WACS {WACS}

WACS: Multivariate Weather-state Approach Conditionally Skew-normal Generator

Description

WACS is a multivariate weather generator for daily climate variables based on weather-states that uses a Markov chain for modeling the succession of weather states. Conditionally to the weather states, the multivariate variables are modeled using the family of Complete Skew-Normal distributions. Parameters are estimated on measured series. Must include a 'Rain' variable and can accept as many other variables as desired.

WACS functions

• WACSdata: Builds a data structure compatible with WACS functions

• WACSestim: Estimation of the parameters of a WACS model

• WACSsimul: Performs simulations based on estimated parameters of the WACS model

• WACSvalid: Performs validations of WACS simulations

• WACScompare: Performs comparisons between two WACS data structures, or between two WACS simulation series

• WACSplot: Plots validation figures from WACSvalid and from WACScompare

• WACSplotdensity: Plots fitted bivariate densities of residuals

Authors

Denis Allard, Ronan Trépos

Reference

• Flecher C., Naveau P., Allard D., Brisson N.(2010) A stochastic weather generator for skewed data. Water Resource Research, 46, W07519

• WACSgen: model, methods and algorithms (2015). Allard D., Biostatistiques et Processus Spatiaux, INRA, Avignon, France. Available at denis.biosp.org

• Flecher, C., Naveau, Ph. and Allard, D. (2009) Estimating the Closed Skew-Normal distributions parameters using weighted moments", Statistics and Probability Letters, 79, 1977-1984.

Examples

## Not run:  
  data(ClimateSeries)
  ThisData = WACSdata(ClimateSeries, from="1995-01-01", to="2012-12-31")
  ThisPar  = WACSestim(ThisData)
  ThisSim  = WACSsimul(ThisPar, from="1995-01-01", to="2012-12-31")
  ThisVal  = WACSvalid(what="Sim",wacsdata = ThisData, wacspar = ThisPar, 
                       wacssimul = ThisSim,varname="tmin")
  WACSplot(ThisVal,file="ThisFile.pdf")

## End(Not run)