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s2dv (version 1.4.0)

A Set of Common Tools for Seasonal to Decadal Verification

Description

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.

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Version

Install

install.packages('s2dv')

Monthly Downloads

353

Version

1.4.0

License

GPL-3

Maintainer

An-Chi Ho

Last Published

March 21st, 2023

Functions in s2dv (1.4.0)

ACC

Compute the spatial anomaly correlation coefficient between the forecast and corresponding observation
AbsBiasSS

Compute the Absolute Mean Bias Skill Score
Ano

Compute forecast or observation anomalies
CDORemap

Interpolate arrays with longitude and latitude dimensions using CDO
Bias

Compute the Mean Bias
AnimateMap

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

Compute the Continuous Ranked Probability Score
Ano_CrossValid

Compute anomalies in cross-validation mode
BrierScore

Compute Brier score, its decomposition, and Brier skill score
AMV

Compute the Atlantic Multidecadal Variability (AMV) index
ColorBar

Draws a Color Bar
Cluster

K-means Clustering
ConfigFileOpen

Functions To Create Open And Save Configuration File
ConfigApplyMatchingEntries

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

Find Similar Entries In Tables Of Datasets
Clim

Compute Bias Corrected Climatologies
ConfigEditDefinition

Add Modify Or Remove Variable Definitions In Configuration
CRPSS

Compute the Continuous Ranked Probability Skill Score
Composite

Compute composites
ConfigEditEntry

Add, Remove Or Edit Entries In The Configuration
EuroAtlanticTC

Teleconnection indices in European Atlantic Ocean region
Corr

Compute the correlation coefficient between an array of forecast and their corresponding observation
ConfigShowTable

Show Configuration Tables And Definitions
GMST

Compute the Global Mean Surface Temperature (GMST) anomalies
Filter

Filter frequency peaks from an array
GSAT

Compute the Global Surface Air Temperature (GSAT) anomalies
Consist_Trend

Compute trend using only model data for which observations are available
DiffCorr

Compute the correlation difference and its significance
EOF

Area-weighted empirical orthogonal function analysis using SVD
Eno

Compute effective sample size with classical method
MeanDims

Average an array along multiple dimensions
NAO

Compute the North Atlantic Oscillation (NAO) Index
InsertDim

Add a named dimension to an array
Histo2Hindcast

Chunk long simulations for comparison with hindcasts
Plot2VarsVsLTime

Plot two scores with confidence intervals in a common plot
PlotSection

Plots A Vertical Section
PlotMatrix

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

Compute persistence
ProbBins

Compute probabilistic information of a forecast relative to a threshold or a quantile
LeapYear

Checks Whether A Year Is Leap Year
Load

Loads Experimental And Observational Data
PlotBoxWhisker

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

Compute the ratio between the ensemble spread and RMSE
RatioRMS

Compute the ratio between the RMSE of two experiments
PlotVsLTime

Plot a score along the forecast time with its confidence interval
PlotStereoMap

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

Compute root mean square error
REOF

Area-weighted empirical orthogonal function analysis with varimax rotation using SVD
ProjectField

Project anomalies onto modes of variability
Spread

Compute interquartile range, maximum-minimum, standard deviation and median absolute deviation
ResidualCorr

Compute the residual correlation and its significance
PlotClim

Plots Climatologies
RandomWalkTest

Random Walk test for skill differences
SPOD

Compute the South Pacific Ocean Dipole (SPOD) index
RatioPredictableComponents

Calculate ratio of predictable components (RPC)
StatSeasAtlHurr

Compute estimate of seasonal mean of Atlantic hurricane activity
RPS

Compute the Ranked Probability Score
RPSS

Compute the Ranked Probability Skill Score
UltimateBrier

Compute Brier scores
Regression

Compute the regression of an array on another along one dimension.
sampleTimeSeries

Sample Of Observational And Experimental Data For Forecast Verification As Area Averages
clim.palette

Generate Climate Color Palettes
Trend

Compute the trend
Reorder

Reorder the dimension of an array
s2dv-package

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

Plot Plumes/Timeseries Of Anomaly Correlation Coefficients
PlotAno

Plot Anomaly time series
PlotEquiMap

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

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

Estimate frequency spectrum
Smoothing

Smooth an array along one dimension
sampleDepthData

Sample of Experimental Data for Forecast Verification In Function Of Latitudes And Depths
TPI

Compute the Tripole Index (TPI) for the Interdecadal Pacific Oscillation (IPO)
ROCSS

Compute the Relative Operating Characteristic Skill Score
SignalNoiseRatio

Calculate Signal-to-noise ratio
Season

Compute seasonal mean or other calculations
RMSSS

Compute root mean square error skill score
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.
sampleMap

Sample Of Observational And Experimental Data For Forecast Verification In Function Of Longitudes And Latitudes