View source: R/CST_MultiMetric.R
MultiMetric | R Documentation |
This function calculates correlation (Anomaly Correlation Coefficient; ACC), root mean square error (RMS) and the root mean square error skill score (RMSSS) of individual anomaly models and multi-models mean (if desired) with the observations on arrays with named dimensions.
MultiMetric(
exp,
obs,
metric = "correlation",
multimodel = TRUE,
time_dim = "ftime",
memb_dim = "member",
sdate_dim = "sdate"
)
exp |
A multidimensional array with named dimensions. |
obs |
A multidimensional array with named dimensions. |
metric |
A character string giving the metric for computing the maximum skill. This must be one of the strings 'correlation', 'rms' or 'rmsss. |
multimodel |
A logical value indicating whether a Multi-Model Mean should be computed. |
time_dim |
Name of the temporal dimension where a mean will be applied. It can be NULL, the default value is 'ftime'. |
memb_dim |
Name of the member dimension. It can be NULL, the default value is 'member'. |
sdate_dim |
Name of the start date dimension or a dimension name identifiying the different forecast. It can be NULL, the default value is 'sdate'. |
A list of arrays containing the statistics of the selected metric in
the element $data
which is a list of arrays: for the metric requested
and others for statistics about its signeificance. The arrays have two dataset
dimensions equal to the 'dataset' dimension in the exp$data
and
obs$data
inputs. If multimodel
is TRUE, the greatest position in
the first dimension correspons to the Multi-Model Mean.
Mishra Niti, niti.mishra@bsc.es
Perez-Zanon Nuria, nuria.perez@bsc.es
Mishra, N., Prodhomme, C., & Guemas, V. (n.d.). Multi-Model Skill Assessment of Seasonal Temperature and Precipitation Forecasts over Europe, 29-31. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s00382-018-4404-z")}
Corr
, RMS
,
RMSSS
and CST_Load
exp <- array(rnorm(2*2*4*5*2*2),
dim = c(dataset = 2, member = 2, sdate = 4, ftime = 5, lat = 2,
lon = 2))
obs <- array(rnorm(1*1*4*5*2*2),
dim = c(dataset = 1, member = 1, sdate = 4, ftime = 5, lat = 2,
lon = 2))
res <- MultiMetric(exp = exp, obs = obs)
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