Reads and writes the data format used in
SDSM's DAT
and OUT
extensions.
# reading
read.sdsm(file, start = 1961, end = 2000, calendar)# writing
write.sdsm(dat, var, start, end, file = "")
name of DAT
or OUT
file
data.frame
of variables to be written
starting year
ending year
name of variable to be written from dat
calender used for data; if unspecified, this is
assumed to be proleptic Gregorian (normal); however, for CCCma
models this should be "365_day", and for Hadley models this should
be "360_day"; see year.length
read.sdsm
returns a data.frame
of the measured
variables. The variables are named V1
…Vn
,
for n ensembles.
If a calendar
is specified, this is stored as an attribute in
the date
data frame column.
This function readings and writes climate data with the
Statistical Downscaling Model, or SDSM. The model uses DAT
extensions for input data, such as daily observations of mean
temperature, and OUT
extensions for modeled output.
Wilby, R.L., Dawson, C.W. and Barrow, E.M. 2002. SDSM --- a decision support tool for the assessment of regional climate change impacts, Environmental Modelling Software, 17 (2), 145--157, 10.1016/S1364-8152(01)00060-3
SDSM can be downloaded free-of-charge for Windows platforms from https://www.sdsm.org.uk/
CGCM1 and HADCM3 model data for SDSM can be downloaded from the Canadian Climate Impacts and Scenarios website: https://web.archive.org/web/20120218192015/http://www.cics.uvic.ca/scenarios/sdsm/select.cgi (archived)
# NOT RUN {
# reading
fname <- system.file("extdata", "GF_2050s_precip.OUT", package="seas")
gf50 <- read.sdsm(fname)
gf50.ss <- seas.sum(gf50, var=paste("V", 1:20, sep=""), name="Grand Forks")
# analysis
image(gf50.ss, var="V1")
image(gf50.ss, var="V2")
image(gf50.ss, var="V3")
# writing
data(mscdata)
hj <- mksub(mscdata, id=2100630)
fname <- paste(tempdir(), "HJ_Obs_prcp.DAT", sep="/")
write.sdsm(hj, "precip", 1961, 2000, fname)
# }
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