Changes between Version 3 and Version 4 of udg/ecoms/RPackage/biascorrection


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Timestamp:
Mar 30, 2015 8:45:18 AM (7 years ago)
Author:
gutierjm
Comment:

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  • udg/ecoms/RPackage/biascorrection

    v3 v4  
    22
    33Taking into account the users' needs, in the following example a calibration of all the variables available, and needed by the users, in the ECOMS-UDG data server.
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     5
     6Since the [http://www.r-project.org/ R] language has been adopted for some key tasks in the EUPORIAS and SPECS projects (including the development of comprehensive validation and statistical-downscaling packages), the `ecomsUDG.Raccess` is envisaged as a user-friendly, R-based interface to the ECOMS User Data Gateway, enabling [http://meteo.unican.es/trac/wiki/udg/ecoms/RPackage/authentication authentication] and remote access to the different datasets (seasonal forecasting, observations, reanalysis) currently available. Moreover, `ecomsUDG.Raccess` implements data homogenization (a single vocabulary) and time filtering/aggregation functionality.
     7
     8The `ecomsUDG.Raccess` package relies on the `rJava` package as an interface to the powerful capabilities of the [http://www.unidata.ucar.edu/downloads/netcdf/netcdf-java-4/index.jsp Unidata's netCDF Java library].
     9
     10{{{#!comment
     11  * [wiki:./Functions Defined Functions]
     12 }}}
     13
     14The following panels show an illustrative use of ECOMS-UDG to obtain the minimum DJF temperature DJF bias for System4 hindcast (one-month lead time) over Europe. WFDEI is used as reference.
     15||= R code =||= Output =||
     16{{{#!td
     17   {{{#!text/R
     18obs <- loadECOMS(dataset = "WFDEI",
     19                  var = "tasmin",
     20                  season = c(12,1,2))
     21prd <- loadECOMS(dataset = "System4_seasonal_15",
     22                  var = "tasmin",
     23                  season = c(12,1,2),
     24                  members = 1:2,
     25                  leadMonth = 1)
     26  }}}
     27  {{{#!text/R
     28obsr <- interpGridData(gridData = obs,
     29                  new.grid = getGrid(prd),
     30                  method = "bilinear")
     31bias <- getBias(obsr,prd)
     32plotMeanField(bias, multi.member = TRUE)
     33  }}}
     34}}}
     35{{{#!td
     36[[Image(bc.png)]]
     37}}}
     38
     39
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    441
    542First of all, the quantile-quantile mapping and the WFDEI data set are considered to calibrate the seven months corresponding to the initialization of November for the period 2001-2010 in an European domain. For the sake of the simplicity, only one member has been considered in this example.
     
    158195obs <- NULL
    159196}}}
    160