Version 7 (modified by juaco, 7 years ago) (diff) |
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Regional-Continental domain selections
In this example we will load data for Europe for the variable surface (2m) minimum temperature (var = tasmin), for the first two members (members = 1:2) of the CFSv2 hindcast (dataset = CFSv2_seasonal_16), considering the wintertime (DJF, season = c(12,1,2)) for the 10-year period 2001-2010 (years = 2001:2010), according to the forecast of previous September (leadMonth = 3). The original variable is stored as 6-hourly data for this particular dataset. Instead of loading the whole 6-hourly time series, or filtering by a particular time as in the previous example we will retrieve the daily mean values, by setting the argument time = "DD", that internally computes the daily mean from the 6-hourly instantaneous values.
> ex2 <- loadECOMS(dataset = "CFSv2_seasonal_16", var = "tasmin", members = 1:2, lonLim = c(-15,35), latLim = c(32, 75), season = c(12,1,2), years = 2001:2010, leadMonth = 3, time = "DD") [2014-06-17 12:47:49] Defining homogeneization parameters for variable "tasmin" NOTE: daily mean will be calculated from the 6-h instantaneous model output [2014-06-17 12:47:49] Defining geo-location parameters [2014-06-17 12:47:49] Defining initialization time parameters [2014-06-17 12:47:54] Retrieving data subset ... [2014-06-17 12:54:33] Done > print(object.size(ex2), units = "Mb") 35 Mb
In this case, the data are stored in a 4D-array, with the dimensions indicated by the dimensionsattribute:
> str(ex2$Data) num [1:902, 1:54, 1:47, 1:2] 17.4 16.4 17.4 18.7 18.4 ... - attr(*, "dimensions")= chr [1:4] "time" "lon" "lat" "member"
This is an example on how to plot the members selected as spatial means for the 10-year period. Note that this example uses the library fields, not attached on load of the ecomUDG.Raccess package:
> library(fields) # Install if not available to reproduce the example > member1 <- apply(ex2$Data[,,,1], FUN = mean, MARGIN = c(2,3)) > member2 <- apply(ex2$Data[,,,2], FUN = mean, MARGIN = c(2,3)) > x <- ex2$xyCoords$x > y <- ex2$xyCoords$y > par(mfrow = c(1,2)) > image.plot(x,y,member1, asp = 1, main = "Member 1") > world(add = TRUE) > image.plot(x,y,member2, asp = 1, main = "Member 2") > world(add = TRUE)
In the particular case of global domain selections (lonLim and latLim arguments set to NULL), it is recommended that only single-member, single-year selections are performed, due to the large size of this type of requests.
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