S1 | R Documentation |
Calculate the S1 score and anomaly correlation for a verification set.
S1(x, ...)
## Default S3 method:
S1(x, ..., xhat, gradFUN = "KernelGradFUN")
## S3 method for class 'SpatialVx'
S1(x, ..., xhat, gradFUN = "KernelGradFUN",
time.point = 1, obs = 1, model = 1)
ACC(x, ...)
## Default S3 method:
ACC(x, ..., xhat, xclim = NULL, xhatclim = NULL)
## S3 method for class 'SpatialVx'
ACC(x, ..., xclim = NULL, xhatclim = NULL,
time.point = 1, obs = 1, model = 1)
x , xhat |
m by n matrices giving the verification and forecast fields, resp. For |
xclim , xhatclim |
m by n matrices giving the climatologies for |
gradFUN |
character identifying a function used to calculate the gradient fields for |
time.point |
numeric or character indicating which time point from the “SpatialVx” verification set to select for analysis. |
obs , model |
numeric indicating which observation/forecast model to select for the analysis. |
... |
optional arguments to the |
The S1 score is given by
S1 = 100*sum(abs(DY_i - DX_i))/sum(max(abs(DY_i),abs(DX_i))),
where DY_i (DX_i)is the gradient at grid point i for the forecast (verification). See Brown et al. (2012) and Thompson and Carter (1972) for more on this score.
The ACC is just the correlation between X - Xclim and Y - Yclim.
single numeric
Eric Gilleland
Brown, B.G., Gilleland, E. and Ebert, E.E. (2012) Chapter 6: Forecasts of spatial fields. pp. 95–117, In Forecast Verification: A Practitioner's Guide in Atmospheric Science, 2nd edition. Edts. Jolliffee, I. T. and Stephenson, D. B., Chichester, West Sussex, U.K.: Wiley, 274 pp.
Thompson, J. C. and Carter, G. M. (1972) On some characteristics of the S1 score. J. Appl. Meteorol., 11, 1384–1385.
kernel2dmeitsjer
data( "UKobs6" )
data( "UKfcst6" )
S1( UKobs6, xhat = UKfcst6 )
ACC( UKobs6, xhat = UKfcst6 )
## Not run:
data( "obs0601" )
data( "wrf4ncar0531" )
data( "ICPg240Locs" )
hold <- make.SpatialVx( obs0601, wrf4ncar0531, loc = ICPg240Locs,
projection = TRUE, map = TRUE, loc.byrow = TRUE,
field.type = "Precipitation", units = "mm/h",
data.name = "ICP NSSL/SPC Spring 2005 Cases",
obs.name = "obs0601", model.name = "wrf4ncar0531" )
plot( hold )
S1( hold )
ACC( hold )
## End(Not run)
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