Assessing Skill of Climate Forecasts on Seasonal-to-Decadal Timescales
Analogs based on large scale fields.
Function to Split Dimension
EOF analysis of multiple variables starting from an array (reduced ver...
Multiple Metrics applied in Multiple Model Anomalies
Computing the Index PDFs for a dataset of SFSs for a hindcats period.
Plot Multiple Lon-Lat Variables In a Single Map According to a Decisio...
Plot one or multiple ensemble forecast pdfs for the same event
Plot Maps of Most Likely Quantiles
Plotting two probability density gaussian functions and the optimal li...
Function to convert any 3-d numerical array to a grid of coloured tria...
Plots the observed weekly means and climatology of a timeseries data
Computing scores of predictability using two dynamical proxies based o...
Print method for s2dv_cube objects
Computing two dinamical proxies of the attractor.
Quantile Mapping for seasonal or decadal forecast data
RainFARM stochastic precipitation downscaling (reduced version)
Function for matching a field of anomalies with a set of maps used as ...
Function for Calculating the Cluster analysis
Performing a Bias Correction conditioned by the dynamical properties o...
Ensemble clustering
AdamontQQCorr computes quantile-quantile correction of seasonal or dec...
Calculate the spatial area-weighted average of multidimensional arrays...
Conversion of 'startR_array' or 'list' objects to 's2dv_cube'
Computing the weighted ensemble means for SFSs.
Computing the Best Index PDFs combining Index PDFs from two SFSs
Computing the weighted tercile probabilities for SFSs.
Computing the weighted terciles for SFSs.
Computing the weights for SFSs using the Best Index PDFs.
Bias Correction based on the mean and standard deviation adjustment
Bind two arrays by a specified named dimension
Forecast Calibration
Make categorical forecast based on a multi-model forecast with potenti...
Generate Training and Evaluation Indices for Cross-Validation
CST_AdamontAnalog finds analogous data in the reference dataset to exp...
CST_AdamontQQCorr computes quantile-quantile correction of seasonal or...
Downscaling using Analogs based on large scale fields.
AEMET Downscaling Precipitation and maximum and minimum temperature do...
Anomalies relative to a climatology along selected dimension with or w...
Calculate the spatial area-weighted average of multidimensional arrays...
Weighting SFSs of a CSTools object.
Bias Correction based on the mean and standard deviation adjustment
Bind two objects of class s2dv_cube
Forecast Calibration
Make categorical forecast based on a multi-model forecast with potenti...
Change the name of one or more dimensions for an object of class s2dv_...
Performing a Bias Correction conditioned by the dynamical properties o...
Ensemble clustering
Add a named dimension to an object of class s2dv_cube
CSTools Data Retreival Function
Function to Merge Dimensions
EOF analysis of multiple variables
Multiple Metrics applied in Multiple Model Anomalies
Multivariate Root Mean Square Error (RMSE)
Computing two dinamical proxies of the attractor in s2dv_cube.
Quantile Mapping for seasonal or decadal forecast data
RainFARM stochastic precipitation downscaling of a CSTools object
Function for matching a field of anomalies with a set of maps used as ...
RainFARM spectral slopes from a CSTools object
Temperature downscaling of a CSTools object using lapse rate correctio...
Compute climatological weights for RainFARM stochastic precipitation d...
Save objects of class 's2dv_cube' to data in NetCDF format
Function to Split Dimension
CSTools data retrieval function using Start
Subset an object of class s2dv_cube
Generate a Summary of the data and metadata in the s2dv_cube object
Compute climatological weights for RainFARM stochastic precipitation d...
RainFARM spectral slopes from an array (reduced version)
Temperature downscaling of a CSTools object using lapse rate correctio...
Creation of a 's2dv_cube' object
Save a multidimensional array with metadata to data in NetCDF format
Function to Split Dimension
AEMET Training Training method (pre-downscaling) based on analogs: syn...
Function for Calculating the Cluster analysis
Exploits dynamical seasonal forecasts in order to provide information relevant to stakeholders at the seasonal timescale. The package contains process-based methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. This package was developed in the context of the ERA4CS project MEDSCOPE and the H2020 S2S4E project and includes contributions from ArticXchange project founded by EU-PolarNet 2. Implements methods described in Pérez-Zanón et al. (2022) <doi:10.5194/gmd-15-6115-2022>, Doblas-Reyes et al. (2005) <doi:10.1111/j.1600-0870.2005.00104.x>, Mishra et al. (2018) <doi:10.1007/s00382-018-4404-z>, Sanchez-Garcia et al. (2019) <doi:10.5194/asr-16-165-2019>, Straus et al. (2007) <doi:10.1175/JCLI4070.1>, Terzago et al. (2018) <doi:10.5194/nhess-18-2825-2018>, Torralba et al. (2017) <doi:10.1175/JAMC-D-16-0204.1>, D'Onofrio et al. (2014) <doi:10.1175/JHM-D-13-096.1>, Verfaillie et al. (2017) <doi:10.5194/gmd-10-4257-2017>, Van Schaeybroeck et al. (2019) <doi:10.1016/B978-0-12-812372-0.00010-8>, Yiou et al. (2013) <doi:10.1007/s00382-012-1626-3>.