s2dverification

Software

s2dverification (seasonal to decadal verification) is an R framework that aids in the analysis of forecasts from the data retrieval stage, through computation of statistics and skill scores against observations, to visualisation of data and results. While some of its components are only targeted to verification of seasonal to decadal climate forecasts, it provides tools that can be useful for verification of forecasts in any field.

Find out more in the overview below, on the wiki page or on the CRAN website.
You can also sign up to the s2dverification mailing list by sending a message with the subject "subscribe" to s2dverification-request@bsc.es if you want to keep abreast of internal discussons or latest development releases.

Software Author: 

Virginie Guemas, Nicolau Manubens, Louis-Philippe Caron, Verónica Torralba, Chloé Prodhomme, Martin Ménégoz, Javier Garcia-Serrano, Fabian Lienert, Ludovic Auger, Isabel Andreu-Burillo

License: 

Apache License (Version 2.0)

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Installation

s2dverification has a system dependency, the CDO libraries, for interpolation of grid data and retrieval of metadata. Make sure you have these libraries installed in the system or download and install from https://code.zmaw.de/projects/cdo.

You can then install the publicly released version of s2dverification from CRAN:

install.packages ("s2dverification")

Or the development version from the GitLab repository:

# install.packages("devtools")
devtools::install_git("https://earth.bsc.es/gitlab/es/s2dverification.git")

Overview

The following diagram depicts the modules of s2dverification and how they interact:

The Data retrieval module allows you to gather and homogenize NetCDF data files stored in a local or remote file system. Some simple previous steps are required, however, to set up some configuration parameters so that the module can locate the source files and recognize the variables of interest.

Once the data has been loaded into an R object, Basic statistics can be computed, such as climatologies, trends, bias correction, smoothing, ...

Either after computing basic statistics or directly from the original data, the functions in the Verification module allow you to compute deterministic and probabilistic scores and skill scores, such as root mean square error, time or spatial correlation or brier score.

Visualisation functions are also provided to plot the results obtained from any of the modules above.

If it's your first time using s2dverification you can check an Example of use spanning its four modules or review the Tutorials section. You will find more detailed examples in the documentation page of each module.

You can also check the examples of usage of each function after attaching the package as follows:

ls('package:s2dverification')
##  [1] "ACC"                        "Alpha"                     
##  [3] "Ano"                        "Ano_CrossValid"            
##  [5] "Clim"                       "ColorBar"                  
##  [7] "ConfigAddEntry"             "ConfigApplyMatchingEntries"
##  [9] "ConfigEditDefinition"       "ConfigEditEntry"           
## [11] "ConfigFileCreate"           "ConfigFileOpen"            
## [13] "ConfigFileSave"             "ConfigRemoveDefinition"    
## [15] "ConfigRemoveEntry"          "ConfigShowDefinitions"     
## [17] "ConfigShowSimilarEntries"   "ConfigShowTable"           
## [19] "Consist_Trend"              "Corr"                      
## [21] "CRPS"                       "Enlarge"                   
## [23] "Eno"                        "EnoNew"                    
## [25] "Filter"                     "FitAcfCoef"                
## [27] "FitAutocor"                 "GenSeries"                 
## [29] "Histo2Hindcast"             "IniListDims"               
## [31] "InsertDim"                  "LeapYear"                  
## [33] "Load"                       "Mean1Dim"                  
## [35] "MeanListDim"                "Plot2VarsVsLTime"          
## [37] "PlotACC"                    "PlotAno"                   
## [39] "PlotClim"                   "PlotEquiMap"               
## [41] "PlotSection"                "PlotStereoMap"             
## [43] "PlotVsLTime"                "ProbBins"                  
## [45] "RatioRMS"                   "RatioSDRMS"                
## [47] "Regression"                 "RMS"                       
## [49] "RMSSS"                      "sampleDepthData"           
## [51] "sampleMap"                  "sampleTimeSeries"          
## [53] "Season"                     "SelIndices"                
## [55] "Smoothing"                  "Spectrum"                  
## [57] "Spread"                     "Trend"
?FunctionName