BLRPM.sim {BLRPM}

R Documentation

Simulating precipitation with the BLRPM

Description

BLRPM.sim is the main function for simulating precipitation with the Bartlett-Lewis rectangular pulse model. It generates storms and cells using the given five BLRPM parameters lambda, gamma, beta, eta, mux for a given simulation time t.sim. The function BLRPM.sim then accumulates a precipitation time series of length t.akk (typically the same as t.sim) with an accumulation time step interval from the generated storms and cells. An offset can be used to delay the precipitation time series for initialization reasons. BLRPM.sim returns a list of different variables and data.frames: Storms, Cells, Stepfun, Precip, time.

Usage

BLRPM.sim(lambda,gamma,beta,eta,mux,t.sim,t.acc,interval,offset)

Arguments

lambda	value specifying the expected storm generation rate [1/units.time]
gamma	value specifying the expected storm duration[1/units.time]
beta	value specifying the expected cell generation rate [1/units.time]
eta	value specifying the expected cell duration [1/units.time]
mux	value specifying the expected cell intenstity [mm/unit.time]
t.sim	value specifying the simulation length [units.time]
t.acc	value specifying the length of the accumulated time series [units.time]. Note: if longer than t.sim only zeros are added after t.sim.
interval	value specifying the accumulation time step [units.time]
offset	value specifying the offset of the accumulated time series with respect to the start time of the simulation [units.time]. Note: negative values are not allowed.

Value

$storms returns data.frame containing information about storms: start, end, number of cells

$cells returns data.frame containing information about cells: start, end, intensity, storm index

$sfn returns stepfunction used to accumulate precipitation time series

$RR returns vector of accumulated precipitation with time step interval [mm/interval]

$time returns vector of time steps [interval]

Author(s)

Christoph Ritschel christoph.ritschel@met.fu-berlin.de

Examples

lambda <- 4/240
gamma <- 1/10
beta <- 0.3
eta <- 2
mux <- 4
t.sim <- 240
t.acc <- t.sim
interval <- 1
offset <- 0
simulation <- BLRPM.sim(lambda,gamma,beta,eta,mux,t.sim,t.acc=t.sim,interval,offset)

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