period,station]
## removing nonworking stations (e.g. time series with NA)
accepted <- array(TRUE,length(names(prec_mes)))
names(accepted) <- names(prec_mes)
for (it in names(prec_mes)) {
accepted[it] <- (length(which(!is.na(prec_mes[,it])))==length(prec_mes[,it]))
}
prec_mes <- prec_mes[,accepted]
## the dateset is reduced!!!
prec_mes <- prec_mes[,1:2]
continuity_ratio <-continuity_ratio(data=prec_mes,lag=0,valmin=0.5)
continuity_ratio1 <-continuity_ratio(data=prec_mes,lag=-1,valmin=0.5)