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  "Package": "CSTools",
  "Title": "Assessing Skill of Climate Forecasts on Seasonal-to-Decadal\nTimescales",
  "Version": "5.3.2",
  "Authors@R": "c(\nperson(\"Nuria\", \"Perez-Zanon\", , \"nuria.perez@bsc.es\", role = \"aut\", comment = c(ORCID = \"0000-0001-8568-3071\")),\nperson(\"Louis-Philippe\", \"Caron\", , \"louis-philippe.caron@bsc.es\", role = \"aut\", comment = c(ORCID = \"0000-0001-5221-0147\")),\nperson(\"Carmen\", \"Alvarez-Castro\", , \"carmen.alvarez-castro@cmcc.it\", role = \"aut\", comment = c(ORCID = \"0000-0002-9958-010X\")),\nperson(\"Lauriane\", \"Batte\", , \"lauriane.batte@meteo.fr\", role = \"aut\"),\nperson(\"Carlos\", \"Delgado\", , \"carlos.delgado@bsc.es\", role = \"aut\"),\nperson(\"Jost\", \"von Hardenberg\", , email = c(\"j.vonhardenberg@isac.cnr.it\", \"jost.hardenberg@polito.it\"), role = \"aut\",  comment = c(ORCID = \"0000-0002-5312-8070\")),\nperson(\"Llorenç\", \"LLedo\", , \"llledo@bsc.es\", role = \"aut\"),\nperson(\"Nicolau\", \"Manubens\", , \"nicolau.manubens@bsc.es\", role = \"aut\"),\nperson(\"Lluís\", \"Palma\", , \"lluis.palma@bsc.es\", role = \"aut\"),\nperson(\"Eroteida\", \"Sanchez-Garcia\", , \"esanchezg@aemet.es\", role = \"aut\"),\nperson(\"Bert\", \"van Schaeybroeck\", , \"bertvs@meteo.be\", role = \"aut\"),\nperson(\"Veronica\", \"Torralba\", , \"veronica.torralba@bsc.es\", role = \"aut\"),\nperson(\"Deborah\", \"Verfaillie\", , \"deborah.verfaillie@bsc.es\", role = \"aut\"),\nperson(\"Eva\", \"Rifà\", , \"eva.rifarovira@bsc.es\", role = c(\"ctb\")),\nperson(\"Filippo\", \"Cali Quaglia\", , \"filippo.caliquaglia@gmail.com\", role = \"ctb\"),\nperson(\"Maria M.\", \"Chaves-Montero\", , \"mariadm.chaves@cmcc.it\", role = \"ctb\"),\nperson(\"Chihchung\", \"Chou\", , \"chihchung.chou@bsc.es\", role = \"ctb\"),\nperson(\"Nicola\", \"Cortesi\", , \"nicola.cortesi@bsc.es\", role = \"ctb\"),\nperson(\"Susanna\", \"Corti\", , \"s.corti@isac.cnr.it\", role = \"ctb\"),\nperson(\"Paolo\", \"Davini\", , \"p.davini@isac.cnr.it\", role = \"ctb\"),\nperson(\"Gildas\", \"Dayon\", , \"gildas.dayon@meteo.fr\", role = \"ctb\"),\nperson(\"Marta\", \"Dominguez\", , \"mdomingueza@aemet.es\", role = \"ctb\"),\nperson(\"Federico\", \"Fabiano\", , \"f.fabiano@isac.cnr.it\", role = \"ctb\"),\nperson(\"Ignazio\", \"Giuntoli\", , \"i.giuntoli@isac.cnr.it\", role = \"ctb\"),\nperson(\"Raul\", \"Marcos\", , \"raul.marcos@bsc.es\", role = \"ctb\"),\nperson(\"Paola\", \"Marson\", , \"paola.marson@meteo.fr\", role = \"ctb\"),\nperson(\"Niti\", \"Mishra\", , \"niti.mishra@bsc.es\", role = \"ctb\"),\nperson(\"Jesus\", \"Peña\", , \"jesus.pena@bsc.es\", role = \"ctb\"),\nperson(\"Francesc\", \"Roura-Adserias\", , \"francesc.roura@bsc.es\", role = \"ctb\"),\nperson(\"Silvia\", \"Terzago\", , \"s.terzago@isac.cnr.it\", role = \"ctb\"),\nperson(\"Danila\", \"Volpi\", , \"d.volpi@isac.cnr.it\", role = \"ctb\"),\nperson(\"An-Chi\", \"Ho\", , \"an.ho@bsc.es\", role = \"ctb\"),\nperson(\"Victoria\", \"Agudetse\", , \"victoria.agudetse@bsc.es\", role = c(\"ctb\", \"cre\")),\nperson(\"Theertha\", \"Kariyathan\", , \"theertha.kariyathan@bsc.es\", role = \"ctb\"),\nperson(\"Eren\", \"Duzenli\", , \"eren.duzenli@bsc.es\", role = \"ctb\"),\nperson(\"BSC-CNS\", role = c(\"cph\")))",
  "Description": "Exploits dynamical seasonal forecasts in order to provide\ninformation relevant to stakeholders at the seasonal timescale.\nThe package contains process-based methods for forecast\ncalibration, bias correction, statistical and stochastic\ndownscaling, optimal forecast combination and multivariate\nverification, as well as basic and advanced tools to obtain\ntailored products. This package was developed in the context of\nthe ERA4CS project MEDSCOPE and the H2020 S2S4E project and\nincludes contributions from ArticXchange project founded by\nEU-PolarNet 2. Implements methods described in Pérez-Zanón et\nal. (2022) <doi:10.5194/gmd-15-6115-2022>, Doblas-Reyes et al.\n(2005) <doi:10.1111/j.1600-0870.2005.00104.x>, Mishra et al.\n(2018) <doi:10.1007/s00382-018-4404-z>, Sanchez-Garcia et al.\n(2019) <doi:10.5194/asr-16-165-2019>, Straus et al. (2007)\n<doi:10.1175/JCLI4070.1>, Terzago et al. (2018)\n<doi:10.5194/nhess-18-2825-2018>, Torralba et al. (2017)\n<doi:10.1175/JAMC-D-16-0204.1>, D'Onofrio et al. (2014)\n<doi:10.1175/JHM-D-13-096.1>, Verfaillie et al. (2017)\n<doi:10.5194/gmd-10-4257-2017>, Van Schaeybroeck et al. (2019)\n<doi:10.1016/B978-0-12-812372-0.00010-8>, Yiou et al. (2013)\n<doi:10.1007/s00382-012-1626-3>.",
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  "Author": "Nuria Perez-Zanon [aut] (ORCID:\n<https://orcid.org/0000-0001-8568-3071>), Louis-Philippe Caron\n[aut] (ORCID: <https://orcid.org/0000-0001-5221-0147>), Carmen\nAlvarez-Castro [aut] (ORCID:\n<https://orcid.org/0000-0002-9958-010X>), Lauriane Batte [aut],\nCarlos Delgado [aut], Jost von Hardenberg [aut] (ORCID:\n<https://orcid.org/0000-0002-5312-8070>), Llorenç LLedo [aut],\nNicolau Manubens [aut], Lluís Palma [aut], Eroteida\nSanchez-Garcia [aut], Bert van Schaeybroeck [aut], Veronica\nTorralba [aut], Deborah Verfaillie [aut], Eva Rifà [ctb],\nFilippo Cali Quaglia [ctb], Maria M. Chaves-Montero [ctb],\nChihchung Chou [ctb], Nicola Cortesi [ctb], Susanna Corti\n[ctb], Paolo Davini [ctb], Gildas Dayon [ctb], Marta Dominguez\n[ctb], Federico Fabiano [ctb], Ignazio Giuntoli [ctb], Raul\nMarcos [ctb], Paola Marson [ctb], Niti Mishra [ctb], Jesus Peña\n[ctb], Francesc Roura-Adserias [ctb], Silvia Terzago [ctb],\nDanila Volpi [ctb], An-Chi Ho [ctb], Victoria Agudetse [ctb,\ncre], Theertha Kariyathan [ctb], Eren Duzenli [ctb], BSC-CNS\n[cph]",
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    "Analogs",
    "AreaWeighted",
    "as.s2dv_cube",
    "BEI_EMWeighting",
    "BEI_PDFBest",
    "BEI_ProbsWeighting",
    "BEI_TercilesWeighting",
    "BEI_Weights",
    "BiasCorrection",
    "BindDim",
    "Calibration",
    "CategoricalEnsCombination",
    "CST_AdamontAnalog",
    "CST_AdamontQQCorr",
    "CST_Analogs",
    "CST_AnalogsPredictors",
    "CST_Anomaly",
    "CST_AreaWeighted",
    "CST_BEI_Weighting",
    "CST_BiasCorrection",
    "CST_BindDim",
    "CST_Calibration",
    "CST_CategoricalEnsCombination",
    "CST_ChangeDimNames",
    "CST_DynBiasCorrection",
    "CST_EnsClustering",
    "CST_InsertDim",
    "CST_Load",
    "CST_MergeDims",
    "CST_MultiEOF",
    "CST_MultiMetric",
    "CST_MultivarRMSE",
    "CST_ProxiesAttractor",
    "CST_QuantileMapping",
    "CST_RainFARM",
    "CST_RegimesAssign",
    "CST_ReorderDims",
    "CST_RFSlope",
    "CST_RFTemp",
    "CST_RFWeights",
    "CST_SaveExp",
    "CST_SplitDim",
    "CST_Start",
    "CST_Subset",
    "CST_Summary",
    "CST_WeatherRegimes",
    "DynBiasCorrection",
    "EnsClustering",
    "EvalTrainIndices",
    "MergeDims",
    "MultiEOF",
    "MultiMetric",
    "PDFIndexHind",
    "PlotCombinedMap",
    "PlotForecastPDF",
    "PlotMostLikelyQuantileMap",
    "PlotPDFsOLE",
    "PlotTriangles4Categories",
    "PlotWeeklyClim",
    "Predictability",
    "ProxiesAttractor",
    "QuantileMapping",
    "RainFARM",
    "RegimesAssign",
    "RF_Weights",
    "RFSlope",
    "RFTemp",
    "s2dv_cube",
    "SaveExp",
    "SplitDim",
    "training_analogs",
    "WeatherRegime"
  ],
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      "name": "lonlat_prec",
      "title": "Sample Of Experimental Precipitation Data In Function Of Longitudes And Latitudes",
      "object": "lonlat_prec",
      "class": [
        "s2dv_cube"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "lonlat_prec_st",
      "title": "Sample Of Experimental Precipitation Data In Function Of Longitudes And Latitudes with Start",
      "object": "lonlat_prec_st",
      "class": [
        "s2dv_cube"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "lonlat_temp",
      "title": "Sample Of Experimental And Observational Climate Data In Function Of Longitudes And Latitudes",
      "object": "lonlat_temp",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "lonlat_temp_st",
      "title": "Sample Of Experimental And Observational Climate Data In Function Of Longitudes And Latitudes with Start",
      "object": "lonlat_temp_st",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": false
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  "_help": [
    {
      "page": "AdamontQQCorr",
      "title": "AdamontQQCorr computes quantile-quantile correction of seasonal or decadal forecast data using weather types",
      "topics": [
        "AdamontQQCorr"
      ]
    },
    {
      "page": "Analogs",
      "title": "Analogs based on large scale fields.",
      "topics": [
        "Analogs"
      ]
    },
    {
      "page": "AreaWeighted",
      "title": "Calculate the spatial area-weighted average of multidimensional arrays.",
      "topics": [
        "AreaWeighted"
      ]
    },
    {
      "page": "as.s2dv_cube",
      "title": "Conversion of 'startR_array' or 'list' objects to 's2dv_cube'",
      "topics": [
        "as.s2dv_cube"
      ]
    },
    {
      "page": "BEI_EMWeighting",
      "title": "Computing the weighted ensemble means for SFSs.",
      "topics": [
        "BEI_EMWeighting"
      ]
    },
    {
      "page": "BEI_PDFBest",
      "title": "Computing the Best Index PDFs combining Index PDFs from two SFSs",
      "topics": [
        "BEI_PDFBest"
      ]
    },
    {
      "page": "BEI_ProbsWeighting",
      "title": "Computing the weighted tercile probabilities for SFSs.",
      "topics": [
        "BEI_ProbsWeighting"
      ]
    },
    {
      "page": "BEI_TercilesWeighting",
      "title": "Computing the weighted terciles for SFSs.",
      "topics": [
        "BEI_TercilesWeighting"
      ]
    },
    {
      "page": "BEI_Weights",
      "title": "Computing the weights for SFSs using the Best Index PDFs.",
      "topics": [
        "BEI_Weights"
      ]
    },
    {
      "page": "BiasCorrection",
      "title": "Bias Correction based on the mean and standard deviation adjustment",
      "topics": [
        "BiasCorrection"
      ]
    },
    {
      "page": "BindDim",
      "title": "Bind two arrays by a specified named dimension",
      "topics": [
        "BindDim"
      ]
    },
    {
      "page": "Calibration",
      "title": "Forecast Calibration",
      "topics": [
        "Calibration"
      ]
    },
    {
      "page": "CategoricalEnsCombination",
      "title": "Make categorical forecast based on a multi-model forecast with potential for calibrate",
      "topics": [
        "CategoricalEnsCombination"
      ]
    },
    {
      "page": "CST_AdamontAnalog",
      "title": "CST_AdamontAnalog finds analogous data in the reference dataset to experiment data based on weather types",
      "topics": [
        "AdamontAnalog",
        "CST_AdamontAnalog"
      ]
    },
    {
      "page": "CST_AdamontQQCorr",
      "title": "CST_AdamontQQCorr computes quantile-quantile correction of seasonal or decadal forecast data using weather types",
      "topics": [
        "CST_AdamontQQCorr"
      ]
    },
    {
      "page": "CST_Analogs",
      "title": "Downscaling using Analogs based on large scale fields.",
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      ]
    },
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      "page": "CST_AnalogsPredictors",
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      "topics": [
        "CST_AnalogsPredictors"
      ]
    },
    {
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      "title": "Anomalies relative to a climatology along selected dimension with or without cross-validation",
      "topics": [
        "CST_Anomaly"
      ]
    },
    {
      "page": "CST_AreaWeighted",
      "title": "Calculate the spatial area-weighted average of multidimensional arrays.",
      "topics": [
        "CST_AreaWeighted"
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      "page": "CST_BEI_Weighting",
      "title": "Weighting SFSs of a CSTools object.",
      "topics": [
        "CST_BEI_Weighting"
      ]
    },
    {
      "page": "CST_BiasCorrection",
      "title": "Bias Correction based on the mean and standard deviation adjustment",
      "topics": [
        "CST_BiasCorrection"
      ]
    },
    {
      "page": "CST_BindDim",
      "title": "Bind two objects of class s2dv_cube",
      "topics": [
        "CST_BindDim"
      ]
    },
    {
      "page": "CST_Calibration",
      "title": "Forecast Calibration",
      "topics": [
        "CST_Calibration"
      ]
    },
    {
      "page": "CST_CategoricalEnsCombination",
      "title": "Make categorical forecast based on a multi-model forecast with potential for calibrate",
      "topics": [
        "CST_CategoricalEnsCombination"
      ]
    },
    {
      "page": "CST_ChangeDimNames",
      "title": "Change the name of one or more dimensions for an object of class s2dv_cube",
      "topics": [
        "CST_ChangeDimNames"
      ]
    },
    {
      "page": "CST_DynBiasCorrection",
      "title": "Performing a Bias Correction conditioned by the dynamical properties of the data.",
      "topics": [
        "CST_DynBiasCorrection"
      ]
    },
    {
      "page": "CST_EnsClustering",
      "title": "Ensemble clustering",
      "topics": [
        "CST_EnsClustering"
      ]
    },
    {
      "page": "CST_InsertDim",
      "title": "Add a named dimension to an object of class s2dv_cube",
      "topics": [
        "CST_InsertDim"
      ]
    },
    {
      "page": "CST_Load",
      "title": "CSTools Data Retreival Function",
      "topics": [
        "CST_Load"
      ]
    },
    {
      "page": "CST_MergeDims",
      "title": "Function to Merge Dimensions",
      "topics": [
        "CST_MergeDims"
      ]
    },
    {
      "page": "CST_MultiEOF",
      "title": "EOF analysis of multiple variables",
      "topics": [
        "CST_MultiEOF"
      ]
    },
    {
      "page": "CST_MultiMetric",
      "title": "Multiple Metrics applied in Multiple Model Anomalies",
      "topics": [
        "CST_MultiMetric"
      ]
    },
    {
      "page": "CST_MultivarRMSE",
      "title": "Multivariate Root Mean Square Error (RMSE)",
      "topics": [
        "CST_MultivarRMSE"
      ]
    },
    {
      "page": "CST_ProxiesAttractor",
      "title": "Computing two dinamical proxies of the attractor in s2dv_cube.",
      "topics": [
        "CST_ProxiesAttractor"
      ]
    },
    {
      "page": "CST_QuantileMapping",
      "title": "Quantile Mapping for seasonal or decadal forecast data",
      "topics": [
        "CST_QuantileMapping"
      ]
    },
    {
      "page": "CST_RainFARM",
      "title": "RainFARM stochastic precipitation downscaling of a CSTools object",
      "topics": [
        "CST_RainFARM"
      ]
    },
    {
      "page": "CST_RegimesAssign",
      "title": "Function for matching a field of anomalies with a set of maps used as a reference (e.g. clusters obtained from the WeatherRegime function)",
      "topics": [
        "CST_RegimesAssign"
      ]
    },
    {
      "page": "CST_ReorderDims",
      "title": "Reorder the dimensions of an s2dv_cube",
      "topics": [
        "CST_ReorderDims"
      ]
    },
    {
      "page": "CST_RFSlope",
      "title": "RainFARM spectral slopes from a CSTools object",
      "topics": [
        "CST_RFSlope"
      ]
    },
    {
      "page": "CST_RFTemp",
      "title": "Temperature downscaling of a CSTools object using lapse rate correction or a reference field",
      "topics": [
        "CST_RFTemp"
      ]
    },
    {
      "page": "CST_RFWeights",
      "title": "Compute climatological weights for RainFARM stochastic precipitation downscaling",
      "topics": [
        "CST_RFWeights"
      ]
    },
    {
      "page": "CST_SaveExp",
      "title": "Save objects of class 's2dv_cube' to data in NetCDF format",
      "topics": [
        "CST_SaveExp"
      ]
    },
    {
      "page": "CST_SplitDim",
      "title": "Function to Split Dimension",
      "topics": [
        "CST_SplitDim"
      ]
    },
    {
      "page": "CST_Start",
      "title": "CSTools data retrieval function using Start",
      "topics": [
        "CST_Start"
      ]
    },
    {
      "page": "CST_Subset",
      "title": "Subset an object of class s2dv_cube",
      "topics": [
        "CST_Subset"
      ]
    },
    {
      "page": "CST_Summary",
      "title": "Generate a Summary of the data and metadata in the s2dv_cube object",
      "topics": [
        "CST_Summary"
      ]
    },
    {
      "page": "CST_WeatherRegimes",
      "title": "Function for Calculating the Cluster analysis",
      "topics": [
        "CST_WeatherRegimes"
      ]
    },
    {
      "page": "DynBiasCorrection",
      "title": "Performing a Bias Correction conditioned by the dynamical properties of the data.",
      "topics": [
        "DynBiasCorrection"
      ]
    },
    {
      "page": "EnsClustering",
      "title": "Ensemble clustering",
      "topics": [
        "EnsClustering"
      ]
    },
    {
      "page": "EvalTrainIndices",
      "title": "Generate Training and Evaluation Indices for Cross-Validation",
      "topics": [
        "EvalTrainIndices"
      ]
    },
    {
      "page": "lonlat_prec",
      "title": "Sample Of Experimental Precipitation Data In Function Of Longitudes And Latitudes",
      "topics": [
        "lonlat_prec"
      ]
    },
    {
      "page": "lonlat_prec_st",
      "title": "Sample Of Experimental Precipitation Data In Function Of Longitudes And Latitudes with Start",
      "topics": [
        "lonlat_prec_st"
      ]
    },
    {
      "page": "lonlat_temp",
      "title": "Sample Of Experimental And Observational Climate Data In Function Of Longitudes And Latitudes",
      "topics": [
        "lonlat_temp"
      ]
    },
    {
      "page": "lonlat_temp_st",
      "title": "Sample Of Experimental And Observational Climate Data In Function Of Longitudes And Latitudes with Start",
      "topics": [
        "lonlat_temp_st"
      ]
    },
    {
      "page": "MergeDims",
      "title": "Function to Split Dimension",
      "topics": [
        "MergeDims"
      ]
    },
    {
      "page": "MultiEOF",
      "title": "EOF analysis of multiple variables starting from an array (reduced version)",
      "topics": [
        "MultiEOF"
      ]
    },
    {
      "page": "MultiMetric",
      "title": "Multiple Metrics applied in Multiple Model Anomalies",
      "topics": [
        "MultiMetric"
      ]
    },
    {
      "page": "PDFIndexHind",
      "title": "Computing the Index PDFs for a dataset of SFSs for a hindcats period.",
      "topics": [
        "PDFIndexHind"
      ]
    },
    {
      "page": "PlotCombinedMap",
      "title": "Plot Multiple Lon-Lat Variables In a Single Map According to a Decision Function",
      "topics": [
        "PlotCombinedMap"
      ]
    },
    {
      "page": "PlotForecastPDF",
      "title": "Plot one or multiple ensemble forecast pdfs for the same event",
      "topics": [
        "PlotForecastPDF"
      ]
    },
    {
      "page": "PlotMostLikelyQuantileMap",
      "title": "Plot Maps of Most Likely Quantiles",
      "topics": [
        "PlotMostLikelyQuantileMap"
      ]
    },
    {
      "page": "PlotPDFsOLE",
      "title": "Plotting two probability density gaussian functions and the optimal linear estimation (OLE) as result of combining them.",
      "topics": [
        "PlotPDFsOLE"
      ]
    },
    {
      "page": "PlotTriangles4Categories",
      "title": "Function to convert any 3-d numerical array to a grid of coloured triangles.",
      "topics": [
        "PlotTriangles4Categories"
      ]
    },
    {
      "page": "PlotWeeklyClim",
      "title": "Plots the observed weekly means and climatology of a timeseries data",
      "topics": [
        "PlotWeeklyClim"
      ]
    },
    {
      "page": "Predictability",
      "title": "Computing scores of predictability using two dynamical proxies based on dynamical systems theory.",
      "topics": [
        "Predictability"
      ]
    },
    {
      "page": "print.s2dv_cube",
      "title": "Print method for s2dv_cube objects",
      "topics": [
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    {
      "page": "ProxiesAttractor",
      "title": "Computing two dinamical proxies of the attractor.",
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    {
      "page": "QuantileMapping",
      "title": "Quantile Mapping for seasonal or decadal forecast data",
      "topics": [
        "QuantileMapping"
      ]
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    {
      "page": "RainFARM",
      "title": "RainFARM stochastic precipitation downscaling (reduced version)",
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    {
      "page": "RegimesAssign",
      "title": "Function for matching a field of anomalies with a set of maps used as a reference (e.g. clusters obtained from the WeatherRegime function).",
      "topics": [
        "RegimesAssign"
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    {
      "page": "RF_Weights",
      "title": "Compute climatological weights for RainFARM stochastic precipitation downscaling",
      "topics": [
        "RF_Weights"
      ]
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    {
      "page": "RFSlope",
      "title": "RainFARM spectral slopes from an array (reduced version)",
      "topics": [
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    },
    {
      "page": "RFTemp",
      "title": "Temperature downscaling of a CSTools object using lapse rate correction (reduced version)",
      "topics": [
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    },
    {
      "page": "s2dv_cube",
      "title": "Creation of a 's2dv_cube' object",
      "topics": [
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    },
    {
      "page": "SaveExp",
      "title": "Save a multidimensional array with metadata to data in NetCDF format",
      "topics": [
        "SaveExp"
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    },
    {
      "page": "SplitDim",
      "title": "Function to Split Dimension",
      "topics": [
        "SplitDim"
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    },
    {
      "page": "training_analogs",
      "title": "AEMET Training Training method (pre-downscaling) based on analogs: synoptic situations and significant predictors.",
      "topics": [
        "training_analogs"
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    },
    {
      "page": "WeatherRegimes",
      "title": "Function for Calculating the Cluster analysis",
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      "source": "BestEstimateIndex_vignette.Rmd",
      "filename": "BestEstimateIndex_vignette.html",
      "title": "Achiving Best Estimate Index",
      "author": "Eroteida Sánchez-García",
      "engine": "knitr::knitr",
      "headings": [
        "Achiving the Precipitation Best prediction giving the NAO index",
        "Loading packages and data",
        "1- Best Estimate Index NAO",
        "2- Compute weights using the Best Estimation of Index NAO",
        "3- Apply weights to a precipitation field",
        "Comparison and visualization"
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      "created": "2019-11-27 22:10:10",
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      "source": "Analogs_vignette.Rmd",
      "filename": "Analogs_vignette.html",
      "title": "Analogs based on large scale for downscaling",
      "author": "M. Carmen Alvarez-Castro and M. del Mar Chaves-Montero (CMCC, Italy)",
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      "headings": [
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        "1. Introduction of the function",
        "Example 1: using data from CSTools",
        "Exemple 2: Load data using CST_Start",
        "Two variables and criteria Large [scale] Distance:",
        "Two variables and criteria Local [scale] Distance:",
        "Two variables and criteria Local [scale] Correlation:",
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      "title": "Data Storage and Retrieval",
      "author": "Nuria Perez",
      "engine": "knitr::knitr",
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        "1. System requirements",
        "2. Overview of CSTools structure",
        "3. Data storage recommendations",
        "4. CST_Load example",
        "5. CST_Start example",
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      "source": "ENSclustering_vignette.Rmd",
      "filename": "ENSclustering_vignette.html",
      "title": "Ensemble Clustering",
      "author": "Ignazio Giuntoli and Federico Fabiano - CNR-ISAC",
      "engine": "knitr::knitr",
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        "1. Preliminary setup",
        "2. Loading the data",
        "3. Launching Ensemble clustering",
        "4. Results retrieval",
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      "created": "2020-07-02 08:30:03",
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      "source": "MostLikelyTercile_vignette.Rmd",
      "filename": "MostLikelyTercile_vignette.html",
      "title": "Most Likely Terciles",
      "author": "Louis-Philippe Caron and Núria Pérez-Zanón",
      "engine": "knitr::knitr",
      "headings": [
        "Computing and displaying the most likely tercile of a seasonal forecast",
        "1. Preliminary setup",
        "2. Loading the data",
        "3. Computing probabilities",
        "4. Visualization with PlotMostLikelyQuantileMap",
        "5. Computing Skill Score",
        "6. Simultaneous visualization of probabilities and skill scores"
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    {
      "source": "MultiModelSkill_vignette.Rmd",
      "filename": "MultiModelSkill_vignette.html",
      "title": "Multi-model Skill Assessment",
      "author": "Nuria Perez",
      "engine": "knitr::knitr",
      "headings": [
        "Multi-model Skill Assessment",
        "1.- Load data",
        "2.- Computing and plotting Anomaly Correlation Coefficient",
        "3.- Computing and plotting Root Mean Square error (RMS)",
        "4.- Computing and plotting Root Mean Square error Skill Scores (RMSSS)"
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      "created": "2019-04-24 13:20:02",
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    {
      "source": "MultivarRMSE_vignette.Rmd",
      "filename": "MultivarRMSE_vignette.html",
      "title": "Multivariate RMSE",
      "author": "Deborah Verfaillie",
      "engine": "knitr::knitr",
      "headings": [
        "Multivariate Root Mean Square Error (RMSE)",
        "1.- Load data",
        "2.- Computing and plotting multivariate RMSEs"
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    {
      "source": "PlotForecastPDF.Rmd",
      "filename": "PlotForecastPDF.html",
      "title": "Plot Forecast PDFs",
      "author": "Francesc Roura-Adserias and Llorenç Lledó",
      "engine": "knitr::knitr",
      "headings": [
        "Plot Forecast PDFs (Probability Distibution Functions)",
        "1. A simple example",
        "2. Customizing the appearance of your plots",
        "3. Adding extremes and observed values",
        "4. Saving your plot to a file",
        "5. A reproducible example using lonlat_temp_st"
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      "created": "2020-02-11 11:50:22",
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    {
      "source": "RainFARM_vignette.Rmd",
      "filename": "RainFARM_vignette.html",
      "title": "Rainfall Filtered Autoregressive Model (RainFARM) precipitation downscaling",
      "author": "Jost von Hardenberg (ISAC-CNR)",
      "engine": "knitr::knitr",
      "headings": [
        "Introduction",
        "Downscaling seasonal precipitation forecasts with RainFARM",
        "Preliminary setup",
        "Standard downscaling without climatological weights",
        "Downscaling using climatological weights",
        "Determining the spectral slopes",
        "Compacting dimensions",
        "Bibliography"
      ],
      "created": "2019-04-24 13:20:02",
      "modified": "2024-01-26 02:38:04",
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    {
      "source": "WeatherRegimes_vignette.Rmd",
      "filename": "WeatherRegimes_vignette.html",
      "title": "Weather Regime Analysis",
      "author": "Verónica Torralba, Nicola Cortesi and Núria Pérez-Zanón",
      "engine": "knitr::knitr",
      "headings": [
        "Weather regime analysis",
        "1- Required packages",
        "2- Retrive data from files",
        "3- Daily anomalies based on a smoothed climatology",
        "4- Weather regimes in observations",
        "5- Visualisation of the observed weather regimes",
        "6- Visualisation of the observed regime persistence",
        "7- Weather regimes in the predictions",
        "8- Visualisation of the predicted weather regimes"
      ],
      "created": "2020-07-02 08:30:03",
      "modified": "2025-11-14 12:40:27",
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