Description Usage Arguments Details Value References See Also Examples
Fits a Censored generalized extreme value distribution EMOS model to ensemble forecasts for specified dates.
1 2 3 | ensembleMOSgev0(ensembleData, trainingDays, consecutive = FALSE,
dates = NULL, control = controlMOSgev0(),
warmStart = FALSE, exchangeable = NULL)
|
ensembleData |
An |
trainingDays |
An integer giving the number of time steps (e.g. days) in the training period. There is no default. |
consecutive |
If |
dates |
The dates for which EMOS forecasting models are desired.
By default, this will be all dates in |
control |
A list of control values for the fitting functions specified via the function controlMOSgev0. For details and default values, see controlMOSgev0. |
warmStart |
If |
exchangeable |
A numeric or character vector or factor indicating groups of
ensemble members that are exchangeable (indistinguishable).
The modeling will have equal parameters within each group.
The default determines exchangeability from |
Given an ensemble of size m: X_1, … , X_m, the
following generalized extreme value distribution EMOS
model left-censored at 0 is fit by ensembleMOSgev0
:
Y ~ GEV_0(μ,σ,q)
where GEV_0 denotes the generalized extreme value distribution left-censored at zero, with location μ, scale σ and shape q. The model is parametrized such that the mean m is a linear function a + b_1 X_1 + … + b_m X_m + s p_0 of the ensemble forecats, where p_0 denotes the ratio of ensemble forecasts that are exactly 0, and the shape parameter σ is a linear function of the ensemble variance c + d MD(X_1,…,X_m), where MD(X_1,…,X_m) is Gini's mean difference. See ensembleMOSgev0 for details.
B
is a vector of fitted regression coefficients: b_1,
…, b_m. Specifically, a, b_1,…, b_m, s, c, d, q are
fitted to optimize
the mean CRPS over the specified training period using
optim
.
A list with the following output components:
training |
A list containing information on the training length and lag and the number of instances used for training for each modeling date. |
a |
A vector of fitted EMOS intercept parameters for each date. |
B |
A matrix of fitted EMOS coefficients for each date. |
s |
A vector of fitted EMOS coefficients for p_0 for each date, see details. |
c,d |
The fitted coefficients for the shape parameter, see details. |
q |
Fitted shape parameter, see details. |
M. Scheuerer, Probabilistic quantitative precipitation forecasting using ensemble model output statistics. Quarterly Journal of the Royal Meteorological Society 140:1086–1096, 2014.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | data("ensBMAtest", package = "ensembleBMA")
ensMemNames <- c("gfs","cmcg","eta","gasp","jma","ngps","tcwb","ukmo")
obs <- paste("PCP24","obs", sep = ".")
ens <- paste("PCP24", ensMemNames, sep = ".")
prcpTestData <- ensembleData(forecasts = ensBMAtest[,ens],
dates = ensBMAtest[,"vdate"],
observations = ensBMAtest[,obs],
station = ensBMAtest[,"station"],
forecastHour = 48,
initializationTime = "00")
prcpTestFitGEV0 <- ensembleMOSgev0(prcpTestData, trainingDays = 25,
dates = "2008010100")
|
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