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s2dverification (version 2.10.3)

Set of Common Tools for Forecast Verification

Description

Set of tools to verify forecasts through the computation of typical prediction scores against one or more observational datasets or reanalyses (a reanalysis being a physical extrapolation of observations that relies on the equations from a model, not a pure observational dataset). Intended for seasonal to decadal climate forecasts although can be useful to verify other kinds of forecasts. The package can be helpful in climate sciences for other purposes than forecasting. To find more details, see the review paper Manubens, N.et al. (2018) .

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Version

Install

install.packages('s2dverification')

Monthly Downloads

89

Version

2.10.3

License

Apache License 2.0

Maintainer

An-Chi Ho

Last Published

April 20th, 2022

Functions in s2dverification (2.10.3)

ConfigEditEntry

Add, Remove Or Edit Entries In The Configuration
AnimateMap

Animate Maps of Forecast/Observed Values or Scores Over Forecast Time
MeanListDim

Averages An Array Along Multiple Dimensions
FitAcfCoef

Fits an AR1 AutoCorrelation Function Using the Cardano Formula
Mean1Dim

Averages An Array Along A Dimension
GenSeries

Generates An AR1 Time Series
Filter

Filter Frequency Peaks From An Array
ConfigFileOpen

Functions To Create Open And Save Configuration File
PlotStereoMap

Maps A Two-Dimensional Variable On A Polar Stereographic Projection
FitAutocor

Fits an AR1 Autocorrelation Function Using Dichotomy
PlotEquiMap

Maps A Two-Dimensional Variable On A Cylindrical Equidistant Projection
Ano

Computes Forecast or Observed Anomalies
RatioSDRMS

Computes the ratio between the ensemble spread and RMSE
RatioRMS

Computes the Ratio Between The RMSE of Two Experiments
Subset

Subset a Data Array
PlotVsLTime

Plots A Score Along The Forecast Time With Its Confidence Interval
ToyModel

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.
PlotLayout

Arrange and Fill Multi-Pannel Layouts With Optional Colour Bar
Consist_Trend

Computes Trends Using Only Model Data For Which Observations Are Available
CDORemap

Interpolates arrays with longitude and latitude dimensions using CDO
BrierScore

Compute Brier Score And Its Decomposition And Brier Skill Score
Smoothing

Smoothes An Array Along A Dimension
Spectrum

Estimates Frequency Spectrum
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
Corr

Computes the correlation coefficient between an array of forecasts and their corresponding observations
Alpha

Estimates AutoCorrelation At Lag 1 following Guemas et al, BAMS, 2013b
sampleTimeSeries

Sample Of Observational And Experimental Data For Forecast Verification As Area Averages
ACC

Computes Anomaly Correlation Coefficient
ConfigShowSimilarEntries

Find Similar Entries In Tables Of Datasets
ConfigShowTable

Show Configuration Tables And Definitions
EOF

Area-Weighted Empirical Orthogonal Function Analysis Using SVD
Histo2Hindcast

Chunks Long Simulations For Comparison With Hindcasts
ConfigApplyMatchingEntries

Apply Matching Entries To Dataset Name And Variable Name To Find Related Info
Enlarge

Extends The Number Of Dimensions of A Matrix
PlotMatrix

Function to convert any numerical table to a grid of coloured squares.
RMS

Computes Root Mean Square Error
IniListDims

Creates A List Of Integer Ranges
InsertDim

Adds A Dimension To An Array
LeapYear

Checks Whether A Year Is Leap Year
PlotSection

Plots A Vertical Section
Eno

Computes Effective Sample Size With Classical Method
ConfigEditDefinition

Add Modify Or Remove Variable Definitions In Configuration
PlotACC

Plot Plumes/Timeseries Of Anomaly Correlation Coefficients
RMSSS

Computes Root Mean Square Skill Score
PlotAno

Plot Raw Or Smoothed Anomalies
PlotClim

Plots Climatologies
PlotBoxWhisker

Box-And-Whisker Plot of Time Series with Ensemble Distribution
EnoNew

Computes Effective Sample Size Following Guemas et al, BAMS, 2013b
ColorBar

Draws a Color Bar
Regression

Computes The Regression Of An Array On Another Along A Dimension
Load

Loads Experimental And Observational Data
Composite

Computes composites
NAO

Computes the North Atlantic Oscillation (NAO) Index
Plot2VarsVsLTime

Plot Two Scores With Confidence Intervals In A Common Plot
Spread

Computes InterQuartile Range, Maximum-Minimum, Standard Deviation and Median Absolute Deviation of the Ensemble Members
.LoadDataFile

Load Data From File Into Environment
StatSeasAtlHurr

Compute estimate of seasonal mean of Atlantic hurricane activity
ProbBins

Computes Probabilistic Information of a Forecast Relative to a Threshold or a Quantile
ProjectField

Project Anomalies onto Modes of Variability
SVD

Single Value Decomposition (Maximum Covariance Analysis)
Trend

Computes the Trend of the Ensemble Mean
Season

Computes Seasonal Means
SelIndices

Slices A Matrix Along A Dimension
clim.palette

Generate Climate Color Palettes
UltimateBrier

Computes Brier Scores
s2dverification

Set of Common Tools for Forecast Verification
Cluster

K-means Clustering
Ano_CrossValid

Computes Anomalies In Cross-Validation Mode
Clim

Computes Bias Corrected Climatologies
ArrayToNetCDF

Save multidimensional R arrays into NetCDF files