{ "_id": "6a1228e0acfb0bcc41d06323", "Package": "SeaVal", "Title": "Validation of Seasonal Weather Forecasts", "Version": "1.2.0", "Authors@R": "c(person(given = \"Claudio\",\nfamily = \"Heinrich-Mertsching\",\nrole = c(\"aut\", \"cre\",\"cph\"),\nemail = \"claudio.heinrich@hotmail.de\",\ncomment = c(ORCID = \"0000-0003-3581-6416\")),\nperson(given = \"Celine\",\nfamily = \"Cunen\",\nrole = c(\"ctb\"),\nemail = \"celine@nr.no\"),\nperson(given = \"Michael\",\nfamily = \"Scheuerer\",\nrole = c(\"ctb\"),\nemail = \"scheuerer@nr.no\"))", "Description": "Provides tools for processing and evaluating seasonal\nweather forecasts, with an emphasis on tercile forecasts. We\nfollow the World Meteorological Organization's \"Guidance on\nVerification of Operational Seasonal Climate Forecasts\",\nS.J.Mason (2018, ISBN: 978-92-63-11220-0, URL:\n). The development was\nsupported by the European Union’s Horizon 2020 research and\ninnovation programme under grant agreement no. 869730 (CONFER).\nA comprehensive online tutorial is available at\n.", "URL": "https://seasonalforecastingengine.github.io/SeaValDoc/,\nhttps://github.com/SeasonalForecastingEngine/SeaVal", "License": "GPL (>= 3)", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.2.3", "Collate": "'auxiliary_functions.R' 'chirps.R' 'data.R' 'diagrams.R'\n'ICPAC_temp.R' 'ncdf_to_dt.R' 'plotting.R' 'quantiles.R'\n'scores.R' 'seasonal.R' 'SeaVal-package.R' 'spatial_grids.R'\n'upscaling.R' 'utils.R'", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-23 22:19:48 UTC", "User": "root" }, "Author": "Claudio Heinrich-Mertsching [aut, cre, cph]\n(), Celine Cunen [ctb],\nMichael Scheuerer [ctb]", "Maintainer": "Claudio Heinrich-Mertsching ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2024-06-15 02:41:00 UTC", "RemoteUrl": 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"Imports" }, { "package": "scales", "role": "Imports" }, { "package": "stringr", "role": "Imports" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 0, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 614, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/SeaVal" }, "_devurl": "https://github.com/seasonalforecastingengine/seavaldoc", "_searchresults": 14, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "extra/SeaVal.html", "manual.pdf" ], "_realowner": "cran", "_cranurl": false, "_releases": [ { "version": "1.0.0", "date": "2023-11-08" }, { "version": "1.1.0", "date": "2023-11-21" }, { "version": "1.1.1", "date": "2023-11-25" }, { "version": "1.2.0", "date": "2024-06-14" } ], "_exports": [ "add_climatology", "add_country", "add_country_names", "add_tercile_cat", "add_tercile_probs", "chirps_dir", "chirps_ver_map_quantiles", "climatology_ens_forecast", "climatology_threshold_exceedence", "combine", "complete_regular_grid", "convert_monthly_to_seasonal", "CPA", "CRPS", "CRPSS", "data_dir", "dimvars", "disc_score_dt", "DISS", "download_chirps_monthly", "download_chirps_prelim_aux", "dt_to_netcdf", "EA_country_names", "EIR", "fc_cols", "get_mask", "get_quantiles", "get_terciles", "ggplot_dt", "GHA_extent", "gha_plot", "grid_info", "HS", "HSS", "IGS", "IGSS", "load_chirps", "lt_cols", "MB", "MBS", "MSD_to_YM", "MSE", "MSES", "netcdf_to_dt", "obs_cols", "obs_dimvars", "PCC", "profit_graph", "REL", "rel_diag", "rel_diag_vec", "RES", "restrict_to_country", "restrict_to_GHA", "ROC_curve", "roc_curve_vec", "roc_score_vec", "ROCS", "round_probs", "RPS", "RPSS", "set_spatial_grid", "space_dimvars", "SRC", "tc_cols", "tendency_diag", "tercile_plot", "tfc_from_efc", "tfc_gha_plot", "tfc_plot", "time_dimvars", "upscale_chirps", "upscale_regular_lon_lat", "ver_map", "ver_map_chirps" ], "_datasets": [ { "name": "chirps_monthly", "title": "Monthly mean precipitation", "object": "chirps_monthly", "class": [ "data.table", "data.frame" ], "fields": [ "lon", "lat", "prec", "month", "year", "terc_cat" ], "rows": 209040, "table": true, "tojson": true }, { "name": "ecmwf_monthly", "title": "Monthly mean precipitation forecast example dataset", "object": "ecmwf_monthly", "class": [ "data.table", "data.frame" ], "fields": [ "lon", "lat", "year", "month", "prec", "member", "below", "normal", "above" ], "rows": 37224, "table": true, "tojson": true } ], "_help": [ { "page": "add_climatology", "title": "Add climatology to a data table", "topics": [ "add_climatology" ] }, { "page": "add_country", "title": "Same as add_country_names", "topics": [ "add_country" ] }, { "page": "add_country_names", "title": "Add country names to a data table with lon/lat coordinates", "topics": [ "add_country_names" ] }, { "page": "add_tercile_cat", "title": "Add a tercile-category column to a data table", "topics": [ "add_tercile_cat" ] }, { "page": "add_tercile_probs", "title": "Add tercile probabilities to ensemble forecasts", "topics": [ "add_tercile_probs" ] }, { "page": "are_all_elements_within_eps", "title": "Check if all elements of x are within tolerance eps of any element in y", "topics": [ "are_all_elements_within_eps" ] }, { "page": "by_cols_ens_fc_score", "title": "Auxiliary function", "topics": [ "by_cols_ens_fc_score" ] }, { "page": "by_cols_terc_fc_score", "title": "Auxiliary function", "topics": [ "by_cols_terc_fc_score" ] }, { "page": "by_cols_terc_fc_score_sp", "title": "Auxiliary function", "topics": [ "by_cols_terc_fc_score_sp" ] }, { "page": "checks_ens_fc_score", "title": "Auxiliary function for scores of ensemble forecasts.", "topics": [ "checks_ens_fc_score" ] }, { "page": "checks_terc_fc_score", "title": "Auxiliary function for scores for tercile forecasts.", "topics": [ "checks_terc_fc_score" ] }, { "page": "chirps_dir", "title": "CHIRPS directory", "topics": [ "chirps_dir" ] }, { "page": "chirps_monthly", "title": "Monthly mean precipitation", "topics": [ "chirps_monthly" ] }, { "page": "chirps_ver_map_quantiles", "title": "Calculates and saves the quantiles of CHIRPS data required for verification maps.", "topics": [ "chirps_ver_map_quantiles" ] }, { "page": "climatology_ens_forecast", "title": "Returns a leave-one-year-out climatology-based ensemble forecast", "topics": [ "climatology_ens_forecast" ] }, { "page": "climatology_threshold_exceedence", "title": "Get climatological prediction for exceedence probabilities.", "topics": [ "climatology_threshold_exceedence" ] }, { "page": "combine", "title": "Combine two data tables", "topics": [ "combine" ] }, { "page": "complete_regular_grid", "title": "Expand Regular Spatial Grid", "topics": [ "complete_regular_grid" ] }, { "page": "convert_monthly_to_seasonal", "title": "Convert a data table from monthly to seasonal format", "topics": [ "convert_monthly_to_seasonal" ] }, { "page": "CPA", "title": "Coefficients of Predictive Ability", "topics": [ "CPA" ] }, { "page": "create_diagram_by_level", "title": "Auxiliary function to simplify grouping for diagrams", "topics": [ "create_diagram_by_level" ] }, { "page": "CRPS", "title": "Continuous Ranked Probability Score", "topics": [ "CRPS" ] }, { "page": "crps_aux", "title": "Auxiliary function for calculating crps.", "topics": [ "crps_aux" ] }, { "page": "crps_aux_esc", "title": "Auxiliary function for calculating crps with ensemble size correction by Ferro et al. 2008.", "topics": [ "crps_aux_esc" ] }, { "page": "CRPSS", "title": "Continuous Ranked Probability Skill Score", "topics": [ "CRPSS" ] }, { "page": "data_dir", "title": "Auxiliary function to access and change the directory used to load and save data.", "topics": [ "data_dir" ] }, { "page": "delete_redundant_files", "title": "Auxiliary function cleaning out the directories, called at the end of the CHIRPS download.", "topics": [ "delete_redundant_files" ] }, { "page": "dimvars", "title": "Get dimension variables", "topics": [ "dimvars" ] }, { "page": "disc_score_dt", "title": "Generalized Discrimination score", "topics": [ "disc_score_dt" ] }, { "page": "DISS", "title": "Generalized discrimination score", "topics": [ "DISS" ] }, { "page": "download_chirps_monthly", "title": "Download monthly CHIRPS-data", "topics": [ "download_chirps_monthly" ] }, { "page": "download_chirps_monthly_high", "title": "Auxiliary function called by download_chirps_monthly", "topics": [ "download_chirps_monthly_high" ] }, { "page": "download_chirps_monthly_low", "title": "Auxiliary function called by download_chirps_monthly", "topics": [ "download_chirps_monthly_low" ] }, { "page": "download_chirps_prelim_aux", "title": "Auxiliary function for downloading the preliminary CHIRPS monthly data", "topics": [ "download_chirps_prelim_aux" ] }, { "page": "dt_to_netcdf", "title": "Write a netcdf from a long data table", "topics": [ "dt_to_netcdf" ] }, { "page": "EA_country_names", "title": "Get names of countries in east Africa", "topics": [ "EA_country_names" ] }, { "page": "ecmwf_monthly", "title": "Monthly mean precipitation forecast example dataset", "topics": [ "ecmwf_monthly" ] }, { "page": "EIR", "title": "Effective Interest Rate", "topics": [ "EIR" ] }, { "page": "fc_cols", "title": "Forecast column names", "topics": [ "fc_cols" ] }, { "page": "get_mask", "title": "Function to create a mask of dry regions from CHIRPS", "topics": [ "get_mask" ] }, { "page": "get_quantiles", "title": "Calculate quantiles from a data table", "topics": [ "get_quantiles" ] }, { "page": "get_terciles", "title": "get terciles from a data table", "topics": [ "get_terciles" ] }, { "page": "ggplot_dt", "title": "plotting function for spatial data", "topics": [ "ggplot_dt" ] }, { "page": "GHA_extent", "title": "GHA-bounding-box", "topics": [ "GHA_extent" ] }, { "page": "gha_plot", "title": "Plotting function with different map for Greater Horn of Africa", "topics": [ "ggplot_dt_gha_map", "ggplot_dt_shf", "gha_plot" ] }, { "page": "grid_info", "title": "Retrieve spatial grid information from a data table", "topics": [ "grid_info" ] }, { "page": "HS", "title": "Hit score", "topics": [ "HS" ] }, { "page": "HSS", "title": "Hit Skill Score", "topics": [ "HSS" ] }, { "page": "IGS", "title": "Ignorance Score", "topics": [ "IGS" ] }, { "page": "IGSS", "title": "Ignorance Skill score", "topics": [ "IGSS" ] }, { "page": "indicator_times_value_aux", "title": "Auxiliary function for multiplying two numbers such that 0 x infty is 0. Needed for the ignorance score: 0log(0) should be 0.", "topics": [ "indicator_times_value_aux" ] }, { "page": "load_chirps", "title": "Function for loading CHIRPS (monthly) data.", "topics": [ "load_chirps" ] }, { "page": "lt_cols", "title": "Data table column names that are recognized as leadtime", "topics": [ "lt_cols" ] }, { "page": "MB", "title": "Multicategory Brier score", "topics": [ "MB" ] }, { "page": "MBS", "title": "Multicategory Brier Skill score", "topics": [ "MBS" ] }, { "page": "modify_dt_map_plotting", "title": "Auxiliary function for checking dimensions for map-plotting", "topics": [ "modify_dt_map_plotting" ] }, { "page": "MSD_to_YM", "title": "Converts time given as 'months since date' (MSD) into years and months (YM)", "topics": [ "MSD_to_YM" ] }, { "page": "MSE", "title": "Mean Square Error of ensemble forecasts.", "topics": [ "MSE" ] }, { "page": "MSES", "title": "Mean Square Error Skill score", "topics": [ "MSES" ] }, { "page": "netcdf_to_dt", "title": "function for converting netcdfs to long data tables.", "topics": [ "netcdf_to_dt" ] }, { "page": "obs_cols", "title": "Observation column names", "topics": [ "obs_cols" ] }, { "page": "obs_dimvars", "title": "Auxiliary function returning observation dimvars.", "topics": [ "obs_dimvars" ] }, { "page": "PCC", "title": "Pearson Correlation Coefficient", "topics": [ "PCC" ] }, { "page": "profit_graph", "title": "(Accumulative) profit graphs", "topics": [ "profit_graph" ] }, { "page": "REL", "title": "Reliability score", "topics": [ "REL" ] }, { "page": "rel_diag", "title": "Reliability Diagrams for tercile forecasts", "topics": [ "rel_diag" ] }, { "page": "rel_diag_vec", "title": "Reliability diagram from vectors of probabilities and observations", "topics": [ "rel_diag_vec" ] }, { "page": "RES", "title": "Resolution score", "topics": [ "RES" ] }, { "page": "restrict_to_country", "title": "restricts data to a specified country", "topics": [ "restrict_to_country" ] }, { "page": "restrict_to_GHA", "title": "restricts data to the Greater Horn of Africa", "topics": [ "restrict_to_confer_region", "restrict_to_GHA" ] }, { "page": "ROC_curve", "title": "ROC curve for tercile forecasts", "topics": [ "ROC_curve" ] }, { "page": "roc_curve_vec", "title": "ROC curves", "topics": [ "roc_curve_vec" ] }, { "page": "roc_score_vec", "title": "ROC score (AUC)", "topics": [ "roc_score_vec" ] }, { "page": "ROCS", "title": "ROC-score/Area Under Curve(AUC)", "topics": [ "ROCS" ] }, { "page": "round_probs", "title": "auxiliary function for rounding probabilities", "topics": [ "round_probs" ] }, { "page": "RPS", "title": "Ranked Probability score", "topics": [ "RPS" ] }, { "page": "RPSS", "title": "Ranked Probability skill score", "topics": [ "RPSS" ] }, { "page": "run_dimension_check_ens_fc_score", "title": "Auxiliary Function", "topics": [ "run_dimension_check_ens_fc_score" ] }, { "page": "run_dimension_check_terc_forecast", "title": "Auxiliary Function", "topics": [ "run_dimension_check_terc_forecast" ] }, { "page": "season_strings_to_int", "title": "Auxiliary function for decoding season-strings", "topics": [ "season_strings_to_int" ] }, { "page": "set_spatial_grid", "title": "Set Spatial Grid Attributes to a Data Table", "topics": [ "set_spatial_grid" ] }, { "page": "space_dimvars", "title": "Auxiliary function", "topics": [ "space_dimvars" ] }, { "page": "SRC", "title": "Compute the slope of the reliability curve", "topics": [ "SRC" ] }, { "page": "tc_cols", "title": "Tercile column names", "topics": [ "tc_cols" ] }, { "page": "tendency_diag", "title": "Tendency diagram from a data table containing tercile forecasts.", "topics": [ "tendency_diag" ] }, { "page": "tercile_plot", "title": "Function for plotting terciles", "topics": [ "tercile_plot" ] }, { "page": "tfc_from_efc", "title": "Get tercile probability forecast from ensemble forecasts", "topics": [ "tfc_from_efc" ] }, { "page": "tfc_gha_plot", "title": "Plotting function with different map for Greater Horn of Africa", "topics": [ "tfc_gha_plot" ] }, { "page": "tfc_plot", "title": "plotting function for tercile forecasts", "topics": [ "tfc_plot" ] }, { "page": "time_dimvars", "title": "Auxiliary function", "topics": [ "time_dimvars" ] }, { "page": "upscale_chirps", "title": "Upscales monthly CHIRPS data to a coarser grid", "topics": [ "upscale_chirps" ] }, { "page": "upscale_regular_lon_lat", "title": "Function for matching data between different grids", "topics": [ "upscale_regular_lon_lat" ] }, { "page": "ver_map", "title": "Plot a verification map of percentiles", "topics": [ "ver_map" ] }, { "page": "ver_map_chirps", "title": "Plot a verification map of percentiles based on precomputed CHIRPS quantiles.", "topics": [ "ver_map_chirps" ] } ], "_readme": "https://github.com/cran/SeaVal/raw/HEAD/README.md", "_rundeps": [ "cli", "cpp11", "data.table", "digest", "farver", "fs", "ggnewscale", "ggplot2", "ggplotify", "glue", "gridGraphics", "gtable", "isoband", 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