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s2dv (version 2.1.0)

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

2.1.0

License

GPL-3

Maintainer

Ariadna Batalla

Last Published

October 13th, 2024

Functions in s2dv (2.1.0)

Compute the Continuous Ranked Probability Score

Interpolate arrays with longitude and latitude dimensions using CDO

Compute anomalies in cross-validation mode

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

Compute forecast or observation anomalies

Compute the Atlantic Multidecadal Variability (AMV) index

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

Compute the Mean Bias

Compute the Absolute Mean Bias Skill Score

Compute Brier score, its decomposition, and Brier skill score

Compute Bias Corrected Climatologies

Compute the Continuous Ranked Probability Skill Score

ConfigShowSimilarEntries

Find Similar Entries In Tables Of Datasets

Functions To Create Open And Save Configuration File

ConfigEditEntry

Add, Remove Or Edit Entries In The Configuration

ConfigEditDefinition

Add Modify Or Remove Variable Definitions In Configuration

K-means Clustering

Draws a Color Bar

ConfigApplyMatchingEntries

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

Compute composites

Area-weighted empirical orthogonal function analysis using SVD

Teleconnection indices in European Atlantic Ocean region

Compute the correlation difference and its significance

Filter frequency peaks from an array

Compute trend using only model data for which observations are available

ConfigShowTable

Show Configuration Tables And Definitions

Compute effective sample size with classical method

Compute the Global Mean Surface Temperature (GMST) anomalies

Compute the Global Surface Air Temperature (GSAT) anomalies

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

Compute probabilistic forecasts or the corresponding observations

Compute the North Atlantic Oscillation (NAO) Index

Compute persistence

Chunk long simulations for comparison with hindcasts

Loads Experimental And Observational Data

Compute mean square error

Checks Whether A Year Is Leap Year

Add a named dimension to an array

Compute mean square error skill score

Average an array along multiple dimensions

Maps A Two-Dimensional Variable On A Polar Stereographic Projection

Plot2VarsVsLTime

Plot two scores with confidence intervals in a common plot

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

Maps A Two-Dimensional Variable On A Cylindrical Equidistant Projection

Plot Anomaly time series

Plots Climatologies

Plots A Vertical Section

Arrange and Fill Multi-Pannel Layouts With Optional Colour Bar

Plot Plumes/Timeseries Of Anomaly Correlation Coefficients

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

Compute root mean square error

Project anomalies onto modes of variability

Compute the Ranked Probability Score

Random Walk test for skill differences

Compute the Relative Operating Characteristic Skill Score

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

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

Compute root mean square error skill score

Compute the Ranked Probability Skill Score

Plot a score along the forecast time with its confidence interval

Compute seasonal mean or other calculations

Compute the residual correlation and its significance

Compute the ratio between the RMSE of two experiments

RatioPredictableComponents

Calculate ratio of predictable components (RPC)

Compute the South Pacific Ocean Dipole (SPOD) index

Compute the ratio between the ensemble spread and RMSE

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

SignalNoiseRatio

Calculate Signal-to-noise ratio

Smooth an array along one dimension

Reorder the dimension of an array

Compute the ratio between the ensemble spread and RMSE

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

Compute the trend

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

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

StatSeasAtlHurr

Compute estimate of seasonal mean of Atlantic hurricane activity

Compute Brier scores

Generate Climate Color Palettes

Estimate frequency spectrum

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.

sampleTimeSeries

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

sampleDepthData

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

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