Package: s2dv 2.1.0

Ariadna Batalla

s2dv: A Set of Common Tools for Seasonal to Decadal Verification

The advanced version of package 's2dverification'. It is intended for 'seasonal to decadal' (s2d) climate forecast verification, but it can also be used in other kinds of forecasts or general climate analysis. This package is specially designed for the comparison between the experimental and observational datasets. The functionality of the included functions covers from data retrieval, data post-processing, skill scores against observation, to visualization. Compared to 's2dverification', 's2dv' is more compatible with the package 'startR', able to use multiple cores for computation and handle multi-dimensional arrays with a higher flexibility. The CDO version used in development is 1.9.8.

Authors:BSC-CNS [aut, cph], An-Chi Ho [aut], Nuria Perez-Zanon [aut], Roberto Bilbao [ctb], Josep Cos [ctb], Carlos Delgado [ctb], Llorenç Lledó [ctb], Andrea Manrique [ctb], Deborah Verfaillie [ctb], Eva Rifà [ctb], Victòria Agudetse [ctb], Nadia Milders [ctb], Ariadna Batalla [ctb, cre]

s2dv_2.1.0.tar.gz
s2dv_2.1.0.tar.gz(r-4.5-noble)s2dv_2.1.0.tar.gz(r-4.4-noble)
s2dv_2.1.0.tgz(r-4.4-emscripten)s2dv_2.1.0.tgz(r-4.3-emscripten)
s2dv.pdf |s2dv.html
s2dv/json (API)
NEWS

# Install 's2dv' in R:
install.packages('s2dv', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • sampleDepthData - Sample of Experimental Data for Forecast Verification In Function Of Latitudes And Depths
  • sampleMap - Sample Of Observational And Experimental Data For Forecast Verification In Function Of Longitudes And Latitudes
  • sampleTimeSeries - Sample Of Observational And Experimental Data For Forecast Verification As Area Averages

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.95 score 3 packages 38 scripts 358 downloads 86 exports 23 dependencies

Last updated 2 months agofrom:fab89c35e8. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 13 2024
R-4.5-linuxOKDec 13 2024

Exports:AbsBiasSSACCAMVAnimateMapAnoAno_CrossValidBiasBrierScoreCDORemapClimclim.colorsclim.paletteClusterColorBarCompositeConfigAddEntryConfigApplyMatchingEntriesConfigEditDefinitionConfigEditEntryConfigFileCreateConfigFileOpenConfigFileSaveConfigRemoveDefinitionConfigRemoveEntryConfigShowDefinitionsConfigShowSimilarEntriesConfigShowTableConsist_TrendCorrCRPSCRPSSDiffCorrEnoEOFEuroAtlanticTCFilterGetProbsGMSTGSATHisto2HindcastInsertDimLeapYearLoadMeanDimsMSEMSSSNAOPersistencePlot2VarsVsLTimePlotACCPlotAnoPlotBoxWhiskerPlotClimPlotEquiMapPlotLayoutPlotMatrixPlotSectionPlotStereoMapPlotVsLTimeProbBinsProjectFieldRandomWalkTestRatioPredictableComponentsRatioRMSRatioSDRMSRegressionREOFReorderResidualCorrRMSRMSSSROCSSRPSRPSSSeasonSignalNoiseRatioSmoothingSpectrumSPODSpreadSprErrStatSeasAtlHurrToyModelTPITrendUltimateBrier

Dependencies:abindBHbigmemorybigmemory.sriClimProjDiagscodetoolsdoParalleleasyNCDFeasyVerificationforeachiteratorsmapprojmapsmultiApplyNbClustncdf4pbapplyPCICtplyrRcppRcppArmadilloSpecsVerificationuuid

Readme and manuals

Help Manual

Help pageTopics
Compute the Absolute Mean Bias Skill ScoreAbsBiasSS
Compute the spatial anomaly correlation coefficient between the forecast and corresponding observationACC
Compute the Atlantic Multidecadal Variability (AMV) indexAMV
Animate Maps of Forecast/Observed Values or Scores Over Forecast TimeAnimateMap
Compute forecast or observation anomaliesAno
Compute anomalies in cross-validation modeAno_CrossValid
Compute the Mean BiasBias
Compute Brier score, its decomposition, and Brier skill scoreBrierScore
Interpolate arrays with longitude and latitude dimensions using CDOCDORemap
Compute Bias Corrected ClimatologiesClim
Generate Climate Color Palettesclim.colors clim.palette
K-means ClusteringCluster
Draws a Color BarColorBar
Compute compositesComposite
Apply Matching Entries To Dataset Name And Variable Name To Find Related InfoConfigApplyMatchingEntries
Add Modify Or Remove Variable Definitions In ConfigurationConfigEditDefinition ConfigRemoveDefinition
Add, Remove Or Edit Entries In The ConfigurationConfigAddEntry ConfigEditEntry ConfigRemoveEntry
Functions To Create Open And Save Configuration FileConfigFileCreate ConfigFileOpen ConfigFileSave
Find Similar Entries In Tables Of DatasetsConfigShowSimilarEntries
Show Configuration Tables And DefinitionsConfigShowDefinitions ConfigShowTable
Compute trend using only model data for which observations are availableConsist_Trend
Compute the correlation coefficient between an array of forecast and their corresponding observationCorr
Compute the Continuous Ranked Probability ScoreCRPS
Compute the Continuous Ranked Probability Skill ScoreCRPSS
Compute the correlation difference and its significanceDiffCorr
Compute effective sample size with classical methodEno
Area-weighted empirical orthogonal function analysis using SVDEOF
Teleconnection indices in European Atlantic Ocean regionEuroAtlanticTC
Filter frequency peaks from an arrayFilter
Compute probabilistic forecasts or the corresponding observationsGetProbs
Compute the Global Mean Surface Temperature (GMST) anomaliesGMST
Compute the Global Surface Air Temperature (GSAT) anomaliesGSAT
Chunk long simulations for comparison with hindcastsHisto2Hindcast
Add a named dimension to an arrayInsertDim
Checks Whether A Year Is Leap YearLeapYear
Loads Experimental And Observational DataLoad
Average an array along multiple dimensionsMeanDims
Compute mean square errorMSE
Compute mean square error skill scoreMSSS
Compute the North Atlantic Oscillation (NAO) IndexNAO
Compute persistencePersistence
Plot two scores with confidence intervals in a common plotPlot2VarsVsLTime
Plot Plumes/Timeseries Of Anomaly Correlation CoefficientsPlotACC
Plot Anomaly time seriesPlotAno
Box-And-Whisker Plot of Time Series with Ensemble DistributionPlotBoxWhisker
Plots ClimatologiesPlotClim
Maps A Two-Dimensional Variable On A Cylindrical Equidistant ProjectionPlotEquiMap
Arrange and Fill Multi-Pannel Layouts With Optional Colour BarPlotLayout
Function to convert any numerical table to a grid of coloured squares.PlotMatrix
Plots A Vertical SectionPlotSection
Maps A Two-Dimensional Variable On A Polar Stereographic ProjectionPlotStereoMap
Plot a score along the forecast time with its confidence intervalPlotVsLTime
Compute probabilistic information of a forecast relative to a threshold or a quantileProbBins
Project anomalies onto modes of variabilityProjectField
Random Walk test for skill differencesRandomWalkTest
Calculate ratio of predictable components (RPC)RatioPredictableComponents
Compute the ratio between the RMSE of two experimentsRatioRMS
Compute the ratio between the ensemble spread and RMSERatioSDRMS
Compute the regression of an array on another along one dimension.Regression
Area-weighted empirical orthogonal function analysis with varimax rotation using SVDREOF
Reorder the dimension of an arrayReorder
Compute the residual correlation and its significanceResidualCorr
Compute root mean square errorRMS
Compute root mean square error skill scoreRMSSS
Compute the Relative Operating Characteristic Skill ScoreROCSS
Compute the Ranked Probability ScoreRPS
Compute the Ranked Probability Skill ScoreRPSS
Sample of Experimental Data for Forecast Verification In Function Of Latitudes And DepthssampleDepthData
Sample Of Observational And Experimental Data For Forecast Verification In Function Of Longitudes And LatitudessampleMap
Sample Of Observational And Experimental Data For Forecast Verification As Area AveragessampleTimeSeries
Compute seasonal mean or other calculationsSeason
Calculate Signal-to-noise ratioSignalNoiseRatio
Smooth an array along one dimensionSmoothing
Estimate frequency spectrumSpectrum
Compute the South Pacific Ocean Dipole (SPOD) indexSPOD
Compute interquartile range, maximum-minimum, standard deviation and median absolute deviationSpread
Compute the ratio between the ensemble spread and RMSESprErr
Compute estimate of seasonal mean of Atlantic hurricane activityStatSeasAtlHurr
Synthetic forecast generator imitating seasonal to decadal forecasts. The components of a forecast: (1) predictabiltiy (2) forecast error (3) non-stationarity and (4) ensemble generation. The forecast can be computed for real observations or observations generated artifically.ToyModel
Compute the Tripole Index (TPI) for the Interdecadal Pacific Oscillation (IPO)TPI
Compute the trendTrend
Compute Brier scoresUltimateBrier