## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.align = "center", warning = FALSE, message = FALSE, eval = FALSE ) ## ----load_package------------------------------------------------------------- # library(clim4health) ## ----------------------------------------------------------------------------- # fcst_path <- system.file("extdata/forecast/", package = "clim4health") # fcst_path <- paste0(fcst_path, "/") # fcst <- c4h_load(fcst_path, # variable = "t2m", # year = 2025, # month = 1, # leadtime_month = "all", # ext = "nc") # # hcst_path <- system.file("extdata/hindcast/", package = "clim4health") # hcst_path <- paste0(hcst_path, "/") # hcst <- c4h_load(hcst_path, # variable = "t2m", # year = 2010:2012, # month = 1, # leadtime_month = "all", # ext = "nc") # # rean_path <- system.file("extdata/reanalysis/", package = "clim4health") # rean_path <- paste0(rean_path, "/") # rean <- c4h_load(rean_path, # variable = "t2m", # year = 2010:2012, # month = 1, # leadtime_month = 1:3, # ext = "nc") ## ----convert_units------------------------------------------------------------ # fcst <- c4h_convert_units(fcst, "celsius") # hcst <- c4h_convert_units(hcst, "celsius") # rean <- c4h_convert_units(rean, "celsius") ## ----explore_data------------------------------------------------------------- # print(rean$dims) # print(hcst$dims) # # print(rean$coords$latitude) # print(hcst$coords$latitude) ## ----plot_raw----------------------------------------------------------------- # # Hindcast data # c4h_plot(hcst, ensemble = TRUE, coordgrid = TRUE) # # # Observations # c4h_plot(rean, ensemble = TRUE, coordgrid = TRUE) ## ----c4h_downscale_parameters,fig.width=10, fig.height=10, fig.align='center', out.width='100%', echo= FALSE, fig.cap="Figure 1: Structure of the c4h_downscale function, outlining its key arguments and general functionality."---- # knitr::include_graphics("https://gitlab.earth.bsc.es/ghr/clim4health/-/blob/main/inst/figures/clim4health_downscale_parameters.svg?ref_type=heads") ## ----------------------------------------------------------------------------- # dwn <- c4h_downscale("Interpolation", # exp = hcst, # method_remap = "bilinear", # target_grid = paste0(rean_path, "t2m_201001.nc")) ## ----------------------------------------------------------------------------- # c4h_plot(dwn$exp, ensemble = TRUE) ## ----------------------------------------------------------------------------- # c4h_plot(rean) ## ----------------------------------------------------------------------------- # dwn <- c4h_downscale("Intbc", exp = hcst, obs = rean, # method_bc = "evmos", method_remap = "bilinear") ## ----------------------------------------------------------------------------- # c4h_plot(dwn$exp, ensemble = TRUE) ## ----------------------------------------------------------------------------- # dwn <- c4h_downscale("Intlr", exp = hcst, obs = rean, # exp_cor = fcst, # method_lr = "basic", # method_remap = "con") ## ----------------------------------------------------------------------------- # c4h_plot(dwn$exp, ensemble = TRUE) ## ----------------------------------------------------------------------------- # dwn <- c4h_downscale("Analogs", exp = hcst, obs = rean) ## ----------------------------------------------------------------------------- # c4h_plot(dwn$exp, ensemble = TRUE) ## ----------------------------------------------------------------------------- # stat_path <- system.file("extdata/stations/", package = "clim4health") # point_locs <- clim4health::c4h_load(stat_path, # ext = "csv", # year = 2010:2012, # month = 1, # leadtime_month = 1:3, # variable = "temp_mean") # # # use c4h_time to obtain monthly data # point_locs <- c4h_time(point_locs, time_aggregation = "monthly", dim_aggregation = "sdate") ## ----point_interpolation------------------------------------------------------ # points <- list(latitude = point_locs$attrs$location$latitude, # longitude = point_locs$attrs$location$longitude) # # dwn <- c4h_downscale("Interpolation", exp = hcst, # points = points, method_point_interp = "bilinear") ## ----plot_point_interpolation------------------------------------------------- # c4h_plot(dwn$exp, ensemble = TRUE, boundaries = "countries") ## ----point_intbc-------------------------------------------------------------- # dwn <- c4h_downscale("Intbc", exp = hcst, obs = rean, # points = points, method_point_interp = "bilinear", # method_bc = "evmos") ## ----------------------------------------------------------------------------- # library(sf) # # # Region municipalities # munip_path <- system.file("extdata", "areas", "munip_vallecauca.gpkg", # package = "clim4health") # munip <- read_sf(munip_path) # # hcst_aggr <- c4h_space(hcst, munip) # rean_aggr <- c4h_space(rean, munip) ## ----------------------------------------------------------------------------- # cal <- c4h_downscale("Intbc", exp = hcst_aggr, obs = rean_aggr, # method_bc = "bias") ## ----------------------------------------------------------------------------- # c4h_plot(hcst_aggr, ensemble = TRUE, boundaries = "countries") # c4h_plot(cal$exp, ensemble = TRUE, boundaries = "countries") # c4h_plot(rean_aggr, ensemble = TRUE, boundaries = "countries") ## ----c4h_downscale_flowchart,fig.width=10, fig.height=10, fig.align='center', out.width='100%', echo= FALSE, fig.cap="Figure 2: Flowchart for selecting downscaling parameters. Dashed lines indicate optional arguments."---- # knitr::include_graphics("https://gitlab.earth.bsc.es/ghr/clim4health/-/blob/develop-vignettes/inst/figures/c4h_downscale.svg?ref_type=heads")