Changes between Version 5 and Version 6 of udg/ecoms/RPackage/examples/continentalSelection


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Timestamp:
Jun 17, 2014 1:10:51 PM (7 years ago)
Author:
juaco
Comment:

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  • udg/ecoms/RPackage/examples/continentalSelection

    v5 v6  
     1= Regional-Continental domain selections
     2
     3In 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 [http://meteo.unican.es/ecoms-udg/RPackage/Examples/pointSelection 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.
     4
     5{{{
     6> 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")
     7[2014-06-17 12:47:49] Defining homogeneization parameters for variable "tasmin"
     8NOTE: daily mean will be calculated from the 6-h instantaneous model output
     9[2014-06-17 12:47:49] Defining geo-location parameters
     10[2014-06-17 12:47:49] Defining initialization time parameters
     11[2014-06-17 12:47:54] Retrieving data subset ...
     12[2014-06-17 12:54:33] Done
     13> print(object.size(ex2), units = "Mb")
     1435 Mb
     15}}}
     16
     17In this case, the data are stored in a 4D-array, with the dimensions indicated by the `dimensions`attribute:
     18
     19{{{
     20> str(ex2$Data)
     21 num [1:902, 1:54, 1:47, 1:2] 17.4 16.4 17.4 18.7 18.4 ...
     22 - attr(*, "dimensions")= chr [1:4] "time" "lon" "lat" "member"
     23}}}
     24
     25This is an example on how to plot the members selected as spatial means for the 10-year period. Note that this example uses the library `fields`, not attached on load of the `ecomUDG.Raccess` package:
     26
     27{{{
     28> library(fields) # Install if not available to reproduce the example
     29> member1 <- apply(ex2$Data[,,,1], FUN = mean, MARGIN = c(2,3))
     30> member2 <- apply(ex2$Data[,,,2], FUN = mean, MARGIN = c(2,3))
     31> x <- ex2$xyCoords$x
     32> y <- ex2$xyCoords$y
     33> par(mfrow = c(1,2))
     34> image.plot(x,y,member1, asp = 1, main = "Member 1")
     35> world(add = TRUE)
     36> image.plot(x,y,member2, asp = 1, main = "Member 2")
     37> world(add = TRUE)
     38}}}
     39
     40
     41[[Image(image-20140617-130616.png)]]
     42
     43
     44
     45
     46
     47{{{#!comment
    148= Alternative visualization tools: Monsoon in the Indian subcontinent
    249